Science.gov

Sample records for accelerated learning techniques

  1. Enhancing healthcare education with accelerated learning techniques.

    PubMed

    Henry, S A; Swartz, R G

    1995-01-01

    In this article, the authors describe innovative teaching techniques that create a learning environment addressing nonverbal and verbal communication. The use of these accelerated learning techniques in a Basic Cardiac Dysrhythmia Course is discussed, and participant learning is measured and analyzed. When these methods, including relaxation, music, and subliminal messages were used, participant exam grades improved. The authors concluded that these simple procedures enhance learning and increase the effectiveness of teaching.

  2. Accelerated Learning Techniques for the Foreign Language Class: A Personal View.

    ERIC Educational Resources Information Center

    Bancroft, W. Jane

    Foreign language instructors cope with problems of learner anxiety in the classroom, fossilization of language use and language skill loss. Relaxation and concentration techniques can alleviate stress and fatigue and improve students' capabilities. Three categories of accelerated learning techniques are: (1) those that serve as a preliminary to…

  3. Can Accelerators Accelerate Learning?

    NASA Astrophysics Data System (ADS)

    Santos, A. C. F.; Fonseca, P.; Coelho, L. F. S.

    2009-03-01

    The 'Young Talented' education program developed by the Brazilian State Funding Agency (FAPERJ) [1] makes it possible for high-schools students from public high schools to perform activities in scientific laboratories. In the Atomic and Molecular Physics Laboratory at Federal University of Rio de Janeiro (UFRJ), the students are confronted with modern research tools like the 1.7 MV ion accelerator. Being a user-friendly machine, the accelerator is easily manageable by the students, who can perform simple hands-on activities, stimulating interest in physics, and getting the students close to modern laboratory techniques.

  4. Network acceleration techniques

    NASA Technical Reports Server (NTRS)

    Crowley, Patricia (Inventor); Awrach, James Michael (Inventor); Maccabe, Arthur Barney (Inventor)

    2012-01-01

    Splintered offloading techniques with receive batch processing are described for network acceleration. Such techniques offload specific functionality to a NIC while maintaining the bulk of the protocol processing in the host operating system ("OS"). The resulting protocol implementation allows the application to bypass the protocol processing of the received data. Such can be accomplished this by moving data from the NIC directly to the application through direct memory access ("DMA") and batch processing the receive headers in the host OS when the host OS is interrupted to perform other work. Batch processing receive headers allows the data path to be separated from the control path. Unlike operating system bypass, however, the operating system still fully manages the network resource and has relevant feedback about traffic and flows. Embodiments of the present disclosure can therefore address the challenges of networks with extreme bandwidth delay products (BWDP).

  5. Accelerated learning approaches for maintenance training

    SciTech Connect

    Erickson, E.J.

    1991-01-01

    As a training tool, Accelerated Learning techniques have been in use since 1956. Trainers from a variety of applications and disciplines have found success in using Accelerated Learning approaches, such as training aids, positive affirmations, memory aids, room arrangement, color patterns, and music. Some have thought that maintenance training and Accelerated Learning have nothing in common. Recent training applications by industry and education of Accelerated Learning are proving very successful by several standards. This paper cites available resource examples and challenges maintenance trainers to adopt new ideas and concepts to accelerate learning in all training setting. 7 refs.

  6. Integrating Internet Video Conferencing Techniques and Online Delivery Systems with Hybrid Classes to Enhance Student Interaction and Learning in Accelerated Programs

    ERIC Educational Resources Information Center

    Beckwith, E. George; Cunniff, Daniel T.

    2009-01-01

    Online course enrollment has increased dramatically over the past few years. The authors cite the reasons for this rapid growth and the opportunities open for enhancing teaching/learning techniques such as video conferencing and hybrid class combinations. The authors outlined an example of an accelerated learning, eight-class session course…

  7. Accelerated Learning: Madness with a Method.

    ERIC Educational Resources Information Center

    Zemke, Ron

    1995-01-01

    Accelerated learning methods have evolved into a variety of holistic techniques that involve participants in the learning process and overcome negative attitudes about learning. These components are part of the mix: the brain, learning environment, music, imaginative activities, suggestion, positive mental state, the arts, multiple intelligences,…

  8. Educational Games: A Technique to Accelerate the Acquisition of Reading Skills of Children with Learning Disabilities

    ERIC Educational Resources Information Center

    Charlton, Beryl; Williams, Randy Lee; McLaughlin, T. F.

    2005-01-01

    This study evaluated the effects of educational games on the performance of eight elementary school students with learning disabilities. The effects of educational games were evaluated in a multiple baseline design across students. The results indicated that each student improved their performance on reading when educational games were in effect.…

  9. Compensation Techniques in Accelerator Physics

    SciTech Connect

    Sayed, Hisham Kamal

    2011-05-01

    Accelerator physics is one of the most diverse multidisciplinary fields of physics, wherein the dynamics of particle beams is studied. It takes more than the understanding of basic electromagnetic interactions to be able to predict the beam dynamics, and to be able to develop new techniques to produce, maintain, and deliver high quality beams for different applications. In this work, some basic theory regarding particle beam dynamics in accelerators will be presented. This basic theory, along with applying state of the art techniques in beam dynamics will be used in this dissertation to study and solve accelerator physics problems. Two problems involving compensation are studied in the context of the MEIC (Medium Energy Electron Ion Collider) project at Jefferson Laboratory. Several chromaticity (the energy dependence of the particle tune) compensation methods are evaluated numerically and deployed in a figure eight ring designed for the electrons in the collider. Furthermore, transverse coupling optics have been developed to compensate the coupling introduced by the spin rotators in the MEIC electron ring design.

  10. Techniques to accelerate dynamic psychotherapy.

    PubMed

    Fosha, D; Slowiaczek, M L

    1997-01-01

    The techniques described above outline specific ways to deepen the patient's affective experience within an emotionally close therapeutic relationship. When effective, they all enhance the patient/therapist bond, raise self-esteem, reduce defensiveness and anxiety, and facilitate emotional healing. Psychodynamic treatment, long or short, is a complex process uniquely constructed by each therapist/patient pair. AEDP strategies are not intended as recipes for treatment. Good dynamic work depends on the therapist's ability to grasp the patient's capacities and limitations, understand relational dynamics, and interact with the patient in an empathically attuned, emotionally receptive, and flexible way. In that context, these strategies can be helpful tools to facilitate and accelerate the process. The choices made by AEDP--privileging adaptive strivings over defensive reactions, the stance of emotional engagement rather than neutrality and abstinence, the focus on health and change over pathology and stasis--are informed by traditional STDP aims to maximize depth, effectiveness, and efficiency. AEDP's contribution is a set of techniques relying on a response repertoire that is available to a wide range of therapists. Therapists can use these techniques to be more effective while simultaneously retaining the experience of speaking with patients in an authentic voice.

  11. An Annotated Bibliography of Accelerated Learning

    ERIC Educational Resources Information Center

    Garcia, GNA

    2007-01-01

    A rich narrative-style bibliography of accelerated learning (reviewing six articles published between 1995-2003). Articles reviewed include: (1) Accelerative learning and the Emerging Science of Wholeness (D. D. Beale); (2) Effective Teaching in Accelerated Learning Programs (D. Boyd); (3) A Critical Theory Perspective on Accelerated Learning (S.…

  12. A Critical Theory Perspective on Accelerated Learning.

    ERIC Educational Resources Information Center

    Brookfield, Stephen D.

    2003-01-01

    Critically analyzes accelerated learning using concepts from Herbert Marcuse (rebellious subjectivity) and Erich Fromm (automaton conformity). Concludes that, by providing distance and separation, accelerated learning has more potential to stimulate critical autonomous thought. (SK)

  13. Investigation of Accelerated Life Prediction Techniques

    DTIC Science & Technology

    1975-10-01

    1974, AD 784 188. 2. Rabinowicz , E., McEntire, R. H., and Shwalkar, B., A TECHNIQUE FOR ACCELERATED LIFE TESTING, Trans. ASME, August 1970, pp...706-710. 3. Rabinowicz , E., FRICTION AND WEAR OF MATERIALS, New York, John Wiley and Sons, 1966. 4. MacGregor, C. W. (ed), HANDBOOK OF

  14. On Convergence Acceleration Techniques for Unstructured Meshes

    NASA Technical Reports Server (NTRS)

    Mavriplis, Dimitri J.

    1998-01-01

    A discussion of convergence acceleration techniques as they relate to computational fluid dynamics problems on unstructured meshes is given. Rather than providing a detailed description of particular methods, the various different building blocks of current solution techniques are discussed and examples of solution strategies using one or several of these ideas are given. Issues relating to unstructured grid CFD problems are given additional consideration, including suitability of algorithms to current hardware trends, memory and cpu tradeoffs, treatment of non-linearities, and the development of efficient strategies for handling anisotropy-induced stiffness. The outlook for future potential improvements is also discussed.

  15. Accelerating Learning By Neural Networks

    NASA Technical Reports Server (NTRS)

    Toomarian, Nikzad; Barhen, Jacob

    1992-01-01

    Electronic neural networks made to learn faster by use of terminal teacher forcing. Method of supervised learning involves addition of teacher forcing functions to excitations fed as inputs to output neurons. Initially, teacher forcing functions are strong enough to force outputs to desired values; subsequently, these functions decay with time. When learning successfully completed, terminal teacher forcing vanishes, and dynamics or neural network become equivalent to those of conventional neural network. Simulated neural network with terminal teacher forcing learned to produce close approximation of circular trajectory in 400 iterations.

  16. Analysis techniques for residual acceleration data

    NASA Technical Reports Server (NTRS)

    Rogers, Melissa J. B.; Alexander, J. Iwan D.; Snyder, Robert S.

    1990-01-01

    Various aspects of residual acceleration data are of interest to low-gravity experimenters. Maximum and mean values and various other statistics can be obtained from data as collected in the time domain. Additional information may be obtained through manipulation of the data. Fourier analysis is discussed as a means of obtaining information about dominant frequency components of a given data window. Transformation of data into different coordinate axes is useful in the analysis of experiments with different orientations and can be achieved by the use of a transformation matrix. Application of such analysis techniques to residual acceleration data provides additional information than what is provided in a time history and increases the effectiveness of post-flight analysis of low-gravity experiments.

  17. Summer Learning: Accelerating Student Success

    ERIC Educational Resources Information Center

    Pitcock, Sarah; Seidel, Bob

    2015-01-01

    As numerous studies from 1906 on have confirmed, children lose ground in learning if they lack opportunities for building skills over the summer. Nonetheless, summer learning loss comes up but rarely in the national discussion of education reform. By the end of summer, students perform on average one month behind where they left off in the spring.…

  18. Accelerated Learning: Technical Training Can Be Fun.

    ERIC Educational Resources Information Center

    Reid, Gerry

    1985-01-01

    This article describes methods for fine tuning instructor skills and other delivery mechanisms aimed at accelerating the learning process. These methods involve the use of association, elaboration, song, role play, loci, hooks, acrostics, guided imagery, relaxation, music, positive mind-setting (suggestology), emotions, early success, and…

  19. Leveraging Experiential Learning Techniques for Transfer

    ERIC Educational Resources Information Center

    Furman, Nate; Sibthorp, Jim

    2013-01-01

    Experiential learning techniques can be helpful in fostering learning transfer. Techniques such as project-based learning, reflective learning, and cooperative learning provide authentic platforms for developing rich learning experiences. In contrast to more didactic forms of instruction, experiential learning techniques foster a depth of learning…

  20. Accelerating materials property predictions using machine learning.

    PubMed

    Pilania, Ghanshyam; Wang, Chenchen; Jiang, Xun; Rajasekaran, Sanguthevar; Ramprasad, Ramamurthy

    2013-09-30

    The materials discovery process can be significantly expedited and simplified if we can learn effectively from available knowledge and data. In the present contribution, we show that efficient and accurate prediction of a diverse set of properties of material systems is possible by employing machine (or statistical) learning methods trained on quantum mechanical computations in combination with the notions of chemical similarity. Using a family of one-dimensional chain systems, we present a general formalism that allows us to discover decision rules that establish a mapping between easily accessible attributes of a system and its properties. It is shown that fingerprints based on either chemo-structural (compositional and configurational information) or the electronic charge density distribution can be used to make ultra-fast, yet accurate, property predictions. Harnessing such learning paradigms extends recent efforts to systematically explore and mine vast chemical spaces, and can significantly accelerate the discovery of new application-specific materials.

  1. Speeding up learning: accelerated distance learning in rehabilitation education.

    PubMed

    Harley, Debra A; Jolivette, Kristine; McNall, Rebecca

    2004-01-01

    Distance learning in higher education involves a continum of technologies ranging from teleconferencing to video streaming. The United States is approaching a crisis in personnel shortages in rehabilitation counseling and education. Because of these shortages, higher education is called upon to produce counselors in an abbreviated period of time. Thus, distance learning is recognized as an integral part of education, especially for adult learners. This article provides an overview and discussion of the relevance of distance and accelerated learning in rehabilitation and higher education.

  2. Adaptive and accelerated tracking-learning-detection

    NASA Astrophysics Data System (ADS)

    Guo, Pengyu; Li, Xin; Ding, Shaowen; Tian, Zunhua; Zhang, Xiaohu

    2013-08-01

    An improved online long-term visual tracking algorithm, named adaptive and accelerated TLD (AA-TLD) based on Tracking-Learning-Detection (TLD) which is a novel tracking framework has been introduced in this paper. The improvement focuses on two aspects, one is adaption, which makes the algorithm not dependent on the pre-defined scanning grids by online generating scale space, and the other is efficiency, which uses not only algorithm-level acceleration like scale prediction that employs auto-regression and moving average (ARMA) model to learn the object motion to lessen the detector's searching range and the fixed number of positive and negative samples that ensures a constant retrieving time, but also CPU and GPU parallel technology to achieve hardware acceleration. In addition, in order to obtain a better effect, some TLD's details are redesigned, which uses a weight including both normalized correlation coefficient and scale size to integrate results, and adjusts distance metric thresholds online. A contrastive experiment on success rate, center location error and execution time, is carried out to show a performance and efficiency upgrade over state-of-the-art TLD with partial TLD datasets and Shenzhou IX return capsule image sequences. The algorithm can be used in the field of video surveillance to meet the need of real-time video tracking.

  3. Neurotechnology to accelerate learning: during marksmanship training.

    PubMed

    Behneman, Adrienne; Berka, Chris; Stevens, Ronald; Vila, Bryan; Tan, Veasna; Galloway, Trysha; Johnson, Robin; Raphael, Giby

    2012-01-01

    This article explores the psychophysiological metrics during expert and novice performances in marksmanship, combat deadly force judgment and decision making (DFJDM), and interactions of teams. Electroencephalography (EEG) and electrocardiography (ECG) are used to characterize the psychophysiological profiles within all categories. Closed-loop biofeedback was administered to accelerate learning during marksmanship training in which the results show a difference in groups that received feedback compared with the control. During known distance marksmanship and DFJDM scenarios, experts show superior ability to control physiology to meet the demands of the task. Expertise in teaming scenarios is characterized by higher levels of cohesiveness than those seen in novices.

  4. Accelerating Multiagent Reinforcement Learning by Equilibrium Transfer.

    PubMed

    Hu, Yujing; Gao, Yang; An, Bo

    2015-07-01

    An important approach in multiagent reinforcement learning (MARL) is equilibrium-based MARL, which adopts equilibrium solution concepts in game theory and requires agents to play equilibrium strategies at each state. However, most existing equilibrium-based MARL algorithms cannot scale due to a large number of computationally expensive equilibrium computations (e.g., computing Nash equilibria is PPAD-hard) during learning. For the first time, this paper finds that during the learning process of equilibrium-based MARL, the one-shot games corresponding to each state's successive visits often have the same or similar equilibria (for some states more than 90% of games corresponding to successive visits have similar equilibria). Inspired by this observation, this paper proposes to use equilibrium transfer to accelerate equilibrium-based MARL. The key idea of equilibrium transfer is to reuse previously computed equilibria when each agent has a small incentive to deviate. By introducing transfer loss and transfer condition, a novel framework called equilibrium transfer-based MARL is proposed. We prove that although equilibrium transfer brings transfer loss, equilibrium-based MARL algorithms can still converge to an equilibrium policy under certain assumptions. Experimental results in widely used benchmarks (e.g., grid world game, soccer game, and wall game) show that the proposed framework: 1) not only significantly accelerates equilibrium-based MARL (up to 96.7% reduction in learning time), but also achieves higher average rewards than algorithms without equilibrium transfer and 2) scales significantly better than algorithms without equilibrium transfer when the state/action space grows and the number of agents increases.

  5. Learn-as-you-go acceleration of cosmological parameter estimates

    SciTech Connect

    Aslanyan, Grigor; Easther, Richard; Price, Layne C. E-mail: r.easther@auckland.ac.nz

    2015-09-01

    Cosmological analyses can be accelerated by approximating slow calculations using a training set, which is either precomputed or generated dynamically. However, this approach is only safe if the approximations are well understood and controlled. This paper surveys issues associated with the use of machine-learning based emulation strategies for accelerating cosmological parameter estimation. We describe a learn-as-you-go algorithm that is implemented in the Cosmo++ code and (1) trains the emulator while simultaneously estimating posterior probabilities; (2) identifies unreliable estimates, computing the exact numerical likelihoods if necessary; and (3) progressively learns and updates the error model as the calculation progresses. We explicitly describe and model the emulation error and show how this can be propagated into the posterior probabilities. We apply these techniques to the Planck likelihood and the calculation of ΛCDM posterior probabilities. The computation is significantly accelerated without a pre-defined training set and uncertainties in the posterior probabilities are subdominant to statistical fluctuations. We have obtained a speedup factor of 6.5 for Metropolis-Hastings and 3.5 for nested sampling. Finally, we discuss the general requirements for a credible error model and show how to update them on-the-fly.

  6. Advance techniques for monitoring human tolerance to positive Gz accelerations

    NASA Technical Reports Server (NTRS)

    Pelligra, R.; Sandler, H.; Rositano, S.; Skrettingland, K.; Mancini, R.

    1973-01-01

    Tolerance to positive g accelerations was measured in ten normal male subjects using both standard and advanced techniques. In addition to routine electrocardiogram, heart rate, respiratory rate, and infrared television, monitoring techniques during acceleration exposure included measurement of peripheral vision loss, noninvasive temporal, brachial, and/or radial arterial blood flow, and automatic measurement of indirect systolic and diastolic blood pressure at 60-sec intervals. Although brachial and radial arterial flow measurements reflected significant cardiovascular changes during and after acceleration, they were inconsistent indices of the onset of grayout or blackout. Temporal arterial blood flow, however, showed a high correlation with subjective peripheral light loss.

  7. A new acceleration technique for the design of fibre gratings.

    PubMed

    Carvalho, J C C; Sousa, M J; Sales Júnior, C S; Costa, J C W A; Francês, C R L; Segatto, M E V

    2006-10-30

    In this paper we propose a novel acceleration technique for the design of fibre gratings based on Genetic Algorithm (GA). It is shown that with an appropriate reformulation of the wavelength sampling scheme it is possible to design high quality optical filters with low computational effort. Our results will show that the proposed technique can reduce significantly the GA's processing time.

  8. Accelerator based techniques for contraband detection

    NASA Astrophysics Data System (ADS)

    Vourvopoulos, George

    1994-05-01

    It has been shown that narcotics, explosives, and other contraband materials, contain various chemical elements such as H, C, N, O, P, S, and Cl in quantities and ratios that differentiate them from each other and from other innocuous substances. Neutrons and γ-rays have the ability to penetrate through various materials at large depths. They are thus able, in a non-intrusive way, to interrogate volumes ranging from suitcases to Sea-Land containers, and have the ability to image the object with an appreciable degree of reliability. Neutron induced reactions such as (n, γ), (n, n') (n, p) or proton induced γ-resonance absorption are some of the reactions currently investigated for the identification of the chemical elements mentioned above. Various DC and pulsed techniques are discussed and their advantages, characteristics, and current progress are shown. Areas where use of these methods is currently under evaluation are detection of hidden explosives, illicit drug interdiction, chemical war agents identification, nuclear waste assay, nuclear weapons destruction and others.

  9. Advance techniques for monitoring human tolerance to +Gz accelerations.

    NASA Technical Reports Server (NTRS)

    Pelligra, R.; Sandler, H.; Rositano, S.; Skrettingland, K.; Mancini, R.

    1972-01-01

    Standard techniques for monitoring the acceleration-stressed human subject have been augmented by measuring (1) temporal, brachial and/or radial arterial blood flow, and (2) indirect systolic and diastolic blood pressure at 60-sec intervals. Results show that the response of blood pressure to positive accelerations is complex and dependent on an interplay of hydrostatic forces, diminishing venous return, redistribution of blood, and other poorly defined compensatory reflexes.

  10. ACCELERATORS: Alignment techniques for DRAGON-I LIA

    NASA Astrophysics Data System (ADS)

    Dai, Zhi-Yong; Xie, Yu-Tong; Li, Hong; Zhang, Wen-Wei; Liu, Yun-Long; Pan, Hai-Feng; Zhang, Lin-Wen; Deng, Jian-Jun

    2009-09-01

    DRAGON-I designed and manufactured by CAEP is a linear induction accelerator which can produce a 20 MeV-3 kA-60 ns electron beam. The high performance required for the machine is determined by the beam quality and thus is greatly dependent on the accelerator alignment. In order to reduce the chromatic effect of the beam, the stretched wire technique has been developed to measure magnetic axes of the cells precisely, and the dipole steering magnets have been equipped into each cell to correct its magnetic axis misalignment. Finally, the laser tracker has been used to examine the installation error of the accelerator. In this paper, different alignment techniques and the primary results are presented and discussed.

  11. GPU accelerating technique for rendering implicitly represented vasculatures.

    PubMed

    Hong, Qingqi; Wang, Beizhan; Li, Qingde; Li, Yan; Wu, Qingqiang

    2014-01-01

    With the flooding datasets of medical Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), implicit modeling techniques are increasingly applied to reconstruct the human organs, especially the vasculature. However, displaying implicitly represented geometric objects arises heavy computational burden. In this study, a Graphics Processing Unit (GPU) accelerating technique was developed for high performance rendering of implicitly represented objects, especially the vasculatures. The experimental results suggested that the rendering performance was greatly enhanced via exploiting the advantages of modern GPUs.

  12. Accelerated Peer-Review Journal Usage Technique for Undergraduates

    ERIC Educational Resources Information Center

    Wallace, J. D.

    2008-01-01

    The internet has given undergraduate students ever-increasing access to academic journals via search engines and online databases. However, students typically do not have the ability to use these journals effectively. This often poses a dilemma for instructors. The accelerated peer-review journal usage (APJU) technique provides a way for…

  13. Statistical Modeling of Photovoltaic Reliability Using Accelerated Degradation Techniques (Poster)

    SciTech Connect

    Lee, J.; Elmore, R.; Jones, W.

    2011-02-01

    We introduce a cutting-edge life-testing technique, accelerated degradation testing (ADT), for PV reliability testing. The ADT technique is a cost-effective and flexible reliability testing method with multiple (MADT) and Step-Stress (SSADT) variants. In an environment with limited resources, including equipment (chambers), test units, and testing time, these techniques can provide statistically rigorous prediction of lifetime and other interesting parameters, such as failure rate, warranty time, mean time to failure, degradation rate, activation energy, acceleration factor, and upper limit level of stress. J-V characterization can be used for degradation data and the generalized Eyring model can be used for the thermal-humidity stress condition. The SSADT model can be constructed based on the cumulative damage model (CEM), which assumes that the remaining test united are failed according to cumulative density function of current stress level regardless of the history on previous stress levels.

  14. The Accelerated Learning Program: Throwing Open the Gates

    ERIC Educational Resources Information Center

    Adams, Peter; Gearhart, Sarah; Miller, Robert; Roberts, Anne

    2009-01-01

    This article reports on the Accelerated Learning Program (ALP), a new model of basic writing that has produced dramatic successes for the basic writing program at the Community College of Baltimore County. Borrowing from mainstreaming programs, studio courses, fast track programs, and learning communities, ALP, for four consecutive semesters, has…

  15. The Journal of Accelerated Learning and Teaching, 1999.

    ERIC Educational Resources Information Center

    Journal of Accelerated Learning and Teaching, 1999

    1999-01-01

    This document comprises the entire output for the journal for 1999. "Brain-Based Learning Longitudinal Study Reveals Solid Academic Achievement Maintenance with Accelerated Learning Practice," is a longitudinal follow-up study to an article in the preceding issue of this journal (v23 n3-4). This study further validates the effectiveness of…

  16. Stimulating Deep Learning Using Active Learning Techniques

    ERIC Educational Resources Information Center

    Yew, Tee Meng; Dawood, Fauziah K. P.; a/p S. Narayansany, Kannaki; a/p Palaniappa Manickam, M. Kamala; Jen, Leong Siok; Hoay, Kuan Chin

    2016-01-01

    When students and teachers behave in ways that reinforce learning as a spectator sport, the result can often be a classroom and overall learning environment that is mostly limited to transmission of information and rote learning rather than deep approaches towards meaningful construction and application of knowledge. A group of college instructors…

  17. Cooperative Learning Techniques in the Classroom.

    ERIC Educational Resources Information Center

    Griffith, Scott C.

    1990-01-01

    Discusses the positive effects of cooperative learning on students' academic achievement, attitudes toward each other, and social and affective development. Describes two cooperative learning techniques with broad utility and adaptability: the jigsaw strategy and student teams achievement division. (SV)

  18. ULTRA-COMPACT ACCELERATOR TECHNOLOGIES FOR APPLICATION IN NUCLEAR TECHNIQUES

    SciTech Connect

    Sampayan, S; Caporaso, G; Chen, Y; Carazo, V; Falabella, S; Guethlein, G; Guse, S; Harris, J R; Hawkins, S; Holmes, C; Krogh, M; Nelson, S; Paul, A C; Pearson, D; Poole, B; Schmidt, R; Sanders, D; Selenes, K; Sitaraman, S; Sullivan, J; Wang, L; Watson, J

    2009-06-11

    We report on compact accelerator technology development for potential use as a pulsed neutron source quantitative post verifier. The technology is derived from our on-going compact accelerator technology development program for radiography under the US Department of Energy and for a clinic sized compact proton therapy systems under an industry sponsored Cooperative Research and Development Agreement. The accelerator technique relies on the synchronous discharge of a prompt pulse generating stacked transmission line structure with the beam transit. The goal of this technology is to achieve {approx}10 MV/m gradients for 10s of nanoseconds pulses and to {approx}100 MV/m gradients for {approx}1 ns systems. As a post verifier for supplementing existing x-ray equipment, this system can remain in a charged, stand-by state with little or no energy consumption. We detail the progress of our overall component development effort with the multilayer dielectric wall insulators (i.e., the accelerator wall), compact power supply technology, kHz repetition-rate surface flashover ion sources, and the prompt pulse generation system consisting of wide-bandgap switches and high performance dielectric materials.

  19. ULTRA-COMPACT ACCELERATOR TECHNOLOGIES FOR APPLICATION IN NUCLEAR TECHNIQUES

    SciTech Connect

    Sampayan, S.; Caporaso, G.; Chen, Y.-J.; Falabella, S.; Guethlein, G.; Harris, J. R.; Hawkins, S.; Holmes, C.; Nelson, S.; Paul, A. C.; Poole, B.; Sanders, D.; Sitaraman, S.; Sullivan, J.; Wang, L.; Watson, J.; Carazo, V.; Guse, S.; Pearson, D.; Schmidt, R.

    2009-12-02

    We report on compact accelerator technology development for potential use as a pulsed neutron source quantitative post verifier. The technology is derived from our on-going compact accelerator technology development program for radiography under the US Department of Energy and for a clinic sized compact proton therapy systems under an industry sponsored Cooperative Research and Development Agreement. The accelerator technique relies on the synchronous discharge of a prompt pulse generating stacked transmission line structure with the beam transit. The goal of this technology is to achieve approx10 MV/m gradients for 10 s of nanoseconds pulses and approx100 MV/m gradients for approx1 ns systems. As a post verifier for supplementing existing x-ray equipment, this system can remain in a charged, stand-by state with little or no energy consumption. We describe the progress of our overall component development effort with the multilayer dielectric wall insulators (i.e., the accelerator wall), compact power supply technology, kHz repetition-rate surface flashover ion sources, and the prompt pulse generation system consisting of wide-bandgap switches and high performance dielectric materials.

  20. Accelerated Learning and Retention: Literature Review and Workshop Review

    DTIC Science & Technology

    2011-03-01

    effectiveness, and the committee found that neurolinguistic programming (NLP) had promise, but had not been shown to be effective. They also...Meier, 2000) have used accelerated learning in training programs . Table 3 provides concrete examples of some of the results offered by approaches...minute counts (as is the case in accelerated programs ), motivation is of critical importance. This is one reason why training interventions aimed to

  1. Assessment Techniques To Enhance Organizational Learning.

    ERIC Educational Resources Information Center

    Lyons, Paul

    This paper addresses the need for group-based or team-based techniques to facilitate organizational learning. It identifies two process-oriented strategies: the role analysis technique (RAT) and the diagnostic window technique. These techniques can be used in meetings to model the intellectual tasks that need to occur in today's learning…

  2. Lessons Learned from Accelerating Opportunity. Lessons Learned Series

    ERIC Educational Resources Information Center

    Wilson, Randall

    2015-01-01

    The Accelerating Opportunity initiative helps our nation's lowest-skilled adults earn college credentials and enter higher-wage jobs faster by combining the Adult Basic Education and career and technical training they need into one integrated curriculum. Based on four years of designing and managing Accelerating Opportunity, Jobs for the Future…

  3. Analysis of Cultural Heritage by Accelerator Techniques and Analytical Imaging

    NASA Astrophysics Data System (ADS)

    Ide-Ektessabi, Ari; Toque, Jay Arre; Murayama, Yusuke

    2011-12-01

    In this paper we present the result of experimental investigation using two very important accelerator techniques: (1) synchrotron radiation XRF and XAFS; and (2) accelerator mass spectrometry and multispectral analytical imaging for the investigation of cultural heritage. We also want to introduce a complementary approach to the investigation of artworks which is noninvasive and nondestructive that can be applied in situ. Four major projects will be discussed to illustrate the potential applications of these accelerator and analytical imaging techniques: (1) investigation of Mongolian Textile (Genghis Khan and Kublai Khan Period) using XRF, AMS and electron microscopy; (2) XRF studies of pigments collected from Korean Buddhist paintings; (3) creating a database of elemental composition and spectral reflectance of more than 1000 Japanese pigments which have been used for traditional Japanese paintings; and (4) visible light-near infrared spectroscopy and multispectral imaging of degraded malachite and azurite. The XRF measurements of the Japanese and Korean pigments could be used to complement the results of pigment identification by analytical imaging through spectral reflectance reconstruction. On the other hand, analysis of the Mongolian textiles revealed that they were produced between 12th and 13th century. Elemental analysis of the samples showed that they contained traces of gold, copper, iron and titanium. Based on the age and trace elements in the samples, it was concluded that the textiles were produced during the height of power of the Mongol empire, which makes them a valuable cultural heritage. Finally, the analysis of the degraded and discolored malachite and azurite demonstrates how multispectral analytical imaging could be used to complement the results of high energy-based techniques.

  4. New modes of particle accelerations techniques and sources. Formal report

    SciTech Connect

    Parsa, Z.

    1996-12-31

    This Report includes copies of transparencies and notes from the presentations made at the Symposium on New Modes of Particle Accelerations - Techniques and Sources, August 19-23, 1996 at the Institute for Theoretical Physics, University of California, Santa Barbara California, that was made available by the authors. Editing, reduction and changes to the authors contributions were made only to fulfill the printing and publication requirements. We would like to take this opportunity and thank the speakers for their informative presentations and for providing copies of their transparencies and notes for inclusion in this Report.

  5. Structure of Accelerated Learning Program (ALP) Efforts, 2000-01.

    ERIC Educational Resources Information Center

    Baenen, Nancy; Yaman, Kimberly

    This report focuses on the structure of instructional assistance available through the Accelerated Learning Program (ALP) to students who show low achievement in the Wake County Public School System (WCPSS), North Carolina. Context information is also provided on other programs available to these students. Reports on ALP student participation,…

  6. The World of Wonder Accelerated Learning Community: A Case Study.

    ERIC Educational Resources Information Center

    Biddle, Julie K.

    This report presents a case study of the World of Wonders Accelerated Learning Community School (WOW). A community school in Ohio is a new kind of public school-an independent public school that is nonsectarian and nondiscriminatory. The report presents three contexts for the study--historical, local and methodological--and highlights some of the…

  7. Marine Forces Reserve: Accelerating Knowledge Flow through Asynchronous Learning Technologies

    DTIC Science & Technology

    2014-12-19

    processes , requirements and legalities about which incoming I-Is have negligible opportunities for advance or rapid learning. In short, the active...Current Knowledge Flow Processes .............................................................. 14 3. Alternate Processes to Accelerate Knowledge Flows...the Reserve component presents unique business processes , requirements and legalities about which incoming I-Is have negligible opportunities for

  8. Accelerating Leadership Development via Immersive Learning and Cognitive Apprenticeship

    ERIC Educational Resources Information Center

    Backus, Clark; Keegan, Kevin; Gluck, Charles; Gulick, Lisa M. V.

    2010-01-01

    The authors put forward an approach to leadership development that builds on the principle of accelerated learning. They argue that leadership development, particularly in a period of recession or slow economic growth, needs to deliver results more quickly and with fewer resources. Indeed, they raise the question of whether or not this is what is…

  9. FEM Techniques for High Stress Detection in Accelerated Fatigue Simulation

    NASA Astrophysics Data System (ADS)

    Veltri, M.

    2016-09-01

    This work presents the theory and a numerical validation study in support to a novel method for a priori identification of fatigue critical regions, with the aim to accelerate durability design in large FEM problems. The investigation is placed in the context of modern full-body structural durability analysis, where a computationally intensive dynamic solution could be required to identify areas with potential for fatigue damage initiation. The early detection of fatigue critical areas can drive a simplification of the problem size, leading to sensible improvement in solution time and model handling while allowing processing of the critical areas in higher detail. The proposed technique is applied to a real life industrial case in a comparative assessment with established practices. Synthetic damage prediction quantification and visualization techniques allow for a quick and efficient comparison between methods, outlining potential application benefits and boundaries.

  10. Machine Learning Techniques in Clinical Vision Sciences.

    PubMed

    Caixinha, Miguel; Nunes, Sandrina

    2017-01-01

    This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration

  11. Fast Imaging Technique for fMRI: Consecutive Multishot Echo Planar Imaging Accelerated with GRAPPA Technique.

    PubMed

    Kang, Daehun; Sung, Yul-Wan; Kang, Chang-Ki

    2015-01-01

    This study was to evaluate the proposed consecutive multishot echo planar imaging (cmsEPI) combined with a parallel imaging technique in terms of signal-to-noise ratio (SNR) and acceleration for a functional imaging study. We developed cmsEPI sequence using both consecutively acquired multishot EPI segments and variable flip angles to minimize the delay between segments and to maximize the SNR, respectively. We also combined cmsEPI with the generalized autocalibrating partially parallel acquisitions (GRAPPA) method. Temporal SNRs were measured at different acceleration factors and number of segments for functional sensitivity evaluation. We also examined the geometric distortions, which inherently occurred in EPI sequence. The practical acceleration factors, R = 2 or R = 3, of the proposed technique improved the temporal SNR by maximally 18% in phantom test and by averagely 8.2% in in vivo experiment, compared to cmsEPI without parallel imaging. The data collection time was decreased in inverse proportion to the acceleration factor as well. The improved temporal SNR resulted in better statistical power when evaluated on the functional response of the brain. In this study, we demonstrated that the combination of cmsEPI with the parallel imaging technique could provide the improved functional sensitivity for functional imaging study, compensating for the lower SNR by cmsEPI.

  12. Fast Imaging Technique for fMRI: Consecutive Multishot Echo Planar Imaging Accelerated with GRAPPA Technique

    PubMed Central

    Kang, Daehun; Sung, Yul-Wan; Kang, Chang-Ki

    2015-01-01

    This study was to evaluate the proposed consecutive multishot echo planar imaging (cmsEPI) combined with a parallel imaging technique in terms of signal-to-noise ratio (SNR) and acceleration for a functional imaging study. We developed cmsEPI sequence using both consecutively acquired multishot EPI segments and variable flip angles to minimize the delay between segments and to maximize the SNR, respectively. We also combined cmsEPI with the generalized autocalibrating partially parallel acquisitions (GRAPPA) method. Temporal SNRs were measured at different acceleration factors and number of segments for functional sensitivity evaluation. We also examined the geometric distortions, which inherently occurred in EPI sequence. The practical acceleration factors, R = 2 or R = 3, of the proposed technique improved the temporal SNR by maximally 18% in phantom test and by averagely 8.2% in in vivo experiment, compared to cmsEPI without parallel imaging. The data collection time was decreased in inverse proportion to the acceleration factor as well. The improved temporal SNR resulted in better statistical power when evaluated on the functional response of the brain. In this study, we demonstrated that the combination of cmsEPI with the parallel imaging technique could provide the improved functional sensitivity for functional imaging study, compensating for the lower SNR by cmsEPI. PMID:26413518

  13. Drama Techniques in Language Learning.

    ERIC Educational Resources Information Center

    Maley, Alan; Duff, Alan

    The drama activities in this teaching guide are designed to develop second language learning skills by constructing situations that require the student to concentrate on the meaning and emotional content of language rather than on its structure. In an attempt to involve the whole personality of the learner in the acquisition of language, the…

  14. Collaborative Learning in the Dance Technique Class

    ERIC Educational Resources Information Center

    Raman, Tanja

    2009-01-01

    This research was designed to enhance dance technique learning by promoting critical thinking amongst students studying on a degree programme at the University of Wales Institute, Cardiff. Students were taught Cunningham-based dance technique using pair work together with the traditional demonstration/copying method. To evaluate the study,…

  15. Lie Group Techniques for Neural Learning

    DTIC Science & Technology

    2005-01-03

    Lie group techniques for Neural Learning Edinburgh June 2004 Elena Celledoni SINTEF Applied Mathematics, IMF-NTNU Lie group techniques for Neural...ORGANIZATION NAME(S) AND ADDRESS(ES) SINTEF Applied Mathematics, IMF-NTNU 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND

  16. Learning to Attend to Threat Accelerates and Enhances Memory Consolidation

    PubMed Central

    Abend, Rany; Karni, Avi; Sadeh, Avi; Fox, Nathan A.; Pine, Daniel S.; Bar-Haim, Yair

    2013-01-01

    Practice on a procedural task involves within-session learning and between-session consolidation of learning, with the latter requiring a minimum of about four hours to evolve due to involvement of slower cellular processes. Learning to attend to threats is vital for survival and thus may involve faster memory consolidation than simple procedural learning. Here, we tested whether attention to threat modulates the time-course and magnitude of learning and memory consolidation effects associated with skill practice. All participants (N = 90) practiced in two sessions on a dot-probe task featuring pairs of neutral and angry faces followed by target probes which were to be discriminated as rapidly as possible. In the attend-threat training condition, targets always appeared at the angry face location, forming an association between threat and target location; target location was unrelated to valence in a control training condition. Within each attention training condition, duration of the between-session rest interval was varied to establish the time-course for emergence of consolidation effects. During the first practice session, we observed robust improvement in task performance (online, within-session gains), followed by saturation of learning. Both training conditions exhibited similar overall learning capacities, but performance in the attend-threat condition was characterized by a faster learning rate relative to control. Consistent with the memory consolidation hypothesis, between-session performance gains (delayed gains) were observed only following a rest interval. However, rest intervals of 1 and 24 hours yielded similar delayed gains, suggesting accelerated consolidation processes. Moreover, attend-threat training resulted in greater delayed gains compared to the control condition. Auxiliary analyses revealed that enhanced performance was retained over several months, and that training to attend to neutral faces resulted in effects similar to control

  17. Accelerated Online Learning: Perceptions of Interaction and Learning Outcomes among African American Students

    ERIC Educational Resources Information Center

    Kuo, Yu-Chun

    2014-01-01

    This study investigated student interaction, satisfaction, and performance in accelerated online learning environments with the use of an online learning course-management system. The interactions assessed in this study included learner-learner interaction, learner-instructor interaction, and learner-content interaction. The participants were…

  18. The Effects of Accelerated Learning on Tertiary Students Learning To Write.

    ERIC Educational Resources Information Center

    Fretz, Barbara L.

    A study investigated how Accelerated Learning (AL), a teaching methodology that purports to increase the quantity and improve the quality of learning, affected tertiary students' knowledge of and skills in writing and their feelings towards writing. AL has its origins in G. Lozanov's "suggestopedia." Believing that formal teaching…

  19. Acceleration of saddle-point searches with machine learning.

    PubMed

    Peterson, Andrew A

    2016-08-21

    In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the number of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.

  20. Fastest Electropolishing Technique on Niobium for Particle Accelerators

    SciTech Connect

    A.T. Wu, S. Jin, R.A. Rimmer, X.Y. Lu, K. Zhao

    2011-09-01

    Field emission on the inner surfaces of niobium (Nb) superconducting radio frequency (SRF) cavities is still one of the major obstacles for reaching high accelerating gradients for SRF community. Our previous experimental results [1] seemed to imply that the threshold of field emission was related to the thickness of Nb surface oxide layers. In this contribution, a more detailed study on the influences of the surface oxide layers on the field emission on Nb surfaces will be reported. By anodization technique, the thickness of the surface pentoxide layer was artificially fabricated from 3nm up to 460nm. A home-made scanning field emission microscope (SFEM) was employed to perform the scans on the surfaces. Emitters were characterized using a scanning electron microscope together with an energy dispersive x-ray analyzer. The experimental results could be understood by a simple model calculation based on classic electromagnetic theory as shown in Ref.1. Possibly implications for Nb SRF cavity applications from this study will be discussed.

  1. m-Learning and holography: Compatible techniques?

    NASA Astrophysics Data System (ADS)

    Calvo, Maria L.

    2014-07-01

    Since the last decades, cell phones have become increasingly popular and are nowadays ubiquitous. New generations of cell phones are now equipped with text messaging, internet, and camera features. They are now making their way into the classroom. This is creating a new teaching and learning technique, the so called m-Learning (or mobile-Learning). Because of the many benefits that cell phones offer, teachers could easily use them as a teaching and learning tool. However, an additional work from the teachers for introducing their students into the m-Learning in the classroom needs to be defined and developed. As an example, optical techniques, based upon interference and diffraction phenomena, such as holography, appear to be convenient topics for m-Learning. They can be approached with simple examples and experiments within the cell phones performances and classroom accessibility. We will present some results carried out at the Faculty of Physical Sciences in UCM to obtain very simple holographic recordings via cell phones. The activities were carried out inside the course on Optical Coherence and Laser, offered to students in the fourth course of the Grade in Physical Sciences. Some open conclusions and proposals will be presented.

  2. Novel production techniques of radioisotopes using electron accelerators

    NASA Astrophysics Data System (ADS)

    Lowe, Daniel Robert

    Non-traditional radioisotope production techniques using a compact, high power linear electron accelerator have been demonstrated and characterized for the production of 18F, 47Sc, 147 Pm, and 99mTc from a variety of target candidates. These isotopes are used extensively in the medical field as diagnostic and therapy radioisotopes, as well as the space industry as RTG's. Primary focus was placed on 99mTc as it constitutes approximately 80% of all diagnostic procedures in the medical community that use radioactive tracers. It was also the prime focus due to recent events at the Chalk River nuclear reactor, which caused global shortages of this isotope a few years ago. A Varian K15 LINAC was first used to show proof of principle in Las Vegas. Various samples were then taken to the Idaho Accelerator Center where they were activated using an electron LINAC capable of electron energies from 4 to 25 MeV at a beam power of approximately 1 kW. Production rates, cross sections, and viability studies were then performed and conducted to assess the effectiveness of the candidate target and the maximum production rate for each radioisotope. Production rates for 18F from lithium fluoride salts were shown to be ideal at 21MeV, namely 1.7 Ci per kg of LiF salt, per kW of beam current, per 10 hour irradiation time. As the typical hospital consumption of 18F is around 500 mCi per day, it is clear that a large amount of 18F can be made from a small (300 gram) sample of LiF salt. However, since there is no current separation process for 18F from 19F, the viability of this technique is limited until a separations technique is developed. Furthermore, the calculated cross section for this reaction is in good agreement with literature, which supports the techniques for the isotopes mentioned below. Production rates for 47Sc from vanadium oxide targets were shown to be a maximum at 25 MeV with a production rate of 2 mCi per day, assuming a 2 kW beam and a 10 kg target. While this

  3. Three visual techniques to enhance interprofessional learning.

    PubMed

    Parsell, G; Gibbs, T; Bligh, J

    1998-07-01

    Many changes in the delivery of healthcare in the UK have highlighted the need for healthcare professionals to learn to work together as teams for the benefit of patients. Whatever the profession or level, whether for postgraduate education and training, continuing professional development, or for undergraduates, learners should have an opportunity to learn about and with, other healthcare practitioners in a stimulating and exciting way. Learning to understand how people think, feel, and react, and the parts they play at work, both as professionals and individuals, can only be achieved through sensitive discussion and exchange of views. Teaching and learning methods must provide opportunities for this to happen. This paper describes three small-group teaching techniques which encourage a high level of learner collaboration and team-working. Learning content is focused on real-life health-care issues and strong visual images are used to stimulate lively discussion and debate. Each description includes the learning objectives of each exercise, basic equipment and resources, and learning outcomes.

  4. Accelerating learning for pro-poor health markets

    PubMed Central

    2014-01-01

    Background Given the rapid evolution of health markets, learning is key to promoting the identification and uptake of health market policies and practices that better serve the needs of the poor. However there are significant challenges to learning about health markets. We discuss the different forms that learning takes, from the development of codified scientific knowledge, through to experience-based learning, all in relationship to health markets. Discussion Notable challenges to learning in health markets include the difficulty of acquiring data from private health care providers, designing evaluations that capture the complex dynamics present within health markets and developing communities of practice that encompass the diverse actors present within health markets, and building trust and mutual understanding across these groups. The paper proposes experimentation with country-specific market data platforms that can integrate relevant evidence from different data sources, and simultaneously exploring strategies to secure better information on private providers and health markets. Possible approaches to adapting evaluation designs so that they are better able to take account of different and changing contexts as well as producing real time findings are discussed. Finally capturing informal knowledge about health markets is key. Communities of practice that bridge different health market actors can help to share such experience-based knowledge and in so doing, may help to formalize it. More geographically-focused communities of practice are needed, and such communities may be supported by innovation brokers and/or be built around member-based organizations. Summary Strategic investments in and support to learning about health markets can address some of the challenges experienced to-date, and accelerate learning that supports health markets that serve the poor. PMID:24961671

  5. Techniques for increasing the reliability of accelerator control system electronics

    SciTech Connect

    Utterback, J.

    1993-09-01

    As the physical size of modern accelerators becomes larger and larger, the number of required control system circuit boards increases, and the probability of one of those circuit boards failing while in service also increases. In order to do physics, the experimenters need the accelerator to provide beam reliably with as little down time as possible. With the advent of colliding beams physics, reliability becomes even more important due to the fact that a control system failure can cause the loss of painstakingly produced antiprotons. These facts prove the importance of keeping reliability in mind when designing and maintaining accelerator control system electronics.

  6. Novel Uses of Video to Accelerate the Surgical Learning Curve.

    PubMed

    Ibrahim, Andrew M; Varban, Oliver A; Dimick, Justin B

    2016-04-01

    Surgeons are under enormous pressure to continually improve and learn new surgical skills. Novel uses of surgical video in the preoperative, intraoperative, and postoperative setting are emerging to accelerate the learning curve of surgical skill and minimize harm to patients. In the preoperative setting, social media outlets provide a valuable platform for surgeons to collaborate and plan for difficult operative cases. Live streaming of video has allowed for intraoperative telementoring. Finally, postoperative use of video has provided structure for peer coaching to evaluate and improve surgical skill. Applying these approaches into practice is becoming easier as most of our surgical platforms (e.g., laparoscopic, and endoscopy) now have video recording technology built in and video editing software has become more user friendly. Future applications of video technology are being developed, including possible integration into accreditation and board certification.

  7. Novel Uses of Video to Accelerate the Surgical Learning Curve

    PubMed Central

    Varban, Oliver A.; Dimick, Justin B.

    2016-01-01

    Abstract Surgeons are under enormous pressure to continually improve and learn new surgical skills. Novel uses of surgical video in the preoperative, intraoperative, and postoperative setting are emerging to accelerate the learning curve of surgical skill and minimize harm to patients. In the preoperative setting, social media outlets provide a valuable platform for surgeons to collaborate and plan for difficult operative cases. Live streaming of video has allowed for intraoperative telementoring. Finally, postoperative use of video has provided structure for peer coaching to evaluate and improve surgical skill. Applying these approaches into practice is becoming easier as most of our surgical platforms (e.g., laparoscopic, and endoscopy) now have video recording technology built in and video editing software has become more user friendly. Future applications of video technology are being developed, including possible integration into accreditation and board certification. PMID:27031876

  8. Some acceleration techniques for calculating the eigenvalues of normal Toeplitz matrices

    NASA Astrophysics Data System (ADS)

    Abdikalykov, A. K.; Ikramov, Kh. D.; Chugunov, V. N.

    2014-12-01

    Certain techniques that can be used for accelerating the calculation of the eigenvalues of normal Toeplitz matrices are described. The run times of the standard Matlab procedure eig with and without the use of these techniques are compared.

  9. Learning at the Speed of Light: Deep Learning and Accelerated Online Graduate Courses

    ERIC Educational Resources Information Center

    Trekles, Anastasia M.

    2013-01-01

    An increasing number of university programs, particularly at the graduate level, are moving to an accelerated, time-compressed model for online degree offerings. However, the literature revealed that research in distance education effectiveness is still confounded by many variables, including course design and student approach to learning.…

  10. Accelerated corneal collagen crosslinking: Technique, efficacy, safety, and applications.

    PubMed

    Medeiros, Carla S; Giacomin, Natalia T; Bueno, Renata L; Ghanem, Ramon C; Moraes, Haroldo V; Santhiago, Marcony R

    2016-12-01

    Corneal collagen crosslinking (CXL) is an approach used to increase the biomechanical stability of the stromal tissue. Over the past 10 years, it has been used to halt the progression of ectatic diseases. According to the photochemical law of reciprocity, the same photochemical effect is achieved with reduced illumination time and correspondingly increased irradiation intensity. Several new CXL devices offer high ultraviolet-A irradiation intensity with different time settings. The main purpose of this review was to discuss the current use of different protocols of accelerated CXL and compare the efficacy and safety of accelerated CXL with the efficacy and safety of the established conventional method. Accelerated CXL proved to be safe and effective in halting progression of corneal ectasia. Corneal shape responses varied considerably, as did the demarcation line at different irradiance settings; the shorter the exposure time, the more superficial the demarcation line.

  11. Machine Learning Strategy for Accelerated Design of Polymer Dielectrics

    PubMed Central

    Mannodi-Kanakkithodi, Arun; Pilania, Ghanshyam; Huan, Tran Doan; Lookman, Turab; Ramprasad, Rampi

    2016-01-01

    The ability to efficiently design new and advanced dielectric polymers is hampered by the lack of sufficient, reliable data on wide polymer chemical spaces, and the difficulty of generating such data given time and computational/experimental constraints. Here, we address the issue of accelerating polymer dielectrics design by extracting learning models from data generated by accurate state-of-the-art first principles computations for polymers occupying an important part of the chemical subspace. The polymers are ‘fingerprinted’ as simple, easily attainable numerical representations, which are mapped to the properties of interest using a machine learning algorithm to develop an on-demand property prediction model. Further, a genetic algorithm is utilised to optimise polymer constituent blocks in an evolutionary manner, thus directly leading to the design of polymers with given target properties. While this philosophy of learning to make instant predictions and design is demonstrated here for the example of polymer dielectrics, it is equally applicable to other classes of materials as well. PMID:26876223

  12. Machine Learning Strategy for Accelerated Design of Polymer Dielectrics.

    PubMed

    Mannodi-Kanakkithodi, Arun; Pilania, Ghanshyam; Huan, Tran Doan; Lookman, Turab; Ramprasad, Rampi

    2016-02-15

    The ability to efficiently design new and advanced dielectric polymers is hampered by the lack of sufficient, reliable data on wide polymer chemical spaces, and the difficulty of generating such data given time and computational/experimental constraints. Here, we address the issue of accelerating polymer dielectrics design by extracting learning models from data generated by accurate state-of-the-art first principles computations for polymers occupying an important part of the chemical subspace. The polymers are 'fingerprinted' as simple, easily attainable numerical representations, which are mapped to the properties of interest using a machine learning algorithm to develop an on-demand property prediction model. Further, a genetic algorithm is utilised to optimise polymer constituent blocks in an evolutionary manner, thus directly leading to the design of polymers with given target properties. While this philosophy of learning to make instant predictions and design is demonstrated here for the example of polymer dielectrics, it is equally applicable to other classes of materials as well.

  13. Machine learning strategy for accelerated design of polymer dielectrics

    DOE PAGES

    Mannodi-Kanakkithodi, Arun; Pilania, Ghanshyam; Huan, Tran Doan; ...

    2016-02-15

    The ability to efficiently design new and advanced dielectric polymers is hampered by the lack of sufficient, reliable data on wide polymer chemical spaces, and the difficulty of generating such data given time and computational/experimental constraints. Here, we address the issue of accelerating polymer dielectrics design by extracting learning models from data generated by accurate state-of-the-art first principles computations for polymers occupying an important part of the chemical subspace. The polymers are ‘fingerprinted’ as simple, easily attainable numerical representations, which are mapped to the properties of interest using a machine learning algorithm to develop an on-demand property prediction model. Further,more » a genetic algorithm is utilised to optimise polymer constituent blocks in an evolutionary manner, thus directly leading to the design of polymers with given target properties. Furthermore, while this philosophy of learning to make instant predictions and design is demonstrated here for the example of polymer dielectrics, it is equally applicable to other classes of materials as well.« less

  14. Machine learning strategy for accelerated design of polymer dielectrics

    SciTech Connect

    Mannodi-Kanakkithodi, Arun; Pilania, Ghanshyam; Huan, Tran Doan; Lookman, Turab; Ramprasad, Rampi

    2016-02-15

    The ability to efficiently design new and advanced dielectric polymers is hampered by the lack of sufficient, reliable data on wide polymer chemical spaces, and the difficulty of generating such data given time and computational/experimental constraints. Here, we address the issue of accelerating polymer dielectrics design by extracting learning models from data generated by accurate state-of-the-art first principles computations for polymers occupying an important part of the chemical subspace. The polymers are ‘fingerprinted’ as simple, easily attainable numerical representations, which are mapped to the properties of interest using a machine learning algorithm to develop an on-demand property prediction model. Further, a genetic algorithm is utilised to optimise polymer constituent blocks in an evolutionary manner, thus directly leading to the design of polymers with given target properties. Furthermore, while this philosophy of learning to make instant predictions and design is demonstrated here for the example of polymer dielectrics, it is equally applicable to other classes of materials as well.

  15. I-NET: interactive neuro-educational technology to accelerate skill learning.

    PubMed

    Raphael, Giby; Berka, Chris; Popovic, Djordje; Chung, Gregory K W K; Nagashima, Sam O; Behneman, Adrienne; Davis, Gene; Johnson, Robin

    2009-01-01

    The learning of a novel task currently rely heavily on conventional classroom instruction with qualitative assessment and observation. Introduction of individualized tutorials with integrated neuroscience-based evaluation techniques could significantly accelerate skill acquisition and provide quantitative evidence of successful training. We have created a suite of adaptive and interactive neuro-educational technologies (I-NET) to increase the pace and efficiency of skill learning. It covers four major themes: 1) Integration of brain monitoring into paced instructional tutorials, 2) Identifying psychophysiological characteristics of expertise using a model population, 3) Developing sensor-based feedback to accelerate novice-to-expert transition, 4) Identifying neurocognitive factors that are predictive of skill acquisition to allow early triage and interventions. We selected rifle marksmanship training as the field of application. Rifle marksmanship is a core skill for the Army and Marine Corps and it involves a combination of classroom instructional learning and field practice involving instantiation of a well-defined set of sensory, motor and cognitive skills. The instrumentation that incorporates the I-NET technologies is called the Adaptive Peak Performance Trainer (APPT). Preliminary analysis of pilot study data for performance data from a novice population that used this device revealed an improved learning trajectory.

  16. Artifical intelligence techniques for tuning linear induction accelerators

    SciTech Connect

    Lager, D.; Brand, H.; Chambers, F.; Coffield, F.; Maurer, W.; Turner, W.

    1991-05-01

    We developed an expert system that acts as an intelligent assistant for tuning particle beam generators called MAESTRO, Model and Expert System Resource for Operators. MAESTRO maintains a knowledge base of the accelerator containing not only the interconnections of the beamline components, but also their physical attributes such as measured magnetic tilts, offsets, and field profiles. MAESTRO incorporates particle trajectory and beam envelope models which are coupled to the knowledge base permitting large numbers of real-time orbit and envelope calculations in the control-room environment. To date we have used this capability in three ways: First, to implement a tuning algorithm for minimizing transverse beam motion. Second, to produce a beam waist with arbitrary radius at the entrance to a brightness diagnostic. And finally, to measure beam energy along the accelerator by fitting orbits to focusing and steering sweeps.

  17. Electrochemical migration technique to accelerate ageing of cementitious materials

    NASA Astrophysics Data System (ADS)

    Babaahmadi, A.; Tang, L.; Abbas, Z.

    2013-07-01

    Durability assessment of concrete structures for constructions in nuclear waste repositories requires long term service life predictions. As deposition of low and intermediate level radioactive waste (LILW) takes up to 100 000 years, it is necessary to analyze the service life of cementitious materials in this time perspective. Using acceleration methods producing aged specimens would decrease the need of extrapolating short term data sets. Laboratory methods are therefore, needed for accelerating the ageing process without making any influencing distortion in the properties of the materials. This paper presents an electro-chemical migration method to increase the rate of calcium leaching from cementitious specimens. This method is developed based on the fact that major long term deterioration process of hardened cement paste in concrete structures for deposition of LILW is due to slow diffusion of calcium ions. In this method the cementitious specimen is placed in an electrochemical cell as a porous path way through which ions can migrate at a rate far higher than diffusion process. The electrical field is applied to the cell in a way to accelerate the ion migration without making destructions in the specimen's micro and macroscopic properties. The anolyte and catholyte solutions are designed favoring dissolution of calcium hydroxide and compensating for the leached calcium ions with another ion like lithium.

  18. Lessons learned on the Ground Test Accelerator control system

    SciTech Connect

    Kozubal, A.J.; Weiss, R.E.

    1994-09-01

    When we initiated the control system design for the Ground Test Accelerator (GTA), we envisioned a system that would be flexible enough to handle the changing requirements of an experimental project. This control system would use a developers` toolkit to reduce the cost and time to develop applications for GTA, and through the use of open standards, the system would accommodate unforeseen requirements as they arose. Furthermore, we would attempt to demonstrate on GTA a level of automation far beyond that achieved by existing accelerator control systems. How well did we achieve these goals? What were the stumbling blocks to deploying the control system, and what assumptions did we make about requirements that turned out to be incorrect? In this paper we look at the process of developing a control system that evolved into what is now the ``Experimental Physics and Industrial Control System`` (EPICS). Also, we assess the impact of this system on the GTA project, as well as the impact of GTA on EPICS. The lessons learned on GTA will be valuable for future projects.

  19. Machine Learning Techniques for Persuasion Detection in Conversation

    DTIC Science & Technology

    2010-06-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MACHINE LEARNING TECHNIQUES FOR PERSUASION DECTECTION IN CONVERSATION by Pedro Ortiz June 2010...2008-06-01—2010-06-31 Machine Learning Techniques for Persuasion Dectection in Conversation Pedro Ortiz Naval Postgraduate School Monterey, CA 93943...automatically detect persuasion in conversations using three traditional machine learning techniques, naive bayes, maximum entropy, and support vector

  20. Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning

    ERIC Educational Resources Information Center

    Firdausiah Mansur, Andi Besse; Yusof, Norazah

    2013-01-01

    Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

  1. Acceleration techniques in the univariate Lipschitz global optimization

    NASA Astrophysics Data System (ADS)

    Sergeyev, Yaroslav D.; Kvasov, Dmitri E.; Mukhametzhanov, Marat S.; De Franco, Angela

    2016-10-01

    Univariate box-constrained Lipschitz global optimization problems are considered in this contribution. Geometric and information statistical approaches are presented. The novel powerful local tuning and local improvement techniques are described in the contribution as well as the traditional ways to estimate the Lipschitz constant. The advantages of the presented local tuning and local improvement techniques are demonstrated using the operational characteristics approach for comparing deterministic global optimization algorithms on the class of 100 widely used test functions.

  2. Machine learning techniques and drug design.

    PubMed

    Gertrudes, J C; Maltarollo, V G; Silva, R A; Oliveira, P R; Honório, K M; da Silva, A B F

    2012-01-01

    The interest in the application of machine learning techniques (MLT) as drug design tools is growing in the last decades. The reason for this is related to the fact that the drug design is very complex and requires the use of hybrid techniques. A brief review of some MLT such as self-organizing maps, multilayer perceptron, bayesian neural networks, counter-propagation neural network and support vector machines is described in this paper. A comparison between the performance of the described methods and some classical statistical methods (such as partial least squares and multiple linear regression) shows that MLT have significant advantages. Nowadays, the number of studies in medicinal chemistry that employ these techniques has considerably increased, in particular the use of support vector machines. The state of the art and the future trends of MLT applications encompass the use of these techniques to construct more reliable QSAR models. The models obtained from MLT can be used in virtual screening studies as well as filters to develop/discovery new chemicals. An important challenge in the drug design field is the prediction of pharmacokinetic and toxicity properties, which can avoid failures in the clinical phases. Therefore, this review provides a critical point of view on the main MLT and shows their potential ability as a valuable tool in drug design.

  3. Accelerated RN-to-BSN Service-Learning Program Serves the Vulnerable.

    PubMed

    Barnes, Margaret

    The definition, implementation, and benefits support the value of service-learning for nursing education. However, accelerated RN-to-BSN programs may have difficulty requiring service-learning experiences. This article offers a biblical rationale for service with vulnerable populations and an example of how service-learning is implemented into the curriculum of an accelerated, nontraditional, online/onsite RN-BSN completion program at a Christian university.

  4. Rotational Acceleration during Head Impact Resulting from Different Judo Throwing Techniques

    PubMed Central

    MURAYAMA, Haruo; HITOSUGI, Masahito; MOTOZAWA, Yasuki; OGINO, Masahiro; KOYAMA, Katsuhiro

    2014-01-01

    Most severe head injuries in judo are reported as acute subdural hematoma. It is thus necessary to examine the rotational acceleration of the head to clarify the mechanism of head injuries. We determined the rotational acceleration of the head when the subject is thrown by judo techniques. One Japanese male judo expert threw an anthropomorphic test device using two throwing techniques, Osoto-gari and Ouchigari. Rotational and translational head accelerations were measured with and without an under-mat. For Osoto-gari, peak resultant rotational acceleration ranged from 4,284.2 rad/s2 to 5,525.9 rad/s2 and peak resultant translational acceleration ranged from 64.3 g to 87.2 g; for Ouchi-gari, the accelerations respectively ranged from 1,708.0 rad/s2 to 2,104.1 rad/s2 and from 120.2 g to 149.4 g. The resultant rotational acceleration did not decrease with installation of an under-mat for both Ouchi-gari and Osoto-gari. We found that head contact with the tatami could result in the peak values of translational and rotational accelerations, respectively. In general, because kinematics of the body strongly affects translational and rotational accelerations of the head, both accelerations should be measured to analyze the underlying mechanism of head injury. As a primary preventative measure, throwing techniques should be restricted to participants demonstrating ability in ukemi techniques to avoid head contact with the tatami. PMID:24477065

  5. Rotational acceleration during head impact resulting from different judo throwing techniques.

    PubMed

    Murayama, Haruo; Hitosugi, Masahito; Motozawa, Yasuki; Ogino, Masahiro; Koyama, Katsuhiro

    2014-01-01

    Most severe head injuries in judo are reported as acute subdural hematoma. It is thus necessary to examine the rotational acceleration of the head to clarify the mechanism of head injuries. We determined the rotational acceleration of the head when the subject is thrown by judo techniques. One Japanese male judo expert threw an anthropomorphic test device using two throwing techniques, Osoto-gari and Ouchi-gari. Rotational and translational head accelerations were measured with and without an under-mat. For Osoto-gari, peak resultant rotational acceleration ranged from 4,284.2 rad/s(2) to 5,525.9 rad/s(2) and peak resultant translational acceleration ranged from 64.3 g to 87.2 g; for Ouchi-gari, the accelerations respectively ranged from 1,708.0 rad/s(2) to 2,104.1 rad/s(2) and from 120.2 g to 149.4 g. The resultant rotational acceleration did not decrease with installation of an under-mat for both Ouchi-gari and Osoto-gari. We found that head contact with the tatami could result in the peak values of translational and rotational accelerations, respectively. In general, because kinematics of the body strongly affects translational and rotational accelerations of the head, both accelerations should be measured to analyze the underlying mechanism of head injury. As a primary preventative measure, throwing techniques should be restricted to participants demonstrating ability in ukemi techniques to avoid head contact with the tatami.

  6. Crystalline Indium Sulphide thin film by photo accelerated deposition technique

    NASA Astrophysics Data System (ADS)

    Dhanya, A. C.; Preetha, K. C.; Deepa, K.; Remadevi, T. L.

    2015-02-01

    Indium sulfide thin films deserve special attention because of its potential application as buffer layers in CIGS based solar cells. Highly transparent indium sulfide (InS) thin films were prepared using a novel method called photo accelerated chemical deposition (PCD). Ultraviolet source of 150 W was used to irradiate the solution. Compared to all other chemical methods, PCD scores its advantage for its low cost, flexible substrate and capable of large area of deposition. Reports on deposition of high quality InS thin films at room temperature are very rare in literature. The precursor solution was initially heated to 90°C for ten minutes and then deposition was carried out at room temperature for two hours. The appearance of the film changed from lemon yellow to bright yellow as the deposition time increased. The sample was characterized for its structural and optical properties. XRD profile showed the polycrystalline behavior of the film with mixed phases having crystallite size of 17 nm. The surface morphology of the films exhibited uniformly distributed honey comb like structures. The film appeared to be smooth and the value of extinction coefficient was negligible. Optical measurements showed that the film has more than 80% transmission in the visible region. The direct band gap energy was 2.47eV. This method is highly suitable for the synthesis of crystalline and transparent indium sulfide thin films and can be used for various photo voltaic applications.

  7. Opportunities to Create Active Learning Techniques in the Classroom

    ERIC Educational Resources Information Center

    Camacho, Danielle J.; Legare, Jill M.

    2015-01-01

    The purpose of this article is to contribute to the growing body of research that focuses on active learning techniques. Active learning techniques require students to consider a given set of information, analyze, process, and prepare to restate what has been learned--all strategies are confirmed to improve higher order thinking skills. Active…

  8. Circular Bioassay Platforms for Applications in Microwave-Accelerated Techniques

    PubMed Central

    Mohammed, Muzaffer; Clement, Travis C.; Aslan, Kadir

    2014-01-01

    In this paper, we present the design of four different circular bioassay platforms, which are suitable for homogeneous microwave heating, using theoretical calculations (i.e., COMSOL™ multiphysics software). Circular bioassay platforms are constructed from poly(methyl methacrylate) (PMMA) for optical transparency between 400–800 nm, has multiple sample capacity (12, 16, 19 and 21 wells) and modified with silver nanoparticle films (SNFs) to be used in microwave-accelerated bioassays (MABs). In addition, a small monomode microwave cavity, which can be operated with an external microwave generator (100 W), for use with the bioassay platforms in MABs is also developed. Our design parameters for the circular bioassay platforms and monomode microwave cavity during microwave heating were: (i) temperature profiles, (ii) electric field distributions, (iii) location of the circular bioassay platforms inside the microwave cavity, and (iv) design and number of wells on the circular bioassay platforms. We have also carried out additional simulations to assess the use of circular bioassay platforms in a conventional kitchen microwave oven (e.g., 900 W). Our results show that the location of the circular bioassay platforms in the microwave cavity was predicted to have a significant effect on the homogeneous heating of these platforms. The 21-well circular bioassay platform design in our monomode microwave cavity was predicted to offer a homogeneous heating pattern, where inter-well temperature was observed to be in between 23.72–24.13°C and intra-well temperature difference was less than 0.21°C for 60 seconds of microwave heating, which was also verified experimentally. PMID:25568813

  9. Circular Bioassay Platforms for Applications in Microwave-Accelerated Techniques.

    PubMed

    Mohammed, Muzaffer; Clement, Travis C; Aslan, Kadir

    2014-12-02

    In this paper, we present the design of four different circular bioassay platforms, which are suitable for homogeneous microwave heating, using theoretical calculations (i.e., COMSOL™ multiphysics software). Circular bioassay platforms are constructed from poly(methyl methacrylate) (PMMA) for optical transparency between 400-800 nm, has multiple sample capacity (12, 16, 19 and 21 wells) and modified with silver nanoparticle films (SNFs) to be used in microwave-accelerated bioassays (MABs). In addition, a small monomode microwave cavity, which can be operated with an external microwave generator (100 W), for use with the bioassay platforms in MABs is also developed. Our design parameters for the circular bioassay platforms and monomode microwave cavity during microwave heating were: (i) temperature profiles, (ii) electric field distributions, (iii) location of the circular bioassay platforms inside the microwave cavity, and (iv) design and number of wells on the circular bioassay platforms. We have also carried out additional simulations to assess the use of circular bioassay platforms in a conventional kitchen microwave oven (e.g., 900 W). Our results show that the location of the circular bioassay platforms in the microwave cavity was predicted to have a significant effect on the homogeneous heating of these platforms. The 21-well circular bioassay platform design in our monomode microwave cavity was predicted to offer a homogeneous heating pattern, where inter-well temperature was observed to be in between 23.72-24.13°C and intra-well temperature difference was less than 0.21°C for 60 seconds of microwave heating, which was also verified experimentally.

  10. How Students Learn: Improving Teaching Techniques for Business Discipline Courses

    ERIC Educational Resources Information Center

    Cluskey, Bob; Elbeck, Matt; Hill, Kathy L.; Strupeck, Dave

    2011-01-01

    The focus of this paper is to familiarize business discipline faculty with cognitive psychology theories of how students learn together with teaching techniques to assist and improve student learning. Student learning can be defined as the outcome from the retrieval (free recall) of desired information. Student learning occurs in two processes.…

  11. Acceleration techniques for dependability simulation. M.S. Thesis

    NASA Technical Reports Server (NTRS)

    Barnette, James David

    1995-01-01

    As computer systems increase in complexity, the need to project system performance from the earliest design and development stages increases. We have to employ simulation for detailed dependability studies of large systems. However, as the complexity of the simulation model increases, the time required to obtain statistically significant results also increases. This paper discusses an approach that is application independent and can be readily applied to any process-based simulation model. Topics include background on classical discrete event simulation and techniques for random variate generation and statistics gathering to support simulation.

  12. Kalman filter techniques for accelerated Cartesian dynamic cardiac imaging.

    PubMed

    Feng, Xue; Salerno, Michael; Kramer, Christopher M; Meyer, Craig H

    2013-05-01

    In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome, and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and signal-to-noise ratio. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view-sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction.

  13. Advances in Climate Informatics: Accelerating Discovery in Climate Science with Machine Learning

    NASA Astrophysics Data System (ADS)

    Monteleoni, C.

    2015-12-01

    Despite the scientific consensus on climate change, drastic uncertainties remain. The climate system is characterized by complex phenomena that are imperfectly observed and even more imperfectly simulated. Climate data is Big Data, yet the magnitude of data and climate model output increasingly overwhelms the tools currently used to analyze them. Computational innovation is therefore needed. Machine learning is a cutting-edge research area at the intersection of computer science and statistics, focused on developing algorithms for big data analytics. Machine learning has revolutionized scientific discovery (e.g. Bioinformatics), and spawned new technologies (e.g. Web search). The impact of machine learning on climate science promises to be similarly profound. The goal of the novel interdisciplinary field of Climate Informatics is to accelerate discovery in climate science with machine learning, in order to shed light on urgent questions about climate change. In this talk, I will survey my research group's progress in the emerging field of climate informatics. Our work includes algorithms to improve the combined predictions of the IPCC multi-model ensemble, applications to seasonal and subseasonal prediction, and a data-driven technique to detect and define extreme events.

  14. Extraction of organochlorine pesticides in sediments using soxhlet, ultrasonic and accelerated solvent extraction techniques

    NASA Astrophysics Data System (ADS)

    Lang, Yinhai; Cao, Zhengmei; Nie, Xinhua

    2005-04-01

    The application of soxhlet, ultrasonic and accelerated solvent extraction techniques to the analysis of six organochlorine pesticides (α-HCH, β-HCH, γ-HCH, o, p‧-DDT, p, p‧-DDT and p, p‧-DDE) in Taihu Lake sediment samples is described. It was found that the limits of quantification ranged from 0.002 µgg-1 to 0.004 µgg-1, and the recoveries of organochlorine pesticides with the three extraction techniques were acceptable (>80.7%). With a mass selective detector, better results were obtained by accelerated solvent extraction using hexane-acetone (1:1) as compared with soxhlet and ultrasonic extraction. It was shown that the accelerated solvent extraction was the optimum technique for the analysis of organochlorine pesticides in sediments. The general features of the three extraction techniques are also presented.

  15. The LeRC rail accelerators: Test designs and diagnostic techniques

    NASA Technical Reports Server (NTRS)

    Zana, L. M.; Kerslake, W. R.; Sturman, J. C.; Wang, S. Y.; Terdan, F. F.

    1983-01-01

    The feasibility of using rail accelerators for various in-space and to-space propulsion applications was investigated. A 1 meter, 24 sq mm bore accelerator was designed with the goal of demonstrating projectile velocities of 15 km/sec using a peak current of 200 kA. A second rail accelerator, 1 meter long with a 156.25 sq mm bore, was designed with clear polycarbonate sidewalls to permit visual observation of the plasma arc. A study of available diagnostic techniques and their application to the rail accelerator is presented. Specific topics of discussion include the use of interferometry and spectroscopy to examine the plasma armature as well as the use of optical sensors to measure rail displacement during acceleration. Standard diagnostics such as current and voltage measurements are also discussed.

  16. Reinforcement learning output feedback NN control using deterministic learning technique.

    PubMed

    Xu, Bin; Yang, Chenguang; Shi, Zhongke

    2014-03-01

    In this brief, a novel adaptive-critic-based neural network (NN) controller is investigated for nonlinear pure-feedback systems. The controller design is based on the transformed predictor form, and the actor-critic NN control architecture includes two NNs, whereas the critic NN is used to approximate the strategic utility function, and the action NN is employed to minimize both the strategic utility function and the tracking error. A deterministic learning technique has been employed to guarantee that the partial persistent excitation condition of internal states is satisfied during tracking control to a periodic reference orbit. The uniformly ultimate boundedness of closed-loop signals is shown via Lyapunov stability analysis. Simulation results are presented to demonstrate the effectiveness of the proposed control.

  17. Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques

    ERIC Educational Resources Information Center

    Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili

    2009-01-01

    In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

  18. Cloud Computing and Validated Learning for Accelerating Innovation in IoT

    ERIC Educational Resources Information Center

    Suciu, George; Todoran, Gyorgy; Vulpe, Alexandru; Suciu, Victor; Bulca, Cristina; Cheveresan, Romulus

    2015-01-01

    Innovation in Internet of Things (IoT) requires more than just creation of technology and use of cloud computing or big data platforms. It requires accelerated commercialization or aptly called go-to-market processes. To successfully accelerate, companies need a new type of product development, the so-called validated learning process.…

  19. A Colloquial Approach: An Active Learning Technique.

    ERIC Educational Resources Information Center

    Arce, Pedro

    1994-01-01

    Addresses the problem of the effectiveness of teaching methodologies on fundamental engineering courses such as transport phenomena. Recommends the colloquial approach, an active learning strategy, to increase student involvement in the learning process. (ZWH)

  20. Challenges of Using Learning Analytics Techniques to Support Mobile Learning

    ERIC Educational Resources Information Center

    Arrigo, Marco; Fulantelli, Giovanni; Taibi, Davide

    2015-01-01

    Evaluation of Mobile Learning remains an open research issue, especially as regards the activities that take place outside the classroom. In this context, Learning Analytics can provide answers, and offer the appropriate tools to enhance Mobile Learning experiences. In this poster we introduce a task-interaction framework, using learning analytics…

  1. Incorporating Active Learning Techniques into a Genetics Class

    ERIC Educational Resources Information Center

    Lee, W. Theodore; Jabot, Michael E.

    2011-01-01

    We revised a sophomore-level genetics class to more actively engage the students in their learning. The students worked in groups on quizzes using the Immediate Feedback Assessment Technique (IF-AT) and active-learning projects. The IF-AT quizzes allowed students to discuss key concepts in small groups and learn the correct answers in class. The…

  2. Using Machine Learning to Accelerate Complex Atomic Structure Elucidation

    NASA Astrophysics Data System (ADS)

    Brouwer, William; Calderin, Lazaro; Sofo, Jorge

    2012-02-01

    Workers in various scientific disciplines seek to develop chemical models for extended and molecular systems. The modeling process revolves around the gradual refinement of model assumptions, through comparison of experimental and computational results. Solid state Nuclear Magnetic Resonance (NMR) is one such experimental technique, providing great insight into chemical order over Angstrom length scales. However, interpretation of spectra for complex materials is difficult, often requiring intensive simulations. Similarly, working forward from the model in order to produce experimental quantities via ab initio is computationally demanding. The work involved in these two significant steps, compounded by the need to iterate back and forth, drastically slows the discovery process for new materials. There is thus great motivation for the derivation of structural models directly from complex experimental data, the subject of this work. Using solid state NMR experimental datasets, in conjunction with ab initio calculations of measurable NMR parameters, a network of machine learning kernels are trained to rapidly yield structural details, on the basis of input NMR spectra. Results for an environmentally relevant material will be presented, and directions for future work.

  3. The evolution of tooling, techniques, and quality control for accelerator dipole magnet cables

    SciTech Connect

    Scanlan, R.M.

    1992-08-01

    The present generation of particle accelerators are utilizing the flattened, compacted, single layer cable design introduced nearly 20 years ago at Rutherford Laboratory. However, the requirements for current density, filament size, dimensional control long lengths, and low current degradation are much more stringent for the present accelerators compared with the earlier Tevatron and HERA accelerators. Also, in order to achieve higher field strengths with efficient use of superconductor, the new designs require wider cables with more strands. These requirements have stimulated an active research effort which has led to significant improvements in critical current density and conductor manufacturing. In addition they have stimulated the development of new cabling techniques, improved tooling, and better measurement techniques. The need to produce over 20 million meters of cable has led to the development of high speed cabling machines and on-line quality assurance measurements. These new developments will be discussed, and areas still requiring improvement will be identified.

  4. Apprenticeship Learning Techniques for Knowledge Based Systems

    DTIC Science & Technology

    1988-12-01

    domain, such as medicine. The Odysseus explanation-based learning program constructs explanations of problem-solving actions in the domain of medical...theories and empirical methods so as to allow construction of an explanation. The Odysseus learning program provides the first demonstration of using the... Odysseus explanation-based learning program is presfuted, which constructs explanations of human problem-solving actions in the domain of medical di

  5. Accelerated Learning in Adult Education and Training and Development. Trends and Issues Alert.

    ERIC Educational Resources Information Center

    Imel, Susan

    In adult education, the term "accelerated learning" (AL) is usually associated with programs designed to meet the needs of adult learners whose many commitments prevent them from participating in traditional programs. Within the field of training and development, however, AL identifies an approach to learning that is multidimensional in…

  6. Accelerate the Learning of 4th and 5th Graders Born into Poverty

    ERIC Educational Resources Information Center

    Pogrow, Stanley

    2009-01-01

    The special learning needs of students in grades 4-5 who are children of poverty have been misunderstood and therefore unaddressed. As a result, many students born into poverty start down a slippery slope of steady academic decline in grades 4 and 5. But specialized, counter-intuitive approaches. Specifically, accelerating the learning of these…

  7. Academic Learning Teams in Accelerated Adult Programs: Online and On-Campus Students' Perceptions

    ERIC Educational Resources Information Center

    Favor, Judy K.; Kulp, Amanda M.

    2015-01-01

    This article reports adult students' (N = 632) perceptions of long-functioning academic learning teams in accelerated online and on-campus business cohort groups in six constructs: attraction to team, performance expectation alignment, workload distribution, intra-team conflict, preference for teamwork, and impact on learning. Comparisons between…

  8. Detecting falls with wearable sensors using machine learning techniques.

    PubMed

    Özdemir, Ahmet Turan; Barshan, Billur

    2014-06-18

    Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects' body at six different positions. Each unit comprises three tri-axial devices (accelerometer, gyroscope, and magnetometer/compass). Fourteen volunteers perform a standardized set of movements including 20 voluntary falls and 16 activities of daily living (ADLs), resulting in a large dataset with 2520 trials. To reduce the computational complexity of training and testing the classifiers, we focus on the raw data for each sensor in a 4 s time window around the point of peak total acceleration of the waist sensor, and then perform feature extraction and reduction. Most earlier studies on fall detection employ rule-based approaches that rely on simple thresholding of the sensor outputs. We successfully distinguish falls from ADLs using six machine learning techniques (classifiers): the k-nearest neighbor (k-NN) classifier, least squares method (LSM), support vector machines (SVM), Bayesian decision making (BDM), dynamic time warping (DTW), and artificial neural networks (ANNs). We compare the performance and the computational complexity of the classifiers and achieve the best results with the k-NN classifier and LSM, with sensitivity, specificity, and accuracy all above 99%. These classifiers also have acceptable computational requirements for training and testing. Our approach would be applicable in real-world scenarios where data records of indeterminate length, containing multiple activities in sequence, are recorded.

  9. Detecting Falls with Wearable Sensors Using Machine Learning Techniques

    PubMed Central

    Özdemir, Ahmet Turan; Barshan, Billur

    2014-01-01

    Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects' body at six different positions. Each unit comprises three tri-axial devices (accelerometer, gyroscope, and magnetometer/compass). Fourteen volunteers perform a standardized set of movements including 20 voluntary falls and 16 activities of daily living (ADLs), resulting in a large dataset with 2520 trials. To reduce the computational complexity of training and testing the classifiers, we focus on the raw data for each sensor in a 4 s time window around the point of peak total acceleration of the waist sensor, and then perform feature extraction and reduction. Most earlier studies on fall detection employ rule-based approaches that rely on simple thresholding of the sensor outputs. We successfully distinguish falls from ADLs using six machine learning techniques (classifiers): the k-nearest neighbor (k-NN) classifier, least squares method (LSM), support vector machines (SVM), Bayesian decision making (BDM), dynamic time warping (DTW), and artificial neural networks (ANNs). We compare the performance and the computational complexity of the classifiers and achieve the best results with the k-NN classifier and LSM, with sensitivity, specificity, and accuracy all above 99%. These classifiers also have acceptable computational requirements for training and testing. Our approach would be applicable in real-world scenarios where data records of indeterminate length, containing multiple activities in sequence, are recorded. PMID:24945676

  10. Total-body irradiation on an isocentric linear accelerator: a radiation output compensation technique.

    PubMed

    Hugtenburg, R P; Turner, J R; Baggarley, S P; Pinchin, D A; Oien, N A; Atkinson, C H; Tremewan, R N

    1994-05-01

    A treatment technique for total-body irradiation (TBI) is proposed that combines arc therapy with dynamic output control to achieve high-grade dose uniformity. The patient lies on a low couch and receives exposure in the prone and supine positions from a modulated arcing beam. The technique has been validated using a personal computer to control the linear accelerator and we demonstrate that only minor alterations to current dynamic therapy systems would be required. We have examined the practical application of this treatment with emphasis on methods of conformal therapy where an optimized dose distribution is prepared from a matrix of caliper measurements taken from the patient. This technique provides a means for regular TBI treatment on a computer-controlled linear accelerator that is easy to set up, requires short exposure times and is comfortable for the patient.

  11. Machine Learning Techniques in Optimal Design

    NASA Technical Reports Server (NTRS)

    Cerbone, Giuseppe

    1992-01-01

    Many important applications can be formalized as constrained optimization tasks. For example, we are studying the engineering domain of two-dimensional (2-D) structural design. In this task, the goal is to design a structure of minimum weight that bears a set of loads. A solution to a design problem in which there is a single load (L) and two stationary support points (S1 and S2) consists of four members, E1, E2, E3, and E4 that connect the load to the support points is discussed. In principle, optimal solutions to problems of this kind can be found by numerical optimization techniques. However, in practice [Vanderplaats, 1984] these methods are slow and they can produce different local solutions whose quality (ratio to the global optimum) varies with the choice of starting points. Hence, their applicability to real-world problems is severely restricted. To overcome these limitations, we propose to augment numerical optimization by first performing a symbolic compilation stage to produce: (a) objective functions that are faster to evaluate and that depend less on the choice of the starting point and (b) selection rules that associate problem instances to a set of recommended solutions. These goals are accomplished by successive specializations of the problem class and of the associated objective functions. In the end, this process reduces the problem to a collection of independent functions that are fast to evaluate, that can be differentiated symbolically, and that represent smaller regions of the overall search space. However, the specialization process can produce a large number of sub-problems. This is overcome by deriving inductively selection rules which associate problems to small sets of specialized independent sub-problems. Each set of candidate solutions is chosen to minimize a cost function which expresses the tradeoff between the quality of the solution that can be obtained from the sub-problem and the time it takes to produce it. The overall solution

  12. Working Adults in Accelerated Cohorts: More than a Learning Community

    ERIC Educational Resources Information Center

    Spaid, Robin; Duff, Evan D.

    2009-01-01

    There are 54 million working adults in the United States without bachelor's degrees (Pusser et al., 2007). Many would like to obtain a college degree but need an educational program that fits their needs. A viable alternative to a traditional college program is an accelerated program in a cohort format. This article highlights best practices for…

  13. Application of real-time digitization techniques in beam measurement for accelerators

    NASA Astrophysics Data System (ADS)

    Zhao, Lei; Zhan, Lin-Song; Gao, Xing-Shun; Liu, Shu-Bin; An, Qi

    2016-04-01

    Beam measurement is very important for accelerators. In this paper, modern digital beam measurement techniques based on IQ (In-phase & Quadrature-phase) analysis are discussed. Based on this method and high-speed high-resolution analog-to-digital conversion, we have completed three beam measurement electronics systems designed for the China Spallation Neutron Source (CSNS), Shanghai Synchrotron Radiation Facility (SSRF), and Accelerator Driven Sub-critical system (ADS). Core techniques of hardware design and real-time system calibration are discussed, and performance test results of these three instruments are also presented. Supported by National Natural Science Foundation of China (11205153, 10875119), Knowledge Innovation Program of the Chinese Academy of Sciences (KJCX2-YW-N27), and the Fundamental Research Funds for the Central Universities (WK2030040029),and the CAS Center for Excellence in Particle Physics (CCEPP).

  14. Accelerated Schools as Learning Organizations: Cases from the University of New Orleans Accelerated School Network.

    ERIC Educational Resources Information Center

    Brunner, Ilse; And Others

    Organizations are the product of the ideas and interactions of those who work in them. The challenge for learning in organizations is to have a shared purpose and vision of the organization, to develop new ideas arising out of the vision and purpose, to test the ideas in the organizational reality, and to communicate that knowledge to other…

  15. Do Classroom Assessment Techniques (CATs) Improve Student Learning?

    ERIC Educational Resources Information Center

    Cottell, Philip; Harwood, Elaine

    1998-01-01

    In a study of effectiveness of classroom assessment techniques (CATs) on student learning, two college accounting teachers each taught two classes, one using CATs and one not using them. Course results did not suggest greater learning in CATs classes, better student participation, or more positive attitudes. Further research is recommended on the…

  16. Using the Four-Questions Technique to Enhance Learning

    ERIC Educational Resources Information Center

    Dietz-Uhler, Beth; Lanter, Jason R.

    2009-01-01

    To assess the effect of a 4-question reflective learning technique on quiz performance, students engaged in an interactive activity, responded to 4 questions to encourage analyzing (i.e., what was learned), reflecting (i.e., why it is important), relating (i.e., how the material related to their personal lives), and generating (i.e., what…

  17. Tunneling Activities Detection Using Machine Learning Techniques

    DTIC Science & Technology

    2010-11-01

    time is quite short. The implementation has been realized on a 3.06 Ghz PC platform running under a Debian distribution. The langage used is Java...therefore this computation time could be reduced using a faster langage such as C if needed. Phase Time Learning Phase 1143 ms Challenge Phase 223 µs Table

  18. Reefs and Learning: Education Evaluation Techniques

    ERIC Educational Resources Information Center

    Stepath, Carl M.

    2006-01-01

    Marine education research designs are discussed, and student learning outcomes while monitoring a coral reef is evaluated. Changes in environmental knowledge and attitudes, ecological intention to act, and direct reef experience were investigated. Differences between student pre-test and the post-test responses were observed, and analysis is…

  19. Solving radiative transfer problems in highly heterogeneous media via domain decomposition and convergence acceleration techniques.

    PubMed

    Previti, Alberto; Furfaro, Roberto; Picca, Paolo; Ganapol, Barry D; Mostacci, Domiziano

    2011-08-01

    This paper deals with finding accurate solutions for photon transport problems in highly heterogeneous media fastly, efficiently and with modest memory resources. We propose an extended version of the analytical discrete ordinates method, coupled with domain decomposition-derived algorithms and non-linear convergence acceleration techniques. Numerical performances are evaluated using a challenging case study available in the literature. A study of accuracy versus computational time and memory requirements is reported for transport calculations that are relevant for remote sensing applications.

  20. A technique for modeling the Earth's gravity field on the basis of satellite accelerations

    NASA Astrophysics Data System (ADS)

    Ditmar, P.; Sluijs, A. A. Van Eck Van Der

    2004-09-01

    A technique is proposed for Earth’s gravity field modeling on the basis of satellite accelerations that are derived from precise orbit data. The functional model rests on Newton’s second law. The computational procedure is based on the pre-conditioned conjugate-gradient (PCCG) method. The data are treated as weighted average accelerations rather than as point-wise ones. As a result, a simple three-point numerical differentiation scheme can be used to derive them. Noise in the orbit-derived accelerations is strongly dependent on frequency. Therefore, the key element of the proposed technique is frequency-dependent data weighting. Fast convergence of the PCCG procedure is ensured by a block-diagonal pre-conditioner (approximation of the normal matrix), which is derived under the so-called Colombo assumptions. Both uninterrupted data sets and data with gaps can be handled. The developed technique is compared with other approaches: (1) the energy balance approach (based on the energy conservation law) and (2) the traditional approach (based on the integration of variational equations). Theoretical considerations, supported by a numerical study, show that the proposed technique is more accurate than the energy balance approach and leads to approximately the same results as the traditional one. The former finding is explained by the fact that the energy balance approach is only sensitive to the along-track force component. Information about the cross-track and the radial component of the gravitational potential gradient is lost because the corresponding force components do no work and do not contribute to the energy balance. Furthermore, it is shown that the proposed technique is much (possibly, orders of magnitude) faster than the traditional one because it does not require the computation of the normal matrix. Hints are given on how the proposed technique can be adapted to the explicit assembling of the normal matrix if the latter is needed for the computation of

  1. Lenses for learning: visual techniques in natural resource management.

    PubMed

    Petheram, L; High, C; Campbell, B M; Stacey, N

    2011-10-01

    In this study, we explored the use of selected visual techniques (e.g. video, photography, diagramming) in facilitating learning among Indigenous communities living in remote protected areas at sites in Vietnam and Australia. The techniques were employed during interviews and workshops aimed at accessing and enhancing local peoples' perspectives on their landscape and on specific natural resource management issues. The effectiveness of the different techniques for enabling learning varied markedly with the context, highlighting the need for facilitator skill and flexibility in application of techniques. Visual techniques helped to engage participants; encourage unrestrained and lateral thinking; provide opportunities for self-expression and reflection; and to expose participants to perspectives of other community members. Valuable insights emerged on broad aspects of learning and these were incorporated into a simple model that highlights three types of conceptualisation found to be important in these processes.

  2. Using Music to Accelerate Language Learning: An Experimental Study

    ERIC Educational Resources Information Center

    Legg, Robert

    2009-01-01

    In recent years there has been considerable public interest in the extra-musical effects of music education, but this has been accompanied by sustained scholarly investigation only to some extent. Research findings have tentatively suggested, however, that a relationship exists between musical learning and language development. This empirical…

  3. The Effect of Blended Instruction on Accelerated Learning

    ERIC Educational Resources Information Center

    Patchan, Melissa M.; Schunn, Christian D.; Sieg, Wilfried; McLaughlin, Dawn

    2016-01-01

    While online instructional technologies are becoming more popular in higher education, educators' opinions about online learning tend to be generally negative. Furthermore, many studies have failed to systematically examine the features that distinguish one instructional mode from another, which weakens possible explanations for why online…

  4. Learned value and object perception: Accelerated perception or biased decisions?

    PubMed

    Rajsic, Jason; Perera, Harendri; Pratt, Jay

    2017-02-01

    Learned value is known to bias visual search toward valued stimuli. However, some uncertainty exists regarding the stage of visual processing that is modulated by learned value. Here, we directly tested the effect of learned value on preattentive processing using temporal order judgments. Across four experiments, we imbued some stimuli with high value and some with low value, using a nonmonetary reward task. In Experiment 1, we replicated the value-driven distraction effect, validating our nonmonetary reward task. Experiment 2 showed that high-value stimuli, but not low-value stimuli, exhibit a prior-entry effect. Experiment 3, which reversed the temporal order judgment task (i.e., reporting which stimulus came second), showed no prior-entry effect, indicating that although a response bias may be present for high-value stimuli, they are still reported as appearing earlier. However, Experiment 4, using a simultaneity judgment task, showed no shift in temporal perception. Overall, our results support the conclusion that learned value biases perceptual decisions about valued stimuli without speeding preattentive stimulus processing.

  5. Beyond Subprime Learning: Accelerating Progress in Early Education. Policy Brief

    ERIC Educational Resources Information Center

    Bornfreund, Laura; McCann, Clare; Williams, Conor; Guernsey, Lisa

    2014-01-01

    Earlier this year, in "Subprime Learning: Early Education in America since the Great Recession," the current state of early education in the U.S. was surveyed by examining progress over the last five years . It was found that while the public, political, and research consensus is stronger than ever, the field remains in dire need of…

  6. Predicting radiotherapy outcomes using statistical learning techniques

    NASA Astrophysics Data System (ADS)

    El Naqa, Issam; Bradley, Jeffrey D.; Lindsay, Patricia E.; Hope, Andrew J.; Deasy, Joseph O.

    2009-09-01

    Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model

  7. Force reconstruction using the sum of weighted accelerations technique -- Max-Flat procedure

    SciTech Connect

    Carne, T.G.; Mayes, R.L.; Bateman, V.I.

    1993-12-31

    Force reconstruction is a procedure in which the externally applied force is inferred from measured structural response rather than directly measured. In a recently developed technique, the response acceleration time-histories are multiplied by scalar weights and summed to produce the reconstructed force. This reconstruction is called the Sum of Weighted Accelerations Technique (SWAT). One step in the application of this technique is the calculation of the appropriate scalar weights. In this paper a new method of estimating the weights, using measured frequency response function data, is developed and contrasted with the traditional SWAT method of inverting the mode-shape matrix. The technique uses frequency response function data, but is not based on deconvolution. An application that will be discussed as part of this paper is the impact into a rigid barrier of a weapon system with an energy-absorbing nose. The nose had been designed to absorb the energy of impact and to mitigate the shock to the interior components.

  8. Exploring the Impacts of Accelerated Delivery on Student Learning, Achievement and Satisfaction

    ERIC Educational Resources Information Center

    Wilkins, Stephen; Martin, Susan; Walker, Ian

    2010-01-01

    This case study examines the impacts on student learning, achievement and satisfaction when year 13 (final year) students at a large UK sixth-form college take a GCE A level in one year instead of the usual two years. Data relating to the entry qualifications and final A level grades achieved by 879 students on both accelerated and non-accelerated…

  9. Learner-Responsive Instructional Strategies for Adults in Accelerated Classroom Formats: Creating Inclusive Learning Environments

    ERIC Educational Resources Information Center

    Gupta, Kalpana

    2012-01-01

    This study was focused on investigating inclusive learning environments in accelerated classroom formats. Three 8-week sections of an undergraduate course at Regis University were examined. Results from observations and surveys were analyzed to determine the effectiveness and consistency of 13 inclusive strategies derived from Wlodkowski and…

  10. Impact of Accelerated Learning Program (ALP) and Other Assistance, 1999-2000.

    ERIC Educational Resources Information Center

    Baenen, Nancy; Lloyd, Wanda

    The Accelerated Learning Program (ALP) was a major new initiative in the Wake County Public School System (WCPSS), North Carolina, in 2000. The ALP was designed to help WCPSS meet its achievement goal of 95% of students scoring at or above grade level at grades 3 and 8 by 2003, with grade levels determined by the North Carolina End of Grade tests.…

  11. Accelerated Learning Program (ALP): Grade 3-8 Evaluation, 2001-02.

    ERIC Educational Resources Information Center

    Baenen, Nancy; Yaman, Kimberly; Lindblad, Mark

    The Wake County Public Schools, North Carolina (WCPSS), initiated the Accelerated Learning Program (ALP) in 1999-2000 as the major new intervention to help all students reach grade-level performance in reading and mathematics. The ALP program was funded through local and state funds, and in 2001-220, 7,285 students received services through ALP.…

  12. The Accelerated Learning Program (ALP) 2000-01: Student Participation and Effectiveness. ALP Report.

    ERIC Educational Resources Information Center

    Baenen, Nancy; Yaman, Kimberly; Lindblad, Mark

    The Accelerated Learning Program (ALP) is the major initiative that the Wake County Public School System (WCPSS), North Carolina, is using to help all students reach grade level performance in reading and mathematics. This report focuses on student participation rates and the impact of the ALP program. Data are from a variety of sources. In the…

  13. Accelerating Teacher Effectiveness: Lessons Learned from Two Decades of New Teacher Induction

    ERIC Educational Resources Information Center

    Moir, Ellen

    2009-01-01

    This article describes 10 lessons learned from two decades of new teacher induction. These include: (1) A new teacher induction program requires a systemwide commitment to teacher development; (2) Induction programs accelerate new teacher effectiveness; (3) Standards-based formative assessment tools document impact; (4) Induction programs build a…

  14. Prompt nuclear analytical techniques for material research in accelerator driven transmutation technologies: Prospects and quantitative analyses

    NASA Astrophysics Data System (ADS)

    Vacík, J.; Hnatowicz, V.; Červená, J.; Peřina, V.; Mach, R.; Peka, I.

    1998-04-01

    Accelerator driven transmutation technology (ADTT) is a promissing way toward liquidation of spent nuclear fuel, nuclear wastes and weapon grade Pu. The ADTT facility comprises a high current (proton) accelerator supplying a subcritical reactor assembly with spallation neutrons. The reactor part is supposed to be cooled by molten fluorides or metals which serve, at the same time, as a carrier of nuclear fuel. Assumed high working temperature (400-600°C) and high radiation load in the subcritical reactor and spallation neutron source put forward the problem of optimal choice of ADTT construction materials, especially from the point of their radiation and corrosion resistance when in contact with liquid working media. The use of prompt nuclear analytical techniques in ADTT related material research is considered and examples of preliminary analytical results obtained using neutron depth profiling method are shown for illustration.

  15. Apprenticeship learning techniques for knowledge-based systems

    SciTech Connect

    Wilkins, D.C.

    1987-01-01

    This thesis describes apprenticeship learning techniques for automation of the transfer of expertise. Apprenticeship learning is a form of learning by watching, in which learning occurs as a byproduct of building explanations of human problem-solving actions. As apprenticeship is the most-powerful method that human experts use to refine and debug their expertise in knowledge-intensive domains such as medicine; this motivates giving such capabilities to an expert system. The major accomplishment in this thesis is showing how an explicit representation of the strategy knowledge to solve a general problem class, such as diagnosis, can provide a basis for learning the knowledge that is specific to a particular domain, such as medicine. The Odysseus learning program provides the first demonstration of using the same technique to transfer of expertise to and from an expert system knowledge base. Another major focus of this thesis is limitations of apprenticeship learning. It is shown that extant techniques for reasoning under uncertainty for expert systems lead to a sociopathic knowledge base.

  16. Predicting radiotherapy outcomes using statistical learning techniques.

    PubMed

    El Naqa, Issam; Bradley, Jeffrey D; Lindsay, Patricia E; Hope, Andrew J; Deasy, Joseph O

    2009-09-21

    Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model

  17. Accelerated Testing Methodology in Constant Stress-Rate Testing for Advanced Structural Ceramics: A Preloading Technique

    NASA Technical Reports Server (NTRS)

    Choi, Sung R.; Gyekenyesi, John P.; Huebert, Dean; Bartlett, Allen; Choi, Han-Ho

    2001-01-01

    Preloading technique was used as a means of an accelerated testing methodology in constant stress-rate ('dynamic fatigue') testing for two different brittle materials. The theory developed previously for fatigue strength as a function of preload was further verified through extensive constant stress-rate testing for glass-ceramic and CRT glass in room temperature distilled water. The preloading technique was also used in this study to identify the prevailing failure mechanisms at elevated temperatures, particularly at lower test rate in which a series of mechanisms would be associated simultaneously with material failure, resulting in significant strength increase or decrease. Two different advanced ceramics including SiC whisker-reinforced composite silicon nitride and 96 wt% alumina were used at elevated temperatures. It was found that the preloading technique can be used as an additional tool to pinpoint the dominant failure mechanism that is associated with such a phenomenon of considerable strength increase or decrease.

  18. Accelerated Testing Methodology in Constant Stress-Rate Testing for Advanced Structural Ceramics: A Preloading Technique

    NASA Technical Reports Server (NTRS)

    Choi, Sung R.; Gyekenyesi, John P.; Huebert, Dean; Bartlett, Allen; Choi, Han-Ho

    2001-01-01

    Preloading technique was used as a means of an accelerated testing methodology in constant stress-rate (dynamic fatigue) testing for two different brittle materials. The theory developed previously for fatigue strength as a function of preload was further verified through extensive constant stress-rate testing for glass-ceramic and CRT glass in room temperature distilled water. The preloading technique was also used in this study to identify the prevailing failure mechanisms at elevated temperatures, particularly at lower test rates in which a series of mechanisms would be associated simultaneously with material failure, resulting in significant strength increase or decrease. Two different advanced ceramics including SiC whisker-reinforced composite silicon nitride and 96 wt% alumina were used at elevated temperatures. It was found that the preloading technique can be used as an additional tool to pinpoint the dominant failure mechanism that is associated with such a phenomenon of considerable strength increase or decrease.

  19. Chronic stress impairs learning and hippocampal cell proliferation in senescence-accelerated prone mice.

    PubMed

    Yan, Weihong; Zhang, Ting; Jia, Weiping; Sun, Xiaojiang; Liu, Xueyuan

    2011-02-25

    Chronic stress can induce cognitive impairment. It is unclear whether a higher susceptibility to chronic stress is associated with the progression of pathological brain aging. Senescence-accelerated prone mouse 8 (SAMP8) is a naturally occurring animal model of accelerated brain aging. Senescence-accelerated resistant mouse 1 (SAMR1) is usually used as the normal control. In this study, we examined the effects of chronic restraint stress (CRS) on learning in the Y-maze, hippocampal cell proliferation, and the expression of brain-derived neurotrophic factor (BDNF) in the hippocampus of 4-month-old SAMP8 and SAMR1. The results showed that exposure to CRS impaired learning and hippocampal cell proliferation in SAMP8 and SAMR1 but to a much greater extent in SAMP8. Furthermore, CRS significantly decreased the expression of BDNF protein and mRNA in the hippocampus of SAMP8 and SAMR1. These data indicated that SAMP8 is more sensitive to the deleterious effects of CRS on learning than SAMR1. A greater decrease in hippocampal cell proliferation caused by chronic stress may be part of the underlying mechanism for the more severe learning deficit observed in SAMP8. In addition, our findings suggested a role of BDNF in the stress-induced impairment of learning and hippocampal cell proliferation in both strains.

  20. Comparison of Acceleration Techniques for Selected Low-Level Bioinformatics Operations

    PubMed Central

    Langenkämper, Daniel; Jakobi, Tobias; Feld, Dustin; Jelonek, Lukas; Goesmann, Alexander; Nattkemper, Tim W.

    2016-01-01

    Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly growing piles of raw data with increasing speed. The number of cores per processor increased in an attempt to compensate for slight increments of clock rates. This technological shift demands changes in software development, especially in the field of high performance computing where parallelization techniques are gaining in importance due to the pressing issue of large sized datasets generated by e.g., modern genomics. This paper presents an overview of state-of-the-art manual and automatic acceleration techniques and lists some applications employing these in different areas of sequence informatics. Furthermore, we provide examples for automatic acceleration of two use cases to show typical problems and gains of transforming a serial application to a parallel one. The paper should aid the reader in deciding for a certain techniques for the problem at hand. We compare four different state-of-the-art automatic acceleration approaches (OpenMP, PluTo-SICA, PPCG, and OpenACC). Their performance as well as their applicability for selected use cases is discussed. While optimizations targeting the CPU worked better in the complex k-mer use case, optimizers for Graphics Processing Units (GPUs) performed better in the matrix multiplication example. But performance is only superior at a certain problem size due to data migration overhead. We show that automatic code parallelization is feasible with current compiler software and yields significant increases in execution speed. Automatic optimizers for CPU are mature and usually no additional manual adjustment is required. In contrast, some automatic parallelizers targeting GPUs still lack maturity and are limited to simple statements and structures. PMID:26904094

  1. Comparison of Acceleration Techniques for Selected Low-Level Bioinformatics Operations.

    PubMed

    Langenkämper, Daniel; Jakobi, Tobias; Feld, Dustin; Jelonek, Lukas; Goesmann, Alexander; Nattkemper, Tim W

    2016-01-01

    Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly growing piles of raw data with increasing speed. The number of cores per processor increased in an attempt to compensate for slight increments of clock rates. This technological shift demands changes in software development, especially in the field of high performance computing where parallelization techniques are gaining in importance due to the pressing issue of large sized datasets generated by e.g., modern genomics. This paper presents an overview of state-of-the-art manual and automatic acceleration techniques and lists some applications employing these in different areas of sequence informatics. Furthermore, we provide examples for automatic acceleration of two use cases to show typical problems and gains of transforming a serial application to a parallel one. The paper should aid the reader in deciding for a certain techniques for the problem at hand. We compare four different state-of-the-art automatic acceleration approaches (OpenMP, PluTo-SICA, PPCG, and OpenACC). Their performance as well as their applicability for selected use cases is discussed. While optimizations targeting the CPU worked better in the complex k-mer use case, optimizers for Graphics Processing Units (GPUs) performed better in the matrix multiplication example. But performance is only superior at a certain problem size due to data migration overhead. We show that automatic code parallelization is feasible with current compiler software and yields significant increases in execution speed. Automatic optimizers for CPU are mature and usually no additional manual adjustment is required. In contrast, some automatic parallelizers targeting GPUs still lack maturity and are limited to simple statements and structures.

  2. [Dosimetric comparison of different techniques for external beam accelerated partial breast irradiation].

    PubMed

    Stelczer, Gábor; Major, Tibor; Mészáros, Norbert; Polgár, Csaba; Pesznyák, Csilla

    2016-11-29

    The aim of this article is to evaluate and compare four different radiotherapy techniques of accelerated partial breast irradiation (APBI) considering planning quality, dosimetric and practical aspects. The investigated techniques are three dimensional conformal radiotherapy (3D-CRT), "step and shoot" (SS) and "sliding window" (SW) intensity-modulated radiotherapy, intensity-modulated arc therapy (RA). CT scans of 10 patients previously treated with APBI were selected for the study. Surgical clips were placed on the borders of the tumour bed during breast conserving surgery. Target volume (PTV) was defined as enlarged CTV, which was created from the tumour bed through volume expansion using individual margins. Planning objectives were set up according to the international recommendations. Non-coplanar fields were used only for the 3D-CRT plans. For each plan homogeneity, conformity and plan quality indices were calculated from volumetric and dosimetric parameters of target volumes and organs at risk. The total monitor units and feasibility were also investigated. There was no significant difference in the coverage of the target volume by the prescribed dose between the techniques. SW plans were significantly more homogeneous (HI=0.033) than the 3D-CRT (HI=0.057) and the RA (HI=0.073) plans. The homogeneity of the SS technique (HI=0.053) did not differ significantly compared to others. The conformity of the 3D-CRT technique was significantly worse (CN=0.62) than that of SS (CN=0.85), SW (CN=0.85) and RA (CN=0.86) plans. There was a significant difference between RA (29.4%) and 3D-CRT (44.1%) and SW (35.6%) plans in the V50% of the ipsilateral breast. Mean V10% of the ipsilateral lung in 3D-CRT (10.1%) plans was significantly lower than in SS (34.3%), SW (34.3%) and RA (35.3%) plans. 3D-CRT technique provided the best heart protection. The shortest treatment times were achieved with RA technique. Good target volume coverage and tolerable dose to the organs at risk

  3. Accelerated Evaluation of Automated Vehicles Safety in Lane-Change Scenarios Based on Importance Sampling Techniques.

    PubMed

    Zhao, Ding; Lam, Henry; Peng, Huei; Bao, Shan; LeBlanc, David J; Nobukawa, Kazutoshi; Pan, Christopher S

    2016-08-05

    Automated vehicles (AVs) must be thoroughly evaluated before their release and deployment. A widely used evaluation approach is the Naturalistic-Field Operational Test (N-FOT), which tests prototype vehicles directly on the public roads. Due to the low exposure to safety-critical scenarios, N-FOTs are time consuming and expensive to conduct. In this paper, we propose an accelerated evaluation approach for AVs. The results can be used to generate motions of the other primary vehicles to accelerate the verification of AVs in simulations and controlled experiments. Frontal collision due to unsafe cut-ins is the target crash type of this paper. Human-controlled vehicles making unsafe lane changes are modeled as the primary disturbance to AVs based on data collected by the University of Michigan Safety Pilot Model Deployment Program. The cut-in scenarios are generated based on skewed statistics of collected human driver behaviors, which generate risky testing scenarios while preserving the statistical information so that the safety benefits of AVs in nonaccelerated cases can be accurately estimated. The cross-entropy method is used to recursively search for the optimal skewing parameters. The frequencies of the occurrences of conflicts, crashes, and injuries are estimated for a modeled AV, and the achieved accelerated rate is around 2000 to 20 000. In other words, in the accelerated simulations, driving for 1000 miles will expose the AV with challenging scenarios that will take about 2 to 20 million miles of real-world driving to encounter. This technique thus has the potential to greatly reduce the development and validation time for AVs.

  4. Accelerated Evaluation of Automated Vehicles Safety in Lane-Change Scenarios Based on Importance Sampling Techniques

    PubMed Central

    Zhao, Ding; Lam, Henry; Peng, Huei; Bao, Shan; LeBlanc, David J.; Nobukawa, Kazutoshi; Pan, Christopher S.

    2016-01-01

    Automated vehicles (AVs) must be thoroughly evaluated before their release and deployment. A widely used evaluation approach is the Naturalistic-Field Operational Test (N-FOT), which tests prototype vehicles directly on the public roads. Due to the low exposure to safety-critical scenarios, N-FOTs are time consuming and expensive to conduct. In this paper, we propose an accelerated evaluation approach for AVs. The results can be used to generate motions of the other primary vehicles to accelerate the verification of AVs in simulations and controlled experiments. Frontal collision due to unsafe cut-ins is the target crash type of this paper. Human-controlled vehicles making unsafe lane changes are modeled as the primary disturbance to AVs based on data collected by the University of Michigan Safety Pilot Model Deployment Program. The cut-in scenarios are generated based on skewed statistics of collected human driver behaviors, which generate risky testing scenarios while preserving the statistical information so that the safety benefits of AVs in nonaccelerated cases can be accurately estimated. The cross-entropy method is used to recursively search for the optimal skewing parameters. The frequencies of the occurrences of conflicts, crashes, and injuries are estimated for a modeled AV, and the achieved accelerated rate is around 2000 to 20 000. In other words, in the accelerated simulations, driving for 1000 miles will expose the AV with challenging scenarios that will take about 2 to 20 million miles of real-world driving to encounter. This technique thus has the potential to greatly reduce the development and validation time for AVs. PMID:27840592

  5. Microwave-accelerated bioassay technique for rapid and quantitative detection of biological and environmental samples.

    PubMed

    Mohammed, Muzaffer; Syed, Maleeha F; Aslan, Kadir

    2016-01-15

    Quantitative detection of molecules of interest from biological and environmental samples in a rapid manner, particularly with a relevant concentration range, is imperative to the timely assessment of human diseases and environmental issues. In this work, we employed the microwave-accelerated bioassay (MAB) technique, which is based on the combined use of circular bioassay platforms and microwave heating, for rapid and quantitative detection of Glial Fibrillary Acidic Protein (GFAP) and Shiga like toxin (STX 1). The proof-of-principle use of the MAB technique with the circular bioassay platforms for the rapid detection of GFAP in buffer based on colorimetric and fluorescence readouts was demonstrated with a 900W kitchen microwave. We also employed the MAB technique with a new microwave system (called the iCrystal system) for the detection of GFAP from mice with brain injuries and STX 1 from a city water stream. Control bioassays included the commercially available gold standard bioassay kits run at room temperature. Our results show that the lower limit of detection (LLOD) of the colorimetric and fluorescence based bioassays for GFAP was decreased by ~1000 times using the MAB technique and our circular bioassay platforms as compared to the commercially available bioassay kits. The overall bioassay time for GFAP and STX 1 was reduced from 4h using commercially available bioassay kits to 10min using the MAB technique.

  6. Microwave-Accelerated Bioassay Technique for Rapid and Quantitative Detection of Biological and Environmental Samples

    PubMed Central

    Mohammed, Muzaffer; Syed, Maleeha F.; Aslan, Kadir

    2015-01-01

    Quantitative detection of molecules of interest from biological and environmental samples in a rapid manner, particularly with a relevant concentration range, is imperative to the timely assessment of human diseases and environmental issues. In this work, we employed the microwave-accelerated bioassay (MAB) technique, which is based on the combined use of circular bioassay platforms and microwave heating, for rapid and quantitative detection of Glial Fibrillary Acidic Protein (GFAP) and Shiga like toxin (STX 1). The proof-of-principle use of the MAB technique with the circular bioassay platforms for the rapid detection of GFAP in buffer based on colorimetric and fluorescence readouts was demonstrated with a 900 W kitchen microwave. We also employed the MAB technique with a new microwave system (called the iCrystal system) for the detection of GFAP from mice with brain injuries and STX 1 from a city water stream. Control bioassays included the commercially available gold standard bioassay kits run at room temperature. Our results show that the lower limit of detection (LLOD) of the colorimetric and fluorescence based bioassays for GFAP was decreased by ~1,000 times using the MAB technique and our circular bioassay platforms as compared to the commercially available bioassay kits. The overall bioassay time for GFAP and STX 1 was reduced from 4 hours using commercially available bioassay kits to 10 minutes using the MAB technique. PMID:26356762

  7. Useful technique for analysis and control of the acceleration beam phase in the azimuthally varying field cyclotron

    NASA Astrophysics Data System (ADS)

    Kurashima, Satoshi; Yuyama, Takahiro; Miyawaki, Nobumasa; Kashiwagi, Hirotsugu; Okumura, Susumu; Fukuda, Mitsuhiro

    2010-03-01

    We have developed a new technique for analysis and control of the acceleration beam phase in the cyclotron. In this technique, the beam current pattern at a fixed radius r is measured by slightly scanning the acceleration frequency in the cyclotron. The acceleration beam phase is obtained by analyzing symmetry of the current pattern. Simple procedure to control the acceleration beam phase by changing coil currents of a few trim coils was established. The beam phase width is also obtained by analyzing gradient of the decreasing part of the current pattern. We verified reliability of this technique with 260 MeV N20e7+ beams which were accelerated on different tuning condition of the cyclotron. When the acceleration beam phase was around 0°, top of the energy gain of cosine wave, and the beam phase width was about 6° in full width at half maximum, a clear turn pattern of the beam was observed with a differential beam probe in the extraction region. Beam phase widths of ion beams at acceleration harmonics of h =1 and h =2 were estimated without beam cutting by phase-defining slits. We also calculated the beam phase widths roughly from the beam current ratio between the injected beam and the accelerated beam in the cyclotron without operating the beam buncher. Both beam phase widths were almost the same for h =1, while phase compressions by a factor of about 3 were confirmed for h =2.

  8. Useful technique for analysis and control of the acceleration beam phase in the azimuthally varying field cyclotron

    SciTech Connect

    Kurashima, Satoshi; Yuyama, Takahiro; Miyawaki, Nobumasa; Kashiwagi, Hirotsugu; Okumura, Susumu; Fukuda, Mitsuhiro

    2010-03-15

    We have developed a new technique for analysis and control of the acceleration beam phase in the cyclotron. In this technique, the beam current pattern at a fixed radius r is measured by slightly scanning the acceleration frequency in the cyclotron. The acceleration beam phase is obtained by analyzing symmetry of the current pattern. Simple procedure to control the acceleration beam phase by changing coil currents of a few trim coils was established. The beam phase width is also obtained by analyzing gradient of the decreasing part of the current pattern. We verified reliability of this technique with 260 MeV {sup 20}Ne{sup 7+} beams which were accelerated on different tuning condition of the cyclotron. When the acceleration beam phase was around 0 deg., top of the energy gain of cosine wave, and the beam phase width was about 6 deg. in full width at half maximum, a clear turn pattern of the beam was observed with a differential beam probe in the extraction region. Beam phase widths of ion beams at acceleration harmonics of h=1 and h=2 were estimated without beam cutting by phase-defining slits. We also calculated the beam phase widths roughly from the beam current ratio between the injected beam and the accelerated beam in the cyclotron without operating the beam buncher. Both beam phase widths were almost the same for h=1, while phase compressions by a factor of about 3 were confirmed for h=2.

  9. Note: Matching index technique for avoiding higher order mode resonance in accelerators: INDUS-2 accelerator as a case study

    SciTech Connect

    Jain, V.; Joshi, S. C.; Bhandarkar, U. V.; Krishnagopal, S.

    2013-08-15

    Resonance between circulating beam frequencies and RF cavity Higher Order Modes (HOMs) of accelerators can lead to coupled-bunch instabilities. Shifting these HOMs to avoid the resonance is a topic of active interest. A study has been carried out for the accelerating cavities of the INDUS-2. For quantitative measure of deciding which modes have to be moved and by how much, we introduce a new index called the matching index (I{sub M}), as a measure of how close a HOM is to the nearest beam mode. Depending on the value of I{sub M}, the operating scenarios are classified as safe and unsafe.

  10. Assessing Performance through Informal Techniques. Learning Package No. 10.

    ERIC Educational Resources Information Center

    Nelson, Carol; Smith, Carl, Comp.

    Originally developed for the Department of Defense Schools (DoDDS) system, this learning package on assessing performance through informal techniques is designed for teachers who wish to upgrade or expand their teaching skills on their own. The package includes a comprehensive search of the ERIC database; a lecture giving an overview on the topic;…

  11. Alternative Service Learning Approaches: Two Techniques that Accommodate Faculty Schedules

    ERIC Educational Resources Information Center

    Heckert, Teresa M.

    2010-01-01

    A primary barrier to the usage of the well-documented pedagogical technique of service learning is time. Successful experiences require faculty to devote significant time to facilitating the community partnership. Another challenge is student readiness for experiences, both in terms of knowledge and motivation. In this article, 2 adaptations are…

  12. Generating a Spanish Affective Dictionary with Supervised Learning Techniques

    ERIC Educational Resources Information Center

    Bermudez-Gonzalez, Daniel; Miranda-Jiménez, Sabino; García-Moreno, Raúl-Ulises; Calderón-Nepamuceno, Dora

    2016-01-01

    Nowadays, machine learning techniques are being used in several Natural Language Processing (NLP) tasks such as Opinion Mining (OM). OM is used to analyse and determine the affective orientation of texts. Usually, OM approaches use affective dictionaries in order to conduct sentiment analysis. These lexicons are labeled manually with affective…

  13. Enhancing Self-Regulated Learning: A Comparison of Instructional Techniques.

    ERIC Educational Resources Information Center

    Travers, Nan L.; Sheckley, Barry G.; Bell, Alexandra A.

    2003-01-01

    Community colleges students (n=24) taught math by instructors trained in self-regulated learning were compared with 54 taught conventionally. Mean scores did not differ but self-regulation techniques strengthened the relations among feedback seeking, self-regulation standard, internal calibration, perceiving choice, and effective learning…

  14. Programmed Learning--Is It an Effective Technique in Teaching?

    ERIC Educational Resources Information Center

    Reddy, N. Y.

    1976-01-01

    In a continuation of a previously published article, this paper presents the results of a study comparing programmed learning techniques with traditional methods of teaching the Telugu language to Hindi sixth grade students. Some advantages of programmed instruction are reported. (LBH)

  15. Use of the Dichotic Listening Technique with Learning Disabilities

    ERIC Educational Resources Information Center

    Obrzut, John E.; Mahoney, Emery B.

    2011-01-01

    Dichotic listening (DL) techniques have been used extensively as a non-invasive procedure to assess language lateralization among children with and without learning disabilities (LD), and with individuals who have other auditory system related brain disorders. Results of studies using DL have indicated that language is lateralized in children with…

  16. Applying machine learning techniques to DNA sequence analysis

    SciTech Connect

    Shavlik, J.W.

    1992-01-01

    We are developing a machine learning system that modifies existing knowledge about specific types of biological sequences. It does this by considering sample members and nonmembers of the sequence motif being learned. Using this information (which we call a domain theory''), our learning algorithm produces a more accurate representation of the knowledge needed to categorize future sequences. Specifically, the KBANN algorithm maps inference rules, such as consensus sequences, into a neural (connectionist) network. Neural network training techniques then use the training examples of refine these inference rules. We have been applying this approach to several problems in DNA sequence analysis and have also been extending the capabilities of our learning system along several dimensions.

  17. Rapid learning-based video stereolization using graphic processing unit acceleration

    NASA Astrophysics Data System (ADS)

    Sun, Tian; Jung, Cheolkon; Wang, Lei; Kim, Joongkyu

    2016-09-01

    Video stereolization has received much attention in recent years due to the lack of stereoscopic three-dimensional (3-D) contents. Although video stereolization can enrich stereoscopic 3-D contents, it is hard to achieve automatic two-dimensional-to-3-D conversion with less computational cost. We proposed rapid learning-based video stereolization using a graphic processing unit (GPU) acceleration. We first generated an initial depth map based on learning from examples. Then, we refined the depth map using saliency and cross-bilateral filtering to make object boundaries clear. Finally, we performed depth-image-based-rendering to generate stereoscopic 3-D views. To accelerate the computation of video stereolization, we provided a parallelizable hybrid GPU-central processing unit (CPU) solution to be suitable for running on GPU. Experimental results demonstrate that the proposed method is nearly 180 times faster than CPU-based processing and achieves a good performance comparable to the-state-of-the-art ones.

  18. Does vocal learning accelerate acoustic diversification? Evolution of contact calls in Neotropical parrots.

    PubMed

    Medina-García, A; Araya-Salas, M; Wright, T F

    2015-10-01

    Learning has been traditionally thought to accelerate the evolutionary change of behavioural traits. We evaluated the evolutionary rate of learned vocalizations and the interplay of morphology and ecology in the evolution of these signals. We examined contact calls of 51 species of Neotropical parrots from the tribe Arini. Parrots are ideal subjects due to their wide range of body sizes and habitats, and their open-ended vocal learning that allows them to modify their calls throughout life. We estimated the evolutionary rate of acoustic parameters of parrot contact calls and compared them to those of morphological traits and habitat. We also evaluated the effect of body mass, bill length, vegetation density and species interactions on acoustic parameters of contact calls while controlling for phylogeny. Evolutionary rates of acoustic parameters did not differ from those of our predictor variables except for spectral entropy, which had a significantly slower rate of evolution. We found support for correlated evolution of call duration, and fundamental and peak frequencies with body mass, and of fundamental frequency with bill length. The degree of sympatry between species did not have a significant effect on acoustic parameters. Our results suggest that parrot contact calls, which are learned acoustic signals, show evolutionary rates similar to those of morphological traits. This is the first study to our knowledge to provide evidence that change through cultural evolution does not necessarily accelerate the evolutionary rate of traits acquired through life-long vocal learning.

  19. Computer-aided auscultation learning system for nursing technique instruction.

    PubMed

    Hou, Chun-Ju; Chen, Yen-Ting; Hu, Ling-Chen; Chuang, Chih-Chieh; Chiu, Yu-Hsien; Tsai, Ming-Shih

    2008-01-01

    Pulmonary auscultation is a physical assessment skill learned by nursing students for examining the respiratory system. Generally, a sound simulator equipped mannequin is used to group teach auscultation techniques via classroom demonstration. However, nursing students cannot readily duplicate this learning environment for self-study. The advancement of electronic and digital signal processing technologies facilitates simulating this learning environment. This study aims to develop a computer-aided auscultation learning system for assisting teachers and nursing students in auscultation teaching and learning. This system provides teachers with signal recording and processing of lung sounds and immediate playback of lung sounds for students. A graphical user interface allows teachers to control the measuring device, draw lung sound waveforms, highlight lung sound segments of interest, and include descriptive text. Effects on learning lung sound auscultation were evaluated for verifying the feasibility of the system. Fifteen nursing students voluntarily participated in the repeated experiment. The results of a paired t test showed that auscultative abilities of the students were significantly improved by using the computer-aided auscultation learning system.

  20. DeepX: Deep Learning Accelerator for Restricted Boltzmann Machine Artificial Neural Networks.

    PubMed

    Kim, Lok-Won

    2017-03-08

    Although there have been many decades of research and commercial presence on high performance general purpose processors, there are still many applications that require fully customized hardware architectures for further computational acceleration. Recently, deep learning has been successfully used to learn in a wide variety of applications, but their heavy computation demand has considerably limited their practical applications. This paper proposes a fully pipelined acceleration architecture to alleviate high computational demand of an artificial neural network (ANN) which is restricted Boltzmann machine (RBM) ANNs. The implemented RBM ANN accelerator (integrating 1024 x 1024 network size, using 128 input cases per batch, and running at a 303-MHz clock frequency) integrated in a state-of-the art field-programmable gate array (FPGA) (Xilinx Virtex 7 XC7V-2000T) provides a computational performance of 301-billion connection-updates-per-second and about 193 times higher performance than a software solution running on general purpose processors. Most importantly, the architecture enables over 4 times (12 times in batch learning) higher performance compared with a previous work when both are implemented in an FPGA device (XC2VP70).

  1. Acceleration of FDTD mode solver by high-performance computing techniques.

    PubMed

    Han, Lin; Xi, Yanping; Huang, Wei-Ping

    2010-06-21

    A two-dimensional (2D) compact finite-difference time-domain (FDTD) mode solver is developed based on wave equation formalism in combination with the matrix pencil method (MPM). The method is validated for calculation of both real guided and complex leaky modes of typical optical waveguides against the bench-mark finite-difference (FD) eigen mode solver. By taking advantage of the inherent parallel nature of the FDTD algorithm, the mode solver is implemented on graphics processing units (GPUs) using the compute unified device architecture (CUDA). It is demonstrated that the high-performance computing technique leads to significant acceleration of the FDTD mode solver with more than 30 times improvement in computational efficiency in comparison with the conventional FDTD mode solver running on CPU of a standard desktop computer. The computational efficiency of the accelerated FDTD method is in the same order of magnitude of the standard finite-difference eigen mode solver and yet require much less memory (e.g., less than 10%). Therefore, the new method may serve as an efficient, accurate and robust tool for mode calculation of optical waveguides even when the conventional eigen value mode solvers are no longer applicable due to memory limitation.

  2. Acceleration and motion-correction techniques for high-resolution intravascular MRI

    PubMed Central

    Hegde, Shashank Sathyanarayana; Zhang, Yi; Bottomley, Paul A.

    2014-01-01

    Purpose High-resolution intravascular (IV) MRI is susceptible to degradation from physiological motion and requires high frame-rates for true endoscopy. Traditional cardiac-gating techniques compromise efficiency by reducing the effective scan rate. Here we test whether compressed sensing (CS) reconstruction and ungated motion-compensation employing projection shifting, could provide faster motion-suppressed, IVMRI. Theory and Methods CS reconstruction is developed for under-sampled Cartesian and radial imaging using a new IVMRI-specific cost function to effectively increase imaging speed. A new motion correction method is presented wherein individual IVMRI projections are shifted based on the IVMRI detector's intrinsic amplitude and phase properties. The methods are tested at 3T in fruit, human vessel specimens, and a rabbit aorta in vivo. Images are compared using Structural-Similarity and ‘Spokal-Variation’ indices. Results Although some residual artifacts persisted, CS acceleration and radial motion compensation strategies reduced motion artefact in vitro and in vivo, allowing effective accelerations of up to eightfold at 200-300μm resolution. Conclusion 3T IVMRI detectors are well-suited to CS and motion correction strategies based on their intrinsic radially-sparse sensitivity profiles and high signal-to-noise ratios. While benefits of faster free-breathing high-resolution IVMRI and reduced motion sensitivity are realized, there are costs to spatial resolution, and some motion artifacts may persist. PMID:25163750

  3. Improvements of the boundary projection acceleration technique applied to the discrete-ordinates transport solver in XYZ geometries

    SciTech Connect

    Masiello, E.; Rossi, T.

    2013-07-01

    In this paper we discuss the latest upgrades of the Boundary Projection Acceleration (BPA) applied to the XYZ transport solver of APOLLO3, namely IDT. The acceleration method is a well-known effective technique for the speed-up of the source iterations of the discrete-ordinates method. The BPA in IDT has been improved in three aspects: the taking into account of the residue on boundary conditions as a boundary source for the acceleration problem, the extension of the method to higher order angular moments in the case of anisotropic scattering and, finally, the application of the method to the multigroup iterations for the acceleration of the fission source and k-effective. The spectrum of the method has been Fourier-analyzed to explore the effectiveness. The 3D mock-up geometry of the ZPPR is presented as final study to test the performances of the acceleration on a realistic whole-core 3D calculation. (authors)

  4. A Model for Accelerating Academic Success of Community College Remedial English Students: Is the Accelerated Learning Program (ALP) Effective and Affordable? CCRC Working Paper No. 21

    ERIC Educational Resources Information Center

    Jenkins, Davis; Speroni, Cecilia; Belfield, Clive; Jaggars, Shanna Smith; Edgecombe, Nikki

    2010-01-01

    This paper presents the findings from a quantitative analysis of the Community College of Baltimore County's Accelerated Learning Program (ALP). Under ALP, students placed into upper-level developmental writing are "mainstreamed" into English 101 classes and simultaneously enrolled in a companion ALP course (taught by the same…

  5. The Open Learning Initiative: Measuring the Effectiveness of the OLI Statistics Course in Accelerating Student Learning

    ERIC Educational Resources Information Center

    Lovett, Marsha; Meyer, Oded; Thille, Candace

    2008-01-01

    The Open Learning Initiative (OLI) is an open educational resources project at Carnegie Mellon University that began in 2002 with a grant from The William and Flora Hewlett Foundation. OLI creates web-based courses that are designed so that students can learn effectively without an instructor. In addition, the courses are often used by instructors…

  6. A Method of Social Collaboration and Knowledge Sharing Acceleration for e-Learning System: The Distance Learning Network Scenario

    NASA Astrophysics Data System (ADS)

    Różewski, Przemysław

    Nowadays, e-learning systems take the form of the Distance Learning Network (DLN) due to widespread use and accessibility of the Internet and networked e-learning services. The focal point of the DLN performance is efficiency of knowledge processing in asynchronous learning mode and facilitating cooperation between students. In addition, the DLN articulates attention to social aspects of the learning process as well. In this paper, a method for the DLN development is proposed. The main research objectives for the proposed method are the processes of acceleration of social collaboration and knowledge sharing in the DLN. The method introduces knowledge-disposed agents (who represent students in educational scenarios) that form a network of individuals aimed to increase their competence. For every agent the competence expansion process is formulated. Based on that outcome the process of dynamic network formation performed on the social and knowledge levels. The method utilizes formal apparatuses of competence set and network game theories combined with an agent system-based approach.

  7. Use of delayed addition techniques to accelerate integer and floating-point calculations in configurable hardware

    NASA Astrophysics Data System (ADS)

    Luo, Zhen; Martonosi, Margaret

    1998-10-01

    This paper proposes and evaluates an approach for improving the performance of arithmetic calculations via delayed addition. Our approach employs the idea used in Wallace trees to delay addition until the end of a repeated calculation such as accumulation or dot-product; this effectively removes carry propagation overhead from the calculation's critical path. We present imager and floating- point designs that use this technique. Our pipelined integer multiply-accumulate design is based on a fairly traditional multiplier design, but with delayed addition as well. This design achieves a 37 MHz clock rate on an XC4036XL-2 FPGA. Next, we present a 32-bit floating-point accumulator based on delayed addition. Here delayed addition requires a novel alignment technique that decouples the incoming operands from the accumulated result. A conservative version of this design achieves a 33 MHz clock rate. Finally, we also present a more aggressive 32-bit floating-point accumulator design that achieves a 66 MHz clock rate. These designs demonstrate the utility of delayed addition for accelerating FPGA calculations in both the integer and floating-point domains.

  8. Visualization of TlBr ionic transport mechanism by the Accelerated Device Degradation technique

    NASA Astrophysics Data System (ADS)

    Datta, Amlan; Becla, Piotr; Motakef, Shariar

    2015-06-01

    Thallium Bromide (TlBr) is a promising gamma radiation semiconductor detector material. However, it is an ionic semiconductor and suffers from polarization. As a result, TlBr devices degrade rapidly at room temperature. Polarization is associated with the flow of ionic current in the crystal under electrical bias, leading to the accumulation of charged ions at the device's electrical contacts. We report a fast and reliable direct characterization technique to identify the effects of various growth and post-growth process modifications on the polarization process. The Accelerated Device Degradation (ADD) characterization technique allows direct observation of nucleation and propagation of ionic transport channels within the TlBr crystals under applied bias. These channels are observed to be initiated both directly under the electrode as well as away from it. The propagation direction is always towards the anode indicating that Br- is the mobile diffusing species within the defect channels. The effective migration energy of the Br- ions was calculated to be 0.33±0.03 eV, which is consistent with other theoretical and experimental results.

  9. Improving Students' Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology.

    PubMed

    Dunlosky, John; Rawson, Katherine A; Marsh, Elizabeth J; Nathan, Mitchell J; Willingham, Daniel T

    2013-01-01

    Many students are being left behind by an educational system that some people believe is in crisis. Improving educational outcomes will require efforts on many fronts, but a central premise of this monograph is that one part of a solution involves helping students to better regulate their learning through the use of effective learning techniques. Fortunately, cognitive and educational psychologists have been developing and evaluating easy-to-use learning techniques that could help students achieve their learning goals. In this monograph, we discuss 10 learning techniques in detail and offer recommendations about their relative utility. We selected techniques that were expected to be relatively easy to use and hence could be adopted by many students. Also, some techniques (e.g., highlighting and rereading) were selected because students report relying heavily on them, which makes it especially important to examine how well they work. The techniques include elaborative interrogation, self-explanation, summarization, highlighting (or underlining), the keyword mnemonic, imagery use for text learning, rereading, practice testing, distributed practice, and interleaved practice. To offer recommendations about the relative utility of these techniques, we evaluated whether their benefits generalize across four categories of variables: learning conditions, student characteristics, materials, and criterion tasks. Learning conditions include aspects of the learning environment in which the technique is implemented, such as whether a student studies alone or with a group. Student characteristics include variables such as age, ability, and level of prior knowledge. Materials vary from simple concepts to mathematical problems to complicated science texts. Criterion tasks include different outcome measures that are relevant to student achievement, such as those tapping memory, problem solving, and comprehension. We attempted to provide thorough reviews for each technique, so this

  10. Imputation of missing data using machine learning techniques

    SciTech Connect

    Lakshminarayan, Kamakshi; Harp, S.A.; Goldman, R.; Samad, T.

    1996-12-31

    A serious problem in mining industrial data bases is that they are often incomplete, and a significant amount of data is missing, or erroneously entered. This paper explores the use of machine-learning based alternatives to standard statistical data completion (data imputation) methods, for dealing with missing data. We have approached the data completion problem using two well-known machine learning techniques. The first is an unsupervised clustering strategy which uses a Bayesian approach to cluster the data into classes. The classes so obtained are then used to predict multiple choices for the attribute of interest. The second technique involves modeling missing variables by supervised induction of a decision tree-based classifier. This predicts the most likely value for the attribute of interest. Empirical tests using extracts from industrial databases maintained by Honeywell customers have been done in order to compare the two techniques. These tests show both approaches are useful and have advantages and disadvantages. We argue that the choice between unsupervised and supervised classification techniques should be influenced by the motivation for solving the missing data problem, and discuss potential applications for the procedures we are developing.

  11. Using machine learning techniques to automate sky survey catalog generation

    NASA Technical Reports Server (NTRS)

    Fayyad, Usama M.; Roden, J. C.; Doyle, R. J.; Weir, Nicholas; Djorgovski, S. G.

    1993-01-01

    We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomar Observatory Sky Survey provides comprehensive photographic coverage of the northern celestial hemisphere. The photographic plates are being digitized into images containing on the order of 10(exp 7) galaxies and 10(exp 8) stars. Since the size of this data set precludes manual analysis and classification of objects, our approach is to develop a software system which integrates independently developed techniques for image processing and data classification. Image processing routines are applied to identify and measure features of sky objects. Selected features are used to determine the classification of each object. GID3* and O-BTree, two inductive learning techniques, are used to automatically learn classification decision trees from examples. We describe the techniques used, the details of our specific application, and the initial encouraging results which indicate that our approach is well-suited to the problem. The benefits of the approach are increased data reduction throughput, consistency of classification, and the automated derivation of classification rules that will form an objective, examinable basis for classifying sky objects. Furthermore, astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems given automatically cataloged data.

  12. Staff Meetings: An Opportunity for Accelerated Training of Employees.

    ERIC Educational Resources Information Center

    Pattison, Sherry A.

    2001-01-01

    Accelerated learning techniques for training incorporated into staff meetings were designed to address different learning styles and modalities. The use of experiential games and multisensory whole-brain approaches was engaging and motivating. (Contains 25 references.) (SK)

  13. Application of Active Learning Techniques to an Advanced Course

    NASA Astrophysics Data System (ADS)

    Knop, R. A.

    2004-05-01

    The New Faculty Workshop provided a wealth of techniques as well as an overriding philosophy for the teaching of undergraduate Physics and Astronomy courses. The focus of the workshop was active learning, summarized in ``Learner-Centered Astronomy Teaching" by Slater & Adams: it's not what you do in class that matters, it's what the students do. Much of the specific focus of the New Faculty Workshop is on teaching the large, introductory Physics classes that many of the faculty present are sure to teach, both algebra-based and calculus-based. Many of these techniques apply directly and with little modification to introductory Astronomy courses. However, little direct attention is given to upper-division undergraduate, or even graduate, courses. In this presentation, I will share my experience in attempting to apply some of the techniques discussed at the New Faculty Workshop to an upper-division course in Galactic Astrophysics at Vanderbilt University during the Spring semester of 2004.

  14. Applying perceptual and adaptive learning techniques for teaching introductory histopathology

    PubMed Central

    Krasne, Sally; Hillman, Joseph D.; Kellman, Philip J.; Drake, Thomas A.

    2013-01-01

    Background: Medical students are expected to master the ability to interpret histopathologic images, a difficult and time-consuming process. A major problem is the issue of transferring information learned from one example of a particular pathology to a new example. Recent advances in cognitive science have identified new approaches to address this problem. Methods: We adapted a new approach for enhancing pattern recognition of basic pathologic processes in skin histopathology images that utilizes perceptual learning techniques, allowing learners to see relevant structure in novel cases along with adaptive learning algorithms that space and sequence different categories (e.g. diagnoses) that appear during a learning session based on each learner's accuracy and response time (RT). We developed a perceptual and adaptive learning module (PALM) that utilized 261 unique images of cell injury, inflammation, neoplasia, or normal histology at low and high magnification. Accuracy and RT were tracked and integrated into a “Score” that reflected students rapid recognition of the pathologies and pre- and post-tests were given to assess the effectiveness. Results: Accuracy, RT and Scores significantly improved from the pre- to post-test with Scores showing much greater improvement than accuracy alone. Delayed post-tests with previously unseen cases, given after 6-7 weeks, showed a decline in accuracy relative to the post-test for 1st-year students, but not significantly so for 2nd-year students. However, the delayed post-test scores maintained a significant and large improvement relative to those of the pre-test for both 1st and 2nd year students suggesting good retention of pattern recognition. Student evaluations were very favorable. Conclusion: A web-based learning module based on the principles of cognitive science showed an evidence for improved recognition of histopathology patterns by medical students. PMID:24524000

  15. The Development of Teaching and Learning in Bright-Field Microscopy Technique

    ERIC Educational Resources Information Center

    Iskandar, Yulita Hanum P.; Mahmud, Nurul Ethika; Wahab, Wan Nor Amilah Wan Abdul; Jamil, Noor Izani Noor; Basir, Nurlida

    2013-01-01

    E-learning should be pedagogically-driven rather than technologically-driven. The objectives of this study are to develop an interactive learning system in bright-field microscopy technique in order to support students' achievement of their intended learning outcomes. An interactive learning system on bright-field microscopy technique was…

  16. Closing the gap: accelerating the translational process in nanomedicine by proposing standardized characterization techniques.

    PubMed

    Khorasani, Ali A; Weaver, James L; Salvador-Morales, Carolina

    2014-01-01

    On the cusp of widespread permeation of nanomedicine, academia, industry, and government have invested substantial financial resources in developing new ways to better treat diseases. Materials have unique physical and chemical properties at the nanoscale compared with their bulk or small-molecule analogs. These unique properties have been greatly advantageous in providing innovative solutions for medical treatments at the bench level. However, nanomedicine research has not yet fully permeated the clinical setting because of several limitations. Among these limitations are the lack of universal standards for characterizing nanomaterials and the limited knowledge that we possess regarding the interactions between nanomaterials and biological entities such as proteins. In this review, we report on recent developments in the characterization of nanomaterials as well as the newest information about the interactions between nanomaterials and proteins in the human body. We propose a standard set of techniques for universal characterization of nanomaterials. We also address relevant regulatory issues involved in the translational process for the development of drug molecules and drug delivery systems. Adherence and refinement of a universal standard in nanomaterial characterization as well as the acquisition of a deeper understanding of nanomaterials and proteins will likely accelerate the use of nanomedicine in common practice to a great extent.

  17. Closing the gap: accelerating the translational process in nanomedicine by proposing standardized characterization techniques

    PubMed Central

    Khorasani, Ali A; Weaver, James L; Salvador-Morales, Carolina

    2014-01-01

    On the cusp of widespread permeation of nanomedicine, academia, industry, and government have invested substantial financial resources in developing new ways to better treat diseases. Materials have unique physical and chemical properties at the nanoscale compared with their bulk or small-molecule analogs. These unique properties have been greatly advantageous in providing innovative solutions for medical treatments at the bench level. However, nanomedicine research has not yet fully permeated the clinical setting because of several limitations. Among these limitations are the lack of universal standards for characterizing nanomaterials and the limited knowledge that we possess regarding the interactions between nanomaterials and biological entities such as proteins. In this review, we report on recent developments in the characterization of nanomaterials as well as the newest information about the interactions between nanomaterials and proteins in the human body. We propose a standard set of techniques for universal characterization of nanomaterials. We also address relevant regulatory issues involved in the translational process for the development of drug molecules and drug delivery systems. Adherence and refinement of a universal standard in nanomaterial characterization as well as the acquisition of a deeper understanding of nanomaterials and proteins will likely accelerate the use of nanomedicine in common practice to a great extent. PMID:25525356

  18. Active Learning Techniques Applied to an Interdisciplinary Mineral Resources Course.

    NASA Astrophysics Data System (ADS)

    Aird, H. M.

    2015-12-01

    An interdisciplinary active learning course was introduced at the University of Puget Sound entitled 'Mineral Resources and the Environment'. Various formative assessment and active learning techniques that have been effective in other courses were adapted and implemented to improve student learning, increase retention and broaden knowledge and understanding of course material. This was an elective course targeted towards upper-level undergraduate geology and environmental majors. The course provided an introduction to the mineral resources industry, discussing geological, environmental, societal and economic aspects, legislation and the processes involved in exploration, extraction, processing, reclamation/remediation and recycling of products. Lectures and associated weekly labs were linked in subject matter; relevant readings from the recent scientific literature were assigned and discussed in the second lecture of the week. Peer-based learning was facilitated through weekly reading assignments with peer-led discussions and through group research projects, in addition to in-class exercises such as debates. Writing and research skills were developed through student groups designing, carrying out and reporting on their own semester-long research projects around the lasting effects of the historical Ruston Smelter on the biology and water systems of Tacoma. The writing of their mini grant proposals and final project reports was carried out in stages to allow for feedback before the deadline. Speakers from industry were invited to share their specialist knowledge as guest lecturers, and students were encouraged to interact with them, with a view to employment opportunities. Formative assessment techniques included jigsaw exercises, gallery walks, placemat surveys, think pair share and take-home point summaries. Summative assessment included discussion leadership, exams, homeworks, group projects, in-class exercises, field trips, and pre-discussion reading exercises

  19. E-Learning System Using Segmentation-Based MR Technique for Learning Circuit Construction

    ERIC Educational Resources Information Center

    Takemura, Atsushi

    2016-01-01

    This paper proposes a novel e-Learning system using the mixed reality (MR) technique for technical experiments involving the construction of electronic circuits. The proposed system comprises experimenters' mobile computers and a remote analysis system. When constructing circuits, each learner uses a mobile computer to transmit image data from the…

  20. Improving face image extraction by using deep learning technique

    NASA Astrophysics Data System (ADS)

    Xue, Zhiyun; Antani, Sameer; Long, L. R.; Demner-Fushman, Dina; Thoma, George R.

    2016-03-01

    The National Library of Medicine (NLM) has made a collection of over a 1.2 million research articles containing 3.2 million figure images searchable using the Open-iSM multimodal (text+image) search engine. Many images are visible light photographs, some of which are images containing faces ("face images"). Some of these face images are acquired in unconstrained settings, while others are studio photos. To extract the face regions in the images, we first applied one of the most widely-used face detectors, a pre-trained Viola-Jones detector implemented in Matlab and OpenCV. The Viola-Jones detector was trained for unconstrained face image detection, but the results for the NLM database included many false positives, which resulted in a very low precision. To improve this performance, we applied a deep learning technique, which reduced the number of false positives and as a result, the detection precision was improved significantly. (For example, the classification accuracy for identifying whether the face regions output by this Viola- Jones detector are true positives or not in a test set is about 96%.) By combining these two techniques (Viola-Jones and deep learning) we were able to increase the system precision considerably, while avoiding the need to manually construct a large training set by manual delineation of the face regions.

  1. Machine learning techniques for energy optimization in mobile embedded systems

    NASA Astrophysics Data System (ADS)

    Donohoo, Brad Kyoshi

    Mobile smartphones and other portable battery operated embedded systems (PDAs, tablets) are pervasive computing devices that have emerged in recent years as essential instruments for communication, business, and social interactions. While performance, capabilities, and design are all important considerations when purchasing a mobile device, a long battery lifetime is one of the most desirable attributes. Battery technology and capacity has improved over the years, but it still cannot keep pace with the power consumption demands of today's mobile devices. This key limiter has led to a strong research emphasis on extending battery lifetime by minimizing energy consumption, primarily using software optimizations. This thesis presents two strategies that attempt to optimize mobile device energy consumption with negligible impact on user perception and quality of service (QoS). The first strategy proposes an application and user interaction aware middleware framework that takes advantage of user idle time between interaction events of the foreground application to optimize CPU and screen backlight energy consumption. The framework dynamically classifies mobile device applications based on their received interaction patterns, then invokes a number of different power management algorithms to adjust processor frequency and screen backlight levels accordingly. The second strategy proposes the usage of machine learning techniques to learn a user's mobile device usage pattern pertaining to spatiotemporal and device contexts, and then predict energy-optimal data and location interface configurations. By learning where and when a mobile device user uses certain power-hungry interfaces (3G, WiFi, and GPS), the techniques, which include variants of linear discriminant analysis, linear logistic regression, non-linear logistic regression, and k-nearest neighbor, are able to dynamically turn off unnecessary interfaces at runtime in order to save energy.

  2. MULTI-BAND DIPOLE AND MULTIPOLE WAKEFIELDS IN NLC TRAVELING WAVE ACCELERATORS USING A WIRE MEASUREMENT TECHNIQUE

    SciTech Connect

    Jones, Roger M

    2002-06-20

    Dipole wakefields in NLC (Next Linear Collider) structures have been measured with ASSET [1] and well predicted by a circuit model [2]. However, the experimental technique is both time-consuming and expensive. Here, we report on kick factor and synchronous frequency determination for 1st and higher order dipole bands for TW (Traveling Wave) accelerators via a wire measurement technique. This stand-alone technique is relatively inexpensive and may lead to an efficient determination of wakefield parameters. The perturbative effect of the wire on the dipole band is pointed out and a two-wire scheme with a limited perturbative effect is also discussed.

  3. Beam manipulation techniques, nonlinear beam dynamics, and space charge effect in high energy high power accelerators

    SciTech Connect

    Lee, S. Y.

    2014-04-07

    We had carried out a design of an ultimate storage ring with beam emittance less than 10 picometer for the feasibility of coherent light source at X-ray wavelength. The accelerator has an inherent small dynamic aperture. We study method to improve the dynamic aperture and collective instability for an ultimate storage ring. Beam measurement and accelerator modeling are an integral part of accelerator physics. We develop the independent component analysis (ICA) and the orbit response matrix method for improving accelerator reliability and performance. In collaboration with scientists in National Laboratories, we also carry out experimental and theoretical studies on beam dynamics. Our proposed research topics are relevant to nuclear and particle physics using high brightness particle and photon beams.

  4. Successes and lessons learned: How to accelerate the base closure process

    SciTech Connect

    Larkin, V.C.; Stoll, R.

    1994-12-31

    Naval Station Puget Sound, Seattle, was nominated for closure by the Base Closure Commission in 1991 (BRAC II) and will be transferred in September of 1995. Historic activities have resulted in petroleum-related environmental issues. Unlike many bases being closed, the politically sensitive issues are not the economics of job losses. Because homeless housing is expected to be included in the selected reuse plan, the primary concerns of the public are reduced real estate values and public safety. In addition to a reuse plan adopted by the Seattle City Council, the Muckleshoot Indian tribe has also submitted an alternative reuse plan to the Navy. Acceleration methods described in this paper include methods for beginning the environmental impact statement (EIS) process before reuse plans are finalized; tracking development of engineering alternatives in parallel with environmental investigations; using field screening data to begin developing plans and specifications for remediation, instead of waiting 6 weeks for analytical results and data validation; using efficient communication techniques to facilitate accelerated review of technical documents by the BCT; expediting removal actions and performing ``cleanups incidental to investigation``; and effectively facilitating members of the Restoration Advisory Board with divergent points of view. This paper will describe acceleration methods that proved to be effective and methods that could be modified to be more effective at other sites.

  5. Development of design technique for vacuum insulation in large size multi-aperture multi-grid accelerator for nuclear fusion

    SciTech Connect

    Kojima, A. Hanada, M.; Tobari, H.; Nishikiori, R.; Hiratsuka, J.; Kashiwagi, M.; Umeda, N.; Yoshida, M.; Ichikawa, M.; Watanabe, K.; Yamano, Y.; Grisham, L. R.

    2016-02-15

    Design techniques for the vacuum insulation have been developed in order to realize a reliable voltage holding capability of multi-aperture multi-grid (MAMuG) accelerators for fusion application. In this method, the nested multi-stage configuration of the MAMuG accelerator can be uniquely designed to satisfy the target voltage within given boundary conditions. The evaluation of the voltage holding capabilities of each acceleration stages was based on the previous experimental results about the area effect and the multi-aperture effect. Since the multi-grid effect was found to be the extension of the area effect by the total facing area this time, the total voltage holding capability of the multi-stage can be estimated from that per single stage by assuming the stage with the highest electric field, the total facing area, and the total apertures. By applying these consideration, the analysis on the 3-stage MAMuG accelerator for JT-60SA agreed well with the past gap-scan experiments with an accuracy of less than 10% variation, which demonstrated the high reliability to design MAMuG accelerators and also multi-stage high voltage bushings.

  6. Development of design technique for vacuum insulation in large size multi-aperture multi-grid accelerator for nuclear fusion.

    PubMed

    Kojima, A; Hanada, M; Tobari, H; Nishikiori, R; Hiratsuka, J; Kashiwagi, M; Umeda, N; Yoshida, M; Ichikawa, M; Watanabe, K; Yamano, Y; Grisham, L R

    2016-02-01

    Design techniques for the vacuum insulation have been developed in order to realize a reliable voltage holding capability of multi-aperture multi-grid (MAMuG) accelerators for fusion application. In this method, the nested multi-stage configuration of the MAMuG accelerator can be uniquely designed to satisfy the target voltage within given boundary conditions. The evaluation of the voltage holding capabilities of each acceleration stages was based on the previous experimental results about the area effect and the multi-aperture effect. Since the multi-grid effect was found to be the extension of the area effect by the total facing area this time, the total voltage holding capability of the multi-stage can be estimated from that per single stage by assuming the stage with the highest electric field, the total facing area, and the total apertures. By applying these consideration, the analysis on the 3-stage MAMuG accelerator for JT-60SA agreed well with the past gap-scan experiments with an accuracy of less than 10% variation, which demonstrated the high reliability to design MAMuG accelerators and also multi-stage high voltage bushings.

  7. 76 FR 45334 - Innovative Techniques for Delivering ITS Learning; Request for Information

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-28

    ... they be implemented? Examples could be e-learning techniques, interactive games, or simulations. The... text messages for quick responses during an e-learning. 7. Are you aware of any learning materials... Research and Innovative Technology Administration Innovative Techniques for Delivering ITS...

  8. Figure Analysis: A Teaching Technique to Promote Visual Literacy and Active Learning

    ERIC Educational Resources Information Center

    Wiles, Amy M.

    2016-01-01

    Learning often improves when active learning techniques are used in place of traditional lectures. For many of these techniques, however, students are expected to apply concepts that they have already grasped. A challenge, therefore, is how to incorporate active learning into the classroom of courses with heavy content, such as molecular-based…

  9. Machine Learning Techniques for Decision Support in Intelligent Data Management

    NASA Astrophysics Data System (ADS)

    Lynnes, C.; Miller, J.; Ramapriyan, H.; Isaac, D.; Harberts, R.

    2002-12-01

    NASA's growth in remote sensing data volumes has kept pace with Moore's Law, i.e., doubling every 18 months, with future growth likely from new instruments. Also, advances in instrumental design (e.g., hyperspectral scanners) and science algorithms are enabling more near-real-time applications of the data. The confluence of low-latency requirements with high data volumes and numbers of files poses major challenges for archive data management. In order to make the right data available at the right time, an archive will need to apply knowledge of the data content in its data management decisions. This decision support domain includes aspects such as automatic quality assessment, feature detection to support caching decisions, and content-based metadata to support efficient data selection. In this study, we evaluate a variety of machine learning algorithms for use in several decision support roles in intelligent data management. Machine learning algorithms such as neural networks and clustering have been used for decision support in business and policy domains. These techniques have found some use in remote sensing, e.g., for cloud and land cover classification. Yet most research on remote sensing data rests on science-based algorithms, such as those based on radiative transfer equations. Machine learning for scientific applications faces challenges such as discretization constraints, non-physical basis, and the difficulty of assembling training sets. However, these difficulties may be less significant in the decision support role. For instance, it is often enough to know whether a data attribute exceeds a certain threshold when selecting it for an application, without knowing the exact value. The training data problem can be surmounted by using products output by the science-based algorithms. On the other hand, an advantage of machine learning algorithms for decision support is their speed once they have been trained. Data management decisions must be made while the

  10. Locomotion training of legged robots using hybrid machine learning techniques

    NASA Technical Reports Server (NTRS)

    Simon, William E.; Doerschuk, Peggy I.; Zhang, Wen-Ran; Li, Andrew L.

    1995-01-01

    In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible

  11. Accelerating the search for global minima on potential energy surfaces using machine learning

    NASA Astrophysics Data System (ADS)

    Carr, S. F.; Garnett, R.; Lo, C. S.

    2016-10-01

    Controlling molecule-surface interactions is key for chemical applications ranging from catalysis to gas sensing. We present a framework for accelerating the search for the global minimum on potential surfaces, corresponding to stable adsorbate-surface structures. We present a technique using Bayesian inference that enables us to predict converged density functional theory potential energies with fewer self-consistent field iterations. We then discuss how this technique fits in with the Bayesian Active Site Calculator, which applies Bayesian optimization to the problem. We demonstrate the performance of our framework using a hematite (Fe2O3) surface and present the adsorption sites found by our global optimization method for various simple hydrocarbons on the rutile TiO2 (110) surface.

  12. Reinforcement learning techniques for controlling resources in power networks

    NASA Astrophysics Data System (ADS)

    Kowli, Anupama Sunil

    As power grids transition towards increased reliance on renewable generation, energy storage and demand response resources, an effective control architecture is required to harness the full functionalities of these resources. There is a critical need for control techniques that recognize the unique characteristics of the different resources and exploit the flexibility afforded by them to provide ancillary services to the grid. The work presented in this dissertation addresses these needs. Specifically, new algorithms are proposed, which allow control synthesis in settings wherein the precise distribution of the uncertainty and its temporal statistics are not known. These algorithms are based on recent developments in Markov decision theory, approximate dynamic programming and reinforcement learning. They impose minimal assumptions on the system model and allow the control to be "learned" based on the actual dynamics of the system. Furthermore, they can accommodate complex constraints such as capacity and ramping limits on generation resources, state-of-charge constraints on storage resources, comfort-related limitations on demand response resources and power flow limits on transmission lines. Numerical studies demonstrating applications of these algorithms to practical control problems in power systems are discussed. Results demonstrate how the proposed control algorithms can be used to improve the performance and reduce the computational complexity of the economic dispatch mechanism in a power network. We argue that the proposed algorithms are eminently suitable to develop operational decision-making tools for large power grids with many resources and many sources of uncertainty.

  13. Use of the dichotic listening technique with learning disabilities.

    PubMed

    Obrzut, John E; Mahoney, Emery B

    2011-07-01

    Dichotic listening (DL) techniques have been used extensively as a non-invasive procedure to assess language lateralization among children with and without learning disabilities (LD), and with individuals who have other auditory system related brain disorders. Results of studies using DL have indicated that language is lateralized in children with LD and that the lateralized language asymmetries do not develop after age 6 nor are they affected by gender. Observed differences in lateralized language processes between control children and those with LD were found not due to delayed cerebral dominance, but rather to deficits in selective attention. In addition, attention factors have a greater influence on auditory processing of verbal than nonverbal stimuli for children with LD, and children with LD exhibit a general processing bias to the same hemisphere unlike control children. Furthermore, employing directed attention conditions in DL experiments has played an important role in explaining learning disabled children's performance on DL tasks. We conclude that auditory perceptual asymmetries as assessed by DL with children who experience LD are the result of the interaction of hemispheric capability and attention factors.

  14. Estimation of alpine skier posture using machine learning techniques.

    PubMed

    Nemec, Bojan; Petrič, Tadej; Babič, Jan; Supej, Matej

    2014-10-13

    High precision Global Navigation Satellite System (GNSS) measurements are becoming more and more popular in alpine skiing due to the relatively undemanding setup and excellent performance. However, GNSS provides only single-point measurements that are defined with the antenna placed typically behind the skier's neck. A key issue is how to estimate other more relevant parameters of the skier's body, like the center of mass (COM) and ski trajectories. Previously, these parameters were estimated by modeling the skier's body with an inverted-pendulum model that oversimplified the skier's body. In this study, we propose two machine learning methods that overcome this shortcoming and estimate COM and skis trajectories based on a more faithful approximation of the skier's body with nine degrees-of-freedom. The first method utilizes a well-established approach of artificial neural networks, while the second method is based on a state-of-the-art statistical generalization method. Both methods were evaluated using the reference measurements obtained on a typical giant slalom course and compared with the inverted-pendulum method. Our results outperform the results of commonly used inverted-pendulum methods and demonstrate the applicability of machine learning techniques in biomechanical measurements of alpine skiing.

  15. Short-term wind speed predictions with machine learning techniques

    NASA Astrophysics Data System (ADS)

    Ghorbani, M. A.; Khatibi, R.; FazeliFard, M. H.; Naghipour, L.; Makarynskyy, O.

    2016-02-01

    Hourly wind speed forecasting is presented by a modeling study with possible applications to practical problems including farming wind energy, aircraft safety and airport operations. Modeling techniques employed in this paper for such short-term predictions are based on the machine learning techniques of artificial neural networks (ANNs) and genetic expression programming (GEP). Recorded values of wind speed were used, which comprised 8 years of collected data at the Kersey site, Colorado, USA. The January data over the first 7 years (2005-2011) were used for model training; and the January data for 2012 were used for model testing. A number of model structures were investigated for the validation of the robustness of these two techniques. The prediction results were compared with those of a multiple linear regression (MLR) method and with the Persistence method developed for the data. The model performances were evaluated using the correlation coefficient, root mean square error, Nash-Sutcliffe efficiency coefficient and Akaike information criterion. The results indicate that forecasting wind speed is feasible using past records of wind speed alone, but the maximum lead time for the data was found to be 14 h. The results show that different techniques would lead to different results, where the choice between them is not easy. Thus, decision making has to be informed of these modeling results and decisions should be arrived at on the basis of an understanding of inherent uncertainties. The results show that both GEP and ANN are equally credible selections and even MLR should not be dismissed, as it has its uses.

  16. Effect of Active Learning Techniques on Students' Choice of Approach to Learning in Dentistry: A South African Case Study

    ERIC Educational Resources Information Center

    Khan, S.

    2011-01-01

    The purpose of this article is to report on empirical work, related to a techniques module, undertaken with the dental students of the University of the Western Cape, South Africa. I will relate how a range of different active learning techniques (tutorials; question papers and mock tests) assisted students to adopt a deep approach to learning in…

  17. Techniques for correcting velocity and density fluctuations of ion beams in ion inducti on accelerators

    NASA Astrophysics Data System (ADS)

    Woo, K. M.; Yu, S. S.; Barnard, J. J.

    2013-06-01

    It is well known that the imperfection of pulse power sources that drive the linear induction accelerators can lead to time-varying fluctuation in the accelerating voltages, which in turn leads to longitudinal emittance growth. We show that this source of emittance growth is correctable, even in space-charge dominated beams with significant transients induced by space-charge waves. Two correction methods are proposed, and their efficacy in reducing longitudinal emittance is demonstrated with three-dimensional particle-in-cell simulations.

  18. Microteaching, an efficient technique for learning effective teaching.

    PubMed

    Remesh, Ambili

    2013-02-01

    Microteaching, a teacher training technique currently practiced worldwide, provides teachers an opportunity to perk up their teaching skills by improving the various simple tasks called teaching skills. With the proven success among the novice and seniors, microteaching helps to promote real-time teaching experiences. The core skills of microteaching such as presentation and reinforcement skills help the novice teachers to learn the art of teaching at ease and to the maximum extent. The impact of this technique has been widely seen in various forms of education such as health sciences, life sciences, and other areas. The emerging changes in medical curricula by the Medical Council of India and the role of medical teachers envisage the need of this special training of teachers and monitoring of their skills for their continued efficient performance at any age. The alleged limitations of microteaching can be minimized by implementing this at the departmental level in several sequences. The author made literature search of research and review articles in various educational databases, journals, and books. From the reference list of published articles, books were also reviewed. This paper presents an outline of the various phases of microteaching, core teaching skills, implementation aspects, and the impact of microteaching on medical education.

  19. Video mining using combinations of unsupervised and supervised learning techniques

    NASA Astrophysics Data System (ADS)

    Divakaran, Ajay; Miyahara, Koji; Peker, Kadir A.; Radhakrishnan, Regunathan; Xiong, Ziyou

    2003-12-01

    We discuss the meaning and significance of the video mining problem, and present our work on some aspects of video mining. A simple definition of video mining is unsupervised discovery of patterns in audio-visual content. Such purely unsupervised discovery is readily applicable to video surveillance as well as to consumer video browsing applications. We interpret video mining as content-adaptive or "blind" content processing, in which the first stage is content characterization and the second stage is event discovery based on the characterization obtained in stage 1. We discuss the target applications and find that using a purely unsupervised approach are too computationally complex to be implemented on our product platform. We then describe various combinations of unsupervised and supervised learning techniques that help discover patterns that are useful to the end-user of the application. We target consumer video browsing applications such as commercial message detection, sports highlights extraction etc. We employ both audio and video features. We find that supervised audio classification combined with unsupervised unusual event discovery enables accurate supervised detection of desired events. Our techniques are computationally simple and robust to common variations in production styles etc.

  20. Application of Machine Learning Approaches for Classifying Sitting Posture Based on Force and Acceleration Sensors

    PubMed Central

    Tanadini, Matteo; Plüss, Stefan; Schnüriger, Karin; Singh, Navrag B.

    2016-01-01

    Occupational musculoskeletal disorders, particularly chronic low back pain (LBP), are ubiquitous due to prolonged static sitting or nonergonomic sitting positions. Therefore, the aim of this study was to develop an instrumented chair with force and acceleration sensors to determine the accuracy of automatically identifying the user's sitting position by applying five different machine learning methods (Support Vector Machines, Multinomial Regression, Boosting, Neural Networks, and Random Forest). Forty-one subjects were requested to sit four times in seven different prescribed sitting positions (total 1148 samples). Sixteen force sensor values and the backrest angle were used as the explanatory variables (features) for the classification. The different classification methods were compared by means of a Leave-One-Out cross-validation approach. The best performance was achieved using the Random Forest classification algorithm, producing a mean classification accuracy of 90.9% for subjects with which the algorithm was not familiar. The classification accuracy varied between 81% and 98% for the seven different sitting positions. The present study showed the possibility of accurately classifying different sitting positions by means of the introduced instrumented office chair combined with machine learning analyses. The use of such novel approaches for the accurate assessment of chair usage could offer insights into the relationships between sitting position, sitting behaviour, and the occurrence of musculoskeletal disorders. PMID:27868066

  1. Incipient fault detection and identification in process systems using accelerating neural network learning

    SciTech Connect

    Parlos, A.G.; Muthusami, J.; Atiya, A.F. . Dept. of Nuclear Engineering)

    1994-02-01

    The objective of this paper is to present the development and numerical testing of a robust fault detection and identification (FDI) system using artificial neural networks (ANNs), for incipient (slowly developing) faults occurring in process systems. The challenge in using ANNs in FDI systems arises because of one's desire to detect faults of varying severity, faults from noisy sensors, and multiple simultaneous faults. To address these issues, it becomes essential to have a learning algorithm that ensures quick convergence to a high level of accuracy. A recently developed accelerated learning algorithm, namely a form of an adaptive back propagation (ABP) algorithm, is used for this purpose. The ABP algorithm is used for the development of an FDI system for a process composed of a direct current motor, a centrifugal pump, and the associated piping system. Simulation studies indicate that the FDI system has significantly high sensitivity to incipient fault severity, while exhibiting insensitivity to sensor noise. For multiple simultaneous faults, the FDI system detects the fault with the predominant signature. The major limitation of the developed FDI system is encountered when it is subjected to simultaneous faults with similar signatures. During such faults, the inherent limitation of pattern-recognition-based FDI methods becomes apparent. Thus, alternate, more sophisticated FDI methods become necessary to address such problems. Even though the effectiveness of pattern-recognition-based FDI methods using ANNs has been demonstrated, further testing using real-world data is necessary.

  2. Multimedia Learning: Cognitive Individual Differences and Display Design Techniques Predict Transfer Learning with Multimedia Learning Modules

    ERIC Educational Resources Information Center

    Austin, Katherine A.

    2009-01-01

    In the wake of the information explosion and rapidly progressing technology [Mayer, R. E. (2001). "Multimedia learning". Cambridge: University Press] formulated a theory that focused on human cognition, rather than technology capacity and features. By measuring the effect of cognitive individual differences and display design manipulations on…

  3. Human Short-Latency Somatosensory Evoked Potentials in Impact Acceleration Research: Equipment, Procedures and Techniques

    DTIC Science & Technology

    1990-10-01

    Instrumentation Data Sheet .......................... 10 Figure 8. Human Physiology Screen One ....................................... 1I1 Figure 9. Human ... Physiology Screen Two...................................... 12 Figure 10. Human Physiology Screen Three ..................................... 12 Figure...Short-Latency Somatosensory Evoked Potentials in Impact Acceleration Research ***** HUMAN PHYSIOLOGY SCREEN***** Please Read First To move from one

  4. Disk-loaded RF waveguide matching techniques applied to silicon woodpile accelerator

    SciTech Connect

    Wu Ziran; England, Joel; Ng, Cho; Tantawi, Sami

    2012-12-21

    Silicon woodpile photonic crystal provides a three-dimensional dielectric waveguide system for high-gradient laser driven acceleration. The woodpile waveguide is periodically loaded in the longitudinal direction; therefore simple cross-sectional mode profile matching is not sufficient to launch the accelerating mode appropriately and will result in significant scattering loss. Hinted by the common nature of longitudinal periodicity between disk-loaded waveguide and woodpile waveguide, several coupler design schemes developed for multi-cell RF cavity are implemented in the woodpile accelerator design. Among them there are the travelling-wave match method based on S-matrix, the periodic VSWR method, and the TE-to-TM coupling iris design. This paper presents design procedures and simulation results using these methods. According to simulations, nearly 100% power transmission between SOI and woodpile waveguides with a travelling-wave match is achieved with a specially designed mode-launching coupler. Constructed by silicon rods extruding into the defect waveguide, the coupling iris provides necessary transition from TE mode to TM accelerating mode, also with negligible coupling loss.

  5. Accelerating rate calorimetry: A new technique for safety studies in lithium systems

    NASA Technical Reports Server (NTRS)

    Ebner, W. B.

    1982-01-01

    The role of exothermic reactions in battery test modes is discussed. The exothermic reactions are characterized with respect to their time-temperature and time-pressure behavior. Reactions occuring for any major exotherm were examined. The accelerating rate calorimetry methods was developed to study lithium cells susceptibility to thermal runaway reactions following certain abuse modes such as forced discharge into reversal and charging.

  6. Comparison of error-amplification and haptic-guidance training techniques for learning of a timing-based motor task by healthy individuals.

    PubMed

    Milot, Marie-Hélène; Marchal-Crespo, Laura; Green, Christopher S; Cramer, Steven C; Reinkensmeyer, David J

    2010-03-01

    Performance errors drive motor learning for many tasks. Some researchers have suggested that reducing performance errors with haptic guidance can benefit learning by demonstrating correct movements, while others have suggested that artificially increasing errors will force faster and more complete learning. This study compared the effect of these two techniques--haptic guidance and error amplification--as healthy subjects learned to play a computerized pinball-like game. The game required learning to press a button using wrist movement at the correct time to make a flipper hit a falling ball to a randomly positioned target. Errors were decreased or increased using a robotic device that retarded or accelerated wrist movement, based on sensed movement initiation timing errors. After training with either error amplification or haptic guidance, subjects significantly reduced their timing errors and generalized learning to untrained targets. However, for a subset of more skilled subjects, training with amplified errors produced significantly greater learning than training with the reduced errors associated with haptic guidance, while for a subset of less skilled subjects, training with haptic guidance seemed to benefit learning more. These results suggest that both techniques help enhanced performance of a timing task, but learning is optimized if training subjects with the appropriate technique based on their baseline skill level.

  7. Rapid Probabilistic Source Inversion Using Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Kaeufl, P.; Valentine, A. P.; Trampert, J.

    2013-12-01

    Determination of earthquake source parameters is an important task in seismology. For many applications, it is also valuable to understand the uncertainties associated with these determinations, and this is particularly true in the context of earthquake early warning and hazard mitigation. We present a framework for probabilistic centroid moment tensor point source inversions in near real-time, applicable to a wide variety of data-types. Our methodology allows us to find an approximation to p(m|d), the conditional probability of source parameters (m) given observations, (d). This approximation is obtained by smoothly interpolating a set of random prior samples, using a machine learning algorithm able to learn the mapping from d to m. The approximation obtained can be evaluated within milliseconds on a standard desktop computer for a new observation (d). This makes the method well suited for use in situations such as earthquake early warning, where inversions must be performed routinely, for a fixed station geometry, and where it is important that results are obtained rapidly. This is a major advantage over traditional sampling based techniques, such as Markov-Chain Monte-Carlo methods, where a re-sampling of the posterior is necessary every time a new observation is made. We demonstrated the method by applying it to a regional static GPS displacement data set for the 2010 MW 7.2 El Mayor Cucapah earthquake in Baja California and obtained estimates of logarithmic magnitude, centroid location and depth, and focal mechanism (Käufl et al., submitted). We will present an extension of this approach to the inversion of full waveforms and explore possibilities for jointly inverting seismic and geodetic data. (1) P. Käufl, A. P. Valentine, T.B. O'Toole, J. Trampert, submitted, Geophysical Journal International

  8. Machine Learning Techniques for Arterial Pressure Waveform Analysis

    PubMed Central

    Almeida, Vânia G.; Vieira, João; Santos, Pedro; Pereira, Tânia; Pereira, H. Catarina; Correia, Carlos; Pego, Mariano; Cardoso, João

    2013-01-01

    The Arterial Pressure Waveform (APW) can provide essential information about arterial wall integrity and arterial stiffness. Most of APW analysis frameworks individually process each hemodynamic parameter and do not evaluate inter-dependencies in the overall pulse morphology. The key contribution of this work is the use of machine learning algorithms to deal with vectorized features extracted from APW. With this purpose, we follow a five-step evaluation methodology: (1) a custom-designed, non-invasive, electromechanical device was used in the data collection from 50 subjects; (2) the acquired position and amplitude of onset, Systolic Peak (SP), Point of Inflection (Pi) and Dicrotic Wave (DW) were used for the computation of some morphological attributes; (3) pre-processing work on the datasets was performed in order to reduce the number of input features and increase the model accuracy by selecting the most relevant ones; (4) classification of the dataset was carried out using four different machine learning algorithms: Random Forest, BayesNet (probabilistic), J48 (decision tree) and RIPPER (rule-based induction); and (5) we evaluate the trained models, using the majority-voting system, comparatively to the respective calculated Augmentation Index (AIx). Classification algorithms have been proved to be efficient, in particular Random Forest has shown good accuracy (96.95%) and high area under the curve (AUC) of a Receiver Operating Characteristic (ROC) curve (0.961). Finally, during validation tests, a correlation between high risk labels, retrieved from the multi-parametric approach, and positive AIx values was verified. This approach gives allowance for designing new hemodynamic morphology vectors and techniques for multiple APW analysis, thus improving the arterial pulse understanding, especially when compared to traditional single-parameter analysis, where the failure in one parameter measurement component, such as Pi, can jeopardize the whole evaluation. PMID

  9. Concepts and techniques: Active electronics and computers in safety-critical accelerator operation

    SciTech Connect

    Frankel, R.S.

    1995-12-31

    The Relativistic Heavy Ion Collider (RHIC) under construction at Brookhaven National Laboratory, requires an extensive Access Control System to protect personnel from Radiation, Oxygen Deficiency and Electrical hazards. In addition, the complicated nature of operation of the Collider as part of a complex of other Accelerators necessitates the use of active electronic measurement circuitry to ensure compliance with established Operational Safety Limits. Solutions were devised which permit the use of modern computer and interconnections technology for Safety-Critical applications, while preserving and enhancing, tried and proven protection methods. In addition a set of Guidelines, regarding required performance for Accelerator Safety Systems and a Handbook of design criteria and rules were developed to assist future system designers and to provide a framework for internal review and regulation.

  10. Accelerator-based analytical technique in the evaluation of some Nigeria’s natural minerals: Fluorite, tourmaline and topaz

    NASA Astrophysics Data System (ADS)

    Olabanji, S. O.; Ige, O. A.; Mazzoli, C.; Ceccato, D.; Akintunde, J. A.; De Poli, M.; Moschini, G.

    2005-10-01

    For the first time, the complementary accelerator-based analytical technique of PIXE and electron microprobe analysis (EMPA) were employed for the characterization of some Nigeria's natural minerals namely fluorite, tourmaline and topaz. These minerals occur in different areas in Nigeria. The minerals are mainly used as gemstones and for other scientific and technological applications and therefore are very important. There is need to characterize them to know the quality of these gemstones and update the geochemical data on them geared towards useful applications. PIXE analysis was carried out using the 1.8 MeV collimated proton beam from the 2.5 MV AN 2000 Van de Graaff accelerator at INFN, LNL, Legnaro, Padova, Italy. The novel results which show many elements at different concentrations in these minerals are presented and discussed.

  11. Successful Application of Active Learning Techniques to Introductory Microbiology.

    ERIC Educational Resources Information Center

    Hoffman, Elizabeth A.

    2001-01-01

    Points out the low student achievement in microbiology courses and presents an active learning method applied in an introductory microbiology course which features daily quizzes, cooperative learning activities, and group projects. (Contains 30 references.) (YDS)

  12. Design and development of a novel nuclear magnetic resonance detection for the gas phase ions by magnetic resonance acceleration technique

    NASA Astrophysics Data System (ADS)

    Fuke, K.; Tona, M.; Fujihara, A.; Sakurai, M.; Ishikawa, H.

    2012-08-01

    Nuclear magnetic resonance (NMR) technique is a well-established powerful tool to study the physical and chemical properties of a wide range of materials. However, presently, NMR applications are essentially limited to materials in the condensed phase. Although magnetic resonance was originally demonstrated in gas phase molecular beam experiments, no application to gas phase molecular ions has yet been demonstrated. Here, we present a novel principle of NMR detection for gas phase ions based on a "magnetic resonance acceleration" technique and describe the design and construction of an apparatus which we are developing. We also present an experimental technique and some results on the formation and manipulation of cold ion packets in a strong magnetic field, which are the key innovations to detect NMR signal using the present method. We expect this novel method to lead new realm for the study of mass-selected gas-phase ions with interesting applications in both fundamental and applied sciences.

  13. Ultra-High Sensitivity Techniques for the Determination of 3 He /4 He Abundances in Helium by Accelerator Mass Spectrometry

    NASA Astrophysics Data System (ADS)

    Mumm, H. P.; Huber, M.; Bauder, W.; Abrams, N.; Deibel, C.; Huffer, C.; Huffman, P.; Schelhammer, K.; Janssens, R.; Jiang, C.; Scott, R.; Pardo, R.; Rehm, K.; Vondrasek, R.; Swank, C.; O'Shaughnessy, C.; Paul, M.; Yang, L.

    2017-01-01

    We report the development of an Accelerator Mass Spectrometry technique to measure the 3He/4He isotopic ratio using a radio frequency (RF) discharge source and the ATLAS facility at Argonne National Laboratory. Control over 3He/4He ratio in helium several orders of magnitude lower than natural abundance is critical for neutron lifetime and source experiments using liquid helium. Due to low ultimate beam currents, the ATLAS accelerator and beam line were tuned using a succession of species of the same M/q. A unique RF source was developed for the experiment due to large natural 3He backgrounds. Analog H_3 + and DH + molecular ions are eliminated by dissociation via a gold stripper foil near the detector. The stripped ions were dispersed in a magnetic spectrograph and 3He2 + ions counted in the focal plane detector. This technique is sensitive to 3 He /4 He ratios in the regime of 10-12 with backgrounds that appear to be below 10-14. The techniques used to reduce the backgrounds and remaining outstanding problems will be presented along with results from measurements on high purity 4He samples.

  14. Validation of Learning Effort Algorithm for Real-Time Non-Interfering Based Diagnostic Technique

    ERIC Educational Resources Information Center

    Hsu, Pi-Shan; Chang, Te-Jeng

    2011-01-01

    The objective of this research is to validate the algorithm of learning effort which is an indicator of a new real-time and non-interfering based diagnostic technique. IC3 Mentor, the adaptive e-learning platform fulfilling the requirements of intelligent tutor system, was applied to 165 university students. The learning records of the subjects…

  15. ESL Teachers' Questioning Technique in an Assessment for Learning Context: Promising or Problematic?

    ERIC Educational Resources Information Center

    Sardareh, Sedigheh Abbasnasab; Saad, Mohd Rashid Mohd; Othman, Abdul Jalil; Me, Rosalam Che

    2014-01-01

    As a crucial feature of assessment for learning (AfL), questioning technique plays an important part in student learning. In an AfL classroom, questioning technique is not merely a pedagogical tool to elicit evidence of students' understanding but also a means to improve their understanding. Effective classroom questioning underpins AfL; However,…

  16. Accelerating atomistic simulations through self-learning bond-boost hyperdynamics

    SciTech Connect

    Perez, Danny; Voter, Arthur F

    2008-01-01

    By altering the potential energy landscape on which molecular dynamics are carried out, the hyperdynamics method of Voter enables one to significantly accelerate the simulation state-to-state dynamics of physical systems. While very powerful, successful application of the method entails solving the subtle problem of the parametrization of the so-called bias potential. In this study, we first clarify the constraints that must be obeyed by the bias potential and demonstrate that fast sampling of the biased landscape is key to the obtention of proper kinetics. We then propose an approach by which the bond boost potential of Miron and Fichthorn can be safely parametrized based on data acquired in the course of a molecular dynamics simulation. Finally, we introduce a procedure, the Self-Learning Bond Boost method, in which the parametrization is step efficiently carried out on-the-fly for each new state that is visited during the simulation by safely ramping up the strength of the bias potential up to its optimal value. The stability and accuracy of the method are demonstrated.

  17. Accelerating the reduction in cervical cancer: what can we learn from the Safe Motherhood movement?

    PubMed

    Tsu, Vivien D; Jeronimo, Jose

    2013-10-01

    As we move toward the post-2015 development agenda, we should reflect on the accomplishments of the Safe Motherhood movement and derive potential lessons to strengthen programs to reduce the burden of cervical cancer. Five key areas have been the focus of attention over the years: definition of the magnitude and distribution of maternal mortality; identification of effective and feasible clinical solutions; advocacy to increase attention, resources, and commitment; leadership through international coalitions; and development of a framework for accountability, with targets and indicators. While efforts have been made in each of these areas for cervical cancer prevention, progress has been constrained by inadequate resources. Data are of variable quality, with few cancer registries in the countries where cervical cancer is most prevalent. There has been substantial progress in identifying feasible and effective clinical and programmatic interventions, and a growing consensus around meaningful indicators. Advocacy on behalf of cervical cancer prevention has been gaining momentum but leadership is still fragmented. With so many of the basic elements for cervical cancer prevention in place, we must use the lessons learned from the Safe Motherhood movement to accelerate the pace of scaling-up cervical cancer prevention activities, saving millions of women's lives in the next decade.

  18. Employment of Adaptive Learning Techniques for the Discrimination of Acoustic Emissions.

    DTIC Science & Technology

    1983-11-01

    8D-1Ai38 142 EMPLOYMENT OP ADAPTIVE LEARNING TECHNIQUES FOR THE I DISCRIMINATION OF ACOU..(U) GENERAL ELECTRIC CORPORATE U Ch, RESEARCH AND...OFSTNDRD-96- 1.5%. 111 11 :%____ 111. %I1~.~ 11 1 - 111 -- k. -Jr -. P. -L -. b. EMPLOYMENT OF ADAPTIVE LEARNING TECHNIQUESEli FOR THE DISCRIMINATION OF...8217Include Security Claaaaficatiano Employment of Adaptive * Learning Techniques for the Discrimination Of Acoustic Emissions (Unclassified) 12.’ PE SNAU.R S

  19. Educating patients: understanding barriers, learning styles, and teaching techniques.

    PubMed

    Beagley, Linda

    2011-10-01

    Health care delivery and education has become a challenge for providers. Nurses and other professionals are challenged daily to assure that the patient has the necessary information to make informed decisions. Patients and their families are given a multitude of information about their health and commonly must make important decisions from these facts. Obstacles that prevent easy delivery of health care information include literacy, culture, language, and physiological barriers. It is up to the nurse to assess and evaluate the patient's learning needs and readiness to learn because everyone learns differently. This article will examine how each of these barriers impact care delivery along with teaching and learning strategies will be examined.

  20. Thermography and machine learning techniques for tomato freshness prediction.

    PubMed

    Xie, Jing; Hsieh, Sheng-Jen; Wang, Hong-Jin; Tan, Zuojun

    2016-12-01

    The United States and China are the world's leading tomato producers. Tomatoes account for over $2 billion annually in farm sales in the U.S. Tomatoes also rank as the world's 8th most valuable agricultural product, valued at $58 billion dollars annually, and quality is highly prized. Nondestructive technologies, such as optical inspection and near-infrared spectrum analysis, have been developed to estimate tomato freshness (also known as grades in USDA parlance). However, determining the freshness of tomatoes is still an open problem. This research (1) illustrates the principle of theory on why thermography might be able to reveal the internal state of the tomatoes and (2) investigates the application of machine learning techniques-artificial neural networks (ANNs) and support vector machines (SVMs)-in combination with transient step heating, and thermography for freshness prediction, which refers to how soon the tomatoes will decay. Infrared images were captured at a sampling frequency of 1 Hz during 40 s of heating followed by 160 s of cooling. The temperatures of the acquired images were plotted. Regions with higher temperature differences between fresh and less fresh (rotten within three days) tomatoes of approximately uniform size and shape were used as the input nodes for ANN and SVM models. The ANN model built using heating and cooling data was relatively optimal. The overall regression coefficient was 0.99. These results suggest that a combination of infrared thermal imaging and ANN modeling methods can be used to predict tomato freshness with higher accuracy than SVM models.

  1. Does Grammatical Structure Accelerate Number Word Learning? Evidence from Learners of Dual and Non-Dual Dialects of Slovenian

    PubMed Central

    Plesničar, Vesna; Razboršek, Tina; Sullivan, Jessica; Barner, David

    2016-01-01

    How does linguistic structure affect children’s acquisition of early number word meanings? Previous studies have tested this question by comparing how children learning languages with different grammatical representations of number learn the meanings of labels for small numbers, like 1, 2, and 3. For example, children who acquire a language with singular-plural marking, like English, are faster to learn the word for 1 than children learning a language that lacks the singular-plural distinction, perhaps because the word for 1 is always used in singular contexts, highlighting its meaning. These studies are problematic, however, because reported differences in number word learning may be due to unmeasured cross-cultural differences rather than specific linguistic differences. To address this problem, we investigated number word learning in four groups of children from a single culture who spoke different dialects of the same language that differed chiefly with respect to how they grammatically mark number. We found that learning a dialect which features “dual” morphology (marking of pairs) accelerated children’s acquisition of the number word two relative to learning a “non-dual” dialect of the same language. PMID:27486802

  2. Accelerated partial breast irradiation with brachytherapy: patient selection and technique considerations

    PubMed Central

    Trifiletti, Daniel M; Romano, Kara D; Showalter, Shayna L; Reardon, Kelli A; Libby, Bruce; Showalter, Timothy N

    2015-01-01

    Accelerated partial breast irradiation (APBI) through breast brachytherapy is a relatively recent development in breast radiotherapy that has gained international favor because of its reduction in treatment duration and normal tissue irradiation while maintaining favorable cancer-specific and cosmetic outcomes. Despite the fact that several large national trials have not reported final results yet, many providers are currently offering APBI to select patients and APBI is listed as a treatment option for selecting patients in the National Comprehensive Cancer Network guidelines. Multiple consensus guidelines exist in selecting patients for APBI, some with conflicting recommendations. In this review, the existing patient selection guidelines are reported, compared, and critiqued, grouping them in helpful subcategories. Unique patient and technical selection factors for APBI with brachytherapy are explored. PMID:26251627

  3. NOVEL TECHNIQUE OF POWER CONTROL IN MAGNETRON TRANSMITTERS FOR INTENSE ACCELERATORS

    SciTech Connect

    Kazakevich, G.; Johnson, R.; Neubauer, M.; Lebedev, V.; Schappert, W.; Yakovlev, V.

    2016-10-21

    A novel concept of a high-power magnetron transmitter allowing dynamic phase and power control at the frequency of locking signal is proposed. The transmitter compensating parasitic phase and amplitude modulations inherent in Superconducting RF (SRF) cavities within closed feedback loops is intended for powering of the intensity-frontier superconducting accelerators. The con- cept uses magnetrons driven by a sufficient resonant (in- jection-locking) signal and fed by the voltage which can be below the threshold of self-excitation. This provides an extended range of power control in a single magnetron at highest efficiency minimizing the cost of RF power unit and the operation cost. Proof-of-principle of the proposed concept demonstrated in pulsed and CW regimes with 2.45 GHz, 1kW magnetrons is discussed here. A conceptual scheme of the high-power transmitter allowing the dynamic wide-band phase and y power controls is presented and discussed.

  4. A Motivational Approach to Student Learning: The Landlord Technique.

    ERIC Educational Resources Information Center

    Lanford, Horace

    A motivational approach to student learning that has been implemented in several courses at Wright University in Ohio consists of six efforts: (1) to instill in students the knowledge of motivation, both from within and without; (2) to make students members of cohesive work groups; (3) to apply theory learned; (4) to demonstrate achievement of…

  5. Using Brain-Based Learning Techniques in High School Science.

    ERIC Educational Resources Information Center

    Pinkerton, K. David

    1994-01-01

    A physics/chemistry teacher examined how brain-based learning environments could produce better learning conditions for students. He used thematic teaching, enriched language, naturally complex, long-term design and construction projects, and multifaceted assessment tools. The one-year curriculum indicated that teachers need not sacrifice content…

  6. Learning Faults Detection by AIS Techniques in CSCL Environments

    ERIC Educational Resources Information Center

    Zedadra, Amina; Lafifi, Yacine

    2015-01-01

    By the increase of e-learning platforms, huge data sets are made from different kinds of the collected traces. These traces differ from one learner to another according to their characteristics (learning styles, preferences, performed actions, etc.). Learners' traces are very heterogeneous and voluminous, so their treatments and exploitations are…

  7. Approaching Assessment from a Learning Perspective: Elevating Assessment beyond Technique

    ERIC Educational Resources Information Center

    Simms, Michele; George, Beena

    2014-01-01

    Assessment is a key process in assuring quality education but how is it linked to the scholarship of teaching and learning (SoTL)? How can we join teaching and learning to the assessment process rather than view it as a stand-alone component in course and/or program development? This paper explores the relationship between assessment and the SoTL…

  8. Multiple Serial List Learning with Two Mnemonic Techniques.

    ERIC Educational Resources Information Center

    Marston, Paul T.; Young, Robert K.

    The classic mnemonic for learning serial lists, the method of loci, and its modern counterpart, the peg system, were compared by having subjects learn three 20-item serial lists. In addition to the type of mnemonic training, list imagery was either high (rated 6-7) or medium (rated 4-5), and instructions were either progressive elaboration (e.g.,…

  9. Using Analogies as an Experiential Learning Technique in Multicultural Education

    ERIC Educational Resources Information Center

    Suthakaran, V.; Filsinger, Keri; White, Brittany

    2013-01-01

    In this article the authors specifically address the use of narratives in the form of analogies as an experiential learning activity. The use of analogies as an experiential learning tool in multicultural education can be helpful in a number of ways. Analogies provide an alternative tool for processing multicultural topics with students who have…

  10. Continuous Surveillance Technique for Flow Accelerated Corrosion of Pipe Wall Using Electromagnetic Acoustic Transducer

    NASA Astrophysics Data System (ADS)

    Kojima, F.; Kosaka, D.; Umetani, K.

    2011-06-01

    In this paper, we propose a on-line monitoring technique using electromagnetic acoustic transducer (EMAT). In the series of laboratory experiments, carbon steel pipes were used and each sample was fabricated to simulate FAC. Electromagnetic acoustic resonance method (EMAR) is successfully tested for pipe wall thickness measurements. The validity and the feasibility of our method are also demonstrated through the laboratory experiments.

  11. Comparative Study on the Different Testing Techniques in Tree Classification for Detecting the Learning Motivation

    NASA Astrophysics Data System (ADS)

    Juliane, C.; Arman, A. A.; Sastramihardja, H. S.; Supriana, I.

    2017-03-01

    Having motivation to learn is a successful requirement in a learning process, and needs to be maintained properly. This study aims to measure learning motivation, especially in the process of electronic learning (e-learning). Here, data mining approach was chosen as a research method. For the testing process, the accuracy comparative study on the different testing techniques was conducted, involving Cross Validation and Percentage Split. The best accuracy was generated by J48 algorithm with a percentage split technique reaching at 92.19 %. This study provided an overview on how to detect the presence of learning motivation in the context of e-learning. It is expected to be good contribution for education, and to warn the teachers for whom they have to provide motivation.

  12. Acceleration Techniques for Recombination of Gases in Electrolysis Microactuators with Nafion®-Coated Electrocatalyst.

    PubMed

    Sheybani, Roya; Meng, Ellis

    2015-12-31

    Recombination of electrolysis gases (oxidation of hydrogen and reduction of oxygen) is an important factor in operation efficiency of devices employing electrolysis such as actuators and also unitized regenerative fuel cells. Several methods of improving recombination speed and repeatability were developed for application to electrolysis microactuators with Nafion®-coated catalytic electrodes. Decreasing the electrolysis chamber volume increased the speed, consistency, and repeatability of the gas recombination rate. To further improve recombination performance, methods to increase the catalyst surface area, hydrophobicity, and availability were developed and evaluated. Of these, including in the electrolyte pyrolyzed-Nafion®-coated Pt segments contained in the actuator chamber accelerated recombination by increasing the catalyst surface area and decreasing the gas transport diffusion path. This approach also reduced variability in recombination encountered under varying actuator orientation (resulting in differing catalyst/gas bubble proximity) and increased the rate of recombination by 2.3 times across all actuator orientations. Repeatability of complete recombination for different generated gas volumes was studied through cycling.

  13. Sizing of single globular DNA molecules by using a circular acceleration technique with laser trapping.

    PubMed

    Hirano, Ken; Nagata, Hideya; Ishido, Tomomi; Tanaka, Yoshio; Baba, Yoshinobu; Ishikawa, Mitsuru

    2008-07-01

    We describe a method for in situ sizing individual huge DNA molecules by laser trapping. Single DNA molecules are reversibly transformed, without mechanical fragmentation of fragile huge-sized DNA, from their random coil state into their globular state induced by condensing agents poly(ethylene glycol) and Mg(2+). With the use of a globular DNA molecule folded by condensation, the critical velocity of the circularly accelerated single globular DNA molecule by laser trapping was found to be proportional to the size of the DNA. Yeast, Saccharomyces cerevisiae, chromosome III (285 kbp) was successfully sized (281 +/- 40 kbp) from a calibration curve scaled using lambda, T4, and yeast chromosome VI (48.5, 166, and 385 kbp, respectively). The use of critical velocity as a sizing parameter makes it possible to size single DNA molecules without prior conformational information, i.e., the radius of a single globular huge DNA molecule as a nanoparticle. A sized single globular DNA molecule could be trapped again for subsequent manipulation, such as transportation of it anywhere. We also investigated a possibility of reusing the globular DNA molecules condensed by PEG and Mg(2+) for PCR and found that PCR efficiency was not deteriorated in the presence of the condensation agents.

  14. Acceleration Techniques for Recombination of Gases in Electrolysis Microactuators with Nafion®-Coated Electrocatalyst

    PubMed Central

    Sheybani, Roya; Meng, Ellis

    2015-01-01

    Recombination of electrolysis gases (oxidation of hydrogen and reduction of oxygen) is an important factor in operation efficiency of devices employing electrolysis such as actuators and also unitized regenerative fuel cells. Several methods of improving recombination speed and repeatability were developed for application to electrolysis microactuators with Nafion®-coated catalytic electrodes. Decreasing the electrolysis chamber volume increased the speed, consistency, and repeatability of the gas recombination rate. To further improve recombination performance, methods to increase the catalyst surface area, hydrophobicity, and availability were developed and evaluated. Of these, including in the electrolyte pyrolyzed-Nafion®-coated Pt segments contained in the actuator chamber accelerated recombination by increasing the catalyst surface area and decreasing the gas transport diffusion path. This approach also reduced variability in recombination encountered under varying actuator orientation (resulting in differing catalyst/gas bubble proximity) and increased the rate of recombination by 2.3 times across all actuator orientations. Repeatability of complete recombination for different generated gas volumes was studied through cycling. PMID:26251561

  15. The cell-in-series method: A technique for accelerated electrode degradation in redox flow batteries

    SciTech Connect

    Pezeshki, Alan M.; Sacci, Robert L.; Veith, Gabriel M.; Zawodzinski, Thomas A.; Mench, Matthew M.

    2015-11-21

    Here, we demonstrate a novel method to accelerate electrode degradation in redox flow batteries and apply this method to the all-vanadium chemistry. Electrode performance degradation occurred seven times faster than in a typical cycling experiment, enabling rapid evaluation of materials. This method also enables the steady-state study of electrodes. In this manner, it is possible to delineate whether specific operating conditions induce performance degradation; we found that both aggressively charging and discharging result in performance loss. Post-mortem x-ray photoelectron spectroscopy of the degraded electrodes was used to resolve the effects of state of charge (SoC) and current on the electrode surface chemistry. For the electrode material tested in this work, we found evidence that a loss of oxygen content on the negative electrode cannot explain decreased cell performance. Furthermore, the effects of decreased electrode and membrane performance on capacity fade in a typical cycling battery were decoupled from crossover; electrode and membrane performance decay were responsible for a 22% fade in capacity, while crossover caused a 12% fade.

  16. The cell-in-series method: A technique for accelerated electrode degradation in redox flow batteries

    DOE PAGES

    Pezeshki, Alan M.; Sacci, Robert L.; Veith, Gabriel M.; ...

    2015-11-21

    Here, we demonstrate a novel method to accelerate electrode degradation in redox flow batteries and apply this method to the all-vanadium chemistry. Electrode performance degradation occurred seven times faster than in a typical cycling experiment, enabling rapid evaluation of materials. This method also enables the steady-state study of electrodes. In this manner, it is possible to delineate whether specific operating conditions induce performance degradation; we found that both aggressively charging and discharging result in performance loss. Post-mortem x-ray photoelectron spectroscopy of the degraded electrodes was used to resolve the effects of state of charge (SoC) and current on the electrodemore » surface chemistry. For the electrode material tested in this work, we found evidence that a loss of oxygen content on the negative electrode cannot explain decreased cell performance. Furthermore, the effects of decreased electrode and membrane performance on capacity fade in a typical cycling battery were decoupled from crossover; electrode and membrane performance decay were responsible for a 22% fade in capacity, while crossover caused a 12% fade.« less

  17. Decrystallization of Crystals Using Gold "Nano-Bullets" and the Metal-Assisted and Microwave-Accelerated Decrystallization Technique.

    PubMed

    Thompson, Nishone; Boone-Kukoyi, Zainab; Shortt, Raquel; Lansiquot, Carisse; Kioko, Bridgit; Bonyi, Enock; Toker, Salih; Ozturk, Birol; Aslan, Kadir

    2016-10-18

    Gout is caused by the overproduction of uric acid and the inefficient metabolism of dietary purines in humans. Current treatments of gout, which include anti-inflammatory drugs, cyclooxygenase-2 inhibitors, and systemic glucocorticoids, have harmful side-effects. Our research laboratory has recently introduced an innovative approach for the decrystallization of biological and chemical crystals using the Metal-Assisted and Microwave-Accelerated Evaporative Decrystallization (MAMAD) technique. In the MAMAD technique, microwave energy is used to heat and activate gold nanoparticles that behave as "nano-bullets" to rapidly disrupt the crystal structure of biological crystals placed on planar surfaces. In this study, crystals of various sizes and compositions were studied as models for tophaceous gout at different stages (i.e., uric acid as small crystals (~10-100 μm) and l-alanine as medium (~300 μm) and large crystals (~4400 μm). Our results showed that the use of the MAMAD technique resulted in the reduction of the size and number of uric acid and l-alanine crystals up to >40% when exposed to intermittent microwave heating (up to 20 W power at 8 GHz) in the presence of 20 nm gold nanoparticles up to 120 s. This study demonstrates that the MAMAD technique can be potentially used as an alternative therapeutic method for the treatment of gout by effective decrystallization of large crystals, similar in size to those that often occur in gout.

  18. Accelerating atomic-level protein simulations by flat-histogram techniques

    NASA Astrophysics Data System (ADS)

    Jónsson, Sigurður Ć.; Mohanty, Sandipan; Irbäck, Anders

    2011-09-01

    Flat-histogram techniques provide a powerful approach to the simulation of first-order-like phase transitions and are potentially very useful for protein studies. Here, we test this approach by implicit solvent all-atom Monte Carlo (MC) simulations of peptide aggregation, for a 7-residue fragment (GIIFNEQ) of the Cu/Zn superoxide dismutase 1 protein (SOD1). In simulations with 8 chains, we observe two distinct aggregated/non-aggregated phases. At the midpoint temperature, these phases coexist, separated by a free-energy barrier of height 2.7 kBT. We show that this system can be successfully studied by carefully implemented flat-histogram techniques. The frequency of barrier crossing, which is low in conventional canonical simulations, can be increased by turning to a two-step procedure based on the Wang-Landau and multicanonical algorithms.

  19. Differences in Effective Target Volume Between Various Techniques of Accelerated Partial Breast Irradiation

    SciTech Connect

    Shaitelman, Simona F.; Vicini, Frank A.; Grills, Inga S.; Martinez, Alvaro A.; Yan Di; Kim, Leonard H.

    2012-01-01

    Purpose: Different cavity expansions are used to define the clinical target volume (CTV) for accelerated partial breast irradiation (APBI) delivered via balloon brachytherapy (1 cm) vs. three-dimensional conformal radiotherapy (3D-CRT) (1.5 cm). Previous studies have argued that the CTVs generated by these different margins are effectively equivalent. In this study, we use deformable registration to assess the effective CTV treated by balloon brachytherapy on clinically representative 3D-CRT planning images. Methods and Materials: Ten patients previously treated with the MammoSite were studied. Each patient had two computed tomography (CT) scans, one acquired before and one after balloon implantation. In-house deformable registration software was used to deform the MammoSite CTV onto the balloonless CT set. The deformed CTV was validated using anatomical landmarks common to both CT scans. Results: The effective CTV treated by the MammoSite was on average 7% {+-} 10% larger and 38% {+-} 4% smaller than 3D-CRT CTVs created using uniform expansions of 1 and 1.5 cm, respectively. The average effective CTV margin was 1.0 cm, the same as the actual MammoSite CTV margin. However, the effective CTV margin was nonuniform and could range from 5 to 15 mm in any given direction. Effective margins <1 cm were attributable to poor cavity-balloon conformance. Balloon size relative to the cavity did not significantly correlate with the effective margin. Conclusion: In this study, the 1.0-cm MammoSite CTV margin treated an effective volume that was significantly smaller than the 3D-CRT CTV based on a 1.5-cm margin.

  20. Auto-adaptive robot-aided therapy using machine learning techniques.

    PubMed

    Badesa, Francisco J; Morales, Ricardo; Garcia-Aracil, Nicolas; Sabater, J M; Casals, Alicia; Zollo, Loredana

    2014-09-01

    This paper presents an application of a classification method to adaptively and dynamically modify the therapy and real-time displays of a virtual reality system in accordance with the specific state of each patient using his/her physiological reactions. First, a theoretical background about several machine learning techniques for classification is presented. Then, nine machine learning techniques are compared in order to select the best candidate in terms of accuracy. Finally, first experimental results are presented to show that the therapy can be modulated in function of the patient state using machine learning classification techniques.

  1. Application of wavelet packet entropy flow manifold learning in bearing factory inspection using the ultrasonic technique.

    PubMed

    Chen, Xiaoguang; Liu, Dan; Xu, Guanghua; Jiang, Kuosheng; Liang, Lin

    2014-12-26

    For decades, bearing factory quality evaluation has been a key problem and the methods used are always static tests. This paper investigates the use of piezoelectric ultrasonic transducers (PUT) as dynamic diagnostic tools and a relevant signal classification technique, wavelet packet entropy (WPEntropy) flow manifold learning, for the evaluation of bearing factory quality. The data were analyzed using wavelet packet entropy (WPEntropy) flow manifold learning. The results showed that the ultrasonic technique with WPEntropy flow manifold learning was able to detect different types of defects on the bearing components. The test method and the proposed technique are described and the different signals are analyzed and discussed.

  2. Application of Wavelet Packet Entropy Flow Manifold Learning in Bearing Factory Inspection Using the Ultrasonic Technique

    PubMed Central

    Chen, Xiaoguang; Liu, Dan; Xu, Guanghua; Jiang, Kuosheng; Liang, Lin

    2015-01-01

    For decades, bearing factory quality evaluation has been a key problem and the methods used are always static tests. This paper investigates the use of piezoelectric ultrasonic transducers (PUT) as dynamic diagnostic tools and a relevant signal classification technique, wavelet packet entropy (WPEntropy) flow manifold learning, for the evaluation of bearing factory quality. The data were analyzed using wavelet packet entropy (WPEntropy) flow manifold learning. The results showed that the ultrasonic technique with WPEntropy flow manifold learning was able to detect different types of defects on the bearing components. The test method and the proposed technique are described and the different signals are analyzed and discussed. PMID:25549173

  3. Accelerated Nursing Degree Programs: Insights into Teaching and Learning Experiences. New Careers in Nursing. Research Report. ETS RR-15-29

    ERIC Educational Resources Information Center

    Millett, Catherine M.; Stickler, Leslie M.; Wang, Haijiang

    2015-01-01

    The Study of Teaching and Learning in Accelerated Nursing Degree Programs explores how nurse educators are adapting their teaching practices for accelerated, second-degree nursing program students. To provide findings on topics including instructional practices and the roles and attitudes of faculty, a web survey was administered to almost 100…

  4. Applying an AR Technique to Enhance Situated Heritage Learning in a Ubiquitous Learning Environment

    ERIC Educational Resources Information Center

    Chang, Yi Hsing; Liu, Jen-ch'iang

    2013-01-01

    Since AR can display 3D materials and learner motivation is enhanced in a situated learning environment, this study explores the learning effectiveness of learners when combining AR technology and the situation learning theory. Based on the concept of embedding the characteristics of augmented reality and situated learning into a real situation to…

  5. The Accelerated Reader Program, Reading Achievement, and Attitudes of Students with Learning Disabilities.

    ERIC Educational Resources Information Center

    Scott, Louise Shewfelt

    This report discusses the outcomes of a study that investigated whether the Accelerated Reader program meets its claim to motivate and improve reading achievement for all students, including those with special needs. The Accelerated Reader program is a computer-based reading management system that includes a database of thousands of books ranging…

  6. Minimally Invasive Techniques to Accelerate the Orthodontic Tooth Movement: A Systematic Review of Animal Studies

    PubMed Central

    Qamruddin, Irfan; Alam, Mohammad Khursheed; Khamis, Mohd Fadhli; Husein, Adam

    2015-01-01

    Objective. To evaluate various noninvasive and minimally invasive procedures for the enhancement of orthodontic tooth movement in animals. Materials and Methods. Literature was searched using NCBI (PubMed, PubMed Central, and PubMed Health), MedPilot (Medline, Catalogue ZB MED, Catalogue Medicine Health, and Excerpta Medica Database (EMBASE)), and Google Scholar from January 2009 till 31 December 2014. We included original articles related to noninvasive and minimally invasive procedures to enhance orthodontic tooth movement in animals. Extraction of data and quality assessments were carried out by two observers independently. Results. The total number of hits was 9195 out of which just 11 fulfilled the inclusion criteria. Nine articles were good and 5 articles were moderate in quality. Low level laser therapy (LLLT) was among the most common noninvasive techniques whereas flapless corticision using various instruments was among the commonest minimally invasive procedures to enhance velocity of tooth movement. Conclusions. LLLT, low intensity pulsed ultrasound (LIPUS), mechanical vibration, and flapless corticision are emerging noninvasive and minimally invasive techniques which need further researches to establish protocols to use them clinically with conviction. PMID:26881201

  7. Accelerator-based analytical technique in the study of some anti-diabetic medicinal plants of Nigeria

    NASA Astrophysics Data System (ADS)

    Olabanji, S. O.; Omobuwajo, O. R.; Ceccato, D.; Adebajo, A. C.; Buoso, M. C.; Moschini, G.

    2008-05-01

    Diabetes mellitus, a clinical syndrome characterized by hyperglycemia due to deficiency of insulin, is a disease involving the endocrine pancreas and causes considerable morbidity and mortality in the world. In Nigeria, many plants, especially those implicated in herbal recipes for the treatment of diabetes, have not been screened for their elemental constituents while information on phytochemistry of some of them is not available. There is therefore the need to document these constituents as some of these plants are becoming increasingly important as herbal drugs or food additives. The accelerator-based technique PIXE, using the 1.8 MeV collimated proton beam from the 2.5 MV AN 2000 Van de Graaff accelerator at INFN, LNL, Legnaro (Padova) Italy, was employed in the determination of the elemental constituents of these anti-diabetic medicinal plants. Leaves of Gardenia ternifolia, Caesalpina pulcherrima, Solemostenon monostachys, whole plant of Momordica charantia and leaf and stem bark of Hunteria umbellata could be taken as vegetables, neutraceuticals, food additives and supplements in the management of diabetes. However, Hexabolus monopetalus root should be used under prescription.

  8. Action Research to Improve the Learning Space for Diagnostic Techniques.

    PubMed

    Ariel, Ellen; Owens, Leigh

    2015-12-01

    The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of "knowledge" and "understanding." The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engage in deep learning using a variety of learning styles. The effectiveness of the new curriculum was assessed by means of on-course student assessment throughout the module, a final exam, an anonymous questionnaire on student evaluation of the different activities and a focus group of volunteers. Although the new curriculum enabled a major part of the student cohort to achieve higher pass grades (p < 0.001), it did not meet the requirements of the weaker students, and the proportion of the students failing the module remained at 34%. The action research applied here provided a number of valuable suggestions from students on how to improve future curricula from their perspective. Most importantly, an interactive online program that facilitated flexibility in the learning space for the different reagents and their interaction in diagnostic tests was proposed. The methods applied to improve and assess a curriculum refresh by involving students as partners in the process, as well as the outcomes, are discussed. Journal of Microbiology & Biology Education.

  9. Using the PubMatrix literature-mining resource to accelerate student-centered learning in a veterinary problem-based learning curriculum.

    PubMed

    David, John; Irizarry, Kristopher J L

    2009-01-01

    Problem-based learning (PBL) creates an atmosphere in which veterinary students must take responsibility for their own education. Unlike a traditional curriculum where students receive discipline-specific information by attending formal lectures, PBL is designed to elicit self-directed, student-centered learning such that each student determines (1) what he/she does not know (learning issues), (2) what he/she needs to learn, (3) how he/she will learn it, and (4) what resources he/she will use. One of the biggest challenges facing students in a PBL curriculum is efficient time management while pursuing learning issues. Bioinformatics resources, such as the PubMatrix literature-mining tool, allow access to tremendous amounts of information almost instantaneously. To accelerate student-centered learning it is necessary to include resources that enhance the rate at which students can process biomedical information. Unlike using the PubMed interface directly, the PubMatrix tool enables users to automate queries, allowing up to 1,000 distinct PubMed queries to be executed per single PubMatrix submission. Users may submit multiple PubMatrix queries per session, resulting in the ability to execute tens of thousands of PubMed queries in a single day. The intuitively organized results, which remain accessible from PubMatrix user accounts, enable students to rapidly assimilate and process hundreds of thousands of individual publication records as they relate to the student's specific learning issues and query terms. Subsequently, students can explore substantially more of the biomedical publication landscape per learning issue and spend a greater fraction of their time actively engaged in resolving their learning issues.

  10. Two Active Learning Techniques Promoted Student Learning of Introductory Earth Science Concepts but Failed to Improve Metacognitive Skills

    NASA Astrophysics Data System (ADS)

    Mora, G.

    2010-12-01

    A consensus exists about the necessity to implement active learning instructional techniques in science classes to improve overall student learning, and in response to this need a number of instructional techniques have been developed. Some of these active learning methodologies have been implemented successfully, but no direct comparison between different instructional techniques exists to date. For that reason, the purpose of this study was to compare the effectiveness in student learning of two active learning methods: peer instruction and lecture tutorials. Evaluation of their effectiveness was measured through the Geoscience Concept Inventory, which was administered at the beginning (pre-test) and at the end (post-test) of each course. Both methods provided statistically significant cognitive knowledge and understanding gains, and both methods were equally effective. Despite these overall gains, about 15% of the students showed no significant gains as measured both by their GCI scores and course grades. A survey about how students study for the course revealed that whereas low performing students employed superficial strategies for learning, high performing students used deep and domain-specific strategies. Curiously, low performing students recommended the use of deeper approaches for learning, yet they themselves failed to employ them.

  11. Successful Application of Active Learning Techniques to Introductory Microbiology

    PubMed Central

    HOFFMAN, ELIZABETH A.

    2001-01-01

    While the traditional lecture format may be a successful way to teach microbiology to both medical and nursing students, it was not an effective means of learning for many prenursing and preprofessional students enrolled in either of the introductory microbiology courses at Ashland Community College, an open enrollment institution. The structure of both Medical Microbiology and Principles of Microbiology was redesigned to allow students to address the material in an active manner. Daily quizzes, student group discussions, scrapbooks, lab project presentations and papers, and extra credit projects were all added in order to allow students maximum exposure to the course material in a manner compatible with various methods of learning. Student knowledge, course evaluations, and student success rates have all improved with the active learning format. PMID:23653538

  12. Aluminum diffusion in Al-implanted AISI 321 stainless steel using accelerator-based characterization techniques

    NASA Astrophysics Data System (ADS)

    Noli, F.; Misaelides, P.; Bethge, K.

    1998-04-01

    The aluminum diffusion in near-surface layers of Al-implanted AISI 321 austenitic stainless steel (Fe/Cr18/Ni8/Ti) was studied using ion beam analysis techniques. The implanted samples were investigated at temperatures between 450°C and 650°C (treatment times up to 144 h in vacuum and in air). The Al-profiles were determined by the 992 keV resonance of the 27Al(p,γ) 28Si nuclear reaction as well as by 4He +-Rutherford Backscattering Spectrometry (RBS). The experimental diffusion coefficients, obtained during this study using Fick's second law, were compared with corresponding literature concerning the aluminum diffusion in other relevant metallic materials. The determination of the depth profiles contributes to the interpretation of the high temperature oxidation behavior of Al-implanted stainless steel surfaces.

  13. A Multi-Technique Approach for Effective Learning.

    ERIC Educational Resources Information Center

    Brillhart, L.; Debs, M. B.

    Triton College, under the auspices of a National Science Foundation grant, has designed a team taught course combining an engineering and rhetoric course in which students are introduced to the engineering profession and its communication techniques. The instructional technique is multi-faceted, integrating simulation of the professional…

  14. Literacy through Cooperative Learning: The Jigsaw Reading Technique. Monograph No. 7.

    ERIC Educational Resources Information Center

    Epstein, Ruth

    The jigsaw reading technique maximizes the interactive basis of cooperative learning. The advantages of cooperative learning are that it increases student independence; promotes peer teaching; can be used in multi-level classrooms; can be used in a variety of content areas; can be adapted for use in all age groups; promotes individual and group…

  15. A Systematic Characterization of Cognitive Techniques for Learning from Textual and Pictorial Representations

    ERIC Educational Resources Information Center

    Ploetzner, Rolf; Lowe, Richard; Schlag, Sabine

    2013-01-01

    Pictorial representations can play a pivotal role in both printed and digital learning material. Although there has been extensive research on cognitive techniques and strategies for learning from text, the same cannot be said for static and dynamic pictorial representations. In this paper we propose a systematic characterization of cognitive…

  16. Analysing Change in Learning Strategies over Time: A Comparison of Three Statistical Techniques

    ERIC Educational Resources Information Center

    Coertjens, Liesje; van Daal, Tine; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

    2013-01-01

    Change in learning strategies during higher education is an important topic of research when considering students' approaches to learning. Regarding the statistical techniques used to analyse this change, repeated measures ANOVA is mostly relied upon. Recently, multilevel and multi-indicator latent growth (MILG) analyses have been used as well.…

  17. Swarm Intelligence: New Techniques for Adaptive Systems to Provide Learning Support

    ERIC Educational Resources Information Center

    Wong, Lung-Hsiang; Looi, Chee-Kit

    2012-01-01

    The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…

  18. Towards Online Delivery of Process-Oriented Guided Inquiry Learning Techniques in Information Technology Courses

    ERIC Educational Resources Information Center

    Trevathan, Jarrod; Myers, Trina

    2013-01-01

    Process-Oriented Guided Inquiry Learning (POGIL) is a technique used to teach in large lectures and tutorials. It invokes interaction, team building, learning and interest through highly structured group work. Currently, POGIL has only been implemented in traditional classroom settings where all participants are physically present. However,…

  19. An Exploratory Investigation of the Effect on a Biofeedback Technique with Hyperactive, Learning Disabled Children.

    ERIC Educational Resources Information Center

    Martin, Larry L.; Hershey, Myrliss

    Studied was the effectiveness of biofeedback techniques in reducing the hyperactive behavior of five hyperactive and four nonhyperactive children (all in elementary level learning disability classes). After 10 15-minute biofeedback training sessions over an 8-week period, Ss learned to raise their finger temperatures an average of 12.92 degrees…

  20. The GenTechnique Project: Developing an Open Environment for Learning Molecular Genetics.

    ERIC Educational Resources Information Center

    Calza, R. E.; Meade, J. T.

    1998-01-01

    The GenTechnique project at Washington State University uses a networked learning environment for molecular genetics learning. The project is developing courseware featuring animation, hyper-link controls, and interactive self-assessment exercises focusing on fundamental concepts. The first pilot course featured a Web-based module on DNA…

  1. The Ticket to Retention: A Classroom Assessment Technique Designed to Improve Student Learning

    ERIC Educational Resources Information Center

    Divoll, Kent A.; Browning, Sandra T.; Vesey, Winona M.

    2012-01-01

    Classroom assessment techniques (CATs) or other closure activities are widely promoted for use in college classrooms. However, research on whether CATs improve student learning are mixed. The authors posit that the results are mixed because CATs were designed to "help teachers find out what students are learning in the classroom and how well…

  2. Learning for Semantic Parsing Using Statistical Syntactic Parsing Techniques

    DTIC Science & Technology

    2010-05-01

    Vasin Punyakanok, Dan Roth and Wen-tau Yih (2005). Generalized inference with multiple semantic role labeling systems. In Proceedings of the Ninth...Uncertainty in Artificial Intelligence (UAI- 2005). Edinburgh, Scotland . Luke S. Zettlemoyer and Michael Collins (2007). Online learning of relaxed

  3. Education as Liberation: The Politics and Techniques of Lifelong Learning

    ERIC Educational Resources Information Center

    Lambeir, Bert

    2005-01-01

    It is taken for granted that the complexity of the information society requires a reorientation of our being in the world. Not surprisingly, the call for lifelong learning and permanent education becomes louder and more intense every day. And while there are various worthwhile initiatives, like alphabetisation courses, the article argues that the…

  4. Cooperative Learning Technique through Internet Based Education: A Model Proposal

    ERIC Educational Resources Information Center

    Ozkan, Hasan Huseyin

    2010-01-01

    Internet is gradually becoming the most valuable learning environment for the people which form the information society. That the internet provides written, oral and visual communication between the participants who are at different places, that it enables the students' interaction with other students and teachers, and that it does these so fast…

  5. An Exploration of Prospective Teachers' Learning of Clinical Interview Techniques

    ERIC Educational Resources Information Center

    Groth, Randall E.; Bergner, Jennifer A.; Burgess, Claudia R.

    2016-01-01

    The present study followed four prospective teachers through the process of learning to interview during an undergraduate research project experience. Participants conducted and video recorded a series of interviews with children. They also carried out guided analyses of the videos and written artefacts from the interviews to formulate conjectures…

  6. Learning Organisations and Child Protection Agencies: Post-Fordist Techniques?

    ERIC Educational Resources Information Center

    Reich, Ann

    2002-01-01

    A study of child protection agencies in New South Wales shows how reforms involving a neoliberal interpretation of the learning organization, rather than encouraging teamwork and employee participation, are used to govern and control. Such new "technologies of training" demand changes in the character and identity of workers. (SK)

  7. Machine learning techniques for fault isolation and sensor placement

    NASA Technical Reports Server (NTRS)

    Carnes, James R.; Fisher, Douglas H.

    1993-01-01

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

  8. Using the Technique of Journal Writing to Learn Emergency Psychiatry

    ERIC Educational Resources Information Center

    Bhuvaneswar, Chaya; Stern, Theodore; Beresin, Eugene

    2009-01-01

    Objective: The authors discuss journal writing in learning emergency psychiatry. Methods: The journal of a psychiatry intern rotating through an emergency department is used as sample material for analysis that could take place in supervision or a resident support group. A range of articles are reviewed that illuminate the relevance of journal…

  9. Caspr3-Deficient Mice Exhibit Low Motor Learning during the Early Phase of the Accelerated Rotarod Task

    PubMed Central

    Hirata, Haruna; Takahashi, Aki; Shimoda, Yasushi; Koide, Tsuyoshi

    2016-01-01

    Caspr3 (Contactin-associated protein-like 3, Cntnap3) is a neural cell adhesion molecule belonging to the Caspr family. We have recently shown that Caspr3 is expressed abundantly between the first and second postnatal weeks in the mouse basal ganglia, including the striatum, external segment of the globus pallidus, subthalamic nucleus, and substantia nigra. However, its physiological role remains largely unknown. In this study, we conducted a series of behavioral analyses on Capsr3-knockout (KO) mice and equivalent wild-type (WT) mice to investigate the role of Caspr3 in brain function. No significant differences were observed in most behavioral traits between Caspr3-KO and WT mice, but we found that Caspr3-KO mice performed poorly during the early phase of the accelerated rotarod task in which latency to falling off a rod rotating with increasing velocity was examined. In the late phase, the performance of the Caspr3-KO mice caught up to the level of WT mice, suggesting that the deletion of Caspr3 caused a delay in motor learning. We then examined changes in neural activity after training on the accelerated rotarod by conducting immunohistochemistry using antibody to c-Fos, an indirect marker for neuronal activity. Experience of the accelerated rotarod task caused increases in the number of c-Fos-positive cells in the dorsal striatum, cerebellum, and motor cortex in both Caspr3-KO and WT mice, but the number of c-Fos-positive cells was significantly lower in the dorsal striatum of Caspr3-KO mice than in that of WT mice. The expression of c-Fos in the ventral striatum of Caspr3-KO and WT mice was not altered by the training. Our findings suggest that reduced activation of neural cells in the dorsal striatum in Caspr3-KO mice leads to a decline in motor learning in the accelerated rotarod task. PMID:26807827

  10. Infusing Motor Learning Research Into Neurorehabilitation Practice: A Historical Perspective With Case Exemplar From the Accelerated Skill Acquisition Program

    PubMed Central

    Winstein, Carolee; Lewthwaite, Rebecca; Blanton, Sarah R.; Wolf, Lois B.; Wishart, Laurie

    2016-01-01

    This special interest article provides a historical framework with a contemporary case example that traces the infusion of the science of motor learning into neurorehabilitation practice. The revolution in neuroscience provided the first evidence for learning-dependent neuroplasticity and presaged the role of motor learning as critical for restorative therapies after stroke. The scientific underpinnings of motor learning have continued to evolve from a dominance of cognitive or information processing perspectives to a blend with neural science and contemporary social-cognitive psychological science. Furthermore, advances in the science of behavior change have contributed insights into influences on sustainable and generalizable gains in motor skills and associated behaviors, including physical activity and other recovery-promoting habits. For neurorehabilitation, these insights have tremendous relevance for the therapist–patient interactions and relationships. We describe a principle-based intervention for neurorehabilitation termed the Accelerated Skill Acquisition Program that we developed. This approach emphasizes integration from a broad set of scientific lines of inquiry including the contemporary fields of motor learning, neuroscience, and the psychological science of behavior change. Three overlapping essential elements—skill acquisition, impairment mitigation, and motivational enhancements—are integrated. PMID:24828523

  11. Automatic particle selection from electron micrographs using machine learning techniques

    PubMed Central

    Sorzano, C.O.S.; Recarte, E.; Alcorlo, M.; Bilbao-Castro, J.R.; San-Martín, C.; Marabini, R.; Carazo, J.M.

    2009-01-01

    The 3D reconstruction of biological specimens using Electron Microscopy is currently capable of achieving subnanometer resolution. Unfortunately, this goal requires gathering tens of thousands of projection images that are frequently selected manually from micrographs. In this paper we introduce a new automatic particle selection that learns from the user which particles are of interest. The training phase is semi-supervised so that the user can correct the algorithm during picking and specifically identify incorrectly picked particles. By treating such errors specially, the algorithm attempts to minimize the number of false positives. We show that our algorithm is able to produce datasets with fewer wrongly selected particles than previously reported methods. Another advantage is that we avoid the need for an initial reference volume from which to generate picking projections by instead learning which particles to pick from the user. This package has been made publicly available in the open-source package Xmipp. PMID:19555764

  12. Optimization of Drive-Bunch Current Profile for Enhanced Transformer Ratio in Beam-Driven Acceleration Techniques

    SciTech Connect

    Lemery, F.; Mihalcea, D.; Prokop, C.R.; Piot, P.; /Northern Illinois U. /Fermilab

    2012-07-08

    In recent years, wakefield acceleration has gained attention due to its high acceleration gradients and cost effectiveness. In beam-driven wakefield acceleration, a critical parameter to optimize is the transformer ratio. It has been shown that current shaping of electron beams allows for enhanced (> 2) transformer ratios. In this paper we present the optimization of the pulse shape of the drive bunch for dielectric-wakefield acceleration.

  13. Dosimetric comparison of 3D conformal, IMRT, and V-MAT techniques for accelerated partial-breast irradiation (APBI).

    PubMed

    Qiu, Jian-Jian; Chang, Zheng; Horton, Janet K; Wu, Qing-Rong Jackie; Yoo, Sua; Yin, Fang-Fang

    2014-01-01

    The purpose is to dosimetrically compare the following 3 delivery techniques: 3-dimensional conformal radiation therapy (3D-CRT), intensity-modulated arc therapy (IMRT), and volumetric-modulated arc therapy (V-MAT) in the treatment of accelerated partial-breast irradiation (APBI). Overall, 16 patients with T1/2N0 breast cancer were treated with 3D-CRT (multiple, noncoplanar photon fields) on the RTOG 0413 partial-breast trial. These cases were subsequently replanned using static gantry IMRT and V-MAT technology to understand dosimetric differences among these 3 techniques. Several dosimetric parameters were used in plan quality evaluation, including dose conformity index (CI) and dose-volume histogram analysis of normal tissue coverage. Quality assurance studies including gamma analysis were performed to compare the measured and calculated dose distributions. The IMRT and V-MAT plans gave more conformal target dose distributions than the 3D-CRT plans (p < 0.05 in CI). The volume of ipsilateral breast receiving 5 and 10Gy was significantly less using the V-MAT technique than with either 3D-CRT or IMRT (p < 0.05). The maximum lung dose and the ipsilateral lung volume receiving 10 (V10) or 20Gy (V20) were significantly less with both V-MAT and IMRT (p < 0.05). The IMRT technique was superior to 3D-CRT and V-MAT of low dose distributions in ipsilateral lung (p < 0.05 in V5 and D5). The total mean monitor units (MUs) for V-MAT (621.0 ± 111.9) were 12.2% less than those for 3D-CRT (707.3 ± 130.9) and 46.5% less than those for IMRT (1161.4 ± 315.6) (p < 0.05). The average machine delivery time was 1.5 ± 0.2 minutes for the V-MAT plans, 7.0 ± 1.6 minutes for the 3D-CRT plans, and 11.5 ± 1.9 minutes for the IMRT plans, demonstrating much less delivery time for V-MAT. Based on this preliminary study, V-MAT and IMRT techniques offer improved dose conformity as compared with 3D-CRT techniques without increasing dose to the ipsilateral lung. In terms of MU and delivery

  14. Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: Initial results for vocal fold nodules

    PubMed Central

    Ghassemi, Marzyeh; Van Stan, Jarrad H.; Mehta, Daryush D.; Zañartu, Matías; Cheyne, Harold A.; Hillman, Robert E.; Guttag, John V.

    2014-01-01

    Voice disorders are medical conditions that often result from vocal abuse/misuse which is referred to generically as vocal hyperfunction. Standard voice assessment approaches cannot accurately determine the actual nature, prevalence, and pathological impact of hyperfunctional vocal behaviors because such behaviors can vary greatly across the course of an individual’s typical day and may not be clearly demonstrated during a brief clinical encounter. Thus, it would be clinically valuable to develop non-invasive ambulatory measures that can reliably differentiate vocal hyperfunction from normal patterns of vocal behavior. As an initial step towards this goal we used an accelerometer taped to the neck surface to provide a continuous, non-invasive acceleration signal designed to capture some aspects of vocal behavior related to a common manifestation of vocal hyperfunction; vocal cord nodules. We gathered data from 12 female adult patients diagnosed with vocal fold nodules and 12 control speakers matched for age and occupation. We derived features from weeklong neck-surface acceleration recordings by using distributions of sound pressure level and fundamental frequency over five-minute windows of the acceleration signal and normalized these features so that inter-subject comparisons were meaningful. We then used supervised machine learning to show that the two groups exhibit distinct vocal behaviors that can be detected using the acceleration signal. We were able to correctly classify 22 of the 24 subjects, suggesting that in the future measures of the acceleration signal could be used to detect patients with the types of aberrant vocal behaviors that are associated with hyperfunctional voice disorders. PMID:24845276

  15. The Effect of Multimodal Remedial Techniques on the Spelling Ability of Learning Disabled Children

    ERIC Educational Resources Information Center

    Narang, Susheela; Gupta, Raj K.

    2014-01-01

    The purpose of the study was to examine the effectiveness of three remedial techniques to improve the spelling ability of students with learning disability. The three techniques, namely, TAK/v, visual orthographic method and listen, speak, read and write (LSRW) method were administered to three experimental groups, each having 13 students with…

  16. Kernel-based machine learning techniques for infrasound signal classification

    NASA Astrophysics Data System (ADS)

    Tuma, Matthias; Igel, Christian; Mialle, Pierrick

    2014-05-01

    Infrasound monitoring is one of four remote sensing technologies continuously employed by the CTBTO Preparatory Commission. The CTBTO's infrasound network is designed to monitor the Earth for potential evidence of atmospheric or shallow underground nuclear explosions. Upon completion, it will comprise 60 infrasound array stations distributed around the globe, of which 47 were certified in January 2014. Three stages can be identified in CTBTO infrasound data processing: automated processing at the level of single array stations, automated processing at the level of the overall global network, and interactive review by human analysts. At station level, the cross correlation-based PMCC algorithm is used for initial detection of coherent wavefronts. It produces estimates for trace velocity and azimuth of incoming wavefronts, as well as other descriptive features characterizing a signal. Detected arrivals are then categorized into potentially treaty-relevant versus noise-type signals by a rule-based expert system. This corresponds to a binary classification task at the level of station processing. In addition, incoming signals may be grouped according to their travel path in the atmosphere. The present work investigates automatic classification of infrasound arrivals by kernel-based pattern recognition methods. It aims to explore the potential of state-of-the-art machine learning methods vis-a-vis the current rule-based and task-tailored expert system. To this purpose, we first address the compilation of a representative, labeled reference benchmark dataset as a prerequisite for both classifier training and evaluation. Data representation is based on features extracted by the CTBTO's PMCC algorithm. As classifiers, we employ support vector machines (SVMs) in a supervised learning setting. Different SVM kernel functions are used and adapted through different hyperparameter optimization routines. The resulting performance is compared to several baseline classifiers. All

  17. Applying effective teaching and learning techniques to nephrology education

    PubMed Central

    Rondon-Berrios, Helbert; Johnston, James R.

    2016-01-01

    The interest in nephrology as a career has declined over the last several years. Some of the reasons cited for this decline include the complexity of the specialty, poor mentoring and inadequate teaching of nephrology from medical school through residency. The purpose of this article is to introduce the reader to advances in the science of adult learning, illustrate best teaching practices in medical education that can be extrapolated to nephrology and introduce the basic teaching methods that can be used on the wards, in clinics and in the classroom. PMID:27679724

  18. Introducing Social Stratification and Inequality: An Active Learning Technique.

    ERIC Educational Resources Information Center

    McCammon, Lucy

    1999-01-01

    Summarizes literature on techniques for teaching social stratification. Describes the three parts of an exercise that enables students to understand economic and political inequality: students are given a family scenario, create household budgets, and finally rework the national budget with their family scenario groups. Discusses student…

  19. Transactional Space: Feedback, Critical Thinking, and Learning Dance Technique

    ERIC Educational Resources Information Center

    Akinleye, Adesola; Payne, Rose

    2016-01-01

    This article explores attitudes about feedback and critical thinking in dance technique classes. The authors discuss an expansion of their teaching practices to include feedback as bidirectional (transactional) and a part of developing critical thinking skills in student dancers. The article was written after the authors undertook research…

  20. Integrative Teaching Techniques and Improvement of German Speaking Learning Skills

    ERIC Educational Resources Information Center

    Litualy, Samuel Jusuf

    2016-01-01

    This research ist a Quasi-Experimental research which only applied to one group without comparison group. It aims to prove whether the implementation of integrative teaching technique has influenced the speaking skill of the students in German Education Study Program of FKIP, Pattimura University. The research was held in the German Education…

  1. "PowerPoint[R] Engagement" Techniques to Foster Deep Learning

    ERIC Educational Resources Information Center

    Berk, Ronald A.

    2011-01-01

    The purpose of this article is to describe a bunch of strategies with which teachers may already be familiar and, perhaps, use regularly, but not always in the context of a formal PowerPoint[R] presentation. Here are the author's top 10 engagement techniques that fit neatly within any version of PowerPoint[R]. Some of these may also be used with…

  2. Accelerating the Use of Weblogs as an Alternative Method to Deliver Case-Based Learning

    ERIC Educational Resources Information Center

    Chen, Charlie; Wu, Jiinpo; Yang, Samuel C.

    2008-01-01

    Weblog technology is an alternative medium to deliver the case-based method of learning business concepts. The social nature of this technology can potentially promote active learning and enhance analytical ability of students. The present research investigates the primary factors contributing to the adoption of Weblog technology by students to…

  3. 76 FR 50224 - Medicare Program; Accountable Care Organization Accelerated Development Learning Sessions; Center...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-12

    ... register a team of senior executives to attend the in-person ADLS. The ADLS will provide executives with the opportunity to learn about core functions of an ACO and ways to build their organization's... intended to provide ACOs with the opportunity to learn from their peers about essential ACO functions...

  4. 76 FR 66931 - Medicare Program; Accountable Care Organization Accelerated Development Learning Sessions; Center...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-28

    ... register a team of senior executives to attend the in- person ADLS. The ADLS will provide executives with the opportunity to learn about core functions of an ACO and ways to build their organization's... provide ACOs with the opportunity to learn from their peers about essential ACO functions and various...

  5. The Accelerating Roles of Higher Education in Regions through the European Lifelong Learning Initiative

    ERIC Educational Resources Information Center

    Nemeth, Balazs

    2010-01-01

    This article assesses the network development and promotion of the learning region model in HEIs in the framework of the European Higher Education Area (EHEA), focusing on quality, partnership and social equality in the Hungarian context. It argues that the learning city-region model can be used and put into practice in many different ways for a…

  6. FRC Separatrix inference using machine-learning techniques

    NASA Astrophysics Data System (ADS)

    Romero, Jesus; Roche, Thomas; the TAE Team

    2016-10-01

    As Field Reversed Configuration (FRC) devices approach lifetimes exceeding the characteristic time of conductive structures external to the plasma, plasma stabilization cannot be achieved solely by the flux conserving effect of the external structures, and active control systems are then necessary. An essential component of such control systems is a reconstruction method for the plasma separatrix suitable for real time. We report on a method to infer the separatrix in an FRC using the information of magnetic probes located externally to the plasma. The method uses machine learning methods, namely Bayesian inference of Gaussian Processes, to obtain the most likely plasma current density distribution given the measurements of magnetic field external to the plasma. From the current sources, flux function and in particular separatrix are easily computed. The reconstruction method is non iterative and hence suitable for deterministic real time applications. Validation results with numerical simulations and application to separatrix inference of C-2U plasma discharges will be presented.

  7. Social Capital and Geography of Learning: Roles in Accelerating the Spread of Integrated Pest Management

    ERIC Educational Resources Information Center

    Palis, Florencia G.; Morin, Stephen; Hossain, Mahabub

    2005-01-01

    This paper aims to show the relevance of spatial proximity and social capital in accelerating the spread of agricultural technologies such as integrated pest management (IPM). The research was done in response to the problem of slow diffusion of agricultural technologies. Both quantitative and qualitative methods were used in investigating the…

  8. Higher Level Open Distance Learning in Europe: The Accelerating Pace of Change.

    ERIC Educational Resources Information Center

    D'Azevedo, R. Charters

    1992-01-01

    Europe's socioeconomic climate will undergo rapid change as the single market becomes a reality and technological change accelerates. With companies in some countries now spending more collectively on training than their governments spend on the higher education sector, it is essential to map out a new European strategy for training for the 1990s.…

  9. An investigation of errorless learning in memory-impaired patients: improving the technique and clarifying theory.

    PubMed

    Tailby, Rebecca; Haslam, Catherine

    2003-01-01

    In rehabilitating individuals who demonstrate severe memory impairment, errorless learning techniques have proven particularly effective. Prevention of errors during acquisition of information leads to better memory than does learning under errorful conditions. This paper presents results of a study investigating errorless learning in three patient groups: those demonstrating mild, moderate, and severe memory impairments. The first goal of the study was to trial a new version of errorless learning, one encouraging more active participation in learning by patients via the use of elaboration and self-generation. This technique led to significantly better memory performance than seen under standard errorless conditions. This finding highlights the value of encouraging active and meaningful involvement by patients in errorless learning, to build upon the benefits flowing from error prevention. A second goal of the study was to clarify the mechanisms underlying errorless learning. Memory performance under errorless and errorful conditions was compared within and across each group of patients, to facilitate theoretical insight into the memory processes underlying performance. The pattern of results observed was equivocal. The data most strongly supported the hypothesis that the benefits seen under errorless learning reflect the operation of residual explicit memory processes, however a concurrent role for implicit memory processes was not ruled out.

  10. Missing the Trees for the Forest?: Learning Environments versus Learning Techniques in Simulations

    ERIC Educational Resources Information Center

    Raymond, Chad

    2012-01-01

    Institutions of higher learning are increasingly asked to defend curricular and pedagogical outcomes. Faculty must demonstrate that simulations are productive tools for learning, but a review of the literature shows that the evidence of their effectiveness is inconclusive, despite their popularity in the classroom. Simulations may in fact help…

  11. Examining Online Learning Patterns with Data Mining Techniques in Peer-Moderated and Teacher-Moderated Courses

    ERIC Educational Resources Information Center

    Hung, Jui-Long; Crooks, Steven M.

    2009-01-01

    The student learning process is important in online learning environments. If instructors can "observe" online learning behaviors, they can provide adaptive feedback, adjust instructional strategies, and assist students in establishing patterns of successful learning activities. This study used data mining techniques to examine and…

  12. Applying manifold learning techniques to the CAESAR database

    NASA Astrophysics Data System (ADS)

    Mendoza-Schrock, Olga; Patrick, James; Arnold, Gregory; Ferrara, Matthew

    2010-04-01

    Understanding and organizing data is the first step toward exploiting sensor phenomenology for dismount tracking. What image features are good for distinguishing people and what measurements, or combination of measurements, can be used to classify the dataset by demographics including gender, age, and race? A particular technique, Diffusion Maps, has demonstrated the potential to extract features that intuitively make sense [1]. We want to develop an understanding of this tool by validating existing results on the Civilian American and European Surface Anthropometry Resource (CAESAR) database. This database, provided by the Air Force Research Laboratory (AFRL) Human Effectiveness Directorate and SAE International, is a rich dataset which includes 40 traditional, anthropometric measurements of 4400 human subjects. If we could specifically measure the defining features for classification, from this database, then the future question will then be to determine a subset of these features that can be measured from imagery. This paper briefly describes the Diffusion Map technique, shows potential for dimension reduction of the CAESAR database, and describes interesting problems to be further explored.

  13. Resistance gene identification from Larimichthys crocea with machine learning techniques

    PubMed Central

    Cai, Yinyin; Liao, Zhijun; Ju, Ying; Liu, Juan; Mao, Yong; Liu, Xiangrong

    2016-01-01

    The research on resistance genes (R-gene) plays a vital role in bioinformatics as it has the capability of coping with adverse changes in the external environment, which can form the corresponding resistance protein by transcription and translation. It is meaningful to identify and predict R-gene of Larimichthys crocea (L.Crocea). It is friendly for breeding and the marine environment as well. Large amounts of L.Crocea’s immune mechanisms have been explored by biological methods. However, much about them is still unclear. In order to break the limited understanding of the L.Crocea’s immune mechanisms and to detect new R-gene and R-gene-like genes, this paper came up with a more useful combination prediction method, which is to extract and classify the feature of available genomic data by machine learning. The effectiveness of feature extraction and classification methods to identify potential novel R-gene was evaluated, and different statistical analyzes were utilized to explore the reliability of prediction method, which can help us further understand the immune mechanisms of L.Crocea against pathogens. In this paper, a webserver called LCRG-Pred is available at http://server.malab.cn/rg_lc/. PMID:27922074

  14. Resistance gene identification from Larimichthys crocea with machine learning techniques

    NASA Astrophysics Data System (ADS)

    Cai, Yinyin; Liao, Zhijun; Ju, Ying; Liu, Juan; Mao, Yong; Liu, Xiangrong

    2016-12-01

    The research on resistance genes (R-gene) plays a vital role in bioinformatics as it has the capability of coping with adverse changes in the external environment, which can form the corresponding resistance protein by transcription and translation. It is meaningful to identify and predict R-gene of Larimichthys crocea (L.Crocea). It is friendly for breeding and the marine environment as well. Large amounts of L.Crocea’s immune mechanisms have been explored by biological methods. However, much about them is still unclear. In order to break the limited understanding of the L.Crocea’s immune mechanisms and to detect new R-gene and R-gene-like genes, this paper came up with a more useful combination prediction method, which is to extract and classify the feature of available genomic data by machine learning. The effectiveness of feature extraction and classification methods to identify potential novel R-gene was evaluated, and different statistical analyzes were utilized to explore the reliability of prediction method, which can help us further understand the immune mechanisms of L.Crocea against pathogens. In this paper, a webserver called LCRG-Pred is available at http://server.malab.cn/rg_lc/.

  15. Systematic infrared image quality improvement using deep learning based techniques

    NASA Astrophysics Data System (ADS)

    Zhang, Huaizhong; Casaseca-de-la-Higuera, Pablo; Luo, Chunbo; Wang, Qi; Kitchin, Matthew; Parmley, Andrew; Monge-Alvarez, Jesus

    2016-10-01

    Infrared thermography (IRT, or thermal video) uses thermographic cameras to detect and record radiation in the longwavelength infrared range of the electromagnetic spectrum. It allows sensing environments beyond the visual perception limitations, and thus has been widely used in many civilian and military applications. Even though current thermal cameras are able to provide high resolution and bit-depth images, there are significant challenges to be addressed in specific applications such as poor contrast, low target signature resolution, etc. This paper addresses quality improvement in IRT images for object recognition. A systematic approach based on image bias correction and deep learning is proposed to increase target signature resolution and optimise the baseline quality of inputs for object recognition. Our main objective is to maximise the useful information on the object to be detected even when the number of pixels on target is adversely small. The experimental results show that our approach can significantly improve target resolution and thus helps making object recognition more efficient in automatic target detection/recognition systems (ATD/R).

  16. TDCS Guided using fMRI Significantly Accelerates Learning to Identify Concealed Objects

    PubMed Central

    Clark, Vincent P.; Coffman, Brian A.; Mayer, Andy R.; Weisend, Michael P.; Lane, Terran D.R.; Calhoun, Vince D.; Raybourn, Elaine M.; Garcia, Christopher M.; Wassermann, Eric M.

    2011-01-01

    The accurate identification of obscured and concealed objects in complex environments was an important skill required for survival during human evolution, and is required today for many forms of expertise. Here we used transcranial direct current stimulation (tDCS) guided using neuroimaging to increase learning rate in a novel, minimally guided discovery-learning paradigm. Ninety-six subjects identified threat-related objects concealed in naturalistic virtual surroundings used in real-world training. A variety of brain networks were found using fMRI data collected at different stages of learning, with two of these networks focused in right inferior frontal and right parietal cortex. Anodal 2.0 mA tDCS performed for 30 minutes over these regions in a series of single-blind, randomized studies resulted in significant improvements in learning and performance compared with 0.1 mA tDCS. This difference in performance increased to a factor of two after a one-hour delay. A dose-response effect of current strength on learning was also found. Taken together, these brain imaging and stimulation studies suggest that right frontal and parietal cortex are involved in learning to identify concealed objects in naturalistic surroundings. Furthermore, they suggest that the application of anodal tDCS over these regions can greatly increase learning, resulting in one of the largest effects on learning yet reported. The methods developed here may be useful to decrease the time required to attain expertise in a variety of settings. PMID:21094258

  17. Applying machine learning techniques to DNA sequence analysis

    SciTech Connect

    Shavlik, J.W. . Dept. of Computer Sciences); Noordewier, M.O. . Dept. of Computer Science)

    1992-01-01

    We are primarily developing a machine teaming (ML) system that modifies existing knowledge about specific types of biological sequences. It does this by considering sample members and nonmembers of the sequence motif being teamed. Using this information, our teaming algorithm produces a more accurate representation of the knowledge needed to categorize future sequences. Specifically, our KBANN algorithm maps inference rules about a given recognition task into a neural network. Neural network training techniques then use the training examples to refine these inference rules. We call these rules a domain theory, following the convention in the machine teaming community. We have been applying this approach to several problems in DNA sequence analysis. In addition, we have been extending the capabilities of our teaming system along several dimensions. We have also been investigating parallel algorithms that perform sequence alignments in the presence of frameshift errors.

  18. Machine learning and spectral techniques for lithological classification

    NASA Astrophysics Data System (ADS)

    Parakh, Khushboo; Thakur, Sanchari; Chudasama, Bijal; Tirodkar, Siddhesh; Porwal, Alok; Bhattacharya, Avik

    2016-04-01

    Experimentations with applications of machine learning algorithms such as random forest (RF), support vector machines (SVM) and fuzzy inference system (FIS) to lithological classification of multispectral datasets are described. The input dataset such as LANDSAT-8 and Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) in conjunction with Shuttle Radar Topography Mission (SRTM) digital elevation are used. The training data included image pixels with known lithoclasses as well as the laboratory spectra of field samples of the major lithoclasses. The study area is a part of Ajmer and Pali Districts, Western Rajasthan, India. The main lithoclasses exposed in the area are amphibolite, granite, calc-silicates, mica-schist, pegmatite and carbonates. In a parallel implementation, spectral parameters derived from the continuum-removed laboratory spectra of the field samples (e.g., band depth) were used in spectral matching algorithms to generate geological maps from the LANDSAT-8 and ASTER data. The classification results indicate that, as compared to the SVM, the RF algorithm provides higher accuracy for the minority class, while for the rest of the classes the two algorithms are comparable. The RF algorithm effectively deals with outliers and also ranks the input spectral bands based on their importance in classification. The FIS approach provides an efficient expert-driven system for lithological classification. It based on matching the image spectral features with the absorption features of the laboratory spectra of the field samples, and returns comparable results for some lithoclasses. The study also establishes spectral parameters of amphibolite, granite, calc-silicates, mica-schist, pegmatite and carbonates that can be used in generating geological maps from multispectral data using spectral matching algorithms.

  19. Prediction in Health Domain Using Bayesian Networks Optimization Based on Induction Learning Techniques

    NASA Astrophysics Data System (ADS)

    Felgaer, Pablo; Britos, Paola; García-Martínez, Ramón

    A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and flexible methods of reasoning. Obtaining it from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper we define an automatic learning method that optimizes the Bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain.

  20. Developing Design Principles for an E-Learning Programme for SME Managers to Support Accelerated Learning at the Workplace

    ERIC Educational Resources Information Center

    Moon, Suzie; Birchall, David; Williams, Sadie; Vrasidas, Charalambos

    2005-01-01

    Purpose: This paper reports on the development of a workplace-based e-learning programme for small and medium enterprise (SME) managers in five European countries. The course is designed to address the specific needs of SME managers who, it has been noted, represent a significant proportion of the EU workforce but often experience difficulty in…

  1. Accelerating the reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning using CUDA.

    PubMed

    Jiansen Li; Jianqi Sun; Ying Song; Yanran Xu; Jun Zhao

    2014-01-01

    An effective way to improve the data acquisition speed of magnetic resonance imaging (MRI) is using under-sampled k-space data, and dictionary learning method can be used to maintain the reconstruction quality. Three-dimensional dictionary trains the atoms in dictionary in the form of blocks, which can utilize the spatial correlation among slices. Dual-dictionary learning method includes a low-resolution dictionary and a high-resolution dictionary, for sparse coding and image updating respectively. However, the amount of data is huge for three-dimensional reconstruction, especially when the number of slices is large. Thus, the procedure is time-consuming. In this paper, we first utilize the NVIDIA Corporation's compute unified device architecture (CUDA) programming model to design the parallel algorithms on graphics processing unit (GPU) to accelerate the reconstruction procedure. The main optimizations operate in the dictionary learning algorithm and the image updating part, such as the orthogonal matching pursuit (OMP) algorithm and the k-singular value decomposition (K-SVD) algorithm. Then we develop another version of CUDA code with algorithmic optimization. Experimental results show that more than 324 times of speedup is achieved compared with the CPU-only codes when the number of MRI slices is 24.

  2. Humanized Foxp2 accelerates learning by enhancing transitions from declarative to procedural performance.

    PubMed

    Schreiweis, Christiane; Bornschein, Ulrich; Burguière, Eric; Kerimoglu, Cemil; Schreiter, Sven; Dannemann, Michael; Goyal, Shubhi; Rea, Ellis; French, Catherine A; Puliyadi, Rathi; Groszer, Matthias; Fisher, Simon E; Mundry, Roger; Winter, Christine; Hevers, Wulf; Pääbo, Svante; Enard, Wolfgang; Graybiel, Ann M

    2014-09-30

    The acquisition of language and speech is uniquely human, but how genetic changes might have adapted the nervous system to this capacity is not well understood. Two human-specific amino acid substitutions in the transcription factor forkhead box P2 (FOXP2) are outstanding mechanistic candidates, as they could have been positively selected during human evolution and as FOXP2 is the sole gene to date firmly linked to speech and language development. When these two substitutions are introduced into the endogenous Foxp2 gene of mice (Foxp2(hum)), cortico-basal ganglia circuits are specifically affected. Here we demonstrate marked effects of this humanization of Foxp2 on learning and striatal neuroplasticity. Foxp2(hum/hum) mice learn stimulus-response associations faster than their WT littermates in situations in which declarative (i.e., place-based) and procedural (i.e., response-based) forms of learning could compete during transitions toward proceduralization of action sequences. Striatal districts known to be differently related to these two modes of learning are affected differently in the Foxp2(hum/hum) mice, as judged by measures of dopamine levels, gene expression patterns, and synaptic plasticity, including an NMDA receptor-dependent form of long-term depression. These findings raise the possibility that the humanized Foxp2 phenotype reflects a different tuning of corticostriatal systems involved in declarative and procedural learning, a capacity potentially contributing to adapting the human brain for speech and language acquisition.

  3. Machine learning techniques accurately classify microbial communities by bacterial vaginosis characteristics.

    PubMed

    Beck, Daniel; Foster, James A

    2014-01-01

    Microbial communities are important to human health. Bacterial vaginosis (BV) is a disease associated with the vagina microbiome. While the causes of BV are unknown, the microbial community in the vagina appears to play a role. We use three different machine-learning techniques to classify microbial communities into BV categories. These three techniques include genetic programming (GP), random forests (RF), and logistic regression (LR). We evaluate the classification accuracy of each of these techniques on two different datasets. We then deconstruct the classification models to identify important features of the microbial community. We found that the classification models produced by the machine learning techniques obtained accuracies above 90% for Nugent score BV and above 80% for Amsel criteria BV. While the classification models identify largely different sets of important features, the shared features often agree with past research.

  4. Machine Learning Techniques Accurately Classify Microbial Communities by Bacterial Vaginosis Characteristics

    PubMed Central

    Beck, Daniel; Foster, James A.

    2014-01-01

    Microbial communities are important to human health. Bacterial vaginosis (BV) is a disease associated with the vagina microbiome. While the causes of BV are unknown, the microbial community in the vagina appears to play a role. We use three different machine-learning techniques to classify microbial communities into BV categories. These three techniques include genetic programming (GP), random forests (RF), and logistic regression (LR). We evaluate the classification accuracy of each of these techniques on two different datasets. We then deconstruct the classification models to identify important features of the microbial community. We found that the classification models produced by the machine learning techniques obtained accuracies above 90% for Nugent score BV and above 80% for Amsel criteria BV. While the classification models identify largely different sets of important features, the shared features often agree with past research. PMID:24498380

  5. Classification of the Regional Ionospheric Disturbance Based on Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Terzi, Merve Begum; Arikan, Orhan; Karatay, Secil; Arikan, Feza; Gulyaeva, Tamara

    2016-08-01

    In this study, Total Electron Content (TEC) estimated from GPS receivers is used to model the regional and local variability that differs from global activity along with solar and geomagnetic indices. For the automated classification of regional disturbances, a classification technique based on a robust machine learning technique that have found wide spread use, Support Vector Machine (SVM) is proposed. Performance of developed classification technique is demonstrated for midlatitude ionosphere over Anatolia using TEC estimates generated from GPS data provided by Turkish National Permanent GPS Network (TNPGN-Active) for solar maximum year of 2011. As a result of implementing developed classification technique to Global Ionospheric Map (GIM) TEC data, which is provided by the NASA Jet Propulsion Laboratory (JPL), it is shown that SVM can be a suitable learning method to detect anomalies in TEC variations.

  6. Solute redistribution and constitutional supercooling effects in vertical Bridgman grown indium gallium antimonide by accelerated crucible rotation technique

    NASA Astrophysics Data System (ADS)

    Vogel, K. Juliet

    The ternary alloy, InxGa1- xSb, is a compound semiconducting material of compositionally tunable bandgap (0.18 - 0.72 eV), making it desirable for use in photovoltaic, photodetector, and other opto-electronic devices in the infra-red regime. In the past, this material has proven to be difficult to synthesize in bulk due to the large phase separation between the constituent binaries. In this work, InxGa1-xSb has been grown in a state-of-the-art, computer-controlled system based on vertical Bridgman technique designed to allow crucible rotation during solidification of the material to reincorporate excess solute and improve material quality. Independent thermocouples allow for in situ monitoring and maintenance of the temperature to 0.2°C precision during crystal growth, reducing compositional inhomogeneities caused by temperature fluctuations. A series of experiments has been performed to evaluate the effect of accelerated crucible rotation technique (ACRT) on the structural quality and compositional homogeneity of bulk-grown InxGa 1-xSb for a starting melt composition of x = 0.25. A lowering rate of 3 mm/hr has been employed, for an overall cooling rate of 5.1°C/hr, which deliberately exceeds the threshold for constitutional supercooling. Scanning electron microscopy (SEM) has been performed on samples of In0.18Ga0.82Sb revealing a 92% percent reduction in micro-cracking with the application of ACRT when compared to synthesis performed without rotation. Furthermore; electron probe microscopy (EPMA) indicates an order of magnitude improvement in compositional homogeneity in the direction of growth with the use of ACRT. Micro-cracking and compositional homogeneity throughout cross-sections of InxGa1-xSb material also indicate areas of improved mixing during solidification, which can be compared to existing models of fluid flow exhibited in ACRT. The boule synthesized with ACRT shows a decrease in compositional deviation of 62% in the first-to-freeze areas of the

  7. Experiencing Mathematics for Connected Understanding: Using the RAMR Framework for Accelerating Students' Learning

    ERIC Educational Resources Information Center

    Nutchey, David; Grant, Edlyn; English, Lyn

    2016-01-01

    This paper reports on the use of the RAMR framework within a curriculum project. Description of the RAMR framework's theoretical bases is followed by two descriptions of students' learning in the classroom. Implications include the need for the teacher to connect student activities in a structured sequence, although this may be predicated on the…

  8. Coaches' and New Urban Teachers' Perceptions of Induction Coaching: Time, Trust, and Accelerated Learning Curves

    ERIC Educational Resources Information Center

    Gardiner, Wendy

    2012-01-01

    Approximately 80% of new teachers have mentors, yet mentoring typically fails to foster new teachers' professional learning--particularly in high-poverty schools. This qualitative study was situated within an urban teacher residency context and explored how six first-year urban teachers and the two induction mentors with whom they worked perceived…

  9. Year 7 Accelerated Learning Curriculum 2006-2010: From a Concept to an Outstanding Curriculum

    ERIC Educational Resources Information Center

    Creswell, Ian

    2011-01-01

    The author, Head of Year 7 at Cantell Maths and Computing College in Southampton, describes the development of an innovative approach to Year 7, which is based on the Qualifications and Curriculum Development Agency programme "Personal, Learning and Thinking Skills". He shows how the new approach evolved and continues to develop…

  10. Fluoxetine Restores Spatial Learning but Not Accelerated Forgetting in Mesial Temporal Lobe Epilepsy

    ERIC Educational Resources Information Center

    Barkas, Lisa; Redhead, Edward; Taylor, Matthew; Shtaya, Anan; Hamilton, Derek A.; Gray, William P.

    2012-01-01

    Learning and memory dysfunction is the most common neuropsychological effect of mesial temporal lobe epilepsy, and because the underlying neurobiology is poorly understood, there are no pharmacological strategies to help restore memory function in these patients. We have demonstrated impairments in the acquisition of an allocentric spatial task,…

  11. Record, Replay, Reflect: Videotaped Lessons Accelerate Learning for Teachers and Coaches

    ERIC Educational Resources Information Center

    Knight, Jim; Bradley, Barbara A.; Hock, Michael; Skrtic, Thomas M.; Knight, David; Brasseur-Hock, Irma; Clark, Jean; Ruggles, Marilyn; Hatton, Carol

    2012-01-01

    New technologies can dramatically change the way people live and work. Jet engines transformed travel. Television revolutionized news and entertainment. Computers and the Internet have transformed just about everything else. And now small video cameras have the potential to transform professional learning. Recognizing the potential of this new…

  12. Teaching Science to Students with Limited English Proficiency Using Cooperative Learning Techniques.

    ERIC Educational Resources Information Center

    LeDuc, Ellen H.

    Minimal class participation by students with limited English proficiency (LEP), and LEP student failure to pass regular classroom tests were addressed through cooperative learning in a second grade science class. Classroom techniques used included strategies for using the scientific method of investigation, hands-on activities, experiments, music,…

  13. Phishtest: Measuring the Impact of Email Headers on the Predictive Accuracy of Machine Learning Techniques

    ERIC Educational Resources Information Center

    Tout, Hicham

    2013-01-01

    The majority of documented phishing attacks have been carried by email, yet few studies have measured the impact of email headers on the predictive accuracy of machine learning techniques in detecting email phishing attacks. Research has shown that the inclusion of a limited subset of email headers as features in training machine learning…

  14. Teaching Vocabulary: The Relationship between Techniques of Teaching and Strategies of Learning New Vocabulary Items

    ERIC Educational Resources Information Center

    Elyas, Tariq; Alfaki, Ibrahim

    2014-01-01

    This study aims to investigate the techniques of teaching new lexis which are adopted by non-native teachers of English language. It also aims to investigate the strategies of learning new lexis which are adopted by learners in relation to their level. The work is based on two hypotheses: It is hypothesized that there is a relationship between the…

  15. An Analysis of Science Instructional Techniques Using Different Media in Learning and Testing Modes.

    ERIC Educational Resources Information Center

    Holliday, William Gibson

    Presented is an analysis of science instructional techniques using different media (printed material and/or audio tapes) in learning and testing modes. Three hypothetical concepts in biology and a retention test for each were developed. Three hundred fifty tenth-grade biology students were randomly assigned to nine subgroups which were…

  16. Computer-Assisted Techniques to Enhance Transformative Learning in First-Year Literature Courses.

    ERIC Educational Resources Information Center

    Jamieson, Marguerite; Kajs, Rebecca; Agee, Anne

    1996-01-01

    Illustrates techniques to foster transformative learning in computer-assisted literature classes: (1) a lesson plan on John Donne's "A Valediction: Forbidding Mourning"; (2) a plan to analyze "Oedipus Rex" using the "Daedalus" Interactive Writing Environment; and (3) a demonstration of how students engage in "meta-reflection" as they explore…

  17. Thank You for Asking: Classroom Assessment Techniques and Students' Perceptions of Learning.

    ERIC Educational Resources Information Center

    Fabry, Victoria J.; Eisenbach, Regina; Curry, Renee R.; Golich, Vicki L.

    1997-01-01

    A study investigated the effect of classroom assessment techniques (CATs) on both content and process of college students' learning. Instructors ask students to provide regular, anonymous feedback about their understanding of course material and the effectiveness of class structure. Comments of students in biology, business management, political…

  18. Group Testing as a Pedagogical Technique to Enhance Learning in Difficult Subjects

    ERIC Educational Resources Information Center

    Scafe, Marla G.

    2011-01-01

    The purpose of this study was to evaluate the effectiveness of group testing as a pedagogical technique to enhance learning in a difficult subject such as statistics. Individual test scores were compared to their group test scores for the same, identical test. A t test was used to compare the scores for 157 randomly selected MBA students enrolled…

  19. Exploring Machine Learning Techniques Using Patient Interactions in Online Health Forums to Classify Drug Safety

    ERIC Educational Resources Information Center

    Chee, Brant Wah Kwong

    2011-01-01

    This dissertation explores the use of personal health messages collected from online message forums to predict drug safety using natural language processing and machine learning techniques. Drug safety is defined as any drug with an active safety alert from the US Food and Drug Administration (FDA). It is believed that this is the first…

  20. Learning L2 German Vocabulary through Reading: The Effect of Three Enhancement Techniques Compared

    ERIC Educational Resources Information Center

    Peters, Elke; Hulstijn, Jan H.; Sercu, Lies; Lutjeharms, Madeline

    2009-01-01

    This study investigated three techniques designed to increase the chances that second language (L2) readers look up and learn unfamiliar words during and after reading an L2 text. Participants in the study, 137 college students in Belgium (L1 = Dutch, L2 = German), were randomly assigned to one of four conditions, forming combinations of two…

  1. The Effect of Cooperative Learning Techniques on College Students' Reading Comprehension

    ERIC Educational Resources Information Center

    Jalilifar, Alireza

    2010-01-01

    This study investigated the impact of Student Team Achievement Divisions (STAD) and Group Investigation (GI), which are two techniques of Cooperative Learning, on students' reading comprehension achievement of English as a Foreign Language (EFL). After administering an English Language Proficiency test (Fowler and Coe, 1976), 90 homogeneous…

  2. Status of the Usage of Active Learning and Teaching Method and Techniques by Social Studies Teachers

    ERIC Educational Resources Information Center

    Akman, Özkan

    2016-01-01

    The purpose of this study was to determine the active learning and teaching methods and techniques which are employed by the social studies teachers working in state schools of Turkey. This usage status was assessed using different variables. This was a case study, wherein the research was limited to 241 social studies teachers. These teachers…

  3. Critique: Can Children with AD/HD Learn Relaxation and Breathing Techniques through Biofeedback Video Games?

    ERIC Educational Resources Information Center

    Wright, Craig; Conlon, Elizabeth

    2009-01-01

    This article presents a critique on K. Amon and A. Campbell's "Can children with AD/HD learn relaxation and breathing techniques through biofeedback video games?". Amon and Campbell reported a successful trial of a commercially available biofeedback program, "The Wild Divine", in reducing symptoms of Attention-Deficit/Hyperactivity Disorder (ADHD)…

  4. Cultivating ICT Students' Interpersonal Soft Skills in Online Learning Environments Using Traditional Active Learning Techniques

    ERIC Educational Resources Information Center

    Myers, Trina S.; Blackman, Anna; Andersen, Trevor; Hay, Rachel; Lee, Ickjai; Gray, Heather

    2014-01-01

    Flexible online delivery of tertiary ICT programs is experiencing rapid growth. Creating an online environment that develops team building and interpersonal skills is difficult due to factors such as student isolation and the individual-centric model of online learning that encourages discrete study rather than teamwork. Incorporating teamwork…

  5. Learning preference as a predictor of academic performance in first year accelerated graduate entry nursing students: a prospective follow-up study.

    PubMed

    Koch, Jane; Salamonson, Yenna; Rolley, John X; Davidson, Patricia M

    2011-08-01

    The growth of accelerated graduate entry nursing programs has challenged traditional approaches to teaching and learning. To date, limited research has been undertaken in the role of learning preferences, language proficiency and academic performance in accelerated programs. Sixty-two first year accelerated graduate entry nursing students, in a single cohort at a university in the western region of Sydney, Australia, were surveyed to assess their learning preference using the Visual, Aural, Read/write and Kinaesthetic (VARK) learning preference questionnaire, together with sociodemographic data, English language acculturation and perceived academic control. Six months following course commencement, the participant's grade point average (GPA) was studied as a measurement of academic performance. A 93% response rate was achieved. The majority of students (62%) reported preference for multiple approaches to learning with the kinaesthetic sensory mode a significant (p=0.009) predictor of academic performance. Students who spoke only English at home had higher mean scores across two of the four categories of VARK sensory modalities, visual and kinaesthetic compared to those who spoke non-English. Further research is warranted to investigate the reasons why the kinaesthetic sensory mode is a predictor of academic performance and to what extent the VARK mean scores of the four learning preference(s) change with improved English language proficiency.

  6. Applying machine learning techniques to DNA sequence analysis. Progress report, February 14, 1991--February 13, 1992

    SciTech Connect

    Shavlik, J.W.

    1992-04-01

    We are developing a machine learning system that modifies existing knowledge about specific types of biological sequences. It does this by considering sample members and nonmembers of the sequence motif being learned. Using this information (which we call a ``domain theory``), our learning algorithm produces a more accurate representation of the knowledge needed to categorize future sequences. Specifically, the KBANN algorithm maps inference rules, such as consensus sequences, into a neural (connectionist) network. Neural network training techniques then use the training examples of refine these inference rules. We have been applying this approach to several problems in DNA sequence analysis and have also been extending the capabilities of our learning system along several dimensions.

  7. Acceleration: It's Elementary

    ERIC Educational Resources Information Center

    Willis, Mariam

    2012-01-01

    Acceleration is one tool for providing high-ability students the opportunity to learn something new every day. Some people talk about acceleration as taking a student out of step. In actuality, what one is doing is putting a student in step with the right curriculum. Whole-grade acceleration, also called grade-skipping, usually happens between…

  8. Predicting copper concentrations in acid mine drainage: a comparative analysis of five machine learning techniques.

    PubMed

    Betrie, Getnet D; Tesfamariam, Solomon; Morin, Kevin A; Sadiq, Rehan

    2013-05-01

    Acid mine drainage (AMD) is a global problem that may have serious human health and environmental implications. Laboratory and field tests are commonly used for predicting AMD, however, this is challenging since its formation varies from site-to-site for a number of reasons. Furthermore, these tests are often conducted at small-scale over a short period of time. Subsequently, extrapolation of these results into large-scale setting of mine sites introduce huge uncertainties for decision-makers. This study presents machine learning techniques to develop models to predict AMD quality using historical monitoring data of a mine site. The machine learning techniques explored in this study include artificial neural networks (ANN), support vector machine with polynomial (SVM-Poly) and radial base function (SVM-RBF) kernels, model tree (M5P), and K-nearest neighbors (K-NN). Input variables (physico-chemical parameters) that influence drainage dynamics are identified and used to develop models to predict copper concentrations. For these selected techniques, the predictive accuracy and uncertainty were evaluated based on different statistical measures. The results showed that SVM-Poly performed best, followed by the SVM-RBF, ANN, M5P, and KNN techniques. Overall, this study demonstrates that the machine learning techniques are promising tools for predicting AMD quality.

  9. Identifying Patients Who Are Unsuitable for Accelerated Partial Breast Irradiation Using Three-dimensional External Beam Conformal Techniques

    SciTech Connect

    Shikama, Naoto; Nakamura, Naoki; Kunishima, Naoaki; Hatanaka, Shogo; Sekiguchi, Kenji

    2012-07-01

    Purpose: Several recent studies reported that severe late toxicities including soft-tissue fibrosis and fat necrosis are present in patients treated with accelerated partial breast irradiation (APBI) and that these toxicities are associated with the large volume of tissue targeted by high-dose irradiation. The present study was performed to clarify which patients are unsuitable for APBI to avoid late severe toxicities. Methods and Materials: Study subjects comprised 50 consecutive patients with Stage 0-II unilateral breast cancer who underwent breast-conserving surgery, and in whom five or six surgical clips were placed during surgery. All patients were subsequently replanned using three-dimensional conformal radiotherapy (3D-CRT) APBI techniques according to the National Surgical Adjuvant Breast and Bowel Project (NSABP) B-39 and Radiation Therapy Oncology Group (RTOG) 0413 protocol. The beam arrangements included mainly noncoplanar four- or five-field beams using 6-MV photons alone. Results: Dose-volume histogram (DVH) constraints for normal tissues according to the NSABP/RTOG protocol were satisfied in 39 patients (78%). Multivariate analysis revealed that only long craniocaudal clip distance (CCD) was correlated with nonoptimal DVH constraints (p = 0.02), but that pathological T stage, anteroposterior clip distance (APD), site of ipsilateral breast (IB) (right/left), location of the tumor (medial/lateral), and IB reference volume were not. DVH constraints were satisfied in 20% of patients with a long CCD ({>=}5.5 cm) and 92% of those with a short CCD (p < 0.0001). Median IB reference volume receiving {>=}50% of the prescribed dose (IB-V{sub 50}) of all patients was 49.0% (range, 31.4-68.6). Multivariate analysis revealed that only a long CCD was correlated with large IB-V{sub 50} (p < 0.0001), but other factors were not. Conclusion: Patients with long CCDs ({>=}5.5 cm) might be unsuitable for 3D-CRT APBI because of nonoptimal DVH constraints and large IB

  10. New Evidence of Success for Community College Remedial English Students: Tracking the Outcomes of Students in the Accelerated Learning Program (ALP). CCRC Working Paper No. 53

    ERIC Educational Resources Information Center

    Cho, Sung-Woo; Kopko, Elizabeth; Jenkins, Davis; Jaggars, Shanna Smith

    2012-01-01

    This paper presents the findings from a follow-up quantitative analysis of the Community College of Baltimore County's Accelerated Learning Program (ALP). The results suggest that among students who enroll in the highest level developmental writing course, participation in ALP is associated with substantially better outcomes in terms of English…

  11. Prediction of mortality after radical cystectomy for bladder cancer by machine learning techniques.

    PubMed

    Wang, Guanjin; Lam, Kin-Man; Deng, Zhaohong; Choi, Kup-Sze

    2015-08-01

    Bladder cancer is a common cancer in genitourinary malignancy. For muscle invasive bladder cancer, surgical removal of the bladder, i.e. radical cystectomy, is in general the definitive treatment which, unfortunately, carries significant morbidities and mortalities. Accurate prediction of the mortality of radical cystectomy is therefore needed. Statistical methods have conventionally been used for this purpose, despite the complex interactions of high-dimensional medical data. Machine learning has emerged as a promising technique for handling high-dimensional data, with increasing application in clinical decision support, e.g. cancer prediction and prognosis. Its ability to reveal the hidden nonlinear interactions and interpretable rules between dependent and independent variables is favorable for constructing models of effective generalization performance. In this paper, seven machine learning methods are utilized to predict the 5-year mortality of radical cystectomy, including back-propagation neural network (BPN), radial basis function (RBFN), extreme learning machine (ELM), regularized ELM (RELM), support vector machine (SVM), naive Bayes (NB) classifier and k-nearest neighbour (KNN), on a clinicopathological dataset of 117 patients of the urology unit of a hospital in Hong Kong. The experimental results indicate that RELM achieved the highest average prediction accuracy of 0.8 at a fast learning speed. The research findings demonstrate the potential of applying machine learning techniques to support clinical decision making.

  12. Exposure to radiation accelerates normal brain aging and produces deficits in spatial learning and memory

    NASA Astrophysics Data System (ADS)

    Shukitt-Hale, B.; Casadesus, G.; Carey, A.; Rabin, B. M.; Joseph, J. A.

    Previous studies have shown that radiation exposure, particularly to particles of high energy and charge (HZE particles), produces deficits in spatial learning and memory. These adverse behavioral effects are similar to those seen in aged animals. It is possible that these shared effects may be produced by the same mechanism; oxidative stress damage to the central nervous system caused by an increased release of reactive oxygen species is likely responsible for the deficits seen in aging and following irradiation. Both aged and irradiated rats display cognitive impairment in tests of spatial learning and memory such as the Morris water maze and the radial arm maze. These rats have decrements in the ability to build spatial representations of the environment and they utilize non-spatial strategies to solve tasks. Furthermore, they show a lack of spatial preference, due to a decline in the ability to process or retain place (position of a goal with reference to a "map" provided by the configuration of numerous cues in the environment) information. These declines in spatial memory occur in measures dependent on both reference and working memory, and in the flexibility to reset mental images. These results show that irradiation with high-energy particles produces age-like decrements in cognitive behavior that may impair the ability of astronauts to perform critical tasks during long-term space travel beyond the magnetosphere. Supported by NASA Grants NAG9-1190 and NAG9-1529

  13. Retrieval of Similar Objects in Simulation Data Using Machine Learning Techniques

    SciTech Connect

    Cantu-Paz, E; Cheung, S-C; Kamath, C

    2003-06-19

    Comparing the output of a physics simulation with an experiment is often done by visually comparing the two outputs. In order to determine which simulation is a closer match to the experiment, more quantitative measures are needed. This paper describes our early experiences with this problem by considering the slightly simpler problem of finding objects in a image that are similar to a given query object. Focusing on a dataset from a fluid mixing problem, we report on our experiments using classification techniques from machine learning to retrieve the objects of interest in the simulation data. The early results reported in this paper suggest that machine learning techniques can retrieve more objects that are similar to the query than distance-based similarity methods.

  14. Machine learning techniques for the prediction of the peptide mobility in capillary zone electrophoresis.

    PubMed

    Yu, Ke; Cheng, Yiyu

    2007-02-15

    Three machine learning techniques including back propagation artificial neural network (BP-ANN), radial basis function artificial neural network (RBF-ANN) and support vector regression (SVR) were applied to predicting the peptide mobility in capillary zone electrophoresis through the development of quantitative structure-mobility relationship (QSMR) models. A data set containing 102 peptides with a large range of size, charge and hydrophobicity was used as a typical study. The optimal modeling parameters of the models were determined by grid-searching approach using 10-fold cross-validation. The predicted results were compared with that obtained by the multiple linear regression (MLR) method. The results showed that the relative standard errors (R.S.E.) of the developed models for the test set obtained by MLR, BP-ANN, RBF-ANN and SVR were 11.21%, 7.47%, 5.79% and 5.75%, respectively, while the R.S.E.s for the external validation set were 11.18%, 7.87%, 7.54% and 7.18%, respectively. The better generalization ability of the QSMR models developed by machine learning techniques over MLR was exactly presented. It was shown that the machine learning techniques were effective for developing the accurate and relaible QSMR models.

  15. A parametric study of unsupervised anomaly detection performance in maritime imagery using manifold learning techniques

    NASA Astrophysics Data System (ADS)

    Olson, C. C.; Doster, T.

    2016-05-01

    We investigate the parameters that govern an unsupervised anomaly detection framework that uses nonlinear techniques to learn a better model of the non-anomalous data. A manifold or kernel-based model is learned from a small, uniformly sampled subset in order to reduce computational burden and under the assumption that anomalous data will have little effect on the learned model because their rarity reduces the likelihood of their inclusion in the subset. The remaining data are then projected into the learned space and their projection errors used as detection statistics. Here, kernel principal component analysis is considered for learning the background model. We consider spectral data from an 8-band multispectral sensor as well as panchromatic infrared images treated by building a data set composed of overlapping image patches. We consider detection performance as a function of patch neighborhood size as well as embedding parameters such as kernel bandwidth and dimension. ROC curves are generated over a range of parameters and compared to RX performance.

  16. SU-C-17A-07: The Development of An MR Accelerator-Enabled Planning-To-Delivery Technique for Stereotactic Palliative Radiotherapy Treatment of Spinal Metastases

    SciTech Connect

    Hoogcarspel, S J; Kontaxis, C; Velden, J M van der; Bol, G H; Vulpen, M van; Lagendijk, J J W; Raaymakers, B W

    2014-06-01

    Purpose: To develop an MR accelerator-enabled online planning-todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases. The technical challenges include; automated stereotactic treatment planning, online MR-based dose calculation and MR guidance during treatment. Methods: Using the CT data of 20 patients previously treated at our institution, a class solution for automated treatment planning for spinal bone metastases was created. For accurate dose simulation right before treatment, we fused geometrically correct online MR data with pretreatment CT data of the target volume (TV). For target tracking during treatment, a dynamic T2-weighted TSE MR sequence was developed. An in house developed GPU based IMRT optimization and dose calculation algorithm was used for fast treatment planning and simulation. An automatically generated treatment plan developed with this treatment planning system was irradiated on a clinical 6 MV linear accelerator and evaluated using a Delta4 dosimeter. Results: The automated treatment planning method yielded clinically viable plans for all patients. The MR-CT fusion based dose calculation accuracy was within 2% as compared to calculations performed with original CT data. The dynamic T2-weighted TSE MR Sequence was able to provide an update of the anatomical location of the TV every 10 seconds. Dose calculation and optimization of the automatically generated treatment plans using only one GPU took on average 8 minutes. The Delta4 measurement of the irradiated plan agreed with the dose calculation with a 3%/3mm gamma pass rate of 86.4%. Conclusions: The development of an MR accelerator-enabled planning-todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases was presented. Future work will involve developing an intrafraction motion adaptation strategy, MR-only dose calculation, radiotherapy quality-assurance in a magnetic field, and streamlining the entire treatment

  17. Group Guidance Services with Self-Regulation Technique to Improve Student Learning Motivation in Junior High School (JHS)

    ERIC Educational Resources Information Center

    Pranoto, Hadi; Atieka, Nurul; Wihardjo, Sihadi Darmo; Wibowo, Agus; Nurlaila, Siti; Sudarmaji

    2016-01-01

    This study aims at: determining students motivation before being given a group guidance with self-regulation technique, determining students' motivation after being given a group counseling with self-regulation technique, generating a model of group counseling with self-regulation technique to improve motivation of learning, determining the…

  18. Comparison of machine learning techniques with classical statistical models in predicting health outcomes.

    PubMed

    Song, Xiaowei; Mitnitski, Arnold; Cox, Jafna; Rockwood, Kenneth

    2004-01-01

    Several machine learning techniques (multilayer and single layer perceptron, logistic regression, least square linear separation and support vector machines) are applied to calculate the risk of death from two biomedical data sets, one from patient care records, and another from a population survey. Each dataset contained multiple sources of information: history of related symptoms and other illnesses, physical examination findings, laboratory tests, medications (patient records dataset), health attitudes, and disabilities in activities of daily living (survey dataset). Each technique showed very good mortality prediction in the acute patients data sample (AUC up to 0.89) and fair prediction accuracy for six year mortality (AUC from 0.70 to 0.76) in individuals from epidemiological database surveys. The results suggest that the nature of data is of primary importance rather than the learning technique. However, the consistently superior performance of the artificial neural network (multi-layer perceptron) indicates that nonlinear relationships (which cannot be discerned by linear separation techniques) can provide additional improvement in correctly predicting health outcomes.

  19. Towards large-scale FAME-based bacterial species identification using machine learning techniques.

    PubMed

    Slabbinck, Bram; De Baets, Bernard; Dawyndt, Peter; De Vos, Paul

    2009-05-01

    In the last decade, bacterial taxonomy witnessed a huge expansion. The swift pace of bacterial species (re-)definitions has a serious impact on the accuracy and completeness of first-line identification methods. Consequently, back-end identification libraries need to be synchronized with the List of Prokaryotic names with Standing in Nomenclature. In this study, we focus on bacterial fatty acid methyl ester (FAME) profiling as a broadly used first-line identification method. From the BAME@LMG database, we have selected FAME profiles of individual strains belonging to the genera Bacillus, Paenibacillus and Pseudomonas. Only those profiles resulting from standard growth conditions have been retained. The corresponding data set covers 74, 44 and 95 validly published bacterial species, respectively, represented by 961, 378 and 1673 standard FAME profiles. Through the application of machine learning techniques in a supervised strategy, different computational models have been built for genus and species identification. Three techniques have been considered: artificial neural networks, random forests and support vector machines. Nearly perfect identification has been achieved at genus level. Notwithstanding the known limited discriminative power of FAME analysis for species identification, the computational models have resulted in good species identification results for the three genera. For Bacillus, Paenibacillus and Pseudomonas, random forests have resulted in sensitivity values, respectively, 0.847, 0.901 and 0.708. The random forests models outperform those of the other machine learning techniques. Moreover, our machine learning approach also outperformed the Sherlock MIS (MIDI Inc., Newark, DE, USA). These results show that machine learning proves very useful for FAME-based bacterial species identification. Besides good bacterial identification at species level, speed and ease of taxonomic synchronization are major advantages of this computational species

  20. Computer-aided classification of lung nodules on computed tomography images via deep learning technique

    PubMed Central

    Hua, Kai-Lung; Hsu, Che-Hao; Hidayati, Shintami Chusnul; Cheng, Wen-Huang; Chen, Yu-Jen

    2015-01-01

    Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain. PMID:26346558

  1. Computer-aided classification of lung nodules on computed tomography images via deep learning technique.

    PubMed

    Hua, Kai-Lung; Hsu, Che-Hao; Hidayati, Shintami Chusnul; Cheng, Wen-Huang; Chen, Yu-Jen

    2015-01-01

    Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain.

  2. MO-F-CAMPUS-I-03: GPU Accelerated Monte Carlo Technique for Fast Concurrent Image and Dose Simulation

    SciTech Connect

    Becchetti, M; Tian, X; Segars, P; Samei, E

    2015-06-15

    Purpose: To develop an accurate and fast Monte Carlo (MC) method of simulating CT that is capable of correlating dose with image quality using voxelized phantoms. Methods: A realistic voxelized phantom based on patient CT data, XCAT, was used with a GPU accelerated MC code for helical MDCT. Simulations were done with both uniform density organs and with textured organs. The organ doses were validated using previous experimentally validated simulations of the same phantom under the same conditions. Images acquired by tracking photons through the phantom with MC require lengthy computation times due to the large number of photon histories necessary for accurate representation of noise. A substantial speed up of the process was attained by using a low number of photon histories with kernel denoising of the projections from the scattered photons. These FBP reconstructed images were validated against those that were acquired in simulations using many photon histories by ensuring a minimal normalized root mean square error. Results: Organ doses simulated in the XCAT phantom are within 10% of the reference values. Corresponding images attained using projection kernel smoothing were attained with 3 orders of magnitude less computation time compared to a reference simulation using many photon histories. Conclusion: Combining GPU acceleration with kernel denoising of scattered photon projections in MC simulations allows organ dose and corresponding image quality to be attained with reasonable accuracy and substantially reduced computation time than is possible with standard simulation approaches.

  3. Auditory inspired machine learning techniques can improve speech intelligibility and quality for hearing-impaired listeners.

    PubMed

    Monaghan, Jessica J M; Goehring, Tobias; Yang, Xin; Bolner, Federico; Wang, Shangqiguo; Wright, Matthew C M; Bleeck, Stefan

    2017-03-01

    Machine-learning based approaches to speech enhancement have recently shown great promise for improving speech intelligibility for hearing-impaired listeners. Here, the performance of three machine-learning algorithms and one classical algorithm, Wiener filtering, was compared. Two algorithms based on neural networks were examined, one using a previously reported feature set and one using a feature set derived from an auditory model. The third machine-learning approach was a dictionary-based sparse-coding algorithm. Speech intelligibility and quality scores were obtained for participants with mild-to-moderate hearing impairments listening to sentences in speech-shaped noise and multi-talker babble following processing with the algorithms. Intelligibility and quality scores were significantly improved by each of the three machine-learning approaches, but not by the classical approach. The largest improvements for both speech intelligibility and quality were found by implementing a neural network using the feature set based on auditory modeling. Furthermore, neural network based techniques appeared more promising than dictionary-based, sparse coding in terms of performance and ease of implementation.

  4. Developing Fire Detection Algorithms by Geostationary Orbiting Platforms and Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Salvador, Pablo; Sanz, Julia; Garcia, Miguel; Casanova, Jose Luis

    2016-08-01

    Fires in general and forest fires specific are a major concern in terms of economical and biological loses. Remote sensing technologies have been focusing on developing several algorithms, adapted to a large kind of sensors, platforms and regions in order to obtain hotspots as faster as possible. The aim of this study is to establish an automatic methodology to develop hotspots detection algorithms with Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor on board Meteosat Second Generation platform (MSG) based on machine learning techniques that can be exportable to others geostationary platforms and sensors and to any area of the Earth. The sensitivity (SE), specificity (SP) and accuracy (AC) parameters have been analyzed in order to develop the final machine learning algorithm taking into account the preferences and final use of the predicted data.

  5. Variance-penalized Markov decision processes: dynamic programming and reinforcement learning techniques

    NASA Astrophysics Data System (ADS)

    Gosavi, Abhijit

    2014-08-01

    In control systems theory, the Markov decision process (MDP) is a widely used optimization model involving selection of the optimal action in each state visited by a discrete-event system driven by Markov chains. The classical MDP model is suitable for an agent/decision-maker interested in maximizing expected revenues, but does not account for minimizing variability in the revenues. An MDP model in which the agent can maximize the revenues while simultaneously controlling the variance in the revenues is proposed. This work is rooted in machine learning/neural network concepts, where updating is based on system feedback and step sizes. First, a Bellman equation for the problem is proposed. Thereafter, convergent dynamic programming and reinforcement learning techniques for solving the MDP are provided along with encouraging numerical results on a small MDP and a preventive maintenance problem.

  6. Magnetic resonance imaging segmentation techniques using batch-type learning vector quantization algorithms.

    PubMed

    Yang, Miin-Shen; Lin, Karen Chia-Ren; Liu, Hsiu-Chih; Lirng, Jiing-Feng

    2007-02-01

    In this article, we propose batch-type learning vector quantization (LVQ) segmentation techniques for the magnetic resonance (MR) images. Magnetic resonance imaging (MRI) segmentation is an important technique to differentiate abnormal and normal tissues in MR image data. The proposed LVQ segmentation techniques are compared with the generalized Kohonen's competitive learning (GKCL) methods, which were proposed by Lin et al. [Magn Reson Imaging 21 (2003) 863-870]. Three MRI data sets of real cases are used in this article. The first case is from a 2-year-old girl who was diagnosed with retinoblastoma in her left eye. The second case is from a 55-year-old woman who developed complete left side oculomotor palsy immediately after a motor vehicle accident. The third case is from an 84-year-old man who was diagnosed with Alzheimer disease (AD). Our comparisons are based on sensitivity of algorithm parameters, the quality of MRI segmentation with the contrast-to-noise ratio and the accuracy of the region of interest tissue. Overall, the segmentation results from batch-type LVQ algorithms present good accuracy and quality of the segmentation images, and also flexibility of algorithm parameters in all the comparison consequences. The results support that the proposed batch-type LVQ algorithms are better than the previous GKCL algorithms. Specifically, the proposed fuzzy-soft LVQ algorithm works well in segmenting AD MRI data set to accurately measure the hippocampus volume in AD MR images.

  7. Mobile Formative Assessment Tool Based on Data Mining Techniques for Supporting Web-Based Learning

    ERIC Educational Resources Information Center

    Chen, Chih-Ming; Chen, Ming-Chuan

    2009-01-01

    Current trends clearly indicate that online learning has become an important learning mode. However, no effective assessment mechanism for learning performance yet exists for e-learning systems. Learning performance assessment aims to evaluate what learners learned during the learning process. Traditional summative evaluation only considers final…

  8. Accelerators, Colliders, and Snakes

    NASA Astrophysics Data System (ADS)

    Courant, Ernest D.

    2003-12-01

    The author traces his involvement in the evolution of particle accelerators over the past 50 years. He participated in building the first billion-volt accelerator, the Brookhaven Cosmotron, which led to the introduction of the "strong-focusing" method that has in turn led to the very large accelerators and colliders of the present day. The problems of acceleration of spin-polarized protons are also addressed, with discussions of depolarizing resonances and "Siberian snakes" as a technique for mitigating these resonances.

  9. A Comparative Research on the Effectivity of Cooperative Learning Method and Jigsaw Technique on Teaching Literary Genres

    ERIC Educational Resources Information Center

    Gocer, Ali

    2010-01-01

    One of the basic purposes of language and literary education is to maintain a target population and the use of proper attitude, method and technique in proper learning environments. Therefore, proper attitudes and methods are to be resorted for students to become active elements of the environment throughout the learning-teaching process. One of…

  10. Cooperative Learning as a Correction and Grammar Revision Technique: Communicative Exchanges, Self-Correction Rates and Scores

    ERIC Educational Resources Information Center

    Servetti, Sara

    2010-01-01

    This paper focuses on cooperative learning (CL) used as a correction and grammar revision technique and considers the data collected in six Italian parallel classes, three of which (sample classes) corrected mistakes and revised grammar through cooperative learning, while the other three (control classes) in a traditional way. All the classes…

  11. Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation.

    PubMed

    Caravaca, Juan; Soria-Olivas, Emilio; Bataller, Manuel; Serrano, Antonio J; Such-Miquel, Luis; Vila-Francés, Joan; Guerrero, Juan F

    2014-02-01

    This work presents the application of machine learning techniques to analyse the influence of physical exercise in the physiological properties of the heart, during ventricular fibrillation. To this end, different kinds of classifiers (linear and neural models) are used to classify between trained and sedentary rabbit hearts. The use of those classifiers in combination with a wrapper feature selection algorithm allows to extract knowledge about the most relevant features in the problem. The obtained results show that neural models outperform linear classifiers (better performance indices and a better dimensionality reduction). The most relevant features to describe the benefits of physical exercise are those related to myocardial heterogeneity, mean activation rate and activation complexity.

  12. Learning from truth: youth participation in field marketing techniques to counter tobacco advertising.

    PubMed

    Eisenberg, Merrill; Ringwalt, Chris; Driscoll, David; Vallee, Manuel; Gullette, Gregory

    2004-01-01

    In 2000, the American Legacy Foundation (Legacy) launched truth, a national, multi-medium tobacco control social marketing campaign targeting youth age 12-17. This paper provides a brief description of one aspect of that campaign, the truth tour, and compares and contrasts the truth tour with commercial field marketing approaches used by the tobacco industry. The methods used for the tour's process evaluation are also described, and two important lessons learned about using field marketing techniques and using youth to implement field marketing techniques in social marketing campaigns are discussed. Social marketing campaigns that target youth may want to launch field marketing activities. The truth tour experience can inform the development of those efforts.

  13. Graphical Technique to Support the Teaching/Learning Process of Software Process Reference Models

    NASA Astrophysics Data System (ADS)

    Espinosa-Curiel, Ismael Edrein; Rodríguez-Jacobo, Josefina; Fernández-Zepeda, José Alberto

    In this paper, we propose a set of diagrams to visualize software process reference models (PRM). The diagrams, called dimods, are the combination of some visual and process modeling techniques such as rich pictures, mind maps, IDEF and RAD diagrams. We show the use of this technique by designing a set of dimods for the Mexican Software Industry Process Model (MoProSoft). Additionally, we perform an evaluation of the usefulness of dimods. The result of the evaluation shows that dimods may be a support tool that facilitates the understanding, memorization, and learning of software PRMs in both, software development organizations and universities. The results also show that dimods may have advantages over the traditional description methods for these types of models.

  14. Getting the Most Out of Dual-Listed Courses: Involving Undergraduate Students in Discussion Through Active Learning Techniques

    NASA Astrophysics Data System (ADS)

    Tasich, C. M.; Duncan, L. L.; Duncan, B. R.; Burkhardt, B. L.; Benneyworth, L. M.

    2015-12-01

    Dual-listed courses will persist in higher education because of resource limitations. The pedagogical differences between undergraduate and graduate STEM student groups and the underlying distinction in intellectual development levels between the two student groups complicate the inclusion of undergraduates in these courses. Active learning techniques are a possible remedy to the hardships undergraduate students experience in graduate-level courses. Through an analysis of both undergraduate and graduate student experiences while enrolled in a dual-listed course, we implemented a variety of learning techniques used to complement the learning of both student groups and enhance deep discussion. Here, we provide details concerning the implementation of four active learning techniques - role play, game, debate, and small group - that were used to help undergraduate students critically discuss primary literature. Student perceptions were gauged through an anonymous, end-of-course evaluation that contained basic questions comparing the course to other courses at the university and other salient aspects of the course. These were given as a Likert scale on which students rated a variety of statements (1 = strongly disagree, 3 = no opinion, and 5 = strongly agree). Undergraduates found active learning techniques to be preferable to traditional techniques with small-group discussions being rated the highest in both enjoyment and enhanced learning. The graduate student discussion leaders also found active learning techniques to improve discussion. In hindsight, students of all cultures may be better able to take advantage of such approaches and to critically read and discuss primary literature when written assignments are used to guide their reading. Applications of active learning techniques can not only address the gap between differing levels of students, but also serve as a complement to student engagement in any science course design.

  15. Accelerating Monte Carlo image reconstruction of a PMMA phantom through variance reduction techniques for quality control in digital mammography.

    PubMed

    Ramos, M; Ferrer, S; Verdu, G

    2005-01-01

    Mammography is a non-invasive technique used for the detection of breast lesions. The use of this technique in a breast screening program requires a continuous quality control testing in mammography units for ensuring a minimum absorbed glandular dose without modifying image quality. Digital mammography has been progressively introduced in screening centers, since recent evolution of photostimulable phosphor detectors. The aim of this work is the validation of a methodology for reconstructing digital images of a polymethyl-methacrylate (PMMA) phantom (P01 model) under pure Monte Carlo techniques. A reference image has been acquired for this phantom under automatic exposure control (AEC) mode (28 kV and 14 mAs). Some variance reduction techniques (VRT) have been applied to improve the efficiency of the simulations, defined as the number of particles reaching the imaging system per starting particle. All images have been used and stored in DICOM format. The results prove that the signal-to-noise ratio (SNR) of the reconstructed images have been increased with the use of the VRT, showing similar values between different employed tallies. As a conclusion, these images could be used during quality control testing for showing any deviation of the exposition parameters from the desired reference level.

  16. A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods.

    PubMed

    Choi, Kihwan; Li, Ruijiang; Nam, Haewon; Xing, Lei

    2014-06-21

    As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate [Formula: see text]. In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques.

  17. Boosting Adolescent and Young Adult Literacy: An Examination of Literacy Teaching and Learning in Philadelphia's Accelerated High Schools

    ERIC Educational Resources Information Center

    Gold, Eva; Edmunds, Kimberly; Maluk, Holly; Reumann-Moore, Rebecca

    2011-01-01

    In 2010-11, the School District of Philadelphia (the District) operated thirteen accelerated high schools that served approximately 2,000 under-credited, over-age students. Each of the accelerated schools was managed by one of seven external providers, each with its own educational approach, and each with a contractual agreement with the…

  18. Optimization of in-cell accelerated solvent extraction technique for the determination of organochlorine pesticides in river sediments.

    PubMed

    Duodu, Godfred Odame; Goonetilleke, Ashantha; Ayoko, Godwin A

    2016-04-01

    Organochlorine pesticides (OCPs) are ubiquitous environmental contaminants with adverse impacts on aquatic biota, wildlife and human health even at low concentrations. However, conventional methods for their determination in river sediments are resource intensive. This paper presents an approach that is rapid and also reliable for the detection of OCPs. Accelerated Solvent Extraction (ASE) with in-cell silica gel clean-up followed by Triple Quadrupole Gas Chromatograph Mass Spectrometry (GCMS/MS) was used to recover OCPs from sediment samples. Variables such as temperature, solvent ratio, adsorbent mass and extraction cycle were evaluated and optimized for the extraction. With the exception of Aldrin, which was unaffected by any of the variables evaluated, the recovery of OCPs from sediment samples was largely influenced by solvent ratio and adsorbent mass and, to some extent, the number of cycles and temperature. The optimized conditions for OCPs extraction in sediment with good recoveries were determined to be 4 cycles, 4.5 g of silica gel, 105 °C, and 4:3 v/v DCM: hexane mixture. With the exception of two compounds (α-BHC and Aldrin) whose recoveries were low (59.73 and 47.66% respectively), the recovery of the other pesticides were in the range 85.35-117.97% with precision <10% RSD. The method developed significantly reduces sample preparation time, the amount of solvent used, matrix interference, and is highly sensitive and selective.

  19. Comparison of supervised and unsupervised machine learning techniques for UXO classification using EMI data

    NASA Astrophysics Data System (ADS)

    Bijamov, Alex; Shubitidze, Fridon; Fernandez, Juan Pablo; Shamatava, Irma; Barrowes, Benjamin E.; O'Neill, Kevin

    2011-06-01

    Classification tools including Support Vector Machines (SVM) and Neural Networks (NN) are employed, and their performances compared for Unexploded Ordnance (UXO) classification using live site electromagnetic induction (EMI) data. Both SVM and NN are examples of supervised machine-learning techniques, whose purpose is to label the features (extracted from the incoming data of the unknown subsurface anomalies) based on previously trained examples. In this paper a set of three features are extracted from the EMI decay curves of the physics-based intrinsic, effective dipole moment, called the total Normalized Surface Magnetic Source (NSMS). This data is first used to train both the SVM and NN models and further serves as a basis for UXO classification. These techniques are then compared to an unsupervised learning approach, based on agglomerative hierarchical clustering followed by Gaussian Mixture modeling. We found that such combination provides reduction in the amount of required training data (which is being requested solely based on the clustering results) and allows for convenient probabilistic interpretation of the classification. The classification results themselves depend on the UXO caliber, material composition and actual live UXO site's conditions. Therefore, here we report the classification results for a live UXO data set, collected at former Camp San Luis Obispo, CA. This study includes four targets-of-interest: 60-mm, 81-mm, and 4.2-in mortars and 2.36-in rockets. The classification performance between clutters and UXO is studied and the corresponding ROC curves are illustrated.

  20. Accelerator Diagnostic Techniques Using Time-Domain Data from a Bunch-by-bunch Longitudinal Feedback System

    SciTech Connect

    Teytelman, Dmitry

    2000-03-30

    A programmable DSP-based longitudinal damping system has been developed for the PEP-II/DAFNE/ALS machines. The DSP-based architecture allows feedback functions to coexist with data acquisition or instrumentation algorithms. The fast sampling rates in these systems (500 MHz) in conjunction with the large distributed memory of the DSP processors make possible several novel beam diagnostics complementary to traditional narrowband spectral measurements. Instantaneous spectral measurements of 250 MHz span with 70 Hz resolution can be made from 14 ms time domain data records captured by the DSP system. The authors present techniques developed for the measurement of modal growth and damping rates and other beam and system diagnostics (calibrations, measurements of the system noise floor). Results from the Advanced Light Source and PEP-II are presented to illustrate these techniques.

  1. Linear Accelerators

    NASA Astrophysics Data System (ADS)

    Sidorin, Anatoly

    2010-01-01

    In linear accelerators the particles are accelerated by either electrostatic fields or oscillating Radio Frequency (RF) fields. Accordingly the linear accelerators are divided in three large groups: electrostatic, induction and RF accelerators. Overview of the different types of accelerators is given. Stability of longitudinal and transverse motion in the RF linear accelerators is briefly discussed. The methods of beam focusing in linacs are described.

  2. Markerless gating for lung cancer radiotherapy based on machine learning techniques

    NASA Astrophysics Data System (ADS)

    Lin, Tong; Li, Ruijiang; Tang, Xiaoli; Dy, Jennifer G.; Jiang, Steve B.

    2009-03-01

    In lung cancer radiotherapy, radiation to a mobile target can be delivered by respiratory gating, for which we need to know whether the target is inside or outside a predefined gating window at any time point during the treatment. This can be achieved by tracking one or more fiducial markers implanted inside or near the target, either fluoroscopically or electromagnetically. However, the clinical implementation of marker tracking is limited for lung cancer radiotherapy mainly due to the risk of pneumothorax. Therefore, gating without implanted fiducial markers is a promising clinical direction. We have developed several template-matching methods for fluoroscopic marker-less gating. Recently, we have modeled the gating problem as a binary pattern classification problem, in which principal component analysis (PCA) and support vector machine (SVM) are combined to perform the classification task. Following the same framework, we investigated different combinations of dimensionality reduction techniques (PCA and four nonlinear manifold learning methods) and two machine learning classification methods (artificial neural networks—ANN and SVM). Performance was evaluated on ten fluoroscopic image sequences of nine lung cancer patients. We found that among all combinations of dimensionality reduction techniques and classification methods, PCA combined with either ANN or SVM achieved a better performance than the other nonlinear manifold learning methods. ANN when combined with PCA achieves a better performance than SVM in terms of classification accuracy and recall rate, although the target coverage is similar for the two classification methods. Furthermore, the running time for both ANN and SVM with PCA is within tolerance for real-time applications. Overall, ANN combined with PCA is a better candidate than other combinations we investigated in this work for real-time gated radiotherapy.

  3. Getting the Most Out of Dual-Listed Courses: Involving Undergraduate Students in Discussion through Active Learning Techniques

    ERIC Educational Resources Information Center

    Duncan, Leslie Lyons; Burkhardt, Bethany L.; Benneyworth, Laura M.; Tasich, Christopher M.; Duncan, Benjamin R.

    2015-01-01

    This article provides readers with details concerning the implementation of four active learning techniques used to help undergraduate students critically discuss primary literature. On the basis of undergraduate and graduate student perceptions and experiences, the authors suggest techniques to enhance the quality of dual-listed courses and…

  4. Analyzing Convergence in e-Learning Resource Filtering Based on ACO Techniques: A Case Study with Telecommunication Engineering Students

    ERIC Educational Resources Information Center

    Munoz-Organero, Mario; Ramirez, Gustavo A.; Merino, Pedro Munoz; Kloos, Carlos Delgado

    2010-01-01

    The use of swarm intelligence techniques in e-learning scenarios provides a way to combine simple interactions of individual students to solve a more complex problem. After getting some data from the interactions of the first students with a central system, the use of these techniques converges to a solution that the rest of the students can…

  5. [Motor capacities involved in the psychomotor skills of the cardiopulmonary resuscitation technique: recommendations for the teaching-learning process].

    PubMed

    Miyadahira, A M

    2001-12-01

    It is a bibliographic study about the identification of the motor capacities involved in the psychomotor skills of the cardiopulmonary resuscitation (CPR) which aims to obtain subsidies to the planning of the teaching-learning process of this skill. It was found that: the motor capacities involved in the psychomotor skill of the CPR technique are predominantly cognitive and motor, involving 9 perceptive-motor capacities and 8 physical proficiency capacities. The CPR technique is a psychomotor skill classified as open, done in series and categorized as a thin and global skill and the teaching-learning process of the CPR technique has an elevated degree of complexity.

  6. The impact of a student learning journal: a two-stage evaluation using the Nominal Group Technique.

    PubMed

    Grant, Andy; Berlin, Anita; Freeman, George K

    2003-11-01

    Reflection offers a strategy that can help learners connect what they learn with their everyday practice. It can also assist them in taking control of their learning and in developing insight into the way that they learn. This study used the Nominal Group Technique to evaluate a reflective learning journal on a one-year course for GPs and pharmaceutical advisers. Changes were introduced in answer to the students' responses in the first year, and the evaluation at the end of the second year showed a significant reduction in students' levels of confusion and anxiety related to keeping the diary. They also said that keeping the diary benefited their learning styles but they reported that keeping a learning diary was time-consuming.

  7. Fielding the magnetically applied pressure-shear technique on the Z accelerator (completion report for MRT 4519).

    SciTech Connect

    Alexander, C. Scott; Haill, Thomas A.; Dalton, Devon Gardner; Rovang, Dean Curtis; Lamppa, Derek C.

    2013-09-01

    The recently developed Magnetically Applied Pressure-Shear (MAPS) experimental technique to measure material shear strength at high pressures on magneto-hydrodynamic (MHD) drive pulsed power platforms was fielded on August 16, 2013 on shot Z2544 utilizing hardware set A0283A. Several technical and engineering challenges were overcome in the process leading to the attempt to measure the dynamic strength of NNSA Ta at 50 GPa. The MAPS technique relies on the ability to apply an external magnetic field properly aligned and time correlated with the MHD pulse. The load design had to be modified to accommodate the external field coils and additional support was required to manage stresses from the pulsed magnets. Further, this represents the first time transverse velocity interferometry has been applied to diagnose a shot at Z. All subsystems performed well with only minor issues related to the new feed design which can be easily addressed by modifying the current pulse shape. Despite the success of each new component, the experiment failed to measure strength in the samples due to spallation failure, most likely in the diamond anvils. To address this issue, hydrocode simulations are being used to evaluate a modified design using LiF windows to minimize tension in the diamond and prevent spall. Another option to eliminate the diamond material from the experiment is also being investigated.

  8. New techniques in large scale metrology toolset data mining to accelerate integrated chip technology development and increase manufacturing efficiencies

    NASA Astrophysics Data System (ADS)

    Solecky, Eric; Rana, Narender; Minns, Allan; Gustafson, Carol; Lindo, Patrick; Cornell, Roger; Llanos, Paul

    2014-04-01

    Today, metrology toolsets report out more information than ever. This information applies not only to process performance but also metrology toolset and recipe performance through various diagnostic metrics. This is most evident on the Critical Dimension Scanning Electron Microscope (CD-SEM). Today state of the art CD-SEMs report out over 250 individual data points and several images per measurement. It is typical for a state of the art fab with numerous part numbers to generate at least 20TB of information over the course of a year on the CD-SEM fleet alone pushing metrology toolsets into the big data regime. Most of this comes from improvements in throughput, increased sampling and new data outputs relative to previous generations of tools. Oftentimes, these new data outputs are useful for helping to determine if the process, metrology recipe or tool is deviating from an ideal state. Many issues could be missed by singularly looking at the key process control metric like the bottom critical dimension (CD) or a small subset of this available information. By leveraging the entire data set the mean time to detect and finding the root cause of issues can be significantly reduced. In this paper a new data mining system is presented that achieves this goal. Examples are shown with a focus on the benefits realized using this new system which helps speed up development cycles of learning and reducing manufacturing cycle-time. This paper concludes discussing future directions to make this capability more effective.

  9. Who is that masked educator? Deconstructing the teaching and learning processes of an innovative humanistic simulation technique.

    PubMed

    McAllister, Margaret; Searl, Kerry Reid; Davis, Susan

    2013-12-01

    Simulation learning in nursing has long made use of mannequins, standardized actors and role play to allow students opportunity to practice technical body-care skills and interventions. Even though numerous strategies have been developed to mimic or amplify clinical situations, a common problem that is difficult to overcome in even the most well-executed simulation experiences, is that students may realize the setting is artificial and fail to fully engage, remember or apply the learning. Another problem is that students may learn technical competence but remain uncertain about communicating with the person. Since communication capabilities are imperative in human service work, simulation learning that only achieves technical competence in students is not fully effective for the needs of nursing education. Furthermore, while simulation learning is a burgeoning space for innovative practices, it has been criticized for the absence of a basis in theory. It is within this context that an innovative simulation learning experience named "Mask-Ed (KRS simulation)", has been deconstructed and the active learning components examined. Establishing a theoretical basis for creative teaching and learning practices provides an understanding of how, why and when simulation learning has been effective and it may help to distinguish aspects of the experience that could be improved. Three conceptual theoretical fields help explain the power of this simulation technique: Vygotskian sociocultural learning theory, applied theatre and embodiment.

  10. A Multidisciplinary Approach to the Characterisation and Accelerated Remediation of Nuclear Contaminated Sites: Less Intrusive Techniques and Better Use of Geographical Information System (GIS) Model Development

    SciTech Connect

    Brydie, J.R.; Hiller, P.; Mathers, D.; Gordon, R.

    2006-07-01

    Rapid, cost effective decommissioning and associated remediation of many nuclear licensed sites requires the physical and chemical characterisation of a range of bulk materials including natural soils, sediments, cementitious materials, miscellaneous historically buried waste and natural waters (surface and groundwaters). Conventional techniques (such as cable percussion drilling, rotary coring of building materials, extensive soil sampling campaigns and [ground]water sampling and analysis) tend to be expensive, time consuming, in many cases provide insufficient data and typically take several months to implement. The high level aim of the work is to reduce the overall time and cost of site characterisation, whilst maintaining quality of information and increasing the safety of field and laboratory personnel. We describe here the integrated technical approach being adopted and developed within Nexia Solutions Ltd. to provide a full in situ site characterisation and modelling capability, resulting in significantly reduced costs and acceleration of the Life Cycle Baseline (LCBL) of many United Kingdom (U. K.) nuclear licensed sites. The evolving technical toolbox includes many off-the-shelf technologies, as well as innovative technologies which have either been originally conceived or have been effectively adapted from a range of technical disciplines. All of the techniques here are either in use or are being actively developed and commissioned. All information gained via in situ techniques is used to iteratively update the Geographical Information System (GIS) conceptual model, allowing further targeted site investigation, informed decision making and optioneering. (authors)

  11. Learning Analytics and Computational Techniques for Detecting and Evaluating Patterns in Learning: An Introduction to the Special Issue

    ERIC Educational Resources Information Center

    Martin, Taylor; Sherin, Bruce

    2013-01-01

    The learning sciences community's interest in learning analytics (LA) has been growing steadily over the past several years. Three recent symposia on the theme (at the American Educational Research Association 2011 and 2012 annual conferences, and the International Conference of the Learning Sciences 2012), organized by Paulo Blikstein, led…

  12. Recognition of Mould Colony on Unhulled Paddy Based on Computer Vision using Conventional Machine-learning and Deep Learning Techniques.

    PubMed

    Sun, Ke; Wang, Zhengjie; Tu, Kang; Wang, Shaojin; Pan, Leiqing

    2016-11-29

    To investigate the potential of conventional and deep learning techniques to recognize the species and distribution of mould in unhulled paddy, samples were inoculated and cultivated with five species of mould, and sample images were captured. The mould recognition methods were built using support vector machine (SVM), back-propagation neural network (BPNN), convolutional neural network (CNN), and deep belief network (DBN) models. An accuracy rate of 100% was achieved by using the DBN model to identify the mould species in the sample images based on selected colour-histogram parameters, followed by the SVM and BPNN models. A pitch segmentation recognition method combined with different classification models was developed to recognize the mould colony areas in the image. The accuracy rates of the SVM and CNN models for pitch classification were approximately 90% and were higher than those of the BPNN and DBN models. The CNN and DBN models showed quicker calculation speeds for recognizing all of the pitches segmented from a single sample image. Finally, an efficient uniform CNN pitch classification model for all five types of sample images was built. This work compares multiple classification models and provides feasible recognition methods for mouldy unhulled paddy recognition.

  13. Recognition of Mould Colony on Unhulled Paddy Based on Computer Vision using Conventional Machine-learning and Deep Learning Techniques

    NASA Astrophysics Data System (ADS)

    Sun, Ke; Wang, Zhengjie; Tu, Kang; Wang, Shaojin; Pan, Leiqing

    2016-11-01

    To investigate the potential of conventional and deep learning techniques to recognize the species and distribution of mould in unhulled paddy, samples were inoculated and cultivated with five species of mould, and sample images were captured. The mould recognition methods were built using support vector machine (SVM), back-propagation neural network (BPNN), convolutional neural network (CNN), and deep belief network (DBN) models. An accuracy rate of 100% was achieved by using the DBN model to identify the mould species in the sample images based on selected colour-histogram parameters, followed by the SVM and BPNN models. A pitch segmentation recognition method combined with different classification models was developed to recognize the mould colony areas in the image. The accuracy rates of the SVM and CNN models for pitch classification were approximately 90% and were higher than those of the BPNN and DBN models. The CNN and DBN models showed quicker calculation speeds for recognizing all of the pitches segmented from a single sample image. Finally, an efficient uniform CNN pitch classification model for all five types of sample images was built. This work compares multiple classification models and provides feasible recognition methods for mouldy unhulled paddy recognition.

  14. Recognition of Mould Colony on Unhulled Paddy Based on Computer Vision using Conventional Machine-learning and Deep Learning Techniques

    PubMed Central

    Sun, Ke; Wang, Zhengjie; Tu, Kang; Wang, Shaojin; Pan, Leiqing

    2016-01-01

    To investigate the potential of conventional and deep learning techniques to recognize the species and distribution of mould in unhulled paddy, samples were inoculated and cultivated with five species of mould, and sample images were captured. The mould recognition methods were built using support vector machine (SVM), back-propagation neural network (BPNN), convolutional neural network (CNN), and deep belief network (DBN) models. An accuracy rate of 100% was achieved by using the DBN model to identify the mould species in the sample images based on selected colour-histogram parameters, followed by the SVM and BPNN models. A pitch segmentation recognition method combined with different classification models was developed to recognize the mould colony areas in the image. The accuracy rates of the SVM and CNN models for pitch classification were approximately 90% and were higher than those of the BPNN and DBN models. The CNN and DBN models showed quicker calculation speeds for recognizing all of the pitches segmented from a single sample image. Finally, an efficient uniform CNN pitch classification model for all five types of sample images was built. This work compares multiple classification models and provides feasible recognition methods for mouldy unhulled paddy recognition. PMID:27897236

  15. SU-E-T-226: Junction Free Craniospinal Irradiation in Linear Accelerator Using Volumetric Modulated Arc Therapy : A Novel Technique Using Dose Tapering

    SciTech Connect

    Sarkar, B; Roy, S; Paul, S; Munshi, A; Roy, Shilpi; Jassal, K; Ganesh, T; Mohanti, BK

    2014-06-01

    Purpose: Spatially separated fields are required for craniospinal irradiation due to field size limitation in linear accelerator. Field junction shits are conventionally done to avoid hot or cold spots. Our study was aimed to demonstrate the feasibility of junction free irradiation plan of craniospinal irradiation (CSI) for Meduloblastoma cases treated in linear accelerator using Volumetric modulated arc therapy (VMAT) technique. Methods: VMAT was planned using multiple isocenters in Monaco V 3.3.0 and delivered in Elekta Synergy linear accelerator. A full arc brain and 40° posterior arc spine fields were planned using two isocentre for short (<1.3 meter height ) and 3 isocentres for taller patients. Unrestricted jaw movement was used in superior-inferior direction. Prescribed dose to PTV was achieved by partial contribution from adjacent beams. A very low dose gradient was generated to taper the isodoses over a long length (>10 cm) at the conventional field junction. Results: In this primary study five patients were planned and three patients were delivered using this novel technique. As the dose contribution from the adjacent beams were varied (gradient) to create a complete dose distribution, therefore there is no specific junction exists in the plan. The junction were extended from 10–14 cm depending on treatment plan. Dose gradient were 9.6±2.3% per cm for brain and 7.9±1.7 % per cm for spine field respectively. Dose delivery error due to positional inaccuracy was calculated for brain and spine field for ±1mm, ±2mm, ±3mm and ±5 mm were 1%–0.8%, 2%–1.6%, 2.8%–2.4% and 4.3%–4% respectively. Conclusion: Dose tapering in junction free CSI do not require a junction shift. Therefore daily imaging for all the field is also not essential. Due to inverse planning dose to organ at risk like thyroid kidney, heart and testis can be reduced significantly. VMAT gives a quicker delivery than Step and shoot or dynamic IMRT.

  16. The Journal of the Society for Accelerative Learning and Teaching, Volume 7.

    ERIC Educational Resources Information Center

    Journal of the Society for Accelerative Learning and Teaching, 1982

    1982-01-01

    The four 1982 numbers of the Journal of the Society for Accelerative Learning and Teaching (SALT) include articles on: a comparison of the Tomatis Method and Suggestopedia; the CLC system of accelerated learning; Suggestopedia in the English-as-a-second-language classroom; experiments with SALT techniques; accelerative learning techniques for…

  17. Quantum-state anomaly detection for arbitrary errors using a machine-learning technique

    NASA Astrophysics Data System (ADS)

    Hara, Satoshi; Ono, Takafumi; Okamoto, Ryo; Washio, Takashi; Takeuchi, Shigeki

    2016-10-01

    The accurate detection of small deviations in given density matrice is important for quantum information processing, which is a difficult task because of the intrinsic fluctuation in density matrices reconstructed using a limited number of experiments. We previously proposed a method for decoherence error detection using a machine-learning technique [S. Hara, T. Ono, R. Okamoto, T. Washio, and S. Takeuchi, Phys. Rev. A 89, 022104 (2014), 10.1103/PhysRevA.89.022104]. However, the previous method is not valid when the errors are just changes in phase. Here, we propose a method that is valid for arbitrary errors in density matrices. The performance of the proposed method is verified using both numerical simulation data and real experimental data.

  18. Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

    PubMed

    Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

  19. Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions

    PubMed Central

    Banik, Shipra; Khodadad Khan, A. F. M.; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange. PMID:24701205

  20. Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

    PubMed Central

    Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M.; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V.; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L.; Bilello, Michel; O'Rourke, Donald M.; Davatzikos, Christos

    2016-01-01

    Background MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). Methods One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Results Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. Conclusions By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood–brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. PMID:26188015

  1. Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling

    NASA Astrophysics Data System (ADS)

    Goetz, J. N.; Brenning, A.; Petschko, H.; Leopold, P.

    2015-08-01

    Statistical and now machine learning prediction methods have been gaining popularity in the field of landslide susceptibility modeling. Particularly, these data driven approaches show promise when tackling the challenge of mapping landslide prone areas for large regions, which may not have sufficient geotechnical data to conduct physically-based methods. Currently, there is no best method for empirical susceptibility modeling. Therefore, this study presents a comparison of traditional statistical and novel machine learning models applied for regional scale landslide susceptibility modeling. These methods were evaluated by spatial k-fold cross-validation estimation of the predictive performance, assessment of variable importance for gaining insights into model behavior and by the appearance of the prediction (i.e. susceptibility) map. The modeling techniques applied were logistic regression (GLM), generalized additive models (GAM), weights of evidence (WOE), the support vector machine (SVM), random forest classification (RF), and bootstrap aggregated classification trees (bundling) with penalized discriminant analysis (BPLDA). These modeling methods were tested for three areas in the province of Lower Austria, Austria. The areas are characterized by different geological and morphological settings. Random forest and bundling classification techniques had the overall best predictive performances. However, the performances of all modeling techniques were for the majority not significantly different from each other; depending on the areas of interest, the overall median estimated area under the receiver operating characteristic curve (AUROC) differences ranged from 2.9 to 8.9 percentage points. The overall median estimated true positive rate (TPR) measured at a 10% false positive rate (FPR) differences ranged from 11 to 15pp. The relative importance of each predictor was generally different between the modeling methods. However, slope angle, surface roughness and plan

  2. Comparison of chiropractic student scores before and after utilizing active learning techniques in a classroom setting.

    PubMed

    Guagliardo, Joseph G; Hoiriis, Kathryn T

    2013-01-01

    Objective : We report the differences in final examination scores achieved by students at the culmination of two different teaching strategies in an introductory skills course. Methods : Multiple choice examination scores from six consecutive academic calendar sessions over 18 months (n = 503) were compared. Two groups were used: Cohort A (n = 290) represented students who were enrolled in the course 3 consecutive academic sessions before an instructional change and Cohort B (n = 213) included students who were enrolled in 3 consecutive academic sessions following the instructional change, which included a more active learning format. Statistical analyses used were 2-tailed independent t-test, one-way ANOVA, Tukey's honestly significant difference (HSD), and effect size. Results : The 2-tailed independent t-test revealed a significant difference between the two groups (t = -3.71, p < .001; 95% confidence interval [CI] 1.29-4.20). Significant difference was found in the highest performing subgroup compared to the lowest performing subgroup in Cohort A (F = 3.343, p = .037). For Cohort A subgroups 1 and 2, Tukey's HSD was p < .028. In Cohort B, no difference was found among subgroups (F = 1.912, p = .150, HSD p > .105). Conclusion : Compared to previous versions of the same course taught by the same instructor, the students in the new course design performed better, suggesting that using active learning techniques helps improve student achievement.

  3. Overview of manifold learning techniques for the investigation of disruptions on JET

    NASA Astrophysics Data System (ADS)

    Cannas, B.; Fanni, A.; Murari, A.; Pau, A.; Sias, G.; EFDA Contributors, JET

    2014-11-01

    Identifying a low-dimensional embedding of a high-dimensional data set allows exploration of the data structure. In this paper we tested some existing manifold learning techniques for discovering such embedding within the multidimensional operational space of a nuclear fusion tokamak. Among the manifold learning methods, the following approaches have been investigated: linear methods, such as principal component analysis and grand tour, and nonlinear methods, such as self-organizing map and its probabilistic variant, generative topographic mapping. In particular, the last two methods allow us to obtain a low-dimensional (typically two-dimensional) map of the high-dimensional operational space of the tokamak. These maps provide a way of visualizing the structure of the high-dimensional plasma parameter space and allow discrimination between regions characterized by a high risk of disruption and those with a low risk of disruption. The data for this study comes from plasma discharges selected from 2005 and up to 2009 at JET. The self-organizing map and generative topographic mapping provide the most benefits in the visualization of very large and high-dimensional datasets. Some measures have been used to evaluate their performance. Special emphasis has been put on the position of outliers and extreme points, map composition, quantization errors and topological errors.

  4. An Analysis of a Digital Variant of the Trail Making Test Using Machine Learning Techniques

    PubMed Central

    Dahmen, Jessamyn; Cook, Diane; Fellows, Robert; Schmitter-Edgecombe, Maureen

    2017-01-01

    BACKGROUND The goal of this work is to develop a digital version of a standard cognitive assessment, the Trail Making Test (TMT), and assess its utility. OBJECTIVE This paper introduces a novel digital version of the TMT and introduces a machine learning based approach to assess its capabilities. METHODS Using digital Trail Making Test (dTMT) data collected from (N=54) older adult participants as feature sets, we use machine learning techniques to analyze the utility of the dTMT and evaluate the insights provided by the digital features. RESULTS Predicted TMT scores correlate well with clinical digital test scores (r=0.98) and paper time to completion scores (r=0.65). Predicted TICS exhibited a small correlation with clinically-derived TICS scores (r=0.12 Part A, r=0.10 Part B). Predicted FAB scores exhibited a small correlation with clinically-derived FAB scores (r=0.13 Part A, r=0.29 for Part B). Digitally-derived features were also used to predict diagnosis (AUC of 0.65). CONCLUSION Our findings indicate that the dTMT is capable of measuring the same aspects of cognition as the paper-based TMT. Furthermore, the dTMT’s additional data may be able to help monitor other cognitive processes not captured by the paper-based TMT alone. PMID:27886019

  5. Comparison of chiropractic student scores before and after utilizing active learning techniques in a classroom setting

    PubMed Central

    Guagliardo, Joseph G.; Hoiriis, Kathryn T.

    2013-01-01

    Objective We report the differences in final examination scores achieved by students at the culmination of two different teaching strategies in an introductory skills course. Methods Multiple choice examination scores from six consecutive academic calendar sessions over 18 months (n = 503) were compared. Two groups were used: Cohort A (n = 290) represented students who were enrolled in the course 3 consecutive academic sessions before an instructional change and Cohort B (n = 213) included students who were enrolled in 3 consecutive academic sessions following the instructional change, which included a more active learning format. Statistical analyses used were 2-tailed independent t-test, one-way ANOVA, Tukey's honestly significant difference (HSD), and effect size. Results The 2-tailed independent t-test revealed a significant difference between the two groups (t = −3.71, p < .001; 95% confidence interval [CI] 1.29–4.20). Significant difference was found in the highest performing subgroup compared to the lowest performing subgroup in Cohort A (F = 3.343, p = .037). For Cohort A subgroups 1 and 2, Tukey's HSD was p < .028. In Cohort B, no difference was found among subgroups (F = 1.912, p = .150, HSD p > .105). Conclusion Compared to previous versions of the same course taught by the same instructor, the students in the new course design performed better, suggesting that using active learning techniques helps improve student achievement. PMID:23964739

  6. Selecting statistical or machine learning techniques for regional landslide susceptibility modelling by evaluating spatial prediction

    NASA Astrophysics Data System (ADS)

    Goetz, Jason; Brenning, Alexander; Petschko, Helene; Leopold, Philip

    2015-04-01

    With so many techniques now available for landslide susceptibility modelling, it can be challenging to decide on which technique to apply. Generally speaking, the criteria for model selection should be tied closely to end users' purpose, which could be spatial prediction, spatial analysis or both. In our research, we focus on comparing the spatial predictive abilities of landslide susceptibility models. We illustrate how spatial cross-validation, a statistical approach for assessing spatial prediction performance, can be applied with the area under the receiver operating characteristic curve (AUROC) as a prediction measure for model comparison. Several machine learning and statistical techniques are evaluated for prediction in Lower Austria: support vector machine, random forest, bundling with penalized linear discriminant analysis, logistic regression, weights of evidence, and the generalized additive model. In addition to predictive performance, the importance of predictor variables in each model was estimated using spatial cross-validation by calculating the change in AUROC performance when variables are randomly permuted. The susceptibility modelling techniques were tested in three areas of interest in Lower Austria, which have unique geologic conditions associated with landslide occurrence. Overall, we found for the majority of comparisons that there were little practical or even statistically significant differences in AUROCs. That is the models' prediction performances were very similar. Therefore, in addition to prediction, the ability to interpret models for spatial analysis and the qualitative qualities of the prediction surface (map) are considered and discussed. The measure of variable importance provided some insight into the model behaviour for prediction, in particular for "black-box" models. However, there were no clear patterns in all areas of interest to why certain variables were given more importance over others.

  7. PARTICLE ACCELERATOR

    DOEpatents

    Teng, L.C.

    1960-01-19

    ABS>A combination of two accelerators, a cyclotron and a ring-shaped accelerator which has a portion disposed tangentially to the cyclotron, is described. Means are provided to transfer particles from the cyclotron to the ring accelerator including a magnetic deflector within the cyclotron, a magnetic shield between the ring accelerator and the cyclotron, and a magnetic inflector within the ring accelerator.

  8. Accelerating orthodontic tooth movement: A new, minimally-invasive corticotomy technique using a 3D-printed surgical template

    PubMed Central

    Giansanti, Matteo

    2016-01-01

    Background A reduction in orthodontic treatment time can be attained using corticotomies. The aggressive nature of corticotomy due to the elevation of muco-periosteal flaps and to the duration of the surgery raised reluctance for its employ among patients and dental community. This study aims to provide detailed information on the design and manufacture of a 3D-printed CAD-CAM (computer-aided design and computer-aided manufacturing) surgical guide which can aid the clinician in achieving a minimally-invasive, flapless corticotomy. Material and Methods An impression of dental arches was created; the models were digitally-acquired using a 3D scanner and saved as STereoLithography ( STL ) files. The patient underwent cone beam computed tomography (CBCT): images of jaws and teeth were transformed into 3D models and saved as an STL file. An acrylic template with the design of a surgical guide was manufactured and scanned. The STLs of jaws, scanned casts, and acrylic templates were matched. 3D modeling software allowed the view of the 3D models from different perspectives and planes with perfect rendering. The 3D model of the acrylic template was transformed into a surgical guide with slots designed to guide, at first, a scalpel blade and then a piezoelectric cutting insert. The 3D STL model of the surgical guide was printed. Results This procedure allowed the manufacturing of a 3D-printed CAD/CAM surgical guide, which overcomes the disadvantages of the corticotomy, removing the need for flap elevation. No discomfort, early surgical complications or unexpected events were observed. Conclusions The effectiveness of this minimally-invasive surgical technique can offer the clinician a valid alternative to other methods currently in use. Key words:Corticotomy, orthodontics, CAD/CAM, minimally invasive, surgical template, 3D printer. PMID:27031067

  9. A Dosimetric Comparison of Accelerated Partial Breast Irradiation Techniques: Multicatheter Interstitial Brachytherapy, Three-Dimensional Conformal Radiotherapy, and Supine Versus Prone Helical Tomotherapy

    SciTech Connect

    Patel, Rakesh R. . E-mail: patel@humonc.wisc.edu; Becker, Stewart J.; Das, Rupak K.; Mackie, Thomas R.

    2007-07-01

    Purpose: To compare dosimetrically four different techniques of accelerated partial breast irradiation (APBI) in the same patient. Methods and Materials: Thirteen post-lumpectomy interstitial brachytherapy (IB) patients underwent imaging with preimplant computed tomography (CT) in the prone and supine position. These CT scans were then used to generate three-dimensional conformal radiotherapy (3D-CRT) and prone and supine helical tomotherapy (PT and ST, respectively) APBI plans and compared with the treated IB plans. Dose-volume histogram analysis and the mean dose (NTD{sub mean}) values were compared. Results: Planning target volume coverage was excellent for all methods. Statistical significance was considered to be a p value <0.05. The mean V100 was significantly lower for IB (12% vs. 15% for PT, 18% for ST, and 26% for 3D-CRT). A greater significant differential was seen when comparing V50 with mean values of 24%, 43%, 47%, and 52% for IB, PT, ST, and 3D-CRT, respectively. The IB and PT were similar and delivered an average lung NTD{sub mean} dose of 1.3 Gy{sub 3} and 1.2 Gy{sub 3}, respectively. Both of these methods were statistically significantly lower than the supine external beam techniques. Overall, all four methods yielded similar low doses to the heart. Conclusions: The use of IB and PT resulted in greater normal tissue sparing (especially ipsilateral breast and lung) than the use of supine external beam techniques of 3D-CRT or ST. However, the choice of APBI technique must be tailored to the patient's anatomy, lumpectomy cavity location, and overall treatment goals.

  10. Assessing the Effectiveness of Inquiry-based Learning Techniques Implemented in Large Classroom Settings

    NASA Astrophysics Data System (ADS)

    Steer, D. N.; McConnell, D. A.; Owens, K.

    2001-12-01

    assessments of knowledge-level learning included evaluations of student responses to pre- and post-instruction conceptual test questions, short group exercises and content-oriented exam questions. Higher level thinking skills were assessed when students completed exercises that required the completion of Venn diagrams, concept maps and/or evaluation rubrics both during class periods and on exams. Initial results indicate that these techniques improved student attendance significantly and improved overall retention in the course by 8-14% over traditional lecture formats. Student scores on multiple choice exam questions were slightly higher (1-3%) for students taught in the active learning environment and short answer questions showed larger gains (7%) over students' scores in a more traditional class structure.

  11. A Novel Semi-Supervised Electronic Nose Learning Technique: M-Training

    PubMed Central

    Jia, Pengfei; Huang, Tailai; Duan, Shukai; Ge, Lingpu; Yan, Jia; Wang, Lidan

    2016-01-01

    When an electronic nose (E-nose) is used to distinguish different kinds of gases, the label information of the target gas could be lost due to some fault of the operators or some other reason, although this is not expected. Another fact is that the cost of getting the labeled samples is usually higher than for unlabeled ones. In most cases, the classification accuracy of an E-nose trained using labeled samples is higher than that of the E-nose trained by unlabeled ones, so gases without label information should not be used to train an E-nose, however, this wastes resources and can even delay the progress of research. In this work a novel multi-class semi-supervised learning technique called M-training is proposed to train E-noses with both labeled and unlabeled samples. We employ M-training to train the E-nose which is used to distinguish three indoor pollutant gases (benzene, toluene and formaldehyde). Data processing results prove that the classification accuracy of E-nose trained by semi-supervised techniques (tri-training and M-training) is higher than that of an E-nose trained only with labeled samples, and the performance of M-training is better than that of tri-training because more base classifiers can be employed by M-training. PMID:26985898

  12. Neural Networks for Modeling and Control of Particle Accelerators

    DOE PAGES

    Edelen, A. L.; Biedron, S. G.; Chase, B. E.; ...

    2016-04-01

    Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

  13. Neural Networks for Modeling and Control of Particle Accelerators

    SciTech Connect

    Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

    2016-04-01

    Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

  14. A FIRST LOOK AT CREATING MOCK CATALOGS WITH MACHINE LEARNING TECHNIQUES

    SciTech Connect

    Xu Xiaoying; Ho, Shirley; Trac, Hy; Schneider, Jeff; Ntampaka, Michelle; Poczos, Barnabas

    2013-08-01

    We investigate machine learning (ML) techniques for predicting the number of galaxies (N{sub gal}) that occupy a halo, given the halo's properties. These types of mappings are crucial for constructing the mock galaxy catalogs necessary for analyses of large-scale structure. The ML techniques proposed here distinguish themselves from traditional halo occupation distribution (HOD) modeling as they do not assume a prescribed relationship between halo properties and N{sub gal}. In addition, our ML approaches are only dependent on parent halo properties (like HOD methods), which are advantageous over subhalo-based approaches as identifying subhalos correctly is difficult. We test two algorithms: support vector machines (SVM) and k-nearest-neighbor (kNN) regression. We take galaxies and halos from the Millennium simulation and predict N{sub gal} by training our algorithms on the following six halo properties: number of particles, M{sub 200}, {sigma}{sub v}, v{sub max}, half-mass radius, and spin. For Millennium, our predicted N{sub gal} values have a mean-squared error (MSE) of {approx}0.16 for both SVM and kNN. Our predictions match the overall distribution of halos reasonably well and the galaxy correlation function at large scales to {approx}5%-10%. In addition, we demonstrate a feature selection algorithm to isolate the halo parameters that are most predictive, a useful technique for understanding the mapping between halo properties and N{sub gal}. Lastly, we investigate these ML-based approaches in making mock catalogs for different galaxy subpopulations (e.g., blue, red, high M{sub star}, low M{sub star}). Given its non-parametric nature as well as its powerful predictive and feature selection capabilities, ML offers an interesting alternative for creating mock catalogs.

  15. The relationships between the use of self-regulated learning strategies and depression among medical students: an accelerated prospective cohort study.

    PubMed

    Van Nguyen, Hung; Laohasiriwong, Wongsa; Saengsuwan, Jiamjit; Thinkhamrop, Bandit; Wright, Pamela

    2015-01-01

    We conducted this study to determine the relationships between the use of self-regulated learning strategies (SRL) and depression scores among medical students. An accelerated prospective cohort study among 623 students at a public medical university in Vietnam was carried out during the academic year 2012-2013. The Depression, Anxiety and Stress Scales (21 items) was used to measure depression scores as the primary research outcome, and to measure anxiety and stress scores as the confounding variables. Fourteen SRL subscales including intrinsic/extrinsic goal orientation, task value, self-efficacy for learning, control of learning beliefs, rehearsal, elaboration, organization, critical thinking, meta-cognitive strategies, time and study environment, effort regulation, peer learning, and help seeking were measured using the Motivated Strategies for Learning Questionnaire. Data were collected at two points in time (once each semester). There were 744 responses at the first time (95.88%) and 623 at time two (drop-out rate of 16.26%). The generalized estimating equation was applied to identify any relationships between the use of each SRL subscale and depression scores at time 2, adjusting for the effects of depression at time 1, anxiety, stress, within cluster correlation, and potential demographic covariates. Separate multivariate GEE analysis indicated that all SRL subscales were significantly negatively associated with depression scores, except for extrinsic goal orientation and peer learning. Whereas full multivariate GEE analysis revealed that self-efficacyT1, help-seekingT1, time and study environmentT2 were found to be significantly negatively associated with depressionT2, adjusting for the effects of depressionT1, anxiety, stress, and demographic covariates. The results should be used to provide appropriate support for medical students to reduce depression.

  16. Microwave Heating of Synthetic Skin Samples for Potential Treatment of Gout Using the Metal-Assisted and Microwave-Accelerated Decrystallization Technique

    PubMed Central

    2016-01-01

    Physical stability of synthetic skin samples during their exposure to microwave heating was investigated to demonstrate the use of the metal-assisted and microwave-accelerated decrystallization (MAMAD) technique for potential biomedical applications. In this regard, optical microscopy and temperature measurements were employed for the qualitative and quantitative assessment of damage to synthetic skin samples during 20 s intermittent microwave heating using a monomode microwave source (at 8 GHz, 2–20 W) up to 120 s. The extent of damage to synthetic skin samples, assessed by the change in the surface area of skin samples, was negligible for microwave power of ≤7 W and more extensive damage (>50%) to skin samples occurred when exposed to >7 W at initial temperature range of 20–39 °C. The initial temperature of synthetic skin samples significantly affected the extent of change in temperature of synthetic skin samples during their exposure to microwave heating. The proof of principle use of the MAMAD technique was demonstrated for the decrystallization of a model biological crystal (l-alanine) placed under synthetic skin samples in the presence of gold nanoparticles. Our results showed that the size (initial size ∼850 μm) of l-alanine crystals can be reduced up to 60% in 120 s without damage to synthetic skin samples using the MAMAD technique. Finite-difference time-domain-based simulations of the electric field distribution of an 8 GHz monomode microwave radiation showed that synthetic skin samples are predicted to absorb ∼92.2% of the microwave radiation. PMID:27917407

  17. Microwave Heating of Synthetic Skin Samples for Potential Treatment of Gout Using the Metal-Assisted and Microwave-Accelerated Decrystallization Technique.

    PubMed

    Toker, Salih; Boone-Kukoyi, Zainab; Thompson, Nishone; Ajifa, Hillary; Clement, Travis; Ozturk, Birol; Aslan, Kadir

    2016-11-30

    Physical stability of synthetic skin samples during their exposure to microwave heating was investigated to demonstrate the use of the metal-assisted and microwave-accelerated decrystallization (MAMAD) technique for potential biomedical applications. In this regard, optical microscopy and temperature measurements were employed for the qualitative and quantitative assessment of damage to synthetic skin samples during 20 s intermittent microwave heating using a monomode microwave source (at 8 GHz, 2-20 W) up to 120 s. The extent of damage to synthetic skin samples, assessed by the change in the surface area of skin samples, was negligible for microwave power of ≤7 W and more extensive damage (>50%) to skin samples occurred when exposed to >7 W at initial temperature range of 20-39 °C. The initial temperature of synthetic skin samples significantly affected the extent of change in temperature of synthetic skin samples during their exposure to microwave heating. The proof of principle use of the MAMAD technique was demonstrated for the decrystallization of a model biological crystal (l-alanine) placed under synthetic skin samples in the presence of gold nanoparticles. Our results showed that the size (initial size ∼850 μm) of l-alanine crystals can be reduced up to 60% in 120 s without damage to synthetic skin samples using the MAMAD technique. Finite-difference time-domain-based simulations of the electric field distribution of an 8 GHz monomode microwave radiation showed that synthetic skin samples are predicted to absorb ∼92.2% of the microwave radiation.

  18. Black Ink and Red Ink (BIRI) Testing: A Testing Method to Evaluate Both Recall and Recognition Learning in Accelerated Adult-Learning Courses

    ERIC Educational Resources Information Center

    Rodgers, Joseph Lee; Rodgers, Jacci L.

    2011-01-01

    We propose, develop, and evaluate the black ink-red ink (BIRI) method of testing. This approach uses two different methods within the same test administration setting, one that matches recognition learning and the other that matches recall learning. Students purposively define their own tradeoff between the two approaches. Evaluation of the method…

  19. Accelerator on a Chip

    SciTech Connect

    England, Joel

    2014-06-30

    SLAC's Joel England explains how the same fabrication techniques used for silicon computer microchips allowed their team to create the new laser-driven particle accelerator chips. (SLAC Multimedia Communications)

  20. Accelerator on a Chip

    ScienceCinema

    England, Joel

    2016-07-12

    SLAC's Joel England explains how the same fabrication techniques used for silicon computer microchips allowed their team to create the new laser-driven particle accelerator chips. (SLAC Multimedia Communications)

  1. Enhancing Learning Management Systems Utility for Blind Students: A Task-Oriented, User-Centered, Multi-Method Evaluation Technique

    ERIC Educational Resources Information Center

    Babu, Rakesh; Singh, Rahul

    2013-01-01

    This paper presents a novel task-oriented, user-centered, multi-method evaluation (TUME) technique and shows how it is useful in providing a more complete, practical and solution-oriented assessment of the accessibility and usability of Learning Management Systems (LMS) for blind and visually impaired (BVI) students. Novel components of TUME…

  2. Helping Adolescents with ADHD & Learning Disabilities: Ready-To-Use Tips, Techniques, and Checklists for School Success.

    ERIC Educational Resources Information Center

    Greenbaum, Judith; Markel, Geraldine

    This manual is intended to provide practical guidance to teachers of adolescents with attention deficit hyperactivity disorder (ADHD) and/or learning disabilities (LD) through specific techniques, teaching strategies, checklists, and student case histories. The 12 chapters address the following topics: (1) an overview of ADHD and LD including…

  3. Examining Mobile Learning Trends 2003-2008: A Categorical Meta-Trend Analysis Using Text Mining Techniques

    ERIC Educational Resources Information Center

    Hung, Jui-Long; Zhang, Ke

    2012-01-01

    This study investigated the longitudinal trends of academic articles in Mobile Learning (ML) using text mining techniques. One hundred and nineteen (119) refereed journal articles and proceedings papers from the SCI/SSCI database were retrieved and analyzed. The taxonomies of ML publications were grouped into twelve clusters (topics) and four…

  4. The Effectiveness of Using WhatsApp Messenger as One of Mobile Learning Techniques to Develop Students' Writing Skills

    ERIC Educational Resources Information Center

    Fattah, Said Fathy El Said Abdul

    2015-01-01

    The present study was an attempt to determine the effectiveness of using a WhatsApp Messenger as one of mobile learning techniques to develop students' writing skills. Participants were 30 second year college students, English department from a private university in Saudi Arabia. The experimental group (N = 15) used WhatsApp technology to develop…

  5. Recognition of Prior Learning as a Technique for Fabricating the Adult Learner: A Genealogical Analysis on Swedish Adult Education Policy

    ERIC Educational Resources Information Center

    Andersson, Per; Fejes, Andreas

    2005-01-01

    This article focuses on the recognition of prior learning and the figure of thought it represents in Swedish policy on adult education. It can be seen as a technique for governing the adult learner and a way of fabricating the subject. We are tracing this thought back in time to see how it has changed and what it consists of. The material analysed…

  6. The Impact of a Modified Cooperative Learning Technique on the Grade Frequencies Observed in a Preparatory Chemistry Course

    NASA Astrophysics Data System (ADS)

    Hayes Russell, Bridget J.

    This dissertation explored the impact of a modified cooperative learning technique on the final grade frequencies observed in a large preparatory chemistry course designed for pre-science majors. Although the use of cooperative learning at all educational levels is well researched and validated in the literature, traditional lectures still dominate as the primary methodology of teaching. This study modified cooperative learning techniques by addressing commonly cited reasons for not using the methodology. Preparatory chemistry students were asked to meet in cooperative groups outside of class time to complete homework assignments. A chi-square goodness-of-fit revealed that the final grade frequency distributions observed were different than expected. Although the distribution was significantly different, the resource investment using this particular design challenged the practical significance of the findings. Further, responses from a survey revealed that the students did not use the suggested group functioning methods that empirically are known to lead to more practically significant results.

  7. A preliminary investigation of the effects of giving testimony and learning yogic breathing techniques on battered women's feelings of depression.

    PubMed

    Franzblau, Susan H; Echevarria, Sonia; Smith, Michelle; Van Cantfort, Thomas E

    2008-12-01

    Researchers have shown that mood and sense of control over one's life are significantly affected by testimony and other forms of disclosure and that learning to control breathing has positive effects on mood and anxiety. This preliminary experiment tests whether African American and European American abused women who give testimony about their experiences of intimate partner violence and learn how to use yogic breathing techniques have reduced feelings of depression. Results indicate that learning yogic breathing techniques alone and combined with giving testimony significantly reduces feelings of depression. Recasting women as authorities on domestic violence and teaching them how to calm their minds by focusing on yogic breathing may be simple and effective ways to help women take control over their bodies and lives.

  8. Using Radar Charts with Qualitative Evaluation: Techniques to Assess Change in Blended Learning

    ERIC Educational Resources Information Center

    Kaczynski, Dan; Wood, Leigh; Harding, Ansie

    2008-01-01

    When university academics implement changes in learning, such as introducing blended learning, it is conventional practice to examine and evaluate the impact of the resulting curriculum reform. Judging the worth and impact of an educational development is a complex task involving subtle differences in learning. Qualitative methods to explore these…

  9. Online Learning Behaviors for Radiology Interns Based on Association Rules and Clustering Technique

    ERIC Educational Resources Information Center

    Chen, Hsing-Shun; Liou, Chuen-He

    2014-01-01

    In a hospital, clinical teachers must also care for patients, so there is less time for the teaching of clinical courses, or for discussing clinical cases with interns. However, electronic learning (e-learning) can complement clinical skills education for interns in a blended-learning process. Students discuss and interact with classmates in an…

  10. The Field Study as an Educational Technique in Open and Distance Learning

    ERIC Educational Resources Information Center

    Vassala, Paraskevi

    2006-01-01

    The main characteristic of Distance Learning is that the student is taught and learns without his tutor's physical presence in the classroom. The opportunity for a direct (face to face) communication between all members of the educational group [tutor counselor (TC) and students] in Distance Learning is offered by the Tutorials/Contact Sessions…

  11. Performance degradation studies on an poly 2,5-benzimidazole high-temperature proton exchange membrane fuel cell using an accelerated degradation technique

    NASA Astrophysics Data System (ADS)

    Jung, Guo-Bin; Chen, Hsin-Hung; Yan, Wei-Mon

    2014-02-01

    In this work, the performance degradation of a poly 2,5-benzimidazole (ABPBI) based high-temperature proton exchange membrane fuel cell (HT-PEMFC) was examined using an accelerated degradation technique (ADT). Experiments using an ADT with 30 min intervals were performed by applying 1.5 V to a membrane electrode assembly (MEA) with hydrogen and nitrogen feeding to the anode and cathode, respectively, to simulate the high voltage generated during fuel cell shutdown and restart. The characterization of the MEAs was performed using in-situ and ex-situ electrochemical methods, such as polarization curves, AC impedance, and cyclic voltammetry (CV), and TEM imaging before and after the ADT experiments. The measured results demonstrated that the ADT testing could be used to dramatically reduce the duration of the degradation. The current output at 0.4 V decreased by 48% after performing ADT testing for 30 min. From the AC impedance, CV and RTGA measurements, the decline in cell performance was found to be primarily due to corrosion and thinning of the catalyst layer (or carbon support) during the first 30 min, leading to the dissolution and agglomeration of the platinum catalyst.

  12. Studies on DNA adduction with heterocyclic amines by accelerator mass spectrometry: a new technique for tracing isotope-labelled DNA adduction.

    PubMed

    Turteltaub, K W; Vogel, J S; Frantz, C E; Fultz, E

    1993-01-01

    DNA adduction in rodents at doses equivalent to human dietary exposure (10(4)-10(6)-fold lower than laboratory studies) is being studied using accelerator mass spectrometry (AMS). AMS is a nuclear physics technique for detection of cosmogenic isotopes and has been used for specifically selecting and counting 14C. Using AMS, DNA adducts are detectable at levels of 1-10 adducts/10(12) nucleotides following acute and chronic dosing regimes with 14C-labelled carcinogens. The adduct detection limit has been imposed by the natural abundance of 14C in the samples and animal-to-animal variation. AMS is also being coupled to HPLC, multidimensional TLC and radio-immunoassay. In addition, AMS's great sensitivity makes it useful for demonstrating that drugs and chemicals do not bind to DNA. The use of AMS, however, is limited to situations where radiolabelled agents can be used. The data suggest that AMS is extremely useful in obtaining quantitative data on the effects of carcinogens on DNA at the low doses common for actual human exposures and may be useful in human studies.

  13. 3D motion adapted gating (3D MAG): a new navigator technique for accelerated acquisition of free breathing navigator gated 3D coronary MR-angiography.

    PubMed

    Hackenbroch, M; Nehrke, K; Gieseke, J; Meyer, C; Tiemann, K; Litt, H; Dewald, O; Naehle, C P; Schild, H; Sommer, T

    2005-08-01

    This study aimed to evaluate the influence of a new navigator technique (3D MAG) on navigator efficiency, total acquisition time, image quality and diagnostic accuracy. Fifty-six patients with suspected coronary artery disease underwent free breathing navigator gated coronary MRA (Intera, Philips Medical Systems, 1.5 T, spatial resolution 0.9x0.9x3 mm3) with and without 3D MAG. Evaluation of both sequences included: 1) navigator scan efficiency, 2) total acquisition time, 3) assessment of image quality and 4) detection of stenoses >50%. Average navigator efficiencies of the LCA and RCA were 43+/-12% and 42+/-12% with and 36+/-16% and 35+/-16% without 3D MAG (P<0.01). Scan time was reduced from 12 min 7 s without to 8 min 55 s with 3D MAG for the LCA and from 12 min 19 s to 9 min 7 s with 3D MAG for the RCA (P<0.01). The average scores of image quality of the coronary MRAs with and without 3D MAG were 3.5+/-0.79 and 3.46+/-0.84 (P>0.05). There was no significant difference in the sensitivity and specificity in the detection of coronary artery stenoses between coronary MRAs with and without 3D MAG (P>0.05). 3D MAG provides accelerated acquisition of navigator gated coronary MRA by about 19% while maintaining image quality and diagnostic accuracy.

  14. Machine learning techniques as a helpful tool toward determination of plaque vulnerability.

    PubMed

    Cilla, Myriam; Martínez, Javier; Peña, Estefanía; Martínez, Miguel Ángel

    2012-04-01

    Atherosclerotic cardiovascular disease results in millions of sudden deaths annually, and coronary artery disease accounts for the majority of this toll. Plaque rupture plays main role in the majority of acute coronary syndromes. Rupture has been usually associated with stress concentrations, which are determined mainly by tissue properties and plaque geometry. The aim of this study is develop a tool, using machine learning techniques to assist the clinical professionals on decisions of the vulnerability of the atheroma plaque. In practice, the main drawbacks of 3-D finite element analysis to predict the vulnerability risk are the huge main memories required and the long computation times. Therefore, it is essential to use these methods which are faster and more efficient. This paper discusses two potential applications of computational technologies, artificial neural networks and support vector machines, used to assess the role of maximum principal stress in a coronary vessel with atheroma plaque as a function of the main geometrical features in order to quantify the vulnerability risk.

  15. A versatile implementation of the psychrometer technique as a learning opportunity in atmospheric physics courses

    NASA Astrophysics Data System (ADS)

    Caporaloni, Marina; Vitullo, Caterina

    2005-01-01

    Even today the psychrometer technique, if properly implemented, is used as a calibration standard for humidity measurements. In order to simplify the cumbersome use of the classical instrument, we recently proposed an original configuration characterized by the unattended operation and real-time readout of temperature sensors. More recently, we have upgraded that system by applying the online data acquisition controlled by a LabVIEW code which also displays the final observable of relative humidity. The program implements the psychrometer algorithm, usually available only in the form of tables, and also the data recording on disk. We describe here how to properly build the instrument and how to guarantee its intrinsic accuracy (typical uncertainty within a few per cent) as well as all the details of the formulae used. The psychrometer, proposed as a project work to university students following new courses on meteorological instrumentation, was found to be a powerful source of learning opportunities. Although at first, the working principle of the instrument looks easy and offers an intuitive interpretation of the concept of humidity, later students become aware of how difficult requirements have to be satisfied in order to realize a reference standard. As a final verification, they are asked to guarantee that this psychrometer implementation strictly conforms to the official recommendations of the World Meteorological Organization (WMO). We present here a few examples of their activities in planning autonomously a series of checks and measurements.

  16. Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

    NASA Technical Reports Server (NTRS)

    Lee, Hanbong

    2016-01-01

    Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

  17. Machine Learning Techniques Applied to Sensor Data Correction in Building Technologies

    SciTech Connect

    Smith, Matt K; Castello, Charles C; New, Joshua Ryan

    2013-01-01

    Since commercial and residential buildings account for nearly half of the United States' energy consumption, making them more energy-efficient is a vital part of the nation's overall energy strategy. Sensors play an important role in this research by collecting data needed to analyze performance of components, systems, and whole-buildings. Given this reliance on sensors, ensuring that sensor data are valid is a crucial problem. Solutions being researched are machine learning techniques, namely: artificial neural networks and Bayesian Networks. Types of data investigated in this study are: (1) temperature; (2) humidity; (3) refrigerator energy consumption; (4) heat pump liquid pressure; and (5) water flow. These data are taken from Oak Ridge National Laboratory's (ORNL) ZEBRAlliance research project which is composed of four single-family homes in Oak Ridge, TN. Results show that for the temperature, humidity, pressure, and flow sensors, data can mostly be predicted with root-mean-square error (RMSE) of less than 10% of the respective sensor's mean value. Results for the energy sensor are not as good; RMSE are centered about 100% of the mean value and are often well above 200%. Bayesian networks have RSME of less than 5% of the respective sensor's mean value, but took substantially longer to train.

  18. A comparison of machine learning techniques for detection of drug target articles.

    PubMed

    Danger, Roxana; Segura-Bedmar, Isabel; Martínez, Paloma; Rosso, Paolo

    2010-12-01

    Important progress in treating diseases has been possible thanks to the identification of drug targets. Drug targets are the molecular structures whose abnormal activity, associated to a disease, can be modified by drugs, improving the health of patients. Pharmaceutical industry needs to give priority to their identification and validation in order to reduce the long and costly drug development times. In the last two decades, our knowledge about drugs, their mechanisms of action and drug targets has rapidly increased. Nevertheless, most of this knowledge is hidden in millions of medical articles and textbooks. Extracting knowledge from this large amount of unstructured information is a laborious job, even for human experts. Drug target articles identification, a crucial first step toward the automatic extraction of information from texts, constitutes the aim of this paper. A comparison of several machine learning techniques has been performed in order to obtain a satisfactory classifier for detecting drug target articles using semantic information from biomedical resources such as the Unified Medical Language System. The best result has been achieved by a Fuzzy Lattice Reasoning classifier, which reaches 98% of ROC area measure.

  19. Machine-learning techniques for geochemical discrimination of 2011 Tohoku tsunami deposits

    PubMed Central

    Kuwatani, Tatsu; Nagata, Kenji; Okada, Masato; Watanabe, Takahiro; Ogawa, Yasumasa; Komai, Takeshi; Tsuchiya, Noriyoshi

    2014-01-01

    Geochemical discrimination has recently been recognised as a potentially useful proxy for identifying tsunami deposits in addition to classical proxies such as sedimentological and micropalaeontological evidence. However, difficulties remain because it is unclear which elements best discriminate between tsunami and non-tsunami deposits. Herein, we propose a mathematical methodology for the geochemical discrimination of tsunami deposits using machine-learning techniques. The proposed method can determine the appropriate combinations of elements and the precise discrimination plane that best discerns tsunami deposits from non-tsunami deposits in high-dimensional compositional space through the use of data sets of bulk composition that have been categorised as tsunami or non-tsunami sediments. We applied this method to the 2011 Tohoku tsunami and to background marine sedimentary rocks. After an exhaustive search of all 262,144 (= 218) combinations of the 18 analysed elements, we observed several tens of combinations with discrimination rates higher than 99.0%. The analytical results show that elements such as Ca and several heavy-metal elements are important for discriminating tsunami deposits from marine sedimentary rocks. These elements are considered to reflect the formation mechanism and origin of the tsunami deposits. The proposed methodology has the potential to aid in the identification of past tsunamis by using other tsunami proxies. PMID:25399750

  20. Observational Astronomy for Undergraduate Majors: A Hands-On Approach for Learning Professional Techniques

    NASA Astrophysics Data System (ADS)

    Doppmann, G.; Hemenway, M. K.

    2000-12-01

    We present a lab curriculum for undergraduates designed to provide hands-on experience with telescope operation, CCD imaging, and data reduction and analysis with IRAF. Theoretical concepts involving telescope optics, CCD detector characteristics, apparent motions of celestial objects, and photometric properties of stars were introduced in weekly lectures and were central to each lab. The students worked in groups of five using our department 16-inch classical Cassegrain telescope with its new Optomechanics mount and drive which facilitated target aquisition and tracking. Digital images were obtained using a KX260 Apogee CCD camera and read out with a PC running CCDSoft in the dome. Students transfered their data via ethernet to a new computing lab for undergraduates that has IRAF packages installed on PCs running linux. Using these state of the art tools, students learned techniques of data reduction and analysis used by the professional community. The five exercises were field tested during the spring 2000 semester. Students first characterized the telescope and CCD detector, becoming familiar with all aspects of taking data and preparing for an observing run. Later labs involved photometry of standard stars to establish telescope throughput and photometry of cluster stars in M44 to verify distance using measured B-V colors. \

  1. Modelling and analysing track cycling Omnium performances using statistical and machine learning techniques.

    PubMed

    Ofoghi, Bahadorreza; Zeleznikow, John; Dwyer, Dan; Macmahon, Clare

    2013-01-01

    This article describes the utilisation of an unsupervised machine learning technique and statistical approaches (e.g., the Kolmogorov-Smirnov test) that assist cycling experts in the crucial decision-making processes for athlete selection, training, and strategic planning in the track cycling Omnium. The Omnium is a multi-event competition that will be included in the summer Olympic Games for the first time in 2012. Presently, selectors and cycling coaches make decisions based on experience and intuition. They rarely have access to objective data. We analysed both the old five-event (first raced internationally in 2007) and new six-event (first raced internationally in 2011) Omniums and found that the addition of the elimination race component to the Omnium has, contrary to expectations, not favoured track endurance riders. We analysed the Omnium data and also determined the inter-relationships between different individual events as well as between those events and the final standings of riders. In further analysis, we found that there is no maximum ranking (poorest performance) in each individual event that riders can afford whilst still winning a medal. We also found the required times for riders to finish the timed components that are necessary for medal winning. The results of this study consider the scoring system of the Omnium and inform decision-making toward successful participation in future major Omnium competitions.

  2. Deep assessment of machine learning techniques using patient treatment in acute abdominal pain in children.

    PubMed

    Blazadonakis, M; Moustakis, V; Charissis, G

    1996-11-01

    Learning from patient records may aid knowledge acquisition and decision making. Existing inductive machine learning (ML) systems such us NewId, CN2, C4.5 and AQ15 learn from past case histories using symbolic and/or numeric values. These systems learn symbolic rules (IF... THEN like) which link an antecedent set of clinical factors to a consequent class or decision. This paper compares the learning performance of alternative ML systems with each other and with respect to a novel approach using logic minimization, called LML, to learn from data. Patient cases were taken from the archives of the Paediatric Surgery Clinic of the University Hospital of Crete, Heraklion, Greece. Comparison of ML system performance is based both on classification accuracy and on informal expert assessment of learned knowledge.

  3. Does Teaching Mnemonics for Vocabulary Learning Make a Difference? Putting the Keyword Method and the Word Part Technique to the Test

    ERIC Educational Resources Information Center

    Wei, Zheng

    2015-01-01

    The present research tested the effectiveness of the word part technique in comparison with the keyword method and self-strategy learning. One hundred and twenty-one Chinese year-one university students were randomly assigned to one of the three learning conditions: word part, keyword or self-strategy learning condition. Half of the target words…

  4. Stereotactic Irradiation of the Postoperative Resection Cavity for Brain Metastasis: A Frameless Linear Accelerator-Based Case Series and Review of the Technique

    SciTech Connect

    Kelly, Paul J.; Alexander, Brian M.; Hacker, Fred; Marcus, Karen J.; Weiss, Stephanie E.

    2012-01-01

    Purpose: Whole-brain radiation therapy (WBRT) is the standard of care after resection of a brain metastasis. However, concern regarding possible neurocognitive effects and the lack of survival benefit with this approach has led to the use of stereotactic radiosurgery (SRS) to the resection cavity in place of WBRT. We report our initial experience using an image-guided linear accelerator-based frameless stereotactic system and review the technical issues in applying this technique. Methods and Materials: We retrospectively reviewed the setup accuracy, treatment outcome, and patterns of failure of the first 18 consecutive cases treated at Brigham and Women's Hospital. The target volume was the resection cavity without a margin excluding the surgical track. Results: The median number of brain metastases per patient was 1 (range, 1-3). The median planning target volume was 3.49 mL. The median prescribed dose was 18 Gy (range, 15-18 Gy) with normalization ranging from 68% to 85%. In all cases, 99% of the planning target volume was covered by the prescribed dose. The median conformity index was 1.6 (range, 1.41-1.92). The SRS was delivered with submillimeter accuracy. At a median follow-up of 12.7 months, local control was achieved in 16/18 cavities treated. True local recurrence occurred in 2 patients. No marginal failures occurred. Distant recurrence occurred in 6/17 patients. Median time to any failure was 7.4 months. No Grade 3 or higher toxicity was recorded. A long interval between initial cancer diagnosis and the development of brain metastasis was the only factor that trended toward a significant association with the absence of recurrence (local or distant) (log-rank p = 0.097). Conclusions: Frameless stereotactic irradiation of the resection cavity after surgery for a brain metastasis is a safe and accurate technique that offers durable local control and defers the use of WBRT in select patients. This technique should be tested in larger prospective studies.

  5. Teaching Laboratory Rodent Research Techniques under the Tenets of Situated Learning Improves Student Confidence and Promotes Collaboration

    PubMed Central

    Whitcomb, Tiffany L; Taylor, Edward W

    2014-01-01

    A targeted needs assessment at our institution revealed that the online system used to train researchers on performing techniques with animals did not provide opportunities to practice skills, introduce learners to animal care staff, nor satisfactorily support researchers’ needs to become comfortable with laboratory animal species. To correct these deficiencies, a series of hands-on training sessions, framed theoretically in situated learning, was developed. This theoretical framework asserts that learning for everyday living (in this case, performing laboratory animal techniques) happens when people interact within the community while using the ‘tools at hand’ (that is, the instruments and jargon of the field). From this perspective, the students work alongside the instructor as apprentices. The instructor creates increasingly challenging learning opportunities as students work toward independently performing techniques. To test our hypothesis that teaching from this perspective improves comfort levels with laboratory animals and promotes collaborative relationships between animal care and research personnel, a mixed-method design involving online surveys (first survey, n = 45; second survey, n = 35) and semistructured interviews (n = 10) was used. Quantitative results revealed that students became more comfortable with laboratory animals and were more likely to contact animal care personnel due to participating in the training program. The qualitative arm of the study identified specific features of the training program that improved comfort levels for students (seeing then doing, working in small groups, learning within a comfortable environment, and building collegial relationships). These results support teaching rodent research techniques from the practical and theoretical approach of situated learning. PMID:25199092

  6. Vascular Surgery Trainees Still Need to Learn How to Sew: Importance of Learning Surgical Techniques in the Era of Endovascular Surgery

    PubMed Central

    Aziz, Faisal

    2015-01-01

    Vascular surgery represents one of the most rapidly evolving specialties in the field of surgery. It was merely 100 years ago when Dr. Alexis Carrel described vascular anastomosis. Over the course of next several decades, vascular surgeons distinguished themselves from general surgeons by horning the techniques of vascular surgery operations. In the era of minimally invasive interventions, the number of endovascular interventions performed by vascular surgeons has increased exponentially. Vascular surgery trainees in the current times spend considerable time in mastering the techniques of endovascular operations. Unfortunately, the reduction in number of open surgical operations has lead to concerns in regards to adequacy of learning open surgical techniques. In future, majority of vascular interventions will be done with minimally invasive techniques. Combination of poor training in open operations and increasing complexity of open surgical operations may lead to poor surgical outcomes. It is the need of the hour for vascular surgery trainees to realize the importance of learning and mastering open surgical techniques. One of the most distinguishing features of contemporary vascular surgeons is their ability to perform both endovascular and open vascular surgery operations, and we should strive to maintain our excellence in both of these arenas. PMID:26029698

  7. Accelerating Decoding-Related Skills in Poor Readers Learning a Foreign Language: A Computer-Based Intervention

    ERIC Educational Resources Information Center

    Björn, Piia Maria; Leppänen, Paavo H. T.

    2013-01-01

    The results of Fast ForWord® training on English decoding-related skills were examined. Finnish fifth-grade students were identified as having reading fluency problems and poor skills in English as a foreign language learned at school and were randomly assigned to either a training group (TRG) or a control group. The TRG ("n"?=?13)…

  8. What can we learn from inverse methods regarding the processes behind the acceleration and retreat of Helheim glacier (Greenland)?

    NASA Astrophysics Data System (ADS)

    Gagliardini, O.; Gillet-chaulet, F.; Martin, N.; Monnier, J.; Singh, J.

    2011-12-01

    Greenland outlet glaciers control the ice discharge toward the sea and the resulting contribution to sea level rise. Physical processes at the root of the observed acceleration and retreat, - decrease of the back force at the calving terminus, increase of basal lubrication and decrease of the lateral friction -, are still not well understood. All these three processes certainly play a role but their relative contributions have not yet been quantified. Helheim glacier, located on the east coast of Greenland, has undergone an enhanced retreat since 2003, and this retreat was concurrent with accelerated ice flow. In this study, the flowline dataset including surface elevation, surface velocity and front position of Helheim from 2001 to 2006 is used to quantify the sensitivity of each of these processes. For that, we used the full-Stokes finite element ice flow model DassFlow/Ice, including adjoint code and full 4d-var data assimilation process in which the control variables are the basal and lateral friction parameters as well as the calving front pressure. For each available date, the sensitivity of each processes is first studied and an optimal distribution is then inferred from the surface measurements. Using this optimal distribution of these parameters, a transient simulation is performed over the whole dataset period. The relative contributions of the basal friction, lateral friction and front back force are then discussed under the light of these new results.

  9. Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators

    PubMed Central

    Irusta, Unai; Morgado, Eduardo; Aramendi, Elisabete; Ayala, Unai; Wik, Lars; Kramer-Johansen, Jo; Eftestøl, Trygve; Alonso-Atienza, Felipe

    2016-01-01

    Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival of out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrillators (AED). AED algorithms for VF-detection are customarily assessed using Holter recordings from public electrocardiogram (ECG) databases, which may be different from the ECG seen during OHCA events. This study evaluates VF-detection using data from both OHCA patients and public Holter recordings. ECG-segments of 4-s and 8-s duration were analyzed. For each segment 30 features were computed and fed to state of the art machine learning (ML) algorithms. ML-algorithms with built-in feature selection capabilities were used to determine the optimal feature subsets for both databases. Patient-wise bootstrap techniques were used to evaluate algorithm performance in terms of sensitivity (Se), specificity (Sp) and balanced error rate (BER). Performance was significantly better for public data with a mean Se of 96.6%, Sp of 98.8% and BER 2.2% compared to a mean Se of 94.7%, Sp of 96.5% and BER 4.4% for OHCA data. OHCA data required two times more features than the data from public databases for an accurate detection (6 vs 3). No significant differences in performance were found for different segment lengths, the BER differences were below 0.5-points in all cases. Our results show that VF-detection is more challenging for OHCA data than for data from public databases, and that accurate VF-detection is possible with segments as short as 4-s. PMID:27441719

  10. Future accelerators (?)

    SciTech Connect

    John Womersley

    2003-08-21

    I describe the future accelerator facilities that are currently foreseen for electroweak scale physics, neutrino physics, and nuclear structure. I will explore the physics justification for these machines, and suggest how the case for future accelerators can be made.

  11. "Mushin": Learning in Technique-Intensive Sports as a Process of Uniting Mind and Body through Complex Learning Theory

    ERIC Educational Resources Information Center

    Light, Richard L.; Kentel, Jeanne Adéle

    2015-01-01

    Background: Interest in the use of learning theory to inform sport and physical-education pedagogy over the past decade beyond games and team sports has been limited. Purpose: Following on from recent interest within the literature in Eastern philosophic traditions, this article draws on the Japanese concept of "mushin" and complex…

  12. Hippocampal-Sparing Whole-Brain Radiotherapy: A 'How-To' Technique Using Helical Tomotherapy and Linear Accelerator-Based Intensity-Modulated Radiotherapy

    SciTech Connect

    Gondi, Vinai; Tolakanahalli, Ranjini; Mehta, Minesh P.; Tewatia, Dinesh; Rowley, Howard; Kuo, John S.; Khuntia, Deepak; Tome, Wolfgang A.

    2010-11-15

    Purpose: Sparing the hippocampus during cranial irradiation poses important technical challenges with respect to contouring and treatment planning. Herein we report our preliminary experience with whole-brain radiotherapy using hippocampal sparing for patients with brain metastases. Methods and Materials: Five anonymous patients previously treated with whole-brain radiotherapy with hippocampal sparing were reviewed. The hippocampus was contoured, and hippocampal avoidance regions were created using a 5-mm volumetric expansion around the hippocampus. Helical tomotherapy and linear accelerator (LINAC)-based intensity-modulated radiotherapy (IMRT) treatment plans were generated for a prescription dose of 30 Gy in 10 fractions. Results: On average, the hippocampal avoidance volume was 3.3 cm{sup 3}, occupying 2.1% of the whole-brain planned target volume. Helical tomotherapy spared the hippocampus, with a median dose of 5.5 Gy and maximum dose of 12.8 Gy. LINAC-based IMRT spared the hippocampus, with a median dose of 7.8 Gy and maximum dose of 15.3 Gy. On a per-fraction basis, mean dose to the hippocampus (normalized to 2-Gy fractions) was reduced by 87% to 0.49 Gy{sub 2} using helical tomotherapy and by 81% to 0.73 Gy{sub 2} using LINAC-based IMRT. Target coverage and homogeneity was acceptable with both IMRT modalities, with differences largely attributed to more rapid dose fall-off with helical tomotherapy. Conclusion: Modern IMRT techniques allow for sparing of the hippocampus with acceptable target coverage and homogeneity. Based on compelling preclinical evidence, a Phase II cooperative group trial has been developed to test the postulated neurocognitive benefit.

  13. Seeing the System through the End Users' Eyes: Shadow Expert Technique for Evaluating the Consistency of a Learning Management System

    NASA Astrophysics Data System (ADS)

    Holzinger, Andreas; Stickel, Christian; Fassold, Markus; Ebner, Martin

    Interface consistency is an important basic concept in web design and has an effect on performance and satisfaction of end users. Consistency also has significant effects on the learning performance of both expert and novice end users. Consequently, the evaluation of consistency within a e-learning system and the ensuing eradication of irritating discrepancies in the user interface redesign is a big issue. In this paper, we report of our experiences with the Shadow Expert Technique (SET) during the evaluation of the consistency of the user interface of a large university learning management system. The main objective of this new usability evaluation method is to understand the interaction processes of end users with a specific system interface. Two teams of usability experts worked independently from each other in order to maximize the objectivity of the results. The outcome of this SET method is a list of recommended changes to improve the user interaction processes, hence to facilitate high consistency.

  14. Ingredients of a Successful Summer Learning Program: A Case Study of the Building Educated Leaders for Life (BELL) Accelerated Learning Summer Program

    ERIC Educational Resources Information Center

    Capizzano, Jeffrey; Bischoff, Kendra; Woodroffe, Nicola; Chaplin, Duncan

    2007-01-01

    Based on positive results from a previous evaluation of a summer learning intervention, the current report describes the specific elements of the successful program so it can be replicated, and investigates potential barriers to implementation and replication. The study estimated impacts of the program overall; the authors could not identify which…

  15. The influence of curricular and extracurricular learning activities on students' choice of chiropractic technique

    PubMed Central

    Sikorski, David M.; KizhakkeVeettil, Anupama; Tobias, Gene S.

    2016-01-01

    Objective: Surveys for the National Board of Chiropractic Examiners indicate that diversified chiropractic technique is the most commonly used chiropractic manipulation method. The study objective was to investigate the influences of our diversified core technique curriculum, a technique survey course, and extracurricular technique activities on students' future practice technique preferences. Methods: We conducted an anonymous, voluntary survey of 1st, 2nd, and 3rd year chiropractic students at our institution. Surveys were pretested for face validity, and data were analyzed using descriptive and inferential statistics. Results: We had 164 students (78% response rate) participate in the survey. Diversified was the most preferred technique for future practice by students, and more than half who completed the chiropractic technique survey course reported changing their future practice technique choice as a result. The students surveyed agreed that the chiropractic technique curriculum and their experiences with chiropractic practitioners were the two greatest bases for their current practice technique preference, and that their participation in extracurricular technique clubs and seminars was less influential. Conclusions: Students appear to have the same practice technique preferences as practicing chiropractors. The chiropractic technique curriculum and the students' experience with chiropractic practitioners seem to have the greatest influence on their choice of chiropractic technique for future practice. Extracurricular activities, including technique clubs and seminars, although well attended, showed a lesser influence on students' practice technique preferences. PMID:26655282

  16. Peer Assessment Learning Sessions (PALS): An Innovative Feedback Technique for Large Engineering Classes

    ERIC Educational Resources Information Center

    O'Moore, Liza; Baldock, Tom

    2007-01-01

    This paper reports the development of innovative assessment sessions within two core technical courses in Civil Engineering at the University of Queensland. Peer Assessment Learning Sessions (PALS) facilitate a student's peer assessment of a colleague's problem-based learning assignment or tutorial within a "traditional" whole-class…

  17. Advancing Research in Second Language Writing through Computational Tools and Machine Learning Techniques: A Research Agenda

    ERIC Educational Resources Information Center

    Crossley, Scott A.

    2013-01-01

    This paper provides an agenda for replication studies focusing on second language (L2) writing and the use of natural language processing (NLP) tools and machine learning algorithms. Specifically, it introduces a range of the available NLP tools and machine learning algorithms and demonstrates how these could be used to replicate seminal studies…

  18. Incorporating Service-Learning, Technology, and Research Supportive Teaching Techniques into the University Chemistry Classroom

    ERIC Educational Resources Information Center

    Saitta, E. K. H.; Bowdon, M. A.; Geiger, C. L.

    2011-01-01

    Technology was integrated into service-learning activities to create an interactive teaching method for undergraduate students at a large research institution. Chemistry students at the University of Central Florida partnered with high school students at Crooms Academy of Information Technology in interactive service learning projects. The…

  19. Scaling-up Process-Oriented Guided Inquiry Learning Techniques for Teaching Large Information Systems Courses

    ERIC Educational Resources Information Center

    Trevathan, Jarrod; Myers, Trina; Gray, Heather

    2014-01-01

    Promoting engagement during lectures becomes significantly more challenging as class sizes increase. Therefore, lecturers need to experiment with new teaching methodologies to embolden deep learning outcomes and to develop interpersonal skills amongst students. Process Oriented Guided Inquiry Learning is a teaching approach that uses highly…

  20. Process Mining Techniques for Analysing Patterns and Strategies in Students' Self-Regulated Learning

    ERIC Educational Resources Information Center

    Bannert, Maria; Reimann, Peter; Sonnenberg, Christoph

    2014-01-01

    Referring to current research on self-regulated learning, we analyse individual regulation in terms of a set of specific sequences of regulatory activities. Successful students perform regulatory activities such as analysing, planning, monitoring and evaluating cognitive and motivational aspects during learning not only with a higher frequency…

  1. Developing Creative and Critical Thinking Abilities in Business Graduates: The Value of Experiential Learning Techniques

    ERIC Educational Resources Information Center

    Hannon, Stephen; McBride, Hugh; Burns, Barbara

    2004-01-01

    Educational programmes should promote an ethos of lifelong learning and develop in graduates the capacity for long-term personal and professional development through self-learning and reflection. A business degree programme should seek to produce graduates who are confident, creative thinkers with the capacity to solve problems, think creatively,…

  2. Student Team Achievement Divisions (STAD) Technique through the Moodle to Enhance Learning Achievement

    ERIC Educational Resources Information Center

    Tiantong, Monchai; Teemuangsai, Sanit

    2013-01-01

    One of the benefits of using collaborative learning is enhancing learning achievement and increasing social skills, and the second benefits is as the more students work together in collaborative groups, the more they understand, retain, and feel better about themselves and their peers, moreover working together in a collaborative environment…

  3. Cloud detection in all-sky images via multi-scale neighborhood features and multiple supervised learning techniques

    NASA Astrophysics Data System (ADS)

    Cheng, Hsu-Yung; Lin, Chih-Lung

    2017-01-01

    Cloud detection is important for providing necessary information such as cloud cover in many applications. Existing cloud detection methods include red-to-blue ratio thresholding and other classification-based techniques. In this paper, we propose to perform cloud detection using supervised learning techniques with multi-resolution features. One of the major contributions of this work is that the features are extracted from local image patches with different sizes to include local structure and multi-resolution information. The cloud models are learned through the training process. We consider classifiers including random forest, support vector machine, and Bayesian classifier. To take advantage of the clues provided by multiple classifiers and various levels of patch sizes, we employ a voting scheme to combine the results to further increase the detection accuracy. In the experiments, we have shown that the proposed method can distinguish cloud and non-cloud pixels more accurately compared with existing works.

  4. Bangle (Zingiber purpureum) Improves Spatial Learning, Reduces Deficits in Memory, and Promotes Neurogenesis in the Dentate Gyrus of Senescence-Accelerated Mouse P8.

    PubMed

    Nakai, Megumi; Iizuka, Michiro; Matsui, Nobuaki; Hosogi, Kazuko; Imai, Akiko; Abe, Noriaki; Shiraishi, Hisashi; Hirata, Ayumu; Yagi, Yusuke; Jobu, Kohei; Yokota, Junko; Kato, Eishin; Hosoda, Shinya; Yoshioka, Saburo; Harada, Kenichi; Kubo, Miwa; Fukuyama, Yoshiyasu; Miyamura, Mitsuhiko

    2016-05-01

    Bangle (Zingiber purpureum) is a tropical ginger that is used as a spice in Southeast Asia. Phenylbutenoid dimers isolated from Bangle have exhibited neurotrophic effects in primary cultured rat cortical neurons and PC12 cells. Furthermore, chronic treatment with phenylbutenoid dimers enhances hippocampal neurogenesis in olfactory bulbectomized mice. In this study, we investigated the effects of Bangle extract on behavior and hippocampal neurogenesis in vivo. SAMP8 mice, which are an established model for accelerated aging, with age-related learning and memory impairments, were given a Bangle-containing diet for 1 month, and subsequent behavioral tests and immunohistochemistry for Ki67, a proliferating cell marker, were performed. We found that the Bangle-containing diet improved spatial learning and memory deficits in the Morris water maze and significantly increased the numbers of Ki67-positive cells in the dentate gyrus of the SAMP8 mice. In addition, the Bangle extract exhibited a neurotrophin-like activity as indicated by the induction of neurite sprouting in PC12 cells. Our results suggest that Bangle is beneficial for the prevention of age-related progression of cognitive impairment.

  5. Some aspects of using new techniques of teaching/learning in education in optics (Abstract only)

    NASA Astrophysics Data System (ADS)

    Suchanska, Malgorzata

    2003-11-01

    The deep learning in Optics can be encouraged by stimulating and considerate teaching. It means that teacher should demonstrate his/her personal commitment to the subject and stress its meaning, relevance and importance to the students. It is also important to allow students to be creative in solving problems and in interpretation of its contents. In order to help the students to become more creative persons it is necessary to enhance the learning process of modern knowledge in Optics, to design and conduct experiments, stimulate passions and interests, allow an access to the e-learning system (Internet) and introduce the psychological training (creativity, communication, lateral thinking etc.) (Abstract only available)

  6. Thomas Edison Accelerated Elementary School.

    ERIC Educational Resources Information Center

    Levin, Henry M.; Chasin, Gene

    This paper describes early outcomes of a Sacramento, California, elementary school that participated in the Accelerated Schools Project. The school, which serves many minority and poor students, began training for the project in 1992. Accelerated Schools were designed to advance the learning rate of students through a gifted and talented approach,…

  7. Natural Acceleration: Supporting Creative Trajectories

    ERIC Educational Resources Information Center

    Cohen, LeoNora M.

    2011-01-01

    "Natural acceleration" happens through an internal fire that burns to learn and may transcend school boundaries. Based on their passionate interests and connections with a domain, children who hunger for domain understandings outside school curricula require different types of acceleration, motivated by these interests. The lifeworks,…

  8. Designing reliability into accelerators

    NASA Astrophysics Data System (ADS)

    Hutton, A.

    1992-07-01

    Future accelerators will have to provide a high degree of reliability. Quality must be designed in right from the beginning and must remain a central theme throughout the project. The problem is similar to the problems facing US industry today, and examples of the successful application of quality engineering will be given. Different aspects of an accelerator project will be addressed: Concept, Design, Motivation, Management Techniques, and Fault Diagnosis. The importance of creating and maintaining a coherent team will be stressed.

  9. Using Dark Matter Haloes to Learn about Cosmic Acceleration: A New Proposal for a Universal Mass Function

    NASA Technical Reports Server (NTRS)

    Prescod-Weinstein, Chanda; Afshordi, Niayesh

    2011-01-01

    Structure formation provides a strong test of any cosmic acceleration model because a successful dark energy model must not inhibit or overpredict the development of observed large-scale structures. Traditional approaches to studies of structure formation in the presence of dark energy or a modified gravity implement a modified Press-Schechter formalism, which relates the linear overdensities to the abundance of dark matter haloes at the same time. We critically examine the universality of the Press-Schechter formalism for different cosmologies, and show that the halo abundance is best correlated with spherical linear overdensity at 94% of collapse (or observation) time. We then extend this argument to ellipsoidal collapse (which decreases the fractional time of best correlation for small haloes), and show that our results agree with deviations from modified Press-Schechter formalism seen in simulated mass functions. This provides a novel universal prescription to measure linear density evolution, based on current and future observations of cluster (or dark matter) halo mass function. In particular, even observations of cluster abundance in a single epoch will constrain the entire history of linear growth of cosmological of perturbations.

  10. Using Elearning techniques to support problem based learning within a clinical simulation laboratory.

    PubMed

    Docherty, Charles; Hoy, Derek; Topp, Helena; Trinder, Kathryn

    2004-01-01

    This paper details the results of the first phase of a project that used eLearning to support students' learning within a simulated environment. The locus was a purpose built Clinical Simulation Laboratory (CSL) where the School's newly adopted philosophy of Problem Based Learning (PBL) was challenged through lecturers reverting to traditional teaching methods. The solution, a student-centred, problem-based approach to the acquisition of clinical skills was developed using learning objects embedded within web pages that substituted for lecturers providing instruction and demonstration. This allowed lecturers to retain their facilitator role, and encouraged students to explore, analyse and make decisions within the safety of a clinical simulation. Learning was enhanced through network communications and reflection on video performances of self and others. Evaluations were positive, students demonstrating increased satisfaction with PBL, improved performance in exams, and increased self-efficacy in the performance of nursing activities. These results indicate that an elearning approach can support PBL in delivering a student centred learning experience.

  11. Phase segmentation of X-ray computer tomography rock images using machine learning techniques: an accuracy and performance study

    NASA Astrophysics Data System (ADS)

    Chauhan, Swarup; Rühaak, Wolfram; Anbergen, Hauke; Kabdenov, Alen; Freise, Marcus; Wille, Thorsten; Sass, Ingo

    2016-07-01

    Performance and accuracy of machine learning techniques to segment rock grains, matrix and pore voxels from a 3-D volume of X-ray tomographic (XCT) grayscale rock images was evaluated. The segmentation and classification capability of unsupervised (k-means, fuzzy c-means, self-organized maps), supervised (artificial neural networks, least-squares support vector machines) and ensemble classifiers (bragging and boosting) were tested using XCT images of andesite volcanic rock, Berea sandstone, Rotliegend sandstone and a synthetic sample. The averaged porosity obtained for andesite (15.8 ± 2.5 %), Berea sandstone (16.3 ± 2.6 %), Rotliegend sandstone (13.4 ± 7.4 %) and the synthetic sample (48.3 ± 13.3 %) is in very good agreement with the respective laboratory measurement data and varies by a factor of 0.2. The k-means algorithm is the fastest of all machine learning algorithms, whereas a least-squares support vector machine is the most computationally expensive. Metrics entropy, purity, mean square root error, receiver operational characteristic curve and 10 K-fold cross-validation were used to determine the accuracy of unsupervised, supervised and ensemble classifier techniques. In general, the accuracy was found to be largely affected by the feature vector selection scheme. As it is always a trade-off between performance and accuracy, it is difficult to isolate one particular machine learning algorithm which is best suited for the complex phase segmentation problem. Therefore, our investigation provides parameters that can help in selecting the appropriate machine learning techniques for phase segmentation.

  12. Diagnostics for induction accelerators

    SciTech Connect

    Fessenden, T.J.

    1996-04-01

    The induction accelerator was conceived by N. C. Christofilos and first realized as the Astron accelerator that operated at LLNL from the early 1960`s to the end of 1975. This accelerator generated electron beams at energies near 6 MeV with typical currents of 600 Amperes in 400 ns pulses. The Advanced Test Accelerator (ATA) built at Livermore`s Site 300 produced 10,000 Ampere beams with pulse widths of 70 ns at energies approaching 50 MeV. Several other electron and ion induction accelerators have been fabricated at LLNL and LBNL. This paper reviews the principal diagnostics developed through efforts by scientists at both laboratories for measuring the current, position, energy, and emittance of beams generated by these high current, short pulse accelerators. Many of these diagnostics are closely related to those developed for other accelerators. However, the very fast and intense current pulses often require special diagnostic techniques and considerations. The physics and design of the more unique diagnostics developed for electron induction accelerators are presented and discussed in detail.

  13. Game Design Narrative for Learning: Appropriating Adventure Game Design Narrative Devices and Techniques for the Design of Interactive Learning Environments

    ERIC Educational Resources Information Center

    Dickey, Michele D.

    2006-01-01

    The purpose of this conceptual analysis is to investigate how contemporary video and computer games might inform instructional design by looking at how narrative devices and techniques support problem solving within complex, multimodal environments. Specifically, this analysis presents a brief overview of game genres and the role of narrative in…

  14. Exposure to 56Fe irradiation accelerates normal brain aging and produces deficits in spatial learning and memory

    NASA Astrophysics Data System (ADS)

    Shukitt-Hale, Barbara; Casadesus, Gemma; Carey, Amanda N.; Rabin, Bernard M.; Joseph, James A.

    Previous studies have shown that radiation exposure, particularly to particles of high energy and charge (HZE particles) such as 56Fe, produces deficits in spatial learning and memory. These adverse behavioral effects are similar to those seen in aged animals. It is possible that these shared effects may be produced by the same mechanism. For example, an increased release of reactive oxygen species, and the subsequent oxidative stress and inflammatory damage caused to the central nervous system, is likely responsible for the deficits seen in aging and following irradiation. Therefore, dietary antioxidants, such as those found in fruits and vegetables, could be used as countermeasures to prevent the behavioral changes seen in these conditions. Both aged and irradiated rats display cognitive impairment in tests of spatial learning and memory such as the Morris water maze and the radial arm maze. These rats have decrements in the ability to build spatial representations of the environment, and they utilize non-spatial strategies to solve tasks. Furthermore, they show a lack of spatial preference, due to a decline in the ability to process or retain place (position of a goal with reference to a “map” provided by the configuration of numerous cues in the environment) information. These declines in spatial memory occur in measures dependent on both reference and working memory, and in the flexibility to reset mental images. These results show that irradiation with 56Fe high-energy particles produces age-like decrements in cognitive behavior that may impair the ability of astronauts, particularly middle-aged ones, to perform critical tasks during long-term space travel beyond the magnetosphere.

  15. Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges.

    PubMed

    Goldstein, Benjamin A; Navar, Ann Marie; Carter, Rickey E

    2016-07-19

    Risk prediction plays an important role in clinical cardiology research. Traditionally, most risk models have been based on regression models. While useful and robust, these statistical methods are limited to using a small number of predictors which operate in the same way on everyone, and uniformly throughout their range. The purpose of this review is to illustrate the use of machine-learning methods for development of risk prediction models. Typically presented as black box approaches, most machine-learning methods are aimed at solving particular challenges that arise in data analysis that are not well addressed by typical regression approaches. To illustrate these challenges, as well as how different methods can address them, we consider trying to predicting mortality after diagnosis of acute myocardial infarction. We use data derived from our institution's electronic health record and abstract data on 13 regularly measured laboratory markers. We walk through different challenges that arise in modelling these data and then introduce different machine-learning approaches. Finally, we discuss general issues in the application of machine-learning methods including tuning parameters, loss functions, variable importance, and missing data. Overall, this review serves as an introduction for those working on risk modelling to approach the diffuse field of machine learning.

  16. Advanced techniques in laser-ion acceleration: Conversion efficiency, beam distribution and energy scaling in the Break-Out Afterburner regime

    NASA Astrophysics Data System (ADS)

    Jung, Daniel; Yin, Lin; Albright, Brian; Gautier, Donald; Hoerlein, Rainer; Johnson, Randall; Kiefer, Daniel; Letzring, Sam; Shah, Rahul; Palaniyappan, Sasikumar; Shimada, Tsutomu; Habs, Dietrich; Fernandez, Juan; Hegelich, Manuel

    2011-10-01

    Recently, increasing laser intensities and contrast made acceleration mechanisms such as the radiation pressure acceleration or the Break-Out Afterburner (BOA) accessible. These mechanisms efficiently couple laser energy into all target ion species, making them a competitive alternative to conventional accelerators. We here present experimental data addressing conversion efficiency and ion distribution scaling for both carbon C6+ and protons within the BOA regime and the transit into the TNSA regime. Unique high resolution measurements of angularly resolved carbon C6+ and proton energy spectra for targets ranging from 30nm to 25microns - recorded with a novel ion wide angle spectrometer - are presented and used to derive thickness scaling estimates. While the measured conversion efficiency for C6+ reaches up to ~6%, peak energies of 1GeV and 120MeV have been measured for C6+ and protons, respectively.

  17. Integrating machine learning techniques and high-resolution imagery to generate GIS-ready information for urban water consumption studies

    NASA Astrophysics Data System (ADS)

    Wolf, Nils; Hof, Angela

    2012-10-01

    Urban sprawl driven by shifts in tourism development produces new suburban landscapes of water consumption on Mediterranean coasts. Golf courses, ornamental, 'Atlantic' gardens and swimming pools are the most striking artefacts of this transformation, threatening the local water supply systems and exacerbating water scarcity. In the face of climate change, urban landscape irrigation is becoming increasingly important from a resource management point of view. This paper adopts urban remote sensing towards a targeted mapping approach using machine learning techniques and highresolution satellite imagery (WorldView-2) to generate GIS-ready information for urban water consumption studies. Swimming pools, vegetation and - as a subgroup of vegetation - turf grass are extracted as important determinants of water consumption. For image analysis, the complex nature of urban environments suggests spatial-spectral classification, i.e. the complementary use of the spectral signature and spatial descriptors. Multiscale image segmentation provides means to extract the spatial descriptors - namely object feature layers - which can be concatenated at pixel level to the spectral signature. This study assesses the value of object features using different machine learning techniques and amounts of labeled information for learning. The results indicate the benefit of the spatial-spectral approach if combined with appropriate classifiers like tree-based ensembles or support vector machines, which can handle high dimensionality. Finally, a Random Forest classifier was chosen to deliver the classified input data for the estimation of evaporative water loss and net landscape irrigation requirements.

  18. Positive Allosteric Modulation of mGluR5 Accelerates Extinction Learning but Not Relearning Following Methamphetamine Self-Administration

    PubMed Central

    Kufahl, Peter R.; Hood, Lauren E.; Nemirovsky, Natali E.; Barabas, Piroska; Halstengard, Casey; Villa, Angel; Moore, Elisabeth; Watterson, Lucas R.; Olive, M. Foster

    2012-01-01

    Recent studies have implicated glutamate neurotransmission as an important substrate for the extinction of conditioned behaviors, including responding for drug reinforcement. Positive allosteric modulation of the type-5 metabotropic glutamate receptor (mGluR5) in particular has emerged as a treatment strategy for the enhancement of extinction of drug-motivated behaviors. Here, we investigated the effects of the mGluR5 positive allosteric modulator CDPPB, a compound known for its cognitive enhancing effects in rodents, on extinction learning in rats with different histories of methamphetamine (METH) training. Rats were trained to self-administer METH under two conditions: 16 daily sessions of short access (90 min/day, ShA), or eight daily sessions of short access followed by eight sessions of long access (6 h/day, LgA). Control rats self-administered sucrose pellets in daily 30 min sessions. Next, rats were administered vehicle or 30 mg/kg CDPPB prior to seven consecutive daily extinction sessions, subjected to additional extinction sessions to re-establish a post-treatment baseline, and then tested for reinstatement of behavior in the presence of METH- or sucrose-paired cues. Rats were then subjected to a second series of extinction sessions, preceded by vehicle or 30 mg/kg CDPPB, and an additional test for cue-triggered reinstatement. CDPPB treatment resulted in a more rapid extinction of responding on the active lever, especially in the early sessions of the first extinction sequence. However, treatment effects were minimal during subsequent cue reinstatement tests and non-existent during the second series of extinction sessions. Rats with histories of ShA, LgA, and sucrose training expressed similar behavioral sensitivities to CDPPB, with LgA rats demonstrating a modestly higher treatment effect. Positive allosteric modulation of mGluR5 may therefore have some beneficial effects on efforts to facilitate extinction learning and reduce methamphetamine

  19. Use of sociometric techniques to assess the social status of mainstreamed children with learning difficulties.

    PubMed

    Frederickson, N L; Furnham, A F

    1998-11-01

    Research on sociometric data collection and analysis methods is reviewed and implications for assessing the social status of mainstreamed children with learning difficulties are evaluated. Recommendations are made for changing existing procedures to account for factors specific to children with learning difficulties and to classrooms where mainstreaming is occurring. Variations between frequently used sociometric classification systems (which categorize children as popular, rejected, average, neglected, and controversial) are described, and information on their reliability and validity is discussed. Further reliability research with mainstreamed children is recommended, as is the application of theoretical accounts of affiliation in designing sociometric methods.

  20. Antisense directed against PS-1 gene decreases brain oxidative markers in aged senescence accelerated mice (SAMP8) and reverses learning and memory impairment: a proteomics study.

    PubMed

    Fiorini, Ada; Sultana, Rukhsana; Förster, Sarah; Perluigi, Marzia; Cenini, Giovanna; Cini, Chiara; Cai, Jian; Klein, Jon B; Farr, Susan A; Niehoff, Michael L; Morley, John E; Kumar, Vijaya B; Allan Butterfield, D

    2013-12-01

    Amyloid β-peptide (Aβ) plays a central role in the pathophysiology of Alzheimer's disease (AD) through the induction of oxidative stress. This peptide is produced by proteolytic cleavage of amyloid precursor protein (APP) by the action of β- and γ-secretases. Previous studies demonstrated that reduction of Aβ, using an antisense oligonucleotide (AO) directed against the Aβ region of APP, reduced oxidative stress-mediated damage and prevented or reverted cognitive deficits in senescence-accelerated prone mice (SAMP8), a useful animal model for investigating the events related to Aβ pathology and possibly to the early phase of AD. In the current study, aged SAMP8 were treated by AO directed against PS-1, a component of the γ-secretase complex, and tested for learning and memory in T-maze foot shock avoidance and novel object recognition. Brain tissue was collected to identify the decrease of oxidative stress and to evaluate the proteins that are differently expressed and oxidized after the reduction in free radical levels induced by Aβ. We used both expression proteomics and redox proteomics approaches. In brain of AO-treated mice a decrease of oxidative stress markers was found, and the proteins identified by proteomics as expressed differently or nitrated are involved in processes known to be impaired in AD. Our results suggest that the treatment with AO directed against PS-1 in old SAMP8 mice reverses learning and memory deficits and reduces Aβ-mediated oxidative stress with restoration to the normal condition and identifies possible pharmacological targets to combat this devastating dementing disease.

  1. A new deflection technique applied to an existing scheme of electrostatic accelerator for high energy neutral beam injection in fusion reactor devices.

    PubMed

    Pilan, N; Antoni, V; De Lorenzi, A; Chitarin, G; Veltri, P; Sartori, E

    2016-02-01

    A scheme of a neutral beam injector (NBI), based on electrostatic acceleration and magneto-static deflection of negative ions, is proposed and analyzed in terms of feasibility and performance. The scheme is based on the deflection of a high energy (2 MeV) and high current (some tens of amperes) negative ion beam by a large magnetic deflector placed between the Beam Source (BS) and the neutralizer. This scheme has the potential of solving two key issues, which at present limit the applicability of a NBI to a fusion reactor: the maximum achievable acceleration voltage and the direct exposure of the BS to the flux of neutrons and radiation coming from the fusion reactor. In order to solve these two issues, a magnetic deflector is proposed to screen the BS from direct exposure to radiation and neutrons so that the voltage insulation between the electrostatic accelerator and the grounded vessel can be enhanced by using compressed SF6 instead of vacuum so that the negative ions can be accelerated at energies higher than 1 MeV. By solving the beam transport with different magnetic deflector properties, an optimum scheme has been found which is shown to be effective to guarantee both the steering effect and the beam aiming.

  2. A new deflection technique applied to an existing scheme of electrostatic accelerator for high energy neutral beam injection in fusion reactor devices

    SciTech Connect

    Pilan, N. Antoni, V.; De Lorenzi, A.; Chitarin, G.; Veltri, P.; Sartori, E.

    2016-02-15

    A scheme of a neutral beam injector (NBI), based on electrostatic acceleration and magneto-static deflection of negative ions, is proposed and analyzed in terms of feasibility and performance. The scheme is based on the deflection of a high energy (2 MeV) and high current (some tens of amperes) negative ion beam by a large magnetic deflector placed between the Beam Source (BS) and the neutralizer. This scheme has the potential of solving two key issues, which at present limit the applicability of a NBI to a fusion reactor: the maximum achievable acceleration voltage and the direct exposure of the BS to the flux of neutrons and radiation coming from the fusion reactor. In order to solve these two issues, a magnetic deflector is proposed to screen the BS from direct exposure to radiation and neutrons so that the voltage insulation between the electrostatic accelerator and the grounded vessel can be enhanced by using compressed SF{sub 6} instead of vacuum so that the negative ions can be accelerated at energies higher than 1 MeV. By solving the beam transport with different magnetic deflector properties, an optimum scheme has been found which is shown to be effective to guarantee both the steering effect and the beam aiming.

  3. Natural Language Processing Techniques in Computer-Assisted Language Learning: Status and Instructional Issues.

    ERIC Educational Resources Information Center

    Holland, V. Melissa; Kaplan, Jonathan D.

    1995-01-01

    Describes the role of natural language processing (NLP) techniques, such as parsing and semantic analysis, within current language tutoring systems. Examines trends, design issues and tradeoffs, and potential contributions of NLP techniques with respect to instructional theory and educational practice. Addresses limitations and problems in using…

  4. Multiple-Choice Testing Using Immediate Feedback--Assessment Technique (IF AT®) Forms: Second-Chance Guessing vs. Second-Chance Learning?

    ERIC Educational Resources Information Center

    Merrel, Jeremy D.; Cirillo, Pier F.; Schwartz, Pauline M.; Webb, Jeffrey A.

    2015-01-01

    Multiple choice testing is a common but often ineffective method for evaluating learning. A newer approach, however, using Immediate Feedback Assessment Technique (IF AT®, Epstein Educational Enterprise, Inc.) forms, offers several advantages. In particular, a student learns immediately if his or her answer is correct and, in the case of an…

  5. Effects of Jigsaw Cooperative Learning and Animation Techniques on Students' Understanding of Chemical Bonding and Their Conceptions of the Particulate Nature of Matter

    ERIC Educational Resources Information Center

    Karacop, Ataman; Doymus, Kemal

    2013-01-01

    The aim of this study was to determine the effect of jigsaw cooperative learning and computer animation techniques on academic achievements of first year university students attending classes in which the unit of chemical bonding is taught within the general chemistry course and these students' learning of the particulate nature of matter of this…

  6. Ubiquitous Learning Website: Scaffold Learners by Mobile Devices with Information-Aware Techniques

    ERIC Educational Resources Information Center

    Chen, G. D.; Chang, C. K.; Wang, C. Y.

    2008-01-01

    The portability and immediate communication properties of mobile devices influence the learning processes in interacting with peers, accessing resources and transferring data. For example, the short message and browsing functions in a cell phone provide users with timely and adaptive information access. Although many studies of mobile learning…

  7. Measurement of Learning Process by Semantic Annotation Technique on Bloom's Taxonomy Vocabulary

    ERIC Educational Resources Information Center

    Yanchinda, Jirawit; Yodmongkol, Pitipong; Chakpitak, Nopasit

    2016-01-01

    A lack of science and technology knowledge understanding of most rural people who had the highest education at elementary education level more than others level is unsuccessfully transferred appropriate technology knowledge for rural sustainable development. This study provides the measurement of the learning process by on Bloom's Taxonomy…

  8. Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval

    ERIC Educational Resources Information Center

    Khribi, Mohamed Koutheair; Jemni, Mohamed; Nasraoui, Olfa

    2009-01-01

    In this paper, we describe an automatic personalization approach aiming to provide online automatic recommendations for active learners without requiring their explicit feedback. Recommended learning resources are computed based on the current learner's recent navigation history, as well as exploiting similarities and dissimilarities among…

  9. Quasi-Facial Communication for Online Learning Using 3D Modeling Techniques

    ERIC Educational Resources Information Center

    Wang, Yushun; Zhuang, Yueting

    2008-01-01

    Online interaction with 3D facial animation is an alternative way of face-to-face communication for distance education. 3D facial modeling is essential for virtual educational environments establishment. This article presents a novel 3D facial modeling solution that facilitates quasi-facial communication for online learning. Our algorithm builds…

  10. Design of a Bahasa Melayu Grammar Online Learning Portal for Form Two Students Using Delphi Technique

    ERIC Educational Resources Information Center

    Leng, Chin Hai; Siraj, Saedah; Asmawi, Adelina; Dewitt, Dorothy; Ranee, Alina

    2013-01-01

    This study was aimed at developing a Bahasa Melayu grammar learning portal for Form Two students (BMGLP). A developmental approach was used in this study. Needs analysis was carried out on the Bahasa Melayu teachers and Form Two students. The results of needs analysis on Form Two students showed that they preferred topics such as question…

  11. Developmental By-Pass Techniques for Teaching the Secondary Learning Disabled Student.

    ERIC Educational Resources Information Center

    Mosby, Robert J., Ed.

    Described is an interdisciplinary mainstreaming program for individualizing instruction for secondary learning disabled students, utilizing resource facilities in grades 7-9 in eight separate centers throughout Franklin County, Missouri. Aspects of this program--such as the developmental and by-pass strategies of instruction employed to help…

  12. Traffic Light Report Provides a New Technique for Assurance of Learning

    ERIC Educational Resources Information Center

    Nash, Rose; Stupans, Ieva; Chalmers, Leanne; Brown, Natalie

    2016-01-01

    The Traffic Light Report (TLR) project is an educational intervention designed for pharmacy undergraduates. This paper reports on analysis of TLR data specifically focusing on its potential as an innovative tool which combines Miller's pyramid, technology and student voice to examine a curriculum for Assurance of Learning (AoL). In 2014, educators…

  13. Helping Learning Disabled Adults through Special Tutorial Techniques. Final Report. 1992-1993.

    ERIC Educational Resources Information Center

    Reading Area Community Coll., PA.

    A project offered special training to instructors and volunteer tutors for adult basic education classes in recognizing and helping adults who are enrolled in adult education programs with learning disabilities. These instructors and tutors were taught the necessary skills through a series of three 3-hour inservice sessions. The regular…

  14. Spatial and Temporal knowledge representation techniques for traditional machine learning classifiers applied to remote sensing data.

    NASA Astrophysics Data System (ADS)

    Cervone, G.; Kafatos, M.

    2005-12-01

    Formulating general hypotheses from limited observations is one of the fundamental principles of scientific discovery. The data mining approach consists, among others, in generating new knowledge analyzing massive amounts of data and using background knowledge. Knowledge representation is one of the fundamental topics of data mining, because the representation language dictates which algorithms to use, as well as the effective usefulness of the learned hypotheses. Programs that use richer representation languages have the advantage of generating hypotheses that are compact and easy to understand, and the disadvantage of being more complex, slower and ususally with more control parameters. On the other hand, programs that use simpler representaiton languages overcome these shortcomings, but fail to generate hypotheses that can be easily interpreted and used for problem solving and decision making. Symbolic machine learning methods, such as decision rule classifiers, use a complex representation language which can be used to describe difficult concepts, and allow to cope with spatial and temporal data, such as remote sensing data. Because data are usually collected as a sequence of observations over time and in specific locations, very often it is necessary to find relations not only in the data per se, but also in the temporal and spatial distribution of the observations. Due to the increasingly large amount of spatial and temporal data collected and analyzed in several fields such as remote sensing, geographical information systems (GIS), bioinformatics, medicine, bank transactions, etc, spatial and temporal knowledge representaion has become a problem of crucial importance. Present research investigates methods to use existing symbolic machine learning classifiers with temporal and spatial data. The data are converted in a representation language which is suitable to learn spatial and temporal relationship without modifying the existing algorithms. Results from

  15. Wake field acceleration experiments

    SciTech Connect

    Simpson, J.D.

    1988-01-01

    Where and how will wake field acceleration devices find use for other than, possibly, accelerators for high energy physics. I don't know that this can be responsibly answered at this time. What I can do is describe some recent results from an ongoing experimental program at Argonne which support the idea that wake field techniques and devices are potentially important for future accelerators. Perhaps this will spawn expanded interest and even new ideas for the use of this new technology. The Argonne program, and in particular the Advanced Accelerator Test Facility (AATF), has been reported in several fairly recent papers and reports. But because this is a substantially new audience for the subject, I will include a brief review of the program and the facility before describing experiments. 10 refs., 7 figs.

  16. Exploring the application of deep learning techniques on medical text corpora.

    PubMed

    Minarro-Giménez, José Antonio; Marín-Alonso, Oscar; Samwald, Matthias

    2014-01-01

    With the rapidly growing amount of biomedical literature it becomes increasingly difficult to find relevant information quickly and reliably. In this study we applied the word2vec deep learning toolkit to medical corpora to test its potential for improving the accessibility of medical knowledge. We evaluated the efficiency of word2vec in identifying properties of pharmaceuticals based on mid-sized, unstructured medical text corpora without any additional background knowledge. Properties included relationships to diseases ('may treat') or physiological processes ('has physiological effect'). We evaluated the relationships identified by word2vec through comparison with the National Drug File - Reference Terminology (NDF-RT) ontology. The results of our first evaluation were mixed, but helped us identify further avenues for employing deep learning technologies in medical information retrieval, as well as using them to complement curated knowledge captured in ontologies and taxonomies.

  17. Development of a machine learning technique for automatic analysis of seafloor image data: Case example, Pogonophora coverage at mud volcanoes

    NASA Astrophysics Data System (ADS)

    Lüdtke, A.; Jerosch, K.; Herzog, O.; Schlüter, M.

    2012-02-01

    Digital image processing provides powerful tools for fast and precise analysis of large image data sets in marine and geoscientific applications. Because of the increasing volume of georeferenced image and video data acquired by underwater platforms such as remotely operated vehicles, means of automatic analysis of the acquired image data are required. A new and fast-developing application is the combination of video imagery and mosaicking techniques for seafloor habitat mapping. In this article we introduce an approach to fully automatic detection and quantification of Pogonophora coverage in seafloor video mosaics from mud volcanoes. The automatic recognition is based on textural image features extracted from the raw image data and classification using machine learning techniques. Classification rates of up to 98.86% were achieved on the training data. The approach was extensively validated on a data set of more than 4000 seafloor video mosaics from the Håkon Mosby Mud Volcano.

  18. Adaptive critic learning techniques for engine torque and air-fuel ratio control.

    PubMed

    Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

    2008-08-01

    A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

  19. LINEAR ACCELERATOR

    DOEpatents

    Colgate, S.A.

    1958-05-27

    An improvement is presented in linear accelerators for charged particles with respect to the stable focusing of the particle beam. The improvement consists of providing a radial electric field transverse to the accelerating electric fields and angularly introducing the beam of particles in the field. The results of the foregoing is to achieve a beam which spirals about the axis of the acceleration path. The combination of the electric fields and angular motion of the particles cooperate to provide a stable and focused particle beam.

  20. Acceleration switch

    DOEpatents

    Abbin, Jr., Joseph P.; Devaney, Howard F.; Hake, Lewis W.

    1982-08-17

    The disclosure relates to an improved integrating acceleration switch of the type having a mass suspended within a fluid filled chamber, with the motion of the mass initially opposed by a spring and subsequently not so opposed.

  1. Acceleration switch

    DOEpatents

    Abbin, J.P. Jr.; Devaney, H.F.; Hake, L.W.

    1979-08-29

    The disclosure relates to an improved integrating acceleration switch of the type having a mass suspended within a fluid filled chamber, with the motion of the mass initially opposed by a spring and subsequently not so opposed.

  2. ION ACCELERATOR

    DOEpatents

    Bell, J.S.

    1959-09-15

    An arrangement for the drift tubes in a linear accelerator is described whereby each drift tube acts to shield the particles from the influence of the accelerating field and focuses the particles passing through the tube. In one embodiment the drift tube is splii longitudinally into quadrants supported along the axis of the accelerator by webs from a yoke, the quadrants. webs, and yoke being of magnetic material. A magnetic focusing action is produced by energizing a winding on each web to set up a magnetic field between adjacent quadrants. In the other embodiment the quadrants are electrically insulated from each other and have opposite polarity voltages on adjacent quadrants to provide an electric focusing fleld for the particles, with the quadrants spaced sufficienily close enough to shield the particles within the tube from the accelerating electric field.

  3. LINEAR ACCELERATOR

    DOEpatents

    Christofilos, N.C.; Polk, I.J.

    1959-02-17

    Improvements in linear particle accelerators are described. A drift tube system for a linear ion accelerator reduces gap capacity between adjacent drift tube ends. This is accomplished by reducing the ratio of the diameter of the drift tube to the diameter of the resonant cavity. Concentration of magnetic field intensity at the longitudinal midpoint of the external sunface of each drift tube is reduced by increasing the external drift tube diameter at the longitudinal center region.

  4. Accelerator-based neutrino oscillation experiments

    SciTech Connect

    Harris, Deborah A.; /Fermilab

    2007-12-01

    Neutrino oscillations were first discovered by experiments looking at neutrinos coming from extra-terrestrial sources, namely the sun and the atmosphere, but we will be depending on earth-based sources to take many of the next steps in this field. This article describes what has been learned so far from accelerator-based neutrino oscillation experiments, and then describe very generally what the next accelerator-based steps are. In section 2 the article discusses how one uses an accelerator to make a neutrino beam, in particular, one made from decays in flight of charged pions. There are several different neutrino detection methods currently in use, or under development. In section 3 these are presented, with a description of the general concept, an example of such a detector, and then a brief discussion of the outstanding issues associated with this detection technique. Finally, section 4 describes how the measurements of oscillation probabilities are made. This includes a description of the near detector technique and how it can be used to make the most precise measurements of neutrino oscillations.

  5. Using a Delphi Technique to Seek Consensus Regarding Definitions, Descriptions and Classification of Terms Related to Implicit and Explicit Forms of Motor Learning

    PubMed Central

    Kleynen, Melanie; Braun, Susy M.; Bleijlevens, Michel H.; Lexis, Monique A.; Rasquin, Sascha M.; Halfens, Jos; Wilson, Mark R.; Beurskens, Anna J.; Masters, Rich S. W.

    2014-01-01

    Background Motor learning is central to domains such as sports and rehabilitation; however, often terminologies are insufficiently uniform to allow effective sharing of experience or translation of knowledge. A study using a Delphi technique was conducted to ascertain level of agreement between experts from different motor learning domains (i.e., therapists, coaches, researchers) with respect to definitions and descriptions of a fundamental conceptual distinction within motor learning, namely implicit and explicit motor learning. Methods A Delphi technique was embedded in multiple rounds of a survey designed to collect and aggregate informed opinions of 49 international respondents with expertise related to motor learning. The survey was administered via an online survey program and accompanied by feedback after each round. Consensus was considered to be reached if ≥70% of the experts agreed on a topic. Results Consensus was reached with respect to definitions of implicit and explicit motor learning, and seven common primary intervention strategies were identified in the context of implicit and explicit motor learning. Consensus was not reached with respect to whether the strategies promote implicit or explicit forms of learning. Discussion The definitions and descriptions agreed upon may aid translation and transfer of knowledge between domains in the field of motor learning. Empirical and clinical research is required to confirm the accuracy of the definitions and to explore the feasibility of the strategies that were identified in research, everyday practice and education. PMID:24968228

  6. Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques

    DTIC Science & Technology

    2007-08-01

    quite robust to input noise. Wang and Acero (2003) propose an extended HMMmodel for the ATIS do- main, where a multiple-word segment is generated from...tational Natural Language Learning (EMNLP-CoNLL-2007), pp. 22–32. Prague, Czech Republic. Ye-Yi Wang and Alex Acero (2003). Combination of CFG and n-gram...2809–2812. Geneva, Switzerland. Ye-Yi Wang, Li Deng and Alex Acero (2005). Spoken language understanding. IEEE Signal Processing Magazine, 22(5):16–31

  7. Accuracy comparison among different machine learning techniques for detecting malicious codes

    NASA Astrophysics Data System (ADS)

    Narang, Komal

    2016-03-01

    In this paper, a machine learning based model for malware detection is proposed. It can detect newly released malware i.e. zero day attack by analyzing operation codes on Android operating system. The accuracy of Naïve Bayes, Support Vector Machine (SVM) and Neural Network for detecting malicious code has been compared for the proposed model. In the experiment 400 benign files, 100 system files and 500 malicious files have been used to construct the model. The model yields the best accuracy 88.9% when neural network is used as classifier and achieved 95% and 82.8% accuracy for sensitivity and specificity respectively.

  8. Effect of a Cooperative Learning Technique on the Academic Performance of High School Students in Mathematics

    ERIC Educational Resources Information Center

    Idowu, Olumuyiwa Ayodeji

    2013-01-01

    Over the past 2 years, almost 45% of the students attending a local suburban high school failed Algebra 2. The purpose of this study was to compare the impact of a cooperative instructional technique (student teams-achievement divisions [STAD]) to traditional instructional methods on performance in high school algebra. Motivational and cognitive…

  9. Can Children with AD/HD Learn Relaxation and Breathing Techniques through Biofeedback Video Games?

    ERIC Educational Resources Information Center

    Amon, Krestina L.; Campbell, Andrew

    2008-01-01

    This study investigated "The Journey to Wild Divine" as a biofeedback management tool teaching breathing and relaxation skills to children with Attention-Deficit/Hyperactivity Disorder (AD/HD). The children played the game by manipulating their heart rate using breathing techniques taught in the game, measured through three finger sensors. Parents…

  10. Theatre Techniques for Language Learning: Assumptions and Suggested Progression of Activities.

    ERIC Educational Resources Information Center

    Anderson, Martha L.

    A discussion of the use of drama activities in Second Language instruction looks at the rationale for using such techniques in the language classroom, describes a progression of drama activities used for an intensive course in intermediate English as a Second Language, and examines other considerations in the use of drama in language teaching.…

  11. Mindfulness for Singers: The Effects of a Targeted Mindfulness Course on Learning Vocal Technique

    ERIC Educational Resources Information Center

    Czajkowski, Anne-Marie L.; Greasley, Alinka E.

    2015-01-01

    This paper reports the development and implementation of a unique Mindfulness for Singers (MfS) course designed to improve singers' vocal technique. Eight university students completed the intervention. Five Facet Mindfulness Questionnaire (FFMQ) scores showed general improvement across all five facets of mindfulness. Qualitative results showed…

  12. Teams Games Tournaments (TGT). Cooperative Technique for Learning Mathematics in Secondary Schools in Bangladesh

    ERIC Educational Resources Information Center

    Salam, Abdus; Hossain, Anwar; Rahman, Shahidur

    2015-01-01

    This study investigates the effects of game playing on performance and attitudes of students towards mathematics of Grade VIII. The study was undergone by implementing TGT technique for the experimental group and typical lecture-based approach for the control group. A same achievement test was employed as in both pre-test and post-test, an…

  13. The Effects of Techniques of Vocabulary Portfolio on L2 Vocabulary Learning

    ERIC Educational Resources Information Center

    Zarei, Abbas Ali; Baftani, Fahimeh Nasiri

    2014-01-01

    To investigate the effects of different techniques of vocabulary portfolio including word map, word wizard, concept wheel, visual thesaurus, and word rose on L2 vocabulary comprehension and production, a sample of 75 female EFL learners of Kish Day Language Institute in Karaj, Iran were selected. They were in five groups and each group received…

  14. Dealing with Conflict and Aggression in Classrooms through Cooperative Learning Technique

    ERIC Educational Resources Information Center

    Singh, Vandana

    2010-01-01

    Demographic and socioeconomic shifts in nation's population and changes in the family structure have placed increasing demands on the schools. There is a pressing need to understand the factors that give rise to and maintain aggressive behaviours across adolescence and also suggest techniques for dealing with the increased incidence of aggression…

  15. The Effect of "Superlearning Techniques" on the Vocabulary Acquisition and Alpha Brainwave Production of Language Learners.

    ERIC Educational Resources Information Center

    Wagner, Michael J.; Tilney, Germaine

    1983-01-01

    A group of adult intensive English students, language teachers, and graduate music education students were taught a 300-word German vocabulary list in a five-week period, some with and some without Baroque music but with superlearning techniques, and some by traditional techniques. Accelerated learning by superlearning methods could not be…

  16. Automatic ultrasonic imaging system with adaptive-learning-network signal-processing techniques

    SciTech Connect

    O'Brien, L.J.; Aravanis, N.A.; Gouge, J.R. Jr.; Mucciardi, A.N.; Lemon, D.K.; Skorpik, J.R.

    1982-04-01

    A conventional pulse-echo imaging system has been modified to operate with a linear ultrasonic array and associated digital electronics to collect data from a series of defects fabricated in aircraft quality steel blocks. A thorough analysis of the defect responses recorded with this modified system has shown that considerable improvements over conventional imaging approaches can be obtained in the crucial areas of defect detection and characterization. A combination of advanced signal processing concepts with the Adaptive Learning Network (ALN) methodology forms the basis for these improvements. Use of established signal processing algorithms such as temporal and spatial beam-forming in concert with a sophisticated detector has provided a reliable defect detection scheme which can be implemented in a microprocessor-based system to operate in an automatic mode.

  17. Learning from social media: utilizing advanced data extraction techniques to understand barriers to breast cancer treatment.

    PubMed

    Freedman, Rachel A; Viswanath, Kasisomayajula; Vaz-Luis, Ines; Keating, Nancy L

    2016-07-01

    Past examinations of breast cancer treatment barriers have typically included registry, claims-based, and smaller survey studies. We examined treatment barriers using a novel, comprehensive, social media analysis of online, candid discussions about breast cancer. Using an innovative toolset to search postings on social networks, message boards, patient communities, and topical sites, we performed a large-scale qualitative analysis. We examined the sentiments and barriers expressed about breast cancer treatments by Internet users during 1 year (2/1/14-1/31/15). We categorized posts based on thematic patterns and examined trends in discussions by race/ethnicity (white/black/Hispanic) when this information was available. We identified 1,024,041 unique posts related to breast cancer treatment. Overall, 57 % of posts expressed negative sentiments. Using machine learning software, we assigned treatment barriers for 387,238 posts (38 %). Barriers included emotional (23 % of posts), preferences and spiritual/religious beliefs (21 %), physical (18 %), resource (15 %), healthcare perceptions (9 %), treatment processes/duration (7 %), and relationships (7 %). Black and Hispanic (vs. white) users more frequently reported barriers related to healthcare perceptions, beliefs, and pre-diagnosis/diagnosis organizational challenges and fewer emotional barriers. Using a novel analysis of diverse social media users, we observed numerous breast cancer treatment barriers that differed by race/ethnicity. Social media is a powerful tool, allowing use of real-world data for qualitative research, capitalizing on the rich discussions occurring spontaneously online. Future research should focus on how to further employ and learn from this type of social intelligence research across all medical disciplines.

  18. Incorporating Experiential Learning Techniques to Improve Self-Efficacy in Clinical Special Care Dentistry Education.

    PubMed

    Watters, Amber L; Stabulas-Savage, Jeanine; Toppin, James D; Janal, Malvin N; Robbins, Miriam R

    2015-09-01

    The New York University College of Dentistry has introduced a clinical rotation for fourth-year dental students that focuses on treating people with special health care needs (PSN). The aim of this study was to investigate the hypothesis that clinical experience in treating patients with special health care needs during predoctoral education is associated with increased self-assessed student ability and comfort and therefore self-efficacy. The study also investigated whether other characteristics, such as prior personal or volunteer experience with this population, service-mindedness, and/or the inclination to treat underserved populations, were associated with comfort in treating PSN. A survey was used to assess changes in students' perceived knowledge, beliefs, and attitudes regarding treating PSN before and after the clinical experience for July 2012-June 2013. The survey included questions about students' service-mindedness, comfort, perceptions of abilities of PSN and educational importance of learning to treat PSN, desire for clinical experience, and future intent or interest in treating PSN. Out of 364 students invited to participate, 127 surveys were returned, for a response rate of 34.9%. The results showed statistically significant increases on six items following training: impressions about the importance of oral health among PSN, comfort in treating people with cognitive disabilities and with medical complexities, intent to treat PSN in future practice, interest in including PSN in postgraduate training, and belief that PSN could be treated in the private practice setting. These students reported preferring to learn in the clinical setting over didactic instruction. This clinical experience was associated with improved self-efficacy in treating PSN and increased intentions to treat this population in future practice. Improvements were particularly evident among those with the least prior experience with PSN and were independent of other aspects of the

  19. We'll Make You a Better Teacher: Learning from Guitar Techniques

    NASA Astrophysics Data System (ADS)

    Greenbowe, Thomas J.

    2008-02-01

    It is worth noting that there are more resources and more uses of technology available world-wide to help individuals become better guitar players than there are resources available to help individuals become better science teachers. Providing resources and services to help individuals become effective chemistry teachers and improve their chemistry teaching and expand their range of techniques is a worthwhile endeavor. This commentary proposes that a new magazine should be developed and designed to complement and augment the Journal of Chemical Education , the Examinations Institute, the BCCEs, and programming at regional, national, and international meetings. We need to be making use of the expertise of chemical educators from around the world to convey the best practices of teaching chemistry. This magazine would feature topics directly relating to teaching chemistry in the classroom and it would include master teachers explaining and discussing chemistry education techniques. A Web site and perhaps a DVD would have digital movies of master chemistry teachers illustrating how they implement a specific technique with students. The Web site would serve as a repository for resources. It would serve as an alternative site for professional development.

  20. Learning.

    ERIC Educational Resources Information Center

    Glaser, Robert

    A report on learning psychology and its relationship to the study of school learning emphasizes the increasing interaction between theorists and educational practitioners, particularly in attempting to learn which variables influence the instructional process and to find an appropriate methodology to measure and evaluate learning. "Learning…