Sample records for accelerated learning techniques

  1. 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…

  2. 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,…

  3. 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…

  4. The effect of team accelerated instruction on students’ mathematics achievement and learning motivation

    NASA Astrophysics Data System (ADS)

    Sri Purnami, Agustina; Adi Widodo, Sri; Charitas Indra Prahmana, Rully

    2018-01-01

    This study aimed to know the improvement of achievement and motivation of learning mathematics by using Team Accelerated Instruction. The research method used was the experiment with descriptive pre-test post-test experiment. The population in this study was all students of class VIII junior high school in Jogjakarta. The sample was taken using cluster random sampling technique. The instrument used in this research was questionnaire and test. Data analysis technique used was Wilcoxon test. It concluded that there was an increase in motivation and student achievement of class VII on linear equation system material by using the learning model of Team Accelerated Instruction. Based on the results of the learning model Team Accelerated Instruction can be used as a variation model in learning mathematics.

  5. 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.…

  6. Effective Teaching in Accelerated Learning Programs

    ERIC Educational Resources Information Center

    Boyd, Drick

    2004-01-01

    According to Wlodkowski (2003), "accelerated learning programs are one of the fastest growing transformations in higher education" (p. 5). The Center for the Study of Accelerated Learning at Regis University has documented at least 250 colleges or universities that offer accelerated learning programs for working adults. By definition, accelerated…

  7. 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…

  8. 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.

  9. 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.

  10. 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)

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

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

    Aslanyan, Grigor; Easther, Richard; Price, Layne C., E-mail: g.aslanyan@auckland.ac.nz, E-mail: r.easther@auckland.ac.nz, E-mail: lpri691@aucklanduni.ac.nz

    2015-09-01

    Cosmological analyses can be accelerated by approximating slow calculations using a training set, which is either precomputed or generated dynamically. However, this approach is only safe if the approximations are well understood and controlled. This paper surveys issues associated with the use of machine-learning based emulation strategies for accelerating cosmological parameter estimation. We describe a learn-as-you-go algorithm that is implemented in the Cosmo++ code and (1) trains the emulator while simultaneously estimating posterior probabilities; (2) identifies unreliable estimates, computing the exact numerical likelihoods if necessary; and (3) progressively learns and updates the error model as the calculation progresses. We explicitlymore » 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.« less

  12. Toward accelerating landslide mapping with interactive machine learning techniques

    NASA Astrophysics Data System (ADS)

    Stumpf, André; Lachiche, Nicolas; Malet, Jean-Philippe; Kerle, Norman; Puissant, Anne

    2013-04-01

    Despite important advances in the development of more automated methods for landslide mapping from optical remote sensing images, the elaboration of inventory maps after major triggering events still remains a tedious task. Image classification with expert defined rules typically still requires significant manual labour for the elaboration and adaption of rule sets for each particular case. Machine learning algorithm, on the contrary, have the ability to learn and identify complex image patterns from labelled examples but may require relatively large amounts of training data. In order to reduce the amount of required training data active learning has evolved as key concept to guide the sampling for applications such as document classification, genetics and remote sensing. The general underlying idea of most active learning approaches is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and/or the data structure to iteratively select the most valuable samples that should be labelled by the user and added in the training set. With relatively few queries and labelled samples, an active learning strategy should ideally yield at least the same accuracy than an equivalent classifier trained with many randomly selected samples. Our study was dedicated to the development of an active learning approach for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. The developed approach is a region-based query heuristic that enables to guide the user attention towards few compact spatial batches rather than distributed points resulting in time savings of 50% and more compared to standard active learning techniques. The approach was tested with multi-temporal and multi-sensor satellite images capturing recent large scale triggering events in Brazil and China and demonstrated balanced user's and producer's accuracies between 74% and 80%. The assessment also

  13. Accelerating Innovation Through Coopetition: The Innovation Learning Network Experience.

    PubMed

    McCarthy, Chris; Ford Carleton, Penny; Krumpholz, Elizabeth; Chow, Marilyn P

    Coopetition, the simultaneous pursuit of cooperation and competition, is a growing force in the innovation landscape. For some organizations, the primary mode of innovation continues to be deeply secretive and highly competitive, but for others, a new style of shared challenges, shared purpose, and shared development has become a superior, more efficient way of working to accelerate innovation capabilities and capacity. Over the last 2 decades, the literature base devoted to coopetition has gradually expanded. However, the field is still in its infancy. The majority of coopetition research is qualitative, primarily consisting of case studies. Few studies have addressed the nonprofit sector or service industries such as health care. The authors believe that this article may offer a unique perspective on coopetition in the context of a US-based national health care learning alliance designed to accelerate innovation, the Innovation Learning Network or ILN. The mission of the ILN is to "Share the joy and pain of innovation," accelerating innovation by sharing solutions, teaching techniques, and cultivating friendships. These 3 pillars (sharing, teaching, and cultivating) form the foundation for coopetition within the ILN. Through the lens of coopetition, we examine the experience of the ILN over the last 10 years and provide case examples that illustrate the benefits and challenges of coopetition in accelerating innovation in health care.

  14. Compensation Techniques in Accelerator Physics

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

    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. Twomore » 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.« less

  15. Comparison of marginal accuracy of castings fabricated by conventional casting technique and accelerated casting technique: an in vitro study.

    PubMed

    Reddy, S Srikanth; Revathi, Kakkirala; Reddy, S Kranthikumar

    2013-01-01

    Conventional casting technique is time consuming when compared to accelerated casting technique. In this study, marginal accuracy of castings fabricated using accelerated and conventional casting technique was compared. 20 wax patterns were fabricated and the marginal discrepancy between the die and patterns were measured using Optical stereomicroscope. Ten wax patterns were used for Conventional casting and the rest for Accelerated casting. A Nickel-Chromium alloy was used for the casting. The castings were measured for marginal discrepancies and compared. Castings fabricated using Conventional casting technique showed less vertical marginal discrepancy than the castings fabricated by Accelerated casting technique. The values were statistically highly significant. Conventional casting technique produced better marginal accuracy when compared to Accelerated casting. The vertical marginal discrepancy produced by the Accelerated casting technique was well within the maximum clinical tolerance limits. Accelerated casting technique can be used to save lab time to fabricate clinical crowns with acceptable vertical marginal discrepancy.

  16. Network acceleration techniques

    NASA Technical Reports Server (NTRS)

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

  17. 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…

  18. Accelerated Learning Options: A Promising Strategy for States. Policy Insights

    ERIC Educational Resources Information Center

    Michelau, Demaree

    2006-01-01

    This issue of Policy Insights draws on findings from WICHE's report Accelerated Learning Options: Moving the Needle on Access and Success, to lay out some of the important policy issues that decision makers might consider when adopting new state policy related to accelerated learning or modifying policies already in existence. The publication…

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  1. Traditional and Accelerated Baccalaureate Nursing Students' Self-Efficacy for Interprofessional Learning.

    PubMed

    Durkin, Anne E; Feinn, Richard S

    The aim of the study was to examine self-efficacy among traditional and accelerated nursing students with regard to interprofessional learning. The World Health Organization and other organizations recognize the need for interprofessional education to prepare health care providers for collaborative practice. Graduates of baccalaureate nursing programs require competence in interprofessional collaboration and communication. Traditional (n = 239) and accelerated (n = 114) nursing students' self-efficacy was measured utilizing Mann et al.'s Self-Efficacy for Interprofessional Experiential Learning Scale. Accelerated students averaged significantly higher than traditional students on the interprofessional team evaluation and feedback subscale (p = .006) and overall self-efficacy (p = .041). Awareness of possible differences between traditional and accelerated nursing students with regard to self-efficacy may help faculty develop effective interprofessional learning experiences for students in each cohort. Although results cannot be generalized, findings from this study provide evidence to guide the selection of learning strategies.

  2. Using machine learning to accelerate sampling-based inversion

    NASA Astrophysics Data System (ADS)

    Valentine, A. P.; Sambridge, M.

    2017-12-01

    In most cases, a complete solution to a geophysical inverse problem (including robust understanding of the uncertainties associated with the result) requires a sampling-based approach. However, the computational burden is high, and proves intractable for many problems of interest. There is therefore considerable value in developing techniques that can accelerate sampling procedures.The main computational cost lies in evaluation of the forward operator (e.g. calculation of synthetic seismograms) for each candidate model. Modern machine learning techniques-such as Gaussian Processes-offer a route for constructing a computationally-cheap approximation to this calculation, which can replace the accurate solution during sampling. Importantly, the accuracy of the approximation can be refined as inversion proceeds, to ensure high-quality results.In this presentation, we describe and demonstrate this approach-which can be seen as an extension of popular current methods, such as the Neighbourhood Algorithm, and bridges the gap between prior- and posterior-sampling frameworks.

  3. 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…

  4. Convolutional Dictionary Learning: Acceleration and Convergence

    NASA Astrophysics Data System (ADS)

    Chun, Il Yong; Fessler, Jeffrey A.

    2018-04-01

    Convolutional dictionary learning (CDL or sparsifying CDL) has many applications in image processing and computer vision. There has been growing interest in developing efficient algorithms for CDL, mostly relying on the augmented Lagrangian (AL) method or the variant alternating direction method of multipliers (ADMM). When their parameters are properly tuned, AL methods have shown fast convergence in CDL. However, the parameter tuning process is not trivial due to its data dependence and, in practice, the convergence of AL methods depends on the AL parameters for nonconvex CDL problems. To moderate these problems, this paper proposes a new practically feasible and convergent Block Proximal Gradient method using a Majorizer (BPG-M) for CDL. The BPG-M-based CDL is investigated with different block updating schemes and majorization matrix designs, and further accelerated by incorporating some momentum coefficient formulas and restarting techniques. All of the methods investigated incorporate a boundary artifacts removal (or, more generally, sampling) operator in the learning model. Numerical experiments show that, without needing any parameter tuning process, the proposed BPG-M approach converges more stably to desirable solutions of lower objective values than the existing state-of-the-art ADMM algorithm and its memory-efficient variant do. Compared to the ADMM approaches, the BPG-M method using a multi-block updating scheme is particularly useful in single-threaded CDL algorithm handling large datasets, due to its lower memory requirement and no polynomial computational complexity. Image denoising experiments show that, for relatively strong additive white Gaussian noise, the filters learned by BPG-M-based CDL outperform those trained by the ADMM approach.

  5. 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.

  6. 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…

  7. Accelerating the Learning of At-Risk Students: An Evaluation of Project ACCEL.

    ERIC Educational Resources Information Center

    Ramaswami, Soundaram

    Project Accelerated Curriculum Classes Emphasizing Learning (ACCEL) was implemented by the Newark School District (New Jersey) in the 1989-90 school year in response to the ineffective practice of retaining underachieving students. The innovative approach of accelerated learning was made available to retained sixth and seventh grade students.…

  8. Accelerated Schools as Professional Learning Communities.

    ERIC Educational Resources Information Center

    Biddle, Julie K.

    The goal of the Accelerated Schools Project (ASP) is to develop schools in which all children achieve at high levels and all members of the school community engage in developing and fulfilling the school's vision. But to fully implement the ASP model, a school must become a learning community that stresses relationships, shared values, and a…

  9. Analysis techniques for residual acceleration data

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  10. The algorithm for duration acceleration of repetitive projects considering the learning effect

    NASA Astrophysics Data System (ADS)

    Chen, Hongtao; Wang, Keke; Du, Yang; Wang, Liwan

    2018-03-01

    Repetitive project optimization problem is common in project scheduling. Repetitive Scheduling Method (RSM) has many irreplaceable advantages in the field of repetitive projects. As the same or similar work is repeated, the proficiency of workers will be correspondingly low to high, and workers will gain experience and improve the efficiency of operations. This is learning effect. Learning effect is one of the important factors affecting the optimization results in repetitive project scheduling. This paper analyzes the influence of the learning effect on the controlling path in RSM from two aspects: one is that the learning effect changes the controlling path, the other is that the learning effect doesn't change the controlling path. This paper proposes corresponding methods to accelerate duration for different types of critical activities and proposes the algorithm for duration acceleration based on the learning effect in RSM. And the paper chooses graphical method to identity activities' types and considers the impacts of the learning effect on duration. The method meets the requirement of duration while ensuring the lowest acceleration cost. A concrete bridge construction project is given to verify the effectiveness of the method. The results of this study will help project managers understand the impacts of the learning effect on repetitive projects, and use the learning effect to optimize project scheduling.

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

    DTIC Science & Technology

    2011-03-01

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

  12. 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

  13. Development Biology Worksheet Oriented Accelerated Learning on Plantae and Ecosystems for 10th-Grade Senior High School Students

    NASA Astrophysics Data System (ADS)

    Dipuja, D. A.; Lufri, L.; Ahda, Y.

    2018-04-01

    The problem that found are learning outcomes student is low on the plantae and ecosystems. Students less motivated and passive learning because learning is teacher center and teaching materials not facilitate student. Therefore, it is necessary to design a worksheet oriented accelerated learning. Accelerated learning approach that can improve motivation and learning activities. The purpose of the research was to produce worksheet oriented accelerated learning on plantae and ecosystems. This research is designed as a research and development by using Plomp model, consists of the preliminary, prototyping, and assessment phase. Data was collected through questionnaires, observation sheet, test, and documentation. The results of the research was worksheet oriented accelerated learning on plantae and ecosystems is very valid.

  14. Evaluation of marginal gap of Ni-Cr copings made with conventional and accelerated casting techniques.

    PubMed

    Tannamala, Pavan Kumar; Azhagarasan, Nagarasampatti Sivaprakasam; Shankar, K Chitra

    2013-01-01

    Conventional casting techniques following the manufacturers' recommendations are time consuming. Accelerated casting techniques have been reported, but their accuracy with base metal alloys has not been adequately studied. We measured the vertical marginal gap of nickel-chromium copings made by conventional and accelerated casting techniques and determined the clinical acceptability of the cast copings in this study. Experimental design, in vitro study, lab settings. Ten copings each were cast by conventional and accelerated casting techniques. All copings were identical, only their mold preparation schedules differed. Microscopic measurements were recorded at ×80 magnification on the perpendicular to the axial wall at four predetermined sites. The marginal gap values were evaluated by paired t test. The mean marginal gap by conventional technique (34.02 μm) is approximately 10 μm lesser than that of accelerated casting technique (44.62 μm). As the P value is less than 0.0001, there is highly significant difference between the two techniques with regard to vertical marginal gap. The accelerated casting technique is time saving and the marginal gap measured was within the clinically acceptable limits and could be an alternative to time-consuming conventional techniques.

  15. Accelerating Multiagent Reinforcement Learning by Equilibrium Transfer.

    PubMed

    Hu, Yujing; Gao, Yang; An, Bo

    2015-07-01

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

  16. 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.

  17. 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.

  18. Neural Networks for Modeling and Control of Particle Accelerators

    NASA Astrophysics Data System (ADS)

    Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

    2016-04-01

    Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. 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 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.

  19. 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…

  20. 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.…

  1. Accuracy of ringless casting and accelerated wax-elimination technique: a comparative in vitro study.

    PubMed

    Prasad, Rahul; Al-Keraif, Abdulaziz Abdullah; Kathuria, Nidhi; Gandhi, P V; Bhide, S V

    2014-02-01

    The purpose of this study was to determine whether the ringless casting and accelerated wax-elimination techniques can be combined to offer a cost-effective, clinically acceptable, and time-saving alternative for fabricating single unit castings in fixed prosthodontics. Sixty standardized wax copings were fabricated on a type IV stone replica of a stainless steel die. The wax patterns were divided into four groups. The first group was cast using the ringless investment technique and conventional wax-elimination method; the second group was cast using the ringless investment technique and accelerated wax-elimination method; the third group was cast using the conventional metal ring investment technique and conventional wax-elimination method; the fourth group was cast using the metal ring investment technique and accelerated wax-elimination method. The vertical marginal gap was measured at four sites per specimen, using a digital optical microscope at 100× magnification. The results were analyzed using two-way ANOVA to determine statistical significance. The vertical marginal gaps of castings fabricated using the ringless technique (76.98 ± 7.59 μm) were significantly less (p < 0.05) than those castings fabricated using the conventional metal ring technique (138.44 ± 28.59 μm); however, the vertical marginal gaps of the conventional (102.63 ± 36.12 μm) and accelerated wax-elimination (112.79 ± 38.34 μm) castings were not statistically significant (p > 0.05). The ringless investment technique can produce castings with higher accuracy and can be favorably combined with the accelerated wax-elimination method as a vital alternative to the time-consuming conventional technique of casting restorations in fixed prosthodontics. © 2013 by the American College of Prosthodontists.

  2. Neural Networks for Modeling and Control of Particle Accelerators

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

    Edelen, A. L.; Biedron, S. G.; Chase, B. E.

    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

  3. Neural Networks for Modeling and Control of Particle Accelerators

    DOE PAGES

    Edelen, A. L.; Biedron, S. G.; Chase, B. E.; ...

    2016-04-01

    Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

  4. Machine Learning Techniques in Clinical Vision Sciences.

    PubMed

    Caixinha, Miguel; Nunes, Sandrina

    2017-01-01

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

  5. 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.…

  6. Ultra-Compact Accelerator Technologies for Application in Nuclear Techniques

    NASA Astrophysics Data System (ADS)

    Sampayan, S.; Caporaso, G.; Chen, Y.-J.; 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.

    2009-12-01

    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 ˜10 MV/m gradients for 10 s of nanoseconds pulses and ˜100 MV/m gradients for ˜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 describe the progress of our overall component development effort with the multilayer dielectric wall insulators (i.e., the accelerator wall), compact power supply technology, kHz repetition-rate surface flashover ion sources, and the prompt pulse generation system consisting of wide-bandgap switches and high performance dielectric materials.

  7. Adaptive Neuron Apoptosis for Accelerating Deep Learning on Large Scale Systems

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

    Siegel, Charles M.; Daily, Jeffrey A.; Vishnu, Abhinav

    Machine Learning and Data Mining (MLDM) algorithms are becoming ubiquitous in {\\em model learning} from the large volume of data generated using simulations, experiments and handheld devices. Deep Learning algorithms -- a class of MLDM algorithms -- are applied for automatic feature extraction, and learning non-linear models for unsupervised and supervised algorithms. Naturally, several libraries which support large scale Deep Learning -- such as TensorFlow and Caffe -- have become popular. In this paper, we present novel techniques to accelerate the convergence of Deep Learning algorithms by conducting low overhead removal of redundant neurons -- {\\em apoptosis} of neurons --more » which do not contribute to model learning, during the training phase itself. We provide in-depth theoretical underpinnings of our heuristics (bounding accuracy loss and handling apoptosis of several neuron types), and present the methods to conduct adaptive neuron apoptosis. We implement our proposed heuristics with the recently introduced TensorFlow and using its recently proposed extension with MPI. Our performance evaluation on two difference clusters -- one connected with Intel Haswell multi-core systems, and other with nVIDIA GPUs -- using InfiniBand, indicates the efficacy of the proposed heuristics and implementations. Specifically, we are able to improve the training time for several datasets by 2-3x, while reducing the number of parameters by 30x (4-5x on average) on datasets such as ImageNet classification. For the Higgs Boson dataset, our implementation improves the accuracy (measured by Area Under Curve (AUC)) for classification from 0.88/1 to 0.94/1, while reducing the number of parameters by 3x in comparison to existing literature, while achieving a 2.44x speedup in comparison to the default (no apoptosis) algorithm.« less

  8. Motivated Strategies for Learning in Accelerated Second-Degree Nursing Students.

    PubMed

    El-Banna, Majeda M; Tebbenhoff, Billinda; Whitlow, Malinda; Wyche, Karen Fraser

    Students in a second-degree accelerated BSN program experience a rigorous curriculum and fast-paced introduction to the nursing profession. This study examined the relationships among self-esteem, motivation, learning strategies, demographic characteristics, and academic achievement. The results indicated that all of the students had good self-esteem; some demographic characteristics influenced the type of motivation and learning strategies they endorsed but did not influence their current academic performance.

  9. Challenges of accelerated aging techniques for elastomer lifetime predictions

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

    Gillen, Kenneth T.; Bernstein, R.; Celina, M.

    Elastomers are often degraded when exposed to air or high humidity for extended times (years to decades). Lifetime estimates normally involve extrapolating accelerated aging results made at higher than ambient environments. Several potential problems associated with such studies are reviewed, and experimental and theoretical methods to address them are provided. The importance of verifying time–temperature superposition of degradation data is emphasized as evidence that the overall nature of the degradation process remains unchanged versus acceleration temperature. The confounding effects that occur when diffusion-limited oxidation (DLO) contributes under accelerated conditions are described, and it is shown that the DLO magnitude canmore » be modeled by measurements or estimates of the oxygen permeability coefficient (P Ox) and oxygen consumption rate (Φ). P Ox and Φ measurements can be influenced by DLO, and it is demonstrated how confident values can be derived. In addition, several experimental profiling techniques that screen for DLO effects are discussed. Values of Φ taken from high temperature to temperatures approaching ambient can be used to more confidently extrapolate accelerated aging results for air-aged materials, and many studies now show that Arrhenius extrapolations bend to lower activation energies as aging temperatures are lowered. Furthermore, best approaches for accelerated aging extrapolations of humidity-exposed materials are also offered.« less

  10. Challenges of accelerated aging techniques for elastomer lifetime predictions

    DOE PAGES

    Gillen, Kenneth T.; Bernstein, R.; Celina, M.

    2015-03-01

    Elastomers are often degraded when exposed to air or high humidity for extended times (years to decades). Lifetime estimates normally involve extrapolating accelerated aging results made at higher than ambient environments. Several potential problems associated with such studies are reviewed, and experimental and theoretical methods to address them are provided. The importance of verifying time–temperature superposition of degradation data is emphasized as evidence that the overall nature of the degradation process remains unchanged versus acceleration temperature. The confounding effects that occur when diffusion-limited oxidation (DLO) contributes under accelerated conditions are described, and it is shown that the DLO magnitude canmore » be modeled by measurements or estimates of the oxygen permeability coefficient (P Ox) and oxygen consumption rate (Φ). P Ox and Φ measurements can be influenced by DLO, and it is demonstrated how confident values can be derived. In addition, several experimental profiling techniques that screen for DLO effects are discussed. Values of Φ taken from high temperature to temperatures approaching ambient can be used to more confidently extrapolate accelerated aging results for air-aged materials, and many studies now show that Arrhenius extrapolations bend to lower activation energies as aging temperatures are lowered. Furthermore, best approaches for accelerated aging extrapolations of humidity-exposed materials are also offered.« less

  11. Incorporating active-learning techniques and competency assessment into a critical care elective course.

    PubMed

    Malcom, Daniel R; Hibbs, Jennifer L

    2012-09-10

    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. 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. 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. A critical care elective course resulted in significantly improved competency in critical care and was well-received by students.

  12. Robert's Rules for Optimal Learning: Model Development, Field Testing, Implications!

    ERIC Educational Resources Information Center

    McGinty, Robert L.

    The value of accelerated learning techniques developed by the national organization for Suggestive Accelerated Learning Techniques (SALT) was tested in a study using Administrative Policy students taking the capstone course in the Eastern Washington University School of Business. Educators have linked the brain and how it functions to various…

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

    ERIC Educational Resources Information Center

    Baenen, Nancy; Yaman, Kimberly

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

  14. 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…

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

    PubMed

    Kim, Lok-Won

    2018-05-01

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

  16. 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…

  17. Storytelling: a teaching-learning technique.

    PubMed

    Geanellos, R

    1996-03-01

    Nurses' stories, arising from the practice world, reconstruct the essence of experience as lived and provide vehicles for learning about nursing. The learning process is forwarded by combining storytelling and reflection. Reflection represents an active, purposive, contemplative and deliberative approach to learning through which learners create meaning from the learning experience. The combination of storytelling and reflection allows the creation of links between the materials at hand and prior and future learning. As a teaching-learning technique storytelling engages learners; organizes information; allows exploration of shared lived experiences without the demands, responsibilities and consequences of practice; facilitates remembering; enhances discussion, problem posing and problem solving; and aids understanding of what it is to nurse and to be a nurse.

  18. 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…

  19. 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).

  20. Accelerating learning for pro-poor health markets.

    PubMed

    Bennett, Sara; Lagomarsino, Gina; Knezovich, Jeffrey; Lucas, Henry

    2014-06-24

    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. 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. 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.

  1. 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

  2. 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.

  3. Prostate Cancer Probability Prediction By Machine Learning Technique.

    PubMed

    Jović, Srđan; Miljković, Milica; Ivanović, Miljan; Šaranović, Milena; Arsić, Milena

    2017-11-26

    The main goal of the study was to explore possibility of prostate cancer prediction by machine learning techniques. In order to improve the survival probability of the prostate cancer patients it is essential to make suitable prediction models of the prostate cancer. If one make relevant prediction of the prostate cancer it is easy to create suitable treatment based on the prediction results. Machine learning techniques are the most common techniques for the creation of the predictive models. Therefore in this study several machine techniques were applied and compared. The obtained results were analyzed and discussed. It was concluded that the machine learning techniques could be used for the relevant prediction of prostate cancer.

  4. 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.

  5. 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…

  6. 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

  7. 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.

  8. A technique for accelerating the convergence of restarted GMRES

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

    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.

  9. Collaborative and Cooperative Learning Techniques. Learning Package No. 6.

    ERIC Educational Resources Information Center

    Compton, Joe; Smith, Carl, Comp.

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

  10. 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

  11. 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.

  12. Problem based learning with scaffolding technique on geometry

    NASA Astrophysics Data System (ADS)

    Bayuningsih, A. S.; Usodo, B.; Subanti, S.

    2018-05-01

    Geometry as one of the branches of mathematics has an important role in the study of mathematics. This research aims to explore the effectiveness of Problem Based Learning (PBL) with scaffolding technique viewed from self-regulation learning toward students’ achievement learning in mathematics. The research data obtained through mathematics learning achievement test and self-regulated learning (SRL) questionnaire. This research employed quasi-experimental research. The subjects of this research are students of the junior high school in Banyumas Central Java. The result of the research showed that problem-based learning model with scaffolding technique is more effective to generate students’ mathematics learning achievement than direct learning (DL). This is because in PBL model students are more able to think actively and creatively. The high SRL category student has better mathematic learning achievement than middle and low SRL categories, and then the middle SRL category has better than low SRL category. So, there are interactions between learning model with self-regulated learning in increasing mathematic learning achievement.

  13. Acceleration of saddle-point searches with machine learning

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

    Peterson, Andrew A., E-mail: andrew-peterson@brown.edu

    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 numbermore » 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.« less

  14. Accelerating what works: using qualitative research methods in developing a change package for a learning collaborative.

    PubMed

    Sorensen, Asta V; Bernard, Shulamit L

    2012-02-01

    Learning (quality improvement) collaboratives are effective vehicles for driving coordinated organizational improvements. A central element of a learning collaborative is the change package-a catalogue of strategies, change concepts, and action steps that guide participants in their improvement efforts. Despite a vast literature describing learning collaboratives, little to no information is available on how the guiding strategies, change concepts, and action items are identified and developed to a replicable and actionable format that can be used to make measurable improvements within participating organizations. The process for developing the change package for the Health Resources and Services Administration's (HRSA) Patient Safety and Clinical Pharmacy Services Collaborative entailed environmental scan and identification of leading practices, case studies, interim debriefing meetings, data synthesis, and a technical expert panel meeting. Data synthesis involved end-of-day debriefings, systematic qualitative analyses, and the use of grounded theory and inductive data analysis techniques. This approach allowed systematic identification of innovative patient safety and clinical pharmacy practices that could be adopted in diverse environments. A case study approach enabled the research team to study practices in their natural environments. Use of grounded theory and inductive data analysis techniques enabled identification of strategies, change concepts, and actionable items that might not have been captured using different approaches. Use of systematic processes and qualitative methods in identification and translation of innovative practices can greatly accelerate the diffusion of innovations and practice improvements. This approach is effective whether or not an individual organization is part of a learning collaborative.

  15. Exploring the Earth Using Deep Learning Techniques

    NASA Astrophysics Data System (ADS)

    Larraondo, P. R.; Evans, B. J. K.; Antony, J.

    2016-12-01

    Research using deep neural networks have significantly matured in recent times, and there is now a surge in interest to apply such methods to Earth systems science and the geosciences. When combined with Big Data, we believe there are opportunities for significantly transforming a number of areas relevant to researchers and policy makers. In particular, by using a combination of data from a range of satellite Earth observations as well as computer simulations from climate models and reanalysis, we can gain new insights into the information that is locked within the data. Global geospatial datasets describe a wide range of physical and chemical parameters, which are mostly available using regular grids covering large spatial and temporal extents. This makes them perfect candidates to apply deep learning methods. So far, these techniques have been successfully applied to image analysis through the use of convolutional neural networks. However, this is only one field of interest, and there is potential for many more use cases to be explored. The deep learning algorithms require fast access to large amounts of data in the form of tensors and make intensive use of CPU in order to train its models. The Australian National Computational Infrastructure (NCI) has recently augmented its Raijin 1.2 PFlop supercomputer with hardware accelerators. Together with NCI's 3000 core high performance OpenStack cloud, these computational systems have direct access to NCI's 10+ PBytes of datasets and associated Big Data software technologies (see http://geonetwork.nci.org.au/ and http://nci.org.au/systems-services/national-facility/nerdip/). To effectively use these computing infrastructures requires that both the data and software are organised in a way that readily supports the deep learning software ecosystem. Deep learning software, such as the open source TensorFlow library, has allowed us to demonstrate the possibility of generating geospatial models by combining information from

  16. Accelerator-based neutrino oscillation experiments

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

    Harris, Deborah A.; /Fermilab

    2007-12-01

    Neutrino oscillations were first discovered by experiments looking at neutrinos coming from extra-terrestrial sources, namely the sun and the atmosphere, but we will be depending on earth-based sources to take many of the next steps in this field. This article describes what has been learned so far from accelerator-based neutrino oscillation experiments, and then describe very generally what the next accelerator-based steps are. In section 2 the article discusses how one uses an accelerator to make a neutrino beam, in particular, one made from decays in flight of charged pions. There are several different neutrino detection methods currently in use,more » or under development. In section 3 these are presented, with a description of the general concept, an example of such a detector, and then a brief discussion of the outstanding issues associated with this detection technique. Finally, section 4 describes how the measurements of oscillation probabilities are made. This includes a description of the near detector technique and how it can be used to make the most precise measurements of neutrino oscillations.« less

  17. Opportunities to Create Active Learning Techniques in the Classroom

    ERIC Educational Resources Information Center

    Camacho, Danielle J.; Legare, Jill M.

    2015-01-01

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

  18. Acceleration display system for aircraft zero-gravity research

    NASA Technical Reports Server (NTRS)

    Millis, Marc G.

    1987-01-01

    The features, design, calibration, and testing of Lewis Research Center's acceleration display system for aircraft zero-gravity research are described. Specific circuit schematics and system specifications are included as well as representative data traces from flown trajectories. Other observations learned from developing and using this system are mentioned where appropriate. The system, now a permanent part of the Lewis Learjet zero-gravity program, provides legible, concise, and necessary guidance information enabling pilots to routinely fly accurate zero-gravity trajectories. Regular use of this system resulted in improvements of the Learjet zero-gravity flight techniques, including a technique to minimize later accelerations. Lewis Gates Learjet trajectory data show that accelerations can be reliably sustained within 0.01 g for 5 consecutive seconds, within 0.02 g for 7 consecutive seconds, and within 0.04 g for up to 20 second. Lewis followed the past practices of acceleration measurement, yet focussed on the acceleration displays. Refinements based on flight experience included evolving the ranges, resolutions, and frequency responses to fit the pilot and the Learjet responses.

  19. Neurotechnology to accelerate learning: during marksmanship training.

    PubMed

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

    2012-01-01

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

  20. Acceleration techniques and their impact on arterial input function sampling: Non-accelerated versus view-sharing and compressed sensing sequences.

    PubMed

    Benz, Matthias R; Bongartz, Georg; Froehlich, Johannes M; Winkel, David; Boll, Daniel T; Heye, Tobias

    2018-07-01

    The aim was to investigate the variation of the arterial input function (AIF) within and between various DCE MRI sequences. A dynamic flow-phantom and steady signal reference were scanned on a 3T MRI using fast low angle shot (FLASH) 2d, FLASH3d (parallel imaging factor (P) = P0, P2, P4), volumetric interpolated breath-hold examination (VIBE) (P = P0, P3, P2 × 2, P2 × 3, P3 × 2), golden-angle radial sparse parallel imaging (GRASP), and time-resolved imaging with stochastic trajectories (TWIST). Signal over time curves were normalized and quantitatively analyzed by full width half maximum (FWHM) measurements to assess variation within and between sequences. The coefficient of variation (CV) for the steady signal reference ranged from 0.07-0.8%. The non-accelerated gradient echo FLASH2d, FLASH3d, and VIBE sequences showed low within sequence variation with 2.1%, 1.0%, and 1.6%. The maximum FWHM CV was 3.2% for parallel imaging acceleration (VIBE P2 × 3), 2.7% for GRASP and 9.1% for TWIST. The FWHM CV between sequences ranged from 8.5-14.4% for most non-accelerated/accelerated gradient echo sequences except 6.2% for FLASH3d P0 and 0.3% for FLASH3d P2; GRASP FWHM CV was 9.9% versus 28% for TWIST. MRI acceleration techniques vary in reproducibility and quantification of the AIF. Incomplete coverage of the k-space with TWIST as a representative of view-sharing techniques showed the highest variation within sequences and might be less suited for reproducible quantification of the AIF. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. The Effect of Learning Based on Technology Model and Assessment Technique toward Thermodynamic Learning Achievement

    NASA Astrophysics Data System (ADS)

    Makahinda, T.

    2018-02-01

    The purpose of this research is to find out the effect of learning model based on technology and assessment technique toward thermodynamic achievement by controlling students intelligence. This research is an experimental research. The sample is taken through cluster random sampling with the total respondent of 80 students. The result of the research shows that the result of learning of thermodynamics of students who taught the learning model of environmental utilization is higher than the learning result of student thermodynamics taught by simulation animation, after controlling student intelligence. There is influence of student interaction, and the subject between models of technology-based learning with assessment technique to student learning result of Thermodynamics, after controlling student intelligence. Based on the finding in the lecture then should be used a thermodynamic model of the learning environment with the use of project assessment technique.

  2. Analyzing the Effects of Various Concept Mapping Techniques on Learning Achievement under Different Learning Styles

    ERIC Educational Resources Information Center

    Chiou, Chei-Chang; Lee, Li-Tze; Tien, Li-Chu; Wang, Yu-Min

    2017-01-01

    This study explored the effectiveness of different concept mapping techniques on the learning achievement of senior accounting students and whether achievements attained using various techniques are affected by different learning styles. The techniques are computer-assisted construct-by-self-concept mapping (CACSB), computer-assisted…

  3. Overview of Fabrication Techniques and Lessons Learned with Accelerator Vacuum Windows

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

    Ader, C. R.; McGee, M. W.; Nobrega, L. E.

    Vacuum thin windows have been used in Fermilab's accelerators for decades and typically have been overlooked in terms of their criticality and fragility. Vacuum windows allow beam to pass through while creating a boundary between vacuum and air or high vacuum and low vacuum areas. The design of vacuum windows, including Titanium and Beryllium windows, will be discussed as well as fabrication, testing, and operational concerns. Failure of windows will be reviewed as well as safety approaches to mitigating failures and extending the lifetimes of vacuum windows. Various methods of calculating the strengths of vacuum windows will be explored, includingmore » FEA.« less

  4. Combining Acceleration Techniques for Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction.

    PubMed

    Huang, Hsuan-Ming; Hsiao, Ing-Tsung

    2017-01-01

    Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.

  5. Machine learning strategy for accelerated design of polymer dielectrics

    DOE PAGES

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

    2016-02-15

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

  6. 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…

  7. Learning style preferences of Australian accelerated postgraduate pre-registration nursing students: A cross-sectional survey.

    PubMed

    McKenna, Lisa; Copnell, Beverley; Butler, Ashleigh E; Lau, Rosalind

    2018-01-01

    Graduate entry programs leading to registration are gaining momentum in nursing. These programs attract student cohorts with professional, cultural, gender and age diversity. As a consequence of this diversity, such accelerated programs challenge traditional pedagogical methods used in nursing and require different approaches. To date, however, there has been limited research on the learning styles of students undertaking these programs to inform academics involved in their delivery. Kolb's Experiential Learning model has been used widely in a variety of educational settings because it is based on the theory of experiential learning. More recently VARK (Visual, Aural, Read/write and Kinaesthetic) model has become popular. The aim of this study was to investigate the learning styles of two cohorts of graduate entry nursing students undertaking an accelerated masters-level program. This was a cross-sectional survey of two cohorts of Master of Nursing Practice students enrolled at a large Australian university. The students were more inclined toward converging (practical) and least toward concrete experience (experiencing) learning styles. The majority of students were more inclined toward kinaesthetic and least toward aural learning style. Findings have implications for academics engaged in teaching graduate entry nursing students. Copyright © 2017. Published by Elsevier Ltd.

  8. eLearning techniques supporting problem based learning in clinical simulation.

    PubMed

    Docherty, Charles; Hoy, Derek; Topp, Helena; Trinder, Kathryn

    2005-08-01

    This paper details the results of the first phase of a project using eLearning to support students' learning within a simulated environment. The locus was a purpose built clinical simulation laboratory (CSL) where the School's philosophy of problem based learning (PBL) was challenged through lecturers using traditional teaching methods. a student-centred, problem based approach to the acquisition of clinical skills that used high quality learning objects embedded within web pages, substituting for lecturers providing instruction and demonstration. This encouraged student nurses to explore, analyse and make decisions within the safety of a clinical simulation. Learning was facilitated 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 eLearning techniques can help students acquire clinical skills in the safety of a simulated environment within the context of a problem based learning curriculum.

  9. 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…

  10. 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.

  11. 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…

  12. Learning Programming Technique through Visual Programming Application as Learning Media with Fuzzy Rating

    ERIC Educational Resources Information Center

    Buditjahjanto, I. G. P. Asto; Nurlaela, Luthfiyah; Ekohariadi; Riduwan, Mochamad

    2017-01-01

    Programming technique is one of the subjects at Vocational High School in Indonesia. This subject contains theory and application of programming utilizing Visual Programming. Students experience some difficulties to learn textual learning. Therefore, it is necessary to develop media as a tool to transfer learning materials. The objectives of this…

  13. 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…

  14. 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…

  15. Learning Physics through Project-Based Learning Game Techniques

    ERIC Educational Resources Information Center

    Baran, Medine; Maskan, Abdulkadir; Yasar, Seyma

    2018-01-01

    The aim of the present study, in which Project and game techniques are used together, is to examine the impact of project-based learning games on students' physics achievement. Participants of the study consist of 34 9th grade students (N = 34). The data were collected using achievement tests and a questionnaire. Throughout the applications, the…

  16. 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,…

  17. The Effectiveness of Accelerated Learning on Student Achievement in Developmental Courses Offered at a Rural Community College

    ERIC Educational Resources Information Center

    Floyd, Anika Z.

    2017-01-01

    The purpose of this study was to examine the effect of the accelerated course learning format on student achievement in developmental English and math courses offered at a rural community college. Due to a rise in the number of underprepared students who enroll in community college, some college officials implemented the accelerated course…

  18. Transfer Learning to Accelerate Interface Structure Searches

    NASA Astrophysics Data System (ADS)

    Oda, Hiromi; Kiyohara, Shin; Tsuda, Koji; Mizoguchi, Teruyasu

    2017-12-01

    Interfaces have atomic structures that are significantly different from those in the bulk, and play crucial roles in material properties. The central structures at the interfaces that provide properties have been extensively investigated. However, determination of even one interface structure requires searching for the stable configuration among many thousands of candidates. Here, a powerful combination of machine learning techniques based on kriging and transfer learning (TL) is proposed as a method for unveiling the interface structures. Using the kriging+TL method, thirty-three grain boundaries were systematically determined from 1,650,660 candidates in only 462 calculations, representing an increase in efficiency over conventional all-candidate calculation methods, by a factor of approximately 3,600.

  19. Lessons learned on the Ground Test Accelerator control system

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

    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 tomore » 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.« less

  20. 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…

  1. 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

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

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

    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.

  3. 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.

  4. The application of machine learning techniques in the clinical drug therapy.

    PubMed

    Meng, Huan-Yu; Jin, Wan-Lin; Yan, Cheng-Kai; Yang, Huan

    2018-05-25

    The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adverse drug reaction control. Due to the limited resources, high costs, long duration, and low hit-to-lead ratio in the development of pharmacogenetics and computer technology, machine learning techniques have assisted novel drug development and have gradually received more attention by researchers. According to current research, machine learning techniques are widely applied in the process of the discovery of new drugs and novel drug targets, the decision surrounding proper therapy and drug dose, and the prediction of drug efficacy and adverse drug reactions. In this article, we discussed the history, workflow, and advantages and disadvantages of machine learning techniques in the processes mentioned above. Although the advantages of machine learning techniques are fairly obvious, the application of machine learning techniques is currently limited. With further research, the application of machine techniques in drug development could be much more widespread and could potentially be one of the major methods used in drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  5. Three visual techniques to enhance interprofessional learning.

    PubMed

    Parsell, G; Gibbs, T; Bligh, J

    1998-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Veltri, M.

    2016-09-01

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

  7. Acceleration: It's Elementary

    ERIC Educational Resources Information Center

    Willis, Mariam

    2012-01-01

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

  8. 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…

  9. Imaging and machine learning techniques for diagnosis of Alzheimer's disease.

    PubMed

    Mirzaei, Golrokh; Adeli, Anahita; Adeli, Hojjat

    2016-12-01

    Alzheimer's disease (AD) is a common health problem in elderly people. There has been considerable research toward the diagnosis and early detection of this disease in the past decade. The sensitivity of biomarkers and the accuracy of the detection techniques have been defined to be the key to an accurate diagnosis. This paper presents a state-of-the-art review of the research performed on the diagnosis of AD based on imaging and machine learning techniques. Different segmentation and machine learning techniques used for the diagnosis of AD are reviewed including thresholding, supervised and unsupervised learning, probabilistic techniques, Atlas-based approaches, and fusion of different image modalities. More recent and powerful classification techniques such as the enhanced probabilistic neural network of Ahmadlou and Adeli should be investigated with the goal of improving the diagnosis accuracy. A combination of different image modalities can help improve the diagnosis accuracy rate. Research is needed on the combination of modalities to discover multi-modal biomarkers.

  10. 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…

  11. Effects of Enhancement Techniques on L2 Incidental Vocabulary Learning

    ERIC Educational Resources Information Center

    Duan, Shiping

    2018-01-01

    Enhancement Techniques are conducive to incidental vocabulary learning. This study investigated the effects of two types of enhancement techniques-multiple-choice glosses (MC) and L1 single-gloss (SG) on L2 incidental learning of new words and retention of them. A total of 89 university learners of English as a Foreign Language (EFL) were asked to…

  12. 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.…

  13. Not another boring lecture: engaging learners with active learning techniques.

    PubMed

    Wolff, Margaret; Wagner, Mary Jo; Poznanski, Stacey; Schiller, Jocelyn; Santen, Sally

    2015-01-01

    Core content in Emergency Medicine Residency Programs is traditionally covered in didactic sessions, despite evidence suggesting that learners do not retain a significant portion of what is taught during lectures. We describe techniques that medical educators can use when leading teaching sessions to foster engagement and encourage self-directed learning, based on current literature and evidence about learning. When these techniques are incorporated, sessions can be effective in delivering core knowledge, contextualizing content, and explaining difficult concepts, leading to increased learning. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. 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…

  15. Contemporary machine learning: techniques for practitioners in the physical sciences

    NASA Astrophysics Data System (ADS)

    Spears, Brian

    2017-10-01

    Machine learning is the science of using computers to find relationships in data without explicitly knowing or programming those relationships in advance. Often without realizing it, we employ machine learning every day as we use our phones or drive our cars. Over the last few years, machine learning has found increasingly broad application in the physical sciences. This most often involves building a model relationship between a dependent, measurable output and an associated set of controllable, but complicated, independent inputs. The methods are applicable both to experimental observations and to databases of simulated output from large, detailed numerical simulations. In this tutorial, we will present an overview of current tools and techniques in machine learning - a jumping-off point for researchers interested in using machine learning to advance their work. We will discuss supervised learning techniques for modeling complicated functions, beginning with familiar regression schemes, then advancing to more sophisticated decision trees, modern neural networks, and deep learning methods. Next, we will cover unsupervised learning and techniques for reducing the dimensionality of input spaces and for clustering data. We'll show example applications from both magnetic and inertial confinement fusion. Along the way, we will describe methods for practitioners to help ensure that their models generalize from their training data to as-yet-unseen test data. We will finally point out some limitations to modern machine learning and speculate on some ways that practitioners from the physical sciences may be particularly suited to help. This work was performed by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  16. Evaluation of the marginal fit of metal copings fabricated on three different marginal designs using conventional and accelerated casting techniques: an in vitro study.

    PubMed

    Vaidya, Sharad; Parkash, Hari; Bhargava, Akshay; Gupta, Sharad

    2014-01-01

    Abundant resources and techniques have been used for complete coverage crown fabrication. Conventional investing and casting procedures for phosphate-bonded investments require a 2- to 4-h procedure before completion. Accelerated casting techniques have been used, but may not result in castings with matching marginal accuracy. The study measured the marginal gap and determined the clinical acceptability of single cast copings invested in a phosphate-bonded investment with the use of conventional and accelerated methods. One hundred and twenty cast coping samples were fabricated using conventional and accelerated methods, with three finish lines: Chamfer, shoulder and shoulder with bevel. Sixty copings were prepared with each technique. Each coping was examined with a stereomicroscope at four predetermined sites and measurements of marginal gaps were documented for each. A master chart was prepared for all the data and was analyzed using Statistical Package for the Social Sciences version. Evidence of marginal gap was then evaluated by t-test. Analysis of variance and Post-hoc analysis were used to compare two groups as well as to make comparisons between three subgroups . Measurements recorded showed no statistically significant difference between conventional and accelerated groups. Among the three marginal designs studied, shoulder with bevel showed the best marginal fit with conventional as well as accelerated casting techniques. Accelerated casting technique could be a vital alternative to the time-consuming conventional casting technique. The marginal fit between the two casting techniques showed no statistical difference.

  17. Machine Learning Techniques for Stellar Light Curve Classification

    NASA Astrophysics Data System (ADS)

    Hinners, Trisha A.; Tat, Kevin; Thorp, Rachel

    2018-07-01

    We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time-series data. We preprocessed over 94 GB of Kepler light curves from the Mikulski Archive for Space Telescopes (MAST) to classify according to 10 distinct physical properties using both representation learning and feature engineering approaches. Studies using machine learning in the field have been primarily done on simulated data, making our study one of the first to use real light-curve data for machine learning approaches. We tuned our data using previous work with simulated data as a template and achieved mixed results between the two approaches. Representation learning using a long short-term memory recurrent neural network produced no successful predictions, but our work with feature engineering was successful for both classification and regression. In particular, we were able to achieve values for stellar density, stellar radius, and effective temperature with low error (∼2%–4%) and good accuracy (∼75%) for classifying the number of transits for a given star. The results show promise for improvement for both approaches upon using larger data sets with a larger minority class. This work has the potential to provide a foundation for future tools and techniques to aid in the analysis of astrophysical data.

  18. 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…

  19. 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.

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

    DTIC Science & Technology

    2014-12-19

    pedagogic techniques that are infeasible in the classroom, and they suggest that in some respects technologically intermediated learning can be even better...appropriate for this research (Yin, 1994). We employ multiple techniques for data collection in the field. Foremost, through a unique relationship between...initial interpretations are both grounded firmly in the data and meaningful to organization participants. The Researchers’ relationship with the focal

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

    PubMed

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

    2011-08-01

    The growth of accelerated graduate entry nursing programs has challenged traditional approaches to teaching and learning. To date, limited research has been undertaken in the role of learning preferences, language proficiency and academic performance in accelerated programs. Sixty-two first year accelerated graduate entry nursing students, in a single cohort at a university in the western region of Sydney, Australia, were surveyed to assess their learning preference using the Visual, Aural, Read/write and Kinaesthetic (VARK) learning preference questionnaire, together with sociodemographic data, English language acculturation and perceived academic control. Six months following course commencement, the participant's grade point average (GPA) was studied as a measurement of academic performance. A 93% response rate was achieved. The majority of students (62%) reported preference for multiple approaches to learning with the kinaesthetic sensory mode a significant (p=0.009) predictor of academic performance. Students who spoke only English at home had higher mean scores across two of the four categories of VARK sensory modalities, visual and kinaesthetic compared to those who spoke non-English. Further research is warranted to investigate the reasons why the kinaesthetic sensory mode is a predictor of academic performance and to what extent the VARK mean scores of the four learning preference(s) change with improved English language proficiency. Copyright © 2010 Elsevier Ltd. All rights reserved.

  2. Practising What We Teach: Vocational Teachers Learn to Research through Applying Action Learning Techniques

    ERIC Educational Resources Information Center

    Lasky, Barbara; Tempone, Irene

    2004-01-01

    Action learning techniques are well suited to the teaching of organisation behaviour students because of their flexibility, inclusiveness, openness, and respect for individuals. They are no less useful as a tool for change for vocational teachers, learning, of necessity, to become researchers. Whereas traditional universities have always had a…

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

    ERIC Educational Resources Information Center

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

    2015-01-01

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

  4. Applying 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. Dictionary learning and time sparsity in dynamic MRI.

    PubMed

    Caballero, Jose; Rueckert, Daniel; Hajnal, Joseph V

    2012-01-01

    Sparse representation methods have been shown to tackle adequately the inherent speed limits of magnetic resonance imaging (MRI) acquisition. Recently, learning-based techniques have been used to further accelerate the acquisition of 2D MRI. The extension of such algorithms to dynamic MRI (dMRI) requires careful examination of the signal sparsity distribution among the different dimensions of the data. Notably, the potential of temporal gradient (TG) sparsity in dMRI has not yet been explored. In this paper, a novel method for the acceleration of cardiac dMRI is presented which investigates the potential benefits of enforcing sparsity constraints on patch-based learned dictionaries and TG at the same time. We show that an algorithm exploiting sparsity on these two domains can outperform previous sparse reconstruction techniques.

  6. Prediction of drug synergy in cancer using ensemble-based machine learning techniques

    NASA Astrophysics Data System (ADS)

    Singh, Harpreet; Rana, Prashant Singh; Singh, Urvinder

    2018-04-01

    Drug synergy prediction plays a significant role in the medical field for inhibiting specific cancer agents. It can be developed as a pre-processing tool for therapeutic successes. Examination of different drug-drug interaction can be done by drug synergy score. It needs efficient regression-based machine learning approaches to minimize the prediction errors. Numerous machine learning techniques such as neural networks, support vector machines, random forests, LASSO, Elastic Nets, etc., have been used in the past to realize requirement as mentioned above. However, these techniques individually do not provide significant accuracy in drug synergy score. Therefore, the primary objective of this paper is to design a neuro-fuzzy-based ensembling approach. To achieve this, nine well-known machine learning techniques have been implemented by considering the drug synergy data. Based on the accuracy of each model, four techniques with high accuracy are selected to develop ensemble-based machine learning model. These models are Random forest, Fuzzy Rules Using Genetic Cooperative-Competitive Learning method (GFS.GCCL), Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Dynamic Evolving Neural-Fuzzy Inference System method (DENFIS). Ensembling is achieved by evaluating the biased weighted aggregation (i.e. adding more weights to the model with a higher prediction score) of predicted data by selected models. The proposed and existing machine learning techniques have been evaluated on drug synergy score data. The comparative analysis reveals that the proposed method outperforms others in terms of accuracy, root mean square error and coefficient of correlation.

  7. A preclustering-based ensemble learning technique for acute appendicitis diagnoses.

    PubMed

    Lee, Yen-Hsien; Hu, Paul Jen-Hwa; Cheng, Tsang-Hsiang; Huang, Te-Chia; Chuang, Wei-Yao

    2013-06-01

    Acute appendicitis is a common medical condition, whose effective, timely diagnosis can be difficult. A missed diagnosis not only puts the patient in danger but also requires additional resources for corrective treatments. An acute appendicitis diagnosis constitutes a classification problem, for which a further fundamental challenge pertains to the skewed outcome class distribution of instances in the training sample. A preclustering-based ensemble learning (PEL) technique aims to address the associated imbalanced sample learning problems and thereby support the timely, accurate diagnosis of acute appendicitis. The proposed PEL technique employs undersampling to reduce the number of majority-class instances in a training sample, uses preclustering to group similar majority-class instances into multiple groups, and selects from each group representative instances to create more balanced samples. The PEL technique thereby reduces potential information loss from random undersampling. It also takes advantage of ensemble learning to improve performance. We empirically evaluate this proposed technique with 574 clinical cases obtained from a comprehensive tertiary hospital in southern Taiwan, using several prevalent techniques and a salient scoring system as benchmarks. The comparative results show that PEL is more effective and less biased than any benchmarks. The proposed PEL technique seems more sensitive to identifying positive acute appendicitis than the commonly used Alvarado scoring system and exhibits higher specificity in identifying negative acute appendicitis. In addition, the sensitivity and specificity values of PEL appear higher than those of the investigated benchmarks that follow the resampling approach. Our analysis suggests PEL benefits from the more representative majority-class instances in the training sample. According to our overall evaluation results, PEL records the best overall performance, and its area under the curve measure reaches 0.619. The

  8. Current Developments in Machine Learning Techniques in Biological Data Mining.

    PubMed

    Dumancas, Gerard G; Adrianto, Indra; Bello, Ghalib; Dozmorov, Mikhail

    2017-01-01

    This supplement is intended to focus on the use of machine learning techniques to generate meaningful information on biological data. This supplement under Bioinformatics and Biology Insights aims to provide scientists and researchers working in this rapid and evolving field with online, open-access articles authored by leading international experts in this field. Advances in the field of biology have generated massive opportunities to allow the implementation of modern computational and statistical techniques. Machine learning methods in particular, a subfield of computer science, have evolved as an indispensable tool applied to a wide spectrum of bioinformatics applications. Thus, it is broadly used to investigate the underlying mechanisms leading to a specific disease, as well as the biomarker discovery process. With a growth in this specific area of science comes the need to access up-to-date, high-quality scholarly articles that will leverage the knowledge of scientists and researchers in the various applications of machine learning techniques in mining biological data.

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

    PubMed

    Wiles, Amy M

    2016-07-08

    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. © 2016 The International Union of Biochemistry and Molecular Biology.

  10. Accelerated Learning: Undergraduate Research Experiences at the Texas A&M Cyclotron Institute

    NASA Astrophysics Data System (ADS)

    Yennello, S. J.

    The Texas A&M Cyclotron Institute (TAMU CI) has had an NSF funded Research Experiences for Undergraduates program since 2004. Each summer about a dozen students from across the country join us for the 10-week program. They are each imbedded in one of the research groups of the TAMU CI and given their own research project. While the main focus of their effort is their individual research project, we also have other activities to broaden their experience. For instance, one of those activities has been involvement in a dedicated group experiment. Because not every experimental group will run during those 10 weeks and the fact that some of the students are in theory research groups, a group research experience allows everyone to actually be involved in an experiment using the accelerator. In stark contrast to the REU students' very focused experience during the summer, Texas A&M undergraduates can be involved in research projects at the Cyclotron throughout the year, often for multiple years. This extended exposure enables Texas A&M students to have a learning experience that cannot be duplicated without a local accelerator. The motivation for the REU program was to share this accelerator experience with students who do not have that opportunity at their home institution.

  11. Encouraging junior community netball players to learn correct safe landing technique.

    PubMed

    White, Peta E; Ullah, Shahid; Donaldson, Alex; Otago, Leonie; Saunders, Natalie; Romiti, Maria; Finch, Caroline F

    2012-01-01

    Behavioural factors and beliefs are important determinants of the adoption of sports injury interventions. This study aimed to understand behavioural factors associated with junior community netball players' intentions to learn correct landing technique during coach-led training sessions, proposed as a means of reducing their risk of lower limb injury. Cross-sectional survey. 287 female players from 58 junior netball teams in the 2007/2008-summer competition completed a 13-item questionnaire developed from the Theory of Planned Behaviour (TPB). This assessed players' attitudes (four items), subjective norms (four), perceived behavioural control (four) and intentions (one) around the safety behaviour of learning correct landing technique at netball training. All items were rated on a seven-point bipolar scale. Cluster-adjusted logistic regression was used to assess which TPB constructs were most associated with strong intentions. Players had positive intentions and attitudes towards learning safe landing technique and perceived positive social pressure from significant others. They also perceived themselves to have considerable control over engaging (or not) in this behaviour. Players' attitudes (p<0.001) and subjective norms (p<0.001), but not perceived behavioural control (p=0.49), were associated with strong intentions to learn correct landing technique at training. Injury prevention implementation strategies aimed at maximising junior players' participation in correct landing training programs should emphasise the benefits of learning correct landing technique (i.e. change attitudes) and involve significant others and role models whom junior players admire (i.e. capitalise on social norms) in the promotion of such programs. Copyright © 2011 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  12. The training and learning process of transseptal puncture using a modified technique.

    PubMed

    Yao, Yan; Ding, Ligang; Chen, Wensheng; Guo, Jun; Bao, Jingru; Shi, Rui; Huang, Wen; Zhang, Shu; Wong, Tom

    2013-12-01

    As the transseptal (TS) puncture has become an integral part of many types of cardiac interventional procedures, its technique that was initial reported for measurement of left atrial pressure in 1950s, continue to evolve. Our laboratory adopted a modified technique which uses only coronary sinus catheter as the landmark to accomplishing TS punctures under fluoroscopy. The aim of this study is prospectively to evaluate the training and learning process for TS puncture guided by this modified technique. Guided by the training protocol, TS puncture was performed in 120 consecutive patients by three trainees without previous personal experience in TS catheterization and one experienced trainer as a controller. We analysed the following parameters: one puncture success rate, total procedure time, fluoroscopic time, and radiation dose. The learning curve was analysed using curve-fitting methodology. The first attempt at TS crossing was successful in 74 (82%), a second attempt was successful in 11 (12%), and 5 patients failed to puncture the interatrial septal finally. The average starting process time was 4.1 ± 0.8 min, and the estimated mean learning plateau was 1.2 ± 0.2 min. The estimated mean learning rate for process time was 25 ± 3 cases. Important aspects of learning curve can be estimated by fitting inverse curves for TS puncture. The study demonstrated that this technique was a simple, safe, economic, and effective approach for learning of TS puncture. Base on the statistical analysis, approximately 29 TS punctures will be needed for trainee to pass the steepest area of learning curve.

  13. Student knowledge and confidence in an elective clinical toxicology course using active-learning techniques.

    PubMed

    Thomas, Michael C; Macias-Moriarity, Liliairica Z

    2014-06-17

    To measure changes in students' knowledge and confidence scores after completing an elective clinical toxicology course in an accelerated doctor of pharmacy (PharmD) program. 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. 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. 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.

  14. Machine learning modelling for predicting soil liquefaction susceptibility

    NASA Astrophysics Data System (ADS)

    Samui, P.; Sitharam, T. G.

    2011-01-01

    This study describes two machine learning techniques applied to predict liquefaction susceptibility of soil based on the standard penetration test (SPT) data from the 1999 Chi-Chi, Taiwan earthquake. The first machine learning technique which uses Artificial Neural Network (ANN) based on multi-layer perceptions (MLP) that are trained with Levenberg-Marquardt backpropagation algorithm. The second machine learning technique uses the Support Vector machine (SVM) that is firmly based on the theory of statistical learning theory, uses classification technique. ANN and SVM have been developed to predict liquefaction susceptibility using corrected SPT [(N1)60] and cyclic stress ratio (CSR). Further, an attempt has been made to simplify the models, requiring only the two parameters [(N1)60 and peck ground acceleration (amax/g)], for the prediction of liquefaction susceptibility. The developed ANN and SVM models have also been applied to different case histories available globally. The paper also highlights the capability of the SVM over the ANN models.

  15. 76 FR 33305 - Medicare Program; Accelerated Development Sessions for Accountable Care Organizations-June 20, 21...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-08

    ... as accelerated development sessions (ADSs) instead of accelerated development learning sessions... Sessions'' is corrected to read ``Accelerated Development Learning Sessions''. (2) In the SUMMARY, the... first of four accelerated development learning sessions (ADLSs) that will provide executives with the...

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

    ERIC Educational Resources Information Center

    Khan, S.

    2011-01-01

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

  17. Application of machine learning techniques to lepton energy reconstruction in water Cherenkov detectors

    NASA Astrophysics Data System (ADS)

    Drakopoulou, E.; Cowan, G. A.; Needham, M. D.; Playfer, S.; Taani, M.

    2018-04-01

    The application of machine learning techniques to the reconstruction of lepton energies in water Cherenkov detectors is discussed and illustrated for TITUS, a proposed intermediate detector for the Hyper-Kamiokande experiment. It is found that applying these techniques leads to an improvement of more than 50% in the energy resolution for all lepton energies compared to an approach based upon lookup tables. Machine learning techniques can be easily applied to different detector configurations and the results are comparable to likelihood-function based techniques that are currently used.

  18. Quantitative elemental analysis of an industrial mineral talc, using accelerator-based analytical technique

    NASA Astrophysics Data System (ADS)

    Olabanji, S. O.; Ige, A. O.; Mazzoli, C.; Ceccato, D.; Ajayi, E. O. B.; De Poli, M.; Moschini, G.

    2005-10-01

    Accelerator-based technique of PIXE was employed for the determination of the elemental concentration of an industrial mineral, talc. Talc is a very versatile mineral in industries with several applications. Due to this, there is a need to know its constituents to ensure that the workers are not exposed to health risks. Besides, microscopic tests on some talc samples in Nigeria confirm that they fall within the BP British Pharmacopoeia standard for tablet formation. However, for these samples to become a local source of raw material for pharmaceutical grade talc, the precise elemental compositions should be established which is the focus of this work. Proton beam produced by the 2.5 MV AN 2000 Van de Graaff accelerator at INFN, LNL, Legnaro, Padova, Italy was used for the PIXE measurements. The results which show the concentration of different elements in the talc samples, their health implications and metabolic roles are presented and discussed.

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

    ERIC Educational Resources Information Center

    Takemura, Atsushi

    2016-01-01

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

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

    PubMed

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

    2008-01-01

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

  1. Comparison of Acid Titration, Conductivity, Flame Photometry, ICP-MS, and Accelerated Lamellae Formation Techniques in Determining Glass Vial Quality.

    PubMed

    Fujimori, Kiyoshi; Lee, Hans; Sloey, Christopher; Ricci, Margaret S; Wen, Zai-Qing; Phillips, Joseph; Nashed-Samuel, Yasser

    2016-01-01

    Certain types of glass vials used as primary containers for liquid formulations of biopharmaceutical drug products have been observed with delamination that produced small glass like flakes termed lamellae under certain conditions during storage. The cause of this delamination is in part related to the glass surface defects, which renders the vials susceptible to flaking, and lamellae are formed during the high-temperature melting and annealing used for vial fabrication and shaping. The current European Pharmacopoeia method to assess glass vial quality utilizes acid titration of vial extract pools to determine hydrolytic resistance or alkalinity. Four alternative techniques with improved throughput, convenience, and/or comprehension were examined by subjecting seven lots of vials to analysis by all techniques. The first three new techniques of conductivity, flame photometry, and inductively coupled plasma mass spectrometry measured the same sample pools as acid titration. All three showed good correlation with alkalinity: conductivity (R(2) = 0.9951), flame photometry sodium (R(2) = 0.9895), and several elements by inductively coupled plasma mass spectrometry [(sodium (R(2) = 0.9869), boron (R(2) = 0.9796), silicon (R(2) = 0.9426), total (R(2) = 0.9639)]. The fourth technique processed the vials under conditions that promote delamination, termed accelerated lamellae formation, and then inspected those vials visually for lamellae. The visual inspection results without the lot with different processing condition correlated well with alkalinity (R(2) = 0.9474). Due to vial processing differences affecting alkalinity measurements and delamination propensity differently, the ratio of silicon and sodium measurements from inductively coupled plasma mass spectrometry was the most informative technique to assess overall vial quality and vial propensity for lamellae formation. The other techniques of conductivity, flame photometry, and accelerated lamellae formation

  2. 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.

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

    PubMed

    Özdemir, Ahmet Turan; Barshan, Billur

    2014-06-18

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  5. 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…

  6. 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,…

  7. Source-to-accelerator quadrupole matching section for a compact linear accelerator

    NASA Astrophysics Data System (ADS)

    Seidl, P. A.; Persaud, A.; Ghiorso, W.; Ji, Q.; Waldron, W. L.; Lal, A.; Vinayakumar, K. B.; Schenkel, T.

    2018-05-01

    Recently, we presented a new approach for a compact radio-frequency (RF) accelerator structure and demonstrated the functionality of the individual components: acceleration units and focusing elements. In this paper, we combine these units to form a working accelerator structure: a matching section between the ion source extraction grids and the RF-acceleration unit and electrostatic focusing quadrupoles between successive acceleration units. The matching section consists of six electrostatic quadrupoles (ESQs) fabricated using 3D-printing techniques. The matching section enables us to capture more beam current and to match the beam envelope to conditions for stable transport in an acceleration lattice. We present data from an integrated accelerator consisting of the source, matching section, and an ESQ doublet sandwiched between two RF-acceleration units.

  8. Simultaneous Multislice Echo Planar Imaging With Blipped Controlled Aliasing in Parallel Imaging Results in Higher Acceleration: A Promising Technique for Accelerated Diffusion Tensor Imaging of Skeletal Muscle.

    PubMed

    Filli, Lukas; Piccirelli, Marco; Kenkel, David; Guggenberger, Roman; Andreisek, Gustav; Beck, Thomas; Runge, Val M; Boss, Andreas

    2015-07-01

    The aim of this study was to investigate the feasibility of accelerated diffusion tensor imaging (DTI) of skeletal muscle using echo planar imaging (EPI) applying simultaneous multislice excitation with a blipped controlled aliasing in parallel imaging results in higher acceleration unaliasing technique. After federal ethics board approval, the lower leg muscles of 8 healthy volunteers (mean [SD] age, 29.4 [2.9] years) were examined in a clinical 3-T magnetic resonance scanner using a 15-channel knee coil. The EPI was performed at a b value of 500 s/mm2 without slice acceleration (conventional DTI) as well as with 2-fold and 3-fold acceleration. Fractional anisotropy (FA) and mean diffusivity (MD) were measured in all 3 acquisitions. Fiber tracking performance was compared between the acquisitions regarding the number of tracks, average track length, and anatomical precision using multivariate analysis of variance and Mann-Whitney U tests. Acquisition time was 7:24 minutes for conventional DTI, 3:53 minutes for 2-fold acceleration, and 2:38 minutes for 3-fold acceleration. Overall FA and MD values ranged from 0.220 to 0.378 and 1.595 to 1.829 mm2/s, respectively. Two-fold acceleration yielded similar FA and MD values (P ≥ 0.901) and similar fiber tracking performance compared with conventional DTI. Three-fold acceleration resulted in comparable MD (P = 0.199) but higher FA values (P = 0.006) and significantly impaired fiber tracking in the soleus and tibialis anterior muscles (number of tracks, P < 0.001; anatomical precision, P ≤ 0.005). Simultaneous multislice EPI with blipped controlled aliasing in parallel imaging results in higher acceleration can remarkably reduce acquisition time in DTI of skeletal muscle with similar image quality and quantification accuracy of diffusion parameters. This may increase the clinical applicability of muscle anisotropy measurements.

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

    PubMed

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

    2018-05-24

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

  10. 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…

  11. Precision Parameter Estimation and Machine Learning

    NASA Astrophysics Data System (ADS)

    Wandelt, Benjamin D.

    2008-12-01

    I discuss the strategy of ``Acceleration by Parallel Precomputation and Learning'' (AP-PLe) that can vastly accelerate parameter estimation in high-dimensional parameter spaces and costly likelihood functions, using trivially parallel computing to speed up sequential exploration of parameter space. This strategy combines the power of distributed computing with machine learning and Markov-Chain Monte Carlo techniques efficiently to explore a likelihood function, posterior distribution or χ2-surface. This strategy is particularly successful in cases where computing the likelihood is costly and the number of parameters is moderate or large. We apply this technique to two central problems in cosmology: the solution of the cosmological parameter estimation problem with sufficient accuracy for the Planck data using PICo; and the detailed calculation of cosmological helium and hydrogen recombination with RICO. Since the APPLe approach is designed to be able to use massively parallel resources to speed up problems that are inherently serial, we can bring the power of distributed computing to bear on parameter estimation problems. We have demonstrated this with the CosmologyatHome project.

  12. 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.

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

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

    Kojima, A., E-mail: kojima.atsushi@jaea.go.jp; Hanada, M.; Tobari, H.

    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 voltagemore » 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.« less

  14. 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,…

  15. 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…

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  18. Suggestive, Accelerative Learning and Teaching: A Manual of Classroom Procedures Based on the Lozanov Method.

    ERIC Educational Resources Information Center

    Schuster, Donald H.; And Others

    The Suggestive Accelerative Learning and Teaching Method uses aspects of suggestion and unusual styles of presenting material to accelerate classroom learning. The essence of this technique is the use of a combination of physical relaxation exercises, mental concentration and suggestive principles to strengthen a person's ego and expand his memory…

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

    PubMed

    Song, Min; Yu, Hwanjo; Han, Wook-Shin

    2011-11-24

    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. 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. 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. Our system is a novel, state-of-the-art technique for efficiently extracting protein-protein interaction pairs.

  20. The Louisiana Accelerated Schools Project First Year Evaluation Report.

    ERIC Educational Resources Information Center

    St. John, Edward P.; And Others

    The Louisiana Accelerated Schools Project (LASP) is a statewide network of schools that are changing from the traditional mode of schooling for at-risk students, which stresses remediation, to one of acceleration, which stresses accelerated learning for all students. The accelerated schools process provides a systematic approach to the…

  1. Learning to learn causal models.

    PubMed

    Kemp, Charles; Goodman, Noah D; Tenenbaum, Joshua B

    2010-09-01

    Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. Copyright © 2010 Cognitive Science Society, Inc.

  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. 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…

  4. 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.

  5. Accelerating simultaneous algebraic reconstruction technique with motion compensation using CUDA-enabled GPU.

    PubMed

    Pang, Wai-Man; Qin, Jing; Lu, Yuqiang; Xie, Yongming; Chui, Chee-Kong; Heng, Pheng-Ann

    2011-03-01

    To accelerate the simultaneous algebraic reconstruction technique (SART) with motion compensation for speedy and quality computed tomography reconstruction by exploiting CUDA-enabled GPU. Two core techniques are proposed to fit SART into the CUDA architecture: (1) a ray-driven projection along with hardware trilinear interpolation, and (2) a voxel-driven back-projection that can avoid redundant computation by combining CUDA shared memory. We utilize the independence of each ray and voxel on both techniques to design CUDA kernel to represent a ray in the projection and a voxel in the back-projection respectively. Thus, significant parallelization and performance boost can be achieved. For motion compensation, we rectify each ray's direction during the projection and back-projection stages based on a known motion vector field. Extensive experiments demonstrate the proposed techniques can provide faster reconstruction without compromising image quality. The process rate is nearly 100 projections s (-1), and it is about 150 times faster than a CPU-based SART. The reconstructed image is compared against ground truth visually and quantitatively by peak signal-to-noise ratio (PSNR) and line profiles. We further evaluate the reconstruction quality using quantitative metrics such as signal-to-noise ratio (SNR) and mean-square-error (MSE). All these reveal that satisfactory results are achieved. The effects of major parameters such as ray sampling interval and relaxation parameter are also investigated by a series of experiments. A simulated dataset is used for testing the effectiveness of our motion compensation technique. The results demonstrate our reconstructed volume can eliminate undesirable artifacts like blurring. Our proposed method has potential to realize instantaneous presentation of 3D CT volume to physicians once the projection data are acquired.

  6. Predictive coding accelerates word recognition and learning in the early stages of language development.

    PubMed

    Ylinen, Sari; Bosseler, Alexis; Junttila, Katja; Huotilainen, Minna

    2017-11-01

    The ability to predict future events in the environment and learn from them is a fundamental component of adaptive behavior across species. Here we propose that inferring predictions facilitates speech processing and word learning in the early stages of language development. Twelve- and 24-month olds' electrophysiological brain responses to heard syllables are faster and more robust when the preceding word context predicts the ending of a familiar word. For unfamiliar, novel word forms, however, word-expectancy violation generates a prediction error response, the strength of which significantly correlates with children's vocabulary scores at 12 months. These results suggest that predictive coding may accelerate word recognition and support early learning of novel words, including not only the learning of heard word forms but also their mapping to meanings. Prediction error may mediate learning via attention, since infants' attention allocation to the entire learning situation in natural environments could account for the link between prediction error and the understanding of word meanings. On the whole, the present results on predictive coding support the view that principles of brain function reported across domains in humans and non-human animals apply to language and its development in the infant brain. A video abstract of this article can be viewed at: http://hy.fi/unitube/video/e1cbb495-41d8-462e-8660-0864a1abd02c. [Correction added on 27 January 2017, after first online publication: The video abstract link was added.]. © 2016 John Wiley & Sons Ltd.

  7. 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.

  8. 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

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

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

    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 canmore » 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.« less

  10. Semantics of User Interface for Image Retrieval: Possibility Theory and Learning Techniques.

    ERIC Educational Resources Information Center

    Crehange, M.; And Others

    1989-01-01

    Discusses the need for a rich semantics for the user interface in interactive image retrieval and presents two methods for building such interfaces: possibility theory applied to fuzzy data retrieval, and a machine learning technique applied to learning the user's deep need. Prototypes developed using videodisks and knowledge-based software are…

  11. Reward prediction error signal enhanced by striatum-amygdala interaction explains the acceleration of probabilistic reward learning by emotion.

    PubMed

    Watanabe, Noriya; Sakagami, Masamichi; Haruno, Masahiko

    2013-03-06

    Learning does not only depend on rationality, because real-life learning cannot be isolated from emotion or social factors. Therefore, it is intriguing to determine how emotion changes learning, and to identify which neural substrates underlie this interaction. Here, we show that the task-independent presentation of an emotional face before a reward-predicting cue increases the speed of cue-reward association learning in human subjects compared with trials in which a neutral face is presented. This phenomenon was attributable to an increase in the learning rate, which regulates reward prediction errors. Parallel to these behavioral findings, functional magnetic resonance imaging demonstrated that presentation of an emotional face enhanced reward prediction error (RPE) signal in the ventral striatum. In addition, we also found a functional link between this enhanced RPE signal and increased activity in the amygdala following presentation of an emotional face. Thus, this study revealed an acceleration of cue-reward association learning by emotion, and underscored a role of striatum-amygdala interactions in the modulation of the reward prediction errors by emotion.

  12. GPU-accelerated computational tool for studying the effectiveness of asteroid disruption techniques

    NASA Astrophysics Data System (ADS)

    Zimmerman, Ben J.; Wie, Bong

    2016-10-01

    This paper presents the development of a new Graphics Processing Unit (GPU) accelerated computational tool for asteroid disruption techniques. Numerical simulations are completed using the high-order spectral difference (SD) method. Due to the compact nature of the SD method, it is well suited for implementation with the GPU architecture, hence solutions are generated at orders of magnitude faster than the Central Processing Unit (CPU) counterpart. A multiphase model integrated with the SD method is introduced, and several asteroid disruption simulations are conducted, including kinetic-energy impactors, multi-kinetic energy impactor systems, and nuclear options. Results illustrate the benefits of using multi-kinetic energy impactor systems when compared to a single impactor system. In addition, the effectiveness of nuclear options is observed.

  13. 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…

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2017-03-01

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

  16. 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…

  17. 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…

  18. Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks

    NASA Astrophysics Data System (ADS)

    Zhang, Huibin; Wang, Yuqiao; Chen, Haoran; Zhao, Yongli; Zhang, Jie

    2017-12-01

    In software defined optical networks (SDON), the centralized control plane may encounter numerous intrusion threatens which compromise the security level of provisioned services. In this paper, the issue of control plane security is studied and two machine-learning-based control plane intrusion detection techniques are proposed for SDON with properly selected features such as bandwidth, route length, etc. We validate the feasibility and efficiency of the proposed techniques by simulations. Results show an accuracy of 83% for intrusion detection can be achieved with the proposed machine-learning-based control plane intrusion detection techniques.

  19. Technique Feature Analysis or Involvement Load Hypothesis: Estimating Their Predictive Power in Vocabulary Learning.

    PubMed

    Gohar, Manoochehr Jafari; Rahmanian, Mahboubeh; Soleimani, Hassan

    2018-02-05

    Vocabulary learning has always been a great concern and has attracted the attention of many researchers. Among the vocabulary learning hypotheses, involvement load hypothesis and technique feature analysis have been proposed which attempt to bring some concepts like noticing, motivation, and generation into focus. In the current study, 90 high proficiency EFL students were assigned into three vocabulary tasks of sentence making, composition, and reading comprehension in order to examine the power of involvement load hypothesis and technique feature analysis frameworks in predicting vocabulary learning. It was unraveled that involvement load hypothesis cannot be a good predictor, and technique feature analysis was a good predictor in pretest to posttest score change and not in during-task activity. The implications of the results will be discussed in the light of preparing vocabulary tasks.

  20. Characteristics of effective summer learning programs in practice.

    PubMed

    Bell, Susanne R; Carrillo, Natalie

    2007-01-01

    The Center for Summer Learning examined various summer program models and found that there are nine characteristics that provide a framework for effective summer programs. In this chapter, the authors demonstrate how effective practices lead to positive results for young people. The nine characteristics of effective summer learning programs are (1) accelerating learning, (2) youth development, (3) proactive approach to summer learning, (4) leadership, (5) advanced planning, (6) staff development, (7) strategic partnerships, (8) evaluation and commitment to program improvement, and (9) sustainability and cost-effectiveness. These characteristics are divided into two sections. The first three characteristics address a program's approach to learning. Summer instructional techniques are most effective when academic learning is woven into enrichment activities and youth development. The second section covers program infrastructure to ensure the organization achieves and maintains quality programming. The nine characteristics complement each other to ensure a strong program that works to prevent summer learning loss and narrow the achievement gap. To demonstrate the variety of high-quality programs that include the nine characteristics, thirteen program profiles at the conclusion of the chapter each highlight one of the characteristics. These profiles show the various approaches that different summer programs have developed to accelerate academic achievement and promote positive development for young people in their communities.

  1. 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.

  2. 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.…

  3. 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.

  4. 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.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

    ERIC Educational Resources Information Center

    Nelson, Carol; Smith, Carl, Comp.

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

  8. Accelerated construction

    DOT National Transportation Integrated Search

    2004-01-01

    Accelerated Construction Technology Transfer (ACTT) is a strategic process that uses various innovative techniques, strategies, and technologies to minimize actual construction time, while enhancing quality and safety on today's large, complex multip...

  9. The colloquial approach: An active learning technique

    NASA Astrophysics Data System (ADS)

    Arce, Pedro

    1994-09-01

    This paper addresses the very important problem of the effectiveness of teaching methodologies in fundamental engineering courses such as transport phenomena. An active learning strategy, termed the colloquial approach, is proposed in order to increase student involvement in the learning process. This methodology is a considerable departure from traditional methods that use solo lecturing. It is based on guided discussions, and it promotes student understanding of new concepts by directing the student to construct new ideas by building upon the current knowledge and by focusing on key cases that capture the essential aspects of new concepts. The colloquial approach motivates the student to participate in discussions, to develop detailed notes, and to design (or construct) his or her own explanation for a given problem. This paper discusses the main features of the colloquial approach within the framework of other current and previous techniques. Problem-solving strategies and the need for new textbooks and for future investigations based on the colloquial approach are also outlined.

  10. 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.

  11. 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.

  12. 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…

  13. 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.

  14. 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

  15. Machine learning and microsimulation techniques on the prognosis of dementia: A systematic literature review.

    PubMed

    Dallora, Ana Luiza; Eivazzadeh, Shahryar; Mendes, Emilia; Berglund, Johan; Anderberg, Peter

    2017-01-01

    Dementia is a complex disorder characterized by poor outcomes for the patients and high costs of care. After decades of research little is known about its mechanisms. Having prognostic estimates about dementia can help researchers, patients and public entities in dealing with this disorder. Thus, health data, machine learning and microsimulation techniques could be employed in developing prognostic estimates for dementia. The goal of this paper is to present evidence on the state of the art of studies investigating and the prognosis of dementia using machine learning and microsimulation techniques. To achieve our goal we carried out a systematic literature review, in which three large databases-Pubmed, Socups and Web of Science were searched to select studies that employed machine learning or microsimulation techniques for the prognosis of dementia. A single backward snowballing was done to identify further studies. A quality checklist was also employed to assess the quality of the evidence presented by the selected studies, and low quality studies were removed. Finally, data from the final set of studies were extracted in summary tables. In total 37 papers were included. The data summary results showed that the current research is focused on the investigation of the patients with mild cognitive impairment that will evolve to Alzheimer's disease, using machine learning techniques. Microsimulation studies were concerned with cost estimation and had a populational focus. Neuroimaging was the most commonly used variable. Prediction of conversion from MCI to AD is the dominant theme in the selected studies. Most studies used ML techniques on Neuroimaging data. Only a few data sources have been recruited by most studies and the ADNI database is the one most commonly used. Only two studies have investigated the prediction of epidemiological aspects of Dementia using either ML or MS techniques. Finally, care should be taken when interpreting the reported accuracy of ML

  16. 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.

  17. The impact of machine learning techniques in the study of bipolar disorder: A systematic review.

    PubMed

    Librenza-Garcia, Diego; Kotzian, Bruno Jaskulski; Yang, Jessica; Mwangi, Benson; Cao, Bo; Pereira Lima, Luiza Nunes; Bermudez, Mariane Bagatin; Boeira, Manuela Vianna; Kapczinski, Flávio; Passos, Ives Cavalcante

    2017-09-01

    Machine learning techniques provide new methods to predict diagnosis and clinical outcomes at an individual level. We aim to review the existing literature on the use of machine learning techniques in the assessment of subjects with bipolar disorder. We systematically searched PubMed, Embase and Web of Science for articles published in any language up to January 2017. We found 757 abstracts and included 51 studies in our review. Most of the included studies used multiple levels of biological data to distinguish the diagnosis of bipolar disorder from other psychiatric disorders or healthy controls. We also found studies that assessed the prediction of clinical outcomes and studies using unsupervised machine learning to build more consistent clinical phenotypes of bipolar disorder. We concluded that given the clinical heterogeneity of samples of patients with BD, machine learning techniques may provide clinicians and researchers with important insights in fields such as diagnosis, personalized treatment and prognosis orientation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Does technology acceleration equate to mask cost acceleration?

    NASA Astrophysics Data System (ADS)

    Trybula, Walter J.; Grenon, Brian J.

    2003-06-01

    The technology acceleration of the ITRS Roadmap has many implications on both the semiconductor sup-plier community and the manufacturers. INTERNATIONAL SEMATECH has revaluated the projected cost of advanced technology masks. Building on the methodology developed in 1996 for mask costs, this work provided a critical review of mask yields and factors relating to the manufacture of photolithography masks. The impact of the yields provided insight into the learning curve for leading edge mask manufac-turing. The projected mask set cost was surprising, and the ability to provide first and second year cost estimates provided additional information on technology introduction. From this information, the impact of technology acceleration can be added to the projected yields to evaluate the impact on mask costs.

  19. 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…

  20. Use of Advanced Machine-Learning Techniques for Non-Invasive Monitoring of Hemorrhage

    DTIC Science & Technology

    2010-04-01

    that state-of-the-art machine learning techniques when integrated with novel non-invasive monitoring technologies could detect subtle, physiological...decompensation. Continuous, non-invasively measured hemodynamic signals (e.g., ECG, blood pressures, stroke volume) were used for the development of machine ... learning algorithms. Accuracy estimates were obtained by building models using 27 subjects and testing on the 28th. This process was repeated 28 times

  1. 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…

  2. 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.

  3. 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…

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

    PubMed

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

    2014-01-01

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

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

    PubMed

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

    2014-06-01

    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 noninvasive ambulatory measures that can reliably differentiate vocal hyperfunction from normal patterns of vocal behavior. As an initial step toward this goal we used an accelerometer taped to the neck surface to provide a continuous, noninvasive acceleration signal designed to capture some aspects of vocal behavior related to vocal cord nodules, a common manifestation of vocal hyperfunction. 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 5-min windows of the acceleration signal and normalized these features so that intersubject 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.

  6. 1985 Particle Accelerator Conference: Accelerator Engineering and Technology, 11th, Vancouver, Canada, May 13-16, 1985, Proceedings

    NASA Astrophysics Data System (ADS)

    Strathdee, A.

    1985-10-01

    The topics discussed are related to high-energy accelerators and colliders, particle sources and electrostatic accelerators, controls, instrumentation and feedback, beam dynamics, low- and intermediate-energy circular accelerators and rings, RF and other acceleration systems, beam injection, extraction and transport, operations and safety, linear accelerators, applications of accelerators, radiation sources, superconducting supercolliders, new acceleration techniques, superconducting components, cryogenics, and vacuum. Accelerator and storage ring control systems are considered along with linear and nonlinear orbit theory, transverse and longitudinal instabilities and cures, beam cooling, injection and extraction orbit theory, high current dynamics, general beam dynamics, and medical and radioisotope applications. Attention is given to superconducting RF structures, magnet technology, superconducting magnets, and physics opportunities with relativistic heavy ion accelerators.

  7. BIOCONAID System (Bionic Control of Acceleration Induced Dimming). Final Report.

    ERIC Educational Resources Information Center

    Rogers, Dana B.; And Others

    The system described represents a new technique for enhancing the fidelity of flight simulators during high acceleration maneuvers. This technique forces the simulator pilot into active participation and energy expenditure similar to the aircraft pilot undergoing actual accelerations. The Bionic Control of Acceleration Induced Dimming (BIOCONAID)…

  8. Using Machine Learning Techniques in the Analysis of Oceanographic Data

    NASA Astrophysics Data System (ADS)

    Falcinelli, K. E.; Abuomar, S.

    2017-12-01

    Acoustic Doppler Current Profilers (ADCPs) are oceanographic tools capable of collecting large amounts of current profile data. Using unsupervised machine learning techniques such as principal component analysis, fuzzy c-means clustering, and self-organizing maps, patterns and trends in an ADCP dataset are found. Cluster validity algorithms such as visual assessment of cluster tendency and clustering index are used to determine the optimal number of clusters in the ADCP dataset. These techniques prove to be useful in analysis of ADCP data and demonstrate potential for future use in other oceanographic applications.

  9. Study of CT image texture using deep learning techniques

    NASA Astrophysics Data System (ADS)

    Dutta, Sandeep; Fan, Jiahua; Chevalier, David

    2018-03-01

    For CT imaging, reduction of radiation dose while improving or maintaining image quality (IQ) is currently a very active research and development topic. Iterative Reconstruction (IR) approaches have been suggested to be able to offer better IQ to dose ratio compared to the conventional Filtered Back Projection (FBP) reconstruction. However, it has been widely reported that often CT image texture from IR is different compared to that from FBP. Researchers have proposed different figure of metrics to quantitate the texture from different reconstruction methods. But there is still a lack of practical and robust method in the field for texture description. This work applied deep learning method for CT image texture study. Multiple dose scans of a 20cm diameter cylindrical water phantom was performed on Revolution CT scanner (GE Healthcare, Waukesha) and the images were reconstructed with FBP and four different IR reconstruction settings. The training images generated were randomly allotted (80:20) to a training and validation set. An independent test set of 256-512 images/class were collected with the same scan and reconstruction settings. Multiple deep learning (DL) networks with Convolution, RELU activation, max-pooling, fully-connected, global average pooling and softmax activation layers were investigated. Impact of different image patch size for training was investigated. Original pixel data as well as normalized image data were evaluated. DL models were reliably able to classify CT image texture with accuracy up to 99%. Results show that the deep learning techniques suggest that CT IR techniques may help lower the radiation dose compared to FBP.

  10. Accelerated Math[TM]. What Works Clearinghouse Intervention Report

    ERIC Educational Resources Information Center

    What Works Clearinghouse, 2011

    2011-01-01

    "Accelerated Math"[TM], published by Renaissance Learning, is a software tool used to customize assignments and monitor progress in math for students in grades 1-12. The "Accelerated Math"[TM] software creates individualized assignments aligned with state standards and national guidelines, scores student work, and generates…

  11. Accelerators as Authentic Training Experiences for Nascent Entrepreneurs

    ERIC Educational Resources Information Center

    Miles, Morgan P.; de Vries, Huibert; Harrison, Geoff; Bliemel, Martin; de Klerk, Saskia; Kasouf, Chick J.

    2017-01-01

    Purpose: The purpose of this paper is to address the role of accelerators as authentic learning-based entrepreneurial training programs. Accelerators facilitate the development and assessment of entrepreneurial competencies in nascent entrepreneurs through the process of creating a start-up venture. Design/methodology/approach: Survey data from…

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

    NASA Astrophysics Data System (ADS)

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

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

  13. Machine learning and microsimulation techniques on the prognosis of dementia: A systematic literature review

    PubMed Central

    Mendes, Emilia; Berglund, Johan; Anderberg, Peter

    2017-01-01

    Background Dementia is a complex disorder characterized by poor outcomes for the patients and high costs of care. After decades of research little is known about its mechanisms. Having prognostic estimates about dementia can help researchers, patients and public entities in dealing with this disorder. Thus, health data, machine learning and microsimulation techniques could be employed in developing prognostic estimates for dementia. Objective The goal of this paper is to present evidence on the state of the art of studies investigating and the prognosis of dementia using machine learning and microsimulation techniques. Method To achieve our goal we carried out a systematic literature review, in which three large databases—Pubmed, Socups and Web of Science were searched to select studies that employed machine learning or microsimulation techniques for the prognosis of dementia. A single backward snowballing was done to identify further studies. A quality checklist was also employed to assess the quality of the evidence presented by the selected studies, and low quality studies were removed. Finally, data from the final set of studies were extracted in summary tables. Results In total 37 papers were included. The data summary results showed that the current research is focused on the investigation of the patients with mild cognitive impairment that will evolve to Alzheimer’s disease, using machine learning techniques. Microsimulation studies were concerned with cost estimation and had a populational focus. Neuroimaging was the most commonly used variable. Conclusions Prediction of conversion from MCI to AD is the dominant theme in the selected studies. Most studies used ML techniques on Neuroimaging data. Only a few data sources have been recruited by most studies and the ADNI database is the one most commonly used. Only two studies have investigated the prediction of epidemiological aspects of Dementia using either ML or MS techniques. Finally, care should be

  14. 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.

  15. Developing the Systems Engineering Experience Accelerator (SEEA) Prototype and Roadmap

    DTIC Science & Technology

    2011-05-31

    Learning Model developed by Kolb , 1984. Figure 3: Learning Process: All Phases of Experiential Learning to be Engaged Profile building engages learners...simulation that will put the learner in an experiential , emotional state and effectively compress time and greatly accelerate the learning of a systems...Taxonomy ................................................................................. 9 2.3 Learning Theory Model and Learner Profile

  16. 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,…

  17. TH-EF-204-04: Experience of IMRT and Other Conformal Techniques in Russia

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

    Krylova, T.

    Joanna E. Cygler, Jan Seuntjens, J. Daniel Bourland, M. Saiful Huq, Josep Puxeu Vaque, Daniel Zucca Aparicio, Tatiana Krylova, Yuri Kirpichev, Eric Ford, Caridad Borras Stereotactic Radiation Therapy (SRT) utilizes small static and dynamic (IMRT) fields, to successfully treat malignant and benign diseases using techniques such as Stereotactic Radiosurgery (SRS) and Stereotactic Body Radiation Therapy (SBRT). SRT is characterized by sharp dose gradients for individual fields and their resultant dose distributions. For appropriate targets, small field radiotherapy offers improved treatment quality by allowing better sparing of organs at risk while delivering the prescribed target dose. Specialized small field treatment deliverymore » systems, such as robotic-controlled linear accelerators, gamma radiosurgery units, and dynamic arc linear accelerators may utilize rigid fixation, image guidance, and tumor tracking, to insure precise dose delivery to static or moving targets. However, in addition to great advantages, small field delivery techniques present special technical challenges for dose calibration due to unique geometries and small field sizes not covered by existing reference dosimetry protocols such as AAPM TG-51 or IAEA TRS 398. In recent years extensive research has been performed to understand small field dosimetry and measurement instrumentation. AAPM, IAEA and ICRU task groups are expected to provide soon recommendations on the dosimetry of small radiation fields. In this symposium we will: 1] discuss the physics, instrumentation, methodologies and challenges for small field radiation dose measurements; 2] review IAEA and ICRU recommendations on prescribing, recording and reporting of small field radiation therapy; 3] discuss selected clinical applications and technical aspects for specialized image-guided, small field, linear accelerator based treatment techniques such as IMRT and SBRT. Learning Objectives: To learn the physics of small fields in

  18. Accelerated Reader Program: What Do Teachers Really Think?

    ERIC Educational Resources Information Center

    Smith, Amy Frances; Westberg, Karen; Hejny, Anne

    2017-01-01

    What do teachers really think about the Accelerated Reader program, a widely used supplemental, independent reading program in which their students read fiction and non-fiction books of their choice and take brief online comprehension quizzes about the books? The Accelerated Reader (AR) program was designed by Renaissance Learning Company to…

  19. The Relationship of Learning Traits, Motivation and Performance-Learning Response Dynamics

    ERIC Educational Resources Information Center

    Hwang, Wu-Yuin; Chang, Chen-Bin; Chen, Gan-Jung

    2004-01-01

    This paper proposes a model of learning dynamics and learning energy, one that analyzes learning systems scientifically. This model makes response to the learner action by means of some equations relating to learning dynamics, learning energy, learning speed, learning force, and learning acceleration, which is analogous to the notion of Newtonian…

  20. Accelerator-based techniques for the support of senior-level undergraduate physics laboratories

    NASA Astrophysics Data System (ADS)

    Williams, J. R.; Clark, J. C.; Isaacs-Smith, T.

    2001-07-01

    Approximately three years ago, Auburn University replaced its aging Dynamitron accelerator with a new 2MV tandem machine (Pelletron) manufactured by the National Electrostatics Corporation (NEC). This new machine is maintained and operated for the University by Physics Department personnel, and the accelerator supports a wide variety of materials modification/analysis studies. Computer software is available that allows the NEC Pelletron to be operated from a remote location, and an Internet link has been established between the Accelerator Laboratory and the Upper-Level Undergraduate Teaching Laboratory in the Physics Department. Additional software supplied by Canberra Industries has also been used to create a second Internet link that allows live-time data acquisition in the Teaching Laboratory. Our senior-level undergraduates and first-year graduate students perform a number of experiments related to radiation detection and measurement as well as several standard accelerator-based experiments that have been added recently. These laboratory exercises will be described, and the procedures used to establish the Internet links between our Teaching Laboratory and the Accelerator Laboratory will be discussed.

  1. Observation of acceleration and deceleration in gigaelectron-volt-per-metre gradient dielectric wakefield accelerators

    DOE PAGES

    O’Shea, B. D.; Andonian, G.; Barber, S. K.; ...

    2016-09-14

    There is urgent need to develop new acceleration techniques capable of exceeding gigaelectron-volt-per-metre (GeV m –1) gradients in order to enable future generations of both light sources and high-energy physics experiments. To address this need, short wavelength accelerators based on wakefields, where an intense relativistic electron beam radiates the demanded fields directly into the accelerator structure or medium, are currently under intense investigation. One such wakefield based accelerator, the dielectric wakefield accelerator, uses a dielectric lined-waveguide to support a wakefield used for acceleration. Here we show gradients of 1.347±0.020 GeV m –1 using a dielectric wakefield accelerator of 15 cmmore » length, with sub-millimetre transverse aperture, by measuring changes of the kinetic state of relativistic electron beams. We follow this measurement by demonstrating accelerating gradients of 320±17 MeV m –1. As a result, both measurements improve on previous measurements by and order of magnitude and show promise for dielectric wakefield accelerators as sources of high-energy electrons.« less

  2. Observation of acceleration and deceleration in gigaelectron-volt-per-metre gradient dielectric wakefield accelerators

    PubMed Central

    O'Shea, B. D.; Andonian, G.; Barber, S. K.; Fitzmorris, K. L.; Hakimi, S.; Harrison, J.; Hoang, P. D.; Hogan, M. J.; Naranjo, B.; Williams, O. B.; Yakimenko, V.; Rosenzweig, J. B.

    2016-01-01

    There is urgent need to develop new acceleration techniques capable of exceeding gigaelectron-volt-per-metre (GeV m−1) gradients in order to enable future generations of both light sources and high-energy physics experiments. To address this need, short wavelength accelerators based on wakefields, where an intense relativistic electron beam radiates the demanded fields directly into the accelerator structure or medium, are currently under intense investigation. One such wakefield based accelerator, the dielectric wakefield accelerator, uses a dielectric lined-waveguide to support a wakefield used for acceleration. Here we show gradients of 1.347±0.020 GeV m−1 using a dielectric wakefield accelerator of 15 cm length, with sub-millimetre transverse aperture, by measuring changes of the kinetic state of relativistic electron beams. We follow this measurement by demonstrating accelerating gradients of 320±17 MeV m−1. Both measurements improve on previous measurements by and order of magnitude and show promise for dielectric wakefield accelerators as sources of high-energy electrons. PMID:27624348

  3. The Teacher's Sourcebook for Cooperative Learning: Practical Techniques, Basic Principles, and Frequently Asked Questions.

    ERIC Educational Resources Information Center

    Jacobs, George M.; Power, Michael A.; Inn, Loh Wan

    This book demonstrates how classroom teachers can use cooperative learning techniques for lesson planning and classroom management. It emphasizes that cooperation among students is powerful, and it notes that just because students are in a group does not mean that they are cooperating. Part 1, "Getting Started with Cooperative Learning," includes…

  4. The Effect of Higher Education Faculty Training in Improvisational Theatre Techniques on Student Learning and Perceptions of Engagement and Faculty Perceptions of Teaching and Learning

    ERIC Educational Resources Information Center

    Massie, DeAnna

    2017-01-01

    College instructors are content experts but ineffective at creating engaging and productive learning environments. This mixed methods study explored how improvisational theatre techniques affect college instructors' ability to increase student engagement and learning. Theoretical foundations included engagement, active learning, collaboration and…

  5. PEPSI-Dock: a detailed data-driven protein-protein interaction potential accelerated by polar Fourier correlation.

    PubMed

    Neveu, Emilie; Ritchie, David W; Popov, Petr; Grudinin, Sergei

    2016-09-01

    Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expansion of Protein Structures and Interactions for Docking (PEPSI-Dock) improves the accuracy of the first stage of the docking pipeline, which will sharpen up the final predictions. Indeed, PEPSI-Dock benefits from the precision of a very detailed data-driven model of the binding free energy used with a global and exhaustive rigid-body search space. As well as being accurate, our computations are among the fastest by virtue of the sparse representation of the pre-computed potentials and FFT-accelerated sampling techniques. Overall, this is the first demonstration of a FFT-accelerated docking method coupled with an arbitrary-shaped distance-dependent interaction potential. First, we present a novel learning process to compute data-driven distant-dependent pairwise potentials, adapted from our previous method used for rescoring of putative protein-protein binding poses. The potential coefficients are learned by combining machine-learning techniques with physically interpretable descriptors. Then, we describe the integration of the deduced potentials into a FFT-accelerated spherical sampling provided by the Hex library. Overall, on a training set of 163 heterodimers, PEPSI-Dock achieves a success rate of 91% mid-quality predictions in the top-10 solutions. On a subset of the protein docking benchmark v5, it achieves 44.4% mid-quality predictions in the top-10 solutions when starting from bound structures and 20.5% when starting from unbound structures. The method runs in 5-15 min on a modern laptop and can easily be extended to other types of interactions. https://team.inria.fr/nano-d/software/PEPSI-Dock sergei.grudinin@inria.fr. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e

  6. Prediction of lung cancer patient survival via supervised machine learning classification techniques.

    PubMed

    Lynch, Chip M; Abdollahi, Behnaz; Fuqua, Joshua D; de Carlo, Alexandra R; Bartholomai, James A; Balgemann, Rayeanne N; van Berkel, Victor H; Frieboes, Hermann B

    2017-12-01

    Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not well understood which types of techniques would yield more predictive information, and which data attributes should be used in order to determine this information. In this study, a number of supervised learning techniques is applied to the SEER database to classify lung cancer patients in terms of survival, including linear regression, Decision Trees, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), and a custom ensemble. Key data attributes in applying these methods include tumor grade, tumor size, gender, age, stage, and number of primaries, with the goal to enable comparison of predictive power between the various methods The prediction is treated like a continuous target, rather than a classification into categories, as a first step towards improving survival prediction. The results show that the predicted values agree with actual values for low to moderate survival times, which constitute the majority of the data. The best performing technique was the custom ensemble with a Root Mean Square Error (RMSE) value of 15.05. The most influential model within the custom ensemble was GBM, while Decision Trees may be inapplicable as it had too few discrete outputs. The results further show that among the five individual models generated, the most accurate was GBM with an RMSE value of 15.32. Although SVM underperformed with an RMSE value of 15.82, statistical analysis singles the SVM as the only model that generated a distinctive output. The results of the models are consistent with a classical Cox proportional hazards model used as a reference technique. We conclude that application of these supervised learning techniques to lung cancer data in the SEER database may be of use to estimate patient survival time

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

    ERIC Educational Resources Information Center

    Jalilifar, Alireza

    2010-01-01

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

  8. New Techniques for Deep Learning with Geospatial Data using TensorFlow, Earth Engine, and Google Cloud Platform

    NASA Astrophysics Data System (ADS)

    Hancher, M.

    2017-12-01

    Recent years have seen promising results from many research teams applying deep learning techniques to geospatial data processing. In that same timeframe, TensorFlow has emerged as the most popular framework for deep learning in general, and Google has assembled petabytes of Earth observation data from a wide variety of sources and made them available in analysis-ready form in the cloud through Google Earth Engine. Nevertheless, developing and applying deep learning to geospatial data at scale has been somewhat cumbersome to date. We present a new set of tools and techniques that simplify this process. Our approach combines the strengths of several underlying tools: TensorFlow for its expressive deep learning framework; Earth Engine for data management, preprocessing, postprocessing, and visualization; and other tools in Google Cloud Platform to train TensorFlow models at scale, perform additional custom parallel data processing, and drive the entire process from a single familiar Python development environment. These tools can be used to easily apply standard deep neural networks, convolutional neural networks, and other custom model architectures to a variety of geospatial data structures. We discuss our experiences applying these and related tools to a range of machine learning problems, including classic problems like cloud detection, building detection, land cover classification, as well as more novel problems like illegal fishing detection. Our improved tools will make it easier for geospatial data scientists to apply modern deep learning techniques to their own problems, and will also make it easier for machine learning researchers to advance the state of the art of those techniques.

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

    PubMed

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

    2015-08-01

    Bladder cancer is a common cancer in genitourinary malignancy. For muscle invasive bladder cancer, surgical removal of the bladder, i.e. radical cystectomy, is in general the definitive treatment which, unfortunately, carries significant morbidities and mortalities. Accurate prediction of the mortality of radical cystectomy is therefore needed. Statistical methods have conventionally been used for this purpose, despite the complex interactions of high-dimensional medical data. Machine learning has emerged as a promising technique for handling high-dimensional data, with increasing application in clinical decision support, e.g. cancer prediction and prognosis. Its ability to reveal the hidden nonlinear interactions and interpretable rules between dependent and independent variables is favorable for constructing models of effective generalization performance. In this paper, seven machine learning methods are utilized to predict the 5-year mortality of radical cystectomy, including back-propagation neural network (BPN), radial basis function (RBFN), extreme learning machine (ELM), regularized ELM (RELM), support vector machine (SVM), naive Bayes (NB) classifier and k-nearest neighbour (KNN), on a clinicopathological dataset of 117 patients of the urology unit of a hospital in Hong Kong. The experimental results indicate that RELM achieved the highest average prediction accuracy of 0.8 at a fast learning speed. The research findings demonstrate the potential of applying machine learning techniques to support clinical decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Fermilab | Science | Particle Accelerators

    Science.gov Websites

    2,300 physicists from all over the world come to Fermilab to conduct experiments using particle particle physics to the next level, collaborating with scientists and laboratories around the world to help world leader in accelerator research, development and industrialization. Learn more about IARC. Fermilab

  11. Distributed and Problem-based Learning Techniques for the Family Communication Course.

    ERIC Educational Resources Information Center

    LeBlanc, H. Paul, III

    Current technological advances have made possible teaching techniques which were previously impossible. Distance and distributed learning technologies have made it possible to instruct outside of the classroom setting. An advantage to this advance includes that ability to reach students who are unable to relocate to the university. However, there…

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2009-05-01

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

  14. Accelerometer Data Analysis and Presentation Techniques

    NASA Technical Reports Server (NTRS)

    Rogers, Melissa J. B.; Hrovat, Kenneth; McPherson, Kevin; Moskowitz, Milton E.; Reckart, Timothy

    1997-01-01

    The NASA Lewis Research Center's Principal Investigator Microgravity Services project analyzes Orbital Acceleration Research Experiment and Space Acceleration Measurement System data for principal investigators of microgravity experiments. Principal investigators need a thorough understanding of data analysis techniques so that they can request appropriate analyses to best interpret accelerometer data. Accelerometer data sampling and filtering is introduced along with the related topics of resolution and aliasing. Specific information about the Orbital Acceleration Research Experiment and Space Acceleration Measurement System data sampling and filtering is given. Time domain data analysis techniques are discussed and example environment interpretations are made using plots of acceleration versus time, interval average acceleration versus time, interval root-mean-square acceleration versus time, trimmean acceleration versus time, quasi-steady three dimensional histograms, and prediction of quasi-steady levels at different locations. An introduction to Fourier transform theory and windowing is provided along with specific analysis techniques and data interpretations. The frequency domain analyses discussed are power spectral density versus frequency, cumulative root-mean-square acceleration versus frequency, root-mean-square acceleration versus frequency, one-third octave band root-mean-square acceleration versus frequency, and power spectral density versus frequency versus time (spectrogram). Instructions for accessing NASA Lewis Research Center accelerometer data and related information using the internet are provided.

  15. Accelerating locomotor savings in learning: compressing four training days to one.

    PubMed

    Day, Kevin A; Leech, Kristan A; Roemmich, Ryan T; Bastian, Amy J

    2018-06-01

    Acquiring new movements requires the capacity of the nervous system to remember previously experienced motor patterns. The phenomenon of faster relearning after initial learning is termed "savings." Here we studied how savings of a novel walking pattern develops over several days of practice and how this process can be accelerated. We introduced participants to a split-belt treadmill adaptation paradigm for 30 min for 5 consecutive days. By training day 5, participants were able to produce near-perfect performance when switching between split and tied-belt environments. We found that this was due to their ability to shift specific elements of their stepping pattern to account for the split treadmill speeds from day to day. We also applied a state-space model to further characterize multiday locomotor savings. We then explored methods of achieving comparable savings with less total training time. We studied people training only on day 1, with either one extended split-belt exposure or alternating four times between split-belt and tied-belt conditions rapidly in succession. Both of these single-day training groups were tested again on day 5. Experiencing four abbreviated exposures on day 1 improved the performance on day 5 compared with one extended exposure on day 1. Moreover, this abbreviated group performed similarly to the group that trained for 4 consecutive days before testing on day 5, despite only having one-quarter of the total training time. These results demonstrate that we can leverage training structure to achieve a high degree of performance while minimizing training sessions. NEW & NOTEWORTHY Learning a new movement requires repetition. Here, we demonstrate how to more efficiently train an adapted walking pattern. By compressing split-belt treadmill training delivered over 4 days to four abbreviated bouts of training delivered on the first day of training, we were able to induce equivalent savings over a 5-day span. These results suggest that we can

  16. 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…

  17. Determining the Deacetylation Degree of Chitosan: Opportunities to Learn Instrumental Techniques

    ERIC Educational Resources Information Center

    Pérez-Álvarez, Leyre; Ruiz-Rubio, Leire; Vilas-Vilela, Jose Luis

    2018-01-01

    To enhance critical thinking and problem-solving skills, a project-based learning (PBL) approach for "Instrumental Techniques" courses in undergraduate physical chemistry was specifically developed for a pharmacy bachelor degree program. The starting point of this PBL was an open-ended question that is close to the student scientist's…

  18. Endoscopic Evacuation of Basal Ganglia Hematoma: Surgical Technique, Outcome, and Learning Curve.

    PubMed

    Ma, Lichao; Hou, Yuanzheng; Zhu, Ruyuan; Chen, Xiaolei

    2017-05-01

    Minimally invasive endoscopic hematoma evacuation is a promising treatment option for intracerebral hemorrhage. However, the technique still needs improvement. We report our clinical experience of using this technique to evacuate deep-seated basal ganglia hematomas. The frontal approach was used in most patients. The preoperative and postoperative hematoma volumes, Glasgow Coma Scale, hematoma evacuation rate, 30-day mortality, and long-term outcome defined by the modified Rankin Scale were analyzed retrospectively. The surgical duration per milliliter of clot (DPM) was calculated. The learning curve for this technique was determined based on the relation between the DPM and evacuation rate per the number of cases experienced. A total of 24 patients were enrolled. The evacuation rate was 87% ± 10%. The average Glasgow Coma Scale score recovered from 8 to 13 after surgery. Twenty-one patients had follow-up data. The follow-up time was 13 ± 6 months. The 30-day mortality after surgery was zero. Forty-eight percent of patients (10/21) achieved a favorable outcome. The DPM (P = 0.92) and evacuation rate (P = 0.64) did not change substantially with the number of cases experienced. Endoscopic port surgery for hematoma evacuation via the frontal approach is a safe surgical option for deep-seated basal ganglia hematomas. This technique is minimally invasive and may be helpful to provide better long-term outcomes for selected patients. For neurosurgeons, the learning curve for this technique is steep, which implies that the skills needed for our technique can be easily acquired. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Student Attitudes toward Accelerated Reader: "Thanks for Asking!"

    ERIC Educational Resources Information Center

    Smith, Amy; Westberg, Karen

    2011-01-01

    The Accelerated Reader program was designed by Renaissance Learning to increase students' motivation to read and students' achievement in reading; however, a review of the literature reveals inconsistent findings about its outcomes. The Renaissance Learning company reports several research studies on their website that suggest the program is…

  20. Epileptic seizure detection in EEG signal using machine learning techniques.

    PubMed

    Jaiswal, Abeg Kumar; Banka, Haider

    2018-03-01

    Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.

  1. Machine Learning Techniques for Global Sensitivity Analysis in Climate Models

    NASA Astrophysics Data System (ADS)

    Safta, C.; Sargsyan, K.; Ricciuto, D. M.

    2017-12-01

    Climate models studies are not only challenged by the compute intensive nature of these models but also by the high-dimensionality of the input parameter space. In our previous work with the land model components (Sargsyan et al., 2014) we identified subsets of 10 to 20 parameters relevant for each QoI via Bayesian compressive sensing and variance-based decomposition. Nevertheless the algorithms were challenged by the nonlinear input-output dependencies for some of the relevant QoIs. In this work we will explore a combination of techniques to extract relevant parameters for each QoI and subsequently construct surrogate models with quantified uncertainty necessary to future developments, e.g. model calibration and prediction studies. In the first step, we will compare the skill of machine-learning models (e.g. neural networks, support vector machine) to identify the optimal number of classes in selected QoIs and construct robust multi-class classifiers that will partition the parameter space in regions with smooth input-output dependencies. These classifiers will be coupled with techniques aimed at building sparse and/or low-rank surrogate models tailored to each class. Specifically we will explore and compare sparse learning techniques with low-rank tensor decompositions. These models will be used to identify parameters that are important for each QoI. Surrogate accuracy requirements are higher for subsequent model calibration studies and we will ascertain the performance of this workflow for multi-site ALM simulation ensembles.

  2. Accelerated Slice Encoding for Metal Artifact Correction

    PubMed Central

    Hargreaves, Brian A.; Chen, Weitian; Lu, Wenmiao; Alley, Marcus T.; Gold, Garry E.; Brau, Anja C. S.; Pauly, John M.; Pauly, Kim Butts

    2010-01-01

    Purpose To demonstrate accelerated imaging with artifact reduction near metallic implants and different contrast mechanisms. Materials and Methods Slice-encoding for metal artifact correction (SEMAC) is a modified spin echo sequence that uses view-angle tilting and slice-direction phase encoding to correct both in-plane and through-plane artifacts. Standard spin echo trains and short-TI inversion recovery (STIR) allow efficient PD-weighted imaging with optional fat suppression. A completely linear reconstruction allows incorporation of parallel imaging and partial Fourier imaging. The SNR effects of all reconstructions were quantified in one subject. 10 subjects with different metallic implants were scanned using SEMAC protocols, all with scan times below 11 minutes, as well as with standard spin echo methods. Results The SNR using standard acceleration techniques is unaffected by the linear SEMAC reconstruction. In all cases with implants, accelerated SEMAC significantly reduced artifacts compared with standard imaging techniques, with no additional artifacts from acceleration techniques. The use of different contrast mechanisms allowed differentiation of fluid from other structures in several subjects. Conclusion SEMAC imaging can be combined with standard echo-train imaging, parallel imaging, partial-Fourier imaging and inversion recovery techniques to offer flexible image contrast with a dramatic reduction of metal-induced artifacts in scan times under 11 minutes. PMID:20373445

  3. Accelerated slice encoding for metal artifact correction.

    PubMed

    Hargreaves, Brian A; Chen, Weitian; Lu, Wenmiao; Alley, Marcus T; Gold, Garry E; Brau, Anja C S; Pauly, John M; Pauly, Kim Butts

    2010-04-01

    To demonstrate accelerated imaging with both artifact reduction and different contrast mechanisms near metallic implants. Slice-encoding for metal artifact correction (SEMAC) is a modified spin echo sequence that uses view-angle tilting and slice-direction phase encoding to correct both in-plane and through-plane artifacts. Standard spin echo trains and short-TI inversion recovery (STIR) allow efficient PD-weighted imaging with optional fat suppression. A completely linear reconstruction allows incorporation of parallel imaging and partial Fourier imaging. The signal-to-noise ratio (SNR) effects of all reconstructions were quantified in one subject. Ten subjects with different metallic implants were scanned using SEMAC protocols, all with scan times below 11 minutes, as well as with standard spin echo methods. The SNR using standard acceleration techniques is unaffected by the linear SEMAC reconstruction. In all cases with implants, accelerated SEMAC significantly reduced artifacts compared with standard imaging techniques, with no additional artifacts from acceleration techniques. The use of different contrast mechanisms allowed differentiation of fluid from other structures in several subjects. SEMAC imaging can be combined with standard echo-train imaging, parallel imaging, partial-Fourier imaging, and inversion recovery techniques to offer flexible image contrast with a dramatic reduction of metal-induced artifacts in scan times under 11 minutes. (c) 2010 Wiley-Liss, Inc.

  4. Particle Acceleration at the Sun and in the Heliosphere

    NASA Technical Reports Server (NTRS)

    Reames, Donald V.

    1999-01-01

    Energetic particles are accelerated in rich profusion at sites throughout the heliosphere. They come from solar flares in the low corona, from shock waves driven outward by coronal mass ejections (CMEs), from planetary magnetospheres and bow shocks. They come from corotating interaction regions (CIRs) produced by high-speed streams in the solar wind, and from the heliospheric termination shock at the outer edge of the heliospheric cavity. We sample all these populations near Earth, but can distinguish them readily by their element and isotope abundances, ionization states, energy spectra, angular distributions and time behavior. Remote spacecraft have probed the spatial distributions of the particles and examined new sources in situ. Most acceleration sources can be "seen" only by direct observation of the particles; few photons are produced at these sites. Wave-particle interactions are an essential feature in acceleration sources and, for shock acceleration, new evidence of energetic-proton-generated waves has come from abundance variations and from local cross-field scattering. Element abundances often tell us the physics the source plasma itself, prior to acceleration. By comparing different populations, we learn more about the sources, and about the physics of acceleration and transport, than we can possibly learn from one source alone.

  5. 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.

  6. Machine-learned and codified synthesis parameters of oxide materials

    NASA Astrophysics Data System (ADS)

    Kim, Edward; Huang, Kevin; Tomala, Alex; Matthews, Sara; Strubell, Emma; Saunders, Adam; McCallum, Andrew; Olivetti, Elsa

    2017-09-01

    Predictive materials design has rapidly accelerated in recent years with the advent of large-scale resources, such as materials structure and property databases generated by ab initio computations. In the absence of analogous ab initio frameworks for materials synthesis, high-throughput and machine learning techniques have recently been harnessed to generate synthesis strategies for select materials of interest. Still, a community-accessible, autonomously-compiled synthesis planning resource which spans across materials systems has not yet been developed. In this work, we present a collection of aggregated synthesis parameters computed using the text contained within over 640,000 journal articles using state-of-the-art natural language processing and machine learning techniques. We provide a dataset of synthesis parameters, compiled autonomously across 30 different oxide systems, in a format optimized for planning novel syntheses of materials.

  7. Accelerator on a Chip

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

    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

    2018-01-16

    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. Journal of Accelerative Learning and Teaching, 1995.

    ERIC Educational Resources Information Center

    Journal of Accelerative Learning and Teaching, 1995

    1995-01-01

    Issues 1 and 2 (combined) of the 1995 journal contain these articles: "Accelerated Learning in a Beginning College-Level French Class at the University of Houston" (Patrice Caux); "The Psychobiology of Learning and Memory" (Don Schuster); "Do the Seeds of Accelerated Language Learning and Teaching Lie in a Behavioral…

  10. Accelerated Brain Aging in Schizophrenia: A Longitudinal Pattern Recognition Study.

    PubMed

    Schnack, Hugo G; van Haren, Neeltje E M; Nieuwenhuis, Mireille; Hulshoff Pol, Hilleke E; Cahn, Wiepke; Kahn, René S

    2016-06-01

    Despite the multitude of longitudinal neuroimaging studies that have been published, a basic question on the progressive brain loss in schizophrenia remains unaddressed: Does it reflect accelerated aging of the brain, or is it caused by a fundamentally different process? The authors used support vector regression, a supervised machine learning technique, to address this question. In a longitudinal sample of 341 schizophrenia patients and 386 healthy subjects with one or more structural MRI scans (1,197 in total), machine learning algorithms were used to build models to predict the age of the brain and the presence of schizophrenia ("schizophrenia score"), based on the gray matter density maps. Age at baseline ranged from 16 to 67 years, and follow-up scans were acquired between 1 and 13 years after the baseline scan. Differences between brain age and chronological age ("brain age gap") and between schizophrenia score and healthy reference score ("schizophrenia gap") were calculated. Accelerated brain aging was calculated from changes in brain age gap between two consecutive measurements. The age prediction model was validated in an independent sample. In schizophrenia patients, brain age was significantly greater than chronological age at baseline (+3.36 years) and progressively increased during follow-up (+1.24 years in addition to the baseline gap). The acceleration of brain aging was not constant: it decreased from 2.5 years/year just after illness onset to about the normal rate (1 year/year) approximately 5 years after illness onset. The schizophrenia gap also increased during follow-up, but more pronounced variability in brain abnormalities at follow-up rendered this increase nonsignificant. The progressive brain loss in schizophrenia appears to reflect two different processes: one relatively homogeneous, reflecting accelerated aging of the brain and related to various measures of outcome, and a more variable one, possibly reflecting individual variation and

  11. 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.

  12. 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…

  13. Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

    PubMed

    Wang, Ding; Liu, Derong

    2018-06-01

    The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Learning Information Systems: Theoretical Foundations.

    ERIC Educational Resources Information Center

    Paul, Terrance D.

    This paper uses the conceptual framework of cybernetics to understand why learning information systems such as the "Accelerated Reader" work so successfully, and to examine how this simple yet incisive concept can be used to accelerate learning at every level and in all disciplines. The first section, "Basic Concepts,"…

  15. Passive avoidance and complex maze learning in the senescence accelerated mouse (SAM): age and strain comparisons of SAM P8 and R1.

    PubMed

    Spangler, Edward L; Patel, Namisha; Speer, Dorey; Hyman, Michael; Hengemihle, John; Markowska, Alicja; Ingram, Donald K

    2002-02-01

    Two strains of the senescence accelerated mouse, P8 and R1,were tested in footshock-motivated passive avoidance (PA; P8, 3-21 months; R1, 3-24 months) and 14-unit T-maze (P8 and R1, 9, and 15 months) tasks. For PA, entry to a dark chamber from a lighted chamber was followed by a brief shock. Latency to enter the dark chamber 24 hours later served as a measure of retention. Two days of active avoidance training in a straight runway preceded 2 days (8 trials/day) of testing in the 14-unit T-maze. For PA retention, older P8 mice entered the dark chamber more quickly than older R1 mice, whereas no differences were observed between young P8 or R1 mice. In the 14-unit T-maze, age-related learning performance deficits were reflected in higher error scores for older mice. P8 mice were actually superior learners; that is, they had lower error scores compared with those of age-matched R1 counterparts. Although PA learning results were in agreement with other reports, results obtained in the 14-unit T-maze were not consistent with previous reports of learning impairments in the P8 senescence accelerated mouse.

  16. 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.

  17. X-ray Observations of Cosmic Ray Acceleration

    NASA Technical Reports Server (NTRS)

    Petre, Robert

    2012-01-01

    Since the discovery of cosmic rays, detection of their sources has remained elusive. A major breakthrough has come through the identification of synchrotron X-rays from the shocks of supernova remnants through imaging and spectroscopic observations by the most recent generation of X-ray observatories. This radiation is most likely produced by electrons accelerated to relativistic energy, and thus has offered the first, albeit indirect, observational evidence that diffusive shock acceleration in supernova remnants produces cosmic rays to TeV energies, possibly as high as the "knee" in the cosmic ray spectrum. X-ray observations have provided information about the maximum energy to which these shOCks accelerate electrons, as well as indirect evidence of proton acceleration. Shock morphologies measured in X-rays have indicated that a substantial fraction of the shock energy can be diverted into particle acceleration. This presentation will summarize what we have learned about cosmic ray acceleration from X-ray observations of supernova remnants over the past two decades.

  18. Accelerated Math®. Primary Mathematics. What Works Clearinghouse Intervention Report

    ERIC Educational Resources Information Center

    What Works Clearinghouse, 2017

    2017-01-01

    "Accelerated Math®," published by Renaissance Learning, is a software tool that provides practice problems for students in grades K-12 and provides teachers with reports to monitor student progress. "Accelerated Math®" creates individualized student assignments, scores the assignments, and generates reports on student progress.…

  19. The application of artificial intelligent techniques to accelerator operations at McMaster University

    NASA Astrophysics Data System (ADS)

    Poehlman, W. F. S.; Garland, Wm. J.; Stark, J. W.

    1993-06-01

    In an era of downsizing and a limited pool of skilled accelerator personnel from which to draw replacements for an aging workforce, the impetus to integrate intelligent computer automation into the accelerator operator's repertoire is strong. However, successful deployment of an "Operator's Companion" is not trivial. Both graphical and human factors need to be recognized as critical areas that require extra care when formulating the Companion. They include interactive graphical user's interface that mimics, for the operator, familiar accelerator controls; knowledge of acquisition phases during development must acknowledge the expert's mental model of machine operation; and automated operations must be seen as improvements to the operator's environment rather than threats of ultimate replacement. Experiences with the PACES Accelerator Operator Companion developed at two sites over the past three years are related and graphical examples are given. The scale of the work involves multi-computer control of various start-up/shutdown and tuning procedures for Model FN and KN Van de Graaff accelerators. The response from licensing agencies has been encouraging.

  20. [Learning experience of acupuncture technique from professor ZHANG Jin].

    PubMed

    Xue, Hongsheng; Zhang, Jin

    2017-08-12

    As a famous acupuncturist in the world, professor ZHANG Jin believes the key of acupuncture technique is the use of force, and the understanding of the "concentrating the force into needle body" is essential to understand the essence of acupuncture technique. With deep study of Huangdi Neijing ( The Inner Canon of Huangdi ) and Zhenjiu Dacheng ( Compendium of Acupuncture and Moxibustion ), the author further learned professor ZHANG Jin 's theory and operation specification of "concentrating force into needle body, so the force arriving before and together with needle". The whole-body force should be subtly focused on the tip of needle, and gentle force at tip of needle could get significant reinforcing and reducing effect. In addition, proper timing at tip of needle could start reinforcing and reducing effect, lead qi to disease location, and achieve superior clinical efficacy.

  1. 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.

  2. Power in the Classroom VII: Linking Behavior Alteration Techniques to Cognitive Learning.

    ERIC Educational Resources Information Center

    Richmond, Virginia P.; And Others

    1987-01-01

    Argues that Behavior Alteration Techniques (BATs) improve students' on-task compliance which, in turn, is consistently associated with achievement. Indicates a substantial relationship between BAT use and cognitive learning on both absolute and relative measures of achievement. Shows that the teachers perceived by students as "good"…

  3. Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

    NASA Astrophysics Data System (ADS)

    Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

    2017-11-01

    This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.

  4. Bridging the gap between high and low acceleration for planetary escape

    NASA Astrophysics Data System (ADS)

    Indrikis, Janis; Preble, Jeffrey C.

    With the exception of the often time consuming analysis by numerical optimization, no single orbit transfer analysis technique exists that can be applied over a wide range of accelerations. Using the simple planetary escape (parabolic trajectory) mission some of the more common techniques are considered as the limiting bastions at the high and the extremely low acceleration regimes. The brachistochrone, the minimum time of flight path, is proposed as the technique to bridge the gap between the high and low acceleration regions, providing a smooth bridge over the entire acceleration spectrum. A smooth and continuous velocity requirement is established for the planetary escape mission. By using these results, it becomes possible to determine the effect of finite accelerations on mission performance and target propulsion and power system designs which are consistent with a desired mission objective.

  5. Accelerator Generation and Thermal Separation (AGATS) of Technetium-99m

    ScienceCinema

    Grover, Blaine

    2018-05-01

    Accelerator Generation and Thermal Separation (AGATS) of Technetium-99m is a linear electron accelerator-based technology for producing medical imaging radioisotopes from a separation process that heats, vaporizes and condenses the desired radioisotope. You can learn more about INL's education programs at http://www.facebook.com/idahonationallaboratory.

  6. Accelerating the kiln drying of oak

    Treesearch

    William T. Simpson

    1980-01-01

    Reducing kiln-drying time for oak lumber can reduce energy requirements as well as reduce lumber inventories. In this work, l-inch northern red oak and white oak were kiln dried from green by a combination of individual accelerating techniques– presurfacing, presteaming, accelerated and smooth schedule, and high-temperature drying below 18 percent moisture content....

  7. Plasma production for electron acceleration by resonant plasma wave

    NASA Astrophysics Data System (ADS)

    Anania, M. P.; Biagioni, A.; Chiadroni, E.; Cianchi, A.; Croia, M.; Curcio, A.; Di Giovenale, D.; Di Pirro, G. P.; Filippi, F.; Ghigo, A.; Lollo, V.; Pella, S.; Pompili, R.; Romeo, S.; Ferrario, M.

    2016-09-01

    Plasma wakefield acceleration is the most promising acceleration technique known nowadays, able to provide very high accelerating fields (10-100 GV/m), enabling acceleration of electrons to GeV energy in few centimeter. However, the quality of the electron bunches accelerated with this technique is still not comparable with that of conventional accelerators (large energy spread, low repetition rate, and large emittance); radiofrequency-based accelerators, in fact, are limited in accelerating field (10-100 MV/m) requiring therefore hundred of meters of distances to reach the GeV energies, but can provide very bright electron bunches. To combine high brightness electron bunches from conventional accelerators and high accelerating fields reachable with plasmas could be a good compromise allowing to further accelerate high brightness electron bunches coming from LINAC while preserving electron beam quality. Following the idea of plasma wave resonant excitation driven by a train of short bunches, we have started to study the requirements in terms of plasma for SPARC_LAB (Ferrario et al., 2013 [1]). In particular here we focus on hydrogen plasma discharge, and in particular on the theoretical and numerical estimates of the ionization process which are very useful to design the discharge circuit and to evaluate the current needed to be supplied to the gas in order to have full ionization. Eventually, the current supplied to the gas simulated will be compared to that measured experimentally.

  8. 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…

  9. Accelerated Application Development: The ORNL Titan Experience

    DOE PAGES

    Joubert, Wayne; Archibald, Richard K.; Berrill, Mark A.; ...

    2015-05-09

    The use of computational accelerators such as NVIDIA GPUs and Intel Xeon Phi processors is now widespread in the high performance computing community, with many applications delivering impressive performance gains. However, programming these systems for high performance, performance portability and software maintainability has been a challenge. In this paper we discuss experiences porting applications to the Titan system. Titan, which began planning in 2009 and was deployed for general use in 2013, was the first multi-petaflop system based on accelerator hardware. To ready applications for accelerated computing, a preparedness effort was undertaken prior to delivery of Titan. In this papermore » we report experiences and lessons learned from this process and describe how users are currently making use of computational accelerators on Titan.« less

  10. Accelerated application development: The ORNL Titan experience

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

    Joubert, Wayne; Archibald, Rick; Berrill, Mark

    2015-08-01

    The use of computational accelerators such as NVIDIA GPUs and Intel Xeon Phi processors is now widespread in the high performance computing community, with many applications delivering impressive performance gains. However, programming these systems for high performance, performance portability and software maintainability has been a challenge. In this paper we discuss experiences porting applications to the Titan system. Titan, which began planning in 2009 and was deployed for general use in 2013, was the first multi-petaflop system based on accelerator hardware. To ready applications for accelerated computing, a preparedness effort was undertaken prior to delivery of Titan. In this papermore » we report experiences and lessons learned from this process and describe how users are currently making use of computational accelerators on Titan.« less

  11. Kuss Middle School: Expanding Time to Accelerate School Improvement

    ERIC Educational Resources Information Center

    Massachusetts 2020, 2012

    2012-01-01

    In 2004, Kuss Middle School became the first school declared "Chronically Underperforming" by the state of Massachusetts. But by 2010, Kuss had transformed itself into a model for schools around the country seeking a comprehensive turnaround strategy. Kuss is using increased learning time as the primary catalyst to accelerate learning,…

  12. Power in the Classroom V: Behavior Alteration Techniques, Communication Training, and Learning.

    ERIC Educational Resources Information Center

    McCroskey, James C.; And Others

    Data gathered from 42 secondary school speech communication teachers and their students formed the foundation for a study that examined the relationship between: (1) differential use of Behavior Alteration Techniques (BATs) by teachers trained or untrained in communication in instruction and (2) learning of students of varying quality levels.…

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

    ERIC Educational Resources Information Center

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

    2016-01-01

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

  14. Role of failure-mechanism identification in accelerated testing

    NASA Technical Reports Server (NTRS)

    Hu, J. M.; Barker, D.; Dasgupta, A.; Arora, A.

    1993-01-01

    Accelerated life testing techniques provide a short-cut method to investigate the reliability of electronic devices with respect to certain dominant failure mechanisms that occur under normal operating conditions. However, accelerated tests have often been conducted without knowledge of the failure mechanisms and without ensuring that the test accelerated the same mechanism as that observed under normal operating conditions. This paper summarizes common failure mechanisms in electronic devices and packages and investigates possible failure mechanism shifting during accelerated testing.

  15. 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.

  16. Computational Accelerator Physics. Proceedings

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

    Bisognano, J.J.; Mondelli, A.A.

    1997-04-01

    The sixty two papers appearing in this volume were presented at CAP96, the Computational Accelerator Physics Conference held in Williamsburg, Virginia from September 24{minus}27,1996. Science Applications International Corporation (SAIC) and the Thomas Jefferson National Accelerator Facility (Jefferson lab) jointly hosted CAP96, with financial support from the U.S. department of Energy`s Office of Energy Research and the Office of Naval reasearch. Topics ranged from descriptions of specific codes to advanced computing techniques and numerical methods. Update talks were presented on nearly all of the accelerator community`s major electromagnetic and particle tracking codes. Among all papers, thirty of them are abstracted formore » the Energy Science and Technology database.(AIP)« less

  17. 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…

  18. Adaptive/learning control of large space structures - System identification techniques. [for multi-configuration flexible spacecraft

    NASA Technical Reports Server (NTRS)

    Thau, F. E.; Montgomery, R. C.

    1980-01-01

    Techniques developed for the control of aircraft under changing operating conditions are used to develop a learning control system structure for a multi-configuration, flexible space vehicle. A configuration identification subsystem that is to be used with a learning algorithm and a memory and control process subsystem is developed. Adaptive gain adjustments can be achieved by this learning approach without prestoring of large blocks of parameter data and without dither signal inputs which will be suppressed during operations for which they are not compatible. The Space Shuttle Solar Electric Propulsion (SEP) experiment is used as a sample problem for the testing of adaptive/learning control system algorithms.

  19. Are They Learning? Are We? Learning Outcomes and the Academic Library

    ERIC Educational Resources Information Center

    Oakleaf, Megan

    2011-01-01

    Since the 1990s, the assessment of learning outcomes in academic libraries has accelerated rapidly, and librarians have come to recognize the necessity of articulating and assessing student learning outcomes. Initially, librarians developed tools and instruments to assess information literacy student learning outcomes. Now, academic librarians are…

  20. Brain computer interface learning for systems based on electrocorticography and intracortical microelectrode arrays.

    PubMed

    Hiremath, Shivayogi V; Chen, Weidong; Wang, Wei; Foldes, Stephen; Yang, Ying; Tyler-Kabara, Elizabeth C; Collinger, Jennifer L; Boninger, Michael L

    2015-01-01

    A brain-computer interface (BCI) system transforms neural activity into control signals for external devices in real time. A BCI user needs to learn to generate specific cortical activity patterns to control external devices effectively. We call this process BCI learning, and it often requires significant effort and time. Therefore, it is important to study this process and develop novel and efficient approaches to accelerate BCI learning. This article reviews major approaches that have been used for BCI learning, including computer-assisted learning, co-adaptive learning, operant conditioning, and sensory feedback. We focus on BCIs based on electrocorticography and intracortical microelectrode arrays for restoring motor function. This article also explores the possibility of brain modulation techniques in promoting BCI learning, such as electrical cortical stimulation, transcranial magnetic stimulation, and optogenetics. Furthermore, as proposed by recent BCI studies, we suggest that BCI learning is in many ways analogous to motor and cognitive skill learning, and therefore skill learning should be a useful metaphor to model BCI learning.

  1. Improving prediction of heart transplantation outcome using deep learning techniques.

    PubMed

    Medved, Dennis; Ohlsson, Mattias; Höglund, Peter; Andersson, Bodil; Nugues, Pierre; Nilsson, Johan

    2018-02-26

    The primary objective of this study is to compare the accuracy of two risk models, International Heart Transplantation Survival Algorithm (IHTSA), developed using deep learning technique, and Index for Mortality Prediction After Cardiac Transplantation (IMPACT), to predict survival after heart transplantation. Data from adult heart transplanted patients between January 1997 to December 2011 were collected from the UNOS registry. The study included 27,860 heart transplantations, corresponding to 27,705 patients. The study cohorts were divided into patients transplanted before 2009 (derivation cohort) and from 2009 (test cohort). The receiver operating characteristic (ROC) values, for the validation cohort, computed for one-year mortality, were 0.654 (95% CI: 0.629-0.679) for IHTSA and 0.608 (0.583-0.634) for the IMPACT model. The discrimination reached a C-index for long-term survival of 0.627 (0.608-0.646) for IHTSA, compared with 0.584 (0.564-0.605) for the IMPACT model. These figures correspond to an error reduction of 12% for ROC and 10% for C-index by using deep learning technique. The predicted one-year mortality rates for were 12% and 22% for IHTSA and IMPACT, respectively, versus an actual mortality rate of 10%. The IHTSA model showed superior discriminatory power to predict one-year mortality and survival over time after heart transplantation compared to the IMPACT model.

  2. Fostering students’ thinking skill and social attitude through STAD cooperative learning technique on tenth grade students of chemistry class

    NASA Astrophysics Data System (ADS)

    Kriswintari, D.; Yuanita, L.; Widodo, W.

    2018-04-01

    The aim of this study was to develop chemistry learning package using Student Teams Achievement Division (STAD) cooperative learning technique to foster students’ thinking skills and social attitudes. The chemistry learning package consisting of lesson plan, handout, students’ worksheet, thinking skill test, and observation sheet of social attitude was developed using the Dick and Carey model. Research subject of this study was chemistry learning package using STAD which was tried out on tenth grade students of SMA Trimurti Surabaya. The tryout was conducted using the one-group pre-test post-test design. Data was collected through observation, test, and questionnaire. The obtained data were analyzed using descriptive qualitative analysis. The findings of this study revealed that the developed chemistry learning package using STAD cooperative learning technique was categorized valid, practice and effective to be implemented in the classroom to foster students’ thinking skill and social attitude.

  3. Accelerated nursing students and theater students: creating a safe environment by acting the part.

    PubMed

    Cangelosi, Pamela R

    2008-01-01

    Traditional approaches to teaching basic nursing skills are being questioned for accelerated, or second-degree, nursing students. Since accelerated nursing students have demonstrated the ability to quickly assimilate new information and to transfer skills from a previous career into a new field, it is thought that they may benefit from teaching strategies that promote experiential learning. Through a hermeneutic phenomenological approach, this study inquired into the experiences of 22 accelerated baccalaureate nursing students to determine if narrative learning in a campus laboratory setting helped them integrate content from classroom and clinical practica and move quickly along the pathway to the competencies that are needed for safe nursing practice. Data analysis revealed the teaching/learning significance of narratives for these students and is identified in the theme, "Creating a Safe Environment".

  4. Analysis of Machine Learning Techniques for Heart Failure Readmissions.

    PubMed

    Mortazavi, Bobak J; Downing, Nicholas S; Bucholz, Emily M; Dharmarajan, Kumar; Manhapra, Ajay; Li, Shu-Xia; Negahban, Sahand N; Krumholz, Harlan M

    2016-11-01

    The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning techniques that address higher dimensional, nonlinear relationships among variables would enhance prediction. We sought to compare the effectiveness of several machine learning algorithms for predicting readmissions. Using data from the Telemonitoring to Improve Heart Failure Outcomes trial, we compared the effectiveness of random forests, boosting, random forests combined hierarchically with support vector machines or logistic regression (LR), and Poisson regression against traditional LR to predict 30- and 180-day all-cause readmissions and readmissions because of heart failure. We randomly selected 50% of patients for a derivation set, and a validation set comprised the remaining patients, validated using 100 bootstrapped iterations. We compared C statistics for discrimination and distributions of observed outcomes in risk deciles for predictive range. In 30-day all-cause readmission prediction, the best performing machine learning model, random forests, provided a 17.8% improvement over LR (mean C statistics, 0.628 and 0.533, respectively). For readmissions because of heart failure, boosting improved the C statistic by 24.9% over LR (mean C statistic 0.678 and 0.543, respectively). For 30-day all-cause readmission, the observed readmission rates in the lowest and highest deciles of predicted risk with random forests (7.8% and 26.2%, respectively) showed a much wider separation than LR (14.2% and 16.4%, respectively). Machine learning methods improved the prediction of readmission after hospitalization for heart failure compared with LR and provided the greatest predictive range in observed readmission rates. © 2016 American Heart Association, Inc.

  5. Present and future prospects of accelerator mass spectrometry

    NASA Astrophysics Data System (ADS)

    Kutschera, Walter

    1988-05-01

    Accelerator mass spectrometry (AMS) has become a powerful technique for measuring extremely low abundances (10 -10 to 10 -15 relative to stable isotopes) of long-lived radioisotopes with half-lives in the range from 10 2 to 10 8 years. With a few exceptions, tandem accelerators turned out to be the most useful instruments for AMS measurements. Both natural (mostly cosmogenic) and manmade (anthropogenic) radioisotopes are studied with this technique. In some cases very low concentrations of stable isotopes are also measured. Applications of AMS cover a large variety of fields including anthropology, archaeology, oceanography, hydrology, climatology, volcanology, mineral exploration, cosmochemistry, meteoritics, glaciology, sedimentary processes, geochronology, environmental physics, astrophysics, nuclear and particle physics. Present and future prospects of AMS will be discussed as an interplay between the continuous development of new techniques and the investigation of problems in the above mentioned fields. Depending on the specific problem to be investigated, different aspects of an AMS system are of importance. Typical factors to be considered are energy range and type of accelerator, and the possibilities of dedicated versus partial use of new or existing accelerators.

  6. NASA FDL: Accelerating Artificial Intelligence Applications in the Space Sciences.

    NASA Astrophysics Data System (ADS)

    Parr, J.; Navas-Moreno, M.; Dahlstrom, E. L.; Jennings, S. B.

    2017-12-01

    NASA has a long history of using Artificial Intelligence (AI) for exploration purposes, however due to the recent explosion of the Machine Learning (ML) field within AI, there are great opportunities for NASA to find expanded benefit. For over two years now, the NASA Frontier Development Lab (FDL) has been at the nexus of bright academic researchers, private sector expertise in AI/ML and NASA scientific problem solving. The FDL hypothesis of improving science results was predicated on three main ideas, faster results could be achieved through sprint methodologies, better results could be achieved through interdisciplinarity, and public-private partnerships could lower costs We present select results obtained during two summer sessions in 2016 and 2017 where the research was focused on topics in planetary defense, space resources and space weather, and utilized variational auto encoders, bayesian optimization, and deep learning techniques like deep, recurrent and residual neural networks. The FDL results demonstrate the power of bridging research disciplines and the potential that AI/ML has for supporting research goals, improving on current methodologies, enabling new discovery and doing so in accelerated timeframes.

  7. RanBP9 overexpression down-regulates phospho-cofilin, causes early synaptic deficits and impaired learning, and accelerates accumulation of amyloid plaques in the mouse brain.

    PubMed

    Palavicini, Juan Pablo; Wang, Hongjie; Minond, Dmitriy; Bianchi, Elisabetta; Xu, Shaohua; Lakshmana, Madepalli K

    2014-01-01

    Loss of synaptic proteins and functional synapses in the brains of patients with Alzheimer's disease (AD) as well as transgenic mouse models expressing amyloid-β protein precursor is now well established. However, the earliest age at which such loss of synapses occurs, and whether known markers of AD progression accelerate functional deficits is completely unknown. We previously showed that RanBP9 overexpression leads to enhanced amyloid plaque burden in a mouse model of AD. In this study, we found significant reductions in the levels of synaptophysin and spinophilin, compared with wild-type controls, in both the cortex and the hippocampus of 5- and 6-month old but not 3- or 4-month old APΔE9/RanBP9 triple transgenic mice, and not in APΔE9 double transgenic mice, nor in RanBP9 single transgenic mice. Interestingly, amyloid plaque burden was also increased in the APΔE9/RanBP9 mice at 5-6 months. Consistent with these results, we found significant deficits in learning and memory in the APΔE9/RanBP9 mice at 5 and 6 month. These data suggest that increased amyloid plaques and accelerated learning and memory deficits and loss of synaptic proteins induced by RanBP9 are correlated. Most importantly, APΔE9/RanBP9 mice also showed significantly reduced levels of the phosphorylated form of cofilin in the hippocampus. Taken together these data suggest that RanBP9 overexpression down-regulates cofilin, causes early synaptic deficits and impaired learning, and accelerates accumulation of amyloid plaques in the mouse brain.

  8. Implementation guidance for accelerated bridge construction in South Dakota

    DOT National Transportation Integrated Search

    2017-09-01

    A study was conducted to investigate implementation of accelerated bridge construction (ABC) in South Dakota. Accelerated bridge construction is defined as construction practices that employ innovative techniques to reduce on-site construction time a...

  9. Revitalizing pathology laboratories in a gastrointestinal pathophysiology course using multimedia and team-based learning techniques.

    PubMed

    Carbo, Alexander R; Blanco, Paola G; Graeme-Cooke, Fiona; Misdraji, Joseph; Kappler, Steven; Shaffer, Kitt; Goldsmith, Jeffrey D; Berzin, Tyler; Leffler, Daniel; Najarian, Robert; Sepe, Paul; Kaplan, Jennifer; Pitman, Martha; Goldman, Harvey; Pelletier, Stephen; Hayward, Jane N; Shields, Helen M

    2012-05-15

    In 2008, we changed the gastrointestinal pathology laboratories in a gastrointestinal pathophysiology course to a more interactive format using modified team-based learning techniques and multimedia presentations. The results were remarkably positive and can be used as a model for pathology laboratory improvement in any organ system. Over a two-year period, engaging and interactive pathology laboratories were designed. The initial restructuring of the laboratories included new case material, Digital Atlas of Video Education Project videos, animations and overlays. Subsequent changes included USMLE board-style quizzes at the beginning of each laboratory, with individual readiness assessment testing and group readiness assessment testing, incorporation of a clinician as a co-teacher and role playing for the student groups. Student responses for pathology laboratory contribution to learning improved significantly compared to baseline. Increased voluntary attendance at pathology laboratories was observed. Spontaneous student comments noted the positive impact of the laboratories on their learning. Pathology laboratory innovations, including modified team-based learning techniques with individual and group self-assessment quizzes, multimedia presentations, and paired teaching by a pathologist and clinical gastroenterologist led to improvement in student perceptions of pathology laboratory contributions to their learning and better pathology faculty evaluations. These changes can be universally applied to other pathology laboratories to improve student satisfaction. Copyright © 2012 Elsevier GmbH. All rights reserved.

  10. The Los Alamos Laser Acceleration of Particles Workshop and beginning of the advanced accelerator concepts field

    NASA Astrophysics Data System (ADS)

    Joshi, C.

    2012-12-01

    The first Advanced Acceleration of Particles-AAC-Workshop (actually named Laser Acceleration of Particles Workshop) was held at Los Alamos in January 1982. The workshop lasted a week and divided all the acceleration techniques into four categories: near field, far field, media, and vacuum. Basic theorems of particle acceleration were postulated (later proven) and specific experiments based on the four categories were formulated. This landmark workshop led to the formation of the advanced accelerator R&D program in the HEP office of the DOE that supports advanced accelerator research to this day. Two major new user facilities at Argonne and Brookhaven and several more directed experimental efforts were built to explore the advanced particle acceleration schemes. It is not an exaggeration to say that the intellectual breadth and excitement provided by the many groups who entered this new field provided the needed vitality to then recently formed APS Division of Beams and the new online journal Physical Review Special Topics-Accelerators and Beams. On this 30th anniversary of the AAC Workshops, it is worthwhile to look back at the legacy of the first Workshop at Los Alamos and the fine groundwork it laid for the field of advanced accelerator concepts that continues to flourish to this day.

  11. Convergence acceleration of viscous flow computations

    NASA Technical Reports Server (NTRS)

    Johnson, G. M.

    1982-01-01

    A multiple-grid convergence acceleration technique introduced for application to the solution of the Euler equations by means of Lax-Wendroff algorithms is extended to treat compressible viscous flow. Computational results are presented for the solution of the thin-layer version of the Navier-Stokes equations using the explicit MacCormack algorithm, accelerated by a convective coarse-grid scheme. Extensions and generalizations are mentioned.

  12. Helping Librarians To Encourage Critical Thinking through Active Learning Techniques in Library Instruction.

    ERIC Educational Resources Information Center

    Swaine, Cynthia Wright

    Encouraging librarians to incorporate critical thinking skills and active learning techniques in their course instruction requires more than talking about it in a department meeting or distributing articles on the topic. At Old Dominion University (Virginia), librarians have tried conducting workshops, had readily-accessible binders of articles…

  13. A systematic FPGA acceleration design for applications based on convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Dong, Hao; Jiang, Li; Li, Tianjian; Liang, Xiaoyao

    2018-04-01

    Most FPGA accelerators for convolutional neural network are designed to optimize the inner acceleration and are ignored of the optimization for the data path between the inner accelerator and the outer system. This could lead to poor performance in applications like real time video object detection. We propose a brand new systematic FPFA acceleration design to solve this problem. This design takes the data path optimization between the inner accelerator and the outer system into consideration and optimizes the data path using techniques like hardware format transformation, frame compression. It also takes fixed-point, new pipeline technique to optimize the inner accelerator. All these make the final system's performance very good, reaching about 10 times the performance comparing with the original system.

  14. Cortical plasticity associated with Braille learning.

    PubMed

    Hamilton, R H; Pascual-Leone, A

    1998-05-01

    Blind subjects who learn to read Braille must acquire the ability to extract spatial information from subtle tactile stimuli. In order to accomplish this, neuroplastic changes appear to take place. During Braille learning, the sensorimotor cortical area devoted to the representation of the reading finger enlarges. This enlargement follows a two-step process that can be demonstrated with transcranial magnetic stimulation mapping and suggests initial unmasking of existing connections and eventual establishment of more stable structural changes. In addition, Braille learning appears to be associated with the recruitment of parts of the occipital, formerly `visual', cortex (V1 and V2) for tactile information processing. In blind, proficient Braille readers, the occipital cortex can be shown not only to be associated with tactile Braille reading but also to be critical for reading accuracy. Recent studies suggest the possibility of applying non-invasive neurophysiological techniques to guide and improve functional outcomes of these plastic changes. Such interventions might provide a means of accelerating functional adjustment to blindness.

  15. Introduction of Parallel GPGPU Acceleration Algorithms for the Solution of Radiative Transfer

    NASA Technical Reports Server (NTRS)

    Godoy, William F.; Liu, Xu

    2011-01-01

    General-purpose computing on graphics processing units (GPGPU) is a recent technique that allows the parallel graphics processing unit (GPU) to accelerate calculations performed sequentially by the central processing unit (CPU). To introduce GPGPU to radiative transfer, the Gauss-Seidel solution of the well-known expressions for 1-D and 3-D homogeneous, isotropic media is selected as a test case. Different algorithms are introduced to balance memory and GPU-CPU communication, critical aspects of GPGPU. Results show that speed-ups of one to two orders of magnitude are obtained when compared to sequential solutions. The underlying value of GPGPU is its potential extension in radiative solvers (e.g., Monte Carlo, discrete ordinates) at a minimal learning curve.

  16. Advanced Accelerators: Particle, Photon and Plasma Wave Interactions

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

    Williams, Ronald L.

    2017-06-29

    The overall objective of this project was to study the acceleration of electrons to very high energies over very short distances based on trapping slowly moving electrons in the fast moving potential wells of large amplitude plasma waves, which have relativistic phase velocities. These relativistic plasma waves, or wakefields, are the basis of table-top accelerators that have been shown to accelerate electrons to the same high energies as kilometer-length linear particle colliders operating using traditional decades-old acceleration techniques. The accelerating electrostatic fields of the relativistic plasma wave accelerators can be as large as GigaVolts/meter, and our goal was to studymore » techniques for remotely measuring these large fields by injecting low energy probe electron beams across the plasma wave and measuring the beam’s deflection. Our method of study was via computer simulations, and these results suggested that the deflection of the probe electron beam was directly proportional to the amplitude of the plasma wave. This is the basis of a proposed diagnostic technique, and numerous studies were performed to determine the effects of changing the electron beam, plasma wave and laser beam parameters. Further simulation studies included copropagating laser beams with the relativistic plasma waves. New interesting results came out of these studies including the prediction that very small scale electron beam bunching occurs, and an anomalous line focusing of the electron beam occurs under certain conditions. These studies were summarized in the dissertation of a graduate student who obtained the Ph.D. in physics. This past research program has motivated ideas for further research to corroborate these results using particle-in-cell simulation tools which will help design a test-of-concept experiment in our laboratory and a scaled up version for testing at a major wakefield accelerator facility.« less

  17. Comparative Evaluation of Conventional and Accelerated Castings on Marginal Fit and Surface Roughness.

    PubMed

    Jadhav, Vivek Dattatray; Motwani, Bhagwan K; Shinde, Jitendra; Adhapure, Prasad

    2017-01-01

    The aim of this study was to evaluate the marginal fit and surface roughness of complete cast crowns made by a conventional and an accelerated casting technique. This study was divided into three parts. In Part I, the marginal fit of full metal crowns made by both casting techniques in the vertical direction was checked, in Part II, the fit of sectional metal crowns in the horizontal direction made by both casting techniques was checked, and in Part III, the surface roughness of disc-shaped metal plate specimens made by both casting techniques was checked. A conventional technique was compared with an accelerated technique. In Part I of the study, the marginal fit of the full metal crowns as well as in Part II, the horizontal fit of sectional metal crowns made by both casting techniques was determined, and in Part III, the surface roughness of castings made with the same techniques was compared. The results of the t -test and independent sample test do not indicate statistically significant differences in the marginal discrepancy detected between the two casting techniques. For the marginal discrepancy and surface roughness, crowns fabricated with the accelerated technique were significantly different from those fabricated with the conventional technique. Accelerated casting technique showed quite satisfactory results, but the conventional technique was superior in terms of marginal fit and surface roughness.

  18. 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.

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

    PubMed

    Zemp, Roland; Tanadini, Matteo; Plüss, Stefan; Schnüriger, Karin; Singh, Navrag B; Taylor, William R; Lorenzetti, Silvio

    2016-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  2. Prediction of activity type in preschool children using machine learning techniques.

    PubMed

    Hagenbuchner, Markus; Cliff, Dylan P; Trost, Stewart G; Van Tuc, Nguyen; Peoples, Gregory E

    2015-07-01

    Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Eleven children aged 3-6 years (mean age=4.8±0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  3. Summer Opportunity To Accelerate Reading (S.O.A.R.) Evaluation, 2001.

    ERIC Educational Resources Information Center

    Cury, Janice

    A study examined a program entitled "Summer Opportunity to Accelerate Reading" (S.O.A.R.), which provided early intervention to accelerate literacy learning for at-risk students completing kindergarten through grade 2 in 2000-01. Subjects were 2188 students enrolled in 12 S.O.A.R. campuses. Ethnicity was diverse with 58% Hispanic…

  4. Application accelerator system having bunch control

    DOEpatents

    Wang, Dunxiong; Krafft, Geoffrey Arthur

    1999-01-01

    An application accelerator system for monitoring the gain of a free electron laser. Coherent Synchrotron Radiation (CSR) detection techniques are used with a bunch length monitor for ultra short, picosec to several tens of femtosec, electron bunches. The monitor employs an application accelerator, a coherent radiation production device, an optical or beam chopping device, an infrared radiation collection device, a narrow-banding filter, an infrared detection device, and a control.

  5. Comparison of two different techniques of cooperative learning approach: Undergraduates' conceptual understanding in the context of hormone biochemistry.

    PubMed

    Mutlu, Ayfer

    2018-03-01

    The purpose of the research was to compare the effects of two different techniques of the cooperative learning approach, namely Team-Game Tournament and Jigsaw, on undergraduates' conceptual understanding in a Hormone Biochemistry course. Undergraduates were randomly assigned to Group 1 (N = 23) and Group 2 (N = 29). Instructions were accomplished using Team-Game Tournament in Group 1 and Jigsaw in Group 2. Before the instructions, all groups were informed about cooperative learning and techniques, their responsibilities in the learning process and accessing of resources. Instructions were conducted under the guidance of the researcher for nine weeks and the Hormone Concept Test developed by the researcher was used before and after the instructions for data collection. According to the results, while both techniques improved students' understanding, Jigsaw was more effective than Team-Game Tournament. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(2):114-120, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.

  6. Modeling of ion acceleration through drift and diffusion at interplanetary shocks

    NASA Technical Reports Server (NTRS)

    Decker, R. B.; Vlahos, L.

    1986-01-01

    A test particle simulation designed to model ion acceleration through drift and diffusion at interplanetary shocks is described. The technique consists of integrating along exact particle orbits in a system where the angle between the shock normal and mean upstream magnetic field, the level of magnetic fluctuations, and the energy of injected particles can assume a range of values. The technique makes it possible to study time-dependent shock acceleration under conditions not amenable to analytical techniques. To illustrate the capability of the numerical model, proton acceleration was considered under conditions appropriate for interplanetary shocks at 1 AU, including large-amplitude transverse magnetic fluctuations derived from power spectra of both ambient and shock-associated MHD waves.

  7. A new perspective on global mean sea level (GMSL) acceleration

    NASA Astrophysics Data System (ADS)

    Watson, Phil J.

    2016-06-01

    The vast body of contemporary climate change science is largely underpinned by the premise of a measured acceleration from anthropogenic forcings evident in key climate change proxies -- greenhouse gas emissions, temperature, and mean sea level. By virtue, over recent years, the issue of whether or not there is a measurable acceleration in global mean sea level has resulted in fierce, widespread professional, social, and political debate. Attempts to measure acceleration in global mean sea level (GMSL) have often used comparatively crude analysis techniques providing little temporal instruction on these key questions. This work proposes improved techniques to measure real-time velocity and acceleration based on five GMSL reconstructions spanning the time frame from 1807 to 2014 with substantially improved temporal resolution. While this analysis highlights key differences between the respective reconstructions, there is now more robust, convincing evidence of recent acceleration in the trend of GMSL.

  8. Theorists and Techniques: Connecting Education Theories to Lamaze Teaching Techniques

    PubMed Central

    Podgurski, Mary Jo

    2016-01-01

    ABSTRACT Should childbirth educators connect education theory to technique? Is there more to learning about theorists than memorizing facts for an assessment? Are childbirth educators uniquely poised to glean wisdom from theorists and enhance their classes with interactive techniques inspiring participant knowledge and empowerment? Yes, yes, and yes. This article will explore how an awareness of education theory can enhance retention of material through interactive learning techniques. Lamaze International childbirth classes already prepare participants for the childbearing year by using positive group dynamics; theory will empower childbirth educators to address education through well-studied avenues. Childbirth educators can provide evidence-based learning techniques in their classes and create true behavioral change. PMID:26848246

  9. Comparative Evaluation of Conventional and Accelerated Castings on Marginal Fit and Surface Roughness

    PubMed Central

    Jadhav, Vivek Dattatray; Motwani, Bhagwan K.; Shinde, Jitendra; Adhapure, Prasad

    2017-01-01

    Aims: The aim of this study was to evaluate the marginal fit and surface roughness of complete cast crowns made by a conventional and an accelerated casting technique. Settings and Design: This study was divided into three parts. In Part I, the marginal fit of full metal crowns made by both casting techniques in the vertical direction was checked, in Part II, the fit of sectional metal crowns in the horizontal direction made by both casting techniques was checked, and in Part III, the surface roughness of disc-shaped metal plate specimens made by both casting techniques was checked. Materials and Methods: A conventional technique was compared with an accelerated technique. In Part I of the study, the marginal fit of the full metal crowns as well as in Part II, the horizontal fit of sectional metal crowns made by both casting techniques was determined, and in Part III, the surface roughness of castings made with the same techniques was compared. Statistical Analysis Used: The results of the t-test and independent sample test do not indicate statistically significant differences in the marginal discrepancy detected between the two casting techniques. Results: For the marginal discrepancy and surface roughness, crowns fabricated with the accelerated technique were significantly different from those fabricated with the conventional technique. Conclusions: Accelerated casting technique showed quite satisfactory results, but the conventional technique was superior in terms of marginal fit and surface roughness. PMID:29042726

  10. Reduced Contact Hour Accelerated Courses and Student Learning

    ERIC Educational Resources Information Center

    Thornton, Barry; Demps, Julius; Jadav, Arpita

    2017-01-01

    Undergraduate instruction in the Davis College of Business at Jacksonville University utilizes two course delivery methods. Traditional daytime classes are 15 weeks long and have approximately 40 contact hours, while evening courses are offered in the Accelerated Degree program in a compressed 8-week format with 24 contact hours. The curriculum is…

  11. 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

  12. Summer Opportunity To Accelerate Reading (S.O.A.R.) Evaluation, 1998.

    ERIC Educational Resources Information Center

    Curry, Janice; Zyskowski, Gloria

    A study examined the "Summer Opportunity to Accelerate Reading" (S.O.A.R.) program, which provided early intervention to accelerate literacy learning for at-risk students entering grades 1-3 in the fall of 1998. Subjects were 388 students enrolled in 3 S.O.A.R. campuses from 37 Austin Independent School District (AISD) elementary schools…

  13. Situating e-Learning: Accelerating Precepts from the Past

    ERIC Educational Resources Information Center

    Carter, Susan; Sturm, Sean; González Geraldo, José Luis

    2014-01-01

    E-learning entails a different cognitive performativity from class or textual teaching and learning. It is critiqued through three case studies from lecturers working digitally in different ways. The authors' various challenges in shifting from the classroom to the "digitas" illuminate the risk of interpassivity into which…

  14. Decrystallization of Crystals Using Gold “Nano-Bullets” and the Metal-Assisted and Microwave-Accelerated Decrystallization Technique

    PubMed Central

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

    2017-01-01

    Gout is caused by the overproduction of uric acid and the inefficient metabolism of dietary purines in humans. Current treatments of gout, which include anti-inflammatory drugs, cyclooxygenase-2 inhibitors, and systemic glucocorticoids, have harmful side-effects. Our research laboratory has recently introduced an innovative approach for the decrystallization of biological and chemical crystals using the Metal-Assisted and Microwave-Accelerated Evaporative Decrystallization (MAMAD) technique. In the MAMAD technique, microwave energy is used to heat and activate gold nanoparticles that behave as “nano-bullets” to rapidly disrupt the crystal structure of biological crystals placed on planar surfaces. In this study, crystals of various sizes and compositions were studied as models for tophaceous gout at different stages (i.e., uric acid as small crystals (~10–100 μm) and L-alanine as medium (~300 μm) and large crystals (~4400 μm). Our results showed that the use of the MAMAD technique resulted in the reduction of the size and number of uric acid and L-alanine crystals up to >40% when exposed to intermittent microwave heating (up to 20 W power at 8 GHz) in the presence of 20 nm gold nanoparticles up to 120 s. This study demonstrates that the MAMAD technique can be potentially used as an alternative therapeutic method for the treatment of gout by effective decrystallization of large crystals, similar in size to those that often occur in gout. PMID:27763557

  15. Application accelerator system having bunch control

    DOEpatents

    Wang, D.; Krafft, G.A.

    1999-06-22

    An application accelerator system for monitoring the gain of a free electron laser is disclosed. Coherent Synchrotron Radiation (CSR) detection techniques are used with a bunch length monitor for ultra short, picosec to several tens of femtosec, electron bunches. The monitor employs an application accelerator, a coherent radiation production device, an optical or beam chopping device, an infrared radiation collection device, a narrow-banding filter, an infrared detection device, and a control. 1 fig.

  16. Cascade Back-Propagation Learning in Neural Networks

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A.

    2003-01-01

    The cascade back-propagation (CBP) algorithm is the basis of a conceptual design for accelerating learning in artificial neural networks. The neural networks would be implemented as analog very-large-scale integrated (VLSI) circuits, and circuits to implement the CBP algorithm would be fabricated on the same VLSI circuit chips with the neural networks. Heretofore, artificial neural networks have learned slowly because it has been necessary to train them via software, for lack of a good on-chip learning technique. The CBP algorithm is an on-chip technique that provides for continuous learning in real time. Artificial neural networks are trained by example: A network is presented with training inputs for which the correct outputs are known, and the algorithm strives to adjust the weights of synaptic connections in the network to make the actual outputs approach the correct outputs. The input data are generally divided into three parts. Two of the parts, called the "training" and "cross-validation" sets, respectively, must be such that the corresponding input/output pairs are known. During training, the cross-validation set enables verification of the status of the input-to-output transformation learned by the network to avoid over-learning. The third part of the data, termed the "test" set, consists of the inputs that are required to be transformed into outputs; this set may or may not include the training set and/or the cross-validation set. Proposed neural-network circuitry for on-chip learning would be divided into two distinct networks; one for training and one for validation. Both networks would share the same synaptic weights.

  17. Ion Beam Facilities at the National Centre for Accelerator based Research using a 3 MV Pelletron Accelerator

    NASA Astrophysics Data System (ADS)

    Trivedi, T.; Patel, Shiv P.; Chandra, P.; Bajpai, P. K.

    A 3.0 MV (Pelletron 9 SDH 4, NEC, USA) low energy ion accelerator has been recently installed as the National Centre for Accelerator based Research (NCAR) at the Department of Pure & Applied Physics, Guru Ghasidas Vishwavidyalaya, Bilaspur, India. The facility is aimed to carried out interdisciplinary researches using ion beams with high current TORVIS (for H, He ions) and SNICS (for heavy ions) ion sources. The facility includes two dedicated beam lines, one for ion beam analysis (IBA) and other for ion implantation/ irradiation corresponding to switching magnet at +20 and -10 degree, respectively. Ions with 60 kV energy are injected into the accelerator tank where after stripping positively charged ions are accelerated up to 29 MeV for Au. The installed ion beam analysis techniques include RBS, PIXE, ERDA and channelling.

  18. Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

    NASA Technical Reports Server (NTRS)

    Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

    2016-01-01

    Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

  19. Development of high intensity linear accelerator for heavy ion inertial fusion driver

    NASA Astrophysics Data System (ADS)

    Lu, Liang; Hattori, Toshiyuki; Hayashizaki, Noriyosu; Ishibashi, Takuya; Okamura, Masahiro; Kashiwagi, Hirotsugu; Takeuchi, Takeshi; Zhao, Hongwei; He, Yuan

    2013-11-01

    In order to verify the direct plasma injection scheme (DPIS), an acceleration test was carried out in 2001 using a radio frequency quadrupole (RFQ) heavy ion linear accelerator (linac) and a CO2-laser ion source (LIS) (Okamura et al., 2002) [1]. The accelerated carbon beam was observed successfully and the obtained current was 9.22 mA for C4+. To confirm the capability of the DPIS, we succeeded in accelerating 60 mA carbon ions with the DPIS in 2004 (Okamura et al., 2004; Kashiwagi and Hattori, 2004) [2,3]. We have studied a multi-beam type RFQ with an interdigital-H (IH) cavity that has a power-efficient structure in the low energy region. We designed and manufactured a two-beam type RFQ linac as a prototype for the multi-beam type linac; the beam acceleration test of carbon beams showed that it successfully accelerated from 5 keV/u up to 60 keV/u with an output current of 108 mA (2×54 mA/channel) (Ishibashi et al., 2011) [4]. We believe that the acceleration techniques of DPIS and the multi-beam type IH-RFQ linac are technical breakthroughs for heavy-ion inertial confinement fusion (HIF). The conceptual design of the RF linac with these techniques for HIF is studied. New accelerator-systems using these techniques for the HIF basic experiment are being designed to accelerate 400 mA carbon ions using four-beam type IH-RFQ linacs with DPIS. A model with a four-beam acceleration cavity was designed and manufactured to establish the proof of principle (PoP) of the accelerator.

  20. Detecting sea-level hazards: Simple regression-based methods for calculating the acceleration of sea level

    USGS Publications Warehouse

    Doran, Kara S.; Howd, Peter A.; Sallenger,, Asbury H.

    2016-01-04

    Recent studies, and most of their predecessors, use tide gage data to quantify SL acceleration, ASL(t). In the current study, three techniques were used to calculate acceleration from tide gage data, and of those examined, it was determined that the two techniques based on sliding a regression window through the time series are more robust compared to the technique that fits a single quadratic form to the entire time series, particularly if there is temporal variation in the magnitude of the acceleration. The single-fit quadratic regression method has been the most commonly used technique in determining acceleration in tide gage data. The inability of the single-fit method to account for time-varying acceleration may explain some of the inconsistent findings between investigators. Properly quantifying ASL(t) from field measurements is of particular importance in evaluating numerical models of past, present, and future SLR resulting from anticipated climate change.

  1. Optimizing laser-driven proton acceleration from overdense targets

    PubMed Central

    Stockem Novo, A.; Kaluza, M. C.; Fonseca, R. A.; Silva, L. O.

    2016-01-01

    We demonstrate how to tune the main ion acceleration mechanism in laser-plasma interactions to collisionless shock acceleration, thus achieving control over the final ion beam properties (e. g. maximum energy, divergence, number of accelerated ions). We investigate this technique with three-dimensional particle-in-cell simulations and illustrate a possible experimental realisation. The setup consists of an isolated solid density target, which is preheated by a first laser pulse to initiate target expansion, and a second one to trigger acceleration. The timing between the two laser pulses allows to access all ion acceleration regimes, ranging from target normal sheath acceleration, to hole boring and collisionless shock acceleration. We further demonstrate that the most energetic ions are produced by collisionless shock acceleration, if the target density is near-critical, ne ≈ 0.5 ncr. A scaling of the laser power shows that 100 MeV protons may be achieved in the PW range. PMID:27435449

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

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

    Hoogcarspel, S J; Kontaxis, C; Velden, J M van der

    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 developedmore » 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

  3. Mass spectrometry with accelerators.

    PubMed

    Litherland, A E; Zhao, X-L; Kieser, W E

    2011-01-01

    As one in a series of articles on Canadian contributions to mass spectrometry, this review begins with an outline of the history of accelerator mass spectrometry (AMS), noting roles played by researchers at three Canadian AMS laboratories. After a description of the unique features of AMS, three examples, (14)C, (10)Be, and (129)I are given to illustrate the methods. The capabilities of mass spectrometry have been extended by the addition of atomic isobar selection, molecular isobar attenuation, further ion acceleration, followed by ion detection and ion identification at essentially zero dark current or ion flux. This has been accomplished by exploiting the techniques and accelerators of atomic and nuclear physics. In 1939, the first principles of AMS were established using a cyclotron. In 1977 the selection of isobars in the ion source was established when it was shown that the (14)N(-) ion was very unstable, or extremely difficult to create, making a tandem electrostatic accelerator highly suitable for assisting the mass spectrometric measurement of the rare long-lived radioactive isotope (14)C in the environment. This observation, together with the large attenuation of the molecular isobars (13)CH(-) and (12)CH 2(-) during tandem acceleration and the observed very low background contamination from the ion source, was found to facilitate the mass spectrometry of (14)C to at least a level of (14)C/C ~ 6 × 10(-16), the equivalent of a radiocarbon age of 60,000 years. Tandem Accelerator Mass Spectrometry, or AMS, has now made possible the accurate radiocarbon dating of milligram-sized carbon samples by ion counting as well as dating and tracing with many other long-lived radioactive isotopes such as (10)Be, (26)Al, (36)Cl, and (129)I. The difficulty of obtaining large anion currents with low electron affinities and the difficulties of isobar separation, especially for the heavier mass ions, has prompted the use of molecular anions and the search for alternative

  4. The charged particle accelerators subsystems modeling

    NASA Astrophysics Data System (ADS)

    Averyanov, G. P.; Kobylyatskiy, A. V.

    2017-01-01

    Presented web-based resource for information support the engineering, science and education in Electrophysics, containing web-based tools for simulation subsystems charged particle accelerators. Formulated the development motivation of Web-Environment for Virtual Electrophysical Laboratories. Analyzes the trends of designs the dynamic web-environments for supporting of scientific research and E-learning, within the framework of Open Education concept.

  5. Mechanism of Isoflavone Aglycone's Effect on Cognitive Performance of Senescence-Accelerated Mice

    ERIC Educational Resources Information Center

    Yang, Hong; Jin, Guifang; Ren, Dongdong; Luo, Sijing; Zhou, Tianhong

    2011-01-01

    This study investigated the effect of isoflavone aglycone (IA) on the learning and memory performance of senescence-accelerated mice, and explored its neural protective mechanism. Results showed that SAM-P/8 senescence-accelerated mice treated with IA performed significantly better in the Y-maze cognitive test than the no treatment control (P less…

  6. Accelerated Leadership Development: Fast Tracking School Leaders

    ERIC Educational Resources Information Center

    Earley, Peter; Jones, Jeff

    2010-01-01

    "Accelerated Leadership Development" captures and communicates the lessons learned from successful fast-track leadership programmes in the private and public sector, and provides a model which schools can follow and customize as they plan their own leadership development strategies. As large numbers of headteachers and other senior staff…

  7. Machine-learning techniques for fast and accurate feature localization in holograms of colloidal particles

    NASA Astrophysics Data System (ADS)

    Hannel, Mark D.; Abdulali, Aidan; O'Brien, Michael; Grier, David G.

    2018-06-01

    Holograms of colloidal particles can be analyzed with the Lorenz-Mie theory of light scattering to measure individual particles' three-dimensional positions with nanometer precision while simultaneously estimating their sizes and refractive indexes. Extracting this wealth of information begins by detecting and localizing features of interest within individual holograms. Conventionally approached with heuristic algorithms, this image analysis problem can be solved faster and more generally with machine-learning techniques. We demonstrate that two popular machine-learning algorithms, cascade classifiers and deep convolutional neural networks (CNN), can solve the feature-localization problem orders of magnitude faster than current state-of-the-art techniques. Our CNN implementation localizes holographic features precisely enough to bootstrap more detailed analyses based on the Lorenz-Mie theory of light scattering. The wavelet-based Haar cascade proves to be less precise, but is so computationally efficient that it creates new opportunities for applications that emphasize speed and low cost. We demonstrate its use as a real-time targeting system for holographic optical trapping.

  8. Who Set the Fire? Determination of Arson Accelerants by GC-MS in an Instrumental Methods Course

    NASA Astrophysics Data System (ADS)

    Sodeman, David A.; Lillard, Sheri J.

    2001-09-01

    Forensic scenarios have advantages over traditional experiments in the instrumental laboratory from the perspectives of both teaching and learning. First, students feel that they are calculating more than just a number from their experiments and that their results have meaning. Second, we are teaching techniques that are used in the real world and students can no longer complain, "This is not how it is done in the real world." This experiment is designed for upper-division chemistry and chemical engineering majors taking an instrumental methods course. The experimental approach simulates the steps an arson investigator would take to determine if arson was the cause of a fire. Charred (unknown) samples of wood and five standards of liquid accelerants are prepared in sealed containers and presented to the students for headspace gas chromatography (GC) with quadrupole mass spectrometric (MS) detection. Students interpret the standards and the charred samples using chromatographic retention times and MS data. From this information, they determine which accelerant was used to start the fire. They are also asked to discuss differences between the chromatograms of the charred sample and the corresponding liquid accelerant.

  9. The laser accelerator-another unicorn in the garden

    NASA Astrophysics Data System (ADS)

    Hand, L. N.

    1981-07-01

    Some proposed techniques for using laser beams to accelerate charged particles was reviewed. Two specific ideas for grating type accelerating structures are discussed. Speculations are presented about how a successful laser accelerator could be used in a multipass collider; a type of machine which would have characteristics intermediate between those of synchrotrons and linear (single pass) colliders. No definite conclusions about practical structures for laser accelerators are reached, but it is suggested that a serious effort be made to design a small prototype machine. Achieving a reasonable luminosity demands that the accelerator either be a cw machine or that laser peak power requirements to be much higher than those presently available. Use of superconducting gratings requires a wavelength in the sub-millimeter range.

  10. TH-EF-204-00: AAPM-AMPR (Russia)-SEFM (Spain) Joint Course On Challenges and Advantages of Small Field Radiation Treatment Techniques

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

    NONE

    Joanna E. Cygler, Jan Seuntjens, J. Daniel Bourland, M. Saiful Huq, Josep Puxeu Vaque, Daniel Zucca Aparicio, Tatiana Krylova, Yuri Kirpichev, Eric Ford, Caridad Borras Stereotactic Radiation Therapy (SRT) utilizes small static and dynamic (IMRT) fields, to successfully treat malignant and benign diseases using techniques such as Stereotactic Radiosurgery (SRS) and Stereotactic Body Radiation Therapy (SBRT). SRT is characterized by sharp dose gradients for individual fields and their resultant dose distributions. For appropriate targets, small field radiotherapy offers improved treatment quality by allowing better sparing of organs at risk while delivering the prescribed target dose. Specialized small field treatment deliverymore » systems, such as robotic-controlled linear accelerators, gamma radiosurgery units, and dynamic arc linear accelerators may utilize rigid fixation, image guidance, and tumor tracking, to insure precise dose delivery to static or moving targets. However, in addition to great advantages, small field delivery techniques present special technical challenges for dose calibration due to unique geometries and small field sizes not covered by existing reference dosimetry protocols such as AAPM TG-51 or IAEA TRS 398. In recent years extensive research has been performed to understand small field dosimetry and measurement instrumentation. AAPM, IAEA and ICRU task groups are expected to provide soon recommendations on the dosimetry of small radiation fields. In this symposium we will: 1] discuss the physics, instrumentation, methodologies and challenges for small field radiation dose measurements; 2] review IAEA and ICRU recommendations on prescribing, recording and reporting of small field radiation therapy; 3] discuss selected clinical applications and technical aspects for specialized image-guided, small field, linear accelerator based treatment techniques such as IMRT and SBRT. Learning Objectives: To learn the physics of small fields in

  11. 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…

  12. Classification of breast tumour using electrical impedance and machine learning techniques.

    PubMed

    Al Amin, Abdullah; Parvin, Shahnaj; Kadir, M A; Tahmid, Tasmia; Alam, S Kaisar; Siddique-e Rabbani, K

    2014-06-01

    When a breast lump is detected through palpation, mammography or ultrasonography, the final test for characterization of the tumour, whether it is malignant or benign, is biopsy. This is invasive and carries hazards associated with any surgical procedures. The present work was undertaken to study the feasibility for such characterization using non-invasive electrical impedance measurements and machine learning techniques. Because of changes in cell morphology of malignant and benign tumours, changes are expected in impedance at a fixed frequency, and versus frequency of measurement. Tetrapolar impedance measurement (TPIM) using four electrodes at the corners of a square region of sides 4 cm was used for zone localization. Data of impedance in two orthogonal directions, measured at 5 and 200 kHz from 19 subjects, and their respective slopes with frequency were subjected to machine learning procedures through the use of feature plots. These patients had single or multiple tumours of various types in one or both breasts, and four of them had malignant tumours, as diagnosed by core biopsy. Although size and depth of the tumours are expected to affect the measurements, this preliminary work ignored these effects. Selecting 12 features from the above measurements, feature plots were drawn for the 19 patients, which displayed considerable overlap between malignant and benign cases. However, based on observed qualitative trend of the measured values, when all the feature values were divided by respective ages, the two types of tumours separated out reasonably well. Using K-NN classification method the results obtained are, positive prediction value: 60%, negative prediction value: 93%, sensitivity: 75%, specificity: 87% and efficacy: 84%, which are very good for such a test on a small sample size. Study on a larger sample is expected to give confidence in this technique, and further improvement of the technique may have the ability to replace biopsy.

  13. Analysis of the accelerated crucible rotation technique applied to the gradient freeze growth of cadmium zinc telluride

    NASA Astrophysics Data System (ADS)

    Divecha, Mia S.; Derby, Jeffrey J.

    2017-06-01

    We employ finite-element modeling to assess the effects of the accelerated crucible rotation technique (ACRT) on cadmium zinc telluride (CZT) crystals grown from a gradient freeze system. Via consideration of tellurium segregation and transport, we show, for the first time, that steady growth from a tellurium-rich melt produces persistent undercooling in front of the growth interface, likely leading to morphological instability. The application of ACRT rearranges melt flows and tellurium transport but, in contrast to conventional wisdom, does not altogether eliminate undercooling of the melt. Rather, a much more complicated picture arises, where spatio-temporal realignment of undercooled melt may act to locally suppress instability. A better understanding of these mechanisms and quantification of their overall effects will allow for future growth optimization.

  14. Miniature penetrator (MinPen) acceleration recorder development test

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

    Franco, R.J.; Platzbecker, M.R.

    1998-08-01

    The Telemetry Technology Development Department at Sandia National Laboratories actively develops and tests acceleration recorders for penetrating weapons. This new acceleration recorder (MinPen) utilizes a microprocessor-based architecture for operational flexibility while maintaining electronics and packaging techniques developed over years of penetrator testing. MinPen has been demonstrated to function in shock environments up to 20,000 Gs. The MinPen instrumentation development has resulted in a rugged, versatile, miniature acceleration recorder and is a valuable tool for penetrator testing in a wide range of applications.

  15. Evaluation of undergraduate clinical learning experiences in the subject of pediatric dentistry using critical incident technique.

    PubMed

    Vyawahare, S; Banda, N R; Choubey, S; Parvekar, P; Barodiya, A; Dutta, S

    2013-01-01

    In pediatric dentistry, the experiences of dental students may help dental educators better prepare graduates to treat the children. Research suggests that student's perceptions should be considered in any discussion of their education, but there has been no systematic examination of India's undergraduate dental students learning experiences. This qualitative investigation aimed to gather and analyze information about experiences in pediatric dentistry from the students' viewpoint using critical incident technique (CIT). The sample group for this investigation came from all 240 3rd and 4th year dental students from all the four dental colleges in Indore. Using CIT, participants were asked to describe at least one positive and one negative experience in detail. They described 308 positive and 359 negative experiences related to the pediatric dentistry clinic. Analysis of the data resulted in the identification of four key factors related to their experiences: 1) The instructor; 2) the patient; 3) the learning process; and 4) the learning environment. The CIT is a useful data collection and analysis technique that provides rich, useful data and has many potential uses in dental education.

  16. Innovative single-shot diagnostics for electrons from laser wakefield acceleration at FLAME

    NASA Astrophysics Data System (ADS)

    Bisesto, F. G.; Anania, M. P.; Cianchi, A.; Chiadroni, E.; Curcio, A.; Ferrario, M.; Pompili, R.; Zigler, A.

    2017-07-01

    Plasma wakefield acceleration is the most promising acceleration technique known nowadays, able to provide very high accelerating fields (> 100 GV/m), enabling acceleration of electrons to GeV energy in few centimeters. Here we present all the plasma related activities currently underway at SPARC_LAB exploiting the high power laser FLAME. In particular, we will give an overview of the single shot diagnostics employed: Electro Optic Sampling (EOS) for temporal measurement and Optical Transition Radiation (OTR) for an innovative one shot emittance measurements. In detail, the EOS technique has been employed to measure for the first time the longitudinal profile of electric field of fast electrons escaping from a solid target, driving the ions and protons acceleration, and to study the impact of using different target shapes. Moreover, a novel scheme for one shot emittance measurements based on OTR, developed and tested at SPARC_LAB LINAC, used in an experiment on electrons from laser wakefield acceleration still undergoing, will be shown.

  17. Modeling target normal sheath acceleration using handoffs between multiple simulations

    NASA Astrophysics Data System (ADS)

    McMahon, Matthew; Willis, Christopher; Mitchell, Robert; King, Frank; Schumacher, Douglass; Akli, Kramer; Freeman, Richard

    2013-10-01

    We present a technique to model the target normal sheath acceleration (TNSA) process using full-scale LSP PIC simulations. The technique allows for a realistic laser, full size target and pre-plasma, and sufficient propagation length for the accelerated ions and electrons. A first simulation using a 2D Cartesian grid models the laser-plasma interaction (LPI) self-consistently and includes field ionization. Electrons accelerated by the laser are imported into a second simulation using a 2D cylindrical grid optimized for the initial TNSA process and incorporating an equation of state. Finally, all of the particles are imported to a third simulation optimized for the propagation of the accelerated ions and utilizing a static field solver for initialization. We also show use of 3D LPI simulations. Simulation results are compared to recent ion acceleration experiments using SCARLET laser at The Ohio State University. This work was performed with support from ASOFR under contract # FA9550-12-1-0341, DARPA, and allocations of computing time from the Ohio Supercomputing Center.

  18. Genetic algorithm enhanced by machine learning in dynamic aperture optimization

    NASA Astrophysics Data System (ADS)

    Li, Yongjun; Cheng, Weixing; Yu, Li Hua; Rainer, Robert

    2018-05-01

    With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given "elite" status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitness of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. The machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.

  19. Compact lumped circuit model of discharges in DC accelerator using partial element equivalent circuit

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

    Banerjee, Srutarshi; Rajan, Rehim N.; Singh, Sandeep K.

    2014-07-01

    DC Accelerators undergoes different types of discharges during its operation. A model depicting the discharges has been simulated to study the different transient conditions. The paper presents a Physics based approach of developing a compact circuit model of the DC Accelerator using Partial Element Equivalent Circuit (PEEC) technique. The equivalent RLC model aids in analyzing the transient behavior of the system and predicting anomalies in the system. The electrical discharges and its properties prevailing in the accelerator can be evaluated by this equivalent model. A parallel coupled voltage multiplier structure is simulated in small scale using few stages of coronamore » guards and the theoretical and practical results are compared. The PEEC technique leads to a simple model for studying the fault conditions in accelerator systems. Compared to the Finite Element Techniques, this technique gives the circuital representation. The lumped components of the PEEC are used to obtain the input impedance and the result is also compared to that of the FEM technique for a frequency range of (0-200) MHz. (author)« less

  20. Hardware Acceleration of Adaptive Neural Algorithms.

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

    James, Conrad D.

    As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - worldmore » conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.« less

  1. Split Bregman multicoil accelerated reconstruction technique: A new framework for rapid reconstruction of cardiac perfusion MRI

    PubMed Central

    Kamesh Iyer, Srikant; Tasdizen, Tolga; Likhite, Devavrat; DiBella, Edward

    2016-01-01

    Purpose: Rapid reconstruction of undersampled multicoil MRI data with iterative constrained reconstruction method is a challenge. The authors sought to develop a new substitution based variable splitting algorithm for faster reconstruction of multicoil cardiac perfusion MRI data. Methods: The new method, split Bregman multicoil accelerated reconstruction technique (SMART), uses a combination of split Bregman based variable splitting and iterative reweighting techniques to achieve fast convergence. Total variation constraints are used along the spatial and temporal dimensions. The method is tested on nine ECG-gated dog perfusion datasets, acquired with a 30-ray golden ratio radial sampling pattern and ten ungated human perfusion datasets, acquired with a 24-ray golden ratio radial sampling pattern. Image quality and reconstruction speed are evaluated and compared to a gradient descent (GD) implementation and to multicoil k-t SLR, a reconstruction technique that uses a combination of sparsity and low rank constraints. Results: Comparisons based on blur metric and visual inspection showed that SMART images had lower blur and better texture as compared to the GD implementation. On average, the GD based images had an ∼18% higher blur metric as compared to SMART images. Reconstruction of dynamic contrast enhanced (DCE) cardiac perfusion images using the SMART method was ∼6 times faster than standard gradient descent methods. k-t SLR and SMART produced images with comparable image quality, though SMART was ∼6.8 times faster than k-t SLR. Conclusions: The SMART method is a promising approach to reconstruct good quality multicoil images from undersampled DCE cardiac perfusion data rapidly. PMID:27036592

  2. Accelerator Science: Collider vs. Fixed Target

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

    Lincoln, Don

    Particle physics experiments employ high energy particle accelerators to make their measurements. However there are many kinds of particle accelerators with many interesting techniques. One important dichotomy is whether one takes a particle beam and have it hit a stationary target of atoms, or whether one takes two counter rotating beams of particles and smashes them together head on. In this video, Fermilab’s Dr. Don Lincoln explains the pros and cons of these two powerful methods of exploring the rules of the universe.

  3. Accelerator Science: Collider vs. Fixed Target

    ScienceCinema

    Lincoln, Don

    2018-01-16

    Particle physics experiments employ high energy particle accelerators to make their measurements. However there are many kinds of particle accelerators with many interesting techniques. One important dichotomy is whether one takes a particle beam and have it hit a stationary target of atoms, or whether one takes two counter rotating beams of particles and smashes them together head on. In this video, Fermilab’s Dr. Don Lincoln explains the pros and cons of these two powerful methods of exploring the rules of the universe.

  4. Accelerating atomic structure search with cluster regularization

    NASA Astrophysics Data System (ADS)

    Sørensen, K. H.; Jørgensen, M. S.; Bruix, A.; Hammer, B.

    2018-06-01

    We present a method for accelerating the global structure optimization of atomic compounds. The method is demonstrated to speed up the finding of the anatase TiO2(001)-(1 × 4) surface reconstruction within a density functional tight-binding theory framework using an evolutionary algorithm. As a key element of the method, we use unsupervised machine learning techniques to categorize atoms present in a diverse set of partially disordered surface structures into clusters of atoms having similar local atomic environments. Analysis of more than 1000 different structures shows that the total energy of the structures correlates with the summed distances of the atomic environments to their respective cluster centers in feature space, where the sum runs over all atoms in each structure. Our method is formulated as a gradient based minimization of this summed cluster distance for a given structure and alternates with a standard gradient based energy minimization. While the latter minimization ensures local relaxation within a given energy basin, the former enables escapes from meta-stable basins and hence increases the overall performance of the global optimization.

  5. Bioimaging of cells and tissues using accelerator-based sources.

    PubMed

    Petibois, Cyril; Cestelli Guidi, Mariangela

    2008-07-01

    A variety of techniques exist that provide chemical information in the form of a spatially resolved image: electron microprobe analysis, nuclear microprobe analysis, synchrotron radiation microprobe analysis, secondary ion mass spectrometry, and confocal fluorescence microscopy. Linear (LINAC) and circular (synchrotrons) particle accelerators have been constructed worldwide to provide to the scientific community unprecedented analytical performances. Now, these facilities match at least one of the three analytical features required for the biological field: (1) a sufficient spatial resolution for single cell (< 1 mum) or tissue (<1 mm) analyses, (2) a temporal resolution to follow molecular dynamics, and (3) a sensitivity in the micromolar to nanomolar range, thus allowing true investigations on biological dynamics. Third-generation synchrotrons now offer the opportunity of bioanalytical measurements at nanometer resolutions with incredible sensitivity. Linear accelerators are more specialized in their physical features but may exceed synchrotron performances. All these techniques have become irreplaceable tools for developing knowledge in biology. This review highlights the pros and cons of the most popular techniques that have been implemented on accelerator-based sources to address analytical issues on biological specimens.

  6. Research on evaluation and standardization of accelerated bridge construction techniques, part II.

    DOT National Transportation Integrated Search

    2015-09-01

    The Michigan Department of Transportation (MDOT) uses Accelerated bridge construction : (ABC) to reduce delays and minimize construction impacts. MDOT contracted and completed : several bridges using prefabricated bridge elements and systems (PBES). ...

  7. Research on evaluation and standardization of accelerated bridge construction techniques, part I.

    DOT National Transportation Integrated Search

    2015-09-01

    The Michigan Department of Transportation (MDOT) uses Accelerated bridge construction : (ABC) to reduce delays and minimize construction impacts. MDOT contracted and completed : several bridges using prefabricated bridge elements and systems (PBES). ...

  8. Implementing Collaborative Learning in Prelicensure Nursing Curricula: Student Perceptions and Learning Outcomes.

    PubMed

    Schoening, Anne M; Selde, M Susan; Goodman, Joely T; Tow, Joyce C; Selig, Cindy L; Wichman, Chris; Cosimano, Amy; Galt, Kimberly A

    2015-01-01

    This study evaluated learning outcomes and student perceptions of collaborative learning in an undergraduate nursing program. Participants in this 3-phase action research study included students enrolled in a traditional and an accelerated nursing program. The number of students who passed the unit examination was not significantly different between the 3 phases. Students had positive and negative perceptions about the use of collaborative learning.

  9. Acceleration modules in linear induction accelerators

    NASA Astrophysics Data System (ADS)

    Wang, Shao-Heng; Deng, Jian-Jun

    2014-05-01

    The Linear Induction Accelerator (LIA) is a unique type of accelerator that is capable of accelerating kilo-Ampere charged particle current to tens of MeV energy. The present development of LIA in MHz bursting mode and the successful application into a synchrotron have broadened LIA's usage scope. Although the transformer model is widely used to explain the acceleration mechanism of LIAs, it is not appropriate to consider the induction electric field as the field which accelerates charged particles for many modern LIAs. We have examined the transition of the magnetic cores' functions during the LIA acceleration modules' evolution, distinguished transformer type and transmission line type LIA acceleration modules, and re-considered several related issues based on transmission line type LIA acceleration module. This clarified understanding should help in the further development and design of LIA acceleration modules.

  10. Retention of Information Taught in Introductory Psychology Courses across Different Accelerated Course Formats

    ERIC Educational Resources Information Center

    Deichert, Nathan T.; Maxwell, Shannon J.; Klotz, Joseph

    2016-01-01

    The current study is a quasi-experimental examination of the effects of traditional and accelerated course formats on learning retention. The study analyzed data on an end-of-course exam collected from 132 students enrolled in introductory psychology courses across 3 course formats: a traditional 16-week format, a 5-week accelerated format, and an…

  11. Modeling Learning and Memory Using Verbal Learning Tests: Results From ACTIVE

    PubMed Central

    Gross, Alden L.

    2013-01-01

    Objective. To investigate the influence of memory training on initial recall and learning. Method. The Advanced Cognitive Training for Independent and Vital Elderly study of community-dwelling adults older than age 65 (n = 1,401). We decomposed trial-level recall in the Auditory Verbal Learning Test (AVLT) and Hopkins Verbal Learning Test (HVLT) into initial recall and learning across trials using latent growth models. Results. Trial-level increases in words recalled in the AVLT and HVLT at each follow-up visit followed an approximately logarithmic shape. Over the 5-year study period, memory training was associated with slower decline in Trial 1 AVLT recall (Cohen’s d = 0.35, p = .03) and steep pre- and posttraining acceleration in learning (d = 1.56, p < .001). Findings were replicated using the HVLT (decline in initial recall, d = 0.60, p = .01; pre- and posttraining acceleration in learning, d = 3.10, p < .001). Because of the immediate training boost, the memory-trained group had a higher level of recall than the control group through the end of the 5-year study period despite faster decline in learning. Discussion. This study contributes to the understanding of the mechanisms by which training benefits memory and expands current knowledge by reporting long-term changes in initial recall and learning, as measured from growth models and by characterization of the impact of memory training on these components. Results reveal that memory training delays the worsening of memory span and boosts learning. PMID:22929389

  12. Modeling learning and memory using verbal learning tests: results from ACTIVE.

    PubMed

    Gross, Alden L; Rebok, George W; Brandt, Jason; Tommet, Doug; Marsiske, Michael; Jones, Richard N

    2013-03-01

    To investigate the influence of memory training on initial recall and learning. The Advanced Cognitive Training for Independent and Vital Elderly study of community-dwelling adults older than age 65 (n = 1,401). We decomposed trial-level recall in the Auditory Verbal Learning Test (AVLT) and Hopkins Verbal Learning Test (HVLT) into initial recall and learning across trials using latent growth models. Trial-level increases in words recalled in the AVLT and HVLT at each follow-up visit followed an approximately logarithmic shape. Over the 5-year study period, memory training was associated with slower decline in Trial 1 AVLT recall (Cohen's d = 0.35, p = .03) and steep pre- and posttraining acceleration in learning (d = 1.56, p < .001). Findings were replicated using the HVLT (decline in initial recall, d = 0.60, p = .01; pre- and posttraining acceleration in learning, d = 3.10, p < .001). Because of the immediate training boost, the memory-trained group had a higher level of recall than the control group through the end of the 5-year study period despite faster decline in learning. This study contributes to the understanding of the mechanisms by which training benefits memory and expands current knowledge by reporting long-term changes in initial recall and learning, as measured from growth models and by characterization of the impact of memory training on these components. Results reveal that memory training delays the worsening of memory span and boosts learning.

  13. Computer modeling of test particle acceleration at oblique shocks

    NASA Technical Reports Server (NTRS)

    Decker, Robert B.

    1988-01-01

    The present evaluation of the basic techniques and illustrative results of charged particle-modeling numerical codes suitable for particle acceleration at oblique, fast-mode collisionless shocks emphasizes the treatment of ions as test particles, calculating particle dynamics through numerical integration along exact phase-space orbits. Attention is given to the acceleration of particles at planar, infinitessimally thin shocks, as well as to plasma simulations in which low-energy ions are injected and accelerated at quasi-perpendicular shocks with internal structure.

  14. Essay: Robert H. Siemann As Leader of the Advanced Accelerator Research Department

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

    Colby, Eric R.; Hogan, Mark J.; /SLAC

    Robert H. Siemann originally conceived of the Advanced Accelerator Research Department (AARD) as an academic, experimental group dedicated to probing the technical limitations of accelerators while providing excellent educational opportunities for young scientists. The early years of the Accelerator Research Department B, as it was then known, were dedicated to a wealth of mostly student-led experiments to examine the promise of advanced accelerator techniques. High-gradient techniques including millimeter-wave rf acceleration, beam-driven plasma acceleration, and direct laser acceleration were pursued, including tests of materials under rf pulsed heating and short-pulse laser radiation, to establish the ultimate limitations on gradient. As themore » department and program grew, so did the motivation to found an accelerator research center that brought experimentalists together in a test facility environment to conduct a broad range of experiments. The Final Focus Test Beam and later the Next Linear Collider Test Accelerator provided unique experimental facilities for AARD staff and collaborators to carry out advanced accelerator experiments. Throughout the evolution of this dynamic program, Bob maintained a department atmosphere and culture more reminiscent of a university research group than a national laboratory department. His exceptional ability to balance multiple roles as scientist, professor, and administrator enabled the creation and preservation of an environment that fostered technical innovation and scholarship.« less

  15. Supporting Student Learning

    ERIC Educational Resources Information Center

    Williamson, Ronald; Blackburn, Barbara R.

    2010-01-01

    The organization and structure of a school can affect one's ability to improve student learning. Structural elements--such as the way time is used, the arrangements for collaboration, and the opportunities for sustained discussion of student learning in one's school--can either be barriers to reform or ways to accelerate the work. This article…

  16. Developing Learning Tool of Control System Engineering Using Matrix Laboratory Software Oriented on Industrial Needs

    NASA Astrophysics Data System (ADS)

    Isnur Haryudo, Subuh; Imam Agung, Achmad; Firmansyah, Rifqi

    2018-04-01

    The purpose of this research is to develop learning media of control technique using Matrix Laboratory software with industry requirement approach. Learning media serves as a tool for creating a better and effective teaching and learning situation because it can accelerate the learning process in order to enhance the quality of learning. Control Techniques using Matrix Laboratory software can enlarge the interest and attention of students, with real experience and can grow independent attitude. This research design refers to the use of research and development (R & D) methods that have been modified by multi-disciplinary team-based researchers. This research used Computer based learning method consisting of computer and Matrix Laboratory software which was integrated with props. Matrix Laboratory has the ability to visualize the theory and analysis of the Control System which is an integration of computing, visualization and programming which is easy to use. The result of this instructional media development is to use mathematical equations using Matrix Laboratory software on control system application with DC motor plant and PID (Proportional-Integral-Derivative). Considering that manufacturing in the field of Distributed Control systems (DCSs), Programmable Controllers (PLCs), and Microcontrollers (MCUs) use PID systems in production processes are widely used in industry.

  17. The Road Taken That Has Made All the Difference: A Narrative Inquiry of Student Engagement and Success in Butler Community College's Accelerated Learning Program in English

    ERIC Educational Resources Information Center

    Nordman, Troy Douglas

    2017-01-01

    The purpose of this dissertation was to investigate whether students who completed the accelerated learning program (ALP) in English at Butler Community College in fall 2016 perceived a three-part, structured approach to the course as having been a significant factor to their persistence and successful completion of the course. These perceptions…

  18. 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),…

  19. 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.

  20. 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…

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

    PubMed

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

    2004-01-01

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

  2. 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.

  3. Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project.

    PubMed

    Sakr, Sherif; Elshawi, Radwa; Ahmed, Amjad M; Qureshi, Waqas T; Brawner, Clinton A; Keteyian, Steven J; Blaha, Michael J; Al-Mallah, Mouaz H

    2017-12-19

    Prior studies have demonstrated that cardiorespiratory fitness (CRF) is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined categories. The aim of this study is to present an evaluation and comparison of how machine learning techniques can be applied on medical records of cardiorespiratory fitness and how the various techniques differ in terms of capabilities of predicting medical outcomes (e.g. mortality). We use data of 34,212 patients free of known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems Between 1991 and 2009 and had a complete 10-year follow-up. Seven machine learning classification techniques were evaluated: Decision Tree (DT), Support Vector Machine (SVM), Artificial Neural Networks (ANN), Naïve Bayesian Classifier (BC), Bayesian Network (BN), K-Nearest Neighbor (KNN) and Random Forest (RF). In order to handle the imbalanced dataset used, the Synthetic Minority Over-Sampling Technique (SMOTE) is used. Two set of experiments have been conducted with and without the SMOTE sampling technique. On average over different evaluation metrics, SVM Classifier has shown the lowest performance while other models like BN, BC and DT performed better. The RF classifier has shown the best performance (AUC = 0.97) among all models trained using the SMOTE sampling. The results show that various ML techniques can significantly vary in terms of its performance for the different evaluation metrics. It is also not necessarily that the more complex the ML model, the more prediction accuracy can be achieved. The prediction performance of all models trained with SMOTE is much better than the performance of models trained without SMOTE. The study shows the potential of machine learning methods for predicting all-cause mortality using cardiorespiratory fitness

  4. SU-F-T-201: Acceleration of Dose Optimization Process Using Dual-Loop Optimization Technique for Spot Scanning Proton Therapy

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

    Hirayama, S; Fujimoto, R

    Purpose: The purpose was to demonstrate a developed acceleration technique of dose optimization and to investigate its applicability to the optimization process in a treatment planning system (TPS) for proton therapy. Methods: In the developed technique, the dose matrix is divided into two parts, main and halo, based on beam sizes. The boundary of the two parts is varied depending on the beam energy and water equivalent depth by utilizing the beam size as a singular threshold parameter. The optimization is executed with two levels of iterations. In the inner loop, doses from the main part are updated, whereas dosesmore » from the halo part remain constant. In the outer loop, the doses from the halo part are recalculated. We implemented this technique to the optimization process in the TPS and investigated the dependence on the target volume of the speedup effect and applicability to the worst-case optimization (WCO) in benchmarks. Results: We created irradiation plans for various cubic targets and measured the optimization time varying the target volume. The speedup effect was improved as the target volume increased, and the calculation speed increased by a factor of six for a 1000 cm3 target. An IMPT plan for the RTOG benchmark phantom was created in consideration of ±3.5% range uncertainties using the WCO. Beams were irradiated at 0, 45, and 315 degrees. The target’s prescribed dose and OAR’s Dmax were set to 3 Gy and 1.5 Gy, respectively. Using the developed technique, the calculation speed increased by a factor of 1.5. Meanwhile, no significant difference in the calculated DVHs was found before and after incorporating the technique into the WCO. Conclusion: The developed technique could be adapted to the TPS’s optimization. The technique was effective particularly for large target cases.« less

  5. Tracking Active Learning in the Medical School Curriculum: A Learning-Centered Approach.

    PubMed

    McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine

    2018-01-01

    Medical education is moving toward active learning during large group lecture sessions. This study investigated the saturation and breadth of active learning techniques implemented in first year medical school large group sessions. Data collection involved retrospective curriculum review and semistructured interviews with 20 faculty. The authors piloted a taxonomy of active learning techniques and mapped learning techniques to attributes of learning-centered instruction. Faculty implemented 25 different active learning techniques over the course of 9 first year courses. Of 646 hours of large group instruction, 476 (74%) involved at least 1 active learning component. The frequency and variety of active learning components integrated throughout the year 1 curriculum reflect faculty familiarity with active learning methods and their support of an active learning culture. This project has sparked reflection on teaching practices and facilitated an evolution from teacher-centered to learning-centered instruction.

  6. Accelerators for Cancer Therapy

    DOE R&D Accomplishments Database

    Lennox, Arlene J.

    2000-05-30

    The vast majority of radiation treatments for cancerous tumors are given using electron linacs that provide both electrons and photons at several energies. Design and construction of these linacs are based on mature technology that is rapidly becoming more and more standardized and sophisticated. The use of hadrons such as neutrons, protons, alphas, or carbon, oxygen and neon ions is relatively new. Accelerators for hadron therapy are far from standardized, but the use of hadron therapy as an alternative to conventional radiation has led to significant improvements and refinements in conventional treatment techniques. This paper presents the rationale for radiation therapy, describes the accelerators used in conventional and hadron therapy, and outlines the issues that must still be resolved in the emerging field of hadron therapy.

  7. The Organizational Culture and Structure of Accelerated Schools.

    ERIC Educational Resources Information Center

    Steaffens, Susan; McCarthy, Jane; Putney, LeAnn; Steinhoff, Carl

    This paper describes the organizational culture and structure of five accelerated schools in the Clark County School District in Nevada, focusing on the similarities and differences among these schools. The cultural aspects of the schools under comparison included the guiding principles, the central values, and the learning philosophy, whereas the…

  8. Optical Diagnostics for Plasma-based Particle Accelerators

    NASA Astrophysics Data System (ADS)

    Muggli, Patric

    2009-05-01

    One of the challenges for plasma-based particle accelerators is to measure the spatio-temporal characteristics of the accelerated particle bunch. ``Optical'' diagnostics are particularly interesting and useful because of the large number of techniques that exits to determine the properties of photon pulses. The accelerated bunch can produce photons pulses that carry information about its characteristics for example through synchrotron radiation in a magnet, Cherenkov radiation in a gas, and transition radiation (TR) at the boundary between two media with different dielectric constants. Depending on the wavelength of the emission when compared to the particle bunch length, the radiation can be incoherent or coherent. Incoherent TR in the optical range (or OTR) is useful to measure the transverse spatial characteristics of the beam, such as charge distribution and size. Coherent TR (or CTR) carries information about the bunch length that can in principle be retrieved by standard auto-correlation or interferometric techniques, as well as by spectral measurements. A measurement of the total CTR energy emitted by bunches with constant charge can also be used as a shot-to-shot measurement for the relative bunch length as the CTR energy is proportional to the square of the bunch population and inversely proportional to its length (for a fixed distribution). Spectral interferometry can also yield the spacing between bunches in the case where multiple bunches are trapped in subsequent buckets of the plasma wave. Cherenkov radiation can be used as an energy threshold diagnostic for low energy particles. Cherenkov, synchrotron and transition radiation can be used in a dispersive section of the beam line to measure the bunch energy spectrum. The application of these diagnostics to plasma-based particle accelerators, with emphasis on the beam-driven, plasma wakefield accelerator (PWFA) at the SLAC National Accelerator Laboratory will be discussed.

  9. Acceleration techniques in the univariate Lipschitz global optimization

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  10. Acceleration and focusing of plasma flows

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

    Griswold, Martin Elias

    The acceleration of flowing plasmas is a fundamental problem that is useful in a wide variety of technological applications. We consider the problem from the perspective of plasma propulsion. Gridded ion thrusters and Hall thrusters are the most commonly used devices to create flowing plasma for space propulsion, but both suffer from fundamental limitations. Gridded ion sources create good quality beams in terms of energy spread and spatial divergence, but the Child-Langmuir law in the non-neutral acceleration region limits the maximum achievable current density. Hall thrusters avoid this limitation by accelerating ions in quasi-neutral plasma but, as a result, producemore » plumes with high spatial divergence and large energy spread. In addition the more complicated magnetized plasma in the Hall Thruster produces oscillations that can reduce the efficiency of the thruster by increasing electron transport to the anode. We present investigations of three techniques to address the fundamental limitations on the performance of each thruster. First, we propose a method to increase the time-averaged current density (and thus thrust density) produced by a gridded ion source above the Child-Langmuir limit by introducing time-varying boundary conditions. Next, we use an electrostatic plasma lens to focus the Hall thruster plume, and finally we develop a technique to suppress a prominent oscillation that degrades the performance of Hall thrusters. The technique to loosen the constraints on current density from gridded ion thrusters actually applies much more broadly to any space charge limited flow. We investigate the technique with a numerical simulation and by proving a theoretical upper bound. While we ultimately conclude that the approach is not suitable for space propulsion, our results proved useful in another area, providing a benchmark for research into the spontaneously time-dependent current that arises in microdiodes. Next, we experimentally demonstrate a novel

  11. Electrostatic accelerators with high energy resolution

    NASA Astrophysics Data System (ADS)

    Uchiyama, T.; Agawa, Y.; Nishihashi, T.; Takagi, K.; Yamakawa, H.; Isoya, A.; Takai, M.; Namba, S.

    1991-05-01

    Several models of electrostatic accelerators based on rotating disks (Disktron) have been manufactured for various ion beam applications like surface analyses and implantation. The high voltage terminal of the Disktron with a terminal voltage of up to 500 kV is open in air, while the generator part is enclosed in FRP (fiber reinforced plastics) or a ceramic vessel filled with sf 6 gas. The 1 MV model is completely enclosed in a steel vessel. A compact tandem accelerator of the pellet chain type with a terminal voltage of 1.5 MV has also been manufactured. The good energy stability of these accelerators, typically in the range of 10 -4, has proved to be quite favorable for applications in precise studies of material surfaces, including the use of microbeam techniques.

  12. Axial-spin technique of endoscopic intracorporeal knot tying: comparison with the conventional technique and objective assessment of knot security, learning curves, and performance efficiency across training levels.

    PubMed

    Gopaldas, Raja R; Rohatgi, Chand

    2009-04-01

    A major limitation of conventional laparoscopic surgery is the placement of an intracorporeal (IC) knot, which requires a significant amount of training and practice. An easier technique of IC knot tying using 90-degree grasper is compared with the conventional technique (CLT). The new axial-spin technique (AST) uses the spin of the instrument shaft to tie IC knots. Fourteen participants stratified into 3 training levels were instructed to tie 50 reef IC knots using each technique on trainers in 3 sessions. The final 5 knots tied using each technique were deemed to be representative of maximal performance efficiency (PE) and randomly subject to tensile strength measurements using a tensiometer at 50 mm/s distraction. Mean knot execution time (mKET) measured in seconds (s), normalized KE time (nET=group mean/mKET), knot holding capacity, relative knot security (RKS), and PE (PE=RKS/nET) of the knots tied were computed and analyzed using paired t and analysis of variance. Variables included knot-tying session, technique and the training level. On completion of the study, junior residents (JR) averaged 51.72 seconds more, senior residents (SR) averaged 26.22 seconds more and attendings (ATT) averaged 19.17 seconds less to tie using CLT compared with the AST (F=40.52, P=0.0001). Across all levels, the CLT technique was taking 83.26 seconds on average to execute an IC knot compared with 59.08 seconds with AST method (t=2.784, P=0.015). Learning curves revealed that JR significantly improved mean KE times with the AST technique (first session vs. final session: 473.8 s vs. 55.9 s) compared with CLT (672.5 s vs. 107.6 s) across the sessions as compared with those in advanced levels of training. The RKS of knots executed by AST was significantly stronger (AST: 13.1 vs. 5.44 N, t=4.9, P=0.0001). The PE of knots executed using the CLT increased geometrically across training levels (JR: 1.35% SR: 5.58% ATT: 11.22%) whereas those of AST showed a linear trend (17.09%; 17

  13. Design of four-beam IH-RFQ linear accelerator

    NASA Astrophysics Data System (ADS)

    Ikeda, Shota; Murata, Aki; Hayashizaki, Noriyosu

    2017-09-01

    The multi-beam acceleration method is an acceleration technique for low-energy high-intensity heavy ion beams, which involves accelerating multiple beams to decrease space charge effects, and then integrating these beams by a beam funneling system. At the Tokyo Institute of Technology a two beam IH-RFQ linear accelerator was developed using a two beam laser ion source with direct plasma injection scheme. This system accelerated a carbon ion beam with a current of 108 mA (54 mA/channel × 2) from 5 up to 60 keV/u. In order to demonstrate that a four-beam IH-RFQ linear accelerator is suitable for high-intensity heavy ion beam acceleration, we have been developing a four-beam prototype. A four-beam IH-RFQ linear accelerator consists of sixteen RFQ electrodes (4 × 4 set) with stem electrodes installed alternately on the upper and lower ridge electrodes. As a part of this development, we have designed a four-beam IH-RFQ linear accelerator using three dimensional electromagnetic simulation software and beam tracking simulation software. From these simulation results, we have designed the stem electrodes, the center plate and the side shells by evaluating the RF properties such as the resonance frequency, the power loss and the electric strength distribution between the RFQ electrodes.

  14. Developing an instrument to measure emotional behaviour abilities of meaningful learning through the Delphi technique.

    PubMed

    Cadorin, Lucia; Bagnasco, Annamaria; Tolotti, Angela; Pagnucci, Nicola; Sasso, Loredana

    2017-09-01

    To identify items for a new instrument that measures emotional behaviour abilities of meaningful learning, according to Fink's Taxonomy. Meaningful learning is an active process that promotes a wider and deeper understanding of concepts. It is the result of an interaction between new and previous knowledge and produces a long-term change of knowledge and skills. To measure meaningful learning capability, it is very important in the education of health professionals to identify problems or special learning needs. For this reason, it is necessary to create valid instruments. A Delphi Study technique was implemented in four phases by means of e-mail. The study was conducted from April-September 2015. An expert panel consisting of ten researchers with experience in Fink's Taxonomy was established to identify the items of the instrument. Data were analysed for conceptual description and item characteristics and attributes were rated. Expert consensus was sought in each of these phases. An 87·5% consensus cut-off was established. After four rounds, consensus was obtained for validation of the content of the instrument 'Assessment of Meaningful learning Behavioural and Emotional Abilities'. This instrument consists of 56 items evaluated on a 6-point Likert-type scale. Foundational Knowledge, Application, Integration, Human Dimension, Caring and Learning How to Learn were the six major categories explored. This content validated tool can help educators (teachers, trainers and tutors) to identify and improve the strategies to support students' learning capability, which could increase their awareness of and/or responsibility in the learning process. © 2017 John Wiley & Sons Ltd.

  15. Kr II laser-induced fluorescence for measuring plasma acceleration.

    PubMed

    Hargus, W A; Azarnia, G M; Nakles, M R

    2012-10-01

    We present the application of laser-induced fluorescence of singly ionized krypton as a diagnostic technique for quantifying the electrostatic acceleration within the discharge of a laboratory cross-field plasma accelerator also known as a Hall effect thruster, which has heritage as spacecraft propulsion. The 728.98 nm Kr II transition from the metastable 5d(4)D(7/2) to the 5p(4)P(5/2)(∘) state was used for the measurement of laser-induced fluorescence within the plasma discharge. From these measurements, it is possible to measure velocity as krypton ions are accelerated from near rest to approximately 21 km/s (190 eV). Ion temperature and the ion velocity distributions may also be extracted from the fluorescence data since available hyperfine splitting data allow for the Kr II 5d(4)D(7/2)-5p(4)P(5/2)(∘) transition lineshape to be modeled. From the analysis, the fluorescence lineshape appears to be a reasonable estimate for the relatively broad ion velocity distributions. However, due to an apparent overlap of the ion creation and acceleration regions within the discharge, the distributed velocity distributions increase ion temperature determination uncertainty significantly. Using the most probable ion velocity as a representative, or characteristic, measure of the ion acceleration, overall propellant energy deposition, and effective electric fields may be calculated. With this diagnostic technique, it is possible to nonintrusively characterize the ion acceleration both within the discharge and in the plume.

  16. 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…

  17. 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)…

  18. Tested by Fire - How two recent Wildfires affected Accelerator Operations at LANL

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

    Spickermann, Thomas

    2012-08-01

    In a little more than a decade two large wild fires threatened Los Alamos and impacted accelerator operations at LANL. In 2000 the Cerro Grande Fire destroyed hundreds of homes, as well as structures and equipment at the DARHT facility. The DARHT accelerators were safe in a fire-proof building. In 2011 the Las Conchas Fire burned about 630 square kilometers (250 square miles) and came dangerously close to Los Alamos/LANL. LANSCE accelerator operations Lessons Learned during Las Conchas fire: (1) Develop a plan to efficiently shut down the accelerator on short notice; (2) Establish clear lines of communication in emergencymore » situations; and (3) Plan recovery and keep squirrels out.« less

  19. 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…

  20. Tracking Active Learning in the Medical School Curriculum: A Learning-Centered Approach

    PubMed Central

    McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine

    2018-01-01

    Background: Medical education is moving toward active learning during large group lecture sessions. This study investigated the saturation and breadth of active learning techniques implemented in first year medical school large group sessions. Methods: Data collection involved retrospective curriculum review and semistructured interviews with 20 faculty. The authors piloted a taxonomy of active learning techniques and mapped learning techniques to attributes of learning-centered instruction. Results: Faculty implemented 25 different active learning techniques over the course of 9 first year courses. Of 646 hours of large group instruction, 476 (74%) involved at least 1 active learning component. Conclusions: The frequency and variety of active learning components integrated throughout the year 1 curriculum reflect faculty familiarity with active learning methods and their support of an active learning culture. This project has sparked reflection on teaching practices and facilitated an evolution from teacher-centered to learning-centered instruction. PMID:29707649

  1. Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies.

    PubMed

    Atkinson, Jonathan A; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E; Griffiths, Marcus; Wells, Darren M

    2017-10-01

    Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. © The Authors 2017. Published by Oxford University Press.

  2. Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies

    PubMed Central

    Atkinson, Jonathan A.; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E.; Griffiths, Marcus

    2017-01-01

    Abstract Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. PMID:29020748

  3. Prototyping high-gradient mm-wave accelerating structures

    DOE PAGES

    Nanni, Emilio A.; Dolgashev, Valery A.; Haase, Andrew; ...

    2017-01-01

    We present single-cell accelerating structures designed for high-gradient testing at 110 GHz. The purpose of this work is to study the basic physics of ultrahigh vacuum RF breakdown in high-gradient RF accelerators. The accelerating structures are π-mode standing-wave cavities fed with a TM 01 circular waveguide. The structures are fabricated using precision milling out of two metal blocks, and the blocks are joined with diffusion bonding and brazing. The impact of fabrication and joining techniques on the cell geometry and RF performance will be discussed. First prototypes had a measured Q 0 of 2800, approaching the theoretical design value ofmore » 3300. The geometry of these accelerating structures are as close as practical to singlecell standing-wave X-band accelerating structures more than 40 of which were tested at SLAC. This wealth of X-band data will serve as a baseline for these 110 GHz tests. Furthermore, the structures will be powered with short pulses from a MW gyrotron oscillator. RF power of 1 MW may allow an accelerating gradient of 400 MeV/m to be reached.« less

  4. Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks

    PubMed Central

    Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

    2017-01-01

    Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks. PMID:28932180

  5. Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks.

    PubMed

    Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

    2017-01-01

    Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

  6. The simulated early learning of cervical spine manipulation technique utilising mannequins.

    PubMed

    Chapman, Peter D; Stomski, Norman J; Losco, Barrett; Walker, Bruce F

    2015-01-01

    Trivial pain or minor soreness commonly follows neck manipulation and has been estimated at one in three treatments. In addition, rare catastrophic events can occur. Some of these incidents have been ascribed to poor technique where the neck is rotated too far. The aims of this study were to design an instrument to measure competency of neck manipulation in beginning students when using a simulation mannequin, and then examine the suitability of using a simulation mannequin to teach the early psychomotor skills for neck chiropractic manipulative therapy. We developed an initial set of questionnaire items and then used an expert panel to assess an instrument for neck manipulation competency among chiropractic students. The study sample comprised all 41 fourth year 2014 chiropractic students at Murdoch University. Students were randomly allocated into either a usual learning or mannequin group. All participants crossed over to undertake the alternative learning method after four weeks. A chi-square test was used to examine differences between groups in the proportion of students achieving an overall pass mark at baseline, four weeks, and eight weeks. This study was conducted between January and March 2014. We successfully developed an instrument of measurement to assess neck manipulation competency in chiropractic students. We then randomised 41 participants to first undertake either "usual learning" (n = 19) or "mannequin learning" (n = 22) for early neck manipulation training. There were no significant differences between groups in the overall pass rate at baseline (χ(2) = 0.10, p = 0.75), four weeks (χ(2) = 0.40, p = 0.53), and eight weeks (χ(2) = 0.07, p = 0.79). This study demonstrates that the use of a mannequin does not affect the manipulation competency grades of early learning students at short term follow up. Our findings have potentially important safety implications as the results indicate that students could initially

  7. Beam by design: Laser manipulation of electrons in modern accelerators

    NASA Astrophysics Data System (ADS)

    Hemsing, Erik; Stupakov, Gennady; Xiang, Dao; Zholents, Alexander

    2014-07-01

    Accelerator-based light sources such as storage rings and free-electron lasers use relativistic electron beams to produce intense radiation over a wide spectral range for fundamental research in physics, chemistry, materials science, biology, and medicine. More than a dozen such sources operate worldwide, and new sources are being built to deliver radiation that meets with the ever-increasing sophistication and depth of new research. Even so, conventional accelerator techniques often cannot keep pace with new demands and, thus, new approaches continue to emerge. In this article, a variety of recently developed and promising techniques that rely on lasers to manipulate and rearrange the electron distribution in order to tailor the properties of the radiation are reviewed. Basic theories of electron-laser interactions, techniques to create microstructures and nanostructures in electron beams, and techniques to produce radiation with customizable waveforms are reviewed. An overview of laser-based techniques for the generation of fully coherent x rays, mode-locked x-ray pulse trains, light with orbital angular momentum, and attosecond or even zeptosecond long coherent pulses in free-electron lasers is presented. Several methods to generate femtosecond pulses in storage rings are also discussed. Additionally, various schemes designed to enhance the performance of light sources through precision beam preparation including beam conditioning, laser heating, emittance exchange, and various laser-based diagnostics are described. Together these techniques represent a new emerging concept of "beam by design" in modern accelerators, which is the primary focus of this article.

  8. Accelerator system and method of accelerating particles

    NASA Technical Reports Server (NTRS)

    Wirz, Richard E. (Inventor)

    2010-01-01

    An accelerator system and method that utilize dust as the primary mass flux for generating thrust are provided. The accelerator system can include an accelerator capable of operating in a self-neutralizing mode and having a discharge chamber and at least one ionizer capable of charging dust particles. The system can also include a dust particle feeder that is capable of introducing the dust particles into the accelerator. By applying a pulsed positive and negative charge voltage to the accelerator, the charged dust particles can be accelerated thereby generating thrust and neutralizing the accelerator system.

  9. 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…

  10. A variable acceleration calibration system

    NASA Astrophysics Data System (ADS)

    Johnson, Thomas H.

    2011-12-01

    A variable acceleration calibration system that applies loads using gravitational and centripetal acceleration serves as an alternative, efficient and cost effective method for calibrating internal wind tunnel force balances. Two proof-of-concept variable acceleration calibration systems are designed, fabricated and tested. The NASA UT-36 force balance served as the test balance for the calibration experiments. The variable acceleration calibration systems are shown to be capable of performing three component calibration experiments with an approximate applied load error on the order of 1% of the full scale calibration loads. Sources of error are indentified using experimental design methods and a propagation of uncertainty analysis. Three types of uncertainty are indentified for the systems and are attributed to prediction error, calibration error and pure error. Angular velocity uncertainty is shown to be the largest indentified source of prediction error. The calibration uncertainties using a production variable acceleration based system are shown to be potentially equivalent to current methods. The production quality system can be realized using lighter materials and a more precise instrumentation. Further research is needed to account for balance deflection, forcing effects due to vibration, and large tare loads. A gyroscope measurement technique is shown to be capable of resolving the balance deflection angle calculation. Long term research objectives include a demonstration of a six degree of freedom calibration, and a large capacity balance calibration.

  11. Innovative single-shot diagnostics for electrons accelerated through laser-plasma interaction at FLAME

    NASA Astrophysics Data System (ADS)

    Bisesto, F. G.; Anania, M. P.; Chiadroni, E.; Cianchi, A.; Costa, G.; Curcio, A.; Ferrario, M.; Galletti, M.; Pompili, R.; Schleifer, E.; Zigler, A.

    2017-05-01

    Plasma wakefield acceleration is the most promising acceleration technique known nowadays, able to provide very high accelerating fields (> 100 GV/m), enabling acceleration of electrons to GeV energy in few centimeters. Here we present all the plasma related activities currently underway at SPARC LAB exploiting the high power laser FLAME. In particular, we will give an overview of the single shot diagnostics employed: Electro Optic Sampling (EOS) for temporal measurement and optical transition radiation (OTR) for an innovative one shot emittance measurements. In detail, the EOS technique has been employed to measure for the first time the longitudinal profile of electric field of fast electrons escaping from a solid target, driving the ions and protons acceleration, and to study the impact of using different target shapes. Moreover, a novel scheme for one shot emittance measurements based on OTR, developed and tested at SPARC LAB LINAC, will be shown.

  12. Gas-filled capillaries for plasma-based accelerators

    NASA Astrophysics Data System (ADS)

    Filippi, F.; Anania, M. P.; Brentegani, E.; Biagioni, A.; Cianchi, A.; Chiadroni, E.; Ferrario, M.; Pompili, R.; Romeo, S.; Zigler, A.

    2017-07-01

    Plasma Wakefield Accelerators are based on the excitation of large amplitude plasma waves excited by either a laser or a particle driver beam. The amplitude of the waves, as well as their spatial dimensions and the consequent accelerating gradient depend strongly on the background electron density along the path of the accelerated particles. The process needs stable and reliable plasma sources, whose density profile must be controlled and properly engineered to ensure the appropriate accelerating mechanism. Plasma confinement inside gas filled capillaries have been studied in the past since this technique allows to control the evolution of the plasma, ensuring a stable and repeatable plasma density distribution during the interaction with the drivers. Moreover, in a gas filled capillary plasma can be pre-ionized by a current discharge to avoid ionization losses. Different capillary geometries have been studied to allow the proper temporal and spatial evolution of the plasma along the acceleration length. Results of this analysis obtained by varying the length and the number of gas inlets will be presented.

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

    NASA Astrophysics Data System (ADS)

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

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

  14. Monte Carlo simulations of particle acceleration at oblique shocks

    NASA Technical Reports Server (NTRS)

    Baring, Matthew G.; Ellison, Donald C.; Jones, Frank C.

    1994-01-01

    The Fermi shock acceleration mechanism may be responsible for the production of high-energy cosmic rays in a wide variety of environments. Modeling of this phenomenon has largely focused on plane-parallel shocks, and one of the most promising techniques for its study is the Monte Carlo simulation of particle transport in shocked fluid flows. One of the principal problems in shock acceleration theory is the mechanism and efficiency of injection of particles from the thermal gas into the accelerated population. The Monte Carlo technique is ideally suited to addressing the injection problem directly, and previous applications of it to the quasi-parallel Earth bow shock led to very successful modeling of proton and heavy ion spectra, as well as other observed quantities. Recently this technique has been extended to oblique shock geometries, in which the upstream magnetic field makes a significant angle Theta(sub B1) to the shock normal. Spectral resutls from test particle Monte Carlo simulations of cosmic-ray acceleration at oblique, nonrelativistic shocks are presented. The results show that low Mach number shocks have injection efficiencies that are relatively insensitive to (though not independent of) the shock obliquity, but that there is a dramatic drop in efficiency for shocks of Mach number 30 or more as the obliquity increases above 15 deg. Cosmic-ray distributions just upstream of the shock reveal prominent bumps at energies below the thermal peak; these disappear far upstream but might be observable features close to astrophysical shocks.

  15. Effectiveness of Blended Learning

    ERIC Educational Resources Information Center

    Rao, A. V. Nageswararao

    2006-01-01

    The introduction of blended learning added new dimension to training, and the possibilities for delivering knowledge and information to learners at an accelerated pace and opened new vistas for knowledge management. Industry pioneers and academicians agree that blended learning will continue to become a driving force in business and in education.…

  16. Machine learning molecular dynamics for the simulation of infrared spectra.

    PubMed

    Gastegger, Michael; Behler, Jörg; Marquetand, Philipp

    2017-10-01

    Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for vibrational anharmonic and dynamical effects - typically neglected by conventional quantum chemistry approaches - we base our machine learning strategy on ab initio molecular dynamics simulations. While these simulations are usually extremely time consuming even for small molecules, we overcome these limitations by leveraging the power of a variety of machine learning techniques, not only accelerating simulations by several orders of magnitude, but also greatly extending the size of systems that can be treated. To this end, we develop a molecular dipole moment model based on environment dependent neural network charges and combine it with the neural network potential approach of Behler and Parrinello. Contrary to the prevalent big data philosophy, we are able to obtain very accurate machine learning models for the prediction of infrared spectra based on only a few hundreds of electronic structure reference points. This is made possible through the use of molecular forces during neural network potential training and the introduction of a fully automated sampling scheme. We demonstrate the power of our machine learning approach by applying it to model the infrared spectra of a methanol molecule, n -alkanes containing up to 200 atoms and the protonated alanine tripeptide, which at the same time represents the first application of machine learning techniques to simulate the dynamics of a peptide. In all of these case studies we find an excellent agreement between the infrared spectra predicted via machine learning models and the respective theoretical and experimental spectra.

  17. Vacuum Plasma Spray Forming of Tungsten Lorentz Force Accelerator Components

    NASA Technical Reports Server (NTRS)

    Zimmerman, Frank R.

    2001-01-01

    The Vacuum Plasma Spray (VPS) Laboratory at NASA's Marshall Space Flight Center has developed and demonstrated a fabrication technique using the VPS process to form anode sections for a Lorentz force accelerator from tungsten. Lorentz force accelerators are an attractive form of electric propulsion that provides continuous, high-efficiency propulsion at useful power levels for such applications as orbit transfers or deep space missions. The VPS process is used to deposit refractory metals such as tungsten onto a graphite mandrel of the desired shape. Because tungsten is reactive at high temperatures, it is thermally sprayed in an inert environment where the plasma gun melts and accelerates the metal powder onto the mandrel. A three-axis robot inside the chamber controls the motion of the plasma spray torch. A graphite mandrel acts as a male mold, forming the required contour and dimensions of the inside surface of the anode. This paper describes the processing techniques, design considerations, and process development associated with the VPS forming of the Lorentz force accelerator.

  18. Quasi-Steady Acceleration Direction Indicator in Three Dimensions

    NASA Technical Reports Server (NTRS)

    DeLombard, Richard; Nelson, Emily S.; Jules, Kenol

    2000-01-01

    Many materials processing and fluids physics experiments conducted in a microgravity environment require knowledge of the orientation of the low-frequency acceleration vector. This need becomes especially acute for space experiments such as directional solidification of a molten semiconductor, which is extremely sensitive to orientation and may involve tens of hours of operations of a materials furnace. These low-frequency acceleration data have been measured for many Shuttle missions with the Orbital Acceleration Research Experiment. Previous attempts at using fluid chambers for acceleration measurements have met with limited success due to pointing and vehicle attitude complications. An acceleration direction indicator is described, which is comprised of two orthogonal short cylinders of fluid, each with a small bubble. The motion and the position of the bubble within the chamber will indicate the direction of the acceleration experienced at the sensor location. The direction of the acceleration vector may then be calculated from these data. The frequency response of such an instrument may be tailored for particular experiments with the proper selection of fluid and gas parameters, surface type, and geometry. A three-dimensional system for sensing and displaying the low-frequency acceleration direction via an innovative technique described in this paper has advantages in terms of size, mass, and power compared with electronic instrumentation systems.

  19. Predicting adherence of patients with HF through machine learning techniques.

    PubMed

    Karanasiou, Georgia Spiridon; Tripoliti, Evanthia Eleftherios; Papadopoulos, Theofilos Grigorios; Kalatzis, Fanis Georgios; Goletsis, Yorgos; Naka, Katerina Kyriakos; Bechlioulis, Aris; Errachid, Abdelhamid; Fotiadis, Dimitrios Ioannis

    2016-09-01

    Heart failure (HF) is a chronic disease characterised by poor quality of life, recurrent hospitalisation and high mortality. Adherence of patient to treatment suggested by the experts has been proven a significant deterrent of the above-mentioned serious consequences. However, the non-adherence rates are significantly high; a fact that highlights the importance of predicting the adherence of the patient and enabling experts to adjust accordingly patient monitoring and management. The aim of this work is to predict the adherence of patients with HF, through the application of machine learning techniques. Specifically, it aims to classify a patient not only as medication adherent or not, but also as adherent or not in terms of medication, nutrition and physical activity (global adherent). Two classification problems are addressed: (i) if the patient is global adherent or not and (ii) if the patient is medication adherent or not. About 11 classification algorithms are employed and combined with feature selection and resampling techniques. The classifiers are evaluated on a dataset of 90 patients. The patients are characterised as medication and global adherent, based on clinician estimation. The highest detection accuracy is 82 and 91% for the first and the second classification problem, respectively.

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  1. 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…

  2. 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.

  3. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    PubMed Central

    Abdulameer, Mohammed Hasan; Othman, Zulaiha Ali

    2014-01-01

    Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584

  4. Genetic algorithm enhanced by machine learning in dynamic aperture optimization

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

    Li, Yongjun; Cheng, Weixing; Yu, Li Hua

    With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less

  5. Genetic algorithm enhanced by machine learning in dynamic aperture optimization

    DOE PAGES

    Li, Yongjun; Cheng, Weixing; Yu, Li Hua; ...

    2018-05-29

    With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less

  6. Accelerated forgetting? An evaluation on the use of long-term forgetting rates in patients with memory problems

    PubMed Central

    Geurts, Sofie; van der Werf, Sieberen P.; Kessels, Roy P. C.

    2015-01-01

    The main focus of this review was to evaluate whether long-term forgetting rates (delayed tests, days, to weeks, after initial learning) are more sensitive measures than standard delayed recall measures to detect memory problems in various patient groups. It has been suggested that accelerated forgetting might be characteristic for epilepsy patients, but little research has been performed in other populations. Here, we identified eleven studies in a wide range of brain injured patient groups, whose long-term forgetting patterns were compared to those of healthy controls. Signs of accelerated forgetting were found in three studies. The results of eight studies showed normal forgetting over time for the patient groups. However, most of the studies used only a recognition procedure, after optimizing initial learning. Based on these results, we recommend the use of a combined recall and recognition procedure to examine accelerated forgetting and we discuss the relevance of standard and optimized learning procedures in clinical practice. PMID:26106343

  7. Accelerated Discovery of Large Electrostrains in BaTiO3 -Based Piezoelectrics Using Active Learning.

    PubMed

    Yuan, Ruihao; Liu, Zhen; Balachandran, Prasanna V; Xue, Deqing; Zhou, Yumei; Ding, Xiangdong; Sun, Jun; Xue, Dezhen; Lookman, Turab

    2018-02-01

    A key challenge in guiding experiments toward materials with desired properties is to effectively navigate the vast search space comprising the chemistry and structure of allowed compounds. Here, it is shown how the use of machine learning coupled to optimization methods can accelerate the discovery of new Pb-free BaTiO 3 (BTO-) based piezoelectrics with large electrostrains. By experimentally comparing several design strategies, it is shown that the approach balancing the trade-off between exploration (using uncertainties) and exploitation (using only model predictions) gives the optimal criterion leading to the synthesis of the piezoelectric (Ba 0.84 Ca 0.16 )(Ti 0.90 Zr 0.07 Sn 0.03 )O 3 with the largest electrostrain of 0.23% in the BTO family. Using Landau theory and insights from density functional theory, it is uncovered that the observed large electrostrain is due to the presence of Sn, which allows for the ease of switching of tetragonal domains under an electric field. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. A new type of accelerator for charged particle cancer therapy

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

    Edgecock, Rob

    2013-04-19

    Non-scaling Fixed Field Alternating Gradient accelerators (ns-FFAGs) show great potential for the acceleration of protons and light ions for the treatment of certain cancers. They have unique features as they combine techniques from the existing types of accelerators, cyclotrons and synchrotrons, and hence look to have advantages over both for this application. However, these unique features meant that it was necessary to build one of these accelerators to show that it works and to undertake a detailed conceptual design of a medical machine. Both of these have now been done. This paper will describe the concepts of this type ofmore » accelerator, show results from the proof-of-principle machine (EMMA) and described the medical machine (PAMELA).« less

  9. Smart Training, Smart Learning: The Role of Cooperative Learning in Training for Youth Services.

    ERIC Educational Resources Information Center

    Doll, Carol A.

    1997-01-01

    Examines cooperative learning in youth services and adult education. Discusses characteristics of cooperative learning techniques; specific cooperative learning techniques (brainstorming, mini-lecture, roundtable technique, send-a-problem problem solving, talking chips technique, and three-step interview); and the role of the trainer. (AEF)

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

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  11. Better Particle Accelerators with SRF Technology

    ScienceCinema

    Padamsee, Hasan; Martinello, Martina; Ross, Marc; Peskin, Michael; Yamamoto, Akira

    2018-01-16

    The use of superconducting radio frequency (SRF) technology is a driving force in the development of particle accelerators. Scientists from around the globe are working together to develop the newest materials and techniques to improve the quality and efficiency of the SRF cavities that are essential for this technology.

  12. Better Particle Accelerators with SRF Technology

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

    Padamsee, Hasan; Martinello, Martina; Ross, Marc

    2017-02-20

    The use of superconducting radio frequency (SRF) technology is a driving force in the development of particle accelerators. Scientists from around the globe are working together to develop the newest materials and techniques to improve the quality and efficiency of the SRF cavities that are essential for this technology.

  13. Techniques for improving transients in learning control systems

    NASA Technical Reports Server (NTRS)

    Chang, C.-K.; Longman, Richard W.; Phan, Minh

    1992-01-01

    A discrete modern control formulation is used to study the nature of the transient behavior of the learning process during repetitions. Several alternative learning control schemes are developed to improve the transient performance. These include a new method using an alternating sign on the learning gain, which is very effective in limiting peak transients and also very useful in multiple-input, multiple-output systems. Other methods include learning at an increasing number of points progressing with time, or an increasing number of points of increasing density.

  14. Accelerating execution of the integrated TIGER series Monte Carlo radiation transport codes

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

    Smith, L.M.; Hochstedler, R.D.

    1997-02-01

    Execution of the integrated TIGER series (ITS) of coupled electron/photon Monte Carlo radiation transport codes has been accelerated by modifying the FORTRAN source code for more efficient computation. Each member code of ITS was benchmarked and profiled with a specific test case that directed the acceleration effort toward the most computationally intensive subroutines. Techniques for accelerating these subroutines included replacing linear search algorithms with binary versions, replacing the pseudo-random number generator, reducing program memory allocation, and proofing the input files for geometrical redundancies. All techniques produced identical or statistically similar results to the original code. Final benchmark timing of themore » accelerated code resulted in speed-up factors of 2.00 for TIGER (the one-dimensional slab geometry code), 1.74 for CYLTRAN (the two-dimensional cylindrical geometry code), and 1.90 for ACCEPT (the arbitrary three-dimensional geometry code).« less

  15. Acceleration and Velocity Sensing from Measured Strain

    NASA Technical Reports Server (NTRS)

    Pak, Chan-Gi; Truax, Roger

    2016-01-01

    A simple approach for computing acceleration and velocity of a structure from the strain is proposed in this study. First, deflection and slope of the structure are computed from the strain using a two-step theory. Frequencies of the structure are computed from the time histories of strain using a parameter estimation technique together with an Autoregressive Moving Average model. From deflection, slope, and frequencies of the structure, acceleration and velocity of the structure can be obtained using the proposed approach. shape sensing, fiber optic strain sensor, system equivalent reduction and expansion process.

  16. 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…

  17. A Severe Weather Laboratory Exercise for an Introductory Weather and Climate Class Using Active Learning Techniques

    ERIC Educational Resources Information Center

    Grundstein, Andrew; Durkee, Joshua; Frye, John; Andersen, Theresa; Lieberman, Jordan

    2011-01-01

    This paper describes a new severe weather laboratory exercise for an Introductory Weather and Climate class, appropriate for first and second year college students (including nonscience majors), that incorporates inquiry-based learning techniques. In the lab, students play the role of meteorologists making forecasts for severe weather. The…

  18. Detection of Accelerating Targets in Clutter Using a De-Chirping Technique

    DTIC Science & Technology

    2014-06-01

    Academy, also in Canberra, working on the the- ory and simulation of spatial optical solitons and light-induced optical switching in nonlinear...signal gain in the receiver. UNCLASSIFIED 1 DSTO–RR–0399 UNCLASSIFIED target along the velocity vector , or equivalently by radar platform. The change of...the tracker uses range rate in its track initiation logic. (2) Lateral acceleration perpendicular to the velocity vector - the target is turning and

  19. Systems analysis of a low-acceleration research facility

    NASA Technical Reports Server (NTRS)

    Martin, Gary L.; Ferebee, Melvin J., Jr.; Wright, Robert L.

    1988-01-01

    The Low-Acceleration Research Facility (LARF), an unmanned free-flier that is boosted from low-earth orbit to a desired altitude using an orbital transfer vehicle is discussed. Design techniques used to minimize acceleration-causing disturbances and to create an ultra-quiet workshop are discussed, focusing on residual acceleration induced by the environment, the spacecraft and experiments. The selection and integration of critical subsystems, such as electrical power and thermal control, that enable the LARf to accomodate sub-microgravity levels for extended periods of time are presented, including a discussion of the Low-Acceleration Module, which will supply the payload with 25.0 kW of power, and up to 11.8 kW in the low-power mode. Also, the data management, communications, guidance, navigation and control, and structural features of supporting subsystems are examined.

  20. High efficiency RF amplifier development over wide dynamic range for accelerator application

    NASA Astrophysics Data System (ADS)

    Mishra, Jitendra Kumar; Ramarao, B. V.; Pande, Manjiri M.; Joshi, Gopal; Sharma, Archana; Singh, Pitamber

    2017-10-01

    Superconducting (SC) cavities in an accelerating section are designed to have the same geometrical velocity factor (βg). For these cavities, Radio Frequency (RF) power needed to accelerate charged particles varies with the particle velocity factor (β). RF power requirement from one cavity to other can vary by 2-5 dB within the accelerating section depending on the energy gain in the cavity and beam current. In this paper, we have presented an idea to improve operating efficiency of the SC RF accelerators using envelope tracking technique. A study on envelope tracking technique without feedback is carried out on a 1 kW, 325 MHz, class B (conduction angle of 180 degrees) tuned load power amplifier (PA). We have derived expressions for the efficiency and power output for tuned load amplifier operating on the envelope tracking technique. From the derived expressions, it is observed that under constant load resistance to the device (MOSFET), optimum amplifier efficiency is invariant whereas output power varies with the square of drain bias voltage. Experimental results on 1 kW PA module show that its optimum efficiency is always greater than 62% with variation less than 5% from mean value over 7 dB dynamic range. Low power amplifier modules are the basic building block for the high power amplifiers. Therefore, results for 1 kW PA modules remain valid for the high power solid state amplifiers built using these PA modules. The SC RF accelerators using these constant efficiency power amplifiers can improve overall accelerator efficiency.

  1. Accelerated spike resampling for accurate multiple testing controls.

    PubMed

    Harrison, Matthew T

    2013-02-01

    Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using permutation tests and for testing pairwise synchrony and precise lagged-correlation between many simultaneously recorded spike trains using interval jitter.

  2. Demonstration of acceleration of relativistic electrons at a dielectric microstructure using femtosecond laser pulses

    DOE PAGES

    Wootton, Kent P.; Wu, Ziran; Cowan, Benjamin M.; ...

    2016-06-02

    Acceleration of electrons using laser-driven dielectric microstructures is a promising technology for the miniaturization of particle accelerators. Achieving the desired GV m –1 accelerating gradients is possible only with laser pulse durations shorter than ~1 ps. In this Letter, we present, to the best of our knowledge, the first demonstration of acceleration of relativistic electrons at a dielectric microstructure driven by femtosecond duration laser pulses. Furthermore, using this technique, an electron accelerating gradient of 690±100 MV m –1 was measured—a record for dielectric laser accelerators.

  3. How to Avoid a Learning Curve in Stapedotomy: A Standardized Surgical Technique.

    PubMed

    Kwok, Pingling; Gleich, Otto; Dalles, Katharina; Mayr, Elisabeth; Jacob, Peter; Strutz, Jürgen

    2017-08-01

    To evaluate, whether a learning curve for beginners in stapedotomy can be avoided by using a prosthesis with thermal memory-shape attachment in combination with a standardized laser-assisted surgical technique. Retrospective case review. Tertiary referral center. Fifty-eight ears were operated by three experienced surgeons and compared with a group of 12 cases operated by a beginner in stapedotomy. Stapedotomy. Difference of pure-tone audiometry thresholds measured before and after surgery. The average postoperative gain for air conduction in the frequencies below 2 kHz was 20 to 25 dB and decreased for the higher frequencies. Using the Mann-Whitney-U test for comparing mean gain between experienced and inexperienced surgeons showed no significant difference (p = 0.281 at 4 kHz and p > 0.7 for the other frequencies). A Spearman rank correlation of the postoperative gain for air- and bone-conduction thresholds was obtained at each test frequency for the first 12 patients consecutively treated with a thermal memory-shape attachment prosthesis by two experienced and one inexperienced surgeon. This analysis does not support the hypothesis of a "learning effect" that should be associated with an improved outcome for successively treated patients. It is possible to avoid a learning curve in stapes surgery by applying a thermal memory-shape prosthesis in a standardized laser-assisted surgical procedure.

  4. Accelerating Advanced MRI Reconstructions on GPUs

    PubMed Central

    Stone, S.S.; Haldar, J.P.; Tsao, S.C.; Hwu, W.-m.W.; Sutton, B.P.; Liang, Z.-P.

    2008-01-01

    Computational acceleration on graphics processing units (GPUs) can make advanced magnetic resonance imaging (MRI) reconstruction algorithms attractive in clinical settings, thereby improving the quality of MR images across a broad spectrum of applications. This paper describes the acceleration of such an algorithm on NVIDIA’s Quadro FX 5600. The reconstruction of a 3D image with 1283 voxels achieves up to 180 GFLOPS and requires just over one minute on the Quadro, while reconstruction on a quad-core CPU is twenty-one times slower. Furthermore, relative to the true image, the error exhibited by the advanced reconstruction is only 12%, while conventional reconstruction techniques incur error of 42%. PMID:21796230

  5. Accelerating Advanced MRI Reconstructions on GPUs.

    PubMed

    Stone, S S; Haldar, J P; Tsao, S C; Hwu, W-M W; Sutton, B P; Liang, Z-P

    2008-10-01

    Computational acceleration on graphics processing units (GPUs) can make advanced magnetic resonance imaging (MRI) reconstruction algorithms attractive in clinical settings, thereby improving the quality of MR images across a broad spectrum of applications. This paper describes the acceleration of such an algorithm on NVIDIA's Quadro FX 5600. The reconstruction of a 3D image with 128(3) voxels achieves up to 180 GFLOPS and requires just over one minute on the Quadro, while reconstruction on a quad-core CPU is twenty-one times slower. Furthermore, relative to the true image, the error exhibited by the advanced reconstruction is only 12%, while conventional reconstruction techniques incur error of 42%.

  6. Who is that masked educator? Deconstructing the teaching and learning processes of an innovative humanistic simulation technique.

    PubMed

    McAllister, Margaret; Searl, Kerry Reid; Davis, Susan

    2013-12-01

    Simulation learning in nursing has long made use of mannequins, standardized actors and role play to allow students opportunity to practice technical body-care skills and interventions. Even though numerous strategies have been developed to mimic or amplify clinical situations, a common problem that is difficult to overcome in even the most well-executed simulation experiences, is that students may realize the setting is artificial and fail to fully engage, remember or apply the learning. Another problem is that students may learn technical competence but remain uncertain about communicating with the person. Since communication capabilities are imperative in human service work, simulation learning that only achieves technical competence in students is not fully effective for the needs of nursing education. Furthermore, while simulation learning is a burgeoning space for innovative practices, it has been criticized for the absence of a basis in theory. It is within this context that an innovative simulation learning experience named "Mask-Ed (KRS simulation)", has been deconstructed and the active learning components examined. Establishing a theoretical basis for creative teaching and learning practices provides an understanding of how, why and when simulation learning has been effective and it may help to distinguish aspects of the experience that could be improved. Three conceptual theoretical fields help explain the power of this simulation technique: Vygotskian sociocultural learning theory, applied theatre and embodiment. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. A new method of measuring gravitational acceleration in an undergraduate laboratory program

    NASA Astrophysics Data System (ADS)

    Wang, Qiaochu; Wang, Chang; Xiao, Yunhuan; Schulte, Jurgen; Shi, Qingfan

    2018-01-01

    This paper presents a high accuracy method to measure gravitational acceleration in an undergraduate laboratory program. The experiment is based on water in a cylindrical vessel rotating about its vertical axis at a constant speed. The water surface forms a paraboloid whose focal length is related to rotational period and gravitational acceleration. This experimental setup avoids classical source errors in determining the local value of gravitational acceleration, so prevalent in the common simple pendulum and inclined plane experiments. The presented method combines multiple physics concepts such as kinematics, classical mechanics and geometric optics, offering the opportunity for lateral as well as project-based learning.

  8. Graphics Processing Unit-Accelerated Nonrigid Registration of MR Images to CT Images During CT-Guided Percutaneous Liver Tumor Ablations.

    PubMed

    Tokuda, Junichi; Plishker, William; Torabi, Meysam; Olubiyi, Olutayo I; Zaki, George; Tatli, Servet; Silverman, Stuart G; Shekher, Raj; Hata, Nobuhiko

    2015-06-01

    Accuracy and speed are essential for the intraprocedural nonrigid magnetic resonance (MR) to computed tomography (CT) image registration in the assessment of tumor margins during CT-guided liver tumor ablations. Although both accuracy and speed can be improved by limiting the registration to a region of interest (ROI), manual contouring of the ROI prolongs the registration process substantially. To achieve accurate and fast registration without the use of an ROI, we combined a nonrigid registration technique on the basis of volume subdivision with hardware acceleration using a graphics processing unit (GPU). We compared the registration accuracy and processing time of GPU-accelerated volume subdivision-based nonrigid registration technique to the conventional nonrigid B-spline registration technique. Fourteen image data sets of preprocedural MR and intraprocedural CT images for percutaneous CT-guided liver tumor ablations were obtained. Each set of images was registered using the GPU-accelerated volume subdivision technique and the B-spline technique. Manual contouring of ROI was used only for the B-spline technique. Registration accuracies (Dice similarity coefficient [DSC] and 95% Hausdorff distance [HD]) and total processing time including contouring of ROIs and computation were compared using a paired Student t test. Accuracies of the GPU-accelerated registrations and B-spline registrations, respectively, were 88.3 ± 3.7% versus 89.3 ± 4.9% (P = .41) for DSC and 13.1 ± 5.2 versus 11.4 ± 6.3 mm (P = .15) for HD. Total processing time of the GPU-accelerated registration and B-spline registration techniques was 88 ± 14 versus 557 ± 116 seconds (P < .000000002), respectively; there was no significant difference in computation time despite the difference in the complexity of the algorithms (P = .71). The GPU-accelerated volume subdivision technique was as accurate as the B-spline technique and required significantly less processing time. The GPU-accelerated

  9. Parallel SOR methods with a parabolic-diffusion acceleration technique for solving an unstructured-grid Poisson equation on 3D arbitrary geometries

    NASA Astrophysics Data System (ADS)

    Zapata, M. A. Uh; Van Bang, D. Pham; Nguyen, K. D.

    2016-05-01

    This paper presents a parallel algorithm for the finite-volume discretisation of the Poisson equation on three-dimensional arbitrary geometries. The proposed method is formulated by using a 2D horizontal block domain decomposition and interprocessor data communication techniques with message passing interface. The horizontal unstructured-grid cells are reordered according to the neighbouring relations and decomposed into blocks using a load-balanced distribution to give all processors an equal amount of elements. In this algorithm, two parallel successive over-relaxation methods are presented: a multi-colour ordering technique for unstructured grids based on distributed memory and a block method using reordering index following similar ideas of the partitioning for structured grids. In all cases, the parallel algorithms are implemented with a combination of an acceleration iterative solver. This solver is based on a parabolic-diffusion equation introduced to obtain faster solutions of the linear systems arising from the discretisation. Numerical results are given to evaluate the performances of the methods showing speedups better than linear.

  10. Automatic Beam Path Analysis of Laser Wakefield Particle Acceleration Data

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

    Rubel, Oliver; Geddes, Cameron G.R.; Cormier-Michel, Estelle

    2009-10-19

    Numerical simulations of laser wakefield particle accelerators play a key role in the understanding of the complex acceleration process and in the design of expensive experimental facilities. As the size and complexity of simulation output grows, an increasingly acute challenge is the practical need for computational techniques that aid in scientific knowledge discovery. To that end, we present a set of data-understanding algorithms that work in concert in a pipeline fashion to automatically locate and analyze high energy particle bunches undergoing acceleration in very large simulation datasets. These techniques work cooperatively by first identifying features of interest in individual timesteps,more » then integrating features across timesteps, and based on the information derived perform analysis of temporally dynamic features. This combination of techniques supports accurate detection of particle beams enabling a deeper level of scientific understanding of physical phenomena than hasbeen possible before. By combining efficient data analysis algorithms and state-of-the-art data management we enable high-performance analysis of extremely large particle datasets in 3D. We demonstrate the usefulness of our methods for a variety of 2D and 3D datasets and discuss the performance of our analysis pipeline.« less

  11. Accelerator mass spectrometry.

    PubMed

    Hellborg, Ragnar; Skog, Göran

    2008-01-01

    In this overview the technique of accelerator mass spectrometry (AMS) and its use are described. AMS is a highly sensitive method of counting atoms. It is used to detect very low concentrations of natural isotopic abundances (typically in the range between 10(-12) and 10(-16)) of both radionuclides and stable nuclides. The main advantages of AMS compared to conventional radiometric methods are the use of smaller samples (mg and even sub-mg size) and shorter measuring times (less than 1 hr). The equipment used for AMS is almost exclusively based on the electrostatic tandem accelerator, although some of the newest systems are based on a slightly different principle. Dedicated accelerators as well as older "nuclear physics machines" can be found in the 80 or so AMS laboratories in existence today. The most widely used isotope studied with AMS is 14C. Besides radiocarbon dating this isotope is used in climate studies, biomedicine applications and many other fields. More than 100,000 14C samples are measured per year. Other isotopes studied include 10Be, 26Al, 36Cl, 41Ca, 59Ni, 129I, U, and Pu. Although these measurements are important, the number of samples of these other isotopes measured each year is estimated to be less than 10% of the number of 14C samples. Copyright 2008 Wiley Periodicals, Inc.

  12. Medical students benefit from the use of ultrasound when learning peripheral IV techniques.

    PubMed

    Osborn, Scott R; Borhart, Joelle; Antonis, Michael S

    2012-03-06

    Recent studies support high success rates after a short learning period of ultrasound IV technique, and increased patient and provider satisfaction when using ultrasound as an adjunct to peripheral IV placement. No study to date has addressed the efficacy for instructing ultrasound-naive providers. We studied the introduction of ultrasound to the teaching technique of peripheral IV insertion on first- and second-year medical students. This was a prospective, randomized, and controlled trial. A total of 69 medical students were randomly assigned to the control group with a classic, landmark-based approach (n = 36) or the real-time ultrasound-guided group (n = 33). Both groups observed a 20-min tutorial on IV placement using both techniques and then attempted vein cannulation. Students were given a survey to report their results and observations by a 10-cm visual analog scale. The survey response rate was 100%. In the two groups, 73.9% stated that they attempted an IV previously, and 63.7% of students had used an ultrasound machine prior to the study. None had used ultrasound for IV access prior to our session. The average number of attempts at cannulation was 1.42 in either group. There was no difference between the control and ultrasound groups in terms of number of attempts (p = 0.31). In both groups, 66.7% of learners were able to cannulate in one attempt, 21.7% in two attempts, and 11.6% in three attempts. The study group commented that they felt they gained more knowledge from the experience (p < 0.005) and that it was easier with ultrasound guidance (p < 0.005). Medical students feel they learn more when using ultrasound after a 20-min tutorial to place IVs and cannulation of the vein feels easier. Success rates are comparable between the traditional and ultrasound teaching approaches.

  13. Technical Design Report for the FACET-II Project at SLAC National Accelerator Laboratory

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

    None, None

    Electrons can “surf” on waves of plasma – a hot gas of charged particles – gaining very high energies in very short distances. This approach, called plasma wakefield acceleration, has the potential to dramatically shrink the size and cost of particle accelerators. Research at the SLAC National Accelerator Laboratory has demonstrated that plasmas can provide 1,000 times the acceleration in a given distance compared with current technologies. Developing revolutionary and more efficient acceleration techniques that allow for an affordable high-energy collider has been the focus of FACET, a National User Facility at SLAC. FACET used part of SLAC’s two-mile-long linearmore » accelerator to generate high-density beams of electrons and their antimatter counterparts, positrons. Research into plasma wakefield acceleration was the primary motivation for constructing FACET. In April 2016, FACET operations came to an end to make way for the second phase of SLAC’s x-ray laser, the LCLS-II, which will use part of the tunnel occupied by FACET. FACET-II is a new test facility to provide the unique capability to develop advanced acceleration and coherent radiation techniques with high-energy electron and positron beams. FACET-II represents a major upgrade over current FACET capabilities and the breadth of the potential research program makes it truly unique.« less

  14. Multivariate Time Series Forecasting of Crude Palm Oil Price Using Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Kanchymalay, Kasturi; Salim, N.; Sukprasert, Anupong; Krishnan, Ramesh; Raba'ah Hashim, Ummi

    2017-08-01

    The aim of this paper was to study the correlation between crude palm oil (CPO) price, selected vegetable oil prices (such as soybean oil, coconut oil, and olive oil, rapeseed oil and sunflower oil), crude oil and the monthly exchange rate. Comparative analysis was then performed on CPO price forecasting results using the machine learning techniques. Monthly CPO prices, selected vegetable oil prices, crude oil prices and monthly exchange rate data from January 1987 to February 2017 were utilized. Preliminary analysis showed a positive and high correlation between the CPO price and soy bean oil price and also between CPO price and crude oil price. Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques. The results were assessed by using criteria of root mean square error (RMSE), means absolute error (MAE), means absolute percentage error (MAPE) and Direction of accuracy (DA). Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method.

  15. Vacuum Plasma Spray Forming of Tungsten Lorentz Force Accelerator Components

    NASA Technical Reports Server (NTRS)

    Zimmerman, Frank R.

    2004-01-01

    The Vacuum Plasma Spray (VPS) Laboratory at NASA's Marshall Space Flight Center, working with the Jet Propulsion Laboratory, has developed and demonstrated a fabrication technique using the VPS process to form anode and cathode sections for a Lorentz force accelerator made from tungsten. Lorentz force accelerators are an attractive form of electric propulsion that provides continuous, high-efficiency propulsion at useful power levels for such applications as orbit transfers or deep space missions. The VPS process is used to deposit refractory metals such as tungsten onto a graphite mandrel of the desired shape. Because tungsten is reactive at high temperatures, it is thermally sprayed in an inert environment where the plasma gun melts and deposits the molten metal powder onto a mandrel. A three-axis robot inside the chamber controls the motion of the plasma spray torch. A graphite mandrel acts as a male mold, forming the required contour and dimensions for the inside surface of the anode or cathode of the accelerator. This paper describes the processing techniques, design considerations, and process development associated with the VPS forming of Lorentz force accelerator components.

  16. Augmenting the bioactivity of polyetheretherketone using a novel accelerated neutral atom beam technique.

    PubMed

    Ajami, S; Coathup, M J; Khoury, J; Blunn, G W

    2017-08-01

    Polyetheretherketone (PEEK) is an alternative to metallic implants in orthopedic applications; however, PEEK is bioinert and does not osteointegrate. In this study, an accelerated neutral atom beam technique (ANAB) was employed to improve the bioactivity of PEEK. The aim was to investigate the growth of human mesenchymal stem cells (hMSCs), human osteoblasts (hOB), and skin fibroblasts (BR3G) on PEEK and ANAB PEEK. The surface roughness and contact angle of PEEK and ANAB PEEK was measured. Cell metabolic activity, proliferation and alkaline phosphatase (ALP) was measured and cell attachment was determined by quantifying adhesion plaques with cells. ANAB treatment increased the surface hydrophilicity [91.74 ± 4.80° (PEEK) vs. 74.82 ± 2.70° (ANAB PEEK), p < 0.001] but did not alter the surface roughness. Metabolic activity and proliferation for all cell types significantly increased on ANAB PEEK compared to PEEK (p < 0.05). Significantly increased cell attachment was measured on ANAB PEEK surfaces. MSCs seeded on ANAB PEEK in the presence of osteogenic media, expressed increased levels of ALP compared to untreated PEEK (p < 0.05) CONCLUSION: Our results demonstrated that ANAB treatment increased the cell attachment, metabolic activity, and proliferation on PEEK. ANAB treatment may improve the osteointegration of PEEK implants. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 1438-1446, 2017. © 2016 Wiley Periodicals, Inc.

  17. Beyond velocity and acceleration: jerk, snap and higher derivatives

    NASA Astrophysics Data System (ADS)

    Eager, David; Pendrill, Ann-Marie; Reistad, Nina

    2016-11-01

    The higher derivatives of motion are rarely discussed in the teaching of classical mechanics of rigid bodies; nevertheless, we experience the effect not only of acceleration, but also of jerk and snap. In this paper we will discuss the third and higher order derivatives of displacement with respect to time, using the trampolines and theme park roller coasters to illustrate this concept. We will also discuss the effects on the human body of different types of acceleration, jerk, snap and higher derivatives, and how they can be used in physics education to further enhance the learning and thus the understanding of classical mechanics concepts.

  18. Development of the Accelerator Mass Spectrometry technology at the Comenius University in Bratislava

    NASA Astrophysics Data System (ADS)

    Povinec, Pavel P.; Masarik, Jozef; Ješkovský, Miroslav; Kaizer, Jakub; Šivo, Alexander; Breier, Robert; Pánik, Ján; Staníček, Jaroslav; Richtáriková, Marta; Zahoran, Miroslav; Zeman, Jakub

    2015-10-01

    An Accelerator Mass Spectrometry (AMS) laboratory has been established at the Centre for Nuclear and Accelerator Technologies (CENTA) at the Comenius University in Bratislava comprising of a MC-SNICS ion source, 3 MV Pelletron tandem accelerator, and an analyzer of accelerated ions. The preparation of targets for 14C and 129I AMS measurements is described in detail. The development of AMS techniques for potassium, uranium and thorium analysis in radiopure materials required for ultra-low background underground experiments is briefly mentioned.

  19. Noninvasive acceleration measurements to characterize knee arthritis and chondromalacia.

    PubMed

    Reddy, N P; Rothschild, B M; Mandal, M; Gupta, V; Suryanarayanan, S

    1995-01-01

    Devising techniques and instrumentation for early detection of knee arthritis and chondromalacia presents a challenge in the domain of biomedical engineering. The purpose of the present investigation was to characterize normal knees and knees affected by osteoarthritis, rheumatoid arthritis, and chondromalacia using a set of noninvasive acceleration measurements. Ultraminiature accelerometers were placed on the skin over the patella in four groups of subjects, and acceleration measurements were obtained during leg rotation. Acceleration measurements were significantly different in the four groups of subjects in the time and frequency domains. Power spectral analysis revealed that the average power was significantly different for these groups over a 100-500 Hz range. Noninvasive acceleration measurements can characterize the normal, arthritis, and chondromalacia knees. However, a study on a larger group of subjects is indicated.

  20. 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…

  1. Impact of corpus domain for sentiment classification: An evaluation study using supervised machine learning techniques

    NASA Astrophysics Data System (ADS)

    Karsi, Redouane; Zaim, Mounia; El Alami, Jamila

    2017-07-01

    Thanks to the development of the internet, a large community now has the possibility to communicate and express its opinions and preferences through multiple media such as blogs, forums, social networks and e-commerce sites. Today, it becomes clearer that opinions published on the web are a very valuable source for decision-making, so a rapidly growing field of research called “sentiment analysis” is born to address the problem of automatically determining the polarity (Positive, negative, neutral,…) of textual opinions. People expressing themselves in a particular domain often use specific domain language expressions, thus, building a classifier, which performs well in different domains is a challenging problem. The purpose of this paper is to evaluate the impact of domain for sentiment classification when using machine learning techniques. In our study three popular machine learning techniques: Support Vector Machines (SVM), Naive Bayes and K nearest neighbors(KNN) were applied on datasets collected from different domains. Experimental results show that Support Vector Machines outperforms other classifiers in all domains, since it achieved at least 74.75% accuracy with a standard deviation of 4,08.

  2. 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.

  3. Application and evaluation of a combination of socratice and learning through discussion techniques.

    PubMed

    van Aswegen, E J; Brink, H I; Steyn, P J

    2001-11-01

    This article has its genesis in the inquirer's interest in the need for internalizing critical thinking, creative thinking and reflective skills in adult learners. As part of a broader study the inquirer used a combination of two techniques over a period of nine months, namely: Socratic discussion/questioning and Learning Through Discussion Technique. The inquirer within this inquiry elected mainly qualitative methods, because they were seen as more adaptable to dealing with multiple realities and more sensitive and adaptable to the many shaping influences and value patterns that may be encountered (Lincoln & Guba, 1989). Purposive sampling was used and sample size (n = 10) was determined by the willingness of potential participants to enlist in the chosen techniques. Feedback from participants was obtained: (1) verbally after each discussion session, and (2) in written format after completion of the course content. The final/summative evaluation was obtained through a semi-structured questionnaire. This was deemed necessary, in that the participants were already studying for the end of the year examination. For the purpose of this condensed report the inquirer reflected only on the feedback obtained with the help of the questionnaire. The empirical study showed that in spite of various adaptation problems experienced, eight (8) of the ten (10) participants felt positive toward the applied techniques.

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

    ERIC Educational Resources Information Center

    Akman, Özkan

    2016-01-01

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

  5. Mobile-Assisted Language Learning and Language Learner Autonomy

    ERIC Educational Resources Information Center

    Lyddon, Paul

    2016-01-01

    In the modern age of exponential knowledge growth and accelerating technological development, the need to engage in lifelong learning is becoming increasingly urgent. Successful lifelong learning, in turn, requires learner autonomy, or "the capacity to take control of one's own learning" (Benson, 2011, p. 58), including all relevant…

  6. The LILIA (laser induced light ions acceleration) experiment at LNF

    NASA Astrophysics Data System (ADS)

    Agosteo, S.; Anania, M. P.; Caresana, M.; Cirrone, G. A. P.; De Martinis, C.; Delle Side, D.; Fazzi, A.; Gatti, G.; Giove, D.; Giulietti, D.; Gizzi, L. A.; Labate, L.; Londrillo, P.; Maggiore, M.; Nassisi, V.; Sinigardi, S.; Tramontana, A.; Schillaci, F.; Scuderi, V.; Turchetti, G.; Varoli, V.; Velardi, L.

    2014-07-01

    Laser-matter interaction at relativistic intensities opens up new research fields in the particle acceleration and related secondary sources, with immediate applications in medical diagnostics, biophysics, material science, inertial confinement fusion, up to laboratory astrophysics. In particular laser-driven ion acceleration is very promising for hadron therapy once the ion energy will attain a few hundred MeV. The limited value of the energy up to now obtained for the accelerated ions is the drawback of such innovative technique to the real applications. LILIA (laser induced light ions acceleration) is an experiment now running at LNF (Frascati) with the goal of producing a real proton beam able to be driven for significant distances (50-75 cm) away from the interaction point and which will act as a source for further accelerating structure. In this paper the description of the experimental setup, the preliminary results of solid target irradiation and start to end simulation for a post-accelerated beam up to 60 MeV are given.

  7. Method for computationally efficient design of dielectric laser accelerator structures

    DOE PAGES

    Hughes, Tyler; Veronis, Georgios; Wootton, Kent P.; ...

    2017-06-22

    Here, dielectric microstructures have generated much interest in recent years as a means of accelerating charged particles when powered by solid state lasers. The acceleration gradient (or particle energy gain per unit length) is an important figure of merit. To design structures with high acceleration gradients, we explore the adjoint variable method, a highly efficient technique used to compute the sensitivity of an objective with respect to a large number of parameters. With this formalism, the sensitivity of the acceleration gradient of a dielectric structure with respect to its entire spatial permittivity distribution is calculated by the use of onlymore » two full-field electromagnetic simulations, the original and ‘adjoint’. The adjoint simulation corresponds physically to the reciprocal situation of a point charge moving through the accelerator gap and radiating. Using this formalism, we perform numerical optimizations aimed at maximizing acceleration gradients, which generate fabricable structures of greatly improved performance in comparison to previously examined geometries.« less

  8. Compact and tunable focusing device for plasma wakefield acceleration

    NASA Astrophysics Data System (ADS)

    Pompili, R.; Anania, M. P.; Chiadroni, E.; Cianchi, A.; Ferrario, M.; Lollo, V.; Notargiacomo, A.; Picardi, L.; Ronsivalle, C.; Rosenzweig, J. B.; Shpakov, V.; Vannozzi, A.

    2018-03-01

    Plasma wakefield acceleration, either driven by ultra-short laser pulses or electron bunches, represents one of the most promising techniques able to overcome the limits of conventional RF technology and allows the development of compact accelerators. In the particle beam-driven scenario, ultra-short bunches with tiny spot sizes are required to enhance the accelerating gradient and preserve the emittance and energy spread of the accelerated bunch. To achieve such tight transverse beam sizes, a focusing system with short focal length is mandatory. Here we discuss the development of a compact and tunable system consisting of three small-bore permanent-magnet quadrupoles with 520 T/m field gradient. The device has been designed in view of the plasma acceleration experiments planned at the SPARC_LAB test-facility. Being the field gradient fixed, the focusing is adjusted by tuning the relative position of the three magnets with nanometer resolution. Details about its magnetic design, beam-dynamics simulations, and preliminary results are examined in the paper.

  9. Conventional and Piecewise Growth Modeling Techniques: Applications and Implications for Investigating Head Start Children's Early Literacy Learning

    ERIC Educational Resources Information Center

    Hindman, Annemarie H.; Cromley, Jennifer G.; Skibbe, Lori E.; Miller, Alison L.

    2011-01-01

    This article reviews the mechanics of conventional and piecewise growth models to demonstrate the unique affordances of each technique for examining the nature and predictors of children's early literacy learning during the transition from preschool through first grade. Using the nationally representative Family and Child Experiences Survey…

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

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

    Qiu, Jian-Jian; Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai

    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 includingmore » 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

  11. A Look at Lifelong Learning.

    ERIC Educational Resources Information Center

    Dutton, Donnie

    Adults must continue to learn. The accelerating pace of cultural change has made today's knowledge and skills tomorrow's obsolescence. A society that makes its educational investment almost entirely in children and youth is on the way to becoming obsolete and is reducing its survival chances. To promote the cause of lifelong learning, we need to…

  12. Testing Gravity and Cosmic Acceleration with Galaxy Clustering

    NASA Astrophysics Data System (ADS)

    Kazin, Eyal; Tinker, J.; Sanchez, A. G.; Blanton, M.

    2012-01-01

    The large-scale structure contains vast amounts of cosmological information that can help understand the accelerating nature of the Universe and test gravity on large scales. Ongoing and future sky surveys are designed to test these using various techniques applied on clustering measurements of galaxies. We present redshift distortion measurements of the Sloan Digital Sky Survey II Luminous Red Galaxy sample. We find that when combining the normalized quadrupole Q with the projected correlation function wp(rp) along with cluster counts (Rapetti et al. 2010), results are consistent with General Relativity. The advantage of combining Q and wp is the addition of the bias information, when using the Halo Occupation Distribution framework. We also present improvements to the standard technique of measuring Hubble expansion rates H(z) and angular diameter distances DA(z) when using the baryonic acoustic feature as a standard ruler. We introduce clustering wedges as an alternative basis to the multipole expansion and show that it yields similar constraints. This alternative basis serves as a useful technique to test for systematics, and ultimately improve measurements of the cosmic acceleration.

  13. Drive Beam Shaping and Witness Bunch Generation for the Plasma Wakefield Accelerator

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

    England, R. J.; Frederico, J.; Hogan, M. J.

    2010-11-04

    High transformer ratio operation of the plasma wake field accelerator requires a tailored drive beam current profile followed by a short witness bunch. We discuss techniques for generating the requisite dual bunches and for obtaining the desired drive beam profile, with emphasis on the FACET experiment at SLAC National Accelerator Laboratory.

  14. Acceleration and Velocity Sensing from Measured Strain

    NASA Technical Reports Server (NTRS)

    Pak, Chan-Gi; Truax, Roger

    2015-01-01

    A simple approach for computing acceleration and velocity of a structure from the strain is proposed in this study. First, deflection and slope of the structure are computed from the strain using a two-step theory. Frequencies of the structure are computed from the time histories of strain using a parameter estimation technique together with an autoregressive moving average model. From deflection, slope, and frequencies of the structure, acceleration and velocity of the structure can be obtained using the proposed approach. Simple harmonic motion is assumed for the acceleration computations, and the central difference equation with a linear autoregressive model is used for the computations of velocity. A cantilevered rectangular wing model is used to validate the simple approach. Quality of the computed deflection, acceleration, and velocity values are independent of the number of fibers. The central difference equation with a linear autoregressive model proposed in this study follows the target response with reasonable accuracy. Therefore, the handicap of the backward difference equation, phase shift, is successfully overcome.

  15. Survey of Analysis of Crime Detection Techniques Using Data Mining and Machine Learning

    NASA Astrophysics Data System (ADS)

    Prabakaran, S.; Mitra, Shilpa

    2018-04-01

    Data mining is the field containing procedures for finding designs or patterns in a huge dataset, it includes strategies at the convergence of machine learning and database framework. It can be applied to various fields like future healthcare, market basket analysis, education, manufacturing engineering, crime investigation etc. Among these, crime investigation is an interesting application to process crime characteristics to help the society for a better living. This paper survey various data mining techniques used in this domain. This study may be helpful in designing new strategies for crime prediction and analysis.

  16. The FuturICT education accelerator

    NASA Astrophysics Data System (ADS)

    Johnson, J.; Buckingham Shum, S.; Willis, A.; Bishop, S.; Zamenopoulos, T.; Swithenby, S.; MacKay, R.; Merali, Y.; Lorincz, A.; Costea, C.; Bourgine, P.; Louçã, J.; Kapenieks, A.; Kelley, P.; Caird, S.; Bromley, J.; Deakin Crick, R.; Goldspink, C.; Collet, P.; Carbone, A.; Helbing, D.

    2012-11-01

    Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year `man-on-the-moon' project is proposed in which FuturICT's unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a `wind tunnel' for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT.

  17. 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…

  18. Demonstration of the hollow channel plasma wakefield accelerator

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

    Gessner, Spencer J.

    2016-09-17

    A plasma wakefield accelerator is a device that converts the energy of a relativistic particle beam into a large-amplitude wave in a plasma. The plasma wave, or wakefield, supports an enormous electricfield that is used to accelerate a trailing particle beam. The plasma wakefield accelerator can therefore be used as a transformer, transferring energy from a high-charge, low-energy particle beam into a high-energy, low-charge particle beam. This technique may lead to a new generation of ultra-compact, high-energy particle accelerators. The past decade has seen enormous progress in the field of plasma wakefield acceleration with experimental demonstrations of the acceleration ofmore » electron beams by several gigaelectron-volts. The acceleration of positron beams in plasma is more challenging, but also necessary for the creation of a high-energy electron-positron collider. Part of the challenge is that the plasma responds asymmetrically to electrons and positrons, leading to increased disruption of the positron beam. One solution to this problem, first proposed over twenty years ago, is to use a hollow channel plasma which symmetrizes the response of the plasma to beams of positive and negative charge, making it possible to accelerate positrons in plasma without disruption. In this thesis, we describe the theory relevant to our experiment and derive new results when needed. We discuss the development and implementation of special optical devices used to create long plasma channels. We demonstrate for the first time the generation of meter-scale plasma channels and the acceleration of positron beams therein.« less

  19. 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.

  20. Convex Accelerated Maximum Entropy Reconstruction

    PubMed Central

    Worley, Bradley

    2016-01-01

    Maximum entropy (MaxEnt) spectral reconstruction methods provide a powerful framework for spectral estimation of nonuniformly sampled datasets. Many methods exist within this framework, usually defined based on the magnitude of a Lagrange multiplier in the MaxEnt objective function. An algorithm is presented here that utilizes accelerated first-order convex optimization techniques to rapidly and reliably reconstruct nonuniformly sampled NMR datasets using the principle of maximum entropy. This algorithm – called CAMERA for Convex Accelerated Maximum Entropy Reconstruction Algorithm – is a new approach to spectral reconstruction that exhibits fast, tunable convergence in both constant-aim and constant-lambda modes. A high-performance, open source NMR data processing tool is described that implements CAMERA, and brief comparisons to existing reconstruction methods are made on several example spectra. PMID:26894476

  1. Effect of Ability Grouping in Reciprocal Teaching Technique of Collaborative Learning on Individual Achievements and Social Skills

    ERIC Educational Resources Information Center

    Sumadi; Degeng, I Nyoman S.; Sulthon; Waras

    2017-01-01

    This research focused on effects of ability grouping in reciprocal teaching technique of collaborative learning on individual achievements dan social skills. The results research showed that (1) there are differences in individual achievement significantly between high group of homogeneous, middle group of homogeneous, low group of homogeneous,…

  2. Thomas Jefferson National Accelerator Facility

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

    Grames, Joseph; Higinbotham, Douglas; Montgomery, Hugh

    The Thomas Jefferson National Accelerator Facility (Jefferson Lab) in Newport News, Virginia, USA, is one of ten national laboratories under the aegis of the Office of Science of the U.S. Department of Energy (DOE). It is managed and operated by Jefferson Science Associates, LLC. The primary facility at Jefferson Lab is the Continuous Electron Beam Accelerator Facility (CEBAF) as shown in an aerial photograph in Figure 1. Jefferson Lab was created in 1984 as CEBAF and started operations for physics in 1995. The accelerator uses superconducting radio-frequency (srf) techniques to generate high-quality beams of electrons with high-intensity, well-controlled polarization. Themore » technology has enabled ancillary facilities to be created. The CEBAF facility is used by an international user community of more than 1200 physicists for a program of exploration and study of nuclear, hadronic matter, the strong interaction and quantum chromodynamics. Additionally, the exceptional quality of the beams facilitates studies of the fundamental symmetries of nature, which complement those of atomic physics on the one hand and of high-energy particle physics on the other. The facility is in the midst of a project to double the energy of the facility and to enhance and expand its experimental facilities. Studies are also pursued with a Free-Electron Laser produced by an energy-recovering linear accelerator.« less

  3. Accelerated testing of space mechanisms

    NASA Technical Reports Server (NTRS)

    Murray, S. Frank; Heshmat, Hooshang

    1995-01-01

    This report contains a review of various existing life prediction techniques used for a wide range of space mechanisms. Life prediction techniques utilized in other non-space fields such as turbine engine design are also reviewed for applicability to many space mechanism issues. The development of new concepts on how various tribological processes are involved in the life of the complex mechanisms used for space applications are examined. A 'roadmap' for the complete implementation of a tribological prediction approach for complex mechanical systems including standard procedures for test planning, analytical models for life prediction and experimental verification of the life prediction and accelerated testing techniques are discussed. A plan is presented to demonstrate a method for predicting the life and/or performance of a selected space mechanism mechanical component.

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

    PubMed

    Rajsic, Jason; Perera, Harendri; Pratt, Jay

    2017-02-01

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

  5. Scoping Study of Machine Learning Techniques for Visualization and Analysis of Multi-source Data in Nuclear Safeguards

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

    Cui, Yonggang

    In implementation of nuclear safeguards, many different techniques are being used to monitor operation of nuclear facilities and safeguard nuclear materials, ranging from radiation detectors, flow monitors, video surveillance, satellite imagers, digital seals to open source search and reports of onsite inspections/verifications. Each technique measures one or more unique properties related to nuclear materials or operation processes. Because these data sets have no or loose correlations, it could be beneficial to analyze the data sets together to improve the effectiveness and efficiency of safeguards processes. Advanced visualization techniques and machine-learning based multi-modality analysis could be effective tools in such integratedmore » analysis. In this project, we will conduct a survey of existing visualization and analysis techniques for multi-source data and assess their potential values in nuclear safeguards.« less

  6. Teaching Computational Geophysics Classes using Active Learning Techniques

    NASA Astrophysics Data System (ADS)

    Keers, H.; Rondenay, S.; Harlap, Y.; Nordmo, I.

    2016-12-01

    We give an overview of our experience in teaching two computational geophysics classes at the undergraduate level. In particular we describe The first class is for most students the first programming class and assumes that the students have had an introductory course in geophysics. In this class the students are introduced to basic Matlab skills: use of variables, basic array and matrix definition and manipulation, basic statistics, 1D integration, plotting of lines and surfaces, making of .m files and basic debugging techniques. All of these concepts are applied to elementary but important concepts in earthquake and exploration geophysics (including epicentre location, computation of travel time curves for simple layered media plotting of 1D and 2D velocity models etc.). It is important to integrate the geophysics with the programming concepts: we found that this enhances students' understanding. Moreover, as this is a 3 year Bachelor program, and this class is taught in the 2nd semester, there is little time for a class that focusses on only programming. In the second class, which is optional and can be taken in the 4th or 6th semester, but often is also taken by Master students we extend the Matlab programming to include signal processing and ordinary and partial differential equations, again with emphasis on geophysics (such as ray tracing and solving the acoustic wave equation). This class also contains a project in which the students have to write a brief paper on a topic in computational geophysics, preferably with programming examples. When teaching these classes it was found that active learning techniques, in which the students actively participate in the class, either individually, in pairs or in groups, are indispensable. We give a brief overview of the various activities that we have developed when teaching theses classes.

  7. Navigating the Active Learning Swamp: Creating an Inviting Environment for Learning.

    ERIC Educational Resources Information Center

    Johnson, Marie C.; Malinowski, Jon C.

    2001-01-01

    Reports on a survey of faculty members (n=29) asking them to define active learning, to rate how effectively different teaching techniques contribute to active learning, and to list the three teaching techniques they use most frequently. Concludes that active learning requires establishing an environment rather than employing a specific teaching…

  8. Prostate cancer detection using machine learning techniques by employing combination of features extracting strategies.

    PubMed

    Hussain, Lal; Ahmed, Adeel; Saeed, Sharjil; Rathore, Saima; Awan, Imtiaz Ahmed; Shah, Saeed Arif; Majid, Abdul; Idris, Adnan; Awan, Anees Ahmed

    2018-02-06

    Prostate is a second leading causes of cancer deaths among men. Early detection of cancer can effectively reduce the rate of mortality caused by Prostate cancer. Due to high and multiresolution of MRIs from prostate cancer require a proper diagnostic systems and tools. In the past researchers developed Computer aided diagnosis (CAD) systems that help the radiologist to detect the abnormalities. In this research paper, we have employed novel Machine learning techniques such as Bayesian approach, Support vector machine (SVM) kernels: polynomial, radial base function (RBF) and Gaussian and Decision Tree for detecting prostate cancer. Moreover, different features extracting strategies are proposed to improve the detection performance. The features extracting strategies are based on texture, morphological, scale invariant feature transform (SIFT), and elliptic Fourier descriptors (EFDs) features. The performance was evaluated based on single as well as combination of features using Machine Learning Classification techniques. The Cross validation (Jack-knife k-fold) was performed and performance was evaluated in term of receiver operating curve (ROC) and specificity, sensitivity, Positive predictive value (PPV), negative predictive value (NPV), false positive rate (FPR). Based on single features extracting strategies, SVM Gaussian Kernel gives the highest accuracy of 98.34% with AUC of 0.999. While, using combination of features extracting strategies, SVM Gaussian kernel with texture + morphological, and EFDs + morphological features give the highest accuracy of 99.71% and AUC of 1.00.

  9. Using Contact Forces and Robot Arm Accelerations to Automatically Rate Surgeon Skill at Peg Transfer.

    PubMed

    Brown, Jeremy D; O Brien, Conor E; Leung, Sarah C; Dumon, Kristoffel R; Lee, David I; Kuchenbecker, Katherine J

    2017-09-01

    Most trainees begin learning robotic minimally invasive surgery by performing inanimate practice tasks with clinical robots such as the Intuitive Surgical da Vinci. Expert surgeons are commonly asked to evaluate these performances using standardized five-point rating scales, but doing such ratings is time consuming, tedious, and somewhat subjective. This paper presents an automatic skill evaluation system that analyzes only the contact force with the task materials, the broad-bandwidth accelerations of the robotic instruments and camera, and the task completion time. We recruited N = 38 participants of varying skill in robotic surgery to perform three trials of peg transfer with a da Vinci Standard robot instrumented with our Smart Task Board. After calibration, three individuals rated these trials on five domains of the Global Evaluative Assessment of Robotic Skill (GEARS) structured assessment tool, providing ground-truth labels for regression and classification machine learning algorithms that predict GEARS scores based on the recorded force, acceleration, and time signals. Both machine learning approaches produced scores on the reserved testing sets that were in good to excellent agreement with the human raters, even when the force information was not considered. Furthermore, regression predicted GEARS scores more accurately and efficiently than classification. A surgeon's skill at robotic peg transfer can be reliably rated via regression using features gathered from force, acceleration, and time sensors external to the robot. We expect improved trainee learning as a result of providing these automatic skill ratings during inanimate task practice on a surgical robot.

  10. 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…

  11. Investigation of a Study Technique To Increase Learning Disabled Students' Reading Comprehension of Expository Text. Final Report.

    ERIC Educational Resources Information Center

    McCormick, Sandra; Cooper, John O.

    The study reported in this paper investigated the effects of a frequently recommended study technique on the comprehension of expository text by high-school students having learning disabilities. The instructional procedure studied was "Survey, Question, Read, Recite, Review" (SQ3R). Six experiments were conducted over a 3-year period,…

  12. 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

  13. First muon acceleration using a radio-frequency accelerator

    NASA Astrophysics Data System (ADS)

    Bae, S.; Choi, H.; Choi, S.; Fukao, Y.; Futatsukawa, K.; Hasegawa, K.; Iijima, T.; Iinuma, H.; Ishida, K.; Kawamura, N.; Kim, B.; Kitamura, R.; Ko, H. S.; Kondo, Y.; Li, S.; Mibe, T.; Miyake, Y.; Morishita, T.; Nakazawa, Y.; Otani, M.; Razuvaev, G. P.; Saito, N.; Shimomura, K.; Sue, Y.; Won, E.; Yamazaki, T.

    2018-05-01

    Muons have been accelerated by using a radio-frequency accelerator for the first time. Negative muonium atoms (Mu- ), which are bound states of positive muons (μ+) and two electrons, are generated from μ+'s through the electron capture process in an aluminum degrader. The generated Mu- 's are initially electrostatically accelerated and injected into a radio-frequency quadrupole linac (RFQ). In the RFQ, the Mu- 's are accelerated to 89 keV. The accelerated Mu- 's are identified by momentum measurement and time of flight. This compact muon linac opens the door to various muon accelerator applications including particle physics measurements and the construction of a transmission muon microscope.

  14. Students' perceptions of effective learning experiences in dental school: a qualitative study using a critical incident technique.

    PubMed

    Victoroff, Kristin Zakariasen; Hogan, Sarah

    2006-02-01

    Students' views of their educational experience can be an important source of information for curriculum assessment. Although quantitative methods, particularly surveys, are frequently used to gather such data, fewer studies have employed qualitative methods to examine students' dental education experiences. The purpose of this study is to explore characteristics of effective learning experiences in dental school using a qualitative method. All third-year (seventy) and fourth-year (seventy) dental students enrolled in one midwestern dental school were invited to participate. Fifty-three dental students (thirty-five male and eighteen female; thirty-two third-year and twenty-one fourth-year) were interviewed using a critical incident interview technique. Each student was asked to describe a specific, particularly effective learning incident that he or she had experienced in dental school and a specific, particularly ineffective learning incident, for comparison. Each interview was audiotaped. Students were assured that only the interviewer and one additional researcher would have access to the tapes. Data analysis resulted in identification of key themes in the data describing characteristics of effective learning experiences. The following characteristics of effective learning experiences were identified: 1) instructor characteristics (personal qualities, "checking-in" with students, and an interactive style); 2) characteristics of the learning process (focus on the "big picture," modeling and demonstrations, opportunities to apply new knowledge, high-quality feedback, focus, specificity and relevance, and peer interactions); and 3) learning environment (culture of the learning environment, technology). Common themes emerged across a wide variety of learning incidents. Although additional research is needed, the characteristics of effective learning experiences identified in this study may have implications for individual course design and for the dental school

  15. Combined use of two supervised learning algorithms to model sea turtle behaviours from tri-axial acceleration data.

    PubMed

    Jeantet, L; Dell'Amico, F; Forin-Wiart, M-A; Coutant, M; Bonola, M; Etienne, D; Gresser, J; Regis, S; Lecerf, N; Lefebvre, F; de Thoisy, B; Le Maho, Y; Brucker, M; Châtelain, N; Laesser, R; Crenner, F; Handrich, Y; Wilson, R; Chevallier, D

    2018-05-23

    Accelerometers are becoming ever more important sensors in animal-attached technology, providing data that allow determination of body posture and movement and thereby helping to elucidate behaviour in animals that are difficult to observe. We sought to validate the identification of sea turtle behaviours from accelerometer signals by deploying tags on the carapace of a juvenile loggerhead ( Caretta caretta ), an adult hawksbill ( Eretmochelys imbricata ) and an adult green turtle ( Chelonia mydas ) at Aquarium La Rochelle, France. We recorded tri-axial acceleration at 50 Hz for each species for a full day while two fixed cameras recorded their behaviours. We identified behaviours from the acceleration data using two different supervised learning algorithms, Random Forest and Classification And Regression Tree (CART), treating the data from the adult animals as separate from the juvenile data. We achieved a global accuracy of 81.30% for the adult hawksbill and green turtle CART model and 71.63% for the juvenile loggerhead, identifying 10 and 12 different behaviours, respectively. Equivalent figures were 86.96% for the adult hawksbill and green turtle Random Forest model and 79.49% for the juvenile loggerhead, for the same behaviours. The use of Random Forest combined with CART algorithms allowed us to understand the decision rules implicated in behaviour discrimination, and thus remove or group together some 'confused' or under--represented behaviours in order to get the most accurate models. This study is the first to validate accelerometer data to identify turtle behaviours and the approach can now be tested on other captive sea turtle species. © 2018. Published by The Company of Biologists Ltd.

  16. The Effect of Blended Instruction on Accelerated Learning

    ERIC Educational Resources Information Center

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

    2016-01-01

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

  17. 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.

  18. Angular distribution of electrons from powerful accelerators

    NASA Astrophysics Data System (ADS)

    Stepovik, A. P.; Lartsev, V. D.; Blinov, V. S.

    2007-07-01

    A technique for measuring the angular distribution of electrons escaping from the center of the window of the IGUR-3 and ÉMIR-M powerful accelerators (designed at the All-Russia Institute of Technical Physics, Russian Federal Nuclear Center) into ambient air is presented, and measurement data are reported. The number of electrons is measured with cable detectors (the solid angle of the collimator of the detector is ≈0.01 sr). The measurements are made in three azimuthal directions in 120° intervals in the polar angle range 0 22°. The angular distributions of the electrons coming out of the accelerators are represented in the form of B splines.

  19. Predicting the trajectories and intensities of hurricanes by applying machine learning techniques

    NASA Astrophysics Data System (ADS)

    Sujithkumar, A.; King, A. W.; Kovilakam, M.; Graves, D.

    2017-12-01

    The world has witnessed an escalation of devastating hurricanes and tropical cyclones over the last three decades. Hurricanes and tropical cyclones of very high magnitude will likely be even more frequent in a warmer world. Thus, precise forecasting of the track and intensity of hurricane/tropical cyclones remains one of the meteorological community's top priorities. However, comprehensive prediction of hurricane/ tropical cyclone is a difficult problem due to the many complexities of underlying physical processes with many variables and complex relations. The availability of global meteorological and hurricane/tropical storm climatological data opens new opportunities for data-driven approaches to hurricane/tropical cyclone modeling. Here we report initial results from two data-driven machine learning techniques, specifically, random forest (RF) and Bayesian learning (BL) to predict the trajectory and intensity of hurricanes and tropical cyclones. We used International Best Track Archive for Climate Stewardship (IBTrACS) data along with weather data from NOAA in a 50 km buffer surrounding each of the reported hurricane and tropical cyclone tracts to train the model. Initial results reveal that both RF and BL are skillful in predicting storm intensity. We will also present results for the more complicated trajectory prediction.

  20. Machine learning techniques applied to the determination of road suitability for the transportation of dangerous substances.

    PubMed

    Matías, J M; Taboada, J; Ordóñez, C; Nieto, P G

    2007-08-17

    This article describes a methodology to model the degree of remedial action required to make short stretches of a roadway suitable for dangerous goods transport (DGT), particularly pollutant substances, using different variables associated with the characteristics of each segment. Thirty-one factors determining the impact of an accident on a particular stretch of road were identified and subdivided into two major groups: accident probability factors and accident severity factors. Given the number of factors determining the state of a particular road segment, the only viable statistical methods for implementing the model were machine learning techniques, such as multilayer perceptron networks (MLPs), classification trees (CARTs) and support vector machines (SVMs). The results produced by these techniques on a test sample were more favourable than those produced by traditional discriminant analysis, irrespective of whether dimensionality reduction techniques were applied. The best results were obtained using SVMs specifically adapted to ordinal data. This technique takes advantage of the ordinal information contained in the data without penalising the computational load. Furthermore, the technique permits the estimation of the utility function that is latent in expert knowledge.

  1. Analytical tools in accelerator physics

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

    Litvinenko, V.N.

    2010-09-01

    This paper is a sub-set of my lectures presented in the Accelerator Physics course (USPAS, Santa Rosa, California, January 14-25, 2008). It is based on my notes I wrote during period from 1976 to 1979 in Novosibirsk. Only few copies (in Russian) were distributed to my colleagues in Novosibirsk Institute of Nuclear Physics. The goal of these notes is a complete description starting from the arbitrary reference orbit, explicit expressions for 4-potential and accelerator Hamiltonian and finishing with parameterization with action and angle variables. To a large degree follow logic developed in Theory of Cyclic Particle Accelerators by A.A.Kolmensky andmore » A.N.Lebedev [Kolomensky], but going beyond the book in a number of directions. One of unusual feature is these notes use of matrix function and Sylvester formula for calculating matrices of arbitrary elements. Teaching the USPAS course motivated me to translate significant part of my notes into the English. I also included some introductory materials following Classical Theory of Fields by L.D. Landau and E.M. Liftsitz [Landau]. A large number of short notes covering various techniques are placed in the Appendices.« less

  2. Acceleration Modes and Transitions in Pulsed Plasma Accelerators

    NASA Technical Reports Server (NTRS)

    Polzin, Kurt A.; Greve, Christine M.

    2018-01-01

    Pulsed plasma accelerators typically operate by storing energy in a capacitor bank and then discharging this energy through a gas, ionizing and accelerating it through the Lorentz body force. Two plasma accelerator types employing this general scheme have typically been studied: the gas-fed pulsed plasma thruster and the quasi-steady magnetoplasmadynamic (MPD) accelerator. The gas-fed pulsed plasma accelerator is generally represented as a completely transient device discharging in approximately 1-10 microseconds. When the capacitor bank is discharged through the gas, a current sheet forms at the breech of the thruster and propagates forward under a j (current density) by B (magnetic field) body force, entraining propellant it encounters. This process is sometimes referred to as detonation-mode acceleration because the current sheet representation approximates that of a strong shock propagating through the gas. Acceleration of the initial current sheet ceases when either the current sheet reaches the end of the device and is ejected or when the current in the circuit reverses, striking a new current sheet at the breech and depriving the initial sheet of additional acceleration. In the quasi-steady MPD accelerator, the pulse is lengthened to approximately 1 millisecond or longer and maintained at an approximately constant level during discharge. The time over which the transient phenomena experienced during startup typically occur is short relative to the overall discharge time, which is now long enough for the plasma to assume a relatively steady-state configuration. The ionized gas flows through a stationary current channel in a manner that is sometimes referred to as the deflagration-mode of operation. The plasma experiences electromagnetic acceleration as it flows through the current channel towards the exit of the device. A device that had a short pulse length but appeared to operate in a plasma acceleration regime different from the gas-fed pulsed plasma

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

    PubMed Central

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

    2017-01-01

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

  4. Deep learning ensemble with asymptotic techniques for oscillometric blood pressure estimation.

    PubMed

    Lee, Soojeong; Chang, Joon-Hyuk

    2017-11-01

    This paper proposes a deep learning based ensemble regression estimator with asymptotic techniques, and offers a method that can decrease uncertainty for oscillometric blood pressure (BP) measurements using the bootstrap and Monte-Carlo approach. While the former is used to estimate SBP and DBP, the latter attempts to determine confidence intervals (CIs) for SBP and DBP based on oscillometric BP measurements. This work originally employs deep belief networks (DBN)-deep neural networks (DNN) to effectively estimate BPs based on oscillometric measurements. However, there are some inherent problems with these methods. First, it is not easy to determine the best DBN-DNN estimator, and worthy information might be omitted when selecting one DBN-DNN estimator and discarding the others. Additionally, our input feature vectors, obtained from only five measurements per subject, represent a very small sample size; this is a critical weakness when using the DBN-DNN technique and can cause overfitting or underfitting, depending on the structure of the algorithm. To address these problems, an ensemble with an asymptotic approach (based on combining the bootstrap with the DBN-DNN technique) is utilized to generate the pseudo features needed to estimate the SBP and DBP. In the first stage, the bootstrap-aggregation technique is used to create ensemble parameters. Afterward, the AdaBoost approach is employed for the second-stage SBP and DBP estimation. We then use the bootstrap and Monte-Carlo techniques in order to determine the CIs based on the target BP estimated using the DBN-DNN ensemble regression estimator with the asymptotic technique in the third stage. The proposed method can mitigate the estimation uncertainty such as large the standard deviation of error (SDE) on comparing the proposed DBN-DNN ensemble regression estimator with the DBN-DNN single regression estimator, we identify that the SDEs of the SBP and DBP are reduced by 0.58 and 0.57  mmHg, respectively. These

  5. The Artificial Intelligence Applications to Learning Programme.

    ERIC Educational Resources Information Center

    Williams, Noel

    1992-01-01

    Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

  6. Gifted Students' Perceptions of an Accelerated Summer Program and Social Support

    ERIC Educational Resources Information Center

    Lee, Seon-Young; Olszewski-Kubilius, Paula; Makel, Matthew C.; Putallaz, Martha

    2015-01-01

    Using survey responses from students who participated in the summer programs at two university-based gifted education institutions, this study examined changes in gifted students' perceptions of their learning environments, accelerated summer programs and regular schools, and social support in lives after participation in the summer programs. Our…

  7. The Effect of Jigsaw Technique on 6th Graders' Learning of Force and Motion Unit and Their Science Attitudes and Motivation

    ERIC Educational Resources Information Center

    Ural, Evrim; Ercan, Orhan; Gençoglan, Durdu Mehmet

    2017-01-01

    The study aims to investigate the effects of jigsaw technique on 6th graders' learning of "Force and Motion" unit, their science learning motivation and their attitudes towards science classes. The sample of the study consisted of 49 6th grade students from two different classes taking the Science and Technology course at a government…

  8. Transient aerodynamic characteristics of vans during the accelerated overtaking process

    NASA Astrophysics Data System (ADS)

    Liu, Li-ning; Wang, Xing-shen; Du, Guang-sheng; Liu, Zheng-gang; Lei, Li

    2018-04-01

    This paper studies the influence of the accelerated overtaking process on the vehicles' transient aerodynamic characteristics, through 3-D numerical simulations with dynamic meshes and sliding interface technique. Numerical accuracy is verified by experimental results. The aerodynamic characteristics of vehicles in the uniform overtaking process and the accelerated overtaking process are compared. It is shown that the speed variation of the overtaking van would influence the aerodynamic characteristics of the two vans, with greater influence on the overtaken van than on the overtaking van. The simulations of three different accelerated overtaking processes show that the greater the acceleration of the overtaking van, the larger the aerodynamic coefficients of the overtaken van. When the acceleration of the overtaking van increases by 1 m/s2, the maximum drag force, side force and yawing moment coefficients of the overtaken van all increase by more than 6%, to seriously affect the power performance and the stability of the vehicles. The analysis of the pressure fields under different accelerated conditions reveals the cause of variations of the aerodynamic characteristics of vehicles.

  9. Radiolabeled Microsphere Technique in Conscious Subjects during Acceleration Exposures on the USAFSAM Centrifuge.

    DTIC Science & Technology

    1980-03-01

    function even though the pump is pumping air into the blood manifold. R-2 is secured to the plate with two thumb screws, and when the syringes are...the scapula . The animals were allowed 2-4 weeks of surgical recovery before the acceleration studies were performed. Experimental Protocol--On the day

  10. Blending Learning: The Evolution of Online and Face-to-Face Education from 2008-2015. Promising Practices in Blended and Online Learning Series

    ERIC Educational Resources Information Center

    Powell, Allison; Watson, John; Staley, Patrick; Patrick, Susan; Horn, Michael; Fetzer, Leslie; Hibbard, Laura; Oglesby, Jonathan; Verma, Sue

    2015-01-01

    In 2008, the International Association for K-12 Online Learning (iNACOL) produced a series of papers documenting promising practices identified throughout the field of K-12 online learning. Since then, we have witnessed a tremendous acceleration of transformative policy and practice driving personalized learning in the K-12 education space. State,…

  11. Accelerated design of bioconversion processes using automated microscale processing techniques.

    PubMed

    Lye, Gary J; Ayazi-Shamlou, Parviz; Baganz, Frank; Dalby, Paul A; Woodley, John M

    2003-01-01

    Microscale processing techniques are rapidly emerging as a means to increase the speed of bioprocess design and reduce material requirements. Automation of these techniques can reduce labour intensity and enable a wider range of process variables to be examined. This article examines recent research on various individual microscale unit operations including microbial fermentation, bioconversion and product recovery techniques. It also explores the potential of automated whole process sequences operated in microwell formats. The power of the whole process approach is illustrated by reference to a particular bioconversion, namely the Baeyer-Villiger oxidation of bicyclo[3.2.0]hept-2-en-6-one for the production of optically pure lactones.

  12. On-Chip Laser-Power Delivery System for Dielectric Laser Accelerators

    NASA Astrophysics Data System (ADS)

    Hughes, Tyler W.; Tan, Si; Zhao, Zhexin; Sapra, Neil V.; Leedle, Kenneth J.; Deng, Huiyang; Miao, Yu; Black, Dylan S.; Solgaard, Olav; Harris, James S.; Vuckovic, Jelena; Byer, Robert L.; Fan, Shanhui; England, R. Joel; Lee, Yun Jo; Qi, Minghao

    2018-05-01

    We propose an on-chip optical-power delivery system for dielectric laser accelerators based on a fractal "tree-network" dielectric waveguide geometry. This system replaces experimentally demanding free-space manipulations of the driving laser beam with chip-integrated techniques based on precise nanofabrication, enabling access to orders-of-magnitude increases in the interaction length and total energy gain for these miniature accelerators. Based on computational modeling, in the relativistic regime, our laser delivery system is estimated to provide 21 keV of energy gain over an acceleration length of 192 μ m with a single laser input, corresponding to a 108-MV/m acceleration gradient. The system may achieve 1 MeV of energy gain over a distance of less than 1 cm by sequentially illuminating 49 identical structures. These findings are verified by detailed numerical simulation and modeling of the subcomponents, and we provide a discussion of the main constraints, challenges, and relevant parameters with regard to on-chip laser coupling for dielectric laser accelerators.

  13. Accelerating Imitation Learning in Relational Domains via Transfer by Initialization

    DTIC Science & Technology

    2013-08-28

    Warcraft , regulation of traffic lights, logistics, and a variety of planning domains. A supervised learning method for imitation learning was recently...some information about the world (traffic density at a signal, distance to the goal etc.). We assume a functional parametrization over the policy and...strategy (RTS) game engine written in C based off the Warcraft series of games. Like all RTS games, it allows multiple agents to be controlled

  14. Learning Organisations--Reengineering Schools for Life Long Learning.

    ERIC Educational Resources Information Center

    O'Sullivan, Fergus

    1997-01-01

    Examines some key ideas behind the learning organization and explains why the concept is so powerful in contemporary contexts. Identifies various types of learning organizations, and suggests an analytical technique for relating styles of organizational learning to the environmental context. The key to becoming a learning organization is…

  15. Lesion Detection in CT Images Using Deep Learning Semantic Segmentation Technique

    NASA Astrophysics Data System (ADS)

    Kalinovsky, A.; Liauchuk, V.; Tarasau, A.

    2017-05-01

    In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For training and testing of the algorithms a domestic dataset of 338 3D CT scans of tuberculosis patients with manually labelled lesions was used. The algorithms which are based on using Deep Convolutional Networks were implemented and applied in three different ways including slice-wise lesion detection in 2D images using semantic segmentation, slice-wise lesion detection in 2D images using sliding window technique as well as straightforward detection of lesions via semantic segmentation in whole 3D CT scans. The algorithms demonstrate superior performance compared to algorithms based on conventional image analysis methods.

  16. Locus coeruleus activation accelerates perceptual learning.

    PubMed

    Glennon, Erin; Carcea, Ioana; Martins, Ana Raquel O; Multani, Jasmin; Shehu, Ina; Svirsky, Mario A; Froemke, Robert C

    2018-05-31

    Neural representations of the external world are constructed and updated in a manner that depends on behavioral context. For neocortical networks, this contextual information is relayed by a diverse range of neuromodulatory systems, which govern attention and signal the value of internal state variables such as arousal, motivation, and stress. Neuromodulators enable cortical circuits to differentially process specific stimuli and modify synaptic strengths in order to maintain short- or long-term memory traces of significant perceptual events and behavioral episodes. One of the most important subcortical neuromodulatory systems for attention and arousal is the noradrenergic locus coeruleus. Here we report that the noradrenergic system can enhance behavior in rats performing a self-initiated auditory recognition task, and optogenetic stimulation of noradrenergic locus coeruleus neurons accelerated the rate at which trained rats began correctly responding to a change in reward contingency. Animals successively progressed through distinct behavioral epochs, including periods of perseverance and exploration that occurred much more rapidly when animals received locus coeruleus stimulation. In parallel, we made recordings from primary auditory cortex and found that pairing tones with locus coeruleus stimulation led to a similar set of changes to cortical tuning profiles. Thus both behavioral and neural responses go through phases of adjustment for exploring and exploiting environmental reward contingencies. Furthermore, behavioral engagement does not necessarily recruit optimal locus coeruleus activity. Copyright © 2018. Published by Elsevier B.V.

  17. Experimental test of photonic entanglement in accelerated reference frames

    NASA Astrophysics Data System (ADS)

    Fink, Matthias; Rodriguez-Aramendia, Ana; Handsteiner, Johannes; Ziarkash, Abdul; Steinlechner, Fabian; Scheidl, Thomas; Fuentes, Ivette; Pienaar, Jacques; Ralph, Timothy C.; Ursin, Rupert

    2017-05-01

    The unification of the theory of relativity and quantum mechanics is a long-standing challenge in contemporary physics. Experimental techniques in quantum optics have only recently reached the maturity required for the investigation of quantum systems under the influence of non-inertial motion, such as being held at rest in gravitational fields, or subjected to uniform accelerations. Here, we report on experiments in which a genuine quantum state of an entangled photon pair is exposed to a series of different accelerations. We measure an entanglement witness for g-values ranging from 30 mg to up to 30 g--under free-fall as well on a spinning centrifuge--and have thus derived an upper bound on the effects of uniform acceleration on photonic entanglement.

  18. Experimental test of photonic entanglement in accelerated reference frames

    PubMed Central

    Fink, Matthias; Rodriguez-Aramendia, Ana; Handsteiner, Johannes; Ziarkash, Abdul; Steinlechner, Fabian; Scheidl, Thomas; Fuentes, Ivette; Pienaar, Jacques; Ralph, Timothy C.; Ursin, Rupert

    2017-01-01

    The unification of the theory of relativity and quantum mechanics is a long-standing challenge in contemporary physics. Experimental techniques in quantum optics have only recently reached the maturity required for the investigation of quantum systems under the influence of non-inertial motion, such as being held at rest in gravitational fields, or subjected to uniform accelerations. Here, we report on experiments in which a genuine quantum state of an entangled photon pair is exposed to a series of different accelerations. We measure an entanglement witness for g-values ranging from 30 mg to up to 30 g—under free-fall as well on a spinning centrifuge—and have thus derived an upper bound on the effects of uniform acceleration on photonic entanglement. PMID:28489082

  19. Experimental test of photonic entanglement in accelerated reference frames.

    PubMed

    Fink, Matthias; Rodriguez-Aramendia, Ana; Handsteiner, Johannes; Ziarkash, Abdul; Steinlechner, Fabian; Scheidl, Thomas; Fuentes, Ivette; Pienaar, Jacques; Ralph, Timothy C; Ursin, Rupert

    2017-05-10

    The unification of the theory of relativity and quantum mechanics is a long-standing challenge in contemporary physics. Experimental techniques in quantum optics have only recently reached the maturity required for the investigation of quantum systems under the influence of non-inertial motion, such as being held at rest in gravitational fields, or subjected to uniform accelerations. Here, we report on experiments in which a genuine quantum state of an entangled photon pair is exposed to a series of different accelerations. We measure an entanglement witness for g-values ranging from 30 mg to up to 30 g-under free-fall as well on a spinning centrifuge-and have thus derived an upper bound on the effects of uniform acceleration on photonic entanglement.

  20. Evaluation of the Accelerated Reader Program in Chesapeake, VA, Public Schools

    ERIC Educational Resources Information Center

    Chase, Elaine; Goodin, Penny; Nichols, W. Randolph

    2010-01-01

    The Accelerated Reader program from Renaissance Learning Inc. is a popular program implemented in elementary and middle schools across the country that encourages students to read and monitors their progress in the program. Despite its widespread use and popularity, there have been some questions about the program's effectiveness at increasing…