Science.gov

Sample records for accelerated learning techniques

  1. LEARN: Playful Techniques To Accelerate Learning.

    ERIC Educational Resources Information Center

    Richards, Regina G.

    The methods outlined in this guide offer teachers a variety of ways to stimulate interest, enhance concentration, increase understanding, and improve memory in their students. Chapter 1 discusses the LEARN (Learning Efficiently And Remembering Mnemonics) system, a set of strategies that help students use a variety of processing styles to a greater…

  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. Accelerated Learning in the Resource Room.

    ERIC Educational Resources Information Center

    Applegate, Roy L.; Hamm, Stephen J.

    1985-01-01

    Accelerated learning techniques can help teachers of learning disabled students adjust the students' arousal levels through imagery, music, and relaxation techniques and remove conditioned barriers to learning through expectancy effects. (CL)

  5. Miniaturization Techniques for Accelerators

    SciTech Connect

    Spencer, James E.

    2003-05-27

    The possibility of laser driven accelerators [1] suggests the need for new structures based on micromachining and integrated circuit technology because of the comparable scales. Thus, we are exploring fully integrated structures including sources, optics (for both light and particle) and acceleration in a common format--an accelerator-on-chip (AOC). Tests suggest a number of preferred materials and techniques but no technical or fundamental roadblocks at scales of order 1 {micro}m or larger.

  6. 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.

  7. 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).

  8. 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…

  9. Reward feedback accelerates motor learning.

    PubMed

    Nikooyan, Ali A; Ahmed, Alaa A

    2015-01-15

    Recent findings have demonstrated that reward feedback alone can drive motor learning. However, it is not yet clear whether reward feedback alone can lead to learning when a perturbation is introduced abruptly, or how a reward gradient can modulate learning. In this study, we provide reward feedback that decays continuously with increasing error. We asked whether it is possible to learn an abrupt visuomotor rotation by reward alone, and if the learning process could be modulated by combining reward and sensory feedback and/or by using different reward landscapes. We designed a novel visuomotor learning protocol during which subjects experienced an abruptly introduced rotational perturbation. Subjects received either visual feedback or reward feedback, or a combination of the two. Two different reward landscapes, where the reward decayed either linearly or cubically with distance from the target, were tested. Results demonstrate that it is possible to learn from reward feedback alone and that the combination of reward and sensory feedback accelerates learning. An analysis of the underlying mechanisms reveals that although reward feedback alone does not allow for sensorimotor remapping, it can nonetheless lead to broad generalization, highlighting a dissociation between remapping and generalization. Also, the combination of reward and sensory feedback accelerates learning without compromising sensorimotor remapping. These findings suggest that the use of reward feedback is a promising approach to either supplement or substitute sensory feedback in the development of improved neurorehabilitation techniques. More generally, they point to an important role played by reward in the motor learning process. PMID:25355957

  10. 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,…

  11. 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.

  12. 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.…

  13. 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)

  14. Modern control techniques for accelerators

    SciTech Connect

    Goodwin, R.W.; Shea, M.F.

    1984-05-01

    Beginning in the mid to late sixties, most new accelerators were designed to include computer based control systems. Although each installation differed in detail, the technology of the sixties and early to mid seventies dictated an architecture that was essentially the same for the control systems of that era. A mini-computer was connected to the hardware and to a console. Two developments have changed the architecture of modern systems: (a) the microprocessor and (b) local area networks. This paper discusses these two developments and demonstrates their impact on control system design and implementation by way of describing a possible architecture for any size of accelerator. Both hardware and software aspects are included.

  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. Using Experiential Learning Techniques

    ERIC Educational Resources Information Center

    Hawtrey, Kim

    2007-01-01

    The author advocates the application of experiential learning in economics courses at the tertiary level. The author evaluates a range of learning methods, both passive and active, in a student survey that provides data on undergraduate attitudes to various class activities. The results indicate a clear student preference for learning activities…

  17. 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.

  18. 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.…

  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. Effective Blended Learning Techniques

    ERIC Educational Resources Information Center

    Gill, Deborah

    2009-01-01

    Blended learning is becoming more prevalent in higher education courses. Reasons for blending range from accommodating more students to improving the quality of courses offered. The purpose of this paper is twofold: (1) to discuss student attitudes towards blended courses versus face-to-face versus completely online courses, and (2) to consider…

  1. 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.

  2. Convergence of reinforcement learning algorithms and acceleration of learning

    NASA Astrophysics Data System (ADS)

    Potapov, A.; Ali, M. K.

    2003-02-01

    The techniques of reinforcement learning have been gaining increasing popularity recently. However, the question of their convergence rate is still open. We consider the problem of choosing the learning steps αn, and their relation with discount γ and exploration degree ɛ. Appropriate choices of these parameters may drastically influence the convergence rate of the techniques. From analytical examples, we conjecture optimal values of αn and then use numerical examples to verify our conjectures.

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

    NASA Astrophysics Data System (ADS)

    Aslanyan, Grigor; Easther, Richard; Price, Layne C.

    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.

  4. Postcards from the Margin: A National Dialogue on Accelerating Learning.

    ERIC Educational Resources Information Center

    Reindl, Travis

    2006-01-01

    The emergence of accelerated learning as a strategy to simultaneously motivate and challenge secondary students offers a prime example of reform driven by the need to better align schools and colleges with economic and social realities. Accelerated learning is a cluster of programs, such as Advanced Placement, International Baccalaureate,…

  5. Adaptive control technique for accelerators using digital signal processing

    SciTech Connect

    Eaton, L.; Jachim, S.; Natter, E.

    1987-01-01

    The use of present Digital Signal Processing (DSP) techniques can drastically reduce the residual rf amplitude and phase error in an accelerating rf cavity. Accelerator beam loading contributes greatly to this residual error, and the low-level rf field control loops cannot completely absorb the fast transient of the error. A feedforward technique using DSP is required to maintain the very stringent rf field amplitude and phase specifications. 7 refs.

  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. 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…

  8. 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.

    1984-01-01

    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. Previously announced in STAR as N83-35053

  9. 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.

  10. 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.

  11. NIOS II processor-based acceleration of motion compensation techniques

    NASA Astrophysics Data System (ADS)

    González, Diego; Botella, Guillermo; Mookherjee, Soumak; Meyer-Bäse, Uwe; Meyer-Bäse, Anke

    2011-06-01

    This paper focuses on the hardware acceleration of motion compensation techniques suitable for the MPEG video compression. A plethora of representative motion estimation search algorithms and the new perspectives are introduced. The methods and designs described here are qualified for medical imaging area where are involved larger images. The structure of the processing systems considered has a good fit for reconfigurable acceleration. The system is based in a platform like FPGA working with the Nios II Microprocessor platform applying C2H acceleration. The paper shows the results in terms of performance and resources needed.

  12. 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.

  13. Traditional and accelerated Ponseti technique: a comparative study.

    PubMed

    Elgohary, Hatem S A; Abulsaad, Mazen

    2015-07-01

    The purpose of this study was to compare the results of traditional and accelerated Ponseti techniques to clarify whether this technique can be done safely in reduced time with complete correction of the deformity and without complications. A total of 66 feet in 41 children with idiopathic club foot and with Pirani score no <4 were included; of these, 34 feet in 20 children were managed with the traditional Ponseti method with one cast a week, in the other 32 feet in 21 children, an accelerated technique was used with casting twice a week, and the Pirani score was used for initial assessment and for follow-up. The results were comparable for both groups; the mean number of casts for full correction was 4.88 ± 0.88 in the traditional group and 5.16 ± 0.72 in the accelerated group. Initial correction was obtained in all cases in both groups, and relapses were observed in 14.7 % in the traditional group and in 15.6 % in the accelerated group. Deformities required from four to seven casts for correction in both groups. There was a statistically significant reduction in the mean time required for correction from onset of manipulation till tenotomy or correction of equines without tenotomy which was 33.36 ± 6.69 days (21-42 days) in the traditional Ponseti group and 18.13 ± 3.02 days (11-22 days) in accelerated Ponseti (P = 0.001). Accelerated Ponseti technique significantly reduces the correction time without affecting the final results; it is quite as safe and effective as the traditional Ponseti. PMID:25633123

  14. 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…

  15. 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.

  16. 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…

  17. A technique for accelerating the convergence of restarted GMRES

    SciTech Connect

    Baker, A H; Jessup, E R; Manteuffel, T

    2004-03-09

    We have observed that the residual vectors at the end of each restart cycle of restarted GMRES often alternate direction in a cyclic fashion, thereby slowing convergence. We present a new technique for accelerating the convergence of restarted GMRES by disrupting this alternating pattern. The new algorithm resembles a full conjugate gradient method with polynomial preconditioning, and its implementation requires minimal changes to the standard restarted GMRES algorithm.

  18. 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…

  19. New modes of particle acceleration, techniques & sources symposium. Summary report

    SciTech Connect

    Parsa, Z.

    1996-12-31

    A Symposium on {open_quotes}New Modes of Particle Acceleration Technique and Sources{close_quotes} was held August 19-23, 1996 at the Institute for Theoretical Physics (ITP) in Santa Barbara. This was the first of the 3 symposia hosted by the ITP and supported by its sponsor the National Science Foundation, as part of our {open_quotes}New Ideas for Particle Accelerators{close_quotes} program. The symposia was organized and chaired by Dr. Zohreh Parsa of ITP/Brookhaven National Laboratory. This Symposium provided a perspective on the future direction of the Advanced Accelerator Research. The experimental study of elementary particles has become concentrated at a few large laboratories throughout the world because of the size and cost of the accelerator facilities needed for this work. For example, the Large Hadron Collider (LHC) at CERN, currently under construction, is 27 km in circumference and is being financed by the European membership of CERN plus contributions from non-member nations. An evolutionary approach to construction of ever higher energy colliders will only continue this trend towards high cost and large size.

  20. 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.

  1. 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,…

  2. 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…

  3. 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…

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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 methods were a…

  9. 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…

  10. Machine Learning and Geometric Technique for SLAM

    NASA Astrophysics Data System (ADS)

    Bernal-Marin, Miguel; Bayro-Corrochano, Eduardo

    This paper describes a new approach for building 3D geometric maps using a laser rangefinder, a stereo camera system and a mathematical system the Conformal Geometric Algebra. The use of a known visual landmarks in the map helps to carry out a good localization of the robot. A machine learning technique is used for recognition of objects in the environment. These landmarks are found using the Viola and Jones algorithm and are represented with their position in the 3D virtual map.

  11. Low-Field Accelerator Structure Couplers and Design Techniques

    SciTech Connect

    Nantista, C

    2004-07-29

    Recent experience with X-band accelerator structure development has shown the rf input coupler to be the region most prone to rf breakdown and degradation, effectively limiting the operating gradient. A major factor in this appears to be high magnetic fields at the sharp edges of the coupling irises. As a first response to this problem, couplers with rounded and thickened iris horns have been employed and successfully tested at high power. To further reduce fields for higher power flow, conceptually new coupler designs have been developed, in which power is coupled through the broadwall of the feed waveguide, rather than through terminating irises. A 'mode launcher' coupler, which launches the TM{sub 01} mode in circular waveguide before coupling through a matching cell into the main structure, has been tested with great success. With peak surface fields below those in the body of the structure, this coupler represented a break-through in the NLC structure program. The design of this coupler and of variations which use beamline space more efficiently are described here. The latter include a coupler in which power passes directly through an iris in the broad wall of the rectangular waveguide into a matching cell, also successfully implemented, and a variation which makes the waveguide itself an accelerating cell. The authors also discuss in some detail a couple of techniques for matching such couplers to travelling-wave structures using a field solver. The first exploits the cell number independence of a travelling-wave match, and the second optimizes using the fields of an internally driven structure.

  12. Gene Profiling Technique to Accelerate Stem Cell Therapies for Eye Diseases

    MedlinePlus

    ... to accelerate stem cell therapies for eye diseases Gene profiling technique to accelerate stem cell therapies for ... The method simultaneously measures the expression of multiple genes, allowing scientists to quickly characterize cells according to ...

  13. Machine-Learning Techniques Applied to Antibacterial Drug Discovery

    PubMed Central

    Durrant, Jacob D.; Amaro, Rommie E.

    2014-01-01

    The emergence of drug-resistant bacteria threatens to catapult humanity back to the pre-antibiotic era. Even now, multi-drug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the resulting vacuum. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics in an academic setting, leading to improved hit rates and faster transitions to pre-clinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field. PMID:25521642

  14. Machine-learning techniques applied to antibacterial drug discovery.

    PubMed

    Durrant, Jacob D; Amaro, Rommie E

    2015-01-01

    The emergence of drug-resistant bacteria threatens to revert humanity back to the preantibiotic era. Even now, multidrug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the pipeline. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug-discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics, leading to improved hit rates and faster transitions to preclinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field. PMID:25521642

  15. 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.

  16. 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. PMID:27544086

  17. 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

  18. 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…

  19. 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. PMID:27031876

  20. 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

  1. 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.…

  2. 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.

  3. 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. PMID:19963623

  4. 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

  5. Machine learning strategy for accelerated design of polymer dielectrics

    DOE PAGESBeta

    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,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

  6. Machine Learning Strategy for Accelerated Design of Polymer Dielectrics

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    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.

  7. Improving Word Learning in Children Using an Errorless Technique

    ERIC Educational Resources Information Center

    Warmington, Meesha; Hitch, Graham J.; Gathercole, Susan E.

    2013-01-01

    The current experiment examined the relative advantage of an errorless learning technique over an errorful one in the acquisition of novel names for unfamiliar objects in typically developing children aged between 7 and 9 years. Errorless learning led to significantly better learning than did errorful learning. Processing speed and vocabulary…

  8. Techniques for Promoting Active Learning. The Cross Papers.

    ERIC Educational Resources Information Center

    Cross, K. Patricia

    This guide offers suggestions for implementing active learning techniques in the community college classroom. The author argues that, although much of the literature on active learning emphasizes collaboration and small-group learning, active learning does not always involve interaction. It must also involve reflection and self-monitoring of both…

  9. 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.…

  10. 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.

  11. Sandia LSI accelerated aging and data acquisition techniques

    SciTech Connect

    Walker, J.E.

    1980-04-01

    The purpose of the Microelectronic Evaluation Laboratory at Sandia is to develop a program for evaluating CMOS LSI (complementary metal oxide silicon - large scale integrated) technology devices which are being used for the first time in a weapon system. These evaluations are based on accelerated aging studies and electrical tests to determine the reliability and life of the devices. In accelerated aging, specific, controlled stresses are applied to the device to accelerate time-to-failure. Data are used tin mathematical models to estimate life in acutal use. The stresses used for this technology are temperature and voltage. The devices are stored at temperatures with or without voltage applied (steady-state or cyclical) and periodically tested until at least 50% failures are encountered. Since most current technologies use epoxy-die-attachment, aging temperatures must be under 200/sup 0/C. This delays device failure, and a 16% failure level is used when this extrapolation is considered valid. Statistical analysis is performed on the resultant data to predict reliability with time. The equipment and procedures used for accelerated aging tests are described in detail. The data acquisition system and its use are discussed. All devices, after functional failure has occurred, are given to the failure analysis group for failure evaluations. In order to improve reliability predictions, failure analysis is most concerned with the separation of freak and main life mechanisms. Through these evaluations, higher reliability and longer device life have become a milestone of the future. (LCL)

  12. Improving Learning Processes: Principles, Strategies and Techniques.

    ERIC Educational Resources Information Center

    Cox, Philip

    This guide, which examines the relationship between learning processes and learning outcomes, is aimed at senior managers, quality managers, and others at colleges and other post-16 learning providers in the United Kingdom. It is intended to help them define the key processes undertaken by learning providers, understand the critical relationships…

  13. Novel learning accelerates systems consolidation of a contextual fear memory.

    PubMed

    Haubrich, Josue; Cassini, Lindsey Freitas; Diehl, Felipe; Santana, Fabiana; Fürstenau de Oliveira, Lucas; de Oliveira Alvares, Lucas; Quillfeldt, Jorge Alberto

    2016-07-01

    After initial encoding memories may undergo a time-dependent reorganization, becoming progressively independent from the hippocampus (HPC) and dependent on cortical regions such as the anterior cingulate cortex (ACC). Although the mechanisms underlying systems consolidation are somewhat known, the factors determining its temporal dynamics are still poorly understood. Here, we studied the influence of novel learning occurring between training and test sessions on the time-course of HPC- and ACC-dependency of contextual fear conditioning (CFC) memory expression. We found that muscimol was disruptive when infused into the HPC up to 35 days after training, while the ACC is vulnerable only after 45 days. However, when animals were subjected to a series of additional, distinct tasks to be learned within the first 3 weeks, muscimol became effective sooner. Muscimol had no effect in the HPC at 20 days after training, exactly when the ACC becomes responsive to this treatment. Thus, our data indicates that the encoding of new information generates a tight interplay between distinct memories, accelerating the reorganization of previously stored long term memories between the hippocampal and cortical areas. © 2016 Wiley Periodicals, Inc. PMID:26860633

  14. 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. PMID:24807456

  15. 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.

  16. Acceleration of ensemble machine learning methods using many-core devices

    NASA Astrophysics Data System (ADS)

    Tamerus, A.; Washbrook, A.; Wyeth, D.

    2015-12-01

    We present a case study into the acceleration of ensemble machine learning methods using many-core devices in collaboration with Toshiba Medical Visualisation Systems Europe (TMVSE). The adoption of GPUs to execute a key algorithm in the classification of medical image data was shown to significantly reduce overall processing time. Using a representative dataset and pre-trained decision trees as input we will demonstrate how the decision forest classification method can be mapped onto the GPU data processing model. It was found that a GPU-based version of the decision forest method resulted in over 138 times speed-up over a single-threaded CPU implementation with further improvements possible. The same GPU-based software was then directly applied to a suitably formed dataset to benefit supervised learning techniques applied in High Energy Physics (HEP) with similar improvements in performance.

  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. 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…

  19. 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…

  20. Techniques used in the alignment of TJNAF's accelerators and experimental halls

    SciTech Connect

    C.J. Curtis; J.C. Dahlberg; W.A. Oren; K.J. Tremblay

    1997-10-13

    With the successful completion of the main accelerator in 1994 the alignment emphasis at the Thomas Jefferson National Accelerator Facility (formerly CEBAF) switched to the continuing installation and upgrades in the three experimental halls. This presentation examines the techniques used in completing the CEBAF machine and also gives an update on the alignment of the new accelerator, a 1 kW free-electron laser, currently being built at the facility.

  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. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. Accelerated wavefront determination technique for optical imaging through scattering medium

    NASA Astrophysics Data System (ADS)

    He, Hexiang; Wong, Kam Sing

    2016-03-01

    Wavefront shaping applied on scattering light is a promising optical imaging method in biological systems. Normally, optimized modulation can be obtained by a Liquid-Crystal Spatial Light Modulator (LC-SLM) and CCD hardware iteration. Here we introduce an improved method for this optimization process. The core of the proposed method is to firstly detect the disturbed wavefront, and then to calculate the modulation phase pattern by computer simulation. In particular, phase retrieval method together with phase conjugation is most effective. In this way, the LC-SLM based system can complete the wavefront optimization and imaging restoration within several seconds which is two orders of magnitude faster than the conventional technique. The experimental results show good imaging quality and may contribute to real time imaging recovery in scattering medium.

  8. 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.

  9. Acceleration techniques for reduced-order models based on proper orthogonal decomposition

    SciTech Connect

    Cizmas, P.; Richardson, B.; Brenner, T.; O'Brien, T.; Breault, R.

    2008-01-01

    This paper presents several acceleration techniques for reduced-order models based on the proper orthogonal decomposition (POD) method. The techniques proposed herein are: (i) an algorithm for splitting the database of snapshots generated by the full-order model; (ii) a method for solving quasi-symmetrical matrices; (iii) a strategy for reducing the frequency of the projection. The acceleration techniques were applied to a POD-based reduced-order model of the twophase flows in fluidized beds. This reduced-order model was developed using numerical results from a full-order computational fluid dynamics model of a two-dimensional fluidized bed. Using these acceleration techniques the computational time of the POD model was two orders of magnitude shorter than the full-order model.

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

    PubMed

    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

  11. 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.

  12. 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.…

  13. Studies of industrial emissions by accelerator-based techniques: A review of applications at CEDAD

    NASA Astrophysics Data System (ADS)

    Calcagnile, L.; Quarta, G.

    2012-04-01

    Different research activities are in progress at the Centre for Dating and Diagnostics (CEDAD), University of Salento, in the field of environmental monitoring by exploiting the potentialities given by the different experimental beam lines implemented on the 3 MV Tande-tron accelerator and dedicated to AMS (Accelerator Mass Spectrome-try) radiocarbon dating and IB A (Ion Beam Analysis). An overview of these activities is presented by showing how accelerator-based analytical techniques can be a powerful tool for monitoring the anthropogenic carbon dioxide emissions from industrial sources and for the assessment of the biogenic content in SRF (Solid Recovered Fuel) burned in WTE (Waste to Energy) plants.

  14. Precision Learning Assessment: An Alternative to Traditional Assessment Techniques.

    ERIC Educational Resources Information Center

    Caltagirone, Paul J.; Glover, Christopher E.

    1985-01-01

    A continuous and curriculum-based assessment method, Precision Learning Assessment (PLA), which integrates precision teaching and norm-referenced techniques, was applied to a math computation curriculum for 214 third graders. The resulting districtwide learning curves defining average annual progress through the computation curriculum provided…

  15. 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…

  16. 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…

  17. Synectics: A Technique for Creative Learning

    ERIC Educational Resources Information Center

    Jimenez, Jacques

    1975-01-01

    Describes the rationale behind Synectics Education Systems (SES) which is primarily a way of thinking. The main feature of the approach is the making of analogies. Two examples of applying the technique are given. Suggestions for using the technique in lesson planning are also given. (BR)

  18. A Center for Accelerated Learning: A Training Program for Elementary and Secondary Foreign Language Teachers.

    ERIC Educational Resources Information Center

    Cullen, Audrey; And Others

    A discussion of accelerated learning in language instruction gives a sample lesson, discusses the methodology used, and summarizes the results of a language teacher training program using the method. The approach is based on recognition and development of brain hemisphere functions to make learning faster and more effective. The sample lesson is a…

  19. 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…

  20. 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…

  1. 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

  2. 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.

  3. The Journal of Accelerated Learning and Teaching, 1997.

    ERIC Educational Resources Information Center

    Boy, Nancy Omaha, Ed.

    1997-01-01

    This document comprises the entire output of the journal for 1997. In the first article, "How Can Educational Psychology Be Meaningful?," E. Jensen's 1995 book, "Brain-Based Learning and Teaching," is reviewed, concluding that the book would be valuable for any teacher who wants to improve the level of students' learning. "Accelerative Learning…

  4. Using Qualitative Observation To Document Group Processes in Accelerated Schools Training: Techniques and Results.

    ERIC Educational Resources Information Center

    McFarland, Katherine; Batten, Constance

    This paper describes the use of qualitative observation techniques for gathering and analyzing data related to group processes during an Accelerated Schools Model training session. The purposes for this research were to observe the training process in order better to facilitate present continuation and future training, to develop questions for…

  5. Predicting radiotherapy outcomes using statistical learning techniques*

    PubMed Central

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

    2013-01-01

    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

  6. 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…

  7. Diffusion dynamics of socially learned foraging techniques in squirrel monkeys.

    PubMed

    Claidière, Nicolas; Messer, Emily J E; Hoppitt, William; Whiten, Andrew

    2013-07-01

    Social network analyses and experimental studies of social learning have each become important domains of animal behavior research in recent years yet have remained largely separate. Here we bring them together, providing the first demonstration of how social networks may shape the diffusion of socially learned foraging techniques. One technique for opening an artificial fruit was seeded in the dominant male of a group of squirrel monkeys and an alternative technique in the dominant male of a second group. We show that the two techniques spread preferentially in the groups in which they were initially seeded and that this process was influenced by monkeys' association patterns. Eigenvector centrality predicted both the speed with which an individual would first succeed in opening the artificial fruit and the probability that they would acquire the cultural variant seeded in their group. These findings demonstrate a positive role of social networks in determining how a new foraging technique diffuses through a population. PMID:23810529

  8. 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…

  9. 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…

  10. 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).

  11. 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…

  12. Increasing Third Grade Social Skills through Cooperative Learning Techniques.

    ERIC Educational Resources Information Center

    Fulton, Mona Layne

    A primary grades specialist implemented a 10-week practicum intervention designed to increase third graders' social skills by training their teachers in cooperative learning techniques and providing cooperatively structured lessons. Eight skills were addressed; these included the skills of accepting peers' ideas for group activities, completing…

  13. Instructional Television: Visual Production Techniques and Learning Comprehension.

    ERIC Educational Resources Information Center

    Silbergleid, Michael Ian

    The purpose of this study was to determine if increasing levels of complexity in visual production techniques would increase the viewer's learning comprehension and the degree of likeness expressed for a college level instructional television program. A total of 119 mass communications students at the University of Alabama participated in the…

  14. 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…

  15. 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.

  16. The Lozanov Method for Accelerating the Learning of Foreign Languages.

    ERIC Educational Resources Information Center

    Stanton, H. E.

    1978-01-01

    Discusses the Lozanov Method of teaching foreign languages developed by Lozanov in Bulgaria. This method (also known as Suggestopedia) uses various techniques such as physical relaxation exercises, mental concentration, classical music, and ego-enhancing suggestions. (CFM)

  17. 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…

  18. Assessing Undergraduate Learning Outcomes between Accelerated Degree and Traditional Student Populations

    ERIC Educational Resources Information Center

    Rawls, Janita; Hammons, Stacy

    2012-01-01

    This study investigated learning outcomes in both traditional and accelerated degree populations. Using the National Survey of Student Engagement, outcomes were examined relating to critical thinking, oral and written communication, and cultural and global understanding. Literature from life stage development and degree delivery mode areas were…

  19. 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…

  20. Veterans' Accelerated Urban Learning for Teaching (V.A.U.L.T.); Program Development and Projection.

    ERIC Educational Resources Information Center

    Webster Coll., St. Louis, MO.

    The Webster College Veterans' Accelerated Urban Learning for Teaching (VAULT) program, initiated in 1968-69, is designed to train the disadvantaged (primarily Negro veterans who would not normally attend college) to teach in ghetto elementary schools. Its purpose is to serve veterans and to control the following deficiencies in higher education:…

  1. 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…

  2. Relationship of impaired brain glucose metabolism to learning deficit in the senescence-accelerated mouse.

    PubMed

    Ohta, H; Nishikawa, H; Hirai, K; Kato, K; Miyamoto, M

    1996-10-11

    The relationship between brain glucose metabolism and learning deficit was examined in the senescence-accelerated-prone mouse (SAMP) 8, which has been proven to be a useful murine model of age-related behavioral disorders. SAMP8, 7 months old, exhibited marked learning impairment in the passive avoidance task, as compared with the control strain, senescence-accelerated-resistant mice (SAMR) 1. SAMP8 also exhibited a reduction in brain glucose metabolism, as indicated by a reduction in [14C]2-deoxyglucose accumulation in the brain following the intravenous injection impaired glucose metabolism correlated significantly with the learning impairment in all brain regions in SAMR1 and SAMP8. In the SAMP8, a significant correlation was observed in the posterior half of the cerebral cortex. These results suggest that the SAMP8 strain is a useful model of not only age-related behavioral disorders, but also glucose hypometabolism observed in aging and dementias. PMID:8905734

  3. 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.

  4. Applying machine learning classification techniques to automate sky object cataloguing

    NASA Astrophysics Data System (ADS)

    Fayyad, Usama M.; Doyle, Richard J.; Weir, W. Nick; Djorgovski, Stanislav

    1993-08-01

    We describe the application of an Artificial Intelligence machine learning techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Mt. Palomar Northern Sky Survey is nearly completed. This survey provides comprehensive coverage of the northern celestial hemisphere in the form of photographic plates. The plates are being transformed into digitized images whose quality will probably not be surpassed in the next ten to twenty years. The images are expected to contain on the order of 107 galaxies and 108 stars. Astronomers wish to determine which of these sky objects belong to various classes of galaxies and stars. Unfortunately, the size of this data set precludes analysis in an exclusively manual fashion. Our approach is to develop a software system which integrates the functions of independently developed techniques for image processing and data classification. Digitized sky images are passed through image processing routines to identify sky objects and to extract a set of features for each object. These routines are used to help select a useful set of attributes for classifying sky objects. Then GID3 (Generalized ID3) and O-B Tree, two inductive learning techniques, learns classification decision trees from examples. These classifiers will then be applied to new data. These developmnent process is highly interactive, with astronomer input playing a vital role. Astronomers refine the feature set used to construct sky object descriptions, and evaluate the performance of the automated classification technique on new data. This paper gives an overview of the machine learning techniques with an emphasis on their general applicability, describes the details of our specific application, and reports the initial encouraging results. The results indicate that our machine learning approach is well-suited to the problem. The primary benefit of the approach is increased data reduction throughput. Another benefit is

  5. Incorporating Active-Learning Techniques and Competency Assessment into a Critical Care Elective Course

    PubMed Central

    Hibbs, Jennifer L.

    2012-01-01

    Objective. To design, implement, and measure the effectiveness of a critical care elective course for second-year students in a 3-year accelerated doctor of pharmacy (PharmD) program. Design. A critical care elective course was developed that used active-learning techniques, including cooperative learning and group presentations, to deliver content on critical care topics. Group presentations had to include a disease state overview, practice guidelines, and clinical recommendations, and were evaluated by course faculty members and peers. Assessment. Students’ mean scores on a 20-question critical-care competency assessment administered before and after the course improved by 11% (p < 0.05). Course evaluations and comments were positive. Conclusion. A critical care elective course resulted in significantly improved competency in critical care and was well-received by students. PMID:23049101

  6. 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.

  7. 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.

  8. Exploring Characterizations of Learning Object Repositories Using Data Mining Techniques

    NASA Astrophysics Data System (ADS)

    Segura, Alejandra; Vidal, Christian; Menendez, Victor; Zapata, Alfredo; Prieto, Manuel

    Learning object repositories provide a platform for the sharing of Web-based educational resources. As these repositories evolve independently, it is difficult for users to have a clear picture of the kind of contents they give access to. Metadata can be used to automatically extract a characterization of these resources by using machine learning techniques. This paper presents an exploratory study carried out in the contents of four public repositories that uses clustering and association rule mining algorithms to extract characterizations of repository contents. The results of the analysis include potential relationships between different attributes of learning objects that may be useful to gain an understanding of the kind of resources available and eventually develop search mechanisms that consider repository descriptions as a criteria in federated search.

  9. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    NASA Astrophysics Data System (ADS)

    García-Pareja, S.; Vilches, M.; Lallena, A. M.

    2007-09-01

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the "hot" regions of the accelerator, an information which is basic to develop a source model for this therapy tool.

  10. Space Mechanisms Lessons Learned and Accelerated Testing Studies

    NASA Technical Reports Server (NTRS)

    Fusaro, Robert L.

    1997-01-01

    A number of mechanism (mechanical moving component) failures and anomalies have recently occurred on satellites. In addition, more demanding operating and life requirements have caused mechanism failures or anomalies to occur even before some satellites were launched (e.g., during the qualification testing of GOES-NEXT, CERES, and the Space Station Freedom Beta Joint Gimbal). For these reasons, it is imperative to determine which mechanisms worked in the past and which have failed so that the best selection of mechanically moving components can be made for future satellites. It is also important to know where the problem areas are so that timely decisions can be made on the initiation of research to develop future needed technology. To chronicle the life and performance characteristics of mechanisms operating in a space environment, a Space Mechanisms Lessons Learned Study was conducted. The work was conducted by the NASA Lewis Research Center and by Mechanical Technologies Inc. (MTI) under contract NAS3-27086. The expectation of the study was to capture and retrieve information relating to the life and performance of mechanisms operating in the space environment to determine what components had operated successfully and what components had produced anomalies.

  11. An improved acoustic microimaging technique with learning overcomplete representation

    NASA Astrophysics Data System (ADS)

    Zhang, Guang-Ming; Harvey, David M.; Braden, Derek R.

    2005-12-01

    Advancements in integrated circuit (IC) package technology are increasingly leading to size shrinkage of modern microelectronic packages. This size reduction presents a challenge for the detection and location of the internal features/defects in the packages, which have approached the resolution limit of conventional acoustic microimaging, an important nondestructive inspection technique in the semiconductor industry. In this paper, to meet the challenge the learning overcomplete representation technique is pursued to decompose an ultrasonic A-scan signal into overcomplete representations over a learned overcomplete dictionary. Ultrasonic echo separation and reflectivity function estimation are then performed by exploiting the sparse representability of ultrasonic pulses. An improved acoustic microimaging technique is proposed by integrating these operations into the conventional acoustic microimaging technique. Its performance is quantitatively evaluated by elaborated experiments on ultrasonic A-scan signals using acoustic microimaging (AMI) error criteria. Results obtained both from simulated and measured A-scans are presented to demonstrate the superior axial resolution and robustness of the proposed technique.

  12. 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

  13. 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. PMID:26904094

  14. Accelerated test techniques for micro-circuits: Evaluation of high temperature (473 k - 573 K) accelerated life test techniques as effective microcircuit screening methods

    NASA Technical Reports Server (NTRS)

    Johnson, G. M.

    1976-01-01

    The application of high temperature accelerated test techniques was shown to be an effective method of microcircuit defect screening. Comprehensive microcircuit evaluations and a series of high temperature (473 K to 573 K) life tests demonstrated that a freak or early failure population of surface contaminated devices could be completely screened in thirty two hours of test at an ambient temperature of 523 K. Equivalent screening at 398 K, as prescribed by current Military and NASA specifications, would have required in excess of 1,500 hours of test. All testing was accomplished with a Texas Instruments' 54L10, low power triple-3 input NAND gate manufactured with a titanium- tungsten (Ti-W), Gold (Au) metallization system. A number of design and/or manufacturing anomalies were also noted with the Ti-W, Au metallization system. Further study of the exact nature and cause(s) of these anomalies is recommended prior to the use of microcircuits with Ti-W, Au metallization in long life/high reliability applications. Photomicrographs of tested circuits are included.

  15. Analysis of mode scattering from an abruptly ended dielectric slab waveguide by an accelerated iteration technique.

    PubMed

    Tigelis, I G; Manenkov, A B

    2000-12-01

    A new modification of the integral equation method using an iteration technique with "accelerating" parameters is presented to solve the problem of guided-mode scattering from an abruptly ended asymmetrical slab waveguide. The optimal choice of the parameters is shown to be closely connected with the variational principle. The electric-field distribution at the terminal plane, the reflection coefficient of the guided mode, and the far-field radiation pattern are computed. Numerical results are presented for several cases of abruptly ended waveguides, including the systems with constant and variable profiles of the refractive indices. The phenomenon of the radiation pattern rotation is examined in detail. PMID:11140485

  16. 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

  17. Contrast-enhanced MR Angiography of the Abdomen with Highly Accelerated Acquisition Techniques

    PubMed Central

    Mostardi, Petrice M.; Glockner, James F.; Young, Phillip M.

    2011-01-01

    Purpose: To demonstrate that highly accelerated (net acceleration factor [Rnet] ≥ 10) acquisition techniques can be used to generate three-dimensional (3D) subsecond timing images, as well as diagnostic-quality high-spatial-resolution contrast material–enhanced (CE) renal magnetic resonance (MR) angiograms with a single split dose of contrast material. Materials and Methods: All studies were approved by the institutional review board and were HIPAA compliant; written consent was obtained from all participants. Twenty-two studies were performed in 10 female volunteers (average age, 47 years; range, 27–62 years) and six patients with renovascular disease (three women; average age, 48 years; range, 37–68 years; three men; average age, 60 years; range, 50–67 years; composite average age, 54 years; range, 38–68 years). The two-part protocol consisted of a low-dose (2 mL contrast material) 3D timing image with approximate 1-second frame time, followed by a high-spatial-resolution (1.0–1.6-mm isotropic voxels) breath-hold 3D renal MR angiogram (18 mL) over the full abdominal field of view. Both acquisitions used two-dimensional (2D) sensitivity encoding acceleration factor (R) of eight and 2D homodyne (HD) acceleration (RHD) of 1.4–1.8 for Rnet = R · RHD of 10 or higher. Statistical analysis included determination of mean values and standard deviations of image quality scores performed by two experienced reviewers with use of eight evaluation criteria. Results: The 2-mL 3D time-resolved image successfully portrayed progressive arterial filling in all 22 studies and provided an anatomic overview of the vasculature. Successful timing was also demonstrated in that the renal MR angiogram showed adequate or excellent portrayal of the main renal arteries in 21 of 22 studies. Conclusion: Two-dimensional acceleration techniques with Rnet of 10 or higher can be used in CE MR angiography to acquire (a) a 3D image series with 1-second frame time, allowing accurate

  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. PMID:26189657

  19. 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.

  20. 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. PMID:26356762

  1. Optimal technique of linear accelerator-based stereotactic radiosurgery for tumors adjacent to brainstem.

    PubMed

    Chang, Chiou-Shiung; Hwang, Jing-Min; Tai, Po-An; Chang, You-Kang; Wang, Yu-Nong; Shih, Rompin; Chuang, Keh-Shih

    2016-01-01

    Stereotactic radiosurgery (SRS) is a well-established technique that is replacing whole-brain irradiation in the treatment of intracranial lesions, which leads to better preservation of brain functions, and therefore a better quality of life for the patient. There are several available forms of linear accelerator (LINAC)-based SRS, and the goal of the present study is to identify which of these techniques is best (as evaluated by dosimetric outcomes statistically) when the target is located adjacent to brainstem. We collected the records of 17 patients with lesions close to the brainstem who had previously been treated with single-fraction radiosurgery. In all, 5 different lesion catalogs were collected, and the patients were divided into 2 distance groups-1 consisting of 7 patients with a target-to-brainstem distance of less than 0.5cm, and the other of 10 patients with a target-to-brainstem distance of ≥ 0.5 and < 1cm. Comparison was then made among the following 3 types of LINAC-based radiosurgery: dynamic conformal arcs (DCA), intensity-modulated radiosurgery (IMRS), and volumetric modulated arc radiotherapy (VMAT). All techniques included multiple noncoplanar beams or arcs with or without intensity-modulated delivery. The volume of gross tumor volume (GTV) ranged from 0.2cm(3) to 21.9cm(3). Regarding the dose homogeneity index (HIICRU) and conformity index (CIICRU) were without significant difference between techniques statistically. However, the average CIICRU = 1.09 ± 0.56 achieved by VMAT was the best of the 3 techniques. Moreover, notable improvement in gradient index (GI) was observed when VMAT was used (0.74 ± 0.13), and this result was significantly better than those achieved by the 2 other techniques (p < 0.05). For V4Gy of brainstem, both VMAT (2.5%) and IMRS (2.7%) were significantly lower than DCA (4.9%), both at the p < 0.05 level. Regarding V2Gy of normal brain, VMAT plans had attained 6.4 ± 5%; this was significantly better (p < 0.05) than

  2. Key Techniques of Flat-Earth Phase Removal by Acceleration on the GPU

    NASA Astrophysics Data System (ADS)

    Gao, Zeng; Zeng, Qiming; Jiao, Jian; Cui, Xiai; Liang, Cunren

    2013-01-01

    Because InSAR processing is complex and time-consuming, parallel computing has been drawing more and more attention from researchers. GPUs (Graphics Processing Units) have become an increasingly important parallel platform for image processing in recent years. They are cheap and convenient, compared with large-scale, expensive high performance computing clusters, which have a small marketplace presence. In this paper, a valid parallelism implemented on the GPU is introduced. Taking the flat-earth phase removal for example, we introduced two different techniques that can accelerate applications dramatically on a GPU. From the experiment results, we can see that the result accomplished on the GPU is the same as on the CPU; the two techniques used really work in performance improvement.

  3. Memorization techniques: Using mnemonics to learn fifth grade science terms

    NASA Astrophysics Data System (ADS)

    Garcia, Juan O.

    The purpose of this study was to determine whether mnemonic instruction could assist students in learning fifth-grade science terminology more effectively than traditional-study methods of recall currently in practice The task was to examine if fifth-grade students were able to learn a mnemonic and then use it to understand science vocabulary; subsequently, to determine if students were able to remember the science terms after a period of time. The problem is that in general, elementary school students are not being successful in science achievement at the fifth grade level. In view of this problem, if science performance is increased at the elementary level, then it is likely that students will be successful when tested at the 8th and 10th grade in science with the Texas Assessment of Knowledge and Skills (TAKS) in the future. Two research questions were posited: (1) Is there a difference in recall achievement when a mnemonic such as method of loci, pegword method, or keyword method is used in learning fifth-grade science vocabulary as compared to the traditional-study method? (2) If using a mnemonic in learning fifth-grade science vocabulary was effective on recall achievement, would this achievement be maintained over a span of time? The need for this study was to assist students in learning science terms and concepts for state accountability purposes. The first assumption was that memorization techniques are not commonly applied in fifth-grade science classes in elementary schools. A second assumption was that mnemonic devices could be used successfully in learning science terms and increase long term retention. The first limitation was that the study was conducted on one campus in one school district in South Texas which limited the generalization of the study. The second limitation was that it included random assigned intact groups as opposed to random student assignment to fifth-grade classroom groups.

  4. 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…

  5. Measurement of time-dependent external moments and forces by the sum of weighted accelerations technique

    SciTech Connect

    Priddy, T.G.; Gregory, D.L.; Coleman, R.G.

    1989-01-01

    Force identification using a sum of weighted accelerations technique (SWAT) is developed for measurement of externally applied force and moment which dynamically excite a structural system. Mode shape coefficients, from a free-body modal characterization, are used to determine two sets of weighting factors which, when used in the SWAT, eliminate the free-body vibrational response. One set of weighting factors, having the units of mass, are used in the SWAT measurement of the resultant force vector. The second set of weighting factors, having the units of first-moment-of-mass, are calculated to measure the moment acting at the center of mass of the external force with a similar sum of weighted accelerations. The theory for determining the force and moment vectors is developed in this paper. We illustrate the technique through the analysis of a simple beam and a rectangular plate. We then demonstrate the analytical predictions with the laboratory testing of softly suspended structures. 8 refs., 16 figs., 1 tab.

  6. Novel technique for injecting and extracting beams in a circular hadron accelerator without using septum magnets

    NASA Astrophysics Data System (ADS)

    Franchi, Andrea; Giovannozzi, Massimo

    2015-07-01

    With a few exceptions, all on-axis injection and extraction schemes implemented in circular particle accelerators, synchrotrons, and storage rings, make use of magnetic and electrostatic septa with systems of slow-pulsing dipoles acting on tens of thousands of turns and fast-pulsing dipoles on just a few. The dipoles create a closed orbit deformation around the septa, usually referred to as an orbit bump. A new approach is presented which obviates the need for the septum deflectors. Fast-pulsing elements are still required, but their strength can be minimized by choosing appropriate local accelerator optics. This technique should increase the beam clearance and reduce the usually high radiation levels found around the septa and also reduce the machine impedance introduced by the fast-pulsing dipoles. The basis of the technique is the creation of stable islands around stable fixed points in horizontal phase space. The trajectories of these islands may then be adjusted to match the position and angle of the incoming or outgoing beam.

  7. Manifold learning techniques for the analysis of hyperspectral ocean data

    NASA Astrophysics Data System (ADS)

    Gillis, David; Bowles, Jeffrey; Lamela, Gia M.; Rhea, William J.; Bachmann, Charles M.; Montes, Marcos; Ainsworth, Tom

    2005-06-01

    A useful technique in hyperspectral data analysis is dimensionality reduction, which replaces the original high dimensional data with low dimensional representations. Usually this is done with linear techniques such as linear mixing or principal components (PCA). While often useful, there is no a priori reason for believing that the data is actually linear. Lately there has been renewed interest in modeling high dimensional data using nonlinear techniques such as manifold learning (ML). In ML, the data is assumed to lie on a low dimensional, possibly curved surface (or manifold). The goal is to discover this manifold and therefore find the best low dimensional representation of the data. Recently, researchers at the Naval Research Lab have begun to model hyperspectral data using ML. We continue this work by applying ML techniques to hyperspectral ocean water data. We focus on water since there are underlying physical reasons for believing that the data lies on a certain type of nonlinear manifold. In particular, ocean data is influenced by three factors: the water parameters, the bottom type, and the depth. For fixed water and bottom types, the spectra that arise by varying the depth will lie on a nonlinear, one dimensional manifold (i.e. a curve). Generally, water scenes will contain a number of different water and bottom types, each combination of which leads to a distinct curve. In this way, the scene may be modeled as a union of one dimensional curves. In this paper, we investigate the use of manifold learning techniques to separate the various curves, thus partitioning the scene into homogeneous areas. We also discuss ways in which these techniques may be able to derive various scene characteristics such as bathymetry.

  8. Loss of histone deacetylase 2 improves working memory and accelerates extinction learning.

    PubMed

    Morris, Michael J; Mahgoub, Melissa; Na, Elisa S; Pranav, Heena; Monteggia, Lisa M

    2013-04-10

    Histone acetylation and deacetylation can be dynamically regulated in response to environmental stimuli and play important roles in learning and memory. Pharmacological inhibition of histone deacetylases (HDACs) improves performance in learning tasks; however, many of these classical agents are "pan-HDAC" inhibitors, and their use makes it difficult to determine the roles of specific HDACs in cognitive function. We took a genetic approach using mice lacking the class I HDACs, HDAC1 or HDAC2, in postmitotic forebrain neurons to investigate the specificity or functional redundancy of these HDACs in learning and synaptic plasticity. We show that selective knock-out of Hdac2 led to a robust acceleration of the extinction rate of conditioned fear responses and a conditioned taste aversion as well as enhanced performance in an attentional set-shifting task. Hdac2 knock-out had no impact on episodic memory or motor learning, suggesting that the effects are task-dependent, with the predominant impact of HDAC2 inhibition being an enhancement in an animal's ability to rapidly adapt its behavioral strategy as a result of changes in associative contingencies. Our results demonstrate that the loss of HDAC2 improves associative learning, with no effect in nonassociative learning tasks, suggesting a specific role for HDAC2 in particular types of learning. HDAC2 may be an intriguing target for cognitive and psychiatric disorders that are characterized by an inability to inhibit behavioral responsiveness to maladaptive or no longer relevant associations. PMID:23575838

  9. Loss of histone deacetylase 2 improves working memory and accelerates extinction learning

    PubMed Central

    Morris, Michael J.; Mahgoub, Melissa; Na, Elisa S.; Pranav, Heena; Monteggia, Lisa. M.

    2013-01-01

    Histone acetylation and deacetylation can be dynamically regulated in response to environmental stimuli and play important roles in learning and memory. Pharmacological inhibition of histone deacetylases (HDACs) improves performance in learning tasks, however these classical agents are ‘pan-HDAC’ inhibitors and their use makes it difficult to determine the roles of specific HDACs in cognitive function. We took a genetic approach using mice lacking the class I HDACs, HDAC1 or HDAC2, in postmitotic forebrain neurons to investigate the specificity or functional redundancy of these HDACs in learning and synaptic plasticity. We show that selective knockout of HDAC2 led to a robust acceleration of the extinction rate of conditioned fear responses and a conditioned taste aversion as well as enhanced performance in an attentional set-shifting task. HDAC2 knockout had no impact on episodic memory or motor learning suggesting that the effects are task-dependent, with the predominant impact of HDAC2 inhibition being an enhancement in an animal’s ability to rapidly adapt its behavioral strategy as a result of changes in associative contingencies. Our results demonstrate that the loss of HDAC2 improves associative learning, with no effect in non-associative learning tasks, suggesting a specific role for HDAC2 in particular types of learning. HDAC2 may be an intriguing target for cognitive and psychiatric disorders that are characterized by an inability to inhibit behavioral responsiveness to maladaptive or no longer relevant associations. PMID:23575838

  10. 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

  11. Active-contour-based image segmentation using machine learning techniques.

    PubMed

    Etyngier, Patrick; Ségonne, Florent; Keriven, Renaud

    2007-01-01

    We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a category of shapes as a finite dimensional manifold which we approximate using Diffusion maps. Our method computes a Delaunay triangulation of the reduced space, considered as Euclidean, and uses the resulting space partition to identify the closest neighbors of any given shape based on its Nyström extension. We derive a non-linear shape prior term designed to attract a shape towards the shape prior manifold at given constant embedding. Results on shapes of ventricle nuclei demonstrate the potential of our method for segmentation tasks. PMID:18051143

  12. 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…

  13. Analyzing angle crashes at unsignalized intersections using machine learning techniques.

    PubMed

    Abdel-Aty, Mohamed; Haleem, Kirolos

    2011-01-01

    A recently developed machine learning technique, multivariate adaptive regression splines (MARS), is introduced in this study to predict vehicles' angle crashes. MARS has a promising prediction power, and does not suffer from interpretation complexity. Negative Binomial (NB) and MARS models were fitted and compared using extensive data collected on unsignalized intersections in Florida. Two models were estimated for angle crash frequency at 3- and 4-legged unsignalized intersections. Treating crash frequency as a continuous response variable for fitting a MARS model was also examined by considering the natural logarithm of the crash frequency. Finally, combining MARS with another machine learning technique (random forest) was explored and discussed. The fitted NB angle crash models showed several significant factors that contribute to angle crash occurrence at unsignalized intersections such as, traffic volume on the major road, the upstream distance to the nearest signalized intersection, the distance between successive unsignalized intersections, median type on the major approach, percentage of trucks on the major approach, size of the intersection and the geographic location within the state. Based on the mean square prediction error (MSPE) assessment criterion, MARS outperformed the corresponding NB models. Also, using MARS for predicting continuous response variables yielded more favorable results than predicting discrete response variables. The generated MARS models showed the most promising results after screening the covariates using random forest. Based on the results of this study, MARS is recommended as an efficient technique for predicting crashes at unsignalized intersections (angle crashes in this study). PMID:21094345

  14. A Guide to the Use of Group Learning Techniques. Teaching and Learning in Higher Education, 5.

    ERIC Educational Resources Information Center

    Ellington, Henry

    This booklet is the third of three sequels to "A Guide to the Selection of Instructional Methods." Following a brief introduction, characteristics, strengths, and weaknesses of five group learning techniques are examined: (1) buzz sessions and similar small-group exercises; (2) class discussions, seminars, and tutorials; (3) participative…

  15. Statistics and Machine Learning based Outlier Detection Techniques for Exoplanets

    NASA Astrophysics Data System (ADS)

    Goel, Amit; Montgomery, Michele

    2015-08-01

    Architectures of planetary systems are observable snapshots in time that can indicate formation and dynamic evolution of planets. The observable key parameters that we consider are planetary mass and orbital period. If planet masses are significantly less than their host star masses, then Keplerian Motion is defined as P^2 = a^3 where P is the orbital period in units of years and a is the orbital period in units of Astronomical Units (AU). Keplerian motion works on small scales such as the size of the Solar System but not on large scales such as the size of the Milky Way Galaxy. In this work, for confirmed exoplanets of known stellar mass, planetary mass, orbital period, and stellar age, we analyze Keplerian motion of systems based on stellar age to seek if Keplerian motion has an age dependency and to identify outliers. For detecting outliers, we apply several techniques based on statistical and machine learning methods such as probabilistic, linear, and proximity based models. In probabilistic and statistical models of outliers, the parameters of a closed form probability distributions are learned in order to detect the outliers. Linear models use regression analysis based techniques for detecting outliers. Proximity based models use distance based algorithms such as k-nearest neighbour, clustering algorithms such as k-means, or density based algorithms such as kernel density estimation. In this work, we will use unsupervised learning algorithms with only the proximity based models. In addition, we explore the relative strengths and weaknesses of the various techniques by validating the outliers. The validation criteria for the outliers is if the ratio of planetary mass to stellar mass is less than 0.001. In this work, we present our statistical analysis of the outliers thus detected.

  16. 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.

  17. 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. PMID:20588502

  18. 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

  19. 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.

  20. 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.

  1. 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)

  2. Machine Learning Techniques for Combining Multi-Model Climate Projections (Invited)

    NASA Astrophysics Data System (ADS)

    Monteleoni, C.

    2013-12-01

    The threat of climate change is one of the greatest challenges currently facing society. Given the profound impact machine learning has made on the natural sciences to which it has been applied, such as the field of bioinformatics, machine learning is poised to accelerate discovery in climate science. Recent advances in the fledgling field of climate informatics have demonstrated the promise of machine learning techniques for problems in climate science. A key problem in climate science is how to combine the projections of the multi-model ensemble of global climate models that inform the Intergovernmental Panel on Climate Change (IPCC). I will present three approaches to this problem. Our Tracking Climate Models (TCM) work demonstrated the promise of an algorithm for online learning with expert advice, for this task. Given temperature projections and hindcasts from 20 IPCC global climate models, and over 100 years of historical temperature data, TCM generated predictions that tracked the changing sequence of which model currently predicts best. On historical data, at both annual and monthly time-scales, and in future simulations, TCM consistently outperformed the average over climate models, the existing benchmark in climate science, at both global and continental scales. We then extended TCM to take into account climate model projections at higher spatial resolutions, and to model geospatial neighborhood influence between regions. Our second algorithm enables neighborhood influence by modifying the transition dynamics of the Hidden Markov Model from which TCM is derived, allowing the performance of spatial neighbors to influence the temporal switching probabilities for the best climate model at a given location. We recently applied a third technique, sparse matrix completion, in which we create a sparse (incomplete) matrix from climate model projections/hindcasts and observed temperature data, and apply a matrix completion algorithm to recover it, yielding

  3. 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.

  4. 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…

  5. 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

  6. Electron-beam manipulation techniques in the SINBAD Linac for external injection in plasma wake-field acceleration

    NASA Astrophysics Data System (ADS)

    Marchetti, B.; Assmann, R.; Behrens, C.; Brinkmann, R.; Dorda, U.; Floettmann, K.; Hartl, I.; Huening, M.; Nie, Y.; Schlarb, H.; Zhu, J.

    2016-09-01

    The SINBAD facility (Short and INnovative Bunches and Accelerators at Desy) is foreseen to host various experiments in the field of production of ultra-short electron bunches and novel high gradient acceleration techniques. Besides studying novel acceleration techniques aiming to produce high brightness short electron bunches, the ARD group at DESY is working on the design of a conventional RF accelerator that will allow the production of low charge (0.5 pC - few pC) ultra-short electron bunches (having full width half maximum, FWHM, length ≤ 1 fs - few fs). The setup will allow the direct experimental comparison of the performance achievable by using different compression techniques (velocity bunching, magnetic compression, hybrid compression schemes). At a later stage the SINBAD linac will be used to inject such electron bunches into a laser driven Plasma Wakefield Accelerator, which imposes strong requirements on parameters such as the arrival time jitter and the pointing stability of the beam. In this paper we review the compression techniques that are foreseen at SINBAD and we underline the differences in terms of peak current, beam quality and arrival time stability.

  7. Radiolabeled microsphere technique in conscious subjects during acceleration exposures on the USAFAM centrifuge. Final report, August 1977-November 1978

    SciTech Connect

    Laughlin, M.H.; Jaggars, J.L.

    1980-03-01

    The methods used to apply the radiolabeled microsphere technique for the study of the effects of +Gz acceleration on regional blood flows are presented. A remote-control system designed to infuse suspensions of microspheres into the left atrium on conscious animals is outlined as is a device which allows the remote, sequential withdrawal of six blood samples. Results are presented which demonstrate that the cautious application of the radiolabeled microsphere technique using the outlined systems can produce good information about the effects of +Gz acceleration on regional blood flows.

  8. Classifying Structures in the ISM with Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Beaumont, Christopher; Goodman, A. A.; Williams, J. P.

    2011-01-01

    The processes which govern molecular cloud evolution and star formation often sculpt structures in the ISM: filaments, pillars, shells, outflows, etc. Because of their morphological complexity, these objects are often identified manually. Manual classification has several disadvantages; the process is subjective, not easily reproducible, and does not scale well to handle increasingly large datasets. We have explored to what extent machine learning algorithms can be trained to autonomously identify specific morphological features in molecular cloud datasets. We show that the Support Vector Machine algorithm can successfully locate filaments and outflows blended with other emission structures. When the objects of interest are morphologically distinct from the surrounding emission, this autonomous classification achieves >90% accuracy. We have developed a set of IDL-based tools to apply this technique to other datasets.

  9. Gene discovery for facioscapulohumeral muscular dystrophy by machine learning techniques.

    PubMed

    González-Navarro, Félix F; Belanche-Muñoz, Lluís A; Gámez-Moreno, María G; Flores-Ríos, Brenda L; Ibarra-Esquer, Jorge E; López-Morteo, Gabriel A

    2016-04-28

    Facioscapulohumeral muscular dystrophy (FSHD) is a neuromuscular disorder that shows a preference for the facial, shoulder and upper arm muscles. FSHD affects about one in 20-400,000 people, and no effective therapeutic strategies are known to halt disease progression or reverse muscle weakness or atrophy. Many genes may be incorrectly regulated in affected muscle tissue, but the mechanisms responsible for the progressive muscle weakness remain largely unknown. Although machine learning (ML) has made significant inroads in biomedical disciplines such as cancer research, no reports have yet addressed FSHD analysis using ML techniques. This study explores a specific FSHD data set from a ML perspective. We report results showing a very promising small group of genes that clearly separates FSHD samples from healthy samples. In addition to numerical prediction figures, we show data visualizations and biological evidence illustrating the potential usefulness of these results. PMID:26960968

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

    PubMed

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

    2014-01-01

    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. PMID:25313492

  11. 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.

  12. Estimation of Alpine Skier Posture Using Machine Learning Techniques

    PubMed Central

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

    2014-01-01

    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. PMID:25313492

  13. Prediction of brain tumor progression using a machine learning technique

    NASA Astrophysics Data System (ADS)

    Shen, Yuzhong; Banerjee, Debrup; Li, Jiang; Chandler, Adam; Shen, Yufei; McKenzie, Frederic D.; Wang, Jihong

    2010-03-01

    A machine learning technique is presented for assessing brain tumor progression by exploring six patients' complete MRI records scanned during their visits in the past two years. There are ten MRI series, including diffusion tensor image (DTI), for each visit. After registering all series to the corresponding DTI scan at the first visit, annotated normal and tumor regions were overlaid. Intensity value of each pixel inside the annotated regions were then extracted across all of the ten MRI series to compose a 10 dimensional vector. Each feature vector falls into one of three categories:normal, tumor, and normal but progressed to tumor at a later time. In this preliminary study, we focused on the trend of brain tumor progression during three consecutive visits, i.e., visit A, B, and C. A machine learning algorithm was trained using the data containing information from visit A to visit B, and the trained model was used to predict tumor progression from visit A to visit C. Preliminary results showed that prediction for brain tumor progression is feasible. An average of 80.9% pixel-wise accuracy was achieved for tumor progression prediction at visit C.

  14. 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.

  15. 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…

  16. 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…

  17. Microteaching, an efficient technique for learning effective teaching

    PubMed Central

    Remesh, Ambili

    2013-01-01

    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. PMID:23914219

  18. 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

  19. Combining active learning and semi-supervised learning techniques to extract protein interaction sentences

    PubMed Central

    2011-01-01

    Background Protein-protein interaction (PPI) extraction has been a focal point of many biomedical research and database curation tools. Both Active Learning and Semi-supervised SVMs have recently been applied to extract PPI automatically. In this paper, we explore combining the AL with the SSL to improve the performance of the PPI task. Methods We propose a novel PPI extraction technique called PPISpotter by combining Deterministic Annealing-based SSL and an AL technique to extract protein-protein interaction. In addition, we extract a comprehensive set of features from MEDLINE records by Natural Language Processing (NLP) techniques, which further improve the SVM classifiers. In our feature selection technique, syntactic, semantic, and lexical properties of text are incorporated into feature selection that boosts the system performance significantly. Results By conducting experiments with three different PPI corpuses, we show that PPISpotter is superior to the other techniques incorporated into semi-supervised SVMs such as Random Sampling, Clustering, and Transductive SVMs by precision, recall, and F-measure. Conclusions Our system is a novel, state-of-the-art technique for efficiently extracting protein-protein interaction pairs. PMID:22168401

  20. Interpersonal Process Recall: An Innovative Technique

    ERIC Educational Resources Information Center

    Benedek, Elissa P.; Bieniek, Christine M.

    1977-01-01

    Three specific skills are described that the novice psychiatric resident must begin to learn: interviewing techniques, self-observation, and empathy. Curriculum effective in accelerating the learning process, i.e., interpersonal process recall, is also discussed. (Author/LBH)

  1. 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

  2. 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. PMID:19787345

  3. 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)

  4. Problem-Based Learning Supported by Semantic Techniques

    ERIC Educational Resources Information Center

    Lozano, Esther; Gracia, Jorge; Corcho, Oscar; Noble, Richard A.; Gómez-Pérez, Asunción

    2015-01-01

    Problem-based learning has been applied over the last three decades to a diverse range of learning environments. In this educational approach, different problems are posed to the learners so that they can develop different solutions while learning about the problem domain. When applied to conceptual modelling, and particularly to Qualitative…

  5. 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.

  6. 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…

  7. Role Play Simulations: The Assessment of an Active Learning Technique and Comparisons with Traditional Lectures.

    ERIC Educational Resources Information Center

    DeNeve, Kristina; Heppner, Mary J.

    1997-01-01

    Use of active learning techniques of role-playing and simulation in an industrial psychology course (n=29 students) is described and assessed. Subjective reports and objective assessments of knowledge retention indicate the approach was effective. The differential importance of active learning and passive learning (lecture) in the college…

  8. 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,…

  9. Exploring Undergraduates' Perceptions of the Use of Active Learning Techniques in Science Lectures

    ERIC Educational Resources Information Center

    Welsh, Ashley J.

    2012-01-01

    This paper examines students' mixed perceptions of the use of active learning techniques in undergraduate science lectures. Written comments from over 250 students offered an in-depth view of why students perceive these techniques as helping or hindering their learning and experience. Fourth- and fifth-year students were more likely to view…

  10. 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.

  11. 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. PMID:26932032

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

    NASA Astrophysics Data System (ADS)

    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.

  13. 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.

  14. Fully parallel write/read in resistive synaptic array for accelerating on-chip learning

    NASA Astrophysics Data System (ADS)

    Gao, Ligang; Wang, I.-Ting; Chen, Pai-Yu; Vrudhula, Sarma; Seo, Jae-sun; Cao, Yu; Hou, Tuo-Hung; Yu, Shimeng

    2015-11-01

    A neuro-inspired computing paradigm beyond the von Neumann architecture is emerging and it generally takes advantage of massive parallelism and is aimed at complex tasks that involve intelligence and learning. The cross-point array architecture with synaptic devices has been proposed for on-chip implementation of the weighted sum and weight update in the learning algorithms. In this work, forming-free, silicon-process-compatible Ta/TaO x /TiO2/Ti synaptic devices are fabricated, in which >200 levels of conductance states could be continuously tuned by identical programming pulses. In order to demonstrate the advantages of parallelism of the cross-point array architecture, a novel fully parallel write scheme is designed and experimentally demonstrated in a small-scale crossbar array to accelerate the weight update in the training process, at a speed that is independent of the array size. Compared to the conventional row-by-row write scheme, it achieves >30× speed-up and >30× improvement in energy efficiency as projected in a large-scale array. If realistic synaptic device characteristics such as device variations are taken into an array-level simulation, the proposed array architecture is able to achieve ∼95% recognition accuracy of MNIST handwritten digits, which is close to the accuracy achieved by software using the ideal sparse coding algorithm.

  15. Accelerated Learning Options: Moving the Needle on Access and Success. A Study of State and Institutional Policies and Practices

    ERIC Educational Resources Information Center

    Western Interstate Commission for Higher Education, 2006

    2006-01-01

    This document was designed to inform members of the policy, education, and research communities about existing state and institutional policies and practices associated with four accelerated learning programs: Advanced Placement (AP), dual/concurrent enrollment, the International Baccalaureate (IB) Diploma Program, and Tech-Prep. This effort was…

  16. 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…

  17. 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…

  18. 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…

  19. Positional cues in serial learning: the spin-list technique.

    PubMed

    Kahana, Michael J; Mollison, Matthew V; Addis, Kelly M

    2010-01-01

    To test the hypothesis that serial learning depends largely on the encoding and retrieval of position-to-item associations, we examined whether people can learn spin lists on which starting position is randomly varied across successive learning trials. By turning positional information from a reliable cue into a source of intertrial interference, we expected learning to be greatly impaired. Contrary to this hypothesis, we found that participants were only slightly worse at serial learning under spin conditions and that this impairment reflects a substantial increase in initiation errors coupled with a small increase in intertrial forgetting. These data show that participants can effectively use nonpositional cues when positional cues are unreliable. PMID:19966242

  20. 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.

  1. Comparison of extraction techniques and modeling of accelerated solvent extraction for the authentication of natural vanilla flavors.

    PubMed

    Cicchetti, Esmeralda; Chaintreau, Alain

    2009-06-01

    Accelerated solvent extraction (ASE) of vanilla beans has been optimized using ethanol as a solvent. A theoretical model is proposed to account for this multistep extraction. This allows the determination, for the first time, of the total amount of analytes initially present in the beans and thus the calculation of recoveries using ASE or any other extraction technique. As a result, ASE and Soxhlet extractions have been determined to be efficient methods, whereas recoveries are modest for maceration techniques and depend on the solvent used. Because industrial extracts are obtained by many different procedures, including maceration in various solvents, authenticating vanilla extracts using quantitative ratios between the amounts of vanilla flavor constituents appears to be unreliable. When authentication techniques based on isotopic ratios are used, ASE is a valid sample preparation technique because it does not induce isotopic fractionation. PMID:19425014

  2. 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.

  3. 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.

  4. Student Knowledge and Confidence in an Elective Clinical Toxicology Course Using Active-Learning Techniques

    PubMed Central

    Macias-Moriarity, Liliairica Z.

    2014-01-01

    Objective. To measure changes in students’ knowledge and confidence scores after completing an elective clinical toxicology course in an accelerated doctor of pharmacy (PharmD) program. Design. Various active-learning techniques were used to create a learner-centered environment. Approximately two-thirds of the course used student-led presentations. Some of those not presenting were assigned to be evaluators, responsible for asking the presenter a question or writing quiz questions based on the presented material. Other learner-centered activities included weekly quizzes and discussions at the conclusion of each presented topic. Assessment. A test instrument designed to measure students’ knowledge and associated level of confidence on each item was administered at the beginning and end of the course. Students’ knowledge and confidence scores increased significantly from pretest to posttest. Conclusions. Students’ increased confidence and knowledge scores were well correlated after course completion, indicating students were better able to self-assess these areas. These findings suggest that confidence could be an additional measure of students' metacognitive skill development. PMID:24954935

  5. 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…

  6. 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

  7. 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. PMID:26753024

  8. 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

  9. Reinforcement Learning in Large Scale Systems Using State Generalization and Multi-Agent Techniques

    NASA Astrophysics Data System (ADS)

    Kimura, Hajime; Aoki, Kei; Kobayashi, Shigenobu

    This paper introduces several problems in reinforcement learning of industrial applications, and shows some techniques to overcome it. Reinforcement learning is known as on-line learning of an input-output mapping through a process of trial and error interactions with its uncertain environment, however, the trial and error will cause fatal damages in real applications. We introduce a planning method, based on reinforcement learning in the simulator. It can be seen as a stochastic approximation of dynamic programming in Markov decision processes. But in large problems, simple grid-tiling to quantize state space for tabular Q-learning is still infeasible. We introduce a generalization technique to approximate value functions in continuous state space, and a multiagent architecture to solve large scale problems. The efficiency of these techniques are shown through experiments in a sewage water-flow control system.

  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. 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. PMID:23910179

  12. 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.

  13. Silhouette method for hidden surface removal in computer holography and its acceleration using the switch-back technique.

    PubMed

    Matsushima, Kyoji; Nakamura, Masaki; Nakahara, Sumio

    2014-10-01

    A powerful technique is presented for occlusion processing in computer holography. The technique offers an improvement on the conventional silhouette method, which is a general wave optics-based occlusion processing method. The proposed technique dramatically reduces the computation time required for computer-generated holograms (CGH) of self-occluded objects. Performance measurements show that a full-parallax high-definition CGH composed of billions of pixels and a small CGH intended to be reconstructed in electro-holography can be computed in only 1.7 h and 4.5 s, respectively, without any hardware acceleration. Optical reconstruction of the high-definition CGH shows natural and continuous motion parallax in the self-occluded object. PMID:25322021

  14. Linear Accelerator-Based Intensity-Modulated Total Marrow Irradiation Technique for Treatment of Hematologic Malignancies: A Dosimetric Feasibility Study

    SciTech Connect

    Yeginer, Mete; Roeske, John C.; Radosevich, James A.; Aydogan, Bulent

    2011-03-15

    Purpose: To investigate the dosimetric feasibility of linear accelerator-based intensity-modulated total marrow irradiation (IM-TMI) in patients with hematologic malignancies. Methods and Materials: Linear accelerator-based IM-TMI treatment planning was performed for 9 patients using the Eclipse treatment planning system. The planning target volume (PTV) consisted of all the bones in the body from the head to the mid-femur, except for the forearms and hands. Organs at risk (OAR) to be spared included the lungs, heart, liver, kidneys, brain, eyes, oral cavity, and bowel and were contoured by a physician on the axial computed tomography images. The three-isocenter technique previously developed by our group was used for treatment planning. We developed and used a common dose-volume objective method to reduce the planning time and planner subjectivity in the treatment planning process. Results: A 95% PTV coverage with the 99% of the prescribed dose of 12 Gy was achieved for all nine patients. The average dose reduction in OAR ranged from 19% for the lungs to 68% for the lenses. The common dose-volume objective method decreased the planning time by an average of 35% and reduced the inter- and intra- planner subjectivity. Conclusion: The results from the present study suggest that the linear accelerator-based IM-TMI technique is clinically feasible. We have demonstrated that linear accelerator-based IM-TMI plans with good PTV coverage and improved OAR sparing can be obtained within a clinically reasonable time using the common dose-volume objective method proposed in the present study.

  15. 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

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

    PubMed

    Marušič, Franc; Žaucer, Rok; 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

  17. 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…

  18. 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…

  19. 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…

  20. 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,…

  1. 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…

  2. 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…

  3. 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.

  4. The Development of Distributed Learning Techniques in Bhutan and Nepal

    ERIC Educational Resources Information Center

    Rennie, Frank; Mason, Robin

    2007-01-01

    This paper discusses research and development work currently being conducted with universities in Bhutan and Nepal to design appropriate systems for distance and distributed learning courses among a network of campus sites. Although working from a high level of awareness of pedagogic skills, staff in the region face two significant impediments in…

  5. 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…

  6. 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…

  7. 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…

  8. Impacts of Vocabulary Acquisition Techniques Instruction on Students' Learning

    ERIC Educational Resources Information Center

    Orawiwatnakul, Wiwat

    2011-01-01

    The objectives of this study were to determine how the selected vocabulary acquisition techniques affected the vocabulary ability of 35 students who took EN 111 and investigate their attitudes towards the techniques instruction. The research study was one-group pretest and post-test design. The instruments employed were in-class exercises…

  9. Advanced quadrature sets and acceleration and preconditioning techniques for the discrete ordinates method in parallel computing environments

    NASA Astrophysics Data System (ADS)

    Longoni, Gianluca

    In the nuclear science and engineering field, radiation transport calculations play a key-role in the design and optimization of nuclear devices. The linear Boltzmann equation describes the angular, energy and spatial variations of the particle or radiation distribution. The discrete ordinates method (S N) is the most widely used technique for solving the linear Boltzmann equation. However, for realistic problems, the memory and computing time require the use of supercomputers. This research is devoted to the development of new formulations for the SN method, especially for highly angular dependent problems, in parallel environments. The present research work addresses two main issues affecting the accuracy and performance of SN transport theory methods: quadrature sets and acceleration techniques. New advanced quadrature techniques which allow for large numbers of angles with a capability for local angular refinement have been developed. These techniques have been integrated into the 3-D SN PENTRAN (Parallel Environment Neutral-particle TRANsport) code and applied to highly angular dependent problems, such as CT-Scan devices, that are widely used to obtain detailed 3-D images for industrial/medical applications. In addition, the accurate simulation of core physics and shielding problems with strong heterogeneities and transport effects requires the numerical solution of the transport equation. In general, the convergence rate of the solution methods for the transport equation is reduced for large problems with optically thick regions and scattering ratios approaching unity. To remedy this situation, new acceleration algorithms based on the Even-Parity Simplified SN (EP-SSN) method have been developed. A new stand-alone code system, PENSSn (Parallel Environment Neutral-particle Simplified SN), has been developed based on the EP-SSN method. The code is designed for parallel computing environments with spatial, angular and hybrid (spatial/angular) domain

  10. Plasma accelerators

    SciTech Connect

    Ruth, R.D.; Chen, P.

    1986-03-01

    In this paper we discuss plasma accelerators which might provide high gradient accelerating fields suitable for TeV linear colliders. In particular we discuss two types of plasma accelerators which have been proposed, the Plasma Beat Wave Accelerator and the Plasma Wake Field Accelerator. We show that the electric fields in the plasma for both schemes are very similar, and thus the dynamics of the driven beams are very similar. The differences appear in the parameters associated with the driving beams. In particular to obtain a given accelerating gradient, the Plasma Wake Field Accelerator has a higher efficiency and a lower total energy for the driving beam. Finally, we show for the Plasma Wake Field Accelerator that one can accelerate high quality low emittance beams and, in principle, obtain efficiencies and energy spreads comparable to those obtained with conventional techniques.

  11. 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

  12. Scattering of the transverse magnetic modes from an abruptly ended strongly asymmetrical slab waveguide by an accelerated integral equation technique.

    PubMed

    Manenkov, A B; Latsas, G P; Tigelis, L G

    2001-12-01

    We study the problem of the scattering of the first TM guided mode from an abruptly ended strongly asymmetrical slab waveguide by an improved iteration technique, which is based on the integral equation method with "accelerating" parameters. We demonstrate that the values of these parameters are related to the variational principle, and we save approximately 1-2 iterations compared with the case in which these parameters are not employed. The tangential electric-field distribution on the terminal plane, the reflection coefficient of the first TM guided mode, and the far-field radiation pattern are computed. Furthermore, a simple technique based on the Aitken extrapolation procedure is employed for faster computation of the higher-order solutions of the reflection coefficient. Numerical results are presented for several cases of abruptly ended waveguides, including systems with variational profile, while special attention is given to the far-field radiation pattern rotation and its explanation. PMID:11760208

  13. 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. PMID:19625669

  14. 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

  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. Accelerated single-beam wavefront reconstruction techniques based on relaxation and multiresolution strategies.

    PubMed

    Falaggis, Konstantinos; Kozacki, Tomasz; Kujawinska, Malgorzata

    2013-05-15

    A previous Letter by Pedrini et al. [Opt. Lett. 30, 833 (2005)] proposed an iterative single-beam wavefront reconstruction algorithm that uses a sequence of interferograms recorded at different planes. In this Letter, the use of relaxation and multiresolution strategies is investigated in terms of accuracy and computational effort. It is shown that the convergence rate of the conventional iterative algorithm can be significantly improved with the use of relaxation techniques combined with a hierarchy of downsampled intensities that are used within a preconditioner. These techniques prove to be more robust, to achieve a higher accuracy, and to overcome the stagnation problem met in the iterative wavefront reconstruction. PMID:23938902

  17. 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…

  18. "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…

  19. A Comparison of the Effects of Super Learning Techniques on the Learning of English as a Second Language.

    ERIC Educational Resources Information Center

    Zeiss, Paul Anthony

    The effects of selected superlearning techniques on the retention of technical vocabulary by Saudi Arabian students learning English as a second language were examined. The sample consisted of 14 Saudi Arabian nationals aged 18 to 21 years enrolled in college level technical vocabulary classes. The study involved three weeks of treatment followed…

  20. Analyzing Complex and Structured Data via Unsupervised Learning Techniques

    NASA Astrophysics Data System (ADS)

    Polsterer, Kai Lars; Gieseke, Fabian; Gianniotis, Nikos; Kügler, Dennis

    2015-08-01

    In the last decades more and more dedicated all-sky-surveys created an enormous amount of data which is publicly available on the internet. The resulting datasets contain spatial, spectral, and temporal information which exhibit complex structures in the respective domain. The capability to deal with morphological features, spectral signatures, and complex time series data has become very important but is still a challenging task. A common approach when processing this kind of structured data is to extract representative features and use those for a further analysis. We present unsupervised learning approaches that help to visualize / cluster these complex data sets by e.g. deriving rotation / translation invariant prototypes or capturing the latent dynamics of time series without employing features and using echo-state-networks instead.

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

    DOE PAGESBeta

    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 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

  2. Automated Technologies and Novel Techniques to Accelerate Protein Crystallography for Structrual Genomics

    SciTech Connect

    Manjasetty,B.; Turnbull, A.; Panjikar, S.; Bussow, K.; Chance, M.

    2008-01-01

    The sequence infrastructure that has arisen through large-scale genomic projects dedicated to protein analysis, has provided a wealth of information and brought together scientists and institutions from all over the world. As a consequence, the development of novel technologies and methodologies in proteomics research is helping to unravel the biochemical and physiological mechanisms of complex multivariate diseases at both a functional and molecular level. In the late sixties, when X-ray crystallography had just been established, the idea of determining protein structure on an almost universal basis was akin to an impossible dream or a miracle. Yet only forty years after, automated protein structure determination platforms have been established. The widespread use of robotics in protein crystallography has had a huge impact at every stage of the pipeline from protein cloning, over-expression, purification, crystallization, data collection, structure solution, refinement, validation and data management- all of which have become more or less automated with minimal human intervention necessary. Here, recent advances in protein crystal structure analysis in the context of structural genomics will be discussed. In addition, this review aims to give an overview of recent developments in high throughput instrumentation, and technologies and strategies to accelerate protein structure/function analysis.

  3. 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.

  4. Figure analysis: A teaching technique to promote visual literacy and active Learning.

    PubMed

    Wiles, Amy M

    2016-07-01

    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 biology courses. An additional challenge is that visual literacy is often overlooked in undergraduate science education. To address both of these challenges, a technique called figure analysis was developed and implemented in three different levels of undergraduate biology courses. Here, students learn content while gaining practice in interpreting visual information by discussing figures with their peers. Student groups also make connections between new and previously learned concepts on their own while in class. The instructor summarizes the material for the class only after students grapple with it in small groups. Students reported a preference for learning by figure analysis over traditional lecture, and female students in particular reported increased confidence in their analytical abilities. There is not a technology requirement for this technique; therefore, it may be utilized both in classrooms and in nontraditional spaces. Additionally, the amount of preparation required is comparable to that of a traditional lecture. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(4):336-344, 2016. PMID:26891952

  5. 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…

  6. Nonlinear optimisation techniques for accelerator performance improvement on-line: recent trials and experiment for the CERN antiproton accumulator

    NASA Astrophysics Data System (ADS)

    Chohan, Vinod

    1986-06-01

    The use of function minimisation techniques for optimum design according to given performance criteria is well-known. Given a well-defined criterion and a means of evaluating it precisely, the problem reduces to choosing the best optimisation procedure to suit the problem. Direct search techniques which do not generally rely on the computation of derivatives of the error function are ideal for on-line improvement of the global accelerator performance since the error function is not known analytically, e.g. the number of antiprotons stored in the antiproton accumulator ring on a pulse-to-pulse basis as a function of all the antiproton production and stochastic cooling system parameters. The user-friendliness of the NODAL interpreter at the man-machine interaction level, its capability to easily control and manipulate equipment as well as its capability to synchronise with respect to time events on a cycle-to-cycle basis makes it suitable for an on-line accelerator performance optimisation type of application. A modular procedure, based on the Simplex technique [1] has been implemented recently which allows function minimisation depending on the error function definition module. This enables an easy manipulation of variables and synchronization with machine events. For the antiproton accumulator (AA), while the circulating beam current transformer lacks the resolution to measure the exact number of antiprotons stored on a pulse-to-pulse basis, there are a large number of electrons produced in the production process [2] and a signal emanating from these can be adapted to provide the performance criterion and appropriate parameters used as function variables in the optimisation process. First trials based on optimisation of injection of antiprotons in the AA look promising, but further work is necessary in the direct definition of the error functions.

  7. 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 compare…

  8. 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…

  9. Accelerating plant DNA barcode reference library construction using herbarium specimens: improved experimental techniques.

    PubMed

    Xu, Chao; Dong, Wenpan; Shi, Shuo; Cheng, Tao; Li, Changhao; Liu, Yanlei; Wu, Ping; Wu, Hongkun; Gao, Peng; Zhou, Shiliang

    2015-11-01

    A well-covered reference library is crucial for successful identification of species by DNA barcoding. The biggest difficulty in building such a reference library is the lack of materials of organisms. Herbarium collections are potentially an enormous resource of materials. In this study, we demonstrate that it is likely to build such reference libraries using the reconstructed (self-primed PCR amplified) DNA from the herbarium specimens. We used 179 rosaceous specimens to test the effects of DNA reconstruction, 420 randomly sampled specimens to estimate the usable percentage and another 223 specimens of true cherries (Cerasus, Rosaceae) to test the coverage of usable specimens to the species. The barcode rbcLb (the central four-sevenths of rbcL gene) and matK was each amplified in two halves and sequenced on Roche GS 454 FLX+. DNA from the herbarium specimens was typically shorter than 300 bp. DNA reconstruction enabled amplification fragments of 400-500 bp without bringing or inducing any sequence errors. About one-third of specimens in the national herbarium of China (PE) were proven usable after DNA reconstruction. The specimens in PE cover all Chinese true cherry species and 91.5% of vascular species listed in Flora of China. It is very possible to build well-covered reference libraries for DNA barcoding of vascular species in China. As exemplified in this study, DNA reconstruction and DNA-labelled next-generation sequencing can accelerate the construction of local reference libraries. By putting the local reference libraries together, a global library for DNA barcoding becomes closer to reality. PMID:25865498

  10. Spontaneous and artificial lesions of magnocellular reticular formation of brainstem deteriorate avoidance learning in senescence-accelerated mouse SAM.

    PubMed

    Yagi, H; Akiguchi, I; Ohta, A; Yagi, N; Hosokawa, M; Takeda, T

    1998-04-27

    The role of the magnocellular reticular formation (MGRF) of the brainstem on learning and memory was examined in memory-deficient mice with spontaneous spongy degeneration in the brainstem (senescence-accelerated mouse, SAMP8) and control mice (accelerated-senescence resistant mouse, SAMR 1). SAMP8 showed spontaneous age-related impairment of learning and memory, as determined by passive and active avoidance responses. The deficits of learning and memory function in passive avoidance performances began at two months of age and increased with ageing. In the brains of SAMP8 at one month of age and older, spongy degeneration was mainly observed in the brainstem, while no vacuoles were evident in SAMR1 control (normal ageing mouse) brains in the age range tested (up to 12 months). The vacuolization in SAMP8 was marked in the MGRF, especially in the dorsomedial MGRF. Quantitative analysis of the vacuolization showed that the total area and number of vacuoles in the MGRF increased with age, and they were affected by the degree of deficits in learning and memory. The latency 24 h after footshock in passive avoidance tests decreased with the increase in total area and number of vacuoles in MGRF. The number of shocks in active avoidance tests increased with the increase in total number and area of vacuoles. Thus, learning and memory ability in passive and active avoidance responses deteriorated with enlargement in the vacuolated area in MGRF, and it was assumed that MGRF (especially, the dorsomedial part) possesses functions related to learning and memory. To confirm this notion, behavior and memory tests (passive avoidance and active avoidance tests, open field tests and shock sensitivity measurements) were carried out in SAMR1 mice, whose bilateral dorsomedial MGRF was destroyed electrolytically (MGRF-lesioned mice). The MGRF-lesioned mice showed no difference from sham mice in sensory threshold or open field activity; however, there was severe deterioration in passive

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

    PubMed

    Hasegawa, Tatsuhito; Koshino, Makoto; Kimura, Haruhiko

    2015-01-01

    In this study, we improved the usability of smartphones by automating a user's operations. We developed an intelligent system using machine learning techniques that periodically detects a user's context on a smartphone. We selected the Android operating system because it has the largest market share and highest flexibility of its development environment. In this paper, we describe an application that automatically adjusts application volume. Adjusting the volume can be easily forgotten because users need to push the volume buttons to alter the volume depending on the given situation. Therefore, we developed an application that automatically adjusts the volume based on learned user settings. Application volume can be set differently from ringtone volume on Android devices, and these volume settings are associated with each specific application including games. Our application records a user's location, the volume setting, the foreground application name and other such attributes as learning data, thereby estimating whether the volume should be adjusted using machine learning techniques via Weka. PMID:25713755

  12. Accelerator test of the coded aperture mask technique for gamma-ray astronomy

    NASA Technical Reports Server (NTRS)

    Jenkins, T. L.; Frye, G. M., Jr.; Owens, A.; Carter, J. N.; Ramsden, D.

    1982-01-01

    A prototype gamma-ray telescope employing the coded aperture mask technique has been constructed and its response to a point source of 20 MeV gamma-rays has been measured. The point spread function is approximately a Gaussian with a standard deviation of 12 arc minutes. This resolution is consistent with the cell size of the mask used and the spatial resolution of the detector. In the context of the present experiment, the error radius of the source position (90 percent confidence level) is 6.1 arc minutes.

  13. 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.

  14. Characterization of radiochromic film scanning techniques used in short-pulse-laser ion acceleration

    SciTech Connect

    Cowan, Joseph S.; Flippo, Kirk A.; Gaillard, Sandrine A.

    2008-10-15

    Radiochromic film (RCF) is increasingly being used as a detector for proton beams from short-pulse laser-matter interaction experiments using the RCF imaging spectroscope technique. The community has traditionally used inexpensive flatbed scanners to digitize and analyze the data, as opposed to more expensive and time-consuming microdensitometers (MicroDs). Often, the RCF densities in some regions exceed an optical density (OD) of 3. Flatbed scanners are generally limited to a maximum OD of {approx}3. Because of the high exposure density, flatbed scanners may yield data that are not reliable due to light scatter and light diffusion from areas of low density to areas of high density. This happens even when the OD is slightly above 1. We will demonstrate the limitations of using flatbed scanners for this type of radiographic media and characterize them compared to measurements made using a MicroD. A technique for cross characterizing both systems using a diffuse densitometer with a NIST wedge will also be presented.

  15. 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

  16. Retrospective analysis of linear accelerator output constancy checks using process control techniques.

    PubMed

    Sanghangthum, Taweap; Suriyapee, Sivalee; Srisatit, Somyot; Pawlicki, Todd

    2013-01-01

    Shewhart control charts have previously been suggested as a process control tool for use in routine linear accelerator (linac) output verifications. However, a comprehensive approach to process control has not been investigated for linac output verifications. The purpose of this work is to investigate a comprehensive process control approach to linac output constancy quality assurance (QA). The RBA-3 dose constancy check was used to verify outputs of photon beams and electron beams delivered by a Varian Clinac 21EX linac. The data were collected during 2009 to 2010. Shewhart-type control charts, exponentially weighted moving average (EWMA) charts, and capability indices were applied to these processes. The Shewhart-type individuals chart (X-chart) was used and the number of data points used to calculate the control limits was varied. The parameters tested for the EWMA charts (smoothing parameter (λ) and the control limit width (L)) were λ = 0.05, L = 2.492; λ = 0.10, L = 2.703; and λ = 0.20, L = 2.860, as well as the number of points used to estimate the initial process mean and variation. Lastly, the number of in-control data points used to determine process capability (C(p)) and acceptability (C(pk)) were investigated, comparing the first in-control run to the longest in-control run of the process data. C(p) and C(pk) values greater than 1.0 were considered acceptable. The 95% confidence intervals were reported. The X-charts detected systematic errors (e.g., device setup errors). In-control run lengths on the X-charts varied from 5 to 30 output measurements (about one to seven months). EWMA charts showed in-control runs ranging from 9 to 33 output measurements (about two to eight months). The C(p) and C(pk) ratios are higher than 1.0 for all energies, except 12 and 20 MeV. However, 10 MV and 6, 9, and 16 MeV were in question when considering the 95% confidence limits. The X-chart should be calculated using 8-12 data points. For EWMA chart, using 4 data points

  17. 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.

  18. An Interactive Learning Environment for Teaching the Imperative and Object-Oriented Programming Techniques in Various Learning Contexts

    NASA Astrophysics Data System (ADS)

    Xinogalos, Stelios

    The acquisition of problem-solving and programming skills in the era of knowledge society seems to be particularly important. Due to the intrinsic difficulty of acquiring such skills various educational tools have been developed. Unfortunately, most of these tools are not utilized. In this paper we present the programming microworlds Karel and objectKarel that support the procedural-imperative and Object-Oriented Programming (OOP) techniques and can be used for supporting the teaching and learning of programming in various learning contexts and audiences. The paper focuses on presenting the pedagogical features that are common to both environments and mainly on presenting the potential uses of these environments.

  19. 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.

  20. The normalized weighting factor method: A novel technique for accelerating the convergence of high-resolution convective schemes

    SciTech Connect

    Darwish, M.D.; Moukalled, F.

    1996-09-01

    This article deals with the development of a new method for accelerating the solution of flow problems discretized using high-resolution convective schemes. The technique is based on the normalized variable and space formulation (NVSF) methodology and is denoted here by the normalized weighting-factor (NWF) method. In contrast with the well-known deferred-correction (DC) procedure, the NWF method is fully implicit and is derived by directly replacing the control-volume face values by their functional relationships in the discretized equation. The direct substitution is performed by the introduction of a variable, NWF, that accounts for the multiplicity of interpolation profiles in HR schemes. The new method is compared with the widely used DC procedure and is shown to be, on average, four times faster.

  1. 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

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

    PubMed

    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

  3. Characterization techniques for fixed-field alternating gradient accelerators and beam studies using the KURRI 150 MeV proton FFAG

    NASA Astrophysics Data System (ADS)

    Sheehy, S. L.; Kelliher, D. J.; Machida, S.; Rogers, C.; Prior, C. R.; Volat, L.; Haj Tahar, M.; Ishi, Y.; Kuriyama, Y.; Sakamoto, M.; Uesugi, T.; Mori, Y.

    2016-07-01

    In this paper we describe the methods and tools used to characterize a 150 MeV proton scaling fixed field alternating gradient (FFAG) accelerator at Kyoto University Research Reactor Institute. Many of the techniques used are unique to this class of machine and are thus of relevance to any future FFAG accelerator. For the first time we detail systematic studies undertaken to improve the beam quality of the FFAG. The control of beam quality in this manner is crucial to demonstrating high power operation of FFAG accelerators in future.

  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. 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

  6. Emittance measurement of the Naval Postgraduate School linear accelerator using optical-transition-radiation techniques. Master's thesis

    SciTech Connect

    Hellstern, M.J.

    1991-09-01

    Using Optical Transition Radiation (OTR) beam diagnostics and Dr. Rule's clear foil interferometer analytic code, the normalized emittance of the Naval Postgraduate School (NPS) Linear Accelerator (linac) has been measured: the normalized horizontal emittance of 97 pi +/- 10 pi mm-mrad and the normalized vertical emittance of 54 pi +/- 8 pi mm-mrad. The experiment was performed independently twice using a Kapton foil/silicon mirror and a nitrocellulose foil/aluminum mirror Wartski interferometer. The Kapton foil provided an initial measurement of the emittance, and provided lessons learned for the nitrocellulose foil measurement. The emittance measurement of the NPS linac indicate that the value maybe too high for most free electron laser applications, but is very useful for radiation effect studies in high temperature superconductors, hardening, beam diagnostics, and for the production of x-rays through novel mechanisms such as transition radiation and parametric x-radiation generation. The beam divergence was determined by comparing theoretically calculated OTR patterns with the experimental data OTR patterns.

  7. 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…

  8. 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…

  9. 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

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

    SciTech Connect

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

    2014-07-01

    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 10 Gy 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 (V{sub 10}) or 20 Gy (V{sub 20}) 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 V{sub 5} and D{sub 5}). 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

  11. 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.

  12. 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…

  13. 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…

  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 Experimental Study for Effectiveness of Super-Learning Technique at Elementary Level in Pakistan

    ERIC Educational Resources Information Center

    Shafqat, Hussain; Muhammad, Sarwar; Imran, Yousaf; Naemullah; Inamullah

    2010-01-01

    The objective of the study was to experience the effectiveness of super-learning technique of teaching at elementary level. The study was conducted with 8th grade students at a public sector school. Pre-test and post-test control group designs were used. Experimental and control groups were formed randomly, the experimental group (N = 62),…

  16. 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…

  17. The Use of Concept-Learning Techniques in Vocabulary Development Instruction. Technical Note.

    ERIC Educational Resources Information Center

    Humes, Ann

    A research and development effort undertaken to test the hypothesis that concept-learning techniques should be used to teach sophisticated vocabulary concepts is described in this report. The first section provides background information. Specifically, it reviews the need for and the current state of vocabulary development instruction; delineates…

  18. 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)…

  19. Comparison of Two Word Learning Techniques and the Effect of Neighborhood Density for Late Talkers

    ERIC Educational Resources Information Center

    DeVeney, Shari L.; Cress, Cynthia J.; Reid, Robert

    2014-01-01

    The investigators compared two techniques for teaching expressive vocabulary to late talkers: modeling with an expectant pause and modeling with an evoked child production. They also explored the influence of neighborhood density on children's real word learning. Three late talkers (ages 25-33 months) received two alternating vocabulary…

  20. Adaptive learning of Multi-Sensor Integration techniques with genetic algorithms

    SciTech Connect

    Baker, J.E.

    1994-06-01

    This research focuses on automating the time-consuming process of developing and optimizing multi-sensor integration techniques. Our approach is currently based on adaptively learning how to exploit low-level image detail. Although this system is specifically designed to be both sensor and application domain independent, an empirical validation with actual multi-modal sensor data is presented.

  1. Making Learning Visible in Kindergarten Classrooms: Pedagogical Documentation as a Formative Assessment Technique

    ERIC Educational Resources Information Center

    Buldu, Mehmet

    2010-01-01

    This study investigated interactions between pedagogical documentation--a formative assessment technique and instructional intervention designed to increase student learning by recording children's experiences--and kindergarten children, families and teachers in the UAE. The study sample comprised six teachers in six kindergarten classrooms, 141…

  2. Debates as a Pedagogical Learning Technique: Empirical Research with Business Students

    ERIC Educational Resources Information Center

    Rao, Pramila

    2010-01-01

    Purpose: The purpose of this paper is to enhance knowledge on debates as a pedagogical learning technique. Design/methodology/approach: This empirical research was conducted in a northeastern university in the USA on graduate and undergraduate business students taking human resource management (HRM) classes. This research was conducted in the…

  3. 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…

  4. 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.

  5. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators of use in cancer therapy

    NASA Astrophysics Data System (ADS)

    García-Pareja, S.; Vilches, M.; Lallena, A. M.

    2010-01-01

    The Monte Carlo simulation of clinical electron linear accelerators requires large computation times to achieve the level of uncertainty required for radiotherapy. In this context, variance reduction techniques play a fundamental role in the reduction of this computational time. Here we describe the use of the ant colony method to control the application of two variance reduction techniques: Splitting and Russian roulette. The approach can be applied to any accelerator in a straightforward way and permits the increasing of the efficiency of the simulation by a factor larger than 50.

  6. Measurement of plutonium and other actinide elements at the center for accelerator mass spectrometry: a comparative assessments of competing techniques

    SciTech Connect

    Hamilton, T H; McAninch, J

    1999-02-01

    initiatives. One potential measurement technique for meeting these requirements is accelerator mass spectrometry (AMS). AMS is a widely accepted analytical technique for measurement of isotopes such as 14 C, 26 Al, 36 Cl (Vogel et al., 1995) but has only recently been demonstrated for the quantitative detection of actinides (Fifield et al., 1996). The Center for Accelerator Mass Spectrometry (CAMS) at the Lawrence Livermore National Laboratory (LLNL) operates the most versatile and most productive AMS instrument in the world (Roberts et al., 1996). The addition of a Heavy Ion Beamline and associated hardware for actinide detection are in an advanced stage of development. Detection limits for actinide elements are expected to be on the order of 1 ´ 10 6 atoms (~0.5 fg) or lower with an initial measurement capacity of a few hundred samples per year. The ultimate detection sensitivity is expected to be ~1 ´ 10 5 atoms. Here we provide a review of non-conventional measurement techniquesÑincluding AMSÑfor the determination of low-levels of 239 Pu and other actinide elements in environmental samples. We include a discussion of potential measurement interferences and sample preparation requirements for the different techniques, and outline our proposed AMS system design and strategic approach for the development of low-level actinide detection capability at CAMS.

  7. 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…

  8. 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…

  9. 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

  10. TDCS guided using fMRI significantly accelerates learning to identify concealed objects.

    PubMed

    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

    2012-01-01

    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 functional magnetic resonance imaging (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 min 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

  11. Three machine learning techniques for automatic determination of rules to control locomotion.

    PubMed

    Jonić, S; Janković, T; Gajić, V; Popović, D

    1999-03-01

    Automatic prediction of gait events (e.g., heel contact, flat foot, initiation of the swing, etc.) and corresponding profiles of the activations of muscles is important for real-time control of locomotion. This paper presents three supervised machine learning (ML) techniques for prediction of the activation patterns of muscles and sensory data, based on the history of sensory data, for walking assisted by a functional electrical stimulation (FES). Those ML's are: 1) a multilayer perceptron with Levenberg-Marquardt modification of backpropagation learning algorithm; 2) an adaptive-network-based fuzzy inference system (ANFIS); and 3) a combination of an entropy minimization type of inductive learning (IL) technique and a radial basis function (RBF) type of artificial neural network with orthogonal least squares learning algorithm. Here we show the prediction of the activation of the knee flexor muscles and the knee joint angle for seven consecutive strides based on the history of the knee joint angle and the ground reaction forces. The data used for training and testing of ML's was obtained from a simulation of walking assisted with an FES system [39]. The ability of generating rules for an FES controller was selected as the most important criterion when comparing the ML's. Other criteria such as generalization of results, computational complexity, and learning rate were also considered. The minimal number of rules and the most explicit and comprehensible rules were obtained by ANFIS. The best generalization was obtained by the IL and RBF network. PMID:10097465

  12. Acceleration of reinforcement learning by policy evaluation using nonstationary iterative method.

    PubMed

    Senda, Kei; Hattori, Suguru; Hishinuma, Toru; Kohda, Takehisa

    2014-12-01

    Typical methods for solving reinforcement learning problems iterate two steps, policy evaluation and policy improvement. This paper proposes algorithms for the policy evaluation to improve learning efficiency. The proposed algorithms are based on the Krylov Subspace Method (KSM), which is a nonstationary iterative method. The algorithms based on KSM are tens to hundreds times more efficient than existing algorithms based on the stationary iterative methods. Algorithms based on KSM are far more efficient than they have been generally expected. This paper clarifies what makes algorithms based on KSM makes more efficient with numerical examples and theoretical discussions. PMID:24733037

  13. 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…

  14. 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…

  15. 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,…

  16. 76 FR 50224 - Medicare Program; Accountable Care Organization Accelerated Development Learning Sessions; Center...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-12

    ... Federal Register (76 FR 28988). Each participating team should consist of two to four senior-level leaders... the opportunity to learn about core functions of an ACO and ways to build their organization's... at https://acoregister.rti.org/ . Click on ``contact us'' to send questions or comments via...

  17. 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 including the…

  18. 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.

  19. Identification and Comparison of Academic Self Regulatory Learning Strategy Use of Students Enrolled in Traditional and Accelerated Baccalaureate Degree Nursing Programs

    ERIC Educational Resources Information Center

    Mullen, Patricia A.

    2009-01-01

    Objective: To explore and compare the use of metacognitive, cognitive, and environmental resource management self regulatory learning (SRL) strategies used by a national sample of students enrolled in traditional and accelerated baccalaureate nursing programs. Background: Learner focused reforms in nursing education require students to assume more…

  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. PMID:26346558

  2. 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

  3. 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…

  4. 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.

  5. Hardware Accelerator for Run-Time Learning Adopted in Object Recognition with Cascade Particle Filter

    NASA Astrophysics Data System (ADS)

    Sugano, Hiroki; Ochi, Hiroyuki; Nakamura, Yukihiro; Miyamoto, Ryusuke

    Recently, many researchers tackle accurate object recognition algorithms and many algorithms are proposed. However, these algorithms have some problems caused by variety of real environments such as a direction change of the object or its shading change. The new tracking algorithm, Cascade Particle Filter, is proposed to fill such demands in real environments by constructing the object model while tracking the objects. We have been investigating to implement accurate object recognition on embedded systems in real-time. In order to apply the Cascade Particle Filter to embedded applications such as surveillance, automotives, and robotics, a hardware accelerator is indispensable because of limitations in power consumption. In this paper we propose a hardware implementation of the Discrete AdaBoost algorithm that is the most computationally intensive part of the Cascade Particle Filter. To implement the proposed hardware, we use PICO Express, a high level synthesis tool provided by Synfora, for rapid prototyping. Implementation result shows that the synthesized hardware has 1, 132, 038 transistors and the die area is 2,195µm × 1,985µm under a 0.180µm library. The simulation result shows that total processing time is about 8.2 milliseconds at 65MHz operation frequency.

  6. 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…

  7. 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…

  8. 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…

  9. 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.

  10. 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.

  11. Detection of blue-white veil areas in dermoscopy images using machine learning techniques

    NASA Astrophysics Data System (ADS)

    Celebi, M. E.; Kingravi, Hassan A.; Aslandogan, Y. A.; Stoecker, William V.

    2006-03-01

    As a result of the advances in skin imaging technology and the development of suitable image processing techniques, during the last decade, there has been a significant increase of interest in the computer-aided diagnosis of skin cancer. Dermoscopy is a non-invasive skin imaging technique which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the useful features in dermoscopic diagnosis is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white "ground-glass" film) which is mostly associated with invasive melanoma. In this preliminary study, a machine learning approach to the detection of blue-white veil areas in dermoscopy images is presented. The method involves pixel classification based on relative and absolute color features using a decision tree classifier. Promising results were obtained on a set of 224 dermoscopy images.

  12. Using synchrotron light to accelerate EUV resist and mask materials learning

    NASA Astrophysics Data System (ADS)

    Naulleau, Patrick; Anderson, Christopher N.; Baclea-an, Lorie-Mae; Denham, Paul; George, Simi; Goldberg, Kenneth A.; Jones, Gideon; McClinton, Brittany; Miyakawa, Ryan; Mochi, Iacopo; Montgomery, Warren; Rekawa, Seno; Wallow, Tom

    2011-03-01

    As commercialization of extreme ultraviolet lithography (EUVL) progresses, direct industry activities are being focused on near term concerns. The question of long term extendibility of EUVL, however, remains crucial given the magnitude of the investments yet required to make EUVL a reality. Extendibility questions are best addressed using advanced research tools such as the SEMATECH Berkeley microfield exposure tool (MET) and actinic inspection tool (AIT). Utilizing Lawrence Berkeley National Laboratory's Advanced Light Source facility as the light source, these tools benefit from the unique properties of synchrotron light enabling research at nodes generations ahead of what is possible with commercial tools. The MET for example uses extremely bright undulator radiation to enable a lossless fully programmable coherence illuminator. Using such a system, resolution enhancing illuminations achieving k1 factors of 0.25 can readily be attained. Given the MET numerical aperture of 0.3, this translates to an ultimate resolution capability of 12 nm. Using such methods, the SEMATECH Berkeley MET has demonstrated resolution in resist to 16-nm half pitch and below in an imageable spin-on hard mask. At a half pitch of 16 nm, this material achieves a line-edge roughness of 2 nm with a correlation length of 6 nm. These new results demonstrate that the observed stall in ultimate resolution progress in chemically amplified resists is a materials issue rather than a tool limitation. With a resolution limit of 20-22 nm, the CAR champion from 2008 remains as the highest performing CAR tested to date. To enable continued advanced learning in EUV resists, SEMATECH has initiated a plan to implement a 0.5 NA microfield tool at the Advanced Light Source synchrotron facility. This tool will be capable of printing down to 8-nm half pitch.

  13. Applications of Machine Learning Techniques in Digital Processing of Images of the Martian Surface

    NASA Astrophysics Data System (ADS)

    Plesko, Catherine S.; Brumby, Steven P.; Armstrong, John C.; Ginder, Elliot A.; Leovy, Conway B.

    2002-11-01

    NASA spacecraft have now returned many thousands of images of the surface of Mars. It is no longer practical to analyze such a large dataset by hand, while the development of handwritten feature extraction tools is expensive and laborious. This project investigates the application of machine learning techniques to problems of feature extraction and digital image processing within the Mars dataset. The Los Alamos GENIE machine learning software system uses a genetic algorithm to assemble feature extraction tools from low-level image operators. Each generated tool is evaluated against training data provided by the user. The best tools in each generation are allowed to "reproduce" to produce the next generation, and the population of tools evolves until it converges to a solution or reaches a level of performance specified by the user. Craters are one of the most scientifically interesting and most numerous features on Mars, and present a wide range of shapes at many spatial scales. We now describe results on development of crater finder algorithms using voting sets of simple classifiers evolved by a machine learning/genetic programming system (the Los Alamos GENIE software).

  14. 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.

  15. 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…

  16. 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…

  17. 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

  18. 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…

  19. Comparison of Machine Learning Techniques for Estimating the Power Consumption ofHousehold Electric Appliances

    NASA Astrophysics Data System (ADS)

    Murata, Hiroshi; Onoda, Takashi; Yoshimoto, Katsuhisa; Nakano, Yukio

    A non-intrusive monitoring system estimates the behavior of individual electric appliances from the measurement of the total household load demand curve. The total load demand curve is measured at the entrance of the power line into the house. The power consumption of individual appliances can be estimated using several machine learning techniques by analyzing the characteristic frequency contents from the load curve of the hosehold. In this paper, we present results of applying several regression methods such as multi-layered perceptrons (MLP), radial basis function networks (RBFN) and Support Vector regressors (SVR) to estimate the power consumption of an air conditioner. Our experiments show RBFN can achieve the best accuracy for the non-intrusive monitoring system.

  20. 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. PMID:24701205

  1. 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. PMID:24480157

  2. 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

  3. 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

  4. A Comparative Study in Learning Curves of Two Different Intracorporeal Knot Tying Techniques

    PubMed Central

    Thiyagarajan, Manuneethimaran; Ravindrakumar, Chandru

    2016-01-01

    Objectives. In our study we are aiming to analyse the learning curves in our surgical trainees by using two standard methods of intracorporeal knot tying. Material and Method. Two randomized groups of trainees are trained with two different intracorporeal knot tying techniques (loop and winding) by single surgeon for eight sessions. In each session participants were allowed to make as many numbers of knots in thirty minutes. The duration for each set of knots and the number of knots for each session were calculated. At the end each session, participants were asked about their frustration level, difficulty in making knot, and dexterity. Results. In winding method the number of knots tied was increasing significantly in each session with less frustration and less difficulty level. Discussion. The suturing and knotting skill improved in every session in both groups. But group B (winding method) trainees made significantly higher number of knots and they took less time for each set of knots than group A (loop method). Although both knotting methods are standard methods, the learning curve is better in loop method. Conclusion. The winding method of knotting is simpler and easier to perform, especially for the surgeons who have limited laparoscopic experience. PMID:27022482

  5. Robotic Transperitoneal Infrarenal Para-Aortic Lymphadenectomy With Double Docking: Technique, Learning Curve, and Perioperative Outcomes.

    PubMed

    Ponce, Jordi; Barahona, Marc; Pla, Maria Jesus; Rovira, Jordi; Garcia-Tejedor, Amparo; Gil-Ibanez, Blanca; Gaspar, Hugo Manuel; Sabria, Enric; Bartolomé, Carlos; Marti, Lola

    2016-01-01

    Para-aortic lymphadenectomy (PAL) is a challenging procedure performed by minimally invasive surgery in very few centers, owing to its intrinsic technical complexity. We describe and assess the feasibility and learning curve of robotic double-docking transperitoneal infrarenal PAL combined with oncological pelvic surgery. Fifty patients who underwent this procedure using the Da Vinci S surgical system between March 2010 and May 2013 were included. The mean operating time for PAL surgery was 76 minutes (range, 32-150 minutes), and the mean number of lymph nodes per patient was 11.8 (range, 1-44). There were no conversions to laparotomy or laparoscopy. The mean length of hospital stay was 2 days (range, 1-25 days). Statistically significant decreases were noted for mean table rotation time (17 ± 6.8 minutes vs 13 ± 3.6 minutes; p = .02) and mean PAL operating time (85.4 ± 25.8 minutes vs 69.8 ± 24.6 minutes; p = .04) when comparing the first 20 patients and the last 30 patients. The number of nodes was similar in the first 20 patients and last 30 patients. The double-docking transperitoneal infrarenal PAL technique combined with oncological pelvic surgery is feasible, with minimal morbidity and a short learning curve. PMID:26898894

  6. 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

  7. Investigating machine learning techniques for MRI-based classification of brain neoplasms

    PubMed Central

    Kanas, Vasileios G.; Davatzikos, Christos

    2015-01-01

    Purpose Diagnosis and characterization of brain neoplasms appears of utmost importance for therapeutic management. The emerging of imaging techniques, such as Magnetic Resonance (MR) imaging, gives insight into pathology, while the combination of several sequences from conventional and advanced protocols (such as perfusion imaging) increases the diagnostic information. To optimally combine the multiple sources and summarize the information into a distinctive set of variables however remains difficult. The purpose of this study is to investigate machine learning algorithms that automatically identify the relevant attributes and are optimal for brain tumor differentiation. Methods Different machine learning techniques are studied for brain tumor classification based on attributes extracted from conventional and perfusion MRI. The attributes, calculated from neoplastic, necrotic, and edematous regions of interest, include shape and intensity characteristics. Attributes subset selection is performed aiming to remove redundant attributes using two filtering methods and a wrapper approach, in combination with three different search algorithms (Best First, Greedy Stepwise and Scatter). The classification frameworks are implemented using the WEKA software. Results The highest average classification accuracy assessed by leave-one-out (LOO) cross-validation on 101 brain neoplasms was achieved using the wrapper evaluator in combination with the Best First search algorithm and the KNN classifier and reached 96.9% when discriminating metastases from gliomas and 94.5% when discriminating high-grade from low-grade neoplasms. Conclusions A computer-assisted classification framework is developed and used for differential diagnosis of brain neoplasms based on MRI. The framework can achieve higher accuracy than most reported studies using MRI. PMID:21516321

  8. 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.

  9. 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.

  10. 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…

  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. A Novel Semi-Supervised Electronic Nose Learning Technique: M-Training.

    PubMed

    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

  13. 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…

  14. A First Look at Creating Mock Catalogs with Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Xu, Xiaoying; Ho, Shirley; Trac, Hy; Schneider, Jeff; Poczos, Barnabas; Ntampaka, Michelle

    2013-08-01

    We investigate machine learning (ML) techniques for predicting the number of galaxies (N 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 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 gal by training our algorithms on the following six halo properties: number of particles, M 200, σ v , v max, half-mass radius, and spin. For Millennium, our predicted N gal values have a mean-squared error (MSE) of ~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 ~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 gal. Lastly, we investigate these ML-based approaches in making mock catalogs for different galaxy subpopulations (e.g., blue, red, high M star, low M 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. 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.

  16. [Determination of diflubenzuron and triflumuron residues in greasy wool by accelerated solvent extraction technique and high performance liquid chromatography].

    PubMed

    Fan, Yuanmu; Huang, Shaotang; Yu, Xuejun; Gu, Xiaojun; Qiu, Yajun; Chen, Shubing; Fang, Keteng; Chen, Jun

    2009-07-01

    A method for the determination of diflubenzuron and triflumuron residues in greasy wool was developed by high performance liquid chromatography (HPLC) coupled with accelerated solvent extraction (ASE). The diflubenzuron and triflumuron residues were extracted with acetonitrile saturated with n-hexane at 80 degrees C and 10.34 MPa. The extract was pretreated by a series of procedures such as freezing-lipid filtration, concentration and purification by solid-phase extraction prior to the determination with HPLC. The target analytes were separated on a Waters Atlants dC18 column (250 mm x 4.6 mm, 5 microm), gradiently eluted with acetonitrile and water as the mobile phases and detected by a photodiode array detector (DAD) at 254 nm. The linear ranges were 0.1 - 10.0 mg/L. There were good linearity between the peak areas and concentrations in the linear range for the analytes, and the correlation coefficients of diflubenzuron and triflumuron were higher than 0.9999. The limits of quantification for diflubenzuron and triflumuron were 0.05 and 0.04 mg/kg (S/N > or = 10), respectively. The method is simple, rapid, sensitive and suitable for preliminary screening of diflubenzuron and triflumuron residues in greasy wool. PMID:19938504

  17. 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. PMID:26838409

  18. 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.

  19. 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. PMID:18319369

  20. Lighting the Way for Learning: A Teacher's Handbook of Practical Approaches and Techniques for Oral-Graphic Symbolic Language Acquirement.

    ERIC Educational Resources Information Center

    McGahan, F. E.; McGahan, Carolyn

    Language consists of symbols written, spoken, or thought about things, places, or feelings seen or unseen. Any block, interference, or impasse to the acquirement of symbolic language can result in a learning disability. Oral language must precede the graphic. The purpose of this handbook is to suggest practical approaches and techniques which will…

  1. 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…

  2. 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…

  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. Headspace Theater: An Innovative Method for Experiential Learning of Psychiatric Symptomatology Using Modified Role-Playing and Improvisational Theater Techniques

    ERIC Educational Resources Information Center

    Ballon, Bruce C.; Silver, Ivan; Fidler, Donald

    2007-01-01

    Objective: Headspace Theater has been developed to allow small group learning of psychiatric conditions by creating role-play situations in which participants are placed in a scenario that simulates the experience of the condition. Method: The authors conducted a literature review of role-playing techniques, interactive teaching, and experiential…

  6. Documenting Experiential Learning: Preparation of a Portfolio for College Credit. TECHNIQUES.

    ERIC Educational Resources Information Center

    Rolls, Dorothea M.

    1987-01-01

    Increasing numbers of colleges and universities are responding to the needs of adults seeking professional training and have come to recognize the value of experiential learning. One method of assessing previous learning is to prepare a portfolio with documentation of life experiences as they related to the learning process. The East Central…

  7. 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…

  8. 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…

  9. 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.

  10. 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. PMID:22287230

  11. Machine-learning techniques for geochemical discrimination of 2011 Tohoku tsunami deposits

    NASA Astrophysics Data System (ADS)

    Kuwatani, Tatsu; Nagata, Kenji; Okada, Masato; Watanabe, Takahiro; Ogawa, Yasumasa; Komai, Takeshi; Tsuchiya, Noriyoshi

    2014-11-01

    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.

  12. 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.

  13. Machine-learning techniques for geochemical discrimination of 2011 Tohoku tsunami deposits.

    PubMed

    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 (= 2(18)) 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

  14. Estimation of seismic building structural types using multi-sensor remote sensing and machine learning techniques

    NASA Astrophysics Data System (ADS)

    Geiß, Christian; Aravena Pelizari, Patrick; Marconcini, Mattia; Sengara, Wayan; Edwards, Mark; Lakes, Tobia; Taubenböck, Hannes

    2015-06-01

    Detailed information about seismic building structural types (SBSTs) is crucial for accurate earthquake vulnerability and risk modeling as it reflects the main load-bearing structures of buildings and, thus, the behavior under seismic load. However, for numerous urban areas in earthquake prone regions this information is mostly outdated, unavailable, or simply not existent. To this purpose, we present an effective approach to estimate SBSTs by combining scarce in situ observations, multi-sensor remote sensing data and machine learning techniques. In particular, an approach is introduced, which deploys a sequential procedure comprising five main steps, namely calculation of features from remote sensing data, feature selection, outlier detection, generation of synthetic samples, and supervised classification under consideration of both Support Vector Machines and Random Forests. Experimental results obtained for a representative study area, including large parts of the city of Padang (Indonesia), assess the capabilities of the presented approach and confirm its great potential for a reliable area-wide estimation of SBSTs and an effective earthquake loss modeling based on remote sensing, which should be further explored in future research activities.

  15. 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.

  16. 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. PMID:20688192

  17. 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. PMID:23320948

  18. 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

  19. 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.

  20. 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. PMID:8985539

  1. 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…

  2. A dosimetry technique for measuring kilovoltage cone-beam CT dose on a linear accelerator using radiotherapy equipment.

    PubMed

    Scandurra, Daniel; Lawford, Catherine E

    2014-01-01

    This work develops a technique for kilovoltage cone-beam CT (CBCT) dosimetry that incorporates both point dose and integral dose in the form of dose length product, and uses readily available radiotherapy equipment. The dose from imaging protocols for a range of imaging parameters and treatment sites was evaluated. Conventional CT dosimetry using 100 mm long pencil chambers has been shown to be inadequate for the large fields in CBCT and has been replaced in this work by a combination of point dose and integral dose. Absolute dose measurements were made with a small volume ion chamber at the central slice of a radiotherapy phantom. Beam profiles were measured using a linear diode array large enough to capture the entire imaging field. These profiles were normalized to absolute dose to form dose line integrals, which were then weighted with radial depth to form the DLPCBCT. This metric is analogous to the standard dose length product (DLP), but derived differently to suit the unique properties of CBCT. Imaging protocols for head and neck, chest, and prostate sites delivered absolute doses of 0.9, 2.2, and 2.9 cGy to the center of the phantom, and DLPCBCT of 28.2, 665.1, and 565.3mGy.cm, respectively. Results are displayed as dose per 100 mAs and as a function of key imaging parameters such as kVp, mAs, and collimator selection in a summary table. DLPCBCT was found to correlate closely with the dimension of the imaging region and provided a good indication of integral dose. It is important to assess integral dose when determining radiation doses to patients using CBCT. By incorporating measured beam profiles and DLP, this technique provides a CBCT dosimetry in radiotherapy phantoms and allows the prediction of imaging dose for new CBCT protocols. PMID:25207398

  3. 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

  4. 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.

  5. 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

  6. Vascular surgery trainees still need to learn how to sew: importance of learning surgical techniques in the era of endovascular surgery.

    PubMed

    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. 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. PMID:24628063

  8. 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.

  9. Linear Accelerators

    SciTech Connect

    Sidorin, Anatoly

    2010-01-05

    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.

  10. 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…

  11. 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…

  12. "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…

  13. 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

  14. 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.

  15. Basis for Cumulative Cultural Evolution in Chimpanzees: Social Learning of a More Efficient Tool-Use Technique

    PubMed Central

    Yamamoto, Shinya; Humle, Tatyana; Tanaka, Masayuki

    2013-01-01

    Background The evidence for culture in non-human animals has been growing incrementally over the past two decades. However, the ability for cumulative cultural evolution, with successive generations building on earlier achievements, in non-human animals remains debated. Faithful social learning of incremental improvements in technique is considered to be a defining feature of human culture, differentiating human from non-human cultures. This study presents the first experimental evidence for chimpanzees' social transmission of a more efficient tool-use technique invented by a conspecific group member. Methodology/Principal Findings The chimpanzees were provided with a straw-tube, and spontaneously demonstrated two different techniques in obtaining juice through a small hole: “dipping” and “straw-sucking”. Both the “dipping” and “straw-sucking” techniques depended on the use of the same tool (straw-tube) for the same target (juice) accessible from exactly the same location (small hole 1 cm in diameter). Therefore the difference between “dipping” and “straw-sucking” was only in “technique”. Although the two techniques differed significantly in their efficiency, their cognitive and perceptuo-motor complexity were comparable. All five chimpanzees who initially performed the “dipping” technique switched to using the more efficient “straw-sucking” technique upon observing a conspecific or human demonstrate the more proficient alternate “straw-sucking” technique. Conclusions/Significance The social learning mechanism involved here was clearly not local or stimulus enhancement, but imitation or emulation of a tool-use technique. When there is no biologically relevant difference in cognitive or perceptuo-motor complexity between two techniques, and when chimpanzees are dissatisfied with their own technique, chimpanzees may socially learn an improved technique upon close observation of a proficient demonstrator. This study provides

  16. Change detection of medical images using dictionary learning techniques and PCA

    NASA Astrophysics Data System (ADS)

    Nika, Varvara; Babyn, Paul; Zhu, Hongmei

    2014-03-01

    Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of MRI scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. In this paper we present the Eigen-Block Change Detection algorithm (EigenBlockCD). It performs local registration and identifies the changes between consecutive MR images of the brain. Blocks of pixels from baseline scan are used to train local dictionaries that are then used to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between L1 and L2 norms as two possible similarity measures in the EigenBlockCD. We show the advantages of L2 norm over L1 norm theoretically and numerically. We also demonstrate the performance of the EigenBlockCD algorithm for detecting changes of MR images and compare our results with those provided in recent literature. Experimental results with both simulated and real MRI scans show that the EigenBlockCD outperforms the previous methods. It detects clinical changes while ignoring the changes due to patient's position and other acquisition artifacts.

  17. 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

  18. Education techniques for lifelong learning: giving a PowerPoint presentation: the art of communicating effectively.

    PubMed

    Collins, Jannette

    2004-01-01

    Effectiveness of an oral presentation depends on the ability of the speaker to communicate with the audience. An important part of this communication is focusing on two to five key points and emphasizing those points during the presentation. Every aspect of the presentation should be purposeful and directed at facilitating learners' achievement of the objectives. This necessitates that the speaker has carefully developed the objectives and built the presentation around attainment of the objectives. The best presentations are rehearsed, not so that the speaker memorizes exactly what he or she will say, but to facilitate the speaker's ability to interact with the audience and portray a relaxed, professional, and confident demeanor. Rehearsal also helps alleviate stage fright. The most useful method of controlling nervousness is to visualize success. When showing images, it is important to orient the audience with an adequate description, point out the relevant findings, and allow enough time for the audience to assimilate the information before moving on. This can be facilitated with appropriate use of a laser pointer, cursor, or use of builds and transitioning. A presentation should be designed to include as much audience participation as possible, no matter the size of the audience. Techniques to encourage audience participation include questioning, brainstorming, small-group activities, role-playing, case-based examples, and directed listening. It is first necessary to motivate and gain attention of the learner for learning to take place. This can be accomplished through appropriate use of humor, anecdotes, and quotations. Attention should be given to posture, body movement, eye contact, and voice when speaking, as how one appears to the audience will have an impact on their reaction to what is presented. PMID:15256638

  19. Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators.

    PubMed

    Figuera, Carlos; 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

  20. 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.

  1. 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…

  2. 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,…

  3. 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 setting, under…

  4. 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…

  5. 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…

  6. 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…

  7. Using Software Testing Techniques for Efficient Handling of Programming Exercises in an e-Learning Platform

    ERIC Educational Resources Information Center

    Schwieren, Joachim; Vossen, Gottfried; Westerkamp, Peter

    2006-01-01

    e-Learning has become a major field of interest in recent years, and multiple approaches and solutions have been developed. A typical form of e-learning application comprises exercise submission and assessment systems that allow students to work on assignments whenever and where they want (i.e., dislocated, asynchronous work). In basic computer…

  8. 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…

  9. 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

  10. Hypofractionated Accelerated Radiotherapy Using Concomitant Intensity-Modulated Radiotherapy Boost Technique for Localized High-Risk Prostate Cancer: Acute Toxicity Results

    SciTech Connect

    Lim, Tee S.; Cheung, Patrick Loblaw, D. Andrew; Morton, Gerard; Sixel, Katharina E.; Pang, Geordi; Basran, Parminder; Zhang Liying; Tirona, Romeo; Szumacher, Ewa; Danjoux, Cyril; Choo, Richard; Thomas, Gillian

    2008-09-01

    Purpose: To evaluate the acute toxicities of hypofractionated accelerated radiotherapy (RT) using a concomitant intensity-modulated RT boost in conjunction with elective pelvic nodal irradiation for high-risk prostate cancer. Methods and Materials: This report focused on 66 patients entered into this prospective Phase I study. The eligible patients had clinically localized prostate cancer with at least one of the following high-risk features (Stage T3, Gleason score {>=}8, or prostate-specific antigen level >20 ng/mL). Patients were treated with 45 Gy in 25 fractions to the pelvic lymph nodes using a conventional four-field technique. A concomitant intensity-modulated radiotherapy boost of 22.5 Gy in 25 fractions was delivered to the prostate. Thus, the prostate received 67.5 Gy in 25 fractions within 5 weeks. Next, the patients underwent 3 years of adjuvant androgen ablative therapy. Acute toxicities were assessed using the Common Terminology Criteria for Adverse Events, version 3.0, weekly during treatment and at 3 months after RT. Results: The median patient age was 71 years. The median pretreatment prostate-specific antigen level and Gleason score was 18.7 ng/L and 8, respectively. Grade 1-2 genitourinary and gastrointestinal toxicities were common during RT but most had settled at 3 months after treatment. Only 5 patients had acute Grade 3 genitourinary toxicity, in the form of urinary incontinence (n = 1), urinary frequency/urgency (n = 3), and urinary retention (n = 1). None of the patients developed Grade 3 or greater gastrointestinal or Grade 4 or greater genitourinary toxicity. Conclusion: The results of the present study have indicated that hypofractionated accelerated RT with a concomitant intensity-modulated RT boost and pelvic nodal irradiation is feasible with acceptable acute toxicity.

  11. Fast perspective volume ray casting method using GPU-based acceleration techniques for translucency rendering in 3D endoluminal CT colonography.

    PubMed

    Lee, Taek-Hee; Lee, Jeongjin; Lee, Ho; Kye, Heewon; Shin, Yeong Gil; Kim, Soo Hong

    2009-08-01

    Recent advances in graphics processing unit (GPU) have enabled direct volume rendering at interactive rates. However, although perspective volume rendering for opaque isosurface is rapidly performed using conventional GPU-based method, perspective volume rendering for non-opaque volume such as translucency rendering is still slow. In this paper, we propose an efficient GPU-based acceleration technique of fast perspective volume ray casting for translucency rendering in computed tomography (CT) colonography. The empty space searching step is separated from the shading and compositing steps, and they are divided into separate processing passes in the GPU. Using this multi-pass acceleration, empty space leaping is performed exactly at the voxel level rather than at the block level, so that the efficiency of empty space leaping is maximized for colon data set, which has many curved or narrow regions. In addition, the numbers of shading and compositing steps are fixed, and additional empty space leapings between colon walls are performed to increase computational efficiency further near the haustral folds. Experiments were performed to illustrate the efficiency of the proposed scheme compared with the conventional GPU-based method, which has been known to be the fastest algorithm. The experimental results showed that the rendering speed of our method was 7.72fps for translucency rendering of 1024x1024 colonoscopy image, which was about 3.54 times faster than that of the conventional method. Since our method performed the fully optimized empty space leaping for any kind of colon inner shapes, the frame-rate variations of our method were about two times smaller than that of the conventional method to guarantee smooth navigation. The proposed method could be successfully applied to help diagnose colon cancer using translucency rendering in virtual colonoscopy. PMID:19541296

  12. Neural Networks for Modeling and Control of Particle Accelerators

    DOE PAGESBeta

    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,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. 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)

  14. Test Retakes by Groups of Students as a Technique to Enhance Learning.

    ERIC Educational Resources Information Center

    Bacon, R. K.; Beyrouty, C. A.

    1988-01-01

    Reviewed is research which supports retesting students to enhance learning. Evaluation results, materials and methods used to implement the procedure are described. Included are tables on student responses concerning involved groups and the value and benefits of retakes. (RT)

  15. 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.

  16. 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. PMID:15360935

  17. Accelerating into the future

    NASA Astrophysics Data System (ADS)

    Murray, Cherry

    2009-05-01

    Accelerator science has traditionally been associated with high-energy physics and nuclear physics. But the use of accelerators in other areas of science, as well as in medicine and industry, is steadily growing. Accelerators are now, for example, used to treat cancer using proton therapy, which can deposit radiation onto a tumour while causing much less damage to surrounding healthy tissue than with other treatment techniques.

  18. Impact of changing trends in technique and learning curve on outcome of hypospadias repair: An experience from tertiary care center

    PubMed Central

    Ansari, M. S.; Agarwal, Shikhar; Sureka, Sanjoy Kumar; Mandhani, Anil; Kapoor, Rakesh; Srivastava, Aneesh

    2016-01-01

    Introduction: Apart from numerous clinical factors, surgical experience and technique are important determinants of hypospadias repair outcome. This study was aimed to evaluate the learning curve of hypospadias repair and the impact of changing trends in surgical techniques on the success of primary hypospadias repair. Materials and Methods: We retrospectively analyzed of data of 324 patients who underwent primary repair of hypospadias between January 1997 and December 2013 at our center. During the initial 8 years, repairs were performed by multiple 5 different urologists. From 2005 onwards, all procedures were performed by a single urologist. The study cohorts was categorized into three groups; Group I, surgeries performed between 1997–2004 by multiple surgeons, Group II, between 2005–2006 during the initial learning curve of a single surgeon, and Group III, from 2007 onwards after completion of the learning curve of the single surgeon. The groups were compared in respect to surgical techniques, overall success and complications. Results: Overall 296 patients fulfilled the inclusion criterion, 93 (31.4%), 50 (16.9%), and 153 (51.7%) in Group I, II, and III, respectively. Overall success was achieved in 60 (64.5%), 32 (64%), and 128 (83.7%) patients among the three groups respectively (P < 0.01). Nineteen (20.4%), 20 (40%), and 96 (62.7%) patients underwent tubularized incised plate repair in Group I, II, and III, with successful outcome in 12 (63.2%), 15 (75%), and 91 (94.8%) patients, respectively (P < 0.01). The most common complication among all groups was urethrocutaneous fistula, 20 (21.5%) in Group I, 11 (22%) in Group II, and 17 (11.1%) in Group III. Conclusion: There is a learning curve for attaining surgical skills in hypospadias surgery. Surgeons dedicated for this surgery provide better results. Tubularized incised plate urethroplasty appear promising in both distal and proximal type hypospadias. PMID:27555680

  19. 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.

  20. Ultrasound techniques in the evaluation of the mediastinum, part 2: mediastinal lymph node anatomy and diagnostic reach of ultrasound techniques, clinical work up of neoplastic and inflammatory mediastinal lymphadenopathy using ultrasound techniques and how to learn mediastinal endosonography

    PubMed Central

    Jenssen, Christian; Annema, Jouke Tabe; Clementsen, Paul; Cui, Xin-Wu; Borst, Mathias Maximilian

    2015-01-01

    Ultrasound imaging has gained importance in pulmonary medicine over the last decades including conventional transcutaneous ultrasound (TUS), endoscopic ultrasound (EUS), and endobronchial ultrasound (EBUS). Mediastinal lymph node (MLN) staging affects the management of patients with both operable and inoperable lung cancer (e.g., surgery vs. combined chemoradiation therapy). Tissue sampling is often indicated for accurate nodal staging. Recent international lung cancer staging guidelines clearly state that endosonography should be the initial tissue sampling test over surgical staging. Mediastinal nodes can be sampled from the airways [endobronchial ultrasound combined with transbronchial needle aspiration (EBUS-TBNA)] or the esophagus [endoscopic ultrasound fine needle aspiration (EUS-FNA)]. EBUS and EUS have a complementary diagnostic yield and in combination virtually all MLNs can be biopsied. Additionally endosonography has an excellent yield in assessing granulomas in patients suspected of sarcoidosis. The aim of this review in two integrative parts is to discuss the current role and future perspectives of all ultrasound techniques available for the evaluation of mediastinal lymphadenopathy and mediastinal staging of lung cancer. A specific emphasis will be on learning mediastinal endosonography. Part 1 deals with an introduction into ultrasound techniques, MLN anatomy and diagnostic reach of ultrasound techniques and part 2 with the clinical work up of neoplastic and inflammatory mediastinal lymphadenopathy using ultrasound techniques and how to learn mediastinal endosonography. PMID:26623120

  1. 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…

  2. 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)…

  3. 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.

  4. 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.

  5. 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…

  6. Combining techniques to reveal emergent effects in infants' segmentation, word learning, and grammar.

    PubMed

    Hollich, George

    2006-01-01

    This paper provides three representative examples that highlight the ways in which procedures can be combined to study interactions across traditional domains of study: segmentation, word learning, and grammar. The first section uses visual familiarization prior to the Headturn Preference Procedure to demonstrate that synchronized visual information aids in speech segmentation in noise. The second section uses audio familiarization prior to the Preferential Looking Procedure to demonstrate that speech perception aids in the learning of meaning. The third section uses visual familiarization prior to the Preferential Looking Procedure to demonstrate that attentional distractions inhibit grammatical understanding. Thus, what infants see affects what they hear. What infants hear affects the words they learn. What infants remember affects the sentences they understand. PMID:16922060

  7. 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)

  8. Accelerator on a Chip

    ScienceCinema

    England, Joel

    2014-07-16

    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)

  9. 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.

  10. 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.

  11. 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…

  12. The Application of Two-Point Touch Cane Technique to Theories of Motor Control and Learning Implications for Orientation and Mobility Training.

    ERIC Educational Resources Information Center

    Croce, Ronald V.; Jacobson, William H.

    1986-01-01

    Basic behavioral processes involved in motor control based on theories of motor control and learning are outlined using the teaching of two-point touch cane technique as an application of the theories. The authors assert the importance of repetition, practice, and sufficient learning time. (Author/CL)

  13. 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…

  14. 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…

  15. 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…

  16. Combining Techniques to Reveal Emergent Effects in Infants' Segmentation, Word Learning, and Grammar

    ERIC Educational Resources Information Center

    Hollich, George

    2006-01-01

    This paper provides three representative examples that highlight the ways in which procedures can be combined to study interactions across traditional domains of study: segmentation, word learning, and grammar. The first section uses visual familiarization prior to the Headturn Preference Procedure to demonstrate that synchronized visual…

  17. Demonstrating a Web-Design Technique in a Distance-Learning Environment

    ERIC Educational Resources Information Center

    Zdenek, Sean

    2004-01-01

    Objective: To lead a brief training session over a distance-learning network. Type of speech: Informative. Point value: 20% of course grade. Requirements: (a) References: Not specified; (b) Length: 15 minutes; (c) Visual aid: Yes; (d) Outline: No; (e) Prerequisite reading: Chapters 12-16, 18 (Bailey, 2002); (f) Additional requirements: None. This…

  18. 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…

  19. Technology in Learning. An Interim Report of the Study Committee on Instructional Aids and Techniques.

    ERIC Educational Resources Information Center

    Ontario Curriculum Inst., Toronto.

    Today's children receive information in relatively unstructured form through communications media which surmount barriers of time and space. In comparison, traditional sequential learning may seem slow and uninteresting. Technological innovation in education would make it possible to place emphasis on student discovery through informative media,…

  20. 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…

  1. 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…

  2. 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…

  3. 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…

  4. Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.

    PubMed

    Zhao, Xiaowei; Ning, Qiao; Chai, Haiting; Ma, Zhiqiang

    2015-06-01

    As a widespread type of protein post-translational modifications (PTMs), succinylation plays an important role in regulating protein conformation, function and physicochemical properties. Compared with the labor-intensive and time-consuming experimental approaches, computational predictions of succinylation sites are much desirable due to their convenient and fast speed. Currently, numerous computational models have been developed to identify PTMs sites through various types of two-class machine learning algorithms. These methods require both positive and negative samples for training. However, designation of the negative samples of PTMs was difficult and if it is not properly done can affect the performance of computational models dramatically. So that in this work, we implemented the first application of positive samples only learning (PSoL) algorithm to succinylation sites prediction problem, which was a special class of semi-supervised machine learning that used positive samples and unlabeled samples to train the model. Meanwhile, we proposed a novel succinylation sites computational predictor called SucPred (succinylation site predictor) by using multiple feature encoding schemes. Promising results were obtained by the SucPred predictor with an accuracy of 88.65% using 5-fold cross validation on the training dataset and an accuracy of 84.40% on the independent testing dataset, which demonstrated that the positive samples only learning algorithm presented here was particularly useful for identification of protein succinylation sites. Besides, the positive samples only learning algorithm can be applied to build predictors for other types of PTMs sites with ease. A web server for predicting succinylation sites was developed and was freely accessible at http://59.73.198.144:8088/SucPred/. PMID:25843215

  5. 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. PMID:26829513

  6. Using Pork Skin as a Practice Medium for Learning Hair Transplantation Techniques.

    PubMed

    Li, Haidong; Song, Tao

    2015-12-01

    A simple technique using pork skin and excess hair and epidermis harvested from anti-wrinkle surgeries was used to practice hair transplantation techniques. This allows inexperienced physicians to practice and perform the traditional steps of hair transplantation without involving an actual patient in the early stages of perfecting technique. The technique uses pork skin during the procedure, while performing real-time hair transplantation simulation. The surgical result of the procedure can then be visualized, and the training process can be repeated at will; peer evaluation is performed after completion. Results showed that residents that practiced this technique scored consistently better than those without the same training background. Every score increased with practice, and the length of time needed to complete the hair transplantation process decreased. A simple technique using pork skin for practicing hair transplantation technique is a valuable training tool, and gives residents a way to practice sound techniques along with more precise anatomical familiarity for hair transplantation surgery, without the risks associated with training on live patients. PMID:26884673

  7. 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…

  8. AN INVESTIGATION OF THE RELATIVE EFFECTIVENESS OF CERTAIN SPECIFIC TV TECHNIQUES ON LEARNING. FINAL REPORT.

    ERIC Educational Resources Information Center

    SCHWARZWALDER, JOHN C.

    GOAL OF THIS STUDY WAS TO ASSESS THE EFFECTS OF CERTAIN AUDITORY AND VISUAL STIMULI PRESENTED BY EDUCATIONAL TV. SPECIFIC QUESTIONS ASKED WHETHER VISUAL REINFORCEMENT, CONTINUITY, AND MANIPULATION TECHNIQUES INCREASE MASTERY OF SCIENCE INFORMATION BY FIFTH GRADERS. 72 TV LESSONS IN 9 AREAS OF SCIENCE, VARYING COMBINATIONS OF THE 3 TECHNIQUES AT…

  9. Traumatic brain injury accelerates amyloid-β deposition and impairs spatial learning in the triple-transgenic mouse model of Alzheimer's disease.

    PubMed

    Shishido, Hajime; Kishimoto, Yasushi; Kawai, Nobuyuki; Toyota, Yasunori; Ueno, Masaki; Kubota, Takashi; Kirino, Yutaka; Tamiya, Takashi

    2016-08-26

    Several pathological and epidemiological studies have demonstrated a possible relationship between traumatic brain injury (TBI) and Alzheimer's disease (AD). However, the exact contribution of TBI to AD onset and progression is unclear. Hence, we examined AD-related histopathological changes and cognitive impairment after TBI in triple transgenic (3×Tg)-AD model mice. Five- to seven-month-old 3×Tg-AD model mice were subjected to either TBI by the weight-drop method or a sham treatment. In the 3×Tg-AD mice subjected to TBI, the spatial learning was not significantly different 7 days after TBI compared to that of the sham-treated 3×Tg-AD mice. However, 28 days after TBI, the 3×Tg-AD mice exhibited significantly lower spatial learning than the sham-treated 3×Tg-AD mice. Correspondingly, while a few amyloid-β (Aβ) plaques were observed in both sham-treated and TBI-treated 3×Tg-AD mouse hippocampus 7 days after TBI, the Aβ deposition was significantly greater in 3×Tg-AD mice 28 days after TBI. Thus, we demonstrated that TBI induced a significant increase in hippocampal Aβ deposition 28 days after TBI compared to that of the control animals, which was associated with worse spatial learning ability in 3×Tg-AD mice. The present study suggests that TBI could be a risk factor for accelerated AD progression, particularly when genetic and hereditary predispositions are involved. PMID:27373531

  10. 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.

  11. 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. PMID:25160253

  12. 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. PMID:18632389

  13. Ability to learn inhaler technique in relation to cognitive scores and tests of praxis in old age

    PubMed Central

    Allen, S; Ragab, S

    2002-01-01

    Clinical observations have shown that some older patients are unable to learn to use a metered dose inhaler (MDI) despite having a normal abbreviated mental test (AMT) score, possibly because of dyspraxia or unrecognised cognitive impairment. Thirty inhaler-naive inpatients (age 76–94) with an AMT score of 8–10 (normal) were studied. Standard MDI training was given and the level of competence reached was scored (inhalation score). A separate observer performed the minimental test (MMT), Barthel index, geriatric depression score (GDS), ideational dyspraxia test (IDT), and ideomotor dyspraxia test (IMD). No correlative or threshold relationship was found between inhalation score and Barthel index, GDS, or IDT. However, a significant correlation was found between inhalation score and IMD (r = 0.45, p = 0.039) and MMT (r = 0.48, p = 0.032) and threshold effects emerged in that no subject with a MMT score of less than 23/30 had an inhalation score of 5/10 or more (adequate technique requires 6/10 or more), and all 17/18 with an inhalation score of 6/10 or more had an IMD of 14/20 or more. The three patients with a MMT >22 and inhalation score <6 had abnormal IMD scores. Inability to learn an adequate inhaler technique in subjects with a normal AMT score appears to be due to unrecognised cognitive impairment or dyspraxia. The MMT is probably a more useful screening test than the AMT score in this context. PMID:11796871

  14. 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

  15. 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.

  16. Permanent prostate brachytherapy: Dosimetric results and analysis of a learning curve with a dynamic dose-feedback technique

    SciTech Connect

    Acher, Peter . E-mail: peter.acher@gstt.nhs.uk; Popert, Rick; Nichol, Janette; Potters, Louis; Morris, Stephen; Beaney, Ronald

    2006-07-01

    Purpose: A permanent prostate brachytherapy (PPB) program utilizing intraoperative inverse-planned dynamic dose-feedback was initiated without prior firsthand experience of alternative techniques. The purpose of this study is to assess the dosimetric learning curve associated with this approach. Methods and Materials: A total of 77 patients underwent PPB implants as monotherapy for localized prostate cancer to a prescription dose of 145 Gy with loose 125I seeds between December 2003 and June 2004. Intraoperative and postoperative dosimetric values, total implanted radioactivity, and operating room (OR) times were compared by sequential case number for all cases. Results: The median intraoperative dosimetric values were: D90 (the minimum dose to 90% of the prostate) = 170 Gy (range, 135-203 Gy), V100 (the volume of the prostate that receives 100% of the prescription dose) = 96% (range, 86-100), V150 = 66% (range, 34-86). Median postoperative dosimetric values were as follows: D90 = 168 Gy (range, 132-197 Gy), V100 = 95% (range, 86-99), V150 = 74% (range, 51-84). Median implanted activity was 0.79 mCi per cubic centimeter of prostate (range, 0.541-1.13). There was no significant correlation by case number on any postoperative dosimetric parameter studied. Door-to-door OR time was reduced from median 138 to 97.5 min per case at the end of the series with a correlation coefficient of -0.76 for the initial 28 cases. Conclusion: Satisfactory dosimetric parameters can be achieved from the outset without a learning curve effect in an appropriately trained environment. The learning curve for dynamic dose-feedback PPB in a clinic naive to other techniques is apparent in terms of OR time.

  17. 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.

  18. 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.

  19. Incorporating Service-Learning, Technology, and Research Supportive Teaching Techniques into the University Chemistry Classroom

    NASA Astrophysics Data System (ADS)

    Saitta, E. K. H.; Bowdon, M. A.; Geiger, C. L.

    2011-12-01

    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 projects allowed UCF students to teach newly acquired content knowledge and build upon course lecture and lab exercises. Activities utilized the web-conferencing tool Adobe Connect Pro to enable interaction with high school students, many of whom have limited access to supplemental educational opportunities due to low socioeconomic status. Seventy chemistry I students created lessons to clarify high school students' misconceptions through the use of refutational texts. In addition, 21 UCF students enrolled in the chemistry II laboratory course acted as virtual lab partners with Crooms students in an interactive guided inquiry experiment focused on chemical kinetics. An overview of project's design, implementation, and assessments are detailed in the case study and serve as a model for future community partnerships. Emerging technologies are emphasized as well as a suggested set of best practices for future projects.

  20. 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…

  1. TELL. Techniques for Effective Language Learning in English as a Second Language.

    ERIC Educational Resources Information Center

    Johnston, Robert S., Ed.; Craig, Ruth Parle, Ed.

    This publication contains a selection of exemplary teaching techniques for instructors of adults in English as a Second Language (ESL). Its scope covers the spectrum of ESL instruction and is designed to assist teachers ranging from the inexperienced to the experienced, without prior inservice orientation. The book contains 202 techniques…

  2. Strategies for Success: Classroom Teaching Techniques for Students with Learning Differences. Second Edition

    ERIC Educational Resources Information Center

    Meltzer, Lynn J.; Roditi, Bethany N.; Steinberg, Joan L.; Rafter Biddle, Kathleen; Taber, Susan E.; Boyle Caron, Kathleen; Kniffin, Leta

    2006-01-01

    Strategies for Success provides realistic and accessible teaching techniques for teachers, special educators, and other professionals working with students at the late elementary, middle, and early high school levels. This book is particularly useful for teachers working in inclusive settings. These strategies can help teachers to understand the…

  3. 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…

  4. 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…

  5. 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…

  6. Techniques of Learning: Self-Modification of Academic Behavior--Trainer's Manual.

    ERIC Educational Resources Information Center

    Zimmerman, Jeff; Handfield, Victoria

    The concept and training procedures of a university-based, student-operated program designed to help other students in the area of academic effectiveness is described in this training manual. The manual offers the guidelines for training peer counselors in the techniques of individual academic counseling, group leadership skills in a co-leadership…

  7. Using Candy Samples to Learn about Sampling Techniques and Statistical Data Evaluation

    ERIC Educational Resources Information Center

    Canaes, Larissa S.; Brancalion, Marcel L.; Rossi, Adriana V.; Rath, Susanne

    2008-01-01

    A classroom exercise for undergraduate and beginning graduate students that takes about one class period is proposed and discussed. It is an easy, interesting exercise that demonstrates important aspects of sampling techniques (sample amount, particle size, and the representativeness of the sample in relation to the bulk material). The exercise…

  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. 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, domains, and…

  10. 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,…

  11. Writing and Assessing Student Learning Objectives: Tips, Techniques, and What Our Community Needs

    NASA Astrophysics Data System (ADS)

    Fraknoi, A.; Hufnagel, B.; Craig, M.

    2014-07-01

    This is a brief summary of the Cosmos in the Classroom conference discussion of Student Learning Objectives (SLOs), increasingly being required by college and university administrations and accreditation agencies around the country. In many cases, professors and instructors are writing these (and then developing instruments to assess them) with no assistance from anyone and little sharing of information during or after the process. We encouraged participants to bring copies of their own SLOs and tools for measuring how effective they were in achieving them. In both plenary and small group discussions, we examined how each of us grappled with SLOs and how we might coordinate efforts regionally and nationally, including the ongoing suggestions of setting up a national library of Astro 101 SLOs.

  12. Patient classification of hypertension in Traditional Chinese Medicine using multi-label learning techniques

    PubMed Central

    2015-01-01

    Background Hypertension is one of the major risk factors for cardiovascular diseases. Research on the patient classification of hypertension has become an important topic because Traditional Chinese Medicine lies primarily in "treatment based on syndromes differentiation of the patients". Methods Clinical data of hypertension was collected with 12 syndromes and 129 symptoms including inspection, tongue, inquiry, and palpation symptoms. Syndromes differentiation was modeled as a patient classification problem in the field of data mining, and a new multi-label learning model BrSmoteSvm was built dealing with the class-imbalanced of the dataset. Results The experiments showed that the BrSmoteSvm had a better results comparing to other multi-label classifiers in the evaluation criteria of Average precision, Coverage, One-error, Ranking loss. Conclusions BrSmoteSvm can model the hypertension's syndromes differentiation better considering the imbalanced problem. PMID:26399893

  13. 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.

  14. 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

  15. 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. PMID:27339067

  16. 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.

  17. High-Confidence Compositional Reliability Assessment of SOA-Based Systems Using Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Challagulla, Venkata U. B.; Bastani, Farokh B.; Yen, I.-Ling

    Service-oriented architecture (SOA) techniques are being increasingly used for developing critical applications, especially network-centric systems. While the SOA paradigm provides flexibility and agility to better respond to changing business requirements, the task of assessing the reliability of SOA-based systems is quite challenging. Deriving high confidence reliability estimates for mission-critical systems can require huge costs and time. SOAsystems/ applications are built by using either atomic or composite services as building blocks. These services are generally assumed to be realized with reuse and logical composition of components. One approach for assessing the reliability of SOA-based systems is to use AI reasoning techniques on dynamically collected failure data of each service and its components as one of the evidences together with results from random testing. Memory-Based Reasoning technique and Bayesian Belief Net-works are verified as the reasoning tools best suited to guide the prediction analysis. A framework constructed from the above approach identifies the least tested and “high usage” input subdomains of the service(s) and performs necessary remedial actions depending on the predicted results.

  18. Knowledge of errors in the teaching-learning process of judo-techniques: osoto-guruma as a case study.

    PubMed

    Prieto, Iván; Gutiérrez-Santiago, Alfonso; Prieto Lage, Miguel Ángel

    2014-06-28

    The aim of this article was to suggest some changes in the teaching-learning process methodology of the judo osoto-guruma technique, establishing the action sequences and the most frequent technical errors committed when performing them. The study was carried out with the participation of 45 students with no experience regarding the fundamentals of judo (21 men and 24 women; age=24.02±3.98 years old) from the Bachelor of Science of Physical Activity and Sport Science at the University of Vigo. The proceeding consisted of a systematic observation of a video recording registered during the technique execution. Data obtained were analyzed by means of descriptive statistics and sequential analysis of T-Patterns (obtained with THEME v.5. Software), identifying: a) the presence of typical inaccuracies during the technique performance; b) a number of chained errors affecting body balance, the position of the supporting foot, the blocking action and the final action of the arms. Findings allowed to suggest some motor tasks to correct the identified inaccuracies, the proper sequential actions to make the execution more effective and some recommendations for the use of feedback. Moreover, these findings could be useful for other professionals in order to correct the key technical errors and prevent diverse injuries. PMID:25114752

  19. 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.

  20. Development of automatic surveillance of animal behaviour and welfare using image analysis and machine learned segmentation technique.

    PubMed

    Nilsson, M; Herlin, A H; Ardö, H; Guzhva, O; Åström, K; Bergsten, C

    2015-11-01

    In this paper the feasibility to extract the proportion of pigs located in different areas of a pig pen by advanced image analysis technique is explored and discussed for possible applications. For example, pigs generally locate themselves in the wet dunging area at high ambient temperatures in order to avoid heat stress, as wetting the body surface is the major path to dissipate the heat by evaporation. Thus, the portion of pigs in the dunging area and resting area, respectively, could be used as an indicator of failure of controlling the climate in the pig environment as pigs are not supposed to rest in the dunging area. The computer vision methodology utilizes a learning based segmentation approach using several features extracted from the image. The learning based approach applied is based on extended state-of-the-art features in combination with a structured prediction framework based on a logistic regression solver using elastic net regularization. In addition, the method is able to produce a probability per pixel rather than form a hard decision. This overcomes some of the limitations found in a setup using grey-scale information only. The pig pen is a difficult imaging environment because of challenging lighting conditions like shadows, poor lighting and poor contrast between pig and background. In order to test practical conditions, a pen containing nine young pigs was filmed from a top view perspective by an Axis M3006 camera with a resolution of 640 × 480 in three, 10-min sessions under different lighting conditions. The results indicate that a learning based method improves, in comparison with greyscale methods, the possibility to reliable identify proportions of pigs in different areas of the pen. Pigs with a changed behaviour (location) in the pen may indicate changed climate conditions. Changed individual behaviour may also indicate inferior health or acute illness. PMID:26189971

  1. Tool wear monitoring by machine learning techniques and singular spectrum analysis

    NASA Astrophysics Data System (ADS)

    Kilundu, Bovic; Dehombreux, Pierre; Chiementin, Xavier

    2011-01-01

    This paper explores the use of data mining techniques for tool condition monitoring in metal cutting. Pseudo-local singular spectrum analysis (SSA) is performed on vibration signals measured on the toolholder. This is coupled to a band-pass filter to allow definition and extraction of features which are sensitive to tool wear. These features are defined, in some frequency bands, from sums of Fourier coefficients of reconstructed and residual signals obtained by SSA. This study highlights two important aspects: strong relevance of information in high frequency vibration components and benefits of the combination of SSA and band-pass filtering to get rid of useless components (noise).

  2. Exploring Machine Learning Techniques For Dynamic Modeling on Future Exascale Systems

    SciTech Connect

    Song, Shuaiwen; Tallent, Nathan R.; Vishnu, Abhinav

    2013-09-23

    Future exascale systems must be optimized for both power and performance at scale in order to achieve DOE’s goal of a sustained petaflop within 20 Megawatts by 2022 [1]. Massive parallelism of the future systems combined with complex memory hierarchies will form a barrier to efficient application and architecture design. These challenges are exacerbated with emerging complex architectures such as GPGPUs and Intel Xeon Phi as parallelism increases orders of magnitude and system power consumption can easily triple or quadruple. Therefore, we need techniques that can reduce the search space for optimization, isolate power-performance bottlenecks, identify root causes for software/hardware inefficiency, and effectively direct runtime scheduling.

  3. Teaching and Learning the Techniques of Conflict Resolution for Challenging Ethics Consultations.

    PubMed

    Bergman, Edward J; Fiester, Autumn

    2015-01-01

    Professional mediators have long possessed a skill set that is uniquely suited to facilitation of difficult conversations between and among individuals in emotionally charged situations. This skill set has increasingly been recognized as invaluable to the work of clinical ethics consultants as they navigate conflicts involving families, surrogates, and providers. Given widespread acknowledgment that communication difficulties lie at the root of many clinical ethics conflicts, mediation offers techniques to enhance communication between conflicting parties. This special section of The Journal of Clinical Ethics focuses on core aspects of the mediation process designed for effective management of clinical conflict emanating from communication breakdowns, highly charged value conflicts, and instances of perceived disrespect. PMID:26752385

  4. Learning techniques to train neural networks as a state selector for inverter-fed induction machines using direct torque control

    SciTech Connect

    Cabrera, L.A.; Elbuluk, M.E.; Zinger, D.S.

    1997-09-01

    Neural networks are receiving attention as controllers for many industrial applications. Although these networks eliminate the need for mathematical models, they require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. This paper discusses the application of neural networks to control induction machines using direct torque control (DTC). A neural network is used to emulate the state selector of the DTC. The training algorithms used in this paper are the backpropagation, adaptive neuron model, extended Kalman filter, and the parallel recursive prediction error. Computer simulations of the motor and neural-network system using the four approaches are presented and compared. Discussions about the parallel recursive prediction error and the extended Kalman filter algorithms as the most promising training techniques is presented, giving their advantages and disadvantages.

  5. Changing teaching techniques and adapting new technologies to improve student learning in an introductory meteorology and climate course

    NASA Astrophysics Data System (ADS)

    Cutrim, E. M.; Rudge, D.; Kits, K.; Mitchell, J.; Nogueira, R.

    2006-06-01

    Responding to the call for reform in science education, changes were made in an introductory meteorology and climate course offered at a large public university. These changes were a part of a larger project aimed at deepening and extending a program of science content courses that model effective teaching strategies for prospective middle school science teachers. Therefore, revisions were made to address misconceptions about meteorological phenomena, foster deeper understanding of key concepts, encourage engagement with the text, and promote inquiry-based learning. Techniques introduced include: use of a flash cards, student reflection questionnaires, writing assignments, and interactive discussions on weather and forecast data using computer technology such as Integrated Data Viewer (IDV). The revision process is described in a case study format. Preliminary results (self-reflection by the instructor, surveys of student opinion, and measurements of student achievement), suggest student learning has been positively influenced. This study is supported by three grants: NSF grant No. 0202923, the Unidata Equipment Award, and the Lucia Harrison Endowment Fund.

  6. Supporting 64-bit global indices in Epetra and other Trilinos packages : techniques used and lessons learned.

    SciTech Connect

    Jhurani, Chetan; Austin, Travis M.; Heroux, Michael Allen; Willenbring, James Michael

    2013-06-01

    The Trilinos Project is an effort to facilitate the design, development, integration and ongoing support of mathematical software libraries within an object-oriented framework. It is intended for large-scale, complex multiphysics engineering and scientific applications [2, 4, 3]. Epetra is one of its basic packages. It provides serial and parallel linear algebra capabilities. Before Trilinos version 11.0, released in 2012, Epetra used the C++ int data-type for storing global and local indices for degrees of freedom (DOFs). Since int is typically 32-bit, this limited the largest problem size to be smaller than approximately two billion DOFs. This was true even if a distributed memory machine could handle larger problems. We have added optional support for C++ long long data-type, which is at least 64-bit wide, for global indices. To save memory, maintain the speed of memory-bound operations, and reduce further changes to the code, the local indices are still 32-bit. We document the changes required to achieve this feature and how the new functionality can be used. We also report on the lessons learned in modifying a mature and popular package from various perspectives - design goals, backward compatibility, engineering decisions, C++ language features, effects on existing users and other packages, and build integration.

  7. Effect of Machine Learning Techniques on SeaQuest Physics Analyses

    NASA Astrophysics Data System (ADS)

    Morton, Daniel; University of Michigan Ann Arbor for SeaQuest Collaboration

    2016-03-01

    Fermilab E906, SeaQuest, implements a 120 GeV proton beam from the Main Injector incident on liquid Deuterium and Hydrogen targets and solid Tungsten, Carbon and Iron targets to produce leptons through the Drell-Yan process. Produced particles impinge on an iron beam dump, which absorbs all but muons and neutrinos. Muon pairs are divided and refocused with two dipole magnets. The primary objective is the extraction of the d / u ratio from the muon production cross section ratio σ (d + p) / σ (p + p) . The SeaQuest spectrometer is optimized to search for coincident dimuons, utilizing four detector stations containing scintillators, drift chambers and proportional tubes. The experiment relies on hodoscope coincidence to determine whether to accept the event. The goal of implementing machine learning algorithms (MLAs) is to improve trigger purity and event classification accuracy on both trigger and reconstruction levels, and thus improve statistical precision in all physics analyses and provide insight into spectrometer acceptance bias as well as potentially providing essential trigger optimization for the search of a dark Higgs candidate. We will report on the present status and plans to implement MLAs into the various triggers and its effect on physics analyses.

  8. Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations

    PubMed Central

    Kaplan, Jonas T.; Man, Kingson; Greening, Steven G.

    2015-01-01

    Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC), and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application. PMID:25859202

  9. Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations.

    PubMed

    Kaplan, Jonas T; Man, Kingson; Greening, Steven G

    2015-01-01

    Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC), and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application. PMID:25859202

  10. Robust band profile extraction using constrained nonparametric machine-learning technique.

    PubMed

    Khan, Shadab; Sanches, João; Ventura, Rodrigo

    2010-10-01

    A typical characteristic of images of bone marrow cells taken during mitosis is poor quality. This renders the task of extraction of accurate band profile, representative of intensity distribution over each chromosome, more challenging. A robust method is hence required to tackle this problem. An algorithm was thus developed, which estimates a single-line medial axis, the basis for computation of band profile. Medial axis was generated by computing a final prediction, using primary and secondary predictions obtained by a nonparametric machine learning algorithm trained with data from chromosome's skeleton, and geometrical properties of medial axis, respectively. Experiments were performed using the LK(1) dataset. The algorithm was found capable of estimating a satisfactory single-line medial axis. Band profile obtained was found to be a good representation of intensity levels in different regions of chromosomes. Additionally, this algorithm is robust in terms of growing a very small seed region into desired medial axis and also handling highly irregular chromosomes. PMID:20643597

  11. A mountain watershed hydrology field course: Experiential learning in hydrologic concepts and measurement techniques

    NASA Astrophysics Data System (ADS)

    Hogue, T. S.; Kinoshita, A. M.; Randell, J.

    2013-12-01

    A field mountainshed hydrology course was offered annually since April 2006 to investigate and quantify hydrologic processes in the Sagehen experimental watershed in the Sierra Nevada, California. This advanced field-based course was offered through the University of California, Los Angeles (UCLA) Civil and Environmental Engineering (CEE) and was primarily for upper division undergraduate students in the hydrology emphasis track. This unique ten-week course focused on the study of catchment processes in snow-dominated and mountainous regions. The course offered a range of activities, including quantifying distributed watershed fluxes, investigating geochemical properties of surface and groundwater systems, measuring channel dynamics and stream morphology, and analysis of snowpack properties. A major component of the course included an extended field trip to Sagehen where students undertook a range of observations and field experiments. Pre-field trip coursework required an in-depth analysis of historical streamflow, precipitation, snow and other regional hydroclimatological data. At Sagehen, students worked together in teams while gaining a range of field experiences. Post-field trip labs included analysis of their collected field data and comparison to previous years' data, culminating in a comprehensive final report and shared with the Sagehen Creek Field Station as part of a cooperative effort. This presentation will highlight course, laboratory and field design, a compilation of observational results, and insight on lessons learned through the course history.

  12. "Digit anatomy": a new technique for learning anatomy using motor memory.

    PubMed

    Oh, Chang-Seok; Won, Hyung-Sun; Kim, Kyong-Jee; Jang, Dong-Su

    2011-01-01

    Gestural motions of the hands and fingers are powerful tools for expressing meanings and concepts, and the nervous system has the capacity to retain multiple long-term motor memories, especially including movements of the hands. We developed many sets of successive movements of both hands, referred to as "digit anatomy," and made students practice the movements which express (1) the aortic arch, subclavian, and thoracoacromial arteries and their branches, (2) the celiac trunk, superior mesenteric artery and their branches, and formation of the portal vein, (3) the heart and the coronary arteries, and (4) the brachial, lumbar, and sacral plexuses. A feedback survey showed that digit anatomy was helpful for the students not only in memorizing anatomical structures but also in understanding their functions. Out of 40 students, 34 of them who learned anatomy with the help of digit anatomy were "very satisfied" or "generally satisfied" with this new teaching method. Digit anatomy that was used to express the aortic arch, subclavian, and thoracoacromial arteries and their branches was more helpful than those representing other structures. Although the movements of digit anatomy are expected to be remembered longer than the exact meaning of each movement, invoking the motor memory of the movement may help to make relearning of the same information easier and faster in the future. PMID:21538938

  13. Local prediction and classification techniques for machine learning and data mining

    NASA Astrophysics Data System (ADS)

    Lanker, Cory L.

    A variety of conditional probability models estimate the regression or class probability function for the purpose of prediction or classification. Bayesian mixture models provide flexible prediction and classification methods for modeling local linearities of the regression or class probability function. A hierarchical Bayes Gaussian mixture model is proposed that directly uses data to define a mixture prior for its Gaussian mixture component parameters. This nonparametric Bayesian mixture model uses the stick-breaking construction of a Dirichlet process model. Prediction and classification comes directly from the posterior distribution via Gibbs sampling. Comprehensive simulation studies demonstrate performance of both the regression and classification methods. Five standard machine learning data sets show prediction and classification results competitive with local methods. A generic classification algorithm is outlined given categorical predictors. If too many categories are present or if many interaction levels affect the class probability function, no current methods can reduce bias effectively. A proposed solution is a generic way to characterize the information about the class probability function available in the predictors through likelihood ratio statistics. This proposed classifier relies on random forests to reduce bias by utilizing all information in the generated log likelihood ratio features. A simulation study and an application data set demonstrate potential advantages of this classification method for categorical predictors.

  14. Monitoring the total organic carbon concentrations in a lake with the integrated data fusion and machine-learning (IDFM) technique

    NASA Astrophysics Data System (ADS)

    Chang, Ni-Bin; Vannah, Benjamin

    2012-10-01

    The concentration of total organic carbon (TOC) in surface waters is subject to seasonal variation, as well as abrupt changes in concentration due to events. In drinking water treatment, TOC is a precursor to disinfection byproducts such as total trihalomethanes (TTHM). With the aid of an early warning system for the detection of TOC concentrations, water treatment operators could make more informed decisions and adjust the treatment processes to minimize the generation of disinfection byproducts. In this paper, a near real-time monitoring system is explored using the Integrated Data Fusion and Machine-learning (IDFM) technique to predict the spatial distribution of TOC in a lake based upon surface reflectance data from satellite imagery. Landsat 5 TM and MODIS Terra satellite imagery can be acquired free of charge, yet MODIS has coarse spatial resolution, while Landsat has a lengthy 16 day revisit time. This difficulty is solved using data fusion algorithms to fuse the fine spatial resolution of Landsat with the daily revisit time of MODIS to generate a synthetic image with both high spatial and temporal resolution. To demonstrate the capabilities of IDFM, this case study uses the fused surface reflectance band data and applied machine-learning techniques to reconstruct the spatiotemporal distribution of TOC in Harsha Lake, which serves as the source water intake for the McEwen Water Treatment Plant in Ohio. The results of this application of IDFM were analyzed using 4 statistical indices, which indicated that the Artificial Neural Network model is capable of reconstructing TOC concentrations throughout the lake.

  15. Current breathomics--a review on data pre-processing techniques and machine learning in metabolomics breath analysis.

    PubMed

    Smolinska, A; Hauschild, A-Ch; Fijten, R R R; Dallinga, J W; Baumbach, J; van Schooten, F J

    2014-06-01

    We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related volatile organic compounds (VOCs). Since the amount of these compounds varies with health status, breathomics holds great promise to deliver non-invasive diagnostic tools. Thus, the main aim of breathomics is to find patterns of VOCs related to abnormal (for instance inflammatory) metabolic processes occurring in the human body. Recently, analytical methods for measuring VOCs in exhaled air with high resolution and high throughput have been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start with the detailed pre-processing pipelines for breathomics data obtained from gas-chromatography mass spectrometry and an ion-mobility spectrometer coupled to multi-capillary columns. The outcome of data pre-processing is a matrix containing the relative abundances of a set of VOCs for a group of patients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus of this paper. We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the community to understand how to profit from a particular method. In parallel, we hope to make the community aware of the existing data fusion methods, as yet unresearched in breathomics. PMID:24713999

  16. A new deflection technique applied to an existing scheme of electrostatic accelerator for high energy neutral beam injection in fusion reactor devices

    NASA Astrophysics Data System (ADS)

    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.

  17. 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. PMID:26932053

  18. Training Veterinary Students in Shelter-Medicine: A Service-Learning Community Classroom Based Technique

    PubMed Central

    Stevens, Brenda J.; Gruen, Margaret E.

    2015-01-01

    Shelter medicine is a rapidly developing field of great importance, and shelters themselves provide abundant training opportunities for veterinary medical students. Students trained in shelter medicine have opportunities to practice zoonotic and species-specific infectious disease control, behavioral evaluation and management, primary care, as well as animal welfare, ethics, and public policy issues. Ranges of sheltering systems now exist, from brick-and-mortar facilities to networks of foster homes with no centralized facility. Exposure to a single shelter setting may not allow students to understand the full range of sheltering systems that exist; a community classroom approach balances the opportunity to introduce students to a diverse array of sheltering systems, while gaining practical experience. This article presents the details and results of a series of two-week, elective clinical rotations with a focus on field and service-learning in animal shelters. The overall aim was to provide opportunities that familiarized students with sheltering systems and provided primary care training. Other priorities included increasing awareness of public health concerns, and equipping students to evaluate shelters on design, operating protocols, infectious disease control, enrichment and community outreach. Students were required to participate in rounds, and complete a project that addressed a need recognized by them during the rotation. This article includes costs associated with the rotation, a blueprint for how the rotation was carried out at our institution, and details of shelters visited and animals treated, including a breakdown of treatments provided. Also discussed are the student projects and student feedback on this valuable clinical experience. PMID:24407109

  19. 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.

  20. Automatic Cataract Classification based on Ultrasound Technique Using Machine Learning: A comparative Study

    NASA Astrophysics Data System (ADS)

    Caxinha, Miguel; Velte, Elena; Santos, Mário; Perdigão, Fernando; Amaro, João; Gomes, Marco; Santos, Jaime

    This paper addresses the use of computer-aided diagnosis (CAD) system for the cataract classification based on ultrasound technique. Ultrasound A-scan signals were acquired in 220 porcine lenses. B-mode and Nakagami images were constructed. Ninety-seven parameters were extracted from acoustical, spectral and image textural analyses and were subjected to feature selection by Principal Component Analysis (PCA). Bayes, K Nearest-Neighbors (KNN), Fisher Linear Discriminant (FLD) and Support Vector Machine (SVM) classifiers were tested. The classification of healthy and cataractous lenses shows a good performance for the four classifiers (F-measure ≥92.68%) with SVM showing the highest performance (90.62%) for initial versus severe cataract classification.

  1. Magnetic Insulation for Electrostatic Accelerators

    SciTech Connect

    Grisham, L. R.

    2011-09-26

    The voltage gradient which can be sustained between electrodes without electrical breakdowns is usually one of the most important parameters in determining the performance which can be obtained in an electrostatic accelerator. We have recently proposed a technique which might permit reliable operation of electrostatic accelerators at higher electric field gradients, perhaps also with less time required for the conditioning process in such accelerators. The idea is to run an electric current through each accelerator stage so as to produce a magnetic field which envelopes each electrode and its electrically conducting support structures. Having the magnetic field everywhere parallel to the conducting surfaces in the accelerator should impede the emission of electrons, and inhibit their ability to acquire energy from the electric field, thus reducing the chance that local electron emission will initiate an arc. A relatively simple experiment to assess this technique is being planned. If successful, this technique might eventually find applicability in electrostatic accelerators for fusion and other applications.

  2. 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…

  3. Mining FDA drug labels using an unsupervised learning technique - topic modeling

    PubMed Central

    2011-01-01

    Background The Food and Drug Administration (FDA) approved drug labels contain a broad array of information, ranging from adverse drug reactions (ADRs) to drug efficacy, risk-benefit consideration, and more. However, the labeling language used to describe these information is free text often containing ambiguous semantic descriptions, which poses a great challenge in retrieving useful information from the labeling text in a consistent and accurate fashion for comparative analysis across drugs. Consequently, this task has largely relied on the manual reading of the full text by experts, which is time consuming and labor intensive. Method In this study, a novel text mining method with unsupervised learning in nature, called topic modeling, was applied to the drug labeling with a goal of discovering “topics” that group drugs with similar safety concerns and/or therapeutic uses together. A total of 794 FDA-approved drug labels were used in this study. First, the three labeling sections (i.e., Boxed Warning, Warnings and Precautions, Adverse Reactions) of each drug label were processed by the Medical Dictionary for Regulatory Activities (MedDRA) to convert the free text of each label to the standard ADR terms. Next, the topic modeling approach with latent Dirichlet allocation (LDA) was applied to generate 100 topics, each associated with a set of drugs grouped together based on the probability analysis. Lastly, the efficacy of the topic modeling was evaluated based on known information about the therapeutic uses and safety data of drugs. Results The results demonstrate that drugs grouped by topics are associated with the same safety concerns and/or therapeutic uses with statistical significance (P<0.05). The identified topics have distinct context that can be directly linked to specific adverse events (e.g., liver injury or kidney injury) or therapeutic application (e.g., antiinfectives for systemic use). We were also able to identify potential adverse events that

  4. Suggestology as an Effective Language Learning Method.

    ERIC Educational Resources Information Center

    MaCoy, Katherine W.

    The methods used and the results obtained by means of the accelerated language learning techniques developed by Georgi Lozanov, Director of the Institute of Suggestology in Bulgaria, are discussed. The following topics are included: (1) discussion of hypermnesia, "super memory," and the reasons foreign languages were chosen for purposes of…

  5. Automatic approach to solve the morphological galaxy classification problem using the sparse representation technique and dictionary learning

    NASA Astrophysics Data System (ADS)

    Diaz-Hernandez, R.; Ortiz-Esquivel, A.; Peregrina-Barreto, H.; Altamirano-Robles, L.; Gonzalez-Bernal, J.

    2016-04-01

    The observation of celestial objects in the sky is a practice that helps astronomers to understand the way in which the Universe is structured. However, due to the large number of observed objects with modern telescopes, the analysis of these by hand is a difficult task. An important part in galaxy research is the morphological structure classification based on the Hubble sequence. In this research, we present an approach to solve the morphological galaxy classification problem in an automatic way by using the Sparse Representation technique and dictionary learning with K-SVD. For the tests in this work, we use a database of galaxies extracted from the Principal Galaxy Catalog (PGC) and the APM Equatorial Catalogue of Galaxies obtaining a total of 2403 useful galaxies. In order to represent each galaxy frame, we propose to calculate a set of 20 features such as Hu's invariant moments, galaxy nucleus eccentricity, gabor galaxy ratio and some other features commonly used in galaxy classification. A stage of feature relevance analysis was performed using Relief-f in order to determine which are the best parameters for the classification tests using 2, 3, 4, 5, 6 and 7 galaxy classes making signal vectors of different length values with the most important features. For the classification task, we use a 20-random cross-validation technique to evaluate classification accuracy with all signal sets achieving a score of 82.27 % for 2 galaxy classes and up to 44.27 % for 7 galaxy classes.

  6. Predicting Species Cover of Marine Macrophyte and Invertebrate Species Combining Hyperspectral Remote Sensing, Machine Learning and Regression Techniques

    PubMed Central

    Kotta, Jonne; Kutser, Tiit; Teeveer, Karolin; Vahtmäe, Ele; Pärnoja, Merli

    2013-01-01

    In order to understand biotic patterns and their changes in nature there is an obvious need for high-quality seamless measurements of such patterns. If remote sensing methods have been applied with reasonable success in terrestrial environment, their use in aquatic ecosystems still remained challenging. In the present study we combined hyperspectral remote sensing and boosted regression tree modelling (BTR), an ensemble method for statistical techniques and machine learning, in order to test their applicability in predicting macrophyte and invertebrate species cover in the optically complex seawater of the Baltic Sea. The BRT technique combined with remote sensing and traditional spatial modelling succeeded in identifying, constructing and testing functionality of abiotic environmental predictors on the coverage of benthic macrophyte and invertebrate species. Our models easily predicted a large quantity of macrophyte and invertebrate species cover and recaptured multitude of interactions between environment and biota indicating a strong potential of the method in the modelling of aquatic species in the large variety of ecosystems. PMID:23755113

  7. Automatic approach to solve the morphological galaxy classification problem using the sparse representation technique and dictionary learning

    NASA Astrophysics Data System (ADS)

    Diaz-Hernandez, R.; Ortiz-Esquivel, A.; Peregrina-Barreto, H.; Altamirano-Robles, L.; Gonzalez-Bernal, J.

    2016-06-01

    The observation of celestial objects in the sky is a practice that helps astronomers to understand the way in which the Universe is structured. However, due to the large number of observed objects with modern telescopes, the analysis of these by hand is a difficult task. An important part in galaxy research is the morphological structure classification based on the Hubble sequence. In this research, we present an approach to solve the morphological galaxy classification problem in an automatic way by using the Sparse Representation technique and dictionary learning with K-SVD. For the tests in this work, we use a database of galaxies extracted from the Principal Galaxy Catalog (PGC) and the APM Equatorial Catalogue of Galaxies obtaining a total of 2403 useful galaxies. In order to represent each galaxy frame, we propose to calculate a set of 20 features such as Hu's invariant moments, galaxy nucleus eccentricity, gabor galaxy ratio and some other features commonly used in galaxy classification. A stage of feature relevance analysis was performed using Relief-f in order to determine which are the best parameters for the classification tests using 2, 3, 4, 5, 6 and 7 galaxy classes making signal vectors of different length values with the most important features. For the classification task, we use a 20-random cross-validation technique to evaluate classification accuracy with all signal sets achieving a score of 82.27 % for 2 galaxy classes and up to 44.27 % for 7 galaxy classes.

  8. What have we learned by applying the data driven modelling techniques in the field of hydrological modelling?

    NASA Astrophysics Data System (ADS)

    Stravs, Luka; Brilly, Mitja

    2010-05-01

    Hydrologic data analysis and hydrologic modelling have become major techniques in hydrology and are used for building hydrologic models to generate synthetic hydrologic records, to forecast hydrologic events, to detect trends and shifts in hydrologic records and to fill in missing data and extend the data sets. Well known, praised and widely used are the so-called conceptual models that are based on the prior theoretical knowledge of all the hydrological processes in the form of theoretically developed or empirically derived equations. A modeller needs a lot of detailed data like river network, land cover, soil characteristics and other geographical data or topographical maps to sucessfully calibrate a conceptual model. The availability of all of the aforementioned data can present quite a significant problem in the process of modelling. On the basis of different approaches to the inclusion of geographical, topographical and other data in conceptual models, we distinguish between distributed, semi-distributed and lumped conceptual models. Empirical, mostly black box models simply connecting input and output hydrolgical data have also been widely used in the field of hydrology, especially in the hydrological praxis. Data driven modelling on the other hand is based on the analysis of the data characterising the system being modelled, which in most cases means finding the best type of model or combination of those to connect the input and output data characterising the system being modelled, while the assumptions or learning about the physical bases of the system being modelled are not the top priority. Also, there is still a lot of scepticism among many hydrologists regarding the usage of data driven modelling techniques in hydrology, because the development of the models from the data is usually seen as a computational exercise and is not related to physical principles and mathematical reasoning. This presentation will give a quick overview of more and less

  9. Assessment techniques for a learning-centered curriculum: evaluation design for adventures in supercomputing

    SciTech Connect

    Helland, B.; Summers, B.G.

    1996-09-01

    As the classroom paradigm shifts from being teacher-centered to being learner-centered, student assessments are evolving from typical paper and pencil testing to other methods of evaluation. Students should be probed for understanding, reasoning, and critical thinking abilities rather than their ability to return memorized facts. The assessment of the Department of Energy`s pilot program, Adventures in Supercomputing (AiS), offers one example of assessment techniques developed for learner-centered curricula. This assessment has employed a variety of methods to collect student data. Methods of assessment used were traditional testing, performance testing, interviews, short questionnaires via email, and student presentations of projects. The data obtained from these sources have been analyzed by a professional assessment team at the Center for Children and Technology. The results have been used to improve the AiS curriculum and establish the quality of the overall AiS program. This paper will discuss the various methods of assessment used and the results.

  10. HPC Usage Behavior Analysis and Performance Estimation with Machine Learning Techniques

    SciTech Connect

    Zhang, Hao; You, Haihang; Hadri, Bilel; Fahey, Mark R

    2012-01-01

    Most researchers with little high performance computing (HPC) experience have difficulties productively using the supercomputing resources. To address this issue, we investigated usage behaviors of the world s fastest academic Kraken supercomputer, and built a knowledge-based recommendation system to improve user productivity. Six clustering techniques, along with three cluster validation measures, were implemented to investigate the underlying patterns of usage behaviors. Besides manually defining a category for very large job submissions, six behavior categories were identified, which cleanly separated the data intensive jobs and computational intensive jobs. Then, job statistics of each behavior category were used to develop a knowledge-based recommendation system that can provide users with instructions about choosing appropriate software packages, setting job parameter values, and estimating job queuing time and runtime. Experiments were conducted to evaluate the performance of the proposed recommendation system, which included 127 job submissions by users from different research fields. Great feedback indicated the usefulness of the provided information. The average runtime estimation accuracy of 64.2%, with 28.9% job termination rate, was achieved in the experiments, which almost doubled the average accuracy in the Kraken dataset.

  11. Wastewater quality monitoring system using sensor fusion and machine learning techniques.

    PubMed

    Qin, Xusong; Gao, Furong; Chen, Guohua

    2012-03-15

    A multi-sensor water quality monitoring system incorporating an UV/Vis spectrometer and a turbidimeter was used to monitor the Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and Oil & Grease (O&G) concentrations of the effluents from the Chinese restaurant on campus and an electrocoagulation-electroflotation (EC-EF) pilot plant. In order to handle the noise and information unbalance in the fused UV/Vis spectra and turbidity measurements during the calibration model building, an improved boosting method, Boosting-Iterative Predictor Weighting-Partial Least Squares (Boosting-IPW-PLS), was developed in the present study. The Boosting-IPW-PLS method incorporates IPW into boosting scheme to suppress the quality-irrelevant variables by assigning small weights, and builds up the models for the wastewater quality predictions based on the weighted variables. The monitoring system was tested in the field with satisfactory results, underlying the potential of this technique for the online monitoring of water quality. PMID:22200261

  12. Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal.

    PubMed

    Hosseinifard, Behshad; Moradi, Mohammad Hassan; Rostami, Reza

    2013-03-01

    Diagnosing depression in the early curable stages is very important and may even save the life of a patient. In this paper, we study nonlinear analysis of EEG signal for discriminating depression patients and normal controls. Forty-five unmedicated depressed patients and 45 normal subjects were participated in this study. Power of four EEG bands and four nonlinear features including detrended fluctuation analysis (DFA), higuchi fractal, correlation dimension and lyapunov exponent were extracted from EEG signal. For discriminating the two groups, k-nearest neighbor, linear discriminant analysis and logistic regression as the classifiers are then used. Highest classification accuracy of 83.3% is obtained by correlation dimension and LR classifier among other nonlinear features. For further improvement, all nonlinear features are combined and applied to classifiers. A classification accuracy of 90% is achieved by all nonlinear features and LR classifier. In all experiments, genetic algorithm is employed to select the most important features. The proposed technique is compared and contrasted with the other reported methods and it is demonstrated that by combining nonlinear features, the performance is enhanced. This study shows that nonlinear analysis of EEG can be a useful method for discriminating depressed patients and normal subjects. It is suggested that this analysis may be a complementary tool to help psychiatrists for diagnosing depressed patients. PMID:23122719

  13. Classification and Ranking of Fermi LAT Gamma-ray Sources from the 3FGL Catalog using Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Saz Parkinson, P. M.; Xu, H.; Yu, P. L. H.; Salvetti, D.; Marelli, M.; Falcone, A. D.

    2016-03-01

    We apply a number of statistical and machine learning techniques to classify and rank gamma-ray sources from the Third Fermi Large Area Telescope Source Catalog (3FGL), according to their likelihood of falling into the two major classes of gamma-ray emitters: pulsars (PSR) or active galactic nuclei (AGNs). Using 1904 3FGL sources that have been identified/associated with AGNs (1738) and PSR (166), we train (using 70% of our sample) and test (using 30%) our algorithms and find that the best overall accuracy (>96%) is obtained with the Random Forest (RF) technique, while using a logistic regression (LR) algorithm results in only marginally lower accuracy. We apply the same techniques on a subsample of 142 known gamma-ray pulsars to classify them into two major subcategories: young (YNG) and millisecond pulsars (MSP). Once more, the RF algorithm has the best overall accuracy (∼90%), while a boosted LR analysis comes a close second. We apply our two best models (RF and LR) to the entire 3FGL catalog, providing predictions on the likely nature of unassociated sources, including the likely type of pulsar (YNG or MSP). We also use our predictions to shed light on the possible nature of some gamma-ray sources with known associations (e.g., binaries, supernova remnants/pulsar wind nebulae). Finally, we provide a list of plausible X-ray counterparts for some pulsar candidates, obtained using Swift, Chandra, and XMM. The results of our study will be of interest both for in-depth follow-up searches (e.g., pulsar) at various wavelengths and for broader population studies.

  14. Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications

    PubMed Central

    Thottakkara, Paul; Ozrazgat-Baslanti, Tezcan; Hupf, Bradley B.; Rashidi, Parisa; Pardalos, Panos; Momcilovic, Petar

    2016-01-01

    Objective To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. Design Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010. Patients 50,318 adult patients undergoing major surgery. Measurements We evaluated the performance of logistic regression, generalized additive models, naïve Bayes and support vector machines for forecasting postoperative sepsis and acute kidney injury. We assessed the impact of feature reduction techniques on predictive performance. Model performance was determined using the area under the receiver operating characteristic curve, accuracy, and positive predicted value. The results were reported based on a 70/30 cross validation procedure where the data were randomly split into 70% used for training the model and the 30% for validation. Main Results The areas under the receiver operating characteristic curve for different models ranged between 0.797 and 0.858 for acute kidney injury and between 0.757 and 0.909 for severe sepsis. Logistic regression, generalized additive model, and support vector machines had better performance compared to Naïve Bayes model. Generalized additive models additionally accounted for non-linearity of continuous clinical variables as depicted in their risk patterns plots. Reducing the input feature space with LASSO had minimal effect on prediction performance, while feature extraction using principal component analysis improved performance of the models. Conclusions Generalized additive models and support vector machines had good performance as risk prediction model for postoperative sepsis and AKI. Feature extraction using principal component analysis improved the predictive performance of all models. PMID:27232332

  15. Examination of geostatistical and machine-learning techniques as interpolators in anisotropic atmospheric environments

    NASA Astrophysics Data System (ADS)

    Tadić, Jovan M.; Ilić, Velibor; Biraud, Sebastien

    2015-06-01

    Selecting which interpolation method to use significantly affects the results of atmospheric studies. The goal of this study is to examine the performance of several interpolation techniques under typical atmospheric conditions. Several types of kriging and artificial neural networks used as spatial interpolators are here compared and evaluated against ordinary kriging, using real airborne CO2 mixing-ratio data and synthetic data. The real data were measured (on December 26, 2012) between Billings and Lamont, near Oklahoma City, Oklahoma, within and above the planetary boundary layer (PBL). Predictions were made all along the flight trajectory within a total volume of 5000 km3 of atmospheric air (27 × 33 × 5.6 km). We evaluated (a) universal kriging, (b) ensemble neural networks, (c) universal kriging with ensemble neural network outputs used as covariates, and (d) ensemble neural networks with ordinary kriging of the residuals as interpolation tools. We found that in certain cases, when the weaknesses of ordinary kriging interpolation schemes (based on an omnidirectional isotropic variogram presumption) became apparent, more sophisticated interpolation methods were in order. In this study, preservation of the potentially nonlinear relationship between the trend and coordinates (by using neural kriging output as a covariate in a universal kriging scheme) was attempted, with varying degrees of success (it was best performer in 4 out of 8 cases). The study confirmed the necessity of selecting an interpolation approach that includes a combination of expert understanding and appropriate interpolation tools. The error analysis showed that uncertainty representations generated by the kriging methods are superior to neural networks, but that the actual error varies from case to case.

  16. Improving Convergence of Backpropagation Learning using Exponential Cost Function

    NASA Astrophysics Data System (ADS)

    Kamruzzaman, Joarder

    Backpropagation, one of the most popular learning algorithms in multi-layered feedforward neural networks, suffers from the drawback of slow convergence. Several modifications have been proposed to accelerate the learning process using different techniques. In this paper, a new cost function expressed as exponential of sum-squared or Log-likelihood is proposed. Weight update using this modification varies the learning rate parameter dynamically during training as opposed to constant learning rate parameter used in standard Backpropagation. Simulation results with different problems demonstrate significant improvement in the learning speed of Backpropagation algorithm.

  17. Detecting flooded areas with machine learning techniques: case study of the Selška Sora river flash flood in September 2007

    NASA Astrophysics Data System (ADS)

    Lamovec, Peter; Veljanovski, Tatjana; Mikoš, Matjaž; Oštir, Krištof

    2013-01-01

    Floods seem to appear with increased frequency from one year to another. They create great damage to property and in some cases even result in lost lives. However, a quick and effective response by rescue services can greatly reduce the consequences. Machine learning techniques can reduce the time necessary for flood mapping. We test various machine learning methods to find the one with the highest classification accuracy. We also present the most important points for quick and effective machine learning procedures on remote sensing data. First, the data must be prepared correctly. We use satellite images, digital terrain models (DTMs), and the river network. The data in its primary form (e.g., bands of multispectral satellite images or DTMs) is insufficient. We also need certain derived attributes, such as the vegetation index or the slope derived from the DTM. Second, we must select suitable training samples and a suitable machine learning method. This approach to determining floods is presented in a case study of flash floods in the Selška Sora river valley. Machine learning techniques have proven successful in quickly determining flooded areas. The best results are produced by the J48 decision tree algorithm. The success of the ensemble machine learning methods is comparable to the J48 algorithm, while the JRip classification is not as good.

  18. Accelerated Reader.

    ERIC Educational Resources Information Center

    Education Commission of the States, Denver, CO.

    This paper provides an overview of Accelerated Reader, a system of computerized testing and record-keeping that supplements the regular classroom reading program. Accelerated Reader's primary goal is to increase literature-based reading practice. The program offers a computer-aided reading comprehension and management program intended to motivate…

  19. Field Observations of Bioaerosols: What We've Learned from Fluorescence, Genetic, and Microscopic Techniques (Invited)

    NASA Astrophysics Data System (ADS)

    Huffman, J. A.; Fröhlich-Nowoisky, J.; Després, V. R.; Elbert, W.; Sinha, B.; Andreae, M. O.; Pöschl, U.

    2009-12-01

    Biogenic aerosols are ubiquitous in the Earth’s atmosphere, influencing atmospheric chemistry and physics, the biosphere, climate, and public health. They play an important role in the spread of biological organisms, and they can cause or enhance human, animal, and plant diseases. Moreover, they can initiate the formation of clouds and precipitation as cloud condensation and ice nuclei (CCN, IN). Primary biogenic aerosol particles (PBAP) such as pollen, fungal spores, and bacteria are emitted directly from the biosphere to the atmosphere. Microscopic investigations have shown that PBAP account for up to ~30% of fine and up to ~70% of coarse particulate matter in rural and rain forest air, and the estimates of PBA emissions range from ~60 Tg a-1 of fine particles up to ~1000 Tg a-1 of total particulate matter. Fungal spores account for a large proportion of PBA with typical number and mass concentrations of ~104 m-3 and ~1 μg m-3 in continental boundary layer air and estimated global emissions of the order of ~50 Tg a-1 and 200 m-2 s-1, respectively [1]. The actual abundance, variability and diversity of PBAP are still poorly understood and quantified, however. By measuring fluorescence at excitation and emission wavelengths specific to viable cells, online techniques with time resolution of minutes are able to detect fluorescent biological aerosol particles (FBAP), which represent a lower limit for the actual abundance of coarse (> 1 μm) PBAP [2]. Continuous sampling (1 - 4 months) was performed at various locations including pristine rain forest, rural and polluted urban sites. Each study exhibited a similar average particle number distribution dominated by a peak at ~3 μm, with coarse FBAP concentrations of the order of ~5x104 m-3 and ~1 μg m-3. Recent advances in the DNA analysis and molecular genetic characterization of aerosol filter samples yield new information about the sources and composition of PBA and provide new insight into regional and global

  20. The Home-School New Educational Partnership: A Handbook of Teacher-Tested Techniques and Activities for Parent-Home Involvement in Children's Learning.

    ERIC Educational Resources Information Center

    Rich, Dorothy; Jones, Cynthia

    This handbook was designed to help teachers promote parent-home involvement in children's learning by providing them with specific techniques and materials to use in working with parents. The handbook begins with a general article discussing why parent-home involvement is important in the educational process and goes on to present 10 tips for…