A new optimized GA-RBF neural network algorithm.

PubMed

Jia, Weikuan; Zhao, Dean; Shen, Tian; Su, Chunyang; Hu, Chanli; Zhao, Yuyan

2014-01-01

When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and recognition precision. Aiming at this problem, we propose a new optimized RBF neural network algorithm based on genetic algorithm (GA-RBF algorithm), which uses genetic algorithm to optimize the weights and structure of RBF neural network; it chooses new ways of hybrid encoding and optimizing simultaneously. Using the binary encoding encodes the number of the hidden layer's neurons and using real encoding encodes the connection weights. Hidden layer neurons number and connection weights are optimized simultaneously in the new algorithm. However, the connection weights optimization is not complete; we need to use least mean square (LMS) algorithm for further leaning, and finally get a new algorithm model. Using two UCI standard data sets to test the new algorithm, the results show that the new algorithm improves the operating efficiency in dealing with complex problems and also improves the recognition precision, which proves that the new algorithm is valid.

Evaluation of the Effects of Hidden Node Problems in IEEE 802.15.7 Uplink Performance

PubMed Central

Ley-Bosch, Carlos; Alonso-González, Itziar; Sánchez-Rodríguez, David; Ramírez-Casañas, Carlos

2016-01-01

In the last few years, the increasing use of LEDs in illumination systems has been conducted due to the emergence of Visible Light Communication (VLC) technologies, in which data communication is performed by transmitting through the visible band of the electromagnetic spectrum. In 2011, the Institute of Electrical and Electronics Engineers (IEEE) published the IEEE 802.15.7 standard for Wireless Personal Area Networks based on VLC. Due to limitations in the coverage of the transmitted signal, wireless networks can suffer from the hidden node problems, when there are nodes in the network whose transmissions are not detected by other nodes. This problem can cause an important degradation in communications when they are made by means of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) access control method, which is used in IEEE 802.15.7 This research work evaluates the effects of the hidden node problem in the performance of the IEEE 802.15.7 standard We implement a simulator and analyze VLC performance in terms of parameters like end-to-end goodput and message loss rate. As part of this research work, a solution to the hidden node problem is proposed, based on the use of idle patterns defined in the standard. Idle patterns are sent by the network coordinator node to communicate to the other nodes that there is an ongoing transmission. The validity of the proposed solution is demonstrated with simulation results. PMID:26861352

Evaluation of the Effects of Hidden Node Problems in IEEE 802.15.7 Uplink Performance.

PubMed

Ley-Bosch, Carlos; Alonso-González, Itziar; Sánchez-Rodríguez, David; Ramírez-Casañas, Carlos

2016-02-06

In the last few years, the increasing use of LEDs in illumination systems has been conducted due to the emergence of Visible Light Communication (VLC) technologies, in which data communication is performed by transmitting through the visible band of the electromagnetic spectrum. In 2011, the Institute of Electrical and Electronics Engineers (IEEE) published the IEEE 802.15.7 standard for Wireless Personal Area Networks based on VLC. Due to limitations in the coverage of the transmitted signal, wireless networks can suffer from the hidden node problems, when there are nodes in the network whose transmissions are not detected by other nodes. This problem can cause an important degradation in communications when they are made by means of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) access control method, which is used in IEEE 802.15.7 This research work evaluates the effects of the hidden node problem in the performance of the IEEE 802.15.7 standard We implement a simulator and analyze VLC performance in terms of parameters like end-to-end goodput and message loss rate. As part of this research work, a solution to the hidden node problem is proposed, based on the use of idle patterns defined in the standard. Idle patterns are sent by the network coordinator node to communicate to the other nodes that there is an ongoing transmission. The validity of the proposed solution is demonstrated with simulation results.

Detecting targets hidden in random forests

NASA Astrophysics Data System (ADS)

Kouritzin, Michael A.; Luo, Dandan; Newton, Fraser; Wu, Biao

2009-05-01

Military tanks, cargo or troop carriers, missile carriers or rocket launchers often hide themselves from detection in the forests. This plagues the detection problem of locating these hidden targets. An electro-optic camera mounted on a surveillance aircraft or unmanned aerial vehicle is used to capture the images of the forests with possible hidden targets, e.g., rocket launchers. We consider random forests of longitudinal and latitudinal correlations. Specifically, foliage coverage is encoded with a binary representation (i.e., foliage or no foliage), and is correlated in adjacent regions. We address the detection problem of camouflaged targets hidden in random forests by building memory into the observations. In particular, we propose an efficient algorithm to generate random forests, ground, and camouflage of hidden targets with two dimensional correlations. The observations are a sequence of snapshots consisting of foliage-obscured ground or target. Theoretically, detection is possible because there are subtle differences in the correlations of the ground and camouflage of the rocket launcher. However, these differences are well beyond human perception. To detect the presence of hidden targets automatically, we develop a Markov representation for these sequences and modify the classical filtering equations to allow the Markov chain observation. Particle filters are used to estimate the position of the targets in combination with a novel random weighting technique. Furthermore, we give positive proof-of-concept simulations.

Nonparametric model validations for hidden Markov models with applications in financial econometrics

PubMed Central

Zhao, Zhibiao

2011-01-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise. PMID:21750601

Hidden shift of the ionome of plants exposed to elevated CO2 depletes minerals at the base of human nutrition

PubMed Central

Loladze, Irakli

2014-01-01

Mineral malnutrition stemming from undiversified plant-based diets is a top global challenge. In C3 plants (e.g., rice, wheat), elevated concentrations of atmospheric carbon dioxide (eCO2) reduce protein and nitrogen concentrations, and can increase the total non-structural carbohydrates (TNC; mainly starch, sugars). However, contradictory findings have obscured the effect of eCO2 on the ionome—the mineral and trace-element composition—of plants. Consequently, CO2-induced shifts in plant quality have been ignored in the estimation of the impact of global change on humans. This study shows that eCO2 reduces the overall mineral concentrations (−8%, 95% confidence interval: −9.1 to −6.9, p<0.00001) and increases TNC:minerals > carbon:minerals in C3 plants. The meta-analysis of 7761 observations, including 2264 observations at state of the art FACE centers, covers 130 species/cultivars. The attained statistical power reveals that the shift is systemic and global. Its potential to exacerbate the prevalence of ‘hidden hunger’ and obesity is discussed. DOI: http://dx.doi.org/10.7554/eLife.02245.001 PMID:24867639

An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization.

PubMed

García-Pedrajas, Nicolás; Ortiz-Boyer, Domingo; Hervás-Martínez, César

2006-05-01

In this work we present a new approach to crossover operator in the genetic evolution of neural networks. The most widely used evolutionary computation paradigm for neural network evolution is evolutionary programming. This paradigm is usually preferred due to the problems caused by the application of crossover to neural network evolution. However, crossover is the most innovative operator within the field of evolutionary computation. One of the most notorious problems with the application of crossover to neural networks is known as the permutation problem. This problem occurs due to the fact that the same network can be represented in a genetic coding by many different codifications. Our approach modifies the standard crossover operator taking into account the special features of the individuals to be mated. We present a new model for mating individuals that considers the structure of the hidden layer and redefines the crossover operator. As each hidden node represents a non-linear projection of the input variables, we approach the crossover as a problem on combinatorial optimization. We can formulate the problem as the extraction of a subset of near-optimal projections to create the hidden layer of the new network. This new approach is compared to a classical crossover in 25 real-world problems with an excellent performance. Moreover, the networks obtained are much smaller than those obtained with classical crossover operator.

Measurement problem and local hidden variables with entangled photons

NASA Astrophysics Data System (ADS)

Muchowski, Eugen

2017-12-01

It is shown that there is no remote action with polarization measurements of photons in singlet state. A model is presented introducing a hidden parameter which determines the polarizer output. This model is able to explain the polarization measurement results with entangled photons. It is not ruled out by Bell's Theorem.

Hidden Markov models and other machine learning approaches in computational molecular biology

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

Baldi, P.

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In thismore » tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.« less

Image segmentation using hidden Markov Gauss mixture models.

PubMed

Pyun, Kyungsuk; Lim, Johan; Won, Chee Sun; Gray, Robert M

2007-07-01

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

Infinite hidden conditional random fields for human behavior analysis.

PubMed

Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja

2013-01-01

Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF (iHCRF), which is a nonparametric model based on hierarchical Dirichlet processes and is capable of automatically learning the optimal number of hidden states for a classification task. We show how we learn the model hyperparameters with an effective Markov-chain Monte Carlo sampling technique, and we explain the process that underlines our iHCRF model with the Restaurant Franchise Rating Agencies analogy. We show that the iHCRF is able to converge to a correct number of represented hidden states, and outperforms the best finite HCRFs--chosen via cross-validation--for the difficult tasks of recognizing instances of agreement, disagreement, and pain. Moreover, the iHCRF manages to achieve this performance in significantly less total training, validation, and testing time.

Tracking problem solving by multivariate pattern analysis and Hidden Markov Model algorithms.

PubMed

Anderson, John R

2012-03-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application involves using fMRI activity to track what students are doing as they solve a sequence of algebra problems. The methodology achieves considerable accuracy at determining both what problem-solving step the students are taking and whether they are performing that step correctly. The second "model discovery" application involves using statistical model evaluation to determine how many substates are involved in performing a step of algebraic problem solving. This research indicates that different steps involve different numbers of substates and these substates are associated with different fluency in algebra problem solving. Copyright © 2011 Elsevier Ltd. All rights reserved.

Mrs. Miniver's Girls: Plucky Girls in "Hidden Figures," "The Zookeeper's Wife," "Their Finest," and "Colossal"

ERIC Educational Resources Information Center

Beck, Bernard

2017-01-01

Four recent movies, "Hidden Figures," "The Zookeeper's Wife," "Their Finest," and "Colossal" exemplify a new cultural version of the movie heroine. This version combines feminism with commitment to solving an overwhelming problem. These heroines, thus, display the character virtues of Wonder Woman and Mrs.…

Early Prediction of Students' Grade Point Averages at Graduation: A Data Mining Approach

ERIC Educational Resources Information Center

Tekin, Ahmet

2014-01-01

Problem Statement: There has recently been interest in educational databases containing a variety of valuable but sometimes hidden data that can be used to help less successful students to improve their academic performance. The extraction of hidden information from these databases often implements aspects of the educational data mining (EDM)…

Dramatising the Hidden Hurt: Acting against Covert Bullying by Adolescent Girls

ERIC Educational Resources Information Center

Burton, Bruce

2010-01-01

This paper, delivered at the International Drama in Education Research Institute (IDIERI) conference in Sydney in July 2009, explores the outcomes of a project designed to apply the applied theatre techniques developed for the Acting Against Bullying programme to the specific problem of covert or hidden bullying by adolescent girls. Conducted in a…

Resisting Age Bias in Digital Literacy Research

ERIC Educational Resources Information Center

Bowen, Lauren Marshall

2011-01-01

Through an eighty-one-year-old woman's literacy narrative, I argue that literacy researchers should pay greater attention to elder writers, readers, and learners. Particularly as notions of literacy shift in digital times, the perspective of a lifespan can reveal otherwise hidden complexities of literacy, including the motivational impact of…

Dynamic extreme learning machine and its approximation capability.

PubMed

Zhang, Rui; Lan, Yuan; Huang, Guang-Bin; Xu, Zong-Ben; Soh, Yeng Chai

2013-12-01

Extreme learning machines (ELMs) have been proposed for generalized single-hidden-layer feedforward networks which need not be neuron alike and perform well in both regression and classification applications. The problem of determining the suitable network architectures is recognized to be crucial in the successful application of ELMs. This paper first proposes a dynamic ELM (D-ELM) where the hidden nodes can be recruited or deleted dynamically according to their significance to network performance, so that not only the parameters can be adjusted but also the architecture can be self-adapted simultaneously. Then, this paper proves in theory that such D-ELM using Lebesgue p-integrable hidden activation functions can approximate any Lebesgue p-integrable function on a compact input set. Simulation results obtained over various test problems demonstrate and verify that the proposed D-ELM does a good job reducing the network size while preserving good generalization performance.

Shape shifting: Local landmarks interfere with navigation by, and recognition of, global shape.

PubMed

Buckley, Matthew G; Smith, Alastair D; Haselgrove, Mark

2014-03-01

An influential theory of spatial navigation states that the boundary shape of an environment is preferentially encoded over and above other spatial cues, such that it is impervious to interference from alternative sources of information. We explored this claim with 3 intradimensional-extradimensional shift experiments, designed to examine the interaction of landmark and geometric features of the environment in a virtual navigation task. In Experiments 1 and 2, participants were first required to find a hidden goal using information provided by the shape of the arena or landmarks integrated into the arena boundary (Experiment 1) or within the arena itself (Experiment 2). Participants were then transferred to a different-shaped arena that contained novel landmarks and were again required to find a hidden goal. In both experiments, participants who were navigating on the basis of cues that were from the same dimension that was previously relevant (intradimensional shift) learned to find the goal significantly faster than participants who were navigating on the basis of cues that were from a dimension that was previously irrelevant (extradimensional shift). This suggests that shape information does not hold special status when learning about an environment. Experiment 3 replicated Experiment 2 and also assessed participants' recognition of the global shape of the navigated arenas. Recognition was attenuated when landmarks were relevant to navigation throughout the experiment. The results of these experiments are discussed in terms of associative and non-associative theories of spatial learning.

“Invisible” Conformers of an Antifungal Disulfide Protein Revealed by Constrained Cold and Heat Unfolding, CEST-NMR Experiments, and Molecular Dynamics Calculations

PubMed Central

Fizil, Ádám; Gáspári, Zoltán; Barna, Terézia; Marx, Florentine; Batta, Gyula

2015-01-01

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two- and three-state analysis of thermal unfolding, that the population of hidden states may weight 20–40 % at 298 K in a disulfide-rich protein. In addition, sensitive 15N-CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR “dark matter”. Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction. PMID:25676351

Reputation and Competition in a Hidden Action Model

PubMed Central

Fedele, Alessandro; Tedeschi, Piero

2014-01-01

The economics models of reputation and quality in markets can be classified in three categories. (i) Pure hidden action, where only one type of seller is present who can provide goods of different quality. (ii) Pure hidden information, where sellers of different types have no control over product quality. (iii) Mixed frameworks, which include both hidden action and hidden information. In this paper we develop a pure hidden action model of reputation and Bertrand competition, where consumers and firms interact repeatedly in a market with free entry. The price of the good produced by the firms is contractible, whilst the quality is noncontractible, hence it is promised by the firms when a contract is signed. Consumers infer future quality from all available information, i.e., both from what they know about past quality and from current prices. According to early contributions, competition should make reputation unable to induce the production of high-quality goods. We provide a simple solution to this problem by showing that high quality levels are sustained as an outcome of a stationary symmetric equilibrium. PMID:25329387

Reputation and competition in a hidden action model.

PubMed

Fedele, Alessandro; Tedeschi, Piero

2014-01-01

The economics models of reputation and quality in markets can be classified in three categories. (i) Pure hidden action, where only one type of seller is present who can provide goods of different quality. (ii) Pure hidden information, where sellers of different types have no control over product quality. (iii) Mixed frameworks, which include both hidden action and hidden information. In this paper we develop a pure hidden action model of reputation and Bertrand competition, where consumers and firms interact repeatedly in a market with free entry. The price of the good produced by the firms is contractible, whilst the quality is noncontractible, hence it is promised by the firms when a contract is signed. Consumers infer future quality from all available information, i.e., both from what they know about past quality and from current prices. According to early contributions, competition should make reputation unable to induce the production of high-quality goods. We provide a simple solution to this problem by showing that high quality levels are sustained as an outcome of a stationary symmetric equilibrium.

Inflation, symmetry, and B-modes

DOE PAGES

Hertzberg, Mark P.

2015-04-20

Here, we examine the role of using symmetry and effective field theory in inflationary model building. We describe the standard formulation of starting with an approximate shift symmetry for a scalar field, and then introducing corrections systematically in order to maintain control over the inflationary potential. We find that this leads to models in good agreement with recent data. On the other hand, there are attempts in the literature to deviate from this paradigm by envoking other symmetries and corrections. In particular: in a suite of recent papers, several authors have made the claim that standard Einstein gravity with amore » cosmological constant and a massless scalar carries conformal symmetry. They claim this conformal symmetry is hidden when the action is written in the Einstein frame, and so has not been fully appreciated in the literature. They further claim that such a theory carries another hidden symmetry; a global SO(1,1) symmetry. By deforming around the global SO(1,1) symmetry, they are able to produce a range of inflationary models with asymptotically flat potentials, whose flatness is claimed to be protected by these symmetries. These models tend to give rise to B-modes with small amplitude. Here we explain that standard Einstein gravity does not in fact possess conformal symmetry. Instead these authors are merely introducing a redundancy into the description, not an actual conformal symmetry. Furthermore, we explain that the only real (global) symmetry in these models is not at all hidden, but is completely manifest when expressed in the Einstein frame; it is in fact the shift symmetry of a scalar field. When analyzed systematically as an effective field theory, deformations do not generally produce asymptotically flat potentials and small B-modes as suggested in these recent papers. Instead, deforming around the shift symmetry systematically, tends to produce models of inflation with B-modes of appreciable amplitude. Such simple models typically also produce the observed red spectral index, Gaussian fluctuations, etc. In short: simple models of inflation, organized by expanding around a shift symmetry, are in excellent agreement with recent data.« less

Effects of the GluN2B-NMDA receptor antagonist Ro 25-6981 on two types of behavioral flexibility in rats.

PubMed

Clark, Emma; Antoniak, Kristen; Feniquito, Alyssandra; Dringenberg, Hans C

2017-02-15

Recent evidence has implicated N-methyl-d-aspartate receptors (NMDARs) in several aspects of learning and behavioral flexibility in rodents. Here, we examined the effects of treatment with Ro 25-6981, a selective antagonist of NMDARs containing GluN2B subunits, on two types of behavioral flexibility in rats, spatial reversal learning and set-shifting (spatial vs. motor strategy). To examine spatial reversal learning, rats were trained to swim to a hidden platform in a water maze over four days. On the following day, the platform was moved to a new location in the maze. Administration of Ro 25-6981 (10mg/kg) selectively impaired the early phase of reversal learning, but all rats learned to navigate to the new platform location over 12 trials. To examine set-shifting, independent groups of rats were trained to either swim to a fixed location (spatial strategy) or use a motor response (e.g., "turn left"; motor strategy) to find a hidden escape platform in a cross-shaped water maze apparatus; after task acquisition, rats were trained on the second, novel strategy (set-shift) following treatment with either Ro 25-6981 (10mg/kg) or saline. Administration of Ro 25-6981 had no effect on the ability of rats to perform the set-shift and use the new strategy to locate the escape platform. These results suggest that, in rats, spatial reversal learning, but not set-shifting, is sensitive to Ro-25-6981 treatment. Thus, NMDARs-GluN2B signaling may play a selective role in some forms of behavioral plasticity, particularly for situations involving the updating of information in the spatial domain. Copyright © 2016 Elsevier B.V. All rights reserved.

Highly Productive Tools For Turning And Milling

NASA Astrophysics Data System (ADS)

Vasilko, Karol

2015-12-01

Beside cutting speed, shift is another important parameter of machining. Its considerable influence is shown mainly in the workpiece machined surface microgeometry. In practice, mainly its combination with the radius of cutting tool tip rounding is used. Options to further increase machining productivity and machined surface quality are hidden in this approach. The paper presents variations of the design of productive cutting tools for lathe work and milling on the base of the use of the laws of the relationship among the highest reached uneveness of machined surface, tool tip radius and shift.

Teaching Evidence-Based Psychiatry: Integrating and Aligning the Formal and Hidden Curricula

ERIC Educational Resources Information Center

Agrawal, Sacha; Szatmari, Peter; Hanson, Mark

2008-01-01

Objective: The authors argue that adopting evidence-based psychiatry will require a paradigm shift in the training of psychiatry residents, and offer some suggestions for how this transformation might be achieved. Methods: The authors review the growing literature that addresses how best to teach evidence-based medicine and highlight several…

Symbolic Insight and Inhibitory Control: Two Problems Facing Young Children on Symbolic Retrieval Tasks

ERIC Educational Resources Information Center

Kuhlmeier, Valerie

2005-01-01

Many recent studies have explored young children's ability to use information from physical representations of space to guide search within the real world. In one commonly used procedure, children are asked to find a hidden toy in a room after observing a smaller toy being hidden in the analogous location in a scale model of the room.…

Passing from Mesoscopy to Macroscopy. The Mesoscopic Parameter \\bar k

NASA Astrophysics Data System (ADS)

Maslov, V. P.

2018-01-01

In previous papers of the author it was shown that, depending on the hidden parameter, purely quantum problems behave like classical ones. In the present paper, it is shown that the Bose-Einstein and the Fermi-Dirac distributions, which until now were regarded as dealing with quantum particles, describe, for the appropriate values of the hidden parameter, the macroscopic thermodynamics of classical molecules.

Harnessing the Hidden Curriculum: A Four-Step Approach to Developing and Reinforcing Reflective Competencies in Medical Clinical Clerkship

ERIC Educational Resources Information Center

Holmes, Cheryl L.; Harris, Ilene B.; Schwartz, Alan J.; Regehr, Glenn

2015-01-01

Changing the culture of medicine through the education of medical students has been proposed as a solution to the intractable problems of our profession. Yet few have explored the issues associated with making students partners in this change. There is a powerful hidden curriculum that perpetuates not only desired attitudes and behaviors but also…

The use of neutrons for the detection of explosives in Civil Security Applications

NASA Astrophysics Data System (ADS)

Pesente, S.; Fabris, D.; Lunardon, M.; Moretto, S.; Nebbia, G.; Viesti, G.

2007-02-01

The search for hidden explosives has been simulated in laboratory conditions by using our Tagged Neutron Inspection System (TNIS). Applications of the TNIS concept to Civil Security problems are discussed in the light of our projects for cargo container inspections. Moreover, neutron attenuation and scattering can be used to search in real time for large quantity of explosive hidden in vehicles.

Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression

PubMed Central

Liu, Yu-Ying; Li, Shuang; Li, Fuxin; Song, Le; Rehg, James M.

2016-01-01

The Continuous-Time Hidden Markov Model (CT-HMM) is an attractive approach to modeling disease progression due to its ability to describe noisy observations arriving irregularly in time. However, the lack of an efficient parameter learning algorithm for CT-HMM restricts its use to very small models or requires unrealistic constraints on the state transitions. In this paper, we present the first complete characterization of efficient EM-based learning methods for CT-HMM models. We demonstrate that the learning problem consists of two challenges: the estimation of posterior state probabilities and the computation of end-state conditioned statistics. We solve the first challenge by reformulating the estimation problem in terms of an equivalent discrete time-inhomogeneous hidden Markov model. The second challenge is addressed by adapting three approaches from the continuous time Markov chain literature to the CT-HMM domain. We demonstrate the use of CT-HMMs with more than 100 states to visualize and predict disease progression using a glaucoma dataset and an Alzheimer’s disease dataset. PMID:27019571

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Bell's theorem and the problem of decidability between the views of Einstein and Bohr.

PubMed

Hess, K; Philipp, W

2001-12-04

Einstein, Podolsky, and Rosen (EPR) have designed a gedanken experiment that suggested a theory that was more complete than quantum mechanics. The EPR design was later realized in various forms, with experimental results close to the quantum mechanical prediction. The experimental results by themselves have no bearing on the EPR claim that quantum mechanics must be incomplete nor on the existence of hidden parameters. However, the well known inequalities of Bell are based on the assumption that local hidden parameters exist and, when combined with conflicting experimental results, do appear to prove that local hidden parameters cannot exist. This fact leaves only instantaneous actions at a distance (called "spooky" by Einstein) to explain the experiments. The Bell inequalities are based on a mathematical model of the EPR experiments. They have no experimental confirmation, because they contradict the results of all EPR experiments. In addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions; for instance, he assumes that the hidden parameters are governed by a single probability measure independent of the analyzer settings. We argue that the mathematical model of Bell excludes a large set of local hidden variables and a large variety of probability densities. Our set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does permit derivation of the quantum result and is consistent with all known experiments.

Phenomenology of pure-gauge hidden valleys at hadron colliders

NASA Astrophysics Data System (ADS)

Juknevich, Jose E.

Expectations for new physics at the LHC have been greatly influenced by the Hierarchy problem of electroweak symmetry breaking. However, there are reasons to believe that the LHC may still discover new physics, but not directly related to the resolution of the Hierarchy problem. To ensure that such a physics does not go undiscovered requires precise understanding of how new phenomena will reveal themselves in the current and future generation of particle-physics experiments. Given this fact it seems sensible to explore other approaches to this problem; we study three alternatives here. In this thesis I argue for the plausibility that the standard model is coupled, through new massive charged or colored particles, to a hidden sector whose low energy dynamics is controlled by a pure Yang-Mills theory, with no light matter. Such a sector would have numerous metastable "hidden glueballs" built from the hidden gluons. These states would decay to particles of the standard model. I consider the phenomenology of this scenario, and find formulas for the lifetimes and branching ratios of the most important of these states. The dominant decays are to two standard model gauge bosons or to fermion-antifermion pairs, or by radiative decays with photon or Higgs emission, leading to jet- and photon-rich signals, and some occasional leptons. The presence of effective operators of different mass dimensions, often competing with each other, together with a great diversity of states, leads to a great variability in the lifetimes and decay modes of the hidden glueballs. I find that most of the operators considered in this work are not heavily constrained by precision electroweak physics, therefore leaving plenty of room in the parameter space to be explored by the future experiments at the LHC. Finally, I discuss several issues on the phenomenology of the new massive particles as well as an outlook for experimental searches.

Synchronization behaviors of coupled systems composed of hidden attractors

NASA Astrophysics Data System (ADS)

Zhang, Ge; Wu, Fuqiang; Wang, Chunni; Ma, Jun

2017-10-01

Based on a class of chaotic system composed of hidden attractors, in which the equilibrium points are described by a circular function, complete synchronization between two identical systems, pattern formation and synchronization of network is investigated, respectively. A statistical factor of synchronization is defined and calculated by using the mean field theory, the dependence of synchronization on bifurcation parameters discussed in numerical way. By setting a chain network, which local kinetic is described by hidden attractors, synchronization approach is investigated. It is found that the synchronization and pattern formation are dependent on the coupling intensity and also the selection of coupling variables. In the end, open problems are proposed for readers’ extensive guidance and investigation.

StegoWall: blind statistical detection of hidden data

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav V.; Herrigel, Alexander; Rytsar, Yuri B.; Pun, Thierry

2002-04-01

Novel functional possibilities, provided by recent data hiding technologies, carry out the danger of uncontrolled (unauthorized) and unlimited information exchange that might be used by people with unfriendly interests. The multimedia industry as well as the research community recognize the urgent necessity for network security and copyright protection, or rather the lack of adequate law for digital multimedia protection. This paper advocates the need for detecting hidden data in digital and analog media as well as in electronic transmissions, and for attempting to identify the underlying hidden data. Solving this problem calls for the development of an architecture for blind stochastic hidden data detection in order to prevent unauthorized data exchange. The proposed architecture is called StegoWall; its key aspects are the solid investigation, the deep understanding, and the prediction of possible tendencies in the development of advanced data hiding technologies. The basic idea of our complex approach is to exploit all information about hidden data statistics to perform its detection based on a stochastic framework. The StegoWall system will be used for four main applications: robust watermarking, secret communications, integrity control and tamper proofing, and internet/network security.

ARPA surveillance technology for detection of targets hidden in foliage

NASA Astrophysics Data System (ADS)

Hoff, Lawrence E.; Stotts, Larry B.

1994-02-01

The processing of large quantities of synthetic aperture radar data in real time is a complex problem. Even the image formation process taxes today's most advanced computers. The use of complex algorithms with multiple channels adds another dimension to the computational problem. Advanced Research Projects Agency (ARPA) is currently planning on using the Paragon parallel processor for this task. The Paragon is small enough to allow its use in a sensor aircraft. Candidate algorithms will be implemented on the Paragon for evaluation for real time processing. In this paper ARPA technology developments for detecting targets hidden in foliage are reviewed and examples of signal processing techniques on field collected data are presented.

Hidden Hazards of Radon: Scanning the Country for Problem Locations.

ERIC Educational Resources Information Center

Gundersen, Linda C. S.

1992-01-01

Describes the geology of the radon problem in the United States and suggests how homeowners can cope with the radio active gas. Vignettes illustrate how and where radon is produced beneath the earth's surface, testing sites and procedures for radon in houses, and locations for potential radon problems across the United States. (MCO)

Contraband: the hidden risk.

PubMed

Pelletier, L R; Poster, E C; Kay, K

1990-01-01

In a 28-month retrospective study of contraband possession in an inpatient psychiatric setting, 54 incidents of contraband confiscation were identified. Incidents were analyzed according to day and shift of occurrence, nature of contraband, patient diagnoses and characteristics, and patient outcome of contraband possession. Study findings stress the importance of clearly stated contraband policies and procedures, especially in light of patient and staff rights and responsibilities.

A Regularized Linear Dynamical System Framework for Multivariate Time Series Analysis.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-01-01

Linear Dynamical System (LDS) is an elegant mathematical framework for modeling and learning Multivariate Time Series (MTS). However, in general, it is difficult to set the dimension of an LDS's hidden state space. A small number of hidden states may not be able to model the complexities of a MTS, while a large number of hidden states can lead to overfitting. In this paper, we study learning methods that impose various regularization penalties on the transition matrix of the LDS model and propose a regularized LDS learning framework (rLDS) which aims to (1) automatically shut down LDSs' spurious and unnecessary dimensions, and consequently, address the problem of choosing the optimal number of hidden states; (2) prevent the overfitting problem given a small amount of MTS data; and (3) support accurate MTS forecasting. To learn the regularized LDS from data we incorporate a second order cone program and a generalized gradient descent method into the Maximum a Posteriori framework and use Expectation Maximization to obtain a low-rank transition matrix of the LDS model. We propose two priors for modeling the matrix which lead to two instances of our rLDS. We show that our rLDS is able to recover well the intrinsic dimensionality of the time series dynamics and it improves the predictive performance when compared to baselines on both synthetic and real-world MTS datasets.

Automatic Hidden-Web Table Interpretation by Sibling Page Comparison

NASA Astrophysics Data System (ADS)

Tao, Cui; Embley, David W.

The longstanding problem of automatic table interpretation still illudes us. Its solution would not only be an aid to table processing applications such as large volume table conversion, but would also be an aid in solving related problems such as information extraction and semi-structured data management. In this paper, we offer a conceptual modeling solution for the common special case in which so-called sibling pages are available. The sibling pages we consider are pages on the hidden web, commonly generated from underlying databases. We compare them to identify and connect nonvarying components (category labels) and varying components (data values). We tested our solution using more than 2,000 tables in source pages from three different domains—car advertisements, molecular biology, and geopolitical information. Experimental results show that the system can successfully identify sibling tables, generate structure patterns, interpret tables using the generated patterns, and automatically adjust the structure patterns, if necessary, as it processes a sequence of hidden-web pages. For these activities, the system was able to achieve an overall F-measure of 94.5%.

"Invisible" conformers of an antifungal disulfide protein revealed by constrained cold and heat unfolding, CEST-NMR experiments, and molecular dynamics calculations.

PubMed

Fizil, Ádám; Gáspári, Zoltán; Barna, Terézia; Marx, Florentine; Batta, Gyula

2015-03-23

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two- and three-state analysis of thermal unfolding, that the population of hidden states may weight 20-40 % at 298 K in a disulfide-rich protein. In addition, sensitive (15) N-CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR "dark matter". Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction. © 2015 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Emergence of higher order rotational symmetry in the hidden order phase of URu 2Si 2

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

Kanchanavatee, N.; Janoschek, M.; Huang, K.

2016-09-30

Electrical resistivity measurements were performed in this paper as functions of temperature, magnetic field, and angle θ between the magnetic field and the c-axis of a URu 2Si 2 single crystal. The resistivity exhibits a two-fold oscillation as a function of θ at high temperatures, which undergoes a 180°-phase shift (sign change) with decreasing temperature at around 35 K. The hidden order transition is manifested as a minimum in the magnetoresistance and amplitude of the two-fold oscillation. Interestingly, the resistivity also showed four-fold, six-fold, and eight-fold symmetries at the hidden order transition. These higher order symmetries were also detected atmore » low temperatures, which could be a sign of the formation of another pseudogap phase above the superconducting transition, consistent with recent evidence for a pseudogap from point-contact spectroscopy measurements and NMR. Measurements of the magnetisation of single crystalline URu 2Si 2 with the magnetic field applied parallel and perpendicular to the crystallographic c-axis revealed regions with linear temperature dependencies between the hidden order transition temperature and about 25 K. Finally, this T-linear behaviour of the magnetisation may be associated with the formation of a precursor phase or ‘pseudogap’ in the density of states in the vicinity of 30–35 K.« less

Optimal matching for prostate brachytherapy seed localization with dimension reduction.

PubMed

Lee, Junghoon; Labat, Christian; Jain, Ameet K; Song, Danny Y; Burdette, Everette C; Fichtinger, Gabor; Prince, Jerry L

2009-01-01

In prostate brachytherapy, x-ray fluoroscopy has been used for intra-operative dosimetry to provide qualitative assessment of implant quality. More recent developments have made possible 3D localization of the implanted radioactive seeds. This is usually modeled as an assignment problem and solved by resolving the correspondence of seeds. It is, however, NP-hard, and the problem is even harder in practice due to the significant number of hidden seeds. In this paper, we propose an algorithm that can find an optimal solution from multiple projection images with hidden seeds. It solves an equivalent problem with reduced dimensional complexity, thus allowing us to find an optimal solution in polynomial time. Simulation results show the robustness of the algorithm. It was validated on 5 phantom and 18 patient datasets, successfully localizing the seeds with detection rate of > or = 97.6% and reconstruction error of < or = 1.2 mm. This is considered to be clinically excellent performance.

Object permanence in domestic dogs (Canis lupus familiaris) and gray wolves (Canis lupus).

PubMed

Fiset, Sylvain; Plourde, Vickie

2013-05-01

Recent evidence suggests that phylogenetic constraints exerted on dogs by the process of domestication have altered the ability of dogs to represent the physical world and the displacement of objects. In this study, invisible (Experiment 1) and visible (Experiment 2) displacement problems were administered to determine whether domestic dogs' and gray wolves' cognitive capacities to infer the position of a hidden object differ. The results revealed that adult dogs and wolves performed similarly in searching for disappearing objects: Both species succeeded the visible displacement tasks but failed the invisible displacement problems. We conclude that physical cognition for finding hidden objects in domestic dogs and gray wolves is alike and unrelated to the process of domestication.

Quasifixed points from scalar sequestering and the little hierarchy problem in supersymmetry

NASA Astrophysics Data System (ADS)

Martin, Stephen P.

2018-02-01

In supersymmetric models with scalar sequestering, superconformal strong dynamics in the hidden sector suppresses the low-energy couplings of mass dimension 2, compared to the squares of the dimension-1 parameters. Taking into account restrictions on the anomalous dimensions in superconformal theories, I point out that the interplay between the hidden and visible sector renormalizations gives rise to quasifixed point running for the supersymmetric Standard Model squared mass parameters, rather than driving them to 0. The extent to which this dynamics can ameliorate the little hierarchy problem in supersymmetry is studied. Models of this type in which the gaugino masses do not unify are arguably more natural, and are certainly more likely to be accessible, eventually, to the Large Hadron Collider.

Parametric inference for biological sequence analysis.

PubMed

Pachter, Lior; Sturmfels, Bernd

2004-11-16

One of the major successes in computational biology has been the unification, by using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied to these problems include hidden Markov models for annotation, tree models for phylogenetics, and pair hidden Markov models for alignment. A single algorithm, the sum-product algorithm, solves many of the inference problems that are associated with different statistical models. This article introduces the polytope propagation algorithm for computing the Newton polytope of an observation from a graphical model. This algorithm is a geometric version of the sum-product algorithm and is used to analyze the parametric behavior of maximum a posteriori inference calculations for graphical models.

XM25 Schedule Delays, Cost Increases, and Performance Problems Continue, and Procurement Quantity Not Justified (REDACTED)

DTIC Science & Technology

2016-08-29

ammunition. (FOUO) Figure 1. XM25 Weapon System and Air Bursting Ammunition 3 Hidden refers to the enemy seeking cover in trenches; behind walls, rocks ...system that fires 25mm high-explosive, air- bursting ammunition to allow soldiers to fire at hidden enemy targets. Findings Army officials could...XM25 Weapon System The XM25 is a semiautomatic, shoulder-fired weapon system that fires 25mm high-explosive, air- bursting ammunition to allow soldiers

Solving the "Hidden Line" Problem

NASA Technical Reports Server (NTRS)

1984-01-01

David Hedgley Jr., a mathematician at Dryden Flight Research Center, has developed an accurate computer program that considers whether a line in a graphic model of a three dimensional object should or should not be visible. The Hidden Line Computer Code, program automatically removes superfluous lines and permits the computer to display an object from specific viewpoints, just as the human eye would see it. Users include Rowland Institute for Science in Cambridge, MA, several departments of Lockheed Georgia Co., and Nebraska Public Power District (NPPD).

Extracting hidden messages in steganographic images

DOE PAGES

Quach, Tu-Thach

2014-07-17

The eventual goal of steganalytic forensic is to extract the hidden messages embedded in steganographic images. A promising technique that addresses this problem partially is steganographic payload location, an approach to reveal the message bits, but not their logical order. It works by finding modified pixels, or residuals, as an artifact of the embedding process. This technique is successful against simple least-significant bit steganography and group-parity steganography. The actual messages, however, remain hidden as no logical order can be inferred from the located payload. This paper establishes an important result addressing this shortcoming: we show that the expected mean residualsmore » contain enough information to logically order the located payload provided that the size of the payload in each stego image is not fixed. The located payload can be ordered as prescribed by the mean residuals to obtain the hidden messages without knowledge of the embedding key, exposing the vulnerability of these embedding algorithms. We provide experimental results to support our analysis.« less

The Economy Goes to College: The Hidden Promise of Higher Education in the Post-Industrial Service Economy

ERIC Educational Resources Information Center

Carnevale, Anthony P.; Rose, Stephen J.

2015-01-01

This report explores the crucial transformation of the United States from an industrial to a post-industrial economy, with a particular focus on the shifting skill levels and incomes of American workers. It shows the increasing value of postsecondary education in today's economy and examines how workers have fared as the nation's focus has shifted…

Failure to cope: the hidden curriculum of emergency department wait times and the implications for clinical training.

PubMed

Webster, Fiona; Rice, Kathleen; Dainty, Katie N; Zwarenstein, Merrick; Durant, Steve; Kuper, Ayelet

2015-01-01

The study explored optimal intraprofessional collaboration between physicians in the emergency department (ED) and those from general internal medicine (GIM). Prior to the study, a policy was initiated that mandated reductions in ED wait times. The researchers examined the impact of these changes on clinical practice and trainee education. In 2010-2011, an ethnographic study was undertaken to observe consults between GIM and ED at an urban teaching hospital in Ontario, Canada. Additional ad hoc interviews were conducted with residents, nurses, and faculty from both departments as well as formal one-on-one interviews with 12 physicians. Data were coded and analyzed using concepts of institutional ethnography. Participants perceived that efficiency was more important than education and was in fact the new definition of "good" patient care. The informal label "failure to cope" to describe high-needs patients suggested that in many instances, patients were experienced as a barrier to optimal efficiency. This resulted in tension during consults as well as reduced opportunities for education. The authors suggest that the emphasis on wait times resulted in more importance being placed on "getting the patient out" of the ED than on providing safe, compassionate, person-centered medical care. Resource constraints were hidden within a discourse that shifted the problem of overcrowding in the ED to patients with complex chronic conditions. The term "failure to cope" became activated when overworked physicians tried to avoid assuming care for high-needs patients, masking institutionally produced stress and possibly altering the way patients are perceived.

Automation and adaptation: Nurses' problem-solving behavior following the implementation of bar coded medication administration technology.

PubMed

Holden, Richard J; Rivera-Rodriguez, A Joy; Faye, Héléne; Scanlon, Matthew C; Karsh, Ben-Tzion

2013-08-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses' operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA's impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians' work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign.

Automation and adaptation: Nurses’ problem-solving behavior following the implementation of bar coded medication administration technology

PubMed Central

Holden, Richard J.; Rivera-Rodriguez, A. Joy; Faye, Héléne; Scanlon, Matthew C.; Karsh, Ben-Tzion

2012-01-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses’ operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA’s impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians’ work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign. PMID:24443642

Using Educational Data Mining Methods to Assess Field-Dependent and Field-Independent Learners' Complex Problem Solving

ERIC Educational Resources Information Center

Angeli, Charoula; Valanides, Nicos

2013-01-01

The present study investigated the problem-solving performance of 101 university students and their interactions with a computer modeling tool in order to solve a complex problem. Based on their performance on the hidden figures test, students were assigned to three groups of field-dependent (FD), field-mixed (FM), and field-independent (FI)…

Simultaneous escaping of explicit and hidden free energy barriers: application of the orthogonal space random walk strategy in generalized ensemble based conformational sampling.

PubMed

Zheng, Lianqing; Chen, Mengen; Yang, Wei

2009-06-21

To overcome the pseudoergodicity problem, conformational sampling can be accelerated via generalized ensemble methods, e.g., through the realization of random walks along prechosen collective variables, such as spatial order parameters, energy scaling parameters, or even system temperatures or pressures, etc. As usually observed, in generalized ensemble simulations, hidden barriers are likely to exist in the space perpendicular to the collective variable direction and these residual free energy barriers could greatly abolish the sampling efficiency. This sampling issue is particularly severe when the collective variable is defined in a low-dimension subset of the target system; then the "Hamiltonian lagging" problem, which reveals the fact that necessary structural relaxation falls behind the move of the collective variable, may be likely to occur. To overcome this problem in equilibrium conformational sampling, we adopted the orthogonal space random walk (OSRW) strategy, which was originally developed in the context of free energy simulation [L. Zheng, M. Chen, and W. Yang, Proc. Natl. Acad. Sci. U.S.A. 105, 20227 (2008)]. Thereby, generalized ensemble simulations can simultaneously escape both the explicit barriers along the collective variable direction and the hidden barriers that are strongly coupled with the collective variable move. As demonstrated in our model studies, the present OSRW based generalized ensemble treatments show improved sampling capability over the corresponding classical generalized ensemble treatments.

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

PubMed

Ranganayaki, V; Deepa, S N

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature.

May Stakeholders be Involved in Design Without Informed Consent? The Case of Hidden Design.

PubMed

Pols, A J K

2017-06-01

Stakeholder involvement in design is desirable from both a practical and an ethical point of view. It is difficult to do well, however, and some problems recur again and again, both of a practical nature, e.g. stakeholders acting strategically rather than openly, and of an ethical nature, e.g. power imbalances unduly affecting the outcome of the process. Hidden Design has been proposed as a method to deal with the practical problems of stakeholder involvement. It aims to do so by taking the observation of stakeholder actions, rather than the outcomes of a deliberative process, as its input. Furthermore, it hides from stakeholders the fact that a design process is taking place so that they will not behave differently than they otherwise would. Both aspects of Hidden Design have raised ethical worries. In this paper I make an ethical analysis of what it means for a design process to leave participants uninformed or deceived rather than acquiring their informed consent beforehand, and to use observation of actions rather than deliberation as input for design, using Hidden Design as a case study. This analysis is based on two sets of normative guidelines: the ethical guidelines for psychological research involving deception or uninformed participants from two professional psychological organisations, and Habermasian norms for a fair and just (deliberative) process. It supports the conclusion that stakeholder involvement in design organised in this way can be ethically acceptable, though under a number of conditions and constraints.

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems

PubMed Central

Ranganayaki, V.; Deepa, S. N.

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature. PMID:27034973

A Game of Hide and Seek: Expectations of Clumpy Resources Influence Hiding and Searching Patterns

PubMed Central

Wilke, Andreas; Minich, Steven; Panis, Megane; Langen, Tom A.; Skufca, Joseph D.; Todd, Peter M.

2015-01-01

Resources are often distributed in clumps or patches in space, unless an agent is trying to protect them from discovery and theft using a dispersed distribution. We uncover human expectations of such spatial resource patterns in collaborative and competitive settings via a sequential multi-person game in which participants hid resources for the next participant to seek. When collaborating, resources were mostly hidden in clumpy distributions, but when competing, resources were hidden in more dispersed (random or hyperdispersed) patterns to increase the searching difficulty for the other player. More dispersed resource distributions came at the cost of higher overall hiding (as well as searching) times, decreased payoffs, and an increased difficulty when the hider had to recall earlier hiding locations at the end of the experiment. Participants’ search strategies were also affected by their underlying expectations, using a win-stay lose-shift strategy appropriate for clumpy resources when searching for collaboratively-hidden items, but moving equally far after finding or not finding an item in competitive settings, as appropriate for dispersed resources. Thus participants showed expectations for clumpy versus dispersed spatial resources that matched the distributions commonly found in collaborative versus competitive foraging settings. PMID:26154661

Reservoir computing on the hypersphere

NASA Astrophysics Data System (ADS)

Andrecut, M.

Reservoir Computing (RC) refers to a Recurrent Neural Network (RNNs) framework, frequently used for sequence learning and time series prediction. The RC system consists of a random fixed-weight RNN (the input-hidden reservoir layer) and a classifier (the hidden-output readout layer). Here, we focus on the sequence learning problem, and we explore a different approach to RC. More specifically, we remove the nonlinear neural activation function, and we consider an orthogonal reservoir acting on normalized states on the unit hypersphere. Surprisingly, our numerical results show that the system’s memory capacity exceeds the dimensionality of the reservoir, which is the upper bound for the typical RC approach based on Echo State Networks (ESNs). We also show how the proposed system can be applied to symmetric cryptography problems, and we include a numerical implementation.

Detection of contraband using microwave radiation

DOEpatents

Toth, Richard P.; Loubriel, Guillermo M.; Bacon, Larry D.; Watson, Robert D.

2002-01-01

The present invention relates to a method and system for using microwave radiation to detect contraband hidden inside of a non-metallic container, such as a pneumatic vehicle tire. The method relies on the attenuation, retardation, time delay, or phase shift of microwave radiation as it passes through the container plus the contraband. The method is non-invasive, non-destructive, low power, and does not require physical contact with the container.

Taking the Shot

ERIC Educational Resources Information Center

Grayson, Jennifer

2011-01-01

In today's high-pressure IT world, almost every opportunity comes hidden inside a problem. And when it comes to "greening" a data center, the problems can be especially daunting, given institutional inertia, budgetary concerns, politics, and more. For CIOs looking to notch up a win with a leaner, greener data center, the key to success often lies…

The Hidden Health Toll: A Cost of Work to the American Woman

ERIC Educational Resources Information Center

Stellman, Jeanne M.

1977-01-01

Large numbers of women work at jobs that present serious health hazards, although most people associate workplace hazards with traditionally "male" jobs. Physical dangers, stress, and fatigue lead to manifold health problems among working women. These problems should be investigated and conditions improved for workers of both sexes. (Author/GC)

Reverse engineering a social agent-based hidden markov model--visage.

PubMed

Chen, Hung-Ching Justin; Goldberg, Mark; Magdon-Ismail, Malik; Wallace, William A

2008-12-01

We present a machine learning approach to discover the agent dynamics that drives the evolution of the social groups in a community. We set up the problem by introducing an agent-based hidden Markov model for the agent dynamics: an agent's actions are determined by micro-laws. Nonetheless, We learn the agent dynamics from the observed communications without knowing state transitions. Our approach is to identify the appropriate micro-laws corresponding to an identification of the appropriate parameters in the model. The model identification problem is then formulated as a mixed optimization problem. To solve the problem, we develop a multistage learning process for determining the group structure, the group evolution, and the micro-laws of a community based on the observed set of communications among actors, without knowing the semantic contents. Finally, to test the quality of our approximations and the feasibility of the approach, we present the results of extensive experiments on synthetic data as well as the results on real communities, such as Enron email and Movie newsgroups. Insight into agent dynamics helps us understand the driving forces behind social evolution.

Bounds on the number of hidden neurons in three-layer binary neural networks.

PubMed

Zhang, Zhaozhi; Ma, Xiaomin; Yang, Yixian

2003-09-01

This paper investigates an important problem concerning the complexity of three-layer binary neural networks (BNNs) with one hidden layer. The neuron in the studied BNNs employs a hard limiter activation function with only integer weights and an integer threshold. The studies are focused on implementations of arbitrary Boolean functions which map from [0, 1]n into [0, 1]. A deterministic algorithm called set covering algorithm (SCA) is proposed for the construction of a three-layer BNN to implement an arbitrary Boolean function. The SCA is based on a unit sphere covering (USC) of the Hamming space (HS) which is chosen in advance. It is proved that for the implementation of an arbitrary Boolean function of n-variables (n > or = 3) by using SCA, [3L/2] hidden neurons are necessary and sufficient, where L is the number of unit spheres contained in the chosen USC of the n-dimensional HS. It is shown that by using SCA, the number of hidden neurons required is much less than that by using a two-parallel hyperplane method. In order to indicate the potential ability of three-layer BNNs, a lower bound on the required number of hidden neurons which is derived by using the method of estimating the Vapnik-Chervonenkis (VC) dimension is also given.

Analysing the hidden curriculum: use of a cultural web

PubMed Central

Mossop, Liz; Dennick, Reg; Hammond, Richard; Robbé, Iain

2013-01-01

CONTEXT Major influences on learning about medical professionalism come from the hidden curriculum. These influences can contribute positively or negatively towards the professional enculturation of clinical students. The fact that there is no validated method for identifying the components of the hidden curriculum poses problems for educators considering professionalism. The aim of this study was to analyse whether a cultural web, adapted from a business context, might assist in the identification of elements of the hidden curriculum at a UK veterinary school. METHODS A qualitative approach was used. Seven focus groups consisting of three staff groups and four student groups were organised. Questioning was framed using the cultural web, which is a model used by business owners to assess their environment and consider how it affects their employees and customers. The focus group discussions were recorded, transcribed and analysed thematically using a combination of a priori and emergent themes. RESULTS The cultural web identified elements of the hidden curriculum for both students and staff. These included: core assumptions; routines; rituals; control systems; organisational factors; power structures, and symbols. Discussions occurred about how and where these issues may affect students’ professional identity development. CONCLUSIONS The cultural web framework functioned well to help participants identify elements of the hidden curriculum. These aspects aligned broadly with previously described factors such as role models and institutional slang. The influence of these issues on a student’s development of a professional identity requires discussion amongst faculty staff, and could be used to develop learning opportunities for students. The framework is promising for the analysis of the hidden curriculum and could be developed as an instrument for implementation in other clinical teaching environments. PMID:23323652

Diagnosis and Management of Hidden Caries in a Primary Molar Tooth.

PubMed

Gera, Arwa; Zilberman, Uri

2017-01-01

Hidden caries is a dentinal lesion beneath the dentinoenamel junction, visible on radiographs. A single report described this lesion in primary dentition. This case report describes a case of hidden caries in a mandibular second primary molar, misdiagnosed as malignant swelling. A 3-year-old white girl was referred to the Department of Pediatric Dentistry with a chief complaint of pain and extraoral swelling on the right side of the mandible for the last 3 months. She was earlier referred to the surgical department for biopsy of the lesion. Radiographic and computed tomography scan examination showed a periapical lesion with buccal plate resorption and radiolucency beneath the enamel on the mesial part of tooth 85. The tooth was extracted, and follow-up of 2 years showed normal development of tooth 45. The main problem is early detection and treatment, since the outer surface of enamel may appear intact on tactile examination. Gera A, Zilberman U. Diagnosis and Management of Hidden Caries in a Primary Molar Tooth. Int J Clin Pediatr Dent 2017;10(1):99-102.

Mining Bug Databases for Unidentified Software Vulnerabilities

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

Dumidu Wijayasekara; Milos Manic; Jason Wright

2012-06-01

Identifying software vulnerabilities is becoming more important as critical and sensitive systems increasingly rely on complex software systems. It has been suggested in previous work that some bugs are only identified as vulnerabilities long after the bug has been made public. These vulnerabilities are known as hidden impact vulnerabilities. This paper discusses the feasibility and necessity to mine common publicly available bug databases for vulnerabilities that are yet to be identified. We present bug database analysis of two well known and frequently used software packages, namely Linux kernel and MySQL. It is shown that for both Linux and MySQL, amore » significant portion of vulnerabilities that were discovered for the time period from January 2006 to April 2011 were hidden impact vulnerabilities. It is also shown that the percentage of hidden impact vulnerabilities has increased in the last two years, for both software packages. We then propose an improved hidden impact vulnerability identification methodology based on text mining bug databases, and conclude by discussing a few potential problems faced by such a classifier.« less

Experimental and Computational Studies on the Scattering of an Edge-Guided Wave by a Hidden Crack on a Racecourse Shaped Hole.

PubMed

Vien, Benjamin Steven; Rose, Louis Raymond Francis; Chiu, Wing Kong

2017-07-01

Reliable and quantitative non-destructive evaluation for small fatigue cracks, in particular those in hard-to-inspect locations, is a challenging problem. Guided waves are advantageous for structural health monitoring due to their slow geometrical decay of amplitude with propagating distance, which is ideal for rapid wide-area inspection. This paper presents a 3D laser vibrometry experimental and finite element analysis of the interaction between an edge-guided wave and a small through-thickness hidden edge crack on a racecourse shaped hole that occurs, in practice, as a fuel vent hole. A piezoelectric transducer is bonded on the straight edge of the hole to generate the incident wave. The excitation signal consists of a 5.5 cycle Hann-windowed tone burst of centre frequency 220 kHz, which is below the cut-off frequency for the first order Lamb wave modes (SH1). Two-dimensional fast Fourier transformation (2D FFT) is applied to the incident and scattered wave field along radial lines emanating from the crack mouth, so as to identify the wave modes and determine their angular variation and amplitude. It is shown experimentally and computationally that mid-plane symmetric edge waves can travel around the hole's edge to detect a hidden crack. Furthermore, the scattered wave field due to a small crack length, a , (compared to the wavelength λ of the incident wave) is shown to be equivalent to a point source consisting of a particular combination of body-force doublets. It is found that the amplitude of the scattered field increases quadratically as a function of a/λ , whereas the scattered wave pattern is independent of crack length for small cracks a < λ . This study of the forward scattering problem from a known crack size provides a useful guide for the inverse problem of hidden crack detection and sizing.

Natural hidden autoantibodies to tissue transglutaminase cross-react with fibrinogen.

PubMed

Zöller-Utz, Ingrid M; Esslinger, Birgit; Schulze-Krebs, Anja; Dieterich, Walburga

2010-03-01

Patients with celiac disease display autoantibodies against tissue transglutaminase (TG2), and the high sensitivity and specificity of these autoantibodies render them a reliable tool for diagnosis. However, we found that denatured sera from healthy persons also showed reactivity against TG2. To further examine the specificity of this phenomenon, sera of healthy individuals and celiac patients were denatured by heat or pH shift. Denatured sera of all individuals showed autoantibodies against TG2 in ELISA that could be specifically inhibited by TG2, but the biological role of these autoantibodies remains unknown. The alpha fibrinogen precursor could be isolated as serum protein that reacts with TG2 antibodies and treated sera reacted with fibrinogen in Western blotting. Cross-reactivity of TG2 antibodies with fibrinogen and vice versa was observed. We hypothesise that denaturation of sera reveals hidden autoantibodies against TG2, which might be normally masked by fibrinogen.

On the Role of Situational Stressors in the Disruption of Global Neural Network Stability during Problem Solving.

PubMed

Liu, Mengting; Amey, Rachel C; Forbes, Chad E

2017-12-01

When individuals are placed in stressful situations, they are likely to exhibit deficits in cognitive capacity over and above situational demands. Despite this, individuals may still persevere and ultimately succeed in these situations. Little is known, however, about neural network properties that instantiate success or failure in both neutral and stressful situations, particularly with respect to regions integral for problem-solving processes that are necessary for optimal performance on more complex tasks. In this study, we outline how hidden Markov modeling based on multivoxel pattern analysis can be used to quantify unique brain states underlying complex network interactions that yield either successful or unsuccessful problem solving in more neutral or stressful situations. We provide evidence that brain network stability and states underlying synchronous interactions in regions integral for problem-solving processes are key predictors of whether individuals succeed or fail in stressful situations. Findings also suggested that individuals utilize discriminate neural patterns in successfully solving problems in stressful or neutral situations. Findings overall highlight how hidden Markov modeling can provide myriad possibilities for quantifying and better understanding the role of global network interactions in the problem-solving process and how the said interactions predict success or failure in different contexts.

A Hidden Surface Algorithm for Computer Generated Halftone Pictures

DTIC Science & Technology

converting data describing three-dimensional objects into data that can be used to generate two-dimensional halftone images. It deals with some problems that arise in black and white, and color shading.

Proximal versus distal cue utilization in spatial navigation: the role of visual acuity?

PubMed

Carman, Heidi M; Mactutus, Charles F

2002-09-01

Proximal versus distal cue use in the Morris water maze is a widely accepted strategy for the dissociation of various problems affecting spatial navigation in rats such as aging, head trauma, lesions, and pharmacological or hormonal agents. Of the limited number of ontogenetic rat studies conducted, the majority have approached the problem of preweanling spatial navigation through a similar proximal-distal dissociation. An implicit assumption among all of these studies has been that the animal's visual system is sufficient to permit robust spatial navigation. We challenged this assumption and have addressed the role of visual acuity in spatial navigation in the preweanling Fischer 344-N rat by training animals to locate a visible (proximal) or hidden (distal) platform using double or null extramaze cues within the testing environment. All pups demonstrated improved performance across training, but animals presented with a visible platform, regardless of extramaze cues, simultaneously reached asymptotic performance levels; animals presented with a hidden platform, dependent upon location of extramaze cues, differentially reached asymptotic performance levels. Probe trial performance, defined by quadrant time and platform crossings, revealed that distal-double-cue pups demonstrated spatial navigational ability superior to that of the remaining groups. These results suggest that a pup's ability to spatially navigate a hidden platform is dependent on not only its response repertoire and task parameters, but also its visual acuity, as determined by the extramaze cue location within the testing environment. The standard hidden versus visible platform dissociation may not be a satisfactory strategy for the control of potential sensory deficits.

Application of shift-and-add algorithms for imaging objects within biological media

NASA Astrophysics Data System (ADS)

Aizert, Avishai; Moshe, Tomer; Abookasis, David

2017-01-01

The Shift-and-Add (SAA) technique is a simple mathematical operation developed to reconstruct, at high spatial resolution, atmospherically degraded solar images obtained from stellar speckle interferometry systems. This method shifts and assembles individual degraded short-exposure images into a single average image with significantly improved contrast and detail. Since the inhomogeneous refractive indices of biological tissue causes light scattering similar to that induced by optical turbulence in the atmospheric layers, we assume that SAA methods can be successfully implemented to reconstruct the image of an object within a scattering biological medium. To test this hypothesis, five SAA algorithms were evaluated for reconstructing images acquired from multiple viewpoints. After successfully retrieving the hidden object's shape, quantitative image quality metrics were derived, enabling comparison of imaging error across a spectrum of layer thicknesses, demonstrating the relative efficacy of each SAA algorithm for biological imaging.

Plasmon Geometric Phase and Plasmon Hall Shift

NASA Astrophysics Data System (ADS)

Shi, Li-kun; Song, Justin C. W.

2018-04-01

The collective plasmonic modes of a metal comprise a simple pattern of oscillating charge density that yields enhanced light-matter interaction. Here we unveil that beneath this familiar facade plasmons possess a hidden internal structure that fundamentally alters its dynamics. In particular, we find that metals with nonzero Hall conductivity host plasmons with an intricate current density configuration that sharply departs from that of ordinary zero Hall conductivity metals. This nontrivial internal structure dramatically enriches the dynamics of plasmon propagation, enabling plasmon wave packets to acquire geometric phases as they scatter. At boundaries, these phases accumulate allowing plasmon waves that reflect off to experience a nonreciprocal parallel shift. This plasmon Hall shift, tunable by Hall conductivity as well as plasmon wavelength, displaces the incident and reflected plasmon trajectories and can be readily probed by near-field photonics techniques. Anomalous plasmon geometric phases dramatically enrich the nanophotonics toolbox, and yield radical new means for directing plasmonic beams.

The broad footprint of climate change from genes to biomes to people.

PubMed

Scheffers, Brett R; De Meester, Luc; Bridge, Tom C L; Hoffmann, Ary A; Pandolfi, John M; Corlett, Richard T; Butchart, Stuart H M; Pearce-Kelly, Paul; Kovacs, Kit M; Dudgeon, David; Pacifici, Michela; Rondinini, Carlo; Foden, Wendy B; Martin, Tara G; Mora, Camilo; Bickford, David; Watson, James E M

2016-11-11

Most ecological processes now show responses to anthropogenic climate change. In terrestrial, freshwater, and marine ecosystems, species are changing genetically, physiologically, morphologically, and phenologically and are shifting their distributions, which affects food webs and results in new interactions. Disruptions scale from the gene to the ecosystem and have documented consequences for people, including unpredictable fisheries and crop yields, loss of genetic diversity in wild crop varieties, and increasing impacts of pests and diseases. In addition to the more easily observed changes, such as shifts in flowering phenology, we argue that many hidden dynamics, such as genetic changes, are also taking place. Understanding shifts in ecological processes can guide human adaptation strategies. In addition to reducing greenhouse gases, climate action and policy must therefore focus equally on strategies that safeguard biodiversity and ecosystems. Copyright © 2016, American Association for the Advancement of Science.

Hydride ions in oxide hosts hidden by hydroxide ions

PubMed Central

Hayashi, Katsuro; Sushko, Peter V.; Hashimoto, Yasuhiro; Shluger, Alexander L.; Hosono, Hideo

2014-01-01

The true oxidation state of formally ‘H−’ ions incorporated in an oxide host is frequently discussed in connection with chemical shifts of 1H nuclear magnetic resonance spectroscopy, as they can exhibit values typically attributed to H+. Here we systematically investigate the link between geometrical structure and chemical shift of H− ions in an oxide host, mayenite, with a combination of experimental and ab initio approaches, in an attempt to resolve this issue. We demonstrate that the electron density near the hydrogen nucleus in an OH− ion (formally H+ state) exceeds that in an H− ion. This behaviour is the opposite to that expected from formal valences. We deduce a relationship between the chemical shift of H− and the distance from the H− ion to the coordinating electropositive cation. This relationship is pivotal for resolving H− species that are masked by various states of H+ ions. PMID:24662678

A general solution to the hidden-line problem. [to graphically represent aerodynamic stability derivatives

NASA Technical Reports Server (NTRS)

Hedgley, D. R., Jr.

1982-01-01

The requirements for computer-generated perspective projections of three dimensional objects has escalated. A general solution was developed. The theoretical solution to this problem is presented. The method is very efficient as it minimizes the selection of points and comparison of line segments and hence avoids the devastation of square-law growth.

A window into the future of the Earth, hidden in the jungles of Costa Rica's volcanoes

NASA Astrophysics Data System (ADS)

Fisher, J. B.; Schwandner, F. M.; Asner, G. P.; Schimel, D.; Norby, R. J.; Keller, M.; Pavlick, R.; Braverman, A. J.; Pieri, D. C.; Diaz, J. A.; Gutierrez, M.; Duarte, E. A.; Lewicki, J. L.; Manning, C. E.; Deering, C. D.; Seibt, U.; Miller, G. R.; Drewry, D.; Chambers, J.

2017-12-01

The CO2 fertilization response of the terrestrial biosphere contributes among the largest sensitivities and uncertainties across projections of the Earth's future. The source of that uncertainty can be pinpointed to the largest fluxes in the biosphere: the tropics. Free Air CO2 Enrichment (FACE) experiments have contributed immensely to our understanding of short-term CO2 fertilization, but, outside of a small pilot study in development, have been absent in the tropics. This is largely due to numerous hurdles of not only conducting such experiments in challenging environments, but also due to the need to expand their extent considerably to encompass the enormous diversity of species-level responses, in addition to the need for multi-decadal scale responses. As such, we have remained at a critical impasse in our ability to advance understanding of the response of the tropical biosphere to increasing CO2. Recent discoveries have found a cluster of volcanoes degassing CO2 into tropical ecosystems in Costa Rica at concentrations similar to future Earth atmosphere levels. The degassing has been occurring persistently from 10s to 100s of years over 10s to 100s of square kilometers, at different levels depending on the volcano. Fortuitously, this provides a natural "experiment" across a range of conditions needed to assess a widespread and long-lived tropical ecosystem response to elevated CO2: tree species will have had time to shift in composition, traits, structure, and function. Nonetheless, due both to the challenges with assessing these changes on the ground, and heterogeneity causing problems with coarse-scale satellite remote sensing observations, this "window" into the future of the Earth has remained veiled. Here, we describe an airborne-based plan designed to uncover this gem hidden in the jungles of Costa Rica's volcanoes.

Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR.

PubMed

Winkler, David A; Le, Tu C

2017-01-01

Neural networks have generated valuable Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models for a wide variety of small molecules and materials properties. They have grown in sophistication and many of their initial problems have been overcome by modern mathematical techniques. QSAR studies have almost always used so-called "shallow" neural networks in which there is a single hidden layer between the input and output layers. Recently, a new and potentially paradigm-shifting type of neural network based on Deep Learning has appeared. Deep learning methods have generated impressive improvements in image and voice recognition, and are now being applied to QSAR and QSAR modelling. This paper describes the differences in approach between deep and shallow neural networks, compares their abilities to predict the properties of test sets for 15 large drug data sets (the kaggle set), discusses the results in terms of the Universal Approximation theorem for neural networks, and describes how DNN may ameliorate or remove troublesome "activity cliffs" in QSAR data sets. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effectiveness of AODV Protocol under Hidden Node Environment

NASA Astrophysics Data System (ADS)

Garg, Ruchi; Sharma, Himanshu; Kumar, Sumit

IEEE 802.11 is a standard for mobile ad hoc networks (MANET), implemented with various different protocols. Ad Hoc on Demand Distance Vector Routing (AODV) is one of the several protocols of IEEE 802.11, intended to provide various Quality of Service (QOS) parameters under acceptable range. To avoid the collision and interference the MAC protocol has only two solutions, one, to sense the physical carrier and second, to use the RTS/CTS handshake mechanism. But with the help of these methods AODV is not free from the problem of hidden nodes like other several protocols. Under the hidden node environment, performance of AODV depends upon various factors. The position of receiver and sender among the other nodes is very crucial and it affects the performance. Under the various situations the AODV is simulated with the help of NS2 and the outcomes are discussed.

The Hidden Lives of Nurses' Cognitive Artifacts.

PubMed

Blaz, Jacquelyn W; Doig, Alexa K; Cloyes, Kristin G; Staggers, Nancy

2016-09-07

Standardizing nursing handoffs at shift change is recommended to improve communication, with electronic tools as the primary approach. However, nurses continue to rely on personally created paper-based cognitive artifacts - their "paper brains" - to support handoffs, indicating a deficiency in available electronic versions. The purpose of this qualitative study was to develop a deep understanding of nurses' paper-based cognitive artifacts in the context of a cancer specialty hospital. After completing 73 hours of hospital unit field observations, 13 medical oncology nurses were purposively sampled, shadowed for a single shift and interviewed using a semi-structured technique. An interpretive descriptive study design guided analysis of the data corpus of field notes, transcribed interviews, images of nurses' paper-based cognitive artifacts, and analytic memos. Findings suggest nurses' paper brains are personal, dynamic, living objects that undergo a life cycle during each shift and evolve over the course of a nurse's career. The life cycle has four phases: Creation, Application, Reproduction, and Destruction. Evolution in a nurse's individually styled, paper brain is triggered by a change in the nurse's environment that reshapes cognitive needs. If a paper brain no longer provides cognitive support in the new environment, it is modified into (adapted) or abandoned (made extinct) for a different format that will provide the necessary support. The "hidden lives" - the life cycle and evolution - of paper brains have implications for the design of successful electronic tools to support nursing practice, including handoff. Nurses' paper brains provide cognitive support beyond the context of handoff. Information retrieval during handoff is undoubtedly an important function of nurses' paper brains, but tools designed to standardize handoff communication without accounting for cognitive needs during all phases of the paper brain life cycle or the ability to evolve with changes to those cognitive needs will be underutilized.

The hidden challenges in role transitions and how leadership coaching can help new leaders find solid ground.

PubMed

Weinstock, Beth

2011-01-01

Leadership coaching is becoming an increasingly important intervention that helps individual nurse executives and managers develop and use the best of their strengths, gifts, and talents. As the need for leadership in nursing becomes urgent and brave souls move into the positions of greater authority and potential impact, they will face challenges as they move up in rank. This article identifies the hidden and often-overlooked challenges that are faced by new leaders as they transition into roles of increased responsibility, and it demonstrates how leadership coaching can help new leaders make successful transitions. As the current health care crisis creates opportunity for new leaders, those who opt for promotions and lateral shifts encounter both expected and surprising challenges. The expected challenges include mastering new content skills, learning new organizational structures, and getting to know new teams. The less obvious stressors include issues of self-esteem, assertiveness, self-consciousness, self-criticism, perfectionism, new boundaries, changing identities, and finding one's own leadership style. These important issues are often kept out of conscious awareness and overlooked at great cost to the individual leader and her institution. Leadership coaching can provide support and practical strategies for managing and overcoming these hidden challenges.

Hidden linkages between urbanization and food systems.

PubMed

Seto, Karen C; Ramankutty, Navin

2016-05-20

Global societies are becoming increasingly urban. This shift toward urban living is changing our relationship with food, including how we shop and what we buy, as well as ideas about sanitation and freshness. Achieving food security in an era of rapid urbanization will require considerably more understanding about how urban and food systems are intertwined. Here we discuss some potential understudied linkages that are ripe for further examination. Copyright © 2016, American Association for the Advancement of Science.

What is the Effect of Interannual Hydroclimatic Variability on Water Supply Reservoir Operations?

NASA Astrophysics Data System (ADS)

Galelli, S.; Turner, S. W. D.

2015-12-01

Rather than deriving from a single distribution and uniform persistence structure, hydroclimatic data exhibit significant trends and shifts in their mean, variance, and lagged correlation through time. Consequentially, observed and reconstructed streamflow records are often characterized by features of interannual variability, including long-term persistence and prolonged droughts. This study examines the effect of these features on the operating performance of water supply reservoirs. We develop a Stochastic Dynamic Programming (SDP) model that can incorporate a regime-shifting climate variable. We then compare the performance of operating policies—designed with and without climate variable—to quantify the contribution of interannual variability to standard policy sub-optimality. The approach uses a discrete-time Markov chain to partition the reservoir inflow time series into small number of 'hidden' climate states. Each state defines a distinct set of inflow transition probability matrices, which are used by the SDP model to condition the release decisions on the reservoir storage, current-period inflow and hidden climate state. The experimental analysis is carried out on 99 hypothetical water supply reservoirs fed from pristine catchments in Australia—all impacted by the Millennium drought. Results show that interannual hydroclimatic variability is a major cause of sub-optimal hedging decisions. The practical import is that conventional optimization methods may misguide operators, particularly in regions susceptible to multi-year droughts.

Problems of Indicator Weights and Multicolinearity in World University Rankings: Comparisons of Three Systems

ERIC Educational Resources Information Center

Soh, Kaycheng

2014-01-01

World university rankings (WUR) use the weight-and-sum approach to arrive at an overall measure which is then used to rank the participating universities of the world. Although the weight-and-sum procedure seems straightforward and accords with common sense, it has hidden methodological or statistical problems which render the meaning of the…

Disconnected Youth in the Research Triangle Region: An Ominous Problem Hidden in Plain Sight

ERIC Educational Resources Information Center

Dodson, David; Guillory, Ferrel; Lipsitz, Joan; Raper, Noah; Rausch, Christina

2008-01-01

In September 2006, the North Carolina GlaxoSmithKline Foundation commissioned MDC, Inc. of Chapel Hill to analyze the problem of "disconnected youth" in the Research Triangle region, determine the current state of the region's responses to the challenge, and recommend steps to deepen and accelerate action on the issue. The research process was…

A Short-Term Population Model of the Suicide Risk: The Case of Spain.

PubMed

De la Poza, Elena; Jódar, Lucas

2018-06-14

A relevant proportion of deaths by suicide have been attributed to other causes that produce the number of suicides remains hidden. The existence of a hidden number of cases is explained by the nature of the problem. Problems like this involve violence, and produce fear and social shame in victims' families. The existence of violence, fear and social shame experienced by victims favours a considerable number of suicides, identified as accidents or natural deaths. This paper proposes a short time discrete compartmental mathematical model to measure the suicidal risk for the case of Spain. The compartment model classifies and quantifies the amount of the Spanish population within the age intervals (16, 78) by their degree of suicide risk and their changes over time. Intercompartmental transits are due to the combination of quantitative and qualitative factors. Results are computed and simulations are performed to analyze the sensitivity of the model under uncertain coefficients.

Hypovigilance Detection for UCAV Operators Based on a Hidden Markov Model

PubMed Central

Kwon, Namyeon; Shin, Yongwook; Ryo, Chuh Yeop; Park, Jonghun

2014-01-01

With the advance of military technology, the number of unmanned combat aerial vehicles (UCAVs) has rapidly increased. However, it has been reported that the accident rate of UCAVs is much higher than that of manned combat aerial vehicles. One of the main reasons for the high accident rate of UCAVs is the hypovigilance problem which refers to the decrease in vigilance levels of UCAV operators while maneuvering. In this paper, we propose hypovigilance detection models for UCAV operators based on EEG signal to minimize the number of occurrences of hypovigilance. To enable detection, we have applied hidden Markov models (HMMs), two of which are used to indicate the operators' dual states, normal vigilance and hypovigilance, and, for each operator, the HMMs are trained as a detection model. To evaluate the efficacy and effectiveness of the proposed models, we conducted two experiments on the real-world data obtained by using EEG-signal acquisition devices, and they yielded satisfactory results. By utilizing the proposed detection models, the problem of hypovigilance of UCAV operators and the problem of high accident rate of UCAVs can be addressed. PMID:24963338

Learning multimodal dictionaries.

PubMed

Monaci, Gianluca; Jost, Philippe; Vandergheynst, Pierre; Mailhé, Boris; Lesage, Sylvain; Gribonval, Rémi

2007-09-01

Real-world phenomena involve complex interactions between multiple signal modalities. As a consequence, humans are used to integrate at each instant perceptions from all their senses in order to enrich their understanding of the surrounding world. This paradigm can be also extremely useful in many signal processing and computer vision problems involving mutually related signals. The simultaneous processing of multimodal data can, in fact, reveal information that is otherwise hidden when considering the signals independently. However, in natural multimodal signals, the statistical dependencies between modalities are in general not obvious. Learning fundamental multimodal patterns could offer deep insight into the structure of such signals. In this paper, we present a novel model of multimodal signals based on their sparse decomposition over a dictionary of multimodal structures. An algorithm for iteratively learning multimodal generating functions that can be shifted at all positions in the signal is proposed, as well. The learning is defined in such a way that it can be accomplished by iteratively solving a generalized eigenvector problem, which makes the algorithm fast, flexible, and free of user-defined parameters. The proposed algorithm is applied to audiovisual sequences and it is able to discover underlying structures in the data. The detection of such audio-video patterns in audiovisual clips allows to effectively localize the sound source on the video in presence of substantial acoustic and visual distractors, outperforming state-of-the-art audiovisual localization algorithms.

Adult-acquired hidden penis in obese patients: a critical survey of the literature.

PubMed

Cavayero, Chase T; Cooper, Meghan A; Harlin, Stephen L

2015-03-01

Hidden penis is anatomically defined by a lack of firm attachments of the skin and dartos fascia to the underlying Buck fascia. To critically appraise the research evidence that could support the most effective surgical techniques for adult-acquired hidden penis in obese patients. Studies investigating patients with a diagnosis of hidden penis were identified. Of these studies, only those with adult patients classified as overweight or obese (body mass index >25) were included in the review. Three reviewers examined the abstracts of the studies identified in the initial Medline search, and abstracts considered potentially relevant underwent full-text review. Studies that included patients with congenital, iatrogenic (eg, circumcision issues or aesthetic genital surgery), or traumatic causes of hidden penis were excluded. Studies that did not define the diagnostic criteria for hidden penis were excluded to minimize the risk of definition bias. The quality of evidence for each study was determined after considering the following sources of bias: method of allocation to study groups, data analysis, presence of baseline differences between groups, objectivity of outcome, and completeness of follow-up. Using these criteria, studies were then graded as high, moderate, or low in quality. Seven studies with a total of 119 patients met the inclusion criteria. All but 1 of the studies were nonrandomized. One study provided a clear presentation of results and appropriate statistical analysis. Six studies accounted for individual-based differences, and 1 study failed to account for baseline differences altogether. Four studies addressed follow-up. One study was of high quality, 2 were of moderate quality, and 4 were of low quality. Building a clinical practice guideline for the surgical management of hidden penis has proven difficult because of a lack of high-quality, statistically significant data in the research synthesis. The authors elucidate the challenges and epitomize the collective wisdom of surgeons who have investigated this problem and emphasize the need for rigorous evaluative studies. © 2015 The American Osteopathic Association.

Self-growing neural network architecture using crisp and fuzzy entropy

NASA Technical Reports Server (NTRS)

Cios, Krzysztof J.

1992-01-01

The paper briefly describes the self-growing neural network algorithm, CID2, which makes decision trees equivalent to hidden layers of a neural network. The algorithm generates a feedforward architecture using crisp and fuzzy entropy measures. The results of a real-life recognition problem of distinguishing defects in a glass ribbon and of a benchmark problem of differentiating two spirals are shown and discussed.

Chronic Elementary Absenteeism: A Problem Hidden in Plain Sight. A Research Brief from Attendance Works and Child & Family Policy Center

ERIC Educational Resources Information Center

Bruner, Charles; Discher, Anne; Chang, Hedy

2011-01-01

Chronic absenteeism--or missing 10 percent or more of school days for any reason--is a proven early warning sign of academic risk and school dropout. Too often, though, this problem is overlooked, especially among elementary students, because of the way attendance data are tracked. This study confirms the premise that districts and schools may…

Fundamental Study on Quantum Nanojets

DTIC Science & Technology

2004-08-01

Pergamon Press. Bell , J. S . 1966 On the problem of hidden variables in quantum mechanics. Rev. of Modern Phys., 38, 447. Berndl, K., Daumer, M...fluid dynamics based on two quantum mechanical perspectives; Schrödinger’s wave mechanics and quantum fluid dynamics based on Hamilton-Jacoby...References 8 2). Direct Problems a). Quantum fluid dynamics formalism based on Hamilton-Jacoby equation are adapted for the numerical

Unsupervised Learning Through Randomized Algorithms for High-Volume High-Velocity Data (ULTRA-HV).

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

Pinar, Ali; Kolda, Tamara G.; Carlberg, Kevin Thomas

Through long-term investments in computing, algorithms, facilities, and instrumentation, DOE is an established leader in massive-scale, high-fidelity simulations, as well as science-leading experimentation. In both cases, DOE is generating more data than it can analyze and the problem is intensifying quickly. The need for advanced algorithms that can automatically convert the abundance of data into a wealth of useful information by discovering hidden structures is well recognized. Such efforts however, are hindered by the massive volume of the data and its high velocity. Here, the challenge is developing unsupervised learning methods to discover hidden structure in high-volume, high-velocity data.

HIPPI: highly accurate protein family classification with ensembles of HMMs.

PubMed

Nguyen, Nam-Phuong; Nute, Michael; Mirarab, Siavash; Warnow, Tandy

2016-11-11

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

Nonlinear dynamical modes of climate variability: from curves to manifolds

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

The growth crisis--and how to escape it.

PubMed

Slywotzky, Adrian J; Wise, Richard

2002-07-01

At a time when companies are poised to seize the growth opportunities of a rebounding economy, many of them, whether they know it or not, face a growth crisis. Even during the boom years of the past decade, only a small fraction of companies enjoyed consistent double-digit revenue growth. And those that did often achieved it through short-term measures--such as mergers and inflated price increases--that don't provide the foundation for growth over the long term. But there is a way out of this predicament. The authors claim that companies can achieve sustained growth by leveraging their "hidden assets," a wide array of underused, intangible capabilities and advantages that most established companies already hold. To date, much of the research on intangible assets has centered on intellectual property and brand recognition. But in this article, the authors uncover a host of other assets that can help spark growth. They identify four major categories of hidden assets: customer relationships, strategic real estate, networks, and information. And they illustrate each with an example of a company that has creatively used its hidden assets to produce new sources of revenue. Executives have spent years learning to create growth using products, facilities, and working capital. But they should really focus on mobilizing their hidden assets to serve their customers' higher-order needs--in other words, create offerings that make customers' lives easier, better, or less expensive. Making that shift in mind-set isn't easy, admit the authors, but companies that do it may not only create meaningful new value for their customers but also produce double-digit revenue and earnings growth for investors.

Naturalness of Electroweak Symmetry Breaking

NASA Astrophysics Data System (ADS)

Espinosa, J. R.

2007-02-01

After revisiting the hierarchy problem of the Standard Model and its implications for the scale of New Physics, I consider the fine tuning problem of electroweak symmetry breaking in two main scenarios beyond the Standard Model: SUSY and Little Higgs models. The main conclusions are that New Physics should appear on the reach of the LHC; that some SUSY models can solve the hierarchy problem with acceptable residual fine tuning and, finally, that Little Higgs models generically suffer from large tunings, many times hidden.

Revealing Stellar Surface Structure Behind Transiting Exoplanets

NASA Astrophysics Data System (ADS)

Dravins, Dainis

2018-04-01

During exoplanet transits, successive stellar surface portions become hidden and differential spectroscopy between various transit phases provide spectra of small surface segments temporarily hidden behind the planet. Line profile changes across the stellar disk offer diagnostics for hydrodynamic modeling, while exoplanet analyses require stellar background spectra to be known along the transit path. Since even giant planets cover only a small fraction of any main-sequence star, very precise observations are required, as well as averaging over numerous spectral lines with similar parameters. Spatially resolved Fe I line profiles across stellar disks have now been retrieved for HD209458 (G0V) and HD189733A (K1V), using data from the UVES and HARPS spectrometers. Free from rotational broadening, spatially resolved profiles are narrower and deeper than in integrated starlight. During transit, the profiles shift towards longer wavelengths, illustrating both stellar rotation at the latitude of transit and the prograde orbital motion of the exoplanets. This method will soon become applicable to more stars, once additional bright exoplanet hosts have been found.

Confocal non-line-of-sight imaging based on the light-cone transform

NASA Astrophysics Data System (ADS)

O’Toole, Matthew; Lindell, David B.; Wetzstein, Gordon

2018-03-01

How to image objects that are hidden from a camera’s view is a problem of fundamental importance to many fields of research, with applications in robotic vision, defence, remote sensing, medical imaging and autonomous vehicles. Non-line-of-sight (NLOS) imaging at macroscopic scales has been demonstrated by scanning a visible surface with a pulsed laser and a time-resolved detector. Whereas light detection and ranging (LIDAR) systems use such measurements to recover the shape of visible objects from direct reflections, NLOS imaging reconstructs the shape and albedo of hidden objects from multiply scattered light. Despite recent advances, NLOS imaging has remained impractical owing to the prohibitive memory and processing requirements of existing reconstruction algorithms, and the extremely weak signal of multiply scattered light. Here we show that a confocal scanning procedure can address these challenges by facilitating the derivation of the light-cone transform to solve the NLOS reconstruction problem. This method requires much smaller computational and memory resources than previous reconstruction methods do and images hidden objects at unprecedented resolution. Confocal scanning also provides a sizeable increase in signal and range when imaging retroreflective objects. We quantify the resolution bounds of NLOS imaging, demonstrate its potential for real-time tracking and derive efficient algorithms that incorporate image priors and a physically accurate noise model. Additionally, we describe successful outdoor experiments of NLOS imaging under indirect sunlight.

Confocal non-line-of-sight imaging based on the light-cone transform.

PubMed

O'Toole, Matthew; Lindell, David B; Wetzstein, Gordon

2018-03-15

How to image objects that are hidden from a camera's view is a problem of fundamental importance to many fields of research, with applications in robotic vision, defence, remote sensing, medical imaging and autonomous vehicles. Non-line-of-sight (NLOS) imaging at macroscopic scales has been demonstrated by scanning a visible surface with a pulsed laser and a time-resolved detector. Whereas light detection and ranging (LIDAR) systems use such measurements to recover the shape of visible objects from direct reflections, NLOS imaging reconstructs the shape and albedo of hidden objects from multiply scattered light. Despite recent advances, NLOS imaging has remained impractical owing to the prohibitive memory and processing requirements of existing reconstruction algorithms, and the extremely weak signal of multiply scattered light. Here we show that a confocal scanning procedure can address these challenges by facilitating the derivation of the light-cone transform to solve the NLOS reconstruction problem. This method requires much smaller computational and memory resources than previous reconstruction methods do and images hidden objects at unprecedented resolution. Confocal scanning also provides a sizeable increase in signal and range when imaging retroreflective objects. We quantify the resolution bounds of NLOS imaging, demonstrate its potential for real-time tracking and derive efficient algorithms that incorporate image priors and a physically accurate noise model. Additionally, we describe successful outdoor experiments of NLOS imaging under indirect sunlight.

What work schedule characteristics constitute a problem to the individual? A representative study of Swedish shift workers.

PubMed

Åkerstedt, Torbjörn; Kecklund, Göran

2017-03-01

The purpose was to investigate which detailed characteristics of shift schedules that are seen as problems to those exposed. A representative national sample of non-day workers (N = 2031) in Sweden was asked whether they had each of a number of particular work schedule characteristics and, if yes, to what extent this constituted a "big problem in life". It was also inquired whether the individual's work schedules had negative consequences for fatigue, sleep and social life. The characteristic with the highest percentage reporting a big problem was "short notice (<1 month) of a new work schedule" (30.5%), <11 h off between shifts (27.8%), and split duty (>1.5 h break at mid-shift, 27.2%). Overtime (>10 h/week), night work, morning work, day/night shifts showed lower prevalences of being a "big problem". Women indicated more problems in general. Short notice was mainly related to negative social effects, while <11 h off between shifts was related to disturbed sleep, fatigue and social difficulties. It was concluded that schedules involving unpredictable working hours (short notice), short daily rest between shifts, and split duty shifts constitute big problems. The results challenge current views of what aspects of shift work need improvement, and negative social consequences seem more important than those related to health. Copyright © 2016 Elsevier Ltd. All rights reserved.

Phasic Triplet Markov Chains.

PubMed

El Yazid Boudaren, Mohamed; Monfrini, Emmanuel; Pieczynski, Wojciech; Aïssani, Amar

2014-11-01

Hidden Markov chains have been shown to be inadequate for data modeling under some complex conditions. In this work, we address the problem of statistical modeling of phenomena involving two heterogeneous system states. Such phenomena may arise in biology or communications, among other fields. Namely, we consider that a sequence of meaningful words is to be searched within a whole observation that also contains arbitrary one-by-one symbols. Moreover, a word may be interrupted at some site to be carried on later. Applying plain hidden Markov chains to such data, while ignoring their specificity, yields unsatisfactory results. The Phasic triplet Markov chain, proposed in this paper, overcomes this difficulty by means of an auxiliary underlying process in accordance with the triplet Markov chains theory. Related Bayesian restoration techniques and parameters estimation procedures according to the new model are then described. Finally, to assess the performance of the proposed model against the conventional hidden Markov chain model, experiments are conducted on synthetic and real data.

Noise-induced cochlear synaptopathy: Past findings and future studies.

PubMed

Kobel, Megan; Le Prell, Colleen G; Liu, Jennifer; Hawks, John W; Bao, Jianxin

2017-06-01

For decades, we have presumed the death of hair cells and spiral ganglion neurons are the main cause of hearing loss and difficulties understanding speech in noise, but new findings suggest synapse loss may be the key contributor. Specifically, recent preclinical studies suggest that the synapses between inner hair cells and spiral ganglion neurons with low spontaneous rates and high thresholds are the most vulnerable subcellular structures, with respect to insults during aging and noise exposure. This cochlear synaptopathy can be "hidden" because this synaptic loss can occur without permanent hearing threshold shifts. This new discovery of synaptic loss opens doors to new research directions. Here, we review a number of recent studies and make suggestions in two critical future research directions. First, based on solid evidence of cochlear synaptopathy in animal models, it is time to apply molecular approaches to identify the underlying molecular mechanisms; improved understanding is necessary for developing rational, effective therapies against this cochlear synaptopathy. Second, in human studies, the data supporting cochlear synaptopathy are indirect although rapid progress has been made. To fully identify changes in function that are directly related this hidden synaptic damage, we argue that a battery of tests including both electrophysiological and behavior tests should be combined for diagnosis of "hidden hearing loss" in clinical studies. This new approach may provide a direct link between cochlear synaptopathy and perceptual difficulties. Copyright © 2016 Elsevier B.V. All rights reserved.

Nondestructive detection of infested chestnuts based on NIR spectroscopy

USDA-ARS?s Scientific Manuscript database

Insect feeding is a significant postharvest problem for processors of Chestnuts (Castanea sativa, Miller). In most cases, damage from insects is 'hidden', i.e. not visually detectable on the fruit surface. Consequently, traditional sorting techniques, including manual sorting, are generally inadequa...

A First Course in Intercultural Communication.

ERIC Educational Resources Information Center

Goodyear, F. H.; Williams, Patrick L.

The Texas Christian University course description, outline, and supporting bibliography deal with the problems of intercultural, interracial communication. The course plan begins with the thesis that racism is institutionalized and that the eradication of racism requires changes in individuals' awareness of their own hidden discriminatory…

Normal Science Education and Its Dangers: The Case of School Chemistry.

ERIC Educational Resources Information Center

Van Berkel, Berry; De Vos, Wobbe; Verdonk, Adri H.; Pilot, Albert

2000-01-01

Attempts to solve the problem of hidden structure in school chemistry. Argues that normal chemistry education is isolated from common sense, everyday life and society, the history and philosophy of science, technology, school physics, and chemical research. (Author/CCM)

National Security Policy and Security Challenges of Maldives

DTIC Science & Technology

2014-06-13

creates the true problems the Maldivians are currently facing. Hidden agendas, unprofessionalism, and low ethical standards of politicians and...based on sharia law. The theories of cultural relativism and democracy strongly advocate the freedoms of societies, thus the Maldivian decision as a

Monitoring the Future: National Survey Results on Drug Use, 1975-2008. Volume I, Secondary School Students. NIH Publication No. 09-7402

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2009-01-01

The Monitoring the Future study has provided the nation with a window into the important, but largely hidden, problem behaviors of illicit drug use, alcohol use, and tobacco use. It has provided a clearer view of the changing topography of these problems among adolescents and adults, a better understanding of the dynamics of factors that drive…

Monitoring the Future: National Survey Results on Drug Use, 1975-2007. Volume I, Secondary School Students. NIH Publication No. 08-6418A

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2008-01-01

The Monitoring the Future study has provided the nation with a window into the important, but largely hidden, problem behaviors of illicit drug use, alcohol use, and tobacco use. It has provided a clearer view of the changing topography of these problems among adolescents and adults, a better understanding of the dynamics of factors that drive…

Monitoring the Future: National Survey Results on Drug Use, 1975-2006. Volume I: Secondary School Students. NIH Publication No. 07-6205

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2007-01-01

The Monitoring the Future study has provided the nation with a window into the important, but largely hidden, problem behaviors of illicit drug use, alcohol use, and tobacco use. It has provided a clearer view of the changing topography of these problems among adolescents and adults, a better understanding of the dynamics of factors that drive…

Object permanence in the food-storing coal tit (Periparus ater) and the non-storing great tit (Parus major): Is the mental representation required?

PubMed

Marhounová, Lucie; Frynta, Daniel; Fuchs, Roman; Landová, Eva

2017-05-01

Object permanence is a cognitive ability that enables animals to mentally represent the continuous existence of temporarily hidden objects. Generally, it develops gradually through six qualitative stages, the evolution of which may be connected with some specific ecological and behavioral factors. In birds, the advanced object permanence skills were reported in several storing species of the Corvidae family. In order to test the association between food-storing and achieved performance within the stages, we compared food-storing coal tits (Periparus ater) and nonstoring great tits (Parus major) using an adapted version of Uzgiris & Hunt's Scale 1 tasks. The coal tits significantly outperformed the great tits in searching for completely hidden objects. Most of the great tits could not solve the task when the object disappeared completely. However, the upper limit for both species is likely to be Stage 4. The coal tits could solve problems with simply hidden objects, but they used alternative strategies rather than mental representation when searching for completely hidden objects, especially if choosing between two locations. Our results also suggest that neophobia did not affect the overall performance in the object permanence tasks. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Sexual Orientation-Related Differences in Virtual Spatial Navigation and Spatial Search Strategies.

PubMed

Rahman, Qazi; Sharp, Jonathan; McVeigh, Meadhbh; Ho, Man-Ling

2017-07-01

Spatial abilities are generally hypothesized to differ between men and women, and people with different sexual orientations. According to the cross-sex shift hypothesis, gay men are hypothesized to perform in the direction of heterosexual women and lesbian women in the direction of heterosexual men on cognitive tests. This study investigated sexual orientation differences in spatial navigation and strategy during a virtual Morris water maze task (VMWM). Forty-four heterosexual men, 43 heterosexual women, 39 gay men, and 34 lesbian/bisexual women (aged 18-54 years) navigated a desktop VMWM and completed measures of intelligence, handedness, and childhood gender nonconformity (CGN). We quantified spatial learning (hidden platform trials), probe trial performance, and cued navigation (visible platform trials). Spatial strategies during hidden and probe trials were classified into visual scanning, landmark use, thigmotaxis/circling, and enfilading. In general, heterosexual men scored better than women and gay men on some spatial learning and probe trial measures and used more visual scan strategies. However, some differences disappeared after controlling for age and estimated IQ (e.g., in visual scanning heterosexual men differed from women but not gay men). Heterosexual women did not differ from lesbian/bisexual women. For both sexes, visual scanning predicted probe trial performance. More feminine CGN scores were associated with lower performance among men and greater performance among women on specific spatial learning or probe trial measures. These results provide mixed evidence for the cross-sex shift hypothesis of sexual orientation-related differences in spatial cognition.

Hidden Worries

ERIC Educational Resources Information Center

Reclaiming Children and Youth, 2013

2013-01-01

Sometimes children are stressed about seemingly small events that escalate into problem behavior. In this article, an insightful teacher discusses restoration of emotional balance by mobilizing positive support from both school and family using A Response Ability Pathways (RAP) intervention. The RAP techniques and how they can be used are…

The Hidden Cost of Saying No!

ERIC Educational Resources Information Center

Dyson, Freeman J.

1975-01-01

Four problems of the regulation of technological development are reviewed: Djerassi's study of the regulation of chemical birth control agents; the downfall of the American supersonic airliner; climate modification; and genetic engineering. The author examines technology and the nature of bureaucratic institutions with respect to the political…

The importance of situation-specific encodings: analysis of a simple connectionist model of letter transposition effects

NASA Astrophysics Data System (ADS)

Fang, Shin-Yi; Smith, Garrett; Tabor, Whitney

2018-04-01

This paper analyses a three-layer connectionist network that solves a translation-invariance problem, offering a novel explanation for transposed letter effects in word reading. Analysis of the hidden unit encodings provides insight into two central issues in cognitive science: (1) What is the novelty of claims of "modality-specific" encodings? and (2) How can a learning system establish a complex internal structure needed to solve a problem? Although these topics (embodied cognition and learnability) are often treated separately, we find a close relationship between them: modality-specific features help the network discover an abstract encoding by causing it to break the initial symmetries of the hidden units in an effective way. While this neural model is extremely simple compared to the human brain, our results suggest that neural networks need not be black boxes and that carefully examining their encoding behaviours may reveal how they differ from classical ideas about the mind-world relationship.

Hidden Markov random field model and Broyden-Fletcher-Goldfarb-Shanno algorithm for brain image segmentation

NASA Astrophysics Data System (ADS)

Guerrout, EL-Hachemi; Ait-Aoudia, Samy; Michelucci, Dominique; Mahiou, Ramdane

2018-05-01

Many routine medical examinations produce images of patients suffering from various pathologies. With the huge number of medical images, the manual analysis and interpretation became a tedious task. Thus, automatic image segmentation became essential for diagnosis assistance. Segmentation consists in dividing the image into homogeneous and significant regions. We focus on hidden Markov random fields referred to as HMRF to model the problem of segmentation. This modelisation leads to a classical function minimisation problem. Broyden-Fletcher-Goldfarb-Shanno algorithm referred to as BFGS is one of the most powerful methods to solve unconstrained optimisation problem. In this paper, we investigate the combination of HMRF and BFGS algorithm to perform the segmentation operation. The proposed method shows very good segmentation results comparing with well-known approaches. The tests are conducted on brain magnetic resonance image databases (BrainWeb and IBSR) largely used to objectively confront the results obtained. The well-known Dice coefficient (DC) was used as similarity metric. The experimental results show that, in many cases, our proposed method approaches the perfect segmentation with a Dice Coefficient above .9. Moreover, it generally outperforms other methods in the tests conducted.

Cognitive shifting and externalising problem behaviour in intellectual disability and autism spectrum disorder.

PubMed

Visser, E M; Berger, H J C; Van Schrojenstein Lantman-De Valk, H M J; Prins, J B; Teunisse, J P

2015-08-01

Behavioural problems are frequently reported in residential care for people with an intellectual disability (ID) in particular when they are additionally diagnosed with autism spectrum disorder (ASD). There are indications that impairment in cognitive shifting may be associated with problem behaviour. The objectives of this study were (1) to examine the relationship of cognitive shifting and severity of ASD symptoms with externalising problem behaviour in individuals with ID, with and without ASD, and (2) to examine whether a diagnosis based on shifting impairment is more predictive of externalising problem behaviour than an ASD diagnosis. Participants consisted of adolescents and young adults with mild ID, with and without ASD (n = 41). Pearson intercorrelations were computed to explore the relationship between shifting impairment and severity of ASD symptoms on the one hand and ratings of externalising problem behaviour on the other hand. t-Tests were performed to analyse differences in externalising problem behaviour. Unlike ASD symptom severity, shifting scores were found to be associated with externalising problem behaviour, but only if shifting was measured using rating scales and not when using neuropsychological tasks. Externalising problem behaviour scores significantly differed when groups were classified according to shifting impairment (impaired vs. non-impaired) but not when they were classified according to ID and ASD diagnoses. It is proposed to use a cognition-based approach when analysing problem behaviour, thus concentrating not so much on ID and ASD diagnosis and their corresponding symptoms, but rather placing the focus on cognitive symptoms. © 2015 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Split-shift work in relation to stress, health and psychosocial work factors among bus drivers.

PubMed

Ihlström, Jonas; Kecklund, Göran; Anund, Anna

2017-01-01

Shift work has been associated with poor health, sleep and fatigue problems and low satisfaction with working hours. However, one type of shift working, namely split shifts, have received little attention. This study examined stress, health and psychosocial aspects of split-shift schedules among bus drivers in urban transport. A questionnaire was distributed to drivers working more than 70% of full time which 235 drivers in total answered. In general, drivers working split-shift schedules (n = 146) did not differ from drivers not working such shifts (n = 83) as regards any of the outcome variables that were studied. However, when individual perceptions towards split-shift schedules were taken into account, a different picture appeared. Bus drivers who reported problems working split shifts (36%) reported poorer health, higher perceived stress, working hours interfering with social life, lower sleep quality, more persistent fatigue and lower general work satisfaction than those who did not view split shifts as a problem. Moreover, drivers who reported problems with split shifts also perceived lower possibilities to influence working hours, indicating lower work time control. This study indicates that split shifts were not associated with increased stress, poorer health and adverse psychosocial work factors for the entire study sample. However, the results showed that individual differences were important and approximately one third of the drivers reported problems with split shifts, which in turn was associated with stress, poor health and negative psychosocial work conditions. More research is needed to understand the individual and organizational determinants of tolerance to split shifts.

Elder Abuse: The Hidden Problem. A Briefing by the Select Committee on Aging, House of Representatives, Ninety-Sixth Congress, First Session (Boston, Massachusetts, June 23, 1979).

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Select Committee on Aging.

This briefing by the Congressional Select Committee on Aging was designed to gather information on the physical and psychological abuse of the elderly. A number of witness reports are included, testifying to the seriousness and extent of the problem of elder abuse. It is pointed out that many victims refuse to admit abuse; public discussions of…

Curricula Equity in Required Ninth-Grade Physical Education.

ERIC Educational Resources Information Center

Napper-Owen, Gloria E.; Kovar, Susan K.; Ermler, Kathy L.; Mehrhof, Joella H.

1999-01-01

Surveyed high school physical educators regarding required physical education programs, examining hidden curriculum about gender equity and culture. Team sports dominated the instructional units. Teachers had problems involving all students in coeducational activities. Female teachers were more apt to teach outside their socially accepted area of…

Allergies: The Hidden Hazard.

ERIC Educational Resources Information Center

Rapp, Doris J.

1990-01-01

Children can suffer from allergies that can markedly affect their behavior and school performance. Once an allergy is suspected, teachers and principals can consider allergens inside the school, outside the school, and related to problem foods or chemicals. A sidebar lists some allergy clues to watch for. Includes nine references. (MLH)

The Camp Caretaker: A Hidden Treasure.

ERIC Educational Resources Information Center

Ezersky, Eugene M.

1996-01-01

At a round-table discussion, five camp caretakers identified common camp maintenance problems. Snow loads, wooden floors, storage of lake equipment, removal of grass cuttings and leaves, local suppliers, vandalism and trespassing, swimming pools, assigning work, use of outside contractors, decisions to replace or repair, job satisfaction, and…

Computer Intelligence: Unlimited and Untapped.

ERIC Educational Resources Information Center

Staples, Betsy

1983-01-01

Herbert Simon (Nobel prize-winning economist/professor) expresses his views on human and artificial intelligence, problem solving, inventing concepts, and the future. Includes comments on expert systems, state of the art in artificial intelligence, robotics, and "Bacon," a computer program that finds scientific laws hidden in raw data.…

29Si nuclear magnetic resonance study of URu 2Si 2 under pressure

DOE PAGES

Shirer, K. R.; Dioguardi, A. P.; Bush, B. T.; ...

2015-12-01

Here, we report 29Si nuclear magnetic resonance measurements of single crystals and aligned powders of URu 2Si 2 under pressure in the hidden order and paramagnetic phases. We find evidence for a reduction of the Knight shift with applied pressure, consistent with previous measurements of the static magnetic susceptibility. Previous measurements of the spin lattice relaxation time revealed a partial suppression of the density of states below 30 K. Here, we find that the temperature at which this suppression occurs is enhanced with applied pressure.

The Hidden Complexity of Biological "Dirty Bombs": Implications for Special Operations Medical Personnel.

PubMed

Washington, Michael A; Blythe, Jauchia

The recent capture of a terrorist in Belgium carrying explosives, fecal matter, and animal tissue may indicate a shift from conventional weapons to crude bacteriological preparations as instruments of terror. It is important to note that although such weapons lack technological sophistication, bacteria are inherently complex, unpredictable, and undetectable in the field. Therefore, it is important that Special Operations medical personnel understand the complications that such seemingly simple devices can add to the treatment of casualties in the field and subsequent evaluation in the clinic. 2016.

Charmonium-nucleon interactions from the time-dependent HAL QCD method

NASA Astrophysics Data System (ADS)

Sugiura, Takuya; Ikeda, Yoichi; Ishii, Noriyoshi

2018-03-01

The charmonium-nucleon effective central interactions have been computed by the time-dependent HAL QCD method. This gives an updated result of a previous study based on the time-independent method, which is now known to be problematic because of the difficulty in achieving the ground-state saturation. We discuss that the result is consistent with the heavy quark symmetry. No bound state is observed from the analysis of the scattering phase shift; however, this shall lead to a future search of the hidden-charm pentaquarks by considering channel-coupling effects.

The Hidden Lives of Nurses’ Cognitive Artifacts

PubMed Central

Doig, Alexa K.; Cloyes, Kristin G.; Staggers, Nancy

2016-01-01

Summary Background Standardizing nursing handoffs at shift change is recommended to improve communication, with electronic tools as the primary approach. However, nurses continue to rely on personally created paper-based cognitive artifacts – their “paper brains” – to support handoffs, indicating a deficiency in available electronic versions. Objective The purpose of this qualitative study was to develop a deep understanding of nurses’ paper-based cognitive artifacts in the context of a cancer specialty hospital. Methods After completing 73 hours of hospital unit field observations, 13 medical oncology nurses were purposively sampled, shadowed for a single shift and interviewed using a semi-structured technique. An interpretive descriptive study design guided analysis of the data corpus of field notes, transcribed interviews, images of nurses’ paper-based cognitive artifacts, and analytic memos. Results Findings suggest nurses’ paper brains are personal, dynamic, living objects that undergo a life cycle during each shift and evolve over the course of a nurse’s career. The life cycle has four phases: Creation, Application, Reproduction, and Destruction. Evolution in a nurse’s individually styled, paper brain is triggered by a change in the nurse’s environment that reshapes cognitive needs. If a paper brain no longer provides cognitive support in the new environment, it is modified into (adapted) or abandoned (made extinct) for a different format that will provide the necessary support. Conclusions The “hidden lives“ – the life cycle and evolution – of paper brains have implications for the design of successful electronic tools to support nursing practice, including handoff. Nurses’ paper brains provide cognitive support beyond the context of handoff. Information retrieval during handoff is undoubtedly an important function of nurses’ paper brains, but tools designed to standardize handoff communication without accounting for cognitive needs during all phases of the paper brain life cycle or the ability to evolve with changes to those cognitive needs will be underutilized. PMID:27602412

A meta-cognitive learning algorithm for a Fully Complex-valued Relaxation Network.

PubMed

Savitha, R; Suresh, S; Sundararajan, N

2012-08-01

This paper presents a meta-cognitive learning algorithm for a single hidden layer complex-valued neural network called "Meta-cognitive Fully Complex-valued Relaxation Network (McFCRN)". McFCRN has two components: a cognitive component and a meta-cognitive component. A Fully Complex-valued Relaxation Network (FCRN) with a fully complex-valued Gaussian like activation function (sech) in the hidden layer and an exponential activation function in the output layer forms the cognitive component. The meta-cognitive component contains a self-regulatory learning mechanism which controls the learning ability of FCRN by deciding what-to-learn, when-to-learn and how-to-learn from a sequence of training data. The input parameters of cognitive components are chosen randomly and the output parameters are estimated by minimizing a logarithmic error function. The problem of explicit minimization of magnitude and phase errors in the logarithmic error function is converted to system of linear equations and output parameters of FCRN are computed analytically. McFCRN starts with zero hidden neuron and builds the number of neurons required to approximate the target function. The meta-cognitive component selects the best learning strategy for FCRN to acquire the knowledge from training data and also adapts the learning strategies to implement best human learning components. Performance studies on a function approximation and real-valued classification problems show that proposed McFCRN performs better than the existing results reported in the literature. Copyright © 2012 Elsevier Ltd. All rights reserved.

Effective Data-Driven Calibration for a Galvanometric Laser Scanning System Using Binocular Stereo Vision.

PubMed

Tu, Junchao; Zhang, Liyan

2018-01-12

A new solution to the problem of galvanometric laser scanning (GLS) system calibration is presented. Under the machine learning framework, we build a single-hidden layer feedforward neural network (SLFN）to represent the GLS system, which takes the digital control signal at the drives of the GLS system as input and the space vector of the corresponding outgoing laser beam as output. The training data set is obtained with the aid of a moving mechanism and a binocular stereo system. The parameters of the SLFN are efficiently solved in a closed form by using extreme learning machine (ELM). By quantitatively analyzing the regression precision with respective to the number of hidden neurons in the SLFN, we demonstrate that the proper number of hidden neurons can be safely chosen from a broad interval to guarantee good generalization performance. Compared to the traditional model-driven calibration, the proposed calibration method does not need a complex modeling process and is more accurate and stable. As the output of the network is the space vectors of the outgoing laser beams, it costs much less training time and can provide a uniform solution to both laser projection and 3D-reconstruction, in contrast with the existing data-driven calibration method which only works for the laser triangulation problem. Calibration experiment, projection experiment and 3D reconstruction experiment are respectively conducted to test the proposed method, and good results are obtained.

Shifting the closed-loop spectrum in the optimal linear quadratic regulator problem for hereditary systems

NASA Technical Reports Server (NTRS)

Gibson, J. S.; Rosen, I. G.

1985-01-01

In the optimal linear quadratic regulator problem for finite dimensional systems, the method known as an alpha-shift can be used to produce a closed-loop system whose spectrum lies to the left of some specified vertical line; that is, a closed-loop system with a prescribed degree of stability. This paper treats the extension of the alpha-shift to hereditary systems. As infinite dimensions, the shift can be accomplished by adding alpha times the identity to the open-loop semigroup generator and then solving an optimal regulator problem. However, this approach does not work with a new approximation scheme for hereditary control problems recently developed by Kappel and Salamon. Since this scheme is among the best to date for the numerical solution of the linear regulator problem for hereditary systems, an alternative method for shifting the closed-loop spectrum is needed. An alpha-shift technique that can be used with the Kappel-Salamon approximation scheme is developed. Both the continuous-time and discrete-time problems are considered. A numerical example which demonstrates the feasibility of the method is included.

Shifting the closed-loop spectrum in the optimal linear quadratic regulator problem for hereditary systems

NASA Technical Reports Server (NTRS)

Gibson, J. S.; Rosen, I. G.

1987-01-01

In the optimal linear quadratic regulator problem for finite dimensional systems, the method known as an alpha-shift can be used to produce a closed-loop system whose spectrum lies to the left of some specified vertical line; that is, a closed-loop system with a prescribed degree of stability. This paper treats the extension of the alpha-shift to hereditary systems. As infinite dimensions, the shift can be accomplished by adding alpha times the identity to the open-loop semigroup generator and then solving an optimal regulator problem. However, this approach does not work with a new approximation scheme for hereditary control problems recently developed by Kappel and Salamon. Since this scheme is among the best to date for the numerical solution of the linear regulator problem for hereditary systems, an alternative method for shifting the closed-loop spectrum is needed. An alpha-shift technique that can be used with the Kappel-Salamon approximation scheme is developed. Both the continuous-time and discrete-time problems are considered. A numerical example which demonstrates the feasibility of the method is included.

Selecting a Learning Management System (LMS) in Developing Countries: Instructors' Evaluation

ERIC Educational Resources Information Center

Cavus, Nadire

2013-01-01

Learning management systems (LMSs) contain hidden costs, unclear user environments, bulky developer and administration manuals, and limitations with regard to interoperability, integration, localization, and bandwidth requirements. Careful evaluation is required in selecting the most appropriate LMS for use, and this is a general problem in…

Aging and Alcohol Abuse: Increasing Counselor Awareness

ERIC Educational Resources Information Center

Williams, June M.; Ballard, Mary B.; Alessi, Hunter

2005-01-01

Alcohol abuse in older adulthood is a rapidly growing but often hidden problem. The authors provide an overview of the issues related to older adult alcohol abuse through a discussion of physiological, psychological, and social risk factors; an examination of appropriate assessment procedures; and an overview of factors related to treatment.

Sniffing out the Secret Poison: Selection Bias in Educational Research

ERIC Educational Resources Information Center

Showalter, Daniel A.; Mullet, Luke B.

2017-01-01

Selection bias is a persistent, and often hidden, problem in educational research. It is the primary obstacle standing in between increasingly available large education datasets and the ability to make valid causal inferences to inform policymaking, research, and practice (Stuart, 2010). This article provides an accessible discussion on the…

Hidden in the Middle: Culture, Value and Reward in Bioinformatics

ERIC Educational Resources Information Center

Lewis, Jamie; Bartlett, Andrew; Atkinson, Paul

2016-01-01

Bioinformatics--the so-called shotgun marriage between biology and computer science--is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised…

Administrative Law: The Hidden Comparative Law Course.

ERIC Educational Resources Information Center

Strauss, Peter L.

1996-01-01

Argues that the main contribution of the Administrative Law course to law students is that it presents problems which contrast with those of the standard court-centered curriculum and can illuminate other areas of law, repeatedly confronting students with doctrinal differences. Offers several examples from civil procedure, constitutional law, and…

Influence of enzymatic hydrolysis on the allergenic reactivity of processed cashew and pistachio

USDA-ARS?s Scientific Manuscript database

Tree nuts constitute one of the main cause of fatal anaphylactic reactions due to food allergy upon direct ingestion and as ingredients (hidden allergens), and cashew and pistachio allergies are considered a serious health problem. Several previous studies have shown that thermal processing may modi...

Hispanics in the Criminal Justice System--the "Nonexistent" Problem.

ERIC Educational Resources Information Center

Mandel, Jerry

1979-01-01

Though hidden from view by being considered "non-existent", the meager evidence indicates that Hispanics have an unusually high arrest and incarceration rate. Hispanic background is rarely asked on the six major sources of criminal justice statistics--statistics of arrests, courts, prisoners, juvenile delinquency, crime victimization, and public…

Evaluating Presentation Skills of Volunteer Trainers.

ERIC Educational Resources Information Center

Mohan, Donna K.

A systematic method for evaluating the presentation skills of volunteer trainers would enable the discovery of hidden problems. It would also increase individual trainer skills and satisfaction and improve the overall effectiveness of the training program. A first step is to determine the general presentation skills a successful volunteer trainer…

Managing Food Allergies in School.

ERIC Educational Resources Information Center

Munoz-Furlong, Anne

1997-01-01

The number of students with food allergies is increasing, with peanuts the leading culprit. Peer pressure and allergens hidden in baked goods can pose problems for school staff. Children with documented life-threatening allergies are covered by the Americans with Disabilities Act. Principals should reassure parents and use Section 504 guidelines…

Off the Wall?

ERIC Educational Resources Information Center

Rittner-Heir, Robbin

2003-01-01

Vandalism is the main problem in maintaining school washrooms. Ways to help schools meet this challenge include designing washrooms with hidden moving parts to cut down on vandalism and making toilet partitions of solid polyethylene plastic which is virtually indestructible, hard to deface, and easy to clean. The article suggests it is worth…

Innovations in the Teaching of Behavioral Sciences in the Preclinical Curriculum

ERIC Educational Resources Information Center

Mack, Kevin

2005-01-01

Objective: In problem-based learning curricula, cases are usually clustered into identified themes or organ systems. While this method of aggregating cases presents clear advantages in terms of resource alignment and student focus, an alternative "hidden cluster" approach provides rich opportunities for content integration. Method: The author…

Sexuality and the Curriculum: The Politics and Practices of Sexuality Education. Critical Issues in the Curriculum.

ERIC Educational Resources Information Center

Sears, James T., Ed.

This book of essays explores the explicit and hidden curriculum of sexuality from kindergarten through college. The 15 interrelated essays challenge conventional assumptions regarding sexuality and the curriculum by applying non-traditional perspectives to traditionally unresolved problems while proposing specific curricular strategies and…

Hidden Disruptions: Technology and Technological Literacy as Influences on Professional Writing Student Teams

ERIC Educational Resources Information Center

McGrady, Lisa

2010-01-01

This article reports on a study designed to explore whether and in what ways individual students' technological literacies might impact collaborative teams. For the collaborative team discussed in this article, technological literacy--specifically, limited repertoires for solving technical problems, clashes between document management strategies,…

A fast and accurate online sequential learning algorithm for feedforward networks.

PubMed

Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N

2006-11-01

In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.

Probability Sampling Method for a Hidden Population Using Respondent-Driven Sampling: Simulation for Cancer Survivors.

PubMed

Jung, Minsoo

2015-01-01

When there is no sampling frame within a certain group or the group is concerned that making its population public would bring social stigma, we say the population is hidden. It is difficult to approach this kind of population survey-methodologically because the response rate is low and its members are not quite honest with their responses when probability sampling is used. The only alternative known to address the problems caused by previous methods such as snowball sampling is respondent-driven sampling (RDS), which was developed by Heckathorn and his colleagues. RDS is based on a Markov chain, and uses the social network information of the respondent. This characteristic allows for probability sampling when we survey a hidden population. We verified through computer simulation whether RDS can be used on a hidden population of cancer survivors. According to the simulation results of this thesis, the chain-referral sampling of RDS tends to minimize as the sample gets bigger, and it becomes stabilized as the wave progresses. Therefore, it shows that the final sample information can be completely independent from the initial seeds if a certain level of sample size is secured even if the initial seeds were selected through convenient sampling. Thus, RDS can be considered as an alternative which can improve upon both key informant sampling and ethnographic surveys, and it needs to be utilized for various cases domestically as well.

Hidden Genetic Variation in LCA9-Associated Congenital Blindness Explained by 5'UTR Mutations and Copy-Number Variations of NMNAT1.

PubMed

Coppieters, Frauke; Todeschini, Anne Laure; Fujimaki, Takuro; Baert, Annelot; De Bruyne, Marieke; Van Cauwenbergh, Caroline; Verdin, Hannah; Bauwens, Miriam; Ongenaert, Maté; Kondo, Mineo; Meire, Françoise; Murakami, Akira; Veitia, Reiner A; Leroy, Bart P; De Baere, Elfride

2015-12-01

Leber congenital amaurosis (LCA) is a severe autosomal-recessive retinal dystrophy leading to congenital blindness. A recently identified LCA gene is NMNAT1, located in the LCA9 locus. Although most mutations in blindness genes are coding variations, there is accumulating evidence for hidden noncoding defects or structural variations (SVs). The starting point of this study was an LCA9-associated consanguineous family in which no coding mutations were found in the LCA9 region. Exploring the untranslated regions of NMNAT1 revealed a novel homozygous 5'UTR variant, c.-70A>T. Moreover, an adjacent 5'UTR variant, c.-69C>T, was identified in a second consanguineous family displaying a similar phenotype. Both 5'UTR variants resulted in decreased NMNAT1 mRNA abundance in patients' lymphocytes, and caused decreased luciferase activity in human retinal pigment epithelial RPE-1 cells. Second, we unraveled pseudohomozygosity of a coding NMNAT1 mutation in two unrelated LCA patients by the identification of two distinct heterozygous partial NMNAT1 deletions. Molecular characterization of the breakpoint junctions revealed a complex Alu-rich genomic architecture. Our study uncovered hidden genetic variation in NMNAT1-associated LCA and emphasized a shift from coding to noncoding regulatory mutations and repeat-mediated SVs in the molecular pathogenesis of heterogeneous recessive disorders such as hereditary blindness. © 2015 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

Minding the gap: Children's difficulty conceptualizing spatial intervals as linear measurement units.

PubMed

Solomon, Tracy L; Vasilyeva, Marina; Huttenlocher, Janellen; Levine, Susan C

2015-11-01

Understanding measurement units is critical to mathematics and science learning, but it is a topic that American students find difficult. In 3 studies, we investigated the challenges underlying this difficulty in kindergarten and second grade by comparing performance on different versions of a linear measurement task. Children measured crayons that were either aligned or shifted relative to the left edge of either a continuous ruler or a row of discrete units. The alignment (aligned, shifted) and the measuring tool (ruler, discrete units) were crossed to form 4 types of problems. Study 1 showed good performance in both grades on both types of aligned problems as well as on the shifted problems with discrete units. In contrast, performance was at chance on the shifted ruler problems. Study 2 showed that performance on shifted discrete unit problems declined when numbers were placed on the units, particularly for kindergarteners, suggesting that on the shifted ruler problems, the presence of numbers may have contributed to children's difficulty. However, Study 3 showed that the difficulty on the shifted ruler problems persisted even when the numbers were removed from the ruler. Taken together, these findings suggest that there are multiple challenges to understanding measurement, but that a key challenge is conceptualizing the ruler as a set of countable spatial interval units. (c) 2015 APA, all rights reserved).

Learning to classify in large committee machines

NASA Astrophysics Data System (ADS)

O'kane, Dominic; Winther, Ole

1994-10-01

The ability of a two-layer neural network to learn a specific non-linearly-separable classification task, the proximity problem, is investigated using a statistical mechanics approach. Both the tree and fully connected architectures are investigated in the limit where the number K of hidden units is large, but still much smaller than the number N of inputs. Both have continuous weights. Within the replica symmetric ansatz, we find that for zero temperature training, the tree architecture exhibits a strong overtraining effect. For nonzero temperature the asymptotic error is lowered, but it is still higher than the corresponding value for the simple perceptron. The fully connected architecture is considered for two regimes. First, for a finite number of examples we find a symmetry among the hidden units as each performs equally well. The asymptotic generalization error is finite, and minimal for T-->∞ where it goes to the same value as for the simple perceptron. For a large number of examples we find a continuous transition to a phase with broken hidden-unit symmetry, which has an asymptotic generalization error equal to zero.

Reinforcement learning state estimator.

PubMed

Morimoto, Jun; Doya, Kenji

2007-03-01

In this study, we propose a novel use of reinforcement learning for estimating hidden variables and parameters of nonlinear dynamical systems. A critical issue in hidden-state estimation is that we cannot directly observe estimation errors. However, by defining errors of observable variables as a delayed penalty, we can apply a reinforcement learning frame-work to state estimation problems. Specifically, we derive a method to construct a nonlinear state estimator by finding an appropriate feedback input gain using the policy gradient method. We tested the proposed method on single pendulum dynamics and show that the joint angle variable could be successfully estimated by observing only the angular velocity, and vice versa. In addition, we show that we could acquire a state estimator for the pendulum swing-up task in which a swing-up controller is also acquired by reinforcement learning simultaneously. Furthermore, we demonstrate that it is possible to estimate the dynamics of the pendulum itself while the hidden variables are estimated in the pendulum swing-up task. Application of the proposed method to a two-linked biped model is also presented.

The Effect of Shift Work on Quality and Stability of Marital Relations.

ERIC Educational Resources Information Center

White, Lynn; Keith, Bruce

1990-01-01

Interviewed a national panel of 1,668 married women and men in 1980 and 1983 to assess effects of shift work on 6 measures of marital quality (marital happiness, interaction, disagreements, general problems, sexual problems, and child-related problems) and probability of divorce. Results suggested that shift work has a modest but general adverse…

Analysis of single ion channel data incorporating time-interval omission and sampling

PubMed Central

The, Yu-Kai; Timmer, Jens

2005-01-01

Hidden Markov models are widely used to describe single channel currents from patch-clamp experiments. The inevitable anti-aliasing filter limits the time resolution of the measurements and therefore the standard hidden Markov model is not adequate anymore. The notion of time-interval omission has been introduced where brief events are not detected. The developed, exact solutions to this problem do not take into account that the measured intervals are limited by the sampling time. In this case the dead-time that specifies the minimal detectable interval length is not defined unambiguously. We show that a wrong choice of the dead-time leads to considerably biased estimates and present the appropriate equations to describe sampled data. PMID:16849220

A simple method to derive bounds on the size and to train multilayer neural networks

NASA Technical Reports Server (NTRS)

Sartori, Michael A.; Antsaklis, Panos J.

1991-01-01

A new derivation is presented for the bounds on the size of a multilayer neural network to exactly implement an arbitrary training set; namely, the training set can be implemented with zero error with two layers and with the number of the hidden-layer neurons equal to no.1 is greater than p - 1. The derivation does not require the separation of the input space by particular hyperplanes, as in previous derivations. The weights for the hidden layer can be chosen almost arbitrarily, and the weights for the output layer can be found by solving no.1 + 1 linear equations. The method presented exactly solves (M), the multilayer neural network training problem, for any arbitrary training set.

Revealing the Hidden Water Budget of an Alpine Volcanic Watershed Using a Bayesian Mixing Model

NASA Astrophysics Data System (ADS)

Markovich, K. H.; Arumi, J. L.; Dahlke, H. E.; Fogg, G. E.

2017-12-01

Climate change is altering alpine water budgets in observable ways, such as snow melting sooner or falling as rain, but also in hidden ways, such as shifting recharge timing and increased evapotranspiration demand leading to diminished summer low flows. The combination of complex hydrogeology and sparse availability of data make it difficult to predict the direction or magnitude of shifts in alpine water budgets, and thus difficult to inform decision-making. We present a data sparse watershed in the Andes Mountains of central Chile in which complex geology, interbasin flows, and surface water-groundwater interactions impede our ability to fully describe the water budget. We collected water samples for stable isotopes and major anions and cations, over the course of water year 2016-17 to characterize the spatial and temporal variability in endmember signatures (snow, rain, and groundwater). We use a Bayesian Hierarchical Model (BHM) to explicitly incorporate uncertainty and prior information into a mixing model, and predict the proportional contribution of snow, rain, and groundwater to streamflow throughout the year for the full catchment as well as its two sub-catchments. Preliminary results suggest that streamflow is likely more rainfall-dominated than previously thought, which not only alters our projections of climate change impacts, but make this watershed a potential example for other watersheds undergoing a snow to rain transition. Understanding how these proportions vary in space and time will help us elucidate key information on stores, fluxes, and timescales of water flow for improved current and future water resource management.

Search for a hidden strange baryon-meson bound state from ϕ production in a nuclear medium

NASA Astrophysics Data System (ADS)

Gao, Haiyan; Huang, Hongxia; Liu, Tianbo; Ping, Jialun; Wang, Fan; Zhao, Zhiwen

2017-05-01

We investigate the hidden strange light baryon-meson system. With the resonating-group method, two bound states, η'-N and ϕ -N , are found in the quark delocalization color screening model. Focusing on the ϕ -N bound state around 1950 MeV, we obtain the total decay width of about 4 MeV by calculating the phase shifts in the resonance scattering processes. To study the feasibility of an experimental search for the ϕ -N bound state, we perform a Monte Carlo simulation of the bound state production with an electron beam and a gold target. In the simulation, we use the CLAS12 detector with the Forward Tagger and the BONUS12 detector in Hall B at Jefferson Lab. Both the signal and the background channels are estimated. We demonstrate that the signal events can be separated from the background with some momentum cuts. Therefore it is feasible to experimentally search for the ϕ -N bound state through the near threshold ϕ meson production from heavy nuclei.

Shift-, rotation-, and scale-invariant shape recognition system using an optical Hough transform

NASA Astrophysics Data System (ADS)

Schmid, Volker R.; Bader, Gerhard; Lueder, Ernst H.

1998-02-01

We present a hybrid shape recognition system with an optical Hough transform processor. The features of the Hough space offer a separate cancellation of distortions caused by translations and rotations. Scale invariance is also provided by suitable normalization. The proposed system extends the capabilities of Hough transform based detection from only straight lines to areas bounded by edges. A very compact optical design is achieved by a microlens array processor accepting incoherent light as direct optical input and realizing the computationally expensive connections massively parallel. Our newly developed algorithm extracts rotation and translation invariant normalized patterns of bright spots on a 2D grid. A neural network classifier maps the 2D features via a nonlinear hidden layer onto the classification output vector. We propose initialization of the connection weights according to regions of activity specifically assigned to each neuron in the hidden layer using a competitive network. The presented system is designed for industry inspection applications. Presently we have demonstrated detection of six different machined parts in real-time. Our method yields very promising detection results of more than 96% correctly classified parts.

Detecting Hidden Diversification Shifts in Models of Trait-Dependent Speciation and Extinction.

PubMed

Beaulieu, Jeremy M; O'Meara, Brian C

2016-07-01

The distribution of diversity can vary considerably from clade to clade. Attempts to understand these patterns often employ state-dependent speciation and extinction models to determine whether the evolution of a particular novel trait has increased speciation rates and/or decreased extinction rates. It is still unclear, however, whether these models are uncovering important drivers of diversification, or whether they are simply pointing to more complex patterns involving many unmeasured and co-distributed factors. Here we describe an extension to the popular state-dependent speciation and extinction models that specifically accounts for the presence of unmeasured factors that could impact diversification rates estimated for the states of any observed trait, addressing at least one major criticism of BiSSE (Binary State Speciation and Extinction) methods. Specifically, our model, which we refer to as HiSSE (Hidden State Speciation and Extinction), assumes that related to each observed state in the model are "hidden" states that exhibit potentially distinct diversification dynamics and transition rates than the observed states in isolation. We also demonstrate how our model can be used as character-independent diversification models that allow for a complex diversification process that is independent of the evolution of a character. Under rigorous simulation tests and when applied to empirical data, we find that HiSSE performs reasonably well, and can at least detect net diversification rate differences between observed and hidden states and detect when diversification rate differences do not correlate with the observed states. We discuss the remaining issues with state-dependent speciation and extinction models in general, and the important ways in which HiSSE provides a more nuanced understanding of trait-dependent diversification. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Naturalness of Electroweak Symmetry Breaking while Waiting for the LHC

NASA Astrophysics Data System (ADS)

Espinosa, J. R.

2007-06-01

After revisiting the hierarchy problem of the Standard Model and its implications for the scale of New Physics, I consider the finetuning problem of electroweak symmetry breaking in several scenarios beyond the Standard Model: SUSY, Little Higgs and "improved naturalness" models. The main conclusions are that: New Physics should appear on the reach of the LHC; some SUSY models can solve the hierarchy problem with acceptable residual tuning; Little Higgs models generically suffer from large tunings, many times hidden; and, finally, that "improved naturalness" models do not generically improve the naturalness of the SM.

Modelling with Difference Equations Supported by GeoGebra: Exploring the Kepler Problem

ERIC Educational Resources Information Center

Kovacs, Zoltan

2010-01-01

The use of difference and differential equations in the modelling is a topic usually studied by advanced students in mathematics. However difference and differential equations appear in the school curriculum in many direct or hidden ways. Difference equations first enter in the curriculum when studying arithmetic sequences. Moreover Newtonian…

Improving School Attendance through Collaboration: A Catalyst for Community Involvement and Change

ERIC Educational Resources Information Center

Childs, Joshua; Grooms, Ain A.

2018-01-01

Chronic absenteeism is often referred to as a problem hidden in plain sight (Chang & Romero, 2008). In recent years, more communities around the United States have been intentional on improving student attendance and limiting the impact of chronic absenteeism. Using qualitative interviews, we sought to understand how one community was…

Curricular Orientations in Elementary School Music: Roles, Pedagogies, and Values.

ERIC Educational Resources Information Center

Bresler, Liora

1996-01-01

Explores the day-to-day music curriculum in three elementary schools. Identifies three orientations toward the role of music education: (1) the functional, based on traditional academic goals and content; (2) the complementary, relegating music to a hidden curriculum; and (3) the expansive, focusing on enhancing perceptual and problem-solving…

Relational Aggression among Boys: Blind Spots and Hidden Dramas

ERIC Educational Resources Information Center

Eriksen, Ingunn Marie; Lyng, Selma Therese

2018-01-01

Although boys too are involved in relational aggression, their experiences are overshadowed by the focus on relational aggression among girls. This paradox mirrors the empirical puzzle that forms the starting point for this article: while teachers saw relational aggression as a 'girl problem', we found a vast undercurrent of relational aggression…

Child Abuse and Neglect in Japan: Coin-Operated-Locker Babies.

ERIC Educational Resources Information Center

Kouno, Akihisa; Johnson, Charles F.

1995-01-01

This paper reviews Japan's child abuse/neglect history, including the incidence of "coin-operated-locker babies," where murdered infants are hidden in railway and airport lockers, and actions taken to reduce this problem. The incidence of child abuse in Japan and the United States is compared, and social influences on the number of…

Is Your School a Dumping Ground?: Hidden Hazards You Can Identify and Eliminate.

ERIC Educational Resources Information Center

Cronin-Jones, Linda L.

1992-01-01

Describes how teachers and students can conduct a schoolwide hazardous waste survey. The activity is an introduction to hazardous waste management and is useful in general physical science, chemistry, and environmental science classes. Two activity worksheets are provided. Explains how schools can clean up hazardous waste problems. (PR)

The Hidden Curriculum of Whiteness: White Teachers, White Territory, and White Community.

ERIC Educational Resources Information Center

Allen, Ricky Lee

This paper suggests that space and spatiality are major features of racial identity and the formation of student resistance. It brings together critical studies of "Whiteness," human territoriality, and theories of resistance in education. The problems between white teachers and students of color can be understood better through a combination of…

Using Graphing to Reveal the Hidden Transformations in Palindrome (and Other Types of) Licence Plates

ERIC Educational Resources Information Center

Nivens, Ryan Andrew

2016-01-01

This article provides a range of activities designed to engage students in using an early form of graphing. While the "Australian Curriculum: Mathematics" (2014) highlights understanding, fluency, problem-solving, and reasoning, the National Research Council (2001) describes five strands of mathematical proficiency, with the additional…

User's Guide for SKETCH

NASA Technical Reports Server (NTRS)

Hedgley, David R., Jr.

2000-01-01

A user's guide for the computer program SKETCH is presented on this disk. SKETCH solves a popular problem in computer graphics-the removal of hidden lines from images of solid objects. Examples and illustrations are included in the guide. Also included is the SKETCH program, so a user can incorporate the information into a particular software system.

Non-Disclosing Students with Disabilities or Learning Challenges: Characteristics and Size of a Hidden Population

ERIC Educational Resources Information Center

Grimes, Susan; Scevak, Jill; Southgate, Erica; Buchanan, Rachel

2017-01-01

Internationally, university students with disabilities (SWD) are recognised as being under-represented in higher education. They face significant problems accessing appropriate accommodations for their disability. Academic outcomes for this group are lower in terms of achievement and graduation rates. The true size of the SWD group at university…

Investigating a Case of Hidden Misinterpretations of an Additive Word Problem: Structural Substitution

ERIC Educational Resources Information Center

Polotskaia, Elena; Savard, Annie; Freiman, Viktor

2016-01-01

According to numerous studies (Barrouillet & Camos 2002; Brousseau 1988; Chevallard 1988; Riley et al. 1984; Schubauer-Leoni & Ntamakiliro, "Revue Des Sciences de L'éducation," 20(1): 87-113, 1994; Vergnaud 1982; Xin, "The Journal of Educational Research," 100(6):347-360, 2007), a combination of many factors, including…

Personality and Occupational Stress in Elite Performers.

ERIC Educational Resources Information Center

Hamilton, Linda H.; Kella, John J.

Performing Arts Psychology has recently emerged as a unique subspecialty comparable to that of Sports Psychology. Attention has been focused on problems common to all performers (e.g., performance anxiety); however, the various stresses within each art form often remain hidden from view. To assess the psychological aspects of different art forms,…

The Relationship between Teachers' Views about Cultural Values and Critical Pedagogy

ERIC Educational Resources Information Center

Yilmaz, Kursad; Altinkurt, Yahya; Ozciftci, Elif

2016-01-01

Problem Statement: Known as basic elements directing individuals' lives, cultural values are hidden cultural elements that influence all evaluations and perceptions. Values, in that sense, are elements individuals are aware of and provide the answer to the "what should I do?" feeling (Schein, 1992). Critical pedagogy is a project based…

Journal of Undergraduate Psychological Research, Vol. 1, No. 1.

ERIC Educational Resources Information Center

Ladd, Sandra L., Ed.; Hughmanick, Michael, Ed.

1974-01-01

Articles resulting from studies conducted by college undergraduates in all areas of experimental psychology are provided, together with abstracts of other papers authored by students in the field of study. The articles are: The Influence of SET on Solving Hidden-Word Problems by Lana I. Boutacoff; Violation of Personal Space in Deviant Adolescents…

Credits and Credibility: Educating Professionals for Cultural Sensitivity.

ERIC Educational Resources Information Center

Morgan, Elizabeth; Weigel, Van

A four-part discussion on cultural sensitivity and good listening skills in development professionals is presented. It is noted that there is much in their educational regimen which militates against developing these habits of mind. It is hypothesized that much of this problem resides in the hidden cultural meanings of professionalism in general…

Processes Underlying Young Children's Spatial Orientation during Movement.

ERIC Educational Resources Information Center

Bremner, J. Gavin; And Others

1994-01-01

Tested children 18 months to 4 years for their ability to relocate a hidden object after self-produced movement around an array of 4 locations. Children encountered no specific difficulty in coordinating dimensions, or they solved the task without recourse to such a system. They also appeared to change strategy when the problem requires more…

Bidirectional extreme learning machine for regression problem and its learning effectiveness.

PubMed

Yang, Yimin; Wang, Yaonan; Yuan, Xiaofang

2012-09-01

It is clear that the learning effectiveness and learning speed of neural networks are in general far slower than required, which has been a major bottleneck for many applications. Recently, a simple and efficient learning method, referred to as extreme learning machine (ELM), was proposed by Huang , which has shown that, compared to some conventional methods, the training time of neural networks can be reduced by a thousand times. However, one of the open problems in ELM research is whether the number of hidden nodes can be further reduced without affecting learning effectiveness. This brief proposes a new learning algorithm, called bidirectional extreme learning machine (B-ELM), in which some hidden nodes are not randomly selected. In theory, this algorithm tends to reduce network output error to 0 at an extremely early learning stage. Furthermore, we find a relationship between the network output error and the network output weights in the proposed B-ELM. Simulation results demonstrate that the proposed method can be tens to hundreds of times faster than other incremental ELM algorithms.

Rule extraction from minimal neural networks for credit card screening.

PubMed

Setiono, Rudy; Baesens, Bart; Mues, Christophe

2011-08-01

While feedforward neural networks have been widely accepted as effective tools for solving classification problems, the issue of finding the best network architecture remains unresolved, particularly so in real-world problem settings. We address this issue in the context of credit card screening, where it is important to not only find a neural network with good predictive performance but also one that facilitates a clear explanation of how it produces its predictions. We show that minimal neural networks with as few as one hidden unit provide good predictive accuracy, while having the added advantage of making it easier to generate concise and comprehensible classification rules for the user. To further reduce model size, a novel approach is suggested in which network connections from the input units to this hidden unit are removed by a very straightaway pruning procedure. In terms of predictive accuracy, both the minimized neural networks and the rule sets generated from them are shown to compare favorably with other neural network based classifiers. The rules generated from the minimized neural networks are concise and thus easier to validate in a real-life setting.

Multilayer neural networks for reduced-rank approximation.

PubMed

Diamantaras, K I; Kung, S Y

1994-01-01

This paper is developed in two parts. First, the authors formulate the solution to the general reduced-rank linear approximation problem relaxing the invertibility assumption of the input autocorrelation matrix used by previous authors. The authors' treatment unifies linear regression, Wiener filtering, full rank approximation, auto-association networks, SVD and principal component analysis (PCA) as special cases. The authors' analysis also shows that two-layer linear neural networks with reduced number of hidden units, trained with the least-squares error criterion, produce weights that correspond to the generalized singular value decomposition of the input-teacher cross-correlation matrix and the input data matrix. As a corollary the linear two-layer backpropagation model with reduced hidden layer extracts an arbitrary linear combination of the generalized singular vector components. Second, the authors investigate artificial neural network models for the solution of the related generalized eigenvalue problem. By introducing and utilizing the extended concept of deflation (originally proposed for the standard eigenvalue problem) the authors are able to find that a sequential version of linear BP can extract the exact generalized eigenvector components. The advantage of this approach is that it's easier to update the model structure by adding one more unit or pruning one or more units when the application requires it. An alternative approach for extracting the exact components is to use a set of lateral connections among the hidden units trained in such a way as to enforce orthogonality among the upper- and lower-layer weights. The authors call this the lateral orthogonalization network (LON) and show via theoretical analysis-and verify via simulation-that the network extracts the desired components. The advantage of the LON-based model is that it can be applied in a parallel fashion so that the components are extracted concurrently. Finally, the authors show the application of their results to the solution of the identification problem of systems whose excitation has a non-invertible autocorrelation matrix. Previous identification methods usually rely on the invertibility assumption of the input autocorrelation, therefore they can not be applied to this case.

Shift work--problems and its impact on female nurses in Udaipur, Rajasthan India.

PubMed

Rathore, H; Shukla, K; Singh, S; Tiwari, G

2012-01-01

Abstract : There is good evidence that shift work has negative effects on workers health, safety and performance. It is quite appropriate that attention is paid to this very important feature of socio-technical systems, which may adversely affect mental and physical health, social life and safety of shift workers. Research into the impact of shift work on professionals has consistently identified a range of negative outcomes in physical, psychological, and social domains (Akerstedt, 1988; Costa, Lievore, Casaletti, Gaffuri, & Folkard, 1989; Kogi, 2005; Paley & Tepas, 1994). Hospitals, the biggest employer in the health care field, employ more night shift workers than any other industry. It can therefore be inferred that in medical domain high percentage of workforce may be affected by problems related to shift work. Thus the present study will provide knowledge base for the problems faced by the female nurses. The present study was undertaken with an objective of getting an insight into the problems faced by female nurses in shift work. . It was found that the female nurses in India worked on roaster pattern of change in shift every seven days. They did not have a say in the change of duties, it could only be done on mutual grounds. Partners of younger group did not much adjust to their shift pattern this created stress among the nurses.The results showed that the female nurses in both the age groups i.e. 30-45 years and 45-60 years faced many problems related to health and well being, fatigue, social and domestic situations. They could not give much time to their children in particular. Travelling in nights was risky for them. Common problem was the insufficient sleep during night shifts. The nurses had to cater to the needs of the family, children in particular along with the adjustments to be made due to shift work. They had to sometimes do the night duties and attend social functions as a part of their duty. Children and husband in some cases did not cooperate this lead to frustration. When asked as to whether they would could shift job if they get regular one more than 50 % said yes this means that there need to be come training and intervention for the shift workers and their family so that the problems faced and their impact on personal health of the female nurses could be reduced.

Relativistic properties of a molecule: energy, linear momentum, angular momentum and boost momentum to order 1/c 2

NASA Astrophysics Data System (ADS)

Cameron, Robert P.; Cotter, J. P.

2018-05-01

We give an explicit and general description of the energy, linear momentum, angular momentum and boost momentum of a molecule to order 1/c 2, where it necessary to take account of kinetic contributions made by the electrons and nuclei as well as electromagnetic contributions made by the intramolecular field. A wealth of interesting subtleties are encountered that are not seen at order 1/c 0, including relativistic Hall shifts, anomalous velocities and hidden momenta. Some of these have well known analogues in solid state physics.

Increased diversification rates follow shifts to bisexuality in liverworts.

PubMed

Laenen, Benjamin; Machac, Antonin; Gradstein, S Robbert; Shaw, Blanka; Patiño, Jairo; Désamoré, Aurélie; Goffinet, Bernard; Cox, Cymon J; Shaw, A Jonathan; Vanderpoorten, Alain

2016-05-01

Shifts in sexual systems are one of the key drivers of species diversification. In contrast to angiosperms, unisexuality prevails in bryophytes. Here, we test the hypotheses that bisexuality evolved from an ancestral unisexual condition and is a key innovation in liverworts. We investigate whether shifts in sexual systems influence diversification using hidden state speciation and extinction analysis (HiSSE). This new method compares the effects of the variable of interest to the best-fitting latent variable, yielding robust and conservative tests. We find that the transitions in sexual systems are significantly biased toward unisexuality, even though bisexuality is coupled with increased diversification. Sexual systems are strongly conserved deep within the liverwort tree but become much more labile toward the present. Bisexuality appears to be a key innovation in liverworts. Its effects on diversification are presumably mediated by the interplay of high fertilization rates, massive spore production and long-distance dispersal, which may separately or together have facilitated liverwort speciation, suppressed their extinction, or both. Importantly, shifts in liverwort sexual systems have the opposite effect when compared to angiosperms, leading to contrasting diversification patterns between the two groups. The high prevalence of unisexuality among liverworts suggests, however, a strong selection for sexual dimorphism. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

The importance of pollen chemistry in evolutionary host shifts of bees

PubMed Central

Vanderplanck, Maryse; Vereecken, Nicolas J.; Grumiau, Laurent; Esposito, Fabiana; Lognay, Georges; Wattiez, Ruddy; Michez, Denis

2017-01-01

Although bee-plant associations are generally maintained through speciation processes, host shifts have occurred during evolution. Understanding shifts between both phylogenetically and morphologically unrelated plants (i.e., host-saltation) is especially important since they could have been key processes in the origin and radiation of bees. Probably far from being a random process, such host-saltation might be driven by hidden constraints associated with plant traits. We selected two clades of oligolectic bees (i.e., Colletes succinctus group and Melitta leporina group) foraging on co-flowering but unrelated host-plants to test this hypothesis. We analyzed floral scent, floral color and chemical composition of pollen from host and non-host plants of these two clades. We did not find evidence for host-plant evolution in the Melitta leporina group driven by one of the assayed floral traits. On the contrary, hosts of the C. succinctus group display similar primary nutritive content of pollen (i.e., amino acids and sterols) but not similar floral scent or color, suggesting that shared pollen chemistry probably mediates saltation in this clade. Our study revealed that constraints shaping floral associations are diverse and clearly depend on species life-history traits, but evidence suggests that pollen chemistry may act as a major floral filter and guide evolutionary host-shifts. PMID:28216663

Field Extension of Real Values of Physical Observables in Classical Theory can Help Attain Quantum Results

NASA Astrophysics Data System (ADS)

Wang, Hai; Kumar, Asutosh; Cho, Minhyung; Wu, Junde

2018-04-01

Physical quantities are assumed to take real values, which stems from the fact that an usual measuring instrument that measures a physical observable always yields a real number. Here we consider the question of what would happen if physical observables are allowed to assume complex values. In this paper, we show that by allowing observables in the Bell inequality to take complex values, a classical physical theory can actually get the same upper bound of the Bell expression as quantum theory. Also, by extending the real field to the quaternionic field, we can puzzle out the GHZ problem using local hidden variable model. Furthermore, we try to build a new type of hidden-variable theory of a single qubit based on the result.

Interferometric Computation Beyond Quantum Theory

NASA Astrophysics Data System (ADS)

Garner, Andrew J. P.

2018-03-01

There are quantum solutions for computational problems that make use of interference at some stage in the algorithm. These stages can be mapped into the physical setting of a single particle travelling through a many-armed interferometer. There has been recent foundational interest in theories beyond quantum theory. Here, we present a generalized formulation of computation in the context of a many-armed interferometer, and explore how theories can differ from quantum theory and still perform distributed calculations in this set-up. We shall see that quaternionic quantum theory proves a suitable candidate, whereas box-world does not. We also find that a classical hidden variable model first presented by Spekkens (Phys Rev A 75(3): 32100, 2007) can also be used for this type of computation due to the epistemic restriction placed on the hidden variable.

Improving the Quality of Alerts and Predicting Intruder's Next Goal with Hidden Colored Petri-Net

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

Yu, Dong; Frincke, Deb A.

2006-06-22

Intrusion detection systems (IDS) often provide poor quality alerts, which are insufficient to support rapid identification of ongoing attacks or predict an intruder’s next likely goal. In this paper, we propose a novel approach to alert post-processing and correlation, the Hidden Colored Petri-Net (HCPN). Different from most other alert correlation methods, our approach treats the alert correlation problem as an inference problem rather than a filter problem. Our approach assumes that the intruder’s actions are unknown to the IDS and can be inferred only from the alerts generated by the IDS sensors. HCPN can describe the relationship between different stepsmore » carried out by intruders, model observations (alerts) and transitions (actions) separately, and associate each token element (system state) with a probability (or confidence). The model is an extension to Colored Petri-Net (CPN) .It is so called “hidden” because the transitions (actions) are not directly observable but can be inferred by looking through the observations (alerts). These features make HCPN especially suitable for discovering intruders’ actions from their partial observations (alerts,) and predicting intruders’ next goal. Our experiments on DARPA evaluation datasets and the attack scenarios from the Grand Challenge Problem (GCP) show that HCPN has promise as a way to reducing false positives and negatives, predicting intruder’s next possible action, uncovering intruders’ intrusion strategies after the attack scenario has happened, and providing confidence scores.« less

Reading and Writing Difficulties--A Problem? EMIR Education and Research.

ERIC Educational Resources Information Center

Ericson, Britta, Ed.

This collection of essays contains a brief description of the symptoms of dyslexia and a definition of the terminology. The meaning of being the mother of a dyslexic child and how to live with this "hidden handicap" are also described. Suggestions regarding how to treat persons with reading and writing difficulties are put forward. After…

Educational Support Group in Changing Caregivers' Psychological Elder Abuse Behavior toward Caring for Institutionalized Elders

ERIC Educational Resources Information Center

Hsieh, Hsiu-Fang; Wang, Jing-Jy; Yen, Maiofen; Liu, Tzu-Ti

2009-01-01

Institutionalized elderly who are frail and dependent are vulnerable to be abused by overwhelmed caregivers especially caregiver psychological abusive behavior is a growing but hidden problem with few evidence-based interventions. The purpose of this study was to examine the effectiveness of an educational support group in alleviating caregiver's…

Hidden Challenges to Education Systems in Transition Economies.

ERIC Educational Resources Information Center

Berryman, Sue E.

This book, published by the World Bank, sounds the alarm for education in Europe and Central Asia (ECA). It describes how the transition from communism to free-market economies has left many countries' educational systems in disarray. At the start of transition, ECA education systems had solved problems that plagued other regions of the world,…

W 4 toda example as hidden Liouville CFT

NASA Astrophysics Data System (ADS)

Furlan, P.; Petkova, V. B.

2017-03-01

We construct correlators in the W 4 Toda 2d conformal field theory for a particular class of representations and demonstrate a relation to a W 2 (Virasoro) theory with different central charge. The relevance of the classical limits of the constructed 3-point functions and braiding matrices to problems in 4d conformal theories is discussed.

Active inference and robot control: a case study

PubMed Central

Nizard, Ange; Friston, Karl; Pezzulo, Giovanni

2016-01-01

Active inference is a general framework for perception and action that is gaining prominence in computational and systems neuroscience but is less known outside these fields. Here, we discuss a proof-of-principle implementation of the active inference scheme for the control or the 7-DoF arm of a (simulated) PR2 robot. By manipulating visual and proprioceptive noise levels, we show under which conditions robot control under the active inference scheme is accurate. Besides accurate control, our analysis of the internal system dynamics (e.g. the dynamics of the hidden states that are inferred during the inference) sheds light on key aspects of the framework such as the quintessentially multimodal nature of control and the differential roles of proprioception and vision. In the discussion, we consider the potential importance of being able to implement active inference in robots. In particular, we briefly review the opportunities for modelling psychophysiological phenomena such as sensory attenuation and related failures of gain control, of the sort seen in Parkinson's disease. We also consider the fundamental difference between active inference and optimal control formulations, showing that in the former the heavy lifting shifts from solving a dynamical inverse problem to creating deep forward or generative models with dynamics, whose attracting sets prescribe desired behaviours. PMID:27683002

Fundamentals of angled-beam ultrasonic NDE for potential characterization of hidden regions of impact damage in composites

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Wertz, John N.; Welter, John T.; Wallentine, Sarah; Lindgren, Eric A.; Kramb, Victoria; Zainey, David

2018-04-01

In this study, the use of angled-beam ultrasonic NDE was explored for the potential characterization of the hidden regions of impact damage in composites. Simulated studies using CIVA FIDEL 2D were used to explore this inspection problem. Quasi-shear (qS) modes can be generated over a wide range of angles and used to reflect off the backwall and interrogate under the top delaminations of impact damage. Secondary probe signals that do propagate normal to the surface were found to be significant under certain probe conditions, and can potentially interfere with weakly scattered signals from within the composite panel. Simulations were used to evaluate the source of the multiple paths of reflections from the edge of a delamination; time-of-flight and amplitude will depend on the depth of the delamination and location of neighboring delaminations. For angled-beam inspections, noise from both the top surface roughness and internal features was found to potentially mask the detection of signals from the edge of delaminations. Lastly, the study explored the potential of generating "guided" waves along the backwall using an angled-beam source and subsequently measuring scattered signals from a far surface crack hidden under a delamination.

Graviweak Unification, Invisible Universe and Dark Energy

NASA Astrophysics Data System (ADS)

Das, C. R.; Laperashvili, L. V.; Tureanu, A.

2013-07-01

We consider a graviweak unification model with the assumption of the existence of a hidden (invisible) sector of our Universe, parallel to the visible world. This Hidden World (HW) is assumed to be a Mirror World (MW) with broken mirror parity. We start with a diffeomorphism invariant theory of a gauge field valued in a Lie algebra g, which is broken spontaneously to the direct sum of the space-time Lorentz algebra and the Yang-Mills algebra: ˜ {g} = {{su}}(2) (grav)L ⊕ {{su}}(2)L — in the ordinary world, and ˜ {g}' = {{su}}(2){' (grav)}R ⊕ {{su}}(2)'R — in the hidden world. Using an extension of the Plebanski action for general relativity, we recover the actions for gravity, SU(2) Yang-Mills and Higgs fields in both (visible and invisible) sectors of the Universe, and also the total action. After symmetry breaking, all physical constants, including the Newton's constants, cosmological constants, Yang-Mills couplings, and other parameters, are determined by a single parameter g present in the initial action, and by the Higgs VEVs. The dark energy problem of this model predicts a too large supersymmetric breaking scale (MSUSY 1010GeV), which is not within the reach of the LHC experiments.

Double Higgs mechanisms, supermassive stable particles and the vacuum energy

NASA Astrophysics Data System (ADS)

Santillán, Osvaldo P.; Gabbanelli, Luciano

2016-07-01

In the present work, a hidden scenario which cast a long-lived superheavy particle A0 and simultaneously an extremely light particle a with mass ma ˜ 10-32-10-33 eV is presented. The potential energy V (a) of the particle a models the vacuum energy density of the universe ρc ≃ 10-47GeV4. On the other hand, the A0 particle may act as superheavy dark matter at present times and the products of its decay may be observed in high energy cosmic ray events. The hidden sector proposed here include light fermions with masses near the neutrino mass mν ˜ 10-2 eV and superheavy ones with masses of the order of the GUT scale, interacting through a hidden SU(2)L interaction which also affects the ordinary sector. The construction of such combined scenario is nontrivial since the presence of light particles may spoil the stability of the heavy particle A0. However, double Higgs mechanisms may be helpful for overcoming this problem. In this context, the stability of the superheavy particle A0 is ensured due to chiral symmetry arguments elaborated in the text.

Biological engineering applications of feedforward neural networks designed and parameterized by genetic algorithms.

PubMed

Ferentinos, Konstantinos P

2005-09-01

Two neural network (NN) applications in the field of biological engineering are developed, designed and parameterized by an evolutionary method based on the evolutionary process of genetic algorithms. The developed systems are a fault detection NN model and a predictive modeling NN system. An indirect or 'weak specification' representation was used for the encoding of NN topologies and training parameters into genes of the genetic algorithm (GA). Some a priori knowledge of the demands in network topology for specific application cases is required by this approach, so that the infinite search space of the problem is limited to some reasonable degree. Both one-hidden-layer and two-hidden-layer network architectures were explored by the GA. Except for the network architecture, each gene of the GA also encoded the type of activation functions in both hidden and output nodes of the NN and the type of minimization algorithm that was used by the backpropagation algorithm for the training of the NN. Both models achieved satisfactory performance, while the GA system proved to be a powerful tool that can successfully replace the problematic trial-and-error approach that is usually used for these tasks.

An Indoor Pedestrian Positioning Method Using HMM with a Fuzzy Pattern Recognition Algorithm in a WLAN Fingerprint System

PubMed Central

Ni, Yepeng; Liu, Jianbo; Liu, Shan; Bai, Yaxin

2016-01-01

With the rapid development of smartphones and wireless networks, indoor location-based services have become more and more prevalent. Due to the sophisticated propagation of radio signals, the Received Signal Strength Indicator (RSSI) shows a significant variation during pedestrian walking, which introduces critical errors in deterministic indoor positioning. To solve this problem, we present a novel method to improve the indoor pedestrian positioning accuracy by embedding a fuzzy pattern recognition algorithm into a Hidden Markov Model. The fuzzy pattern recognition algorithm follows the rule that the RSSI fading has a positive correlation to the distance between the measuring point and the AP location even during a dynamic positioning measurement. Through this algorithm, we use the RSSI variation trend to replace the specific RSSI value to achieve a fuzzy positioning. The transition probability of the Hidden Markov Model is trained by the fuzzy pattern recognition algorithm with pedestrian trajectories. Using the Viterbi algorithm with the trained model, we can obtain a set of hidden location states. In our experiments, we demonstrate that, compared with the deterministic pattern matching algorithm, our method can greatly improve the positioning accuracy and shows robust environmental adaptability. PMID:27618053

A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton

PubMed Central

Das, Raibatak; Cairo, Christopher W.; Coombs, Daniel

2009-01-01

The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation. PMID:19893741

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

PubMed

Pound, Michael P; Atkinson, Jonathan A; Townsend, Alexandra J; Wilson, Michael H; Griffiths, Marcus; Jackson, Aaron S; Bulat, Adrian; Tzimiropoulos, Georgios; Wells, Darren M; Murchie, Erik H; Pridmore, Tony P; French, Andrew P

2017-10-01

In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, hence the motivation for finding a fully automated approach. Deep learning is an emerging field that promises unparalleled results on many data analysis problems. Building on artificial neural networks, deep approaches have many more hidden layers in the network, and hence have greater discriminative and predictive power. We demonstrate the use of such approaches as part of a plant phenotyping pipeline. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping and demonstrate state-of-the-art results (>97% accuracy) for root and shoot feature identification and localization. We use fully automated trait identification using deep learning to identify quantitative trait loci in root architecture datasets. The majority (12 out of 14) of manually identified quantitative trait loci were also discovered using our automated approach based on deep learning detection to locate plant features. We have shown deep learning-based phenotyping to have very good detection and localization accuracy in validation and testing image sets. We have shown that such features can be used to derive meaningful biological traits, which in turn can be used in quantitative trait loci discovery pipelines. This process can be completely automated. We predict a paradigm shift in image-based phenotyping bought about by such deep learning approaches, given sufficient training sets. © The Authors 2017. Published by Oxford University Press.

The hidden web and the fentanyl problem: Detection of ocfentanil as an adulterant in heroin.

PubMed

Quintana, Pol; Ventura, Mireia; Grifell, Marc; Palma, Alvaro; Galindo, Liliana; Fornís, Iván; Gil, Cristina; Carbón, Xoán; Caudevilla, Fernando; Farré, Magí; Torrens, Marta

2017-02-01

The popularization of anonymous markets such as Silk Road is challenging current drug policy and may provide a new context for old issues, such as adulteration of heroin with fentanyl derivatives. The aims of this paper are to report the presence of ocfentanil, a novel, potent, non-controlled fentanyl analog, in samples sold as heroin in the hidden web, and to summarize the effects reported by users. In 2015, four samples allegedly bought as heroin in cryptomarkets of the hidden web were sent to Energy Control for analysis. Energy Control is a Spanish harm reduction NGO that offers anonymous drug checking with the purpose of adapting counselling to the specific substances present in the drug and monitor the drug market. Identification was performed by GC/MS and LC/MS/MS. We contacted the submitters of the samples and performed an Internet search to retrieve additional information. One sample contained ocfentanil, caffeine and heroin. Three samples contained the aforementioned substances plus paracetamol. Two out of the four contacted users reported distinct short acting, opioid-like effects. No fora discussion could be found about the effects of ocfentanil, neither web pages nor individuals advertising the substance. We report the presence of a new substance detected in the hidden web as an adulterant of heroin, ocfentanil. It has short acting opioid-like effects, roughly the same potency as fentanyl, and can be injected, snorted or smoked. Severe side effects have been associated with its use, including one death. No discussion about this substance could be found in the Internet, which suggests this substance has not been sold as such. Available data about purities of drugs purchased in cryptomarkets suggest that adulteration is not a severe problem and this agrees with users' perceptions. However, this study suggests that adulteration is a real threat not only at the street level, but also for users that buy substances in cryptomarkets, and suggest the need for harm reduction initiatives in this setting. Copyright © 2016 Elsevier B.V. All rights reserved.

A gratuitous β-Lactamase inducer uncovers hidden active site dynamics of the Staphylococcus aureus BlaR1 sensor domain.

PubMed

Frederick, Thomas E; Peng, Jeffrey W

2018-01-01

Increasing evidence shows that active sites of proteins have non-trivial conformational dynamics. These dynamics include active site residues sampling different local conformations that allow for multiple, and possibly novel, inhibitor binding poses. Yet, active site dynamics garner only marginal attention in most inhibitor design efforts and exert little influence on synthesis strategies. This is partly because synthesis requires a level of atomic structural detail that is frequently missing in current characterizations of conformational dynamics. In particular, while the identity of the mobile protein residues may be clear, the specific conformations they sample remain obscure. Here, we show how an appropriate choice of ligand can significantly sharpen our abilities to describe the interconverting binding poses (conformations) of protein active sites. Specifically, we show how 2-(2'-carboxyphenyl)-benzoyl-6-aminopenicillanic acid (CBAP) exposes otherwise hidden dynamics of a protein active site that binds β-lactam antibiotics. When CBAP acylates (binds) the active site serine of the β-lactam sensor domain of BlaR1 (BlaRS), it shifts the time scale of the active site dynamics to the slow exchange regime. Slow exchange enables direct characterization of inter-converting protein and bound ligand conformations using NMR methods. These methods include chemical shift analysis, 2-d exchange spectroscopy, off-resonance ROESY of the bound ligand, and reduced spectral density mapping. The active site architecture of BlaRS is shared by many β-lactamases of therapeutic interest, suggesting CBAP could expose functional motions in other β-lactam binding proteins. More broadly, CBAP highlights the utility of identifying chemical probes common to structurally homologous proteins to better expose functional motions of active sites.

Software environment for implementing engineering applications on MIMD computers

NASA Technical Reports Server (NTRS)

Lopez, L. A.; Valimohamed, K. A.; Schiff, S.

1990-01-01

In this paper the concept for a software environment for developing engineering application systems for multiprocessor hardware (MIMD) is presented. The philosophy employed is to solve the largest problems possible in a reasonable amount of time, rather than solve existing problems faster. In the proposed environment most of the problems concerning parallel computation and handling of large distributed data spaces are hidden from the application program developer, thereby facilitating the development of large-scale software applications. Applications developed under the environment can be executed on a variety of MIMD hardware; it protects the application software from the effects of a rapidly changing MIMD hardware technology.

Health consequences of shift-work: the case of iranian hospital security personnel.

PubMed

Abedini, Roghayeh; Soltanzadeh, Ahmad; Faghih, Mohammad Amin; Mohammadi, Heidar; Kamalinia, Mojtaba; Mohraz, Majid Habibi; Arassi, Maziyar; Veyseh, Peyman Piran; Aghaei, Hamed; Hosseini, Seyed Younes

2015-01-01

Shift-work, which is an ergonomics issue in workplaces, can negatively affect workers. The security personnel of medical centers in Iran have multiple responsibilities and consequently are exposed to such unwanted situations as observing patients, disputing with patient's attendants, unwanted shift schedules, and being away from family for long periods. This study assessed health problems of Iranian hospital security personnel (shift-worker personnel) using the Survey of Shift-workers (SOS) questionnaire (Persian version). This cross-sectional study was conducted in seven medical centers (4 hospitals and 3 clinics). A total of 416 workers were surveyed: shift-workers (exposed group) (n=209) and non-shift-workers (unexposed group) (n=207). The prevalence of adverse health effects was higher in shift-workers than day-workers. The level of education and mean Body Mass Index (BMI) in shift-workers were significantly higher compared with day-workers. The prevalence of gastrointestinal disorders, cardiovascular and psychological problems were also significantly higher in shift-workers compared with day-workers. Overall, the prevalence of health problems among the security personnel of medical centers was high. Hence, it is recommended that personnel be put under periodic monitoring and receive medical counseling and treatment if there is any disorder.

The free fall of an apple: conceptual subtleties and implications for physics teaching

NASA Astrophysics Data System (ADS)

Assis, A. K. T.; Karam, R. A. S.

2018-05-01

The study of free fall is thoroughly present in physics teaching at all levels. From the point of view of Newtonian dynamics it appears to be extremely simple, as it consists of a two-body problem with a constant force generating a constant acceleration. However, there are several important conceptual subtleties and hidden assumptions involved in this problem, which are rarely discussed in educational settings. In this work we present some of these subtleties and argue that explicitly addressing them has significant pedagogical benefits.

Area-Preserving Diffeomorphisms, W∞ and { U}q [sl(2)] in Chern-Simons Theory and the Quantum Hall System

NASA Astrophysics Data System (ADS)

Kogan, Ian I.

We discuss a quantum { U}q [sl(2)] symmetry in the Landau problem, which naturally arises due to the relation between { U}q [sl(2)] and the group of magnetic translations. The latter is connected with W∞ and area-preserving (symplectic) diffeomorphisms which are the canonical transformations in the two-dimensional phase space. We shall discuss the hidden quantum symmetry in a 2 + 1 gauge theory with the Chern-Simons term and in a quantum Hall system, which are both connected with the Landau problem.

Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the ‘Extreme Learning Machine’ Algorithm

PubMed Central

McDonnell, Mark D.; Tissera, Migel D.; Vladusich, Tony; van Schaik, André; Tapson, Jonathan

2015-01-01

Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the ‘Extreme Learning Machine’ (ELM) approach, which also enables a very rapid training time (∼ 10 minutes). Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random ‘receptive field’ sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems. PMID:26262687

Cascade Error Projection: A Learning Algorithm for Hardware Implementation

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Daud, Taher

1996-01-01

In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.

Probabilistic hazard assessment for skin sensitization potency by dose–response modeling using feature elimination instead of quantitative structure–activity relationships

PubMed Central

McKim, James M.; Hartung, Thomas; Kleensang, Andre; Sá-Rocha, Vanessa

2016-01-01

Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose–response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse outcome pathways (AOP) and the development of tests reflecting these mechanisms. Simple approaches to combine skin sensitization data sets, such as weight of evidence, fail due to problems in information redundancy and high dimension-ality. The problem is further amplified when potency information (dose/response) of hazards would be estimated. Skin sensitization currently serves as the foster child for AOP and ITS development, as legislative pressures combined with a very good mechanistic understanding of contact dermatitis have led to test development and relatively large high-quality data sets. We curated such a data set and combined a recursive variable selection algorithm to evaluate the information available through in silico, in chemico and in vitro assays. Chemical similarity alone could not cluster chemicals’ potency, and in vitro models consistently ranked high in recursive feature elimination. This allows reducing the number of tests included in an ITS. Next, we analyzed with a hidden Markov model that takes advantage of an intrinsic inter-relationship among the local lymph node assay classes, i.e. the monotonous connection between local lymph node assay and dose. The dose-informed random forest/hidden Markov model was superior to the dose-naive random forest model on all data sets. Although balanced accuracy improvement may seem small, this obscures the actual improvement in misclassifications as the dose-informed hidden Markov model strongly reduced "false-negatives" (i.e. extreme sensitizers as non-sensitizer) on all data sets. PMID:26046447

Probabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.

PubMed

Luechtefeld, Thomas; Maertens, Alexandra; McKim, James M; Hartung, Thomas; Kleensang, Andre; Sá-Rocha, Vanessa

2015-11-01

Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose-response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse outcome pathways (AOP) and the development of tests reflecting these mechanisms. Simple approaches to combine skin sensitization data sets, such as weight of evidence, fail due to problems in information redundancy and high dimensionality. The problem is further amplified when potency information (dose/response) of hazards would be estimated. Skin sensitization currently serves as the foster child for AOP and ITS development, as legislative pressures combined with a very good mechanistic understanding of contact dermatitis have led to test development and relatively large high-quality data sets. We curated such a data set and combined a recursive variable selection algorithm to evaluate the information available through in silico, in chemico and in vitro assays. Chemical similarity alone could not cluster chemicals' potency, and in vitro models consistently ranked high in recursive feature elimination. This allows reducing the number of tests included in an ITS. Next, we analyzed with a hidden Markov model that takes advantage of an intrinsic inter-relationship among the local lymph node assay classes, i.e. the monotonous connection between local lymph node assay and dose. The dose-informed random forest/hidden Markov model was superior to the dose-naive random forest model on all data sets. Although balanced accuracy improvement may seem small, this obscures the actual improvement in misclassifications as the dose-informed hidden Markov model strongly reduced " false-negatives" (i.e. extreme sensitizers as non-sensitizer) on all data sets. Copyright © 2015 John Wiley & Sons, Ltd.

Affective State Level Recognition in Naturalistic Facial and Vocal Expressions.

PubMed

Meng, Hongying; Bianchi-Berthouze, Nadia

2014-03-01

Naturalistic affective expressions change at a rate much slower than the typical rate at which video or audio is recorded. This increases the probability that consecutive recorded instants of expressions represent the same affective content. In this paper, we exploit such a relationship to improve the recognition performance of continuous naturalistic affective expressions. Using datasets of naturalistic affective expressions (AVEC 2011 audio and video dataset, PAINFUL video dataset) continuously labeled over time and over different dimensions, we analyze the transitions between levels of those dimensions (e.g., transitions in pain intensity level). We use an information theory approach to show that the transitions occur very slowly and hence suggest modeling them as first-order Markov models. The dimension levels are considered to be the hidden states in the Hidden Markov Model (HMM) framework. Their discrete transition and emission matrices are trained by using the labels provided with the training set. The recognition problem is converted into a best path-finding problem to obtain the best hidden states sequence in HMMs. This is a key difference from previous use of HMMs as classifiers. Modeling of the transitions between dimension levels is integrated in a multistage approach, where the first level performs a mapping between the affective expression features and a soft decision value (e.g., an affective dimension level), and further classification stages are modeled as HMMs that refine that mapping by taking into account the temporal relationships between the output decision labels. The experimental results for each of the unimodal datasets show overall performance to be significantly above that of a standard classification system that does not take into account temporal relationships. In particular, the results on the AVEC 2011 audio dataset outperform all other systems presented at the international competition.

Dark matter versus Mach's principle.

NASA Astrophysics Data System (ADS)

von Borzeszkowski, H.-H.; Treder, H.-J.

1998-02-01

Empirical and theoretical evidence show that the astrophysical problem of dark matter might be solved by a theory of Einstein-Mayer type. In this theory up to global Lorentz rotations the reference system is determined by the motion of cosmic matter. Thus one is led to a "Riemannian space with teleparallelism" realizing a geometric version of the Mach-Einstein doctrine. The field equations of this gravitational theory contain hidden matter terms where the existence of hidden matter is inferred safely from its gravitational effects. It is argued that in the nonrelativistic mechanical approximation they provide an inertia-free mechanics where the inertial mass of a body is induced by the gravitational action of the comic masses. Interpreted form the Newtonian point of view this mechanics shows that the effective gravitational mass of astrophysical objects depends on r such that one expects the existence of dark matter.

Maximum likelihood: Extracting unbiased information from complex networks

NASA Astrophysics Data System (ADS)

Garlaschelli, Diego; Loffredo, Maria I.

2008-07-01

The choice of free parameters in network models is subjective, since it depends on what topological properties are being monitored. However, we show that the maximum likelihood (ML) principle indicates a unique, statistically rigorous parameter choice, associated with a well-defined topological feature. We then find that, if the ML condition is incompatible with the built-in parameter choice, network models turn out to be intrinsically ill defined or biased. To overcome this problem, we construct a class of safely unbiased models. We also propose an extension of these results that leads to the fascinating possibility to extract, only from topological data, the “hidden variables” underlying network organization, making them “no longer hidden.” We test our method on World Trade Web data, where we recover the empirical gross domestic product using only topological information.

SPEECH TO FACULTY OF HARVARD-BOSTON SUMMER PROGRAM AT PREPLANNING MEETINGS.

ERIC Educational Resources Information Center

HAIZLIP, HAROLD

THE AREA TO WHICH THIS GROUP OF TEACHERS WILL BE SENT IS CHARACTERIZED BY ITS LARGE INFLUX OF POOR NEGRO FAMILIES WITH POOR CULTURAL BACKGROUNDS. SOME OF THE PROBLEMS OF THIS AREA WILL REQUIRE A BROAD-SCALE, CAREFULLY ANALYZED, AND PLANNED ATTACK WITHIN AND BY PUBLIC SCHOOLS. EVERY SCHOOL HAS A HIDDEN OR SUBLIMINAL CURRICULUM WHICH TEACHES, IN…

Substance Abuse: A Hidden Problem within the D/deaf and Hard of Hearing Communities

ERIC Educational Resources Information Center

Guthmann, Debra; Graham, Vicki

2004-01-01

Current research indicates that D/deaf and hard of hearing clients seeking treatment for substance abuse often encounter obstacles in receiving the help they need. Many of these obstacles are the result of a lack of knowledge and experience with regard to treating D/deaf and hard of hearing people. Programs designed for hearing people that attempt…

Hidden Dangers within Our Schools: What Are These Safety Problems and How Can We Fix Them? Safety in the Schools

ERIC Educational Resources Information Center

Gunzelmann, Betsy

2005-01-01

Safety in the schools involves much more than metal detectors and disaster plans. Although such catastrophe preparation is necessary, we often overlook less obvious beliefs and practices that put children's everyday safety at risk. According to the well-known pediatrician T. Berry Brazelton and the child psychiatrist Stanley Greenspan (2000), all…

The Role of Hidden Curricula on the Resistance Behavior of Undergraduate Students in Psychological Counseling and Guidance at a Turkish University

ERIC Educational Resources Information Center

Yuksel, Sedat

2006-01-01

Student resistance can be a very important problem for the instructors in universities. Student resistance includes the conscious and preplanned behaviors towards the information presented to them in the classroom and the institutional practices. Typically, student resistance takes the form of passive or active non-compliance with roles and…

Monitoring the Future National Survey Results on Drug Use, 1975-2010. Volume I, Secondary School Students

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2011-01-01

The Monitoring the Future (MTF) study involves an ongoing series of national surveys of American adolescents and adults that has provided the nation with a vital window into the important, but largely hidden, problem behaviors of illegal drug use, alcohol use, tobacco use, anabolic steroid use, and psychotherapeutic drug use. For more than a third…

On the complexity of neural network classifiers: a comparison between shallow and deep architectures.

PubMed

Bianchini, Monica; Scarselli, Franco

2014-08-01

Recently, researchers in the artificial neural network field have focused their attention on connectionist models composed by several hidden layers. In fact, experimental results and heuristic considerations suggest that deep architectures are more suitable than shallow ones for modern applications, facing very complex problems, e.g., vision and human language understanding. However, the actual theoretical results supporting such a claim are still few and incomplete. In this paper, we propose a new approach to study how the depth of feedforward neural networks impacts on their ability in implementing high complexity functions. First, a new measure based on topological concepts is introduced, aimed at evaluating the complexity of the function implemented by a neural network, used for classification purposes. Then, deep and shallow neural architectures with common sigmoidal activation functions are compared, by deriving upper and lower bounds on their complexity, and studying how the complexity depends on the number of hidden units and the used activation function. The obtained results seem to support the idea that deep networks actually implements functions of higher complexity, so that they are able, with the same number of resources, to address more difficult problems.

Neural net classification of x-ray pistachio nut data

NASA Astrophysics Data System (ADS)

Casasent, David P.; Sipe, Michael A.; Schatzki, Thomas F.; Keagy, Pamela M.; Le, Lan Chau

1996-12-01

Classification results for agricultural products are presented using a new neural network. This neural network inherently produces higher-order decision surfaces. It achieves this with fewer hidden layer neurons than other classifiers require. This gives better generalization. It uses new techniques to select the number of hidden layer neurons and adaptive algorithms that avoid other such ad hoc parameter selection problems; it allows selection of the best classifier parameters without the need to analyze the test set results. The agriculture case study considered is the inspection and classification of pistachio nuts using x- ray imagery. Present inspection techniques cannot provide good rejection of worm damaged nuts without rejecting too many good nuts. X-ray imagery has the potential to provide 100% inspection of such agricultural products in real time. Only preliminary results are presented, but these indicate the potential to reduce major defects to 2% of the crop with 1% of good nuts rejected. Future image processing techniques that should provide better features to improve performance and allow inspection of a larger variety of nuts are noted. These techniques and variations of them have uses in a number of other agricultural product inspection problems.

Clustering Multivariate Time Series Using Hidden Markov Models

PubMed Central

Ghassempour, Shima; Girosi, Federico; Maeder, Anthony

2014-01-01

In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs), where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers. PMID:24662996

Detecting network communities beyond assortativity-related attributes

NASA Astrophysics Data System (ADS)

Liu, Xin; Murata, Tsuyoshi; Wakita, Ken

2014-07-01

In network science, assortativity refers to the tendency of links to exist between nodes with similar attributes. In social networks, for example, links tend to exist between individuals of similar age, nationality, location, race, income, educational level, religious belief, and language. Thus, various attributes jointly affect the network topology. An interesting problem is to detect community structure beyond some specific assortativity-related attributes ρ, i.e., to take out the effect of ρ on network topology and reveal the hidden community structures which are due to other attributes. An approach to this problem is to redefine the null model of the modularity measure, so as to simulate the effect of ρ on network topology. However, a challenge is that we do not know to what extent the network topology is affected by ρ and by other attributes. In this paper, we propose a distance modularity, which allows us to freely choose any suitable function to simulate the effect of ρ. Such freedom can help us probe the effect of ρ and detect the hidden communities which are due to other attributes. We test the effectiveness of distance modularity on synthetic benchmarks and two real-world networks.

Extracting duration information in a picture category decoding task using hidden Markov Models

NASA Astrophysics Data System (ADS)

Pfeiffer, Tim; Heinze, Nicolai; Frysch, Robert; Deouell, Leon Y.; Schoenfeld, Mircea A.; Knight, Robert T.; Rose, Georg

2016-04-01

Objective. Adapting classifiers for the purpose of brain signal decoding is a major challenge in brain-computer-interface (BCI) research. In a previous study we showed in principle that hidden Markov models (HMM) are a suitable alternative to the well-studied static classifiers. However, since we investigated a rather straightforward task, advantages from modeling of the signal could not be assessed. Approach. Here, we investigate a more complex data set in order to find out to what extent HMMs, as a dynamic classifier, can provide useful additional information. We show for a visual decoding problem that besides category information, HMMs can simultaneously decode picture duration without an additional training required. This decoding is based on a strong correlation that we found between picture duration and the behavior of the Viterbi paths. Main results. Decoding accuracies of up to 80% could be obtained for category and duration decoding with a single classifier trained on category information only. Significance. The extraction of multiple types of information using a single classifier enables the processing of more complex problems, while preserving good training results even on small databases. Therefore, it provides a convenient framework for online real-life BCI utilizations.

Hidden physics models: Machine learning of nonlinear partial differential equations

NASA Astrophysics Data System (ADS)

Raissi, Maziar; Karniadakis, George Em

2018-03-01

While there is currently a lot of enthusiasm about "big data", useful data is usually "small" and expensive to acquire. In this paper, we present a new paradigm of learning partial differential equations from small data. In particular, we introduce hidden physics models, which are essentially data-efficient learning machines capable of leveraging the underlying laws of physics, expressed by time dependent and nonlinear partial differential equations, to extract patterns from high-dimensional data generated from experiments. The proposed methodology may be applied to the problem of learning, system identification, or data-driven discovery of partial differential equations. Our framework relies on Gaussian processes, a powerful tool for probabilistic inference over functions, that enables us to strike a balance between model complexity and data fitting. The effectiveness of the proposed approach is demonstrated through a variety of canonical problems, spanning a number of scientific domains, including the Navier-Stokes, Schrödinger, Kuramoto-Sivashinsky, and time dependent linear fractional equations. The methodology provides a promising new direction for harnessing the long-standing developments of classical methods in applied mathematics and mathematical physics to design learning machines with the ability to operate in complex domains without requiring large quantities of data.

Interactive computer aided shift scheduling.

PubMed

Gaertner, J

2001-12-01

This paper starts with a discussion of computer aided shift scheduling. After a brief review of earlier approaches, two conceptualizations of this field are introduced: First, shift scheduling as a field that ranges from extremely stable rosters at one pole to rather market-like approaches on the other pole. Unfortunately, already small alterations of a scheduling problem (e.g., the number of groups, the number of shifts) may call for rather different approaches and tools. Second, their environment shapes scheduling problems and scheduling has to be done within idiosyncratic organizational settings. This calls for the amalgamation of scheduling with other tasks (e.g., accounting) and for reflections whether better solutions might become possible by changes in the problem definition (e.g., other service levels, organizational changes). Therefore shift scheduling should be understood as a highly connected problem. Building upon these two conceptualizations, a few examples of software that ease scheduling in some areas of this field are given and future research questions are outlined.

Lesbian health and the assumption of heterosexuality: an organizational perspective.

PubMed

Daley, Andrea

2003-01-01

This study used a qualitative research design to explore hospital policies and practices and the assumption of female heterosexuality. The assumption of heterosexuality is a product of discursive practices that normalize heterosexuality and individualize lesbian sexual identities. Literature indicates that the assumption of female heterosexuality is implicated in both the invisibility and marked visibility of lesbians as service users. This research adds to existing literature by shifting the focus of study from individual to organizational practices and, in so doing, seeks to uncover hidden truths, explore the functional power of language, and allow for the discovery of what we know and--equally as important--how we know.

A Navajo Paradigm for Long Life Happiness--and for Reversing Navajo Language Shift.

ERIC Educational Resources Information Center

House, Deborah

1997-01-01

Describes a Navajo model by which individuals may assume responsibility for reversing Navajo language shift. Argues that reversing Navajo language shift requires that Navajos acknowledge the problem, that Navajo principles of balance and the natural order be applied to the problem, and that Navajo individuals and families make a commitment to…

Shift work-related problems in 16-h night shift nurses (1): Development of an automated data processing system for questionnaires, heart rate, physical activity and posture.

PubMed

Fukuda, H; Takahashi, M; Miki, K; Haratani, T; Kurabayashi, L; Hisanaga, N; Arito, H; Takahashi, H; Egoshi, M; Sakurai, M

1999-04-01

To assess the shift work-related problems associated with a 16-h night shift in a two-shift system, we took the following important factors into consideration; the interaction between circadian rhythms and the longer night shift, the type of morningness and eveningness experienced, the subjective sleep feeling, the subjects' daily behavior, the effectiveness of taking a nap during the long night shift, and finally the effectiveness of using several different kinds of measuring devices. Included among the measuring devices used were a standard questionnaire, repetitive self-assessment of subjective symptoms and daily behavior at short intervals, and a continuous recording of such objective indices as physical activity and heart rate. A potential problem lies in the fact that field studies that use such measures tend to produce a mass of data, and are thus faced with the accompanying technical problem of analyzing such a large amount of data (time, effort and cost). To solve the data analysis problem, we developed an automated data processing system. Through the use of an image scanner with a paper feeder, standard paper, an optical character recognition function and common application software, we were able to analyze a mass of data continuously and automatically within a short time. Our system should prove useful for field studies that produce a large amount of data collected with several different kinds of measuring devices.

Mean-field theory of baryonic matter for QCD in the large Nc and heavy quark mass limits

NASA Astrophysics Data System (ADS)

Adhikari, Prabal; Cohen, Thomas D.

2013-11-01

We discuss theoretical issues pertaining to baryonic matter in the combined heavy-quark and large Nc limits of QCD. Witten's classic argument that baryons and interacting systems of baryons can be described in a mean-field approximation with each of the quarks moving in an average potential due to the remaining quarks is heuristic. It is important to justify this heuristic description for the case of baryonic matter since systems of interacting baryons are intrinsically more complicated than single baryons due to the possibility of hidden color states—states in which the subsystems making up the entire baryon crystal are not color-singlet nucleons but rather colorful states coupled together to make a color-singlet state. In this work, we provide a formal justification of this heuristic prescription. In order to do this, we start by taking the heavy quark limit, thus effectively reducing the problem to a many-body quantum mechanical system. This problem can be formulated in terms of integrals over coherent states, which for this problem are simple Slater determinants. We show that for the many-body problem, the support region for these integrals becomes narrow at large Nc, yielding an energy which is well approximated by a single coherent state—that is a mean-field description. Corrections to the energy are of relative order 1/Nc. While hidden color states are present in the exact state of the heavy quark system, they only influence the interaction energy below leading order in 1/Nc.

Entrepreneurial Regions: Do Macro-Psychological Cultural Characteristics of Regions Help Solve the "Knowledge Paradox" of Economics?

PubMed

Obschonka, Martin; Stuetzer, Michael; Gosling, Samuel D; Rentfrow, Peter J; Lamb, Michael E; Potter, Jeff; Audretsch, David B

2015-01-01

In recent years, modern economies have shifted away from being based on physical capital and towards being based on new knowledge (e.g., new ideas and inventions). Consequently, contemporary economic theorizing and key public policies have been based on the assumption that resources for generating knowledge (e.g., education, diversity of industries) are essential for regional economic vitality. However, policy makers and scholars have discovered that, contrary to expectations, the mere presence of, and investments in, new knowledge does not guarantee a high level of regional economic performance (e.g., high entrepreneurship rates). To date, this "knowledge paradox" has resisted resolution. We take an interdisciplinary perspective to offer a new explanation, hypothesizing that "hidden" regional culture differences serve as a crucial factor that is missing from conventional economic analyses and public policy strategies. Focusing on entrepreneurial activity, we hypothesize that the statistical relation between knowledge resources and entrepreneurial vitality (i.e., high entrepreneurship rates) in a region will depend on "hidden" regional differences in entrepreneurial culture. To capture such "hidden" regional differences, we derive measures of entrepreneurship-prone culture from two large personality datasets from the United States (N = 935,858) and Great Britain (N = 417,217). In both countries, the findings were consistent with the knowledge-culture-interaction hypothesis. A series of nine additional robustness checks underscored the robustness of these results. Naturally, these purely correlational findings cannot provide direct evidence for causal processes, but the results nonetheless yield a remarkably consistent and robust picture in the two countries. In doing so, the findings raise the idea of regional culture serving as a new causal candidate, potentially driving the knowledge paradox; such an explanation would be consistent with research on the psychological characteristics of entrepreneurs.

Constructive Metacognitive Activity Shift in Mathematical Problem Solving

ERIC Educational Resources Information Center

Hastuti, Intan Dwi; Nusantara, Toto; Subanji; Susanto, Hery

2016-01-01

This study aims to describe the constructive metacognitive activity shift of eleventh graders in solving a mathematical problem. Subjects in this study were 10 students in grade 11 of SMAN 1 Malang. They were divided into 4 groups. Three types of metacognitive activity undertaken by students when completing mathematical problem are awareness,…

Hidden momentum of electrons, nuclei, atoms, and molecules

NASA Astrophysics Data System (ADS)

Cameron, Robert P.; Cotter, J. P.

2018-04-01

We consider the positions and velocities of electrons and spinning nuclei and demonstrate that these particles harbour hidden momentum when located in an electromagnetic field. This hidden momentum is present in all atoms and molecules, however it is ultimately canceled by the momentum of the electromagnetic field. We point out that an electron vortex in an electric field might harbour a comparatively large hidden momentum and recognize the phenomenon of hidden hidden momentum.

The Hidden Diversity of Flagellated Protists in Soil.

PubMed

Venter, Paul Christiaan; Nitsche, Frank; Arndt, Hartmut

2018-07-01

Protists are among the most diverse and abundant eukaryotes in soil. However, gaps between described and sequenced protist morphospecies still present a pending problem when surveying environmental samples for known species using molecular methods. The number of sequences in the molecular PR 2 database (∼130,000) is limited compared to the species richness expected (>1 million protist species) - limiting the recovery rate. This is important, since high throughput sequencing (HTS) methods are used to find associative patterns between functional traits, taxa and environmental parameters. We performed HTS to survey soil flagellates in 150 grasslands of central Europe, and tested the recovery rate of ten previously isolated and cultivated cercomonad species, among locally found diversity. We recovered sequences for reference soil flagellate species, but also a great number of their phylogenetically evaluated genetic variants, among rare and dominant taxa with presumably own biogeography. This was recorded among dominant (cercozoans, Sandona), rare (apusozoans) and a large hidden diversity of predominantly aquatic protists in soil (choanoflagellates, bicosoecids) often forming novel clades associated with uncultured environmental sequences. Evaluating the reads, instead of the OTUs that individual reads are usually clustered into, we discovered that much of this hidden diversity may be lost due to clustering. Copyright © 2018 Elsevier GmbH. All rights reserved.

A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data.

PubMed

Wang, Xiaomeng; Peng, Ling; Chi, Tianhe; Li, Mengzhu; Yao, Xiaojing; Shao, Jing

2015-01-01

Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.

Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

NASA Astrophysics Data System (ADS)

Zhu, Shijia; Wang, Yadong

2015-12-01

Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

Noninvasive Fetal ECG: the PhysioNet/Computing in Cardiology Challenge 2013.

PubMed

Silva, Ikaro; Behar, Joachim; Sameni, Reza; Zhu, Tingting; Oster, Julien; Clifford, Gari D; Moody, George B

2013-03-01

The PhysioNet/CinC 2013 Challenge aimed to stimulate rapid development and improvement of software for estimating fetal heart rate (FHR), fetal interbeat intervals (FRR), and fetal QT intervals (FQT), from multichannel recordings made using electrodes placed on the mother's abdomen. For the challenge, five data collections from a variety of sources were used to compile a large standardized database, which was divided into training, open test, and hidden test subsets. Gold-standard fetal QRS and QT interval annotations were developed using a novel crowd-sourcing framework. The challenge organizers used the hidden test subset to evaluate 91 open-source software entries submitted by 53 international teams of participants in three challenge events, estimating FHR, FRR, and FQT using the hidden test subset, which was not available for study by participants. Two additional events required only user-submitted QRS annotations to evaluate FHR and FRR estimation accuracy using the open test subset available to participants. The challenge yielded a total of 91 open-source software entries. The best of these achieved average estimation errors of 187bpm 2 for FHR, 20.9 ms for FRR, and 152.7 ms for FQT. The open data sets, scoring software, and open-source entries are available at PhysioNet for researchers interested on working on these problems.

Self-growing neural network architecture using crisp and fuzzy entropy

NASA Technical Reports Server (NTRS)

Cios, Krzysztof J.

1992-01-01

The paper briefly describes the self-growing neural network algorithm, CID3, which makes decision trees equivalent to hidden layers of a neural network. The algorithm generates a feedforward architecture using crisp and fuzzy entropy measures. The results for a real-life recognition problem of distinguishing defects in a glass ribbon, and for a benchmark problen of telling two spirals apart are shown and discussed.

Monitoring the Future: National Survey Results on Drug Use, 1975-2005. Volume I. Secondary School Students

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2006-01-01

In 2005, the Monitoring the Future study marked its 31st year of conducting national surveys of substance use among American young people. Beginning with the first survey of high school seniors in 1975, the study has provided the nation with a window through which to view the important, but largely hidden, problem behaviors of illicit drug use,…

Troublesome aspects of the Renyi-MaxEnt treatment.

PubMed

Plastino, A; Rocca, M C; Pennini, F

2016-07-01

We study in great detail the possible existence of a Renyi-associated thermodynamics, with negative results. In particular, we uncover a hidden relation in Renyi's variational problem (MaxEnt). This relation connects the two associated Lagrange multipliers (canonical ensemble) with the mean energy 〈U〉 and the Renyi parameter α. As a consequence of such relation, we obtain anomalous Renyi-MaxEnt thermodynamic results.

Skin Color and Latinos: The Origins and Contemporary Patterns of Ethnoracial Ambiguity among Mexican Americans and Puerto Ricans. Report Number 1.

ERIC Educational Resources Information Center

Montalvo, Frank F.

Failure to understand the role of skin color in the development of ethnoracial identity among Hispanic Americans has led to continued psychic and educational problems for them, hidden the cause of real and potential divisiveness in the community, and prevented the development of effective strategies for overcoming ethnic prejudice. The ethnic…

Test results of smart aircraft fastener for KC-135 structural integrity

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg

1998-07-01

Hidden and inaccessible corrosion in aircraft structures is the number one logistics problem for the US Air Force, with an estimated maintenance cost in excess of $LR 1.0B per year in 1990-equivalent dollars. The Smart Aircraft Fastener Evaluation (SAFE) system was developed to provide early warning detection of corrosion-related symptoms in hidden locations of aircraft structures. The SAFE system incorporates an in situ measurement approach that measures and autonomously records several environmental conditions within a Hi-Lok aircraft fastener that could cause corrosion. The SAFE system integrates a miniature electrochemical microsensor array and a time-of-wetness sensor with an ultra low power 8-bit microcontroller and 4- Mbyte solid-state FLASH archival memory to measure evidence of active corrosion. A summary of the technical approach and a detailed analysis of the KC-135 lap joint test coupon results are presented.

Smart fastener for KC-135 structural integrity monitoring

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg

1997-06-01

Hidden and inaccessible corrosion in aircraft structures is the number-one logistics problem for the U.S. Air Force, with an estimated maintenance cost in excess of $DOL1.0 billion per year in 1990-equivalent dollars. The Smart Aircraft Fastener Evaluation (SAFE) system is being developed to provide early warning detection of corrosion- related symptoms in hidden locations of aircraft structures. The SAFE incorporates an in situ measurement approach that measures and autonomously records several environmental conditions (i.e., pH, temperature, chloride, free potential, time-of-wetness) within a Hi-Lok aircraft fastener that could cause corrosion to occur. The SAFE system integrates a miniature electrochemical microsensor array and a time-of- wetness sensor with an ultra-low-power 8-bit microcontroller and 5-Mbyte solid-state FLASH archival memory to measure the evidence of active corrosion. A summary of the technical approach, system design definition, software architecture, and future field test plans will be presented.

Passive Acoustic Leak Detection for Sodium Cooled Fast Reactors Using Hidden Markov Models

NASA Astrophysics Data System (ADS)

Marklund, A. Riber; Kishore, S.; Prakash, V.; Rajan, K. K.; Michel, F.

2016-06-01

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970s and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), the proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control.

Experimental entanglement distillation and 'hidden' non-locality.

PubMed

Kwiat, P G; Barraza-Lopez, S; Stefanov, A; Gisin, N

2001-02-22

Entangled states are central to quantum information processing, including quantum teleportation, efficient quantum computation and quantum cryptography. In general, these applications work best with pure, maximally entangled quantum states. However, owing to dissipation and decoherence, practically available states are likely to be non-maximally entangled, partially mixed (that is, not pure), or both. To counter this problem, various schemes of entanglement distillation, state purification and concentration have been proposed. Here we demonstrate experimentally the distillation of maximally entangled states from non-maximally entangled inputs. Using partial polarizers, we perform a filtering process to maximize the entanglement of pure polarization-entangled photon pairs generated by spontaneous parametric down-conversion. We have also applied our methods to initial states that are partially mixed. After filtering, the distilled states demonstrate certain non-local correlations, as evidenced by their violation of a form of Bell's inequality. Because the initial states do not have this property, they can be said to possess 'hidden' non-locality.

ECG signal analysis through hidden Markov models.

PubMed

Andreão, Rodrigo V; Dorizzi, Bernadette; Boudy, Jérôme

2006-08-01

This paper presents an original hidden Markov model (HMM) approach for online beat segmentation and classification of electrocardiograms. The HMM framework has been visited because of its ability of beat detection, segmentation and classification, highly suitable to the electrocardiogram (ECG) problem. Our approach addresses a large panel of topics some of them never studied before in other HMM related works: waveforms modeling, multichannel beat segmentation and classification, and unsupervised adaptation to the patient's ECG. The performance was evaluated on the two-channel QT database in terms of waveform segmentation precision, beat detection and classification. Our waveform segmentation results compare favorably to other systems in the literature. We also obtained high beat detection performance with sensitivity of 99.79% and a positive predictivity of 99.96%, using a test set of 59 recordings. Moreover, premature ventricular contraction beats were detected using an original classification strategy. The results obtained validate our approach for real world application.

Adaptive distributed source coding.

PubMed

Varodayan, David; Lin, Yao-Chung; Girod, Bernd

2012-05-01

We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.

Noise-tolerant parity learning with one quantum bit

NASA Astrophysics Data System (ADS)

Park, Daniel K.; Rhee, June-Koo K.; Lee, Soonchil

2018-03-01

Demonstrating quantum advantage with less powerful but more realistic devices is of great importance in modern quantum information science. Recently, a significant quantum speedup was achieved in the problem of learning a hidden parity function with noise. However, if all data qubits at the query output are completely depolarized, the algorithm fails. In this work, we present a quantum parity learning algorithm that exhibits quantum advantage as long as one qubit is provided with nonzero polarization in each query. In this scenario, the quantum parity learning naturally becomes deterministic quantum computation with one qubit. Then the hidden parity function can be revealed by performing a set of operations that can be interpreted as measuring nonlocal observables on the auxiliary result qubit having nonzero polarization and each data qubit. We also discuss the source of the quantum advantage in our algorithm from the resource-theoretic point of view.

Generating a New Higher-Dimensional Coupled Integrable Dispersionless System: Algebraic Structures, Bäcklund Transformation and Hidden Structural Symmetries

NASA Astrophysics Data System (ADS)

Souleymanou, Abbagari; Thomas, B. Bouetou; Timoleon, C. Kofane

2013-08-01

The prolongation structure methodologies of Wahlquist—Estabrook [H.D. Wahlquist and F.B. Estabrook, J. Math. Phys. 16 (1975) 1] for nonlinear differential equations are applied to a more general set of coupled integrable dispersionless system. Based on the obtained prolongation structure, a Lie-Algebra valued connection of a closed ideal of exterior differential forms related to the above system is constructed. A Lie-Algebra representation of some hidden structural symmetries of the previous system, its Bäcklund transformation using the Riccati form of the linear eigenvalue problem and their general corresponding Lax-representation are derived. In the wake of the previous results, we extend the above prolongation scheme to higher-dimensional systems from which a new (2 + 1)-dimensional coupled integrable dispersionless system is unveiled along with its inverse scattering formulation, which applications are straightforward in nonlinear optics where additional propagating dimension deserves some attention.

Active semi-supervised learning method with hybrid deep belief networks.

PubMed

Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

2014-01-01

In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

Hidden reentrant and Larkin-Ovchinnikov-Fulde-Ferrell superconducting phases in a magnetic field in a (TMTSF)2ClO4.

PubMed

Lebed, A G

2011-08-19

We solve a long-standing problem about a theoretical description of the upper critical magnetic field, parallel to conducting layers and perpendicular to conducting chains, in a (TMTSF)(2)ClO(4) superconductor. In particular, we explain why the experimental upper critical field, H(c2)(b')≃6 T, is higher than both the quasiclassical upper critical field and the Clogston paramagnetic limit. We show that this property is due to the coexistence of the hidden reentrant and Larkin-Ovchinnikov-Fulde-Ferrell phases in a magnetic field in the form of three plane waves with nonzero momenta of the Cooper pairs. Our results are in good qualitative and quantitative agreement with the recent experimental measurements of H(c2)(b') and support a singlet d-wave-like scenario of superconductivity in (TMTSF)(2)ClO(4). © 2011 American Physical Society

Analysis of Accuracy and Epoch on Back-propagation BFGS Quasi-Newton

NASA Astrophysics Data System (ADS)

Silaban, Herlan; Zarlis, Muhammad; Sawaluddin

2017-12-01

Back-propagation is one of the learning algorithms on artificial neural networks that have been widely used to solve various problems, such as pattern recognition, prediction and classification. The Back-propagation architecture will affect the outcome of learning processed. BFGS Quasi-Newton is one of the functions that can be used to change the weight of back-propagation. This research tested some back-propagation architectures using classical back-propagation and back-propagation with BFGS. There are 7 architectures that have been tested on glass dataset with various numbers of neurons, 6 architectures with 1 hidden layer and 1 architecture with 2 hidden layers. BP with BFGS improves the convergence of the learning process. The average improvement convergence is 98.34%. BP with BFGS is more optimal on architectures with smaller number of neurons with decreased epoch number is 94.37% with the increase of accuracy about 0.5%.

How should we question young children's understanding of aspectuality?

PubMed

Waters, Gillian M; Beck, Sarah R

2012-09-01

In two experiments, we investigated whether 4- to 5-year-old children's ability to demonstrate their understanding of aspectuality was influenced by how the test question was phrased. In Experiment 1, 60 children chose whether to look or feel to gain information about a hidden object (identifiable by sight or touch). Test questions referred either to the perceptual aspect of the hidden object (e.g., whether it was red or blue), the modality dimension (e.g., what colour it was), or the object's identity (e.g., which one it was). Children who heard the identity question performed worse than those who heard the aspect or dimension question. Further investigation in Experiment 2 (N= 23) established that children's difficulty with the identity question was not due to a problem recalling the objects. We discuss how the results of these methodological investigations impact on researchers' assessment of the development of aspectuality understanding. ©2011 The British Psychological Society.

Essays on environmental policies, corruption, and energy

NASA Astrophysics Data System (ADS)

Baksi, Soham

This thesis consists of four essays. The first essay looks at pollution taxation under capital mobility, and analyzes the role of pre-commitment by countries to their pollution tax rate. A polluting firm sells its product in two countries, and can locate and produce in a single country or in both countries. Due to the discrete-choice nature of the firm's location problem, the countries' welfare functions are discontinuous in their pollution tax rate. We show that when the countries cannot pre-commit to their pollution tax, the firm can still engender tax competition between them by strategically locating in both the countries. Moreover, pre-commitment pollution taxation may not be welfare improving for the countries, although it always makes the firm better off. The second essay studies the effect of liberalization on corruption. Corruptible inspectors enforce an environmental regulation on firms, and are monitored by an honest regulator. Liberalization not only increases the variety of goods and the marginal utility of accepting a bribe, but also puts pressure on the regulator to curb corruption. The interaction of these two effects can cause corruption to initially increase with liberalization, and then decrease beyond a threshold. Moreover, equilibrium corruption is lower when the regulator is able to pre-commit to her monitoring frequency. The third essay analyzes optimal labeling (information revelation) procedures for hidden attributes of credence goods. Consumers are heterogeneous in their preference for the hidden attribute, and producers can either self-label their products, or have them certified by a third party. The government can impose self or third-party labeling requirements on either the "green" or the "brown" producers. When corrupt producers can affix spurious labels, the government needs to monitor them. A mandatory self-labeling policy is shown to generally dominate mandatory third-party labeling. The fourth essay develops formulas for computing the economy-wide energy intensity decline rate by aggregating sectoral energy efficiency improvements, and sectoral shifts in economic activities. The formulas are used to (i) construct plausible scenarios for the global rate of energy intensity decline, and (ii) show the restraining role of the "electricity generation" sector on the energy intensity decline rate.

[Geriatric assessment. Development, status quo and perspectives].

PubMed

Lüttje, D; Varwig, D; Teigel, B; Gilhaus, B

2011-08-01

Multimorbidity is typical for geriatric patients. Problems not identified in time may lead to increased hospitalisation or prolonged hospital stay. Problems of multimorbidity are not covered by most guidelines or clinical pathways. The geriatric assessment supports standard clinical and technical assessment. Geriatric identification screening is basic for general practitioners and in emergency rooms to filter those patients bearing a special risk. Geriatric basic assessment covers most of the problems relevant for people in old age, revealing even problems that had so far been hidden. It permits to structure a comprehensive and holistic therapeutic approach and to evaluate the targets of treatment relevant for independent living and well-being. This results in reduction of morbidity and mortality. Assessment tools focusing on pain, nutrition and frailty should be added to the standardized geriatric basic assessment in Germany.

Prospects for mirage mediation

NASA Astrophysics Data System (ADS)

Pierce, Aaron; Thaler, Jesse

2006-09-01

Mirage mediation reduces the fine-tuning in the minimal supersymmetric standard model by dynamically arranging a cancellation between anomaly-mediated and modulus-mediated supersymmetry breaking. We explore the conditions under which a mirage ``messenger scale'' is generated near the weak scale and the little hierarchy problem is solved. We do this by explicitly including the dynamics of the SUSY-breaking sector needed to cancel the cosmological constant. The most plausible scenario for generating a low mirage scale does not readily admit an extra-dimensional interpretation. We also review the possibilities for solving the μ/Bμ problem in such theories, a potential hidden source of fine-tuning.

Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction.

PubMed

Fessler, J A; Booth, S D

1999-01-01

Gradient-based iterative methods often converge slowly for tomographic image reconstruction and image restoration problems, but can be accelerated by suitable preconditioners. Diagonal preconditioners offer some improvement in convergence rate, but do not incorporate the structure of the Hessian matrices in imaging problems. Circulant preconditioners can provide remarkable acceleration for inverse problems that are approximately shift-invariant, i.e., for those with approximately block-Toeplitz or block-circulant Hessians. However, in applications with nonuniform noise variance, such as arises from Poisson statistics in emission tomography and in quantum-limited optical imaging, the Hessian of the weighted least-squares objective function is quite shift-variant, and circulant preconditioners perform poorly. Additional shift-variance is caused by edge-preserving regularization methods based on nonquadratic penalty functions. This paper describes new preconditioners that approximate more accurately the Hessian matrices of shift-variant imaging problems. Compared to diagonal or circulant preconditioning, the new preconditioners lead to significantly faster convergence rates for the unconstrained conjugate-gradient (CG) iteration. We also propose a new efficient method for the line-search step required by CG methods. Applications to positron emission tomography (PET) illustrate the method.

[Sleep quality of nurses working in shifts - Hungarian adaptation of the Bergen Shift Work Sleep Questionnaire].

PubMed

Fusz, Katalin; Tóth, Ákos; Fullér, Noémi; Müller, Ágnes; Oláh, András

2015-12-06

Sleep disorders among shift workers are common problems due to the disturbed circadian rhythm. The Bergen Shift Work Sleep Questionnaire assesses discrete sleep problems related to work shifts (day, evening and night shifts) and rest days. The aim of the study was to develop the Hungarian version of this questionnaire and to compare the sleep quality of nurses in different work schedules. 326 nurses working in shifts filled in the questionnaire. The authors made convergent and discriminant validation of the questionnaire with the Athens Insomnia Scale and the Perceived Stress Questionnaire. The questionnaire based on psychometric characteristics was suitable to assess sleep disorders associated with shift work in a Hungarian sample. The frequency of discrete symptoms significantly (p<0.001) differed with the shifts. Nurses experienced the worst sleep quality and daytime fatigue after the night shift. Nurses working in irregular shift system had worse sleep quality than nurses working in regular and flexible shift system (p<0.001). The sleep disorder of nurses working in shifts should be assessed with the Hungarian version of the Bergen Shift Work Sleep Questionnaire on a nationally representative sample, and the least burdensome shift system could be established.

Phylogenetic analysis at deep timescales: unreliable gene trees, bypassed hidden support, and the coalescence/concatalescence conundrum.

PubMed

Gatesy, John; Springer, Mark S

2014-11-01

Large datasets are required to solve difficult phylogenetic problems that are deep in the Tree of Life. Currently, two divergent systematic methods are commonly applied to such datasets: the traditional supermatrix approach (= concatenation) and "shortcut" coalescence (= coalescence methods wherein gene trees and the species tree are not co-estimated). When applied to ancient clades, these contrasting frameworks often produce congruent results, but in recent phylogenetic analyses of Placentalia (placental mammals), this is not the case. A recent series of papers has alternatively disputed and defended the utility of shortcut coalescence methods at deep phylogenetic scales. Here, we examine this exchange in the context of published phylogenomic data from Mammalia; in particular we explore two critical issues - the delimitation of data partitions ("genes") in coalescence analysis and hidden support that emerges with the combination of such partitions in phylogenetic studies. Hidden support - increased support for a clade in combined analysis of all data partitions relative to the support evident in separate analyses of the various data partitions, is a hallmark of the supermatrix approach and a primary rationale for concatenating all characters into a single matrix. In the most extreme cases of hidden support, relationships that are contradicted by all gene trees are supported when all of the genes are analyzed together. A valid fear is that shortcut coalescence methods might bypass or distort character support that is hidden in individual loci because small gene fragments are analyzed in isolation. Given the extensive systematic database for Mammalia, the assumptions and applicability of shortcut coalescence methods can be assessed with rigor to complement a small but growing body of simulation work that has directly compared these methods to concatenation. We document several remarkable cases of hidden support in both supermatrix and coalescence paradigms and argue that in most instances, the emergent support in the shortcut coalescence analyses is an artifact. By referencing rigorous molecular clock studies of Mammalia, we suggest that inaccurate gene trees that imply unrealistically deep coalescences debilitate shortcut coalescence analyses of the placental dataset. We document contradictory coalescence results for Placentalia, and outline a critical conundrum that challenges the general utility of shortcut coalescence methods at deep phylogenetic scales. In particular, the basic unit of analysis in coalescence analysis, the coalescence-gene, is expected to shrink in size as more taxa are analyzed, but as the amount of data for reconstruction of a gene tree ratchets downward, the number of nodes in the gene tree that need to be resolved ratchets upward. Some advocates of shortcut coalescence methods have attempted to address problems with inaccurate gene trees by concatenating multiple coalescence-genes to yield "gene trees" that better match the species tree. However, this hybrid concatenation/coalescence approach, "concatalescence," contradicts the most basic biological rationale for performing a coalescence analysis in the first place. We discuss this reality in the context of recent simulation work that also suggests inaccurate reconstruction of gene trees is more problematic for shortcut coalescence methods than deep coalescence of independently segregating loci is for concatenation methods. Copyright © 2014 Elsevier Inc. All rights reserved.

Efficient free energy calculations by combining two complementary tempering sampling methods.

PubMed

Xie, Liangxu; Shen, Lin; Chen, Zhe-Ning; Yang, Mingjun

2017-01-14

Although energy barriers can be efficiently crossed in the reaction coordinate (RC) guided sampling, this type of method suffers from identification of the correct RCs or requirements of high dimensionality of the defined RCs for a given system. If only the approximate RCs with significant barriers are used in the simulations, hidden energy barriers with small to medium height would exist in other degrees of freedom (DOFs) relevant to the target process and consequently cause the problem of insufficient sampling. To address the sampling in this so-called hidden barrier situation, here we propose an effective approach to combine temperature accelerated molecular dynamics (TAMD), an efficient RC-guided sampling method, with the integrated tempering sampling (ITS), a generalized ensemble sampling method. In this combined ITS-TAMD method, the sampling along the major RCs with high energy barriers is guided by TAMD and the sampling of the rest of the DOFs with lower but not negligible barriers is enhanced by ITS. The performance of ITS-TAMD to three systems in the processes with hidden barriers has been examined. In comparison to the standalone TAMD or ITS approach, the present hybrid method shows three main improvements. (1) Sampling efficiency can be improved at least five times even if in the presence of hidden energy barriers. (2) The canonical distribution can be more accurately recovered, from which the thermodynamic properties along other collective variables can be computed correctly. (3) The robustness of the selection of major RCs suggests that the dimensionality of necessary RCs can be reduced. Our work shows more potential applications of the ITS-TAMD method as the efficient and powerful tool for the investigation of a broad range of interesting cases.

Efficient free energy calculations by combining two complementary tempering sampling methods

NASA Astrophysics Data System (ADS)

Xie, Liangxu; Shen, Lin; Chen, Zhe-Ning; Yang, Mingjun

2017-01-01

Although energy barriers can be efficiently crossed in the reaction coordinate (RC) guided sampling, this type of method suffers from identification of the correct RCs or requirements of high dimensionality of the defined RCs for a given system. If only the approximate RCs with significant barriers are used in the simulations, hidden energy barriers with small to medium height would exist in other degrees of freedom (DOFs) relevant to the target process and consequently cause the problem of insufficient sampling. To address the sampling in this so-called hidden barrier situation, here we propose an effective approach to combine temperature accelerated molecular dynamics (TAMD), an efficient RC-guided sampling method, with the integrated tempering sampling (ITS), a generalized ensemble sampling method. In this combined ITS-TAMD method, the sampling along the major RCs with high energy barriers is guided by TAMD and the sampling of the rest of the DOFs with lower but not negligible barriers is enhanced by ITS. The performance of ITS-TAMD to three systems in the processes with hidden barriers has been examined. In comparison to the standalone TAMD or ITS approach, the present hybrid method shows three main improvements. (1) Sampling efficiency can be improved at least five times even if in the presence of hidden energy barriers. (2) The canonical distribution can be more accurately recovered, from which the thermodynamic properties along other collective variables can be computed correctly. (3) The robustness of the selection of major RCs suggests that the dimensionality of necessary RCs can be reduced. Our work shows more potential applications of the ITS-TAMD method as the efficient and powerful tool for the investigation of a broad range of interesting cases.

The hidden costs of coastal hazards: Implications for risk assessment and mitigation

USGS Publications Warehouse

Kunreuther, H.; Platt, R.; Baruch, S.; Bernknopf, R.L.; Buckley, M.; Burkett, V.; Conrad, D.; Davidson, T.; Deutsch, K.; Geis, D.; Jannereth, M.; Knap, A.; Lane, H.; Ljung, G.; McCauley, M.; Mileti, D.; Miller, T.; Morrow, B.; Meyers, J.; Pielke, R.; Pratt, A.; Tripp, J.

2000-01-01

Society has limited hazard mitigation dollars to invest. Which actions will be most cost effective, considering the true range of impacts and costs incurred? In 1997, the H. John Heinz III Center for Science, Economics and the Environment began a two-year study with a panel of experts to help develop new strategies to identify and reduce the costs of weather-related hazards associated with rapidly increasing coastal development activities.The Hidden Costs of Coastal Hazards presents the panel's findings, offering the first in-depth study that considers the costs of coastal hazards to natural resources, social institutions, business, and the built environment. Using Hurricane Hugo, which struck South Carolina in 1989, as a case study, it provides for the first time information on the full range of economic costs caused by a major coastal hazard event. The book:describes and examines unreported, undocumented, and hidden costs such as losses due to business interruption, reduction in property values, interruption of social services, psychological trauma, damage to natural systems, and othersexamines the concepts of risk and vulnerability, and discusses conventional approaches to risk assessment and the emerging area of vulnerability assessmentrecommends a comprehensive framework for developing and implementing mitigation strategiesdocuments the human impact of Hurricane Hugo and provides insight from those who lived through it.The Hidden Costs of Coastal Hazards takes a structured approach to the problem of coastal hazards, offering a new framework for community-based hazard mitigation along with specific recommendations for implementation. Decisionmakers -- both policymakers and planners -- who are interested in coastal hazard issues will find the book a unique source of new information and insight, as will private-sector decisionmakers including lenders, investors, developers, and insurers of coastal property.

Redesigning the exploitation of wheat genetic resources.

PubMed

Longin, C Friedrich H; Reif, Jochen C

2014-10-01

More than half a million wheat genetic resources are resting in gene banks worldwide. Unlocking their hidden favorable genetic diversity for breeding is pivotal for enhancing grain yield potential, and averting future food shortages. Here, we propose exploiting recent advances in hybrid wheat technology to uncover the masked breeding values of wheat genetic resources. The gathered phenotypic information will enable a targeted choice of accessions with high value for pre-breeding among this plethora of genetic resources. We intend to provoke a paradigm shift in pre-breeding strategies for grain yield, moving away from allele mining toward genome-wide selection to bridge the yield gap between genetic resources and elite breeding pools. Copyright © 2014 Elsevier Ltd. All rights reserved.

Quantum gap and spin-wave excitations in the Kitaev model on a triangular lattice

NASA Astrophysics Data System (ADS)

Avella, Adolfo; Di Ciolo, Andrea; Jackeli, George

2018-05-01

We study the effects of quantum fluctuations on the dynamical generation of a gap and on the evolution of the spin-wave spectra of a frustrated magnet on a triangular lattice with bond-dependent Ising couplings, analog of the Kitaev honeycomb model. The quantum fluctuations lift the subextensive degeneracy of the classical ground-state manifold by a quantum order-by-disorder mechanism. Nearest-neighbor chains remain decoupled and the surviving discrete degeneracy of the ground state is protected by a hidden model symmetry. We show how the four-spin interaction, emergent from the fluctuations, generates a spin gap shifting the nodal lines of the linear spin-wave spectrum to finite energies.

Hot Evolved Companions to Intermediate-Mass Main-Sequence Stars: Solving the Mystery of KOI-81

NASA Astrophysics Data System (ADS)

Gies, Douglas

2010-09-01

The NASA Kepler Science Team recently announced the discovery of twotransiting binaries that have "planets" hotter than their host stars.These systems probably represent the first known examples of white dwarfsformed through mass loss and transfer among intermediate mass, closebinary stars. Here we propose to obtain COS FUV spectroscopy of one ofthese systems, KOI-81, in order to detect the hot companion in a part of the spectrum where it is relatively bright. The spectral flux and Doppler shift measurements will yield the temperatures, masses, radii, and compositions of both components. These observations will provide our first opportunity to explore this previously hidden stage of close binary evolution.

Population Health in Canada: A Brief Critique

PubMed Central

Coburn, David; Denny, Keith; Mykhalovskiy, Eric; McDonough, Peggy; Robertson, Ann; Love, Rhonda

2003-01-01

An internationally influential model of population health was developed in Canada in the 1990s, shifting the research agenda beyond health care to the social and economic determinants of health. While agreeing that health has important social determinants, the authors believe that this model has serious shortcomings; they critique the model by focusing on its hidden assumptions. Assumptions about how knowledge is produced and an implicit interest group perspective exclude the sociopolitical and class contexts that shape interest group power and citizen health. Overly rationalist assumptions about change understate the role of agency. The authors review the policy and practice implications of the Canadian population health model and point to alternative ways of viewing the determinants of health. PMID:12604479

Perceived unmet need and barriers to care amongst street-involved people who use illicit drugs.

PubMed

Hyshka, Elaine; Anderson, Jalene Tayler; Wild, T Cameron

2017-05-01

Research on perceived unmet need for care for mental health and substance use problems focuses on general populations to the detriment of hidden populations. This study describes prevalence and correlates of perceived unmet need for care in a community-based sample of street-involved people who use illicit drugs and identifies barriers to care. A sample of 320 street-involved people who use drugs participated in a structured, interviewer-assisted survey in Edmonton, Canada. The survey included the Perceived Need for Care Questionnaire, which assessed unmet need for care for mental health and substance use problems across seven service types. Logistic regression examined the associations between perceived unmet need, extent of socioeconomic marginalisation and problem severity. Barriers underlying unmet service needs were also examined. Most (82%) participants reported unmet need for one or more services during the past year. Odds of reporting one or more unmet needs were elevated amongst participants reporting substantial housing instability (adjusted odds ratio = 2.37; 95% confidence interval 1.19-4.28) and amongst participants meeting criteria for drug dependence (adjusted odds ratio = 1.22; 95% confidence interval 1.03-1.50), even after adjustment for sociodemographic covariates. Structural, rather than motivational barriers were the most commonly reported reasons underlying unmet service needs. Street-involved people who use drugs experience very high rates of perceived unmet need for care for mental health and substance use problems. General population studies on perceived unmet need are insufficient for understanding needs and barriers to care in hidden populations.[Hyshka E, Anderson JT, Wild TC. Perceived unmet need and barriers to care amongst street-involved people who use illicit drugs. Drug Alcohol Rev 2017;36:295-304]. © 2016 Australasian Professional Society on Alcohol and other Drugs.

Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and Hidden Markov Models in the Natural Language Call Routing Problem

NASA Astrophysics Data System (ADS)

Rustamov, Samir; Mustafayev, Elshan; Clements, Mark A.

2018-04-01

The context analysis of customer requests in a natural language call routing problem is investigated in the paper. One of the most significant problems in natural language call routing is a comprehension of client request. With the aim of finding a solution to this issue, the Hybrid HMM and ANFIS models become a subject to an examination. Combining different types of models (ANFIS and HMM) can prevent misunderstanding by the system for identification of user intention in dialogue system. Based on these models, the hybrid system may be employed in various language and call routing domains due to nonusage of lexical or syntactic analysis in classification process.

Committee opinion no. 507: human trafficking.

PubMed

2011-09-01

Human trafficking is a widespread problem with estimates ranging from 14,000 to 50,000 individuals trafficked into the United States annually. This hidden population involves the commercial sex industry, agriculture, factories, hotel and restaurant businesses, domestic workers, marriage brokers, and some adoption firms. Because 80% of trafficked individuals are women and girls, women’s health care providers may better serve their diverse patient population by increasing their awareness of this problem. The exploitation of people of any race, gender, sexual orientation, or ethnicity is unacceptable at any time, in any place. The members of the American College of Obstetricians and Gynecologists should be aware of this problem and strive to recognize and assist their patients who are victims or who have been victims of human trafficking.

Total Quality Management: A Guide to Implementation

DTIC Science & Technology

1989-08-01

Kaizen. New York: Random House. 1986. Ishikawa , Kaoru . Guide to Quality Control. Asian Productivity Organization. 1984. Ishikawa , Kaoru . What is Total...with the problems and the new management principles are based on the complexities of the new Systems Age. The theories of Deming, Juran, Ishikawa , and...Progress. Jun 1985. Miller, Jeffery G. and Thomas E. Vollmann. "The Hidden Factory." Harvard Business Review. Sep-Oct 1985. Shimoyamada, Kaoru . "The

Monitoring the Future: National Survey Results on Drug Use, 1975-2009. Volume I: Secondary School Students. NIH Publication No. 10-7584

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2010-01-01

The Monitoring the Future (MTF) study is an ongoing series of national surveys of American adolescents and adults that has provided the nation with a vital window into the important, but largely hidden, problem behaviors of illegal drug use, alcohol use, tobacco use, anabolic steroid use, and psychotherapeutic drug use. For more than a third of…

Proposed Test of Relative Phase as Hidden Variable in Quantum Mechanics

DTIC Science & Technology

2012-01-01

implicitly due to its ubiquity in quantum theory , but searches for dependence of measurement outcome on other parameters have been lacking. For a two -state...implemen- tation for the specific case of an atomic two -state system with laser-induced fluores- cence for measurement. Keywords Quantum measurement...Measurement postulate · Born rule 1 Introduction 1.1 Problems with Quantum Measurement Quantum theory prescribes probabilities for outcomes of measurements

Lymphogranuloma venereum: a hidden emerging problem, Barcelona, 2011.

PubMed

Vargas-Leguas, H; Garcia de Olalla, P; Arando, M; Armengol, P; Barbera, Mj; Vall, M; Vives, A; Martin-Ezquerra, G; Alsina, M; Blanco, J; Munoz, C; Caballero, E; Andreu, A; Ros, M; Gorrindo, P; Dominguez, A; Cayla, Ja

2012-01-12

From the beginning of 2007 until the end of 2011, 146 cases of lymphogranuloma venereum (LGV) were notified to the Barcelona Public Health Agency. Some 49% of them were diagnosed and reported in 2011, mainly in men who have sex with men. Almost half of them, 32 cases, were reported between July and September. This cluster represents the largest since 2004. This article presents the ongoing outbreak of LGV in Barcelona.

Monitoring the Future: National Survey Results on Drug Use, 1975-2004. Volume I: Secondary School Students, 2004

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2005-01-01

In 2004 the Monitoring the Future study marked its 30th year of conducting national surveys of substance use among American young people. Beginning with the first survey of high school seniors in 1975, the study has provided the nation with a window through which to view the important, but largely hidden, problem behaviors of illicit drug use,…

Hidden Realities inside PBL Design Processes: Is Consensus Design an Impossible Clash of Interest between the Individual and the Collective, and Is Architecture Its First Victim?

ERIC Educational Resources Information Center

Pihl, Ole

2015-01-01

How do architecture students experience the contradictions between the individual and the group at the Department of Architecture and Design of Aalborg University? The Problem-Based Learning model has been extensively applied to the department's degree programs in coherence with the Integrated Design Process, but is a group-based architecture and…

Attentional Selection in Object Recognition

DTIC Science & Technology

1993-02-01

order. It also affects the choice of strategies in both the 24 A Computational Model of Attentional Selection filtering and arbiter stages. The set...such processing. In Treisman’s model this was hidden in the concept of the selection filter . Later computational models of attention tried to...This thesis presents a novel approach to the selection problem by propos. ing a computational model of visual attentional selection as a paradigm for

Monitoring the Future. National Survey Results on Drug Use, 1975-2009. Volume I, Secondary School Students. NIH Publication Number 10-7584

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2010-01-01

The Monitoring the Future (MTF) study is an ongoing series of national surveys of American adolescents and adults that has provided the nation with a vital window into the important, but largely hidden, problem behaviors of illegal drug use, alcohol use, tobacco use, anabolic steroid use, and psychotherapeutic drug use. For more than a third of a…

Search protocols for hidden forensic objects beneath floors and within walls.

PubMed

Ruffell, Alastair; Pringle, Jamie K; Forbes, Shari

2014-04-01

The burial of objects (human remains, explosives, weapons) below or behind concrete, brick, plaster or tiling may be associated with serious crime and are difficult locations to search. These are quite common forensic search scenarios but little has been published on them to-date. Most documented discoveries are accidental or from suspect/witness testimony. The problem in locating such hidden objects means a random or chance-based approach is not advisable. A preliminary strategy is presented here, based on previous studies, augmented by primary research where new technology or applications are required. This blend allows a rudimentary search workflow, from remote desktop study, to non-destructive investigation through to recommendations as to how the above may inform excavation, demonstrated here with a case study from a homicide investigation. Published case studies on the search for human remains demonstrate the problems encountered when trying to find and recover sealed-in and sealed-over locations. Established methods include desktop study, photography, geophysics and search dogs: these are integrated with new technology (LiDAR and laser scanning; photographic rectification; close-quarter aerial imagery; ground-penetrating radar on walls and gamma-ray/neutron activation radiography) to propose this possible search strategy. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Binary space partitioning trees and their uses

NASA Technical Reports Server (NTRS)

Bell, Bradley N.

1989-01-01

Binary Space Partitioning (BSP) trees have some qualities that make them useful in solving many graphics related problems. The purpose is to describe what a BSP tree is, and how it can be used to solve the problem of hidden surface removal, and constructive solid geometry. The BSP tree is based on the idea that a plane acting as a divider subdivides space into two parts with one being on the positive side and the other on the negative. A polygonal solid is then represented as the volume defined by the collective interior half spaces of the solid's bounding surfaces. The nature of how the tree is organized lends itself well for sorting polygons relative to an arbitrary point in 3 space. The speed at which the tree can be traversed for depth sorting is fast enough to provide hidden surface removal at interactive speeds. The fact that a BSP tree actually represents a polygonal solid as a bounded volume also makes it quite useful in performing the boolean operations used in constructive solid geometry. Due to the nature of the BSP tree, polygons can be classified as they are subdivided. The ability to classify polygons as they are subdivided can enhance the simplicity of implementing constructive solid geometry.

Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

NASA Astrophysics Data System (ADS)

Jiang, Fei-Bo; Dai, Qian-Wei; Dong, Li

2016-06-01

Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.

Adaptive Online Sequential ELM for Concept Drift Tackling

PubMed Central

Basaruddin, Chan

2016-01-01

A machine learning method needs to adapt to over time changes in the environment. Such changes are known as concept drift. In this paper, we propose concept drift tackling method as an enhancement of Online Sequential Extreme Learning Machine (OS-ELM) and Constructive Enhancement OS-ELM (CEOS-ELM) by adding adaptive capability for classification and regression problem. The scheme is named as adaptive OS-ELM (AOS-ELM). It is a single classifier scheme that works well to handle real drift, virtual drift, and hybrid drift. The AOS-ELM also works well for sudden drift and recurrent context change type. The scheme is a simple unified method implemented in simple lines of code. We evaluated AOS-ELM on regression and classification problem by using concept drift public data set (SEA and STAGGER) and other public data sets such as MNIST, USPS, and IDS. Experiments show that our method gives higher kappa value compared to the multiclassifier ELM ensemble. Even though AOS-ELM in practice does not need hidden nodes increase, we address some issues related to the increasing of the hidden nodes such as error condition and rank values. We propose taking the rank of the pseudoinverse matrix as an indicator parameter to detect “underfitting” condition. PMID:27594879

Robust Hidden Markov Model based intelligent blood vessel detection of fundus images.

PubMed

Hassan, Mehdi; Amin, Muhammad; Murtza, Iqbal; Khan, Asifullah; Chaudhry, Asmatullah

2017-11-01

In this paper, we consider the challenging problem of detecting retinal vessel networks. Precise detection of retinal vessel networks is vital for accurate eye disease diagnosis. Most of the blood vessel tracking techniques may not properly track vessels in presence of vessels' occlusion. Owing to problem in sensor resolution or acquisition of fundus images, it is possible that some part of vessel may occlude. In this scenario, it becomes a challenging task to accurately trace these vital vessels. For this purpose, we have proposed a new robust and intelligent retinal vessel detection technique on Hidden Markov Model. The proposed model is able to successfully track vessels in the presence of occlusion. The effectiveness of the proposed technique is evaluated on publically available standard DRIVE dataset of the fundus images. The experiments show that the proposed technique not only outperforms the other state of the art methodologies of retinal blood vessels segmentation, but it is also capable of accurate occlusion handling in retinal vessel networks. The proposed technique offers better average classification accuracy, sensitivity, specificity, and area under the curve (AUC) of 95.7%, 81.0%, 97.0%, and 90.0% respectively, which shows the usefulness of the proposed technique. Copyright © 2017 Elsevier B.V. All rights reserved.

Raman scattering study on the hidden order and antiferromagnetic phases in URu2-xFexSi2

NASA Astrophysics Data System (ADS)

Kung, Hsiang-Hsi; Ran, Sheng; Kanchanavatee, Noravee; Lee, Alexander; Krapivin, Viktor; Haule, Kristjan; Maple, M. Brian; Blumberg, Girsh

The heavy fermion compound URu2Si2 possesses an unusual ground state known as the ``hidden order'' (HO) phase below T = 17 . 5 K, which evolves into an large moment antiferromagnetic (LMAFM) phase under pressure. A recent Raman scattering study shows that an A2 g symmetry (D4 h) in-gap mode emerges in the HO phase, characterizing the excitation from a chirality density wave. Here, we report Raman scattering results for single crystal URu2-xFexSi2 with x <= 0 . 2 , where the Fe substitution acts as chemical pressure, shifting the system's ground state from HO to LMAFM. We found that the A2 g mode softens with doping, vanishes at the HO and LMAFM phase boundary, then re-emerges and hardens with doping in the LMAFM phase. The relations between the A2 g mode energy and the strength of the HO/LMAFM order parameters will be discussed in this talk. GB and HHK acknowledge support from DOE BES Award DE-SC0005463. AL and VK acknowledge NSF Award DMR-1104884. KH acknowledges NSF Award DMR-1405303. MBM, SR and NK acknowledge DOE BES Award DE-FG02-04ER46105 and NSF Award DMR 1206553.

Task complexity modifies the search strategy of rats.

PubMed

Ruprecht, Chad M; Taylor, C Drew; Wolf, Joshua E; Leising, Kenneth J

2014-01-01

Human and non-human animals exhibit a variety of response strategies (e.g., place responding) when searching for a familiar place or evading predators. We still know little about the conditions that support the use of each strategy. We trained rats to locate a hidden food reward in a small-scale spatial search task. The complexity of the search task was manipulated by reducing the number of search locations (25, 4, and 2) within an open-field apparatus and by comparison to a path-based apparatus (plus-maze). After rats were trained to reliably locate the hidden food, each apparatus was shifted to gauge whether rats were searching at the location of the goal relative to extramaze cues (i.e., place responding), or searching in the direction of the goal relative to a combination of intramaze and extramaze cues (i.e.,directional responding). The results indicate that the open field supported place responding when more than two response locations were present, whereas, the four-arm plus-maze supported strong directional responding. These results extend prior research into the role of task demands on search strategy, as well as support the use of the four-choice open field as an analog to the Morris water task for future studies targeting the neural underpinnings of place responding.

Emoticon-Based Ambivalent Expression: A Hidden Indicator for Unusual Behaviors in Weibo.

PubMed

Hu, Yue; Zhao, Jichang; Wu, Junjie

2016-01-01

Recent decades have witnessed online social media being a big-data window for testifying conventional social theories quantitatively and exploring much detailed human behavioral patterns. In this paper, by tracing the emoticon use in Weibo, a group of hidden "ambivalent users" are disclosed for frequently posting ambivalent tweets containing both positive and negative emotions. Further investigation reveals that this ambivalent expression could be a novel indicator of many unusual social behaviors. For instance, ambivalent users with the female as the majority like to make a sound in midnights and at weekends. They mention their close friends frequently in ambivalent tweets, which attract more replies and serve as a more private communication way. Ambivalent users also respond differently to public affairs from others and demonstrate more interests in entertainment and sports events. Moreover, the sentiment shift in ambivalent tweets is more evident than usual and exhibits a clear "negative to positive" pattern. The above observations, though being promiscuous seemingly, actually point to the self-regulation of negative mood in Weibo, which could find its basis from the traditional emotion management theories in sociology but makes an important extension to the online environment in this study. Finally, as an interesting corollary, ambivalent users are found connected with compulsive buyers and turn out to be perfect targets for online marketing.

GPHMM: an integrated hidden Markov model for identification of copy number alteration and loss of heterozygosity in complex tumor samples using whole genome SNP arrays

PubMed Central

Li, Ao; Liu, Zongzhi; Lezon-Geyda, Kimberly; Sarkar, Sudipa; Lannin, Donald; Schulz, Vincent; Krop, Ian; Winer, Eric; Harris, Lyndsay; Tuck, David

2011-01-01

There is an increasing interest in using single nucleotide polymorphism (SNP) genotyping arrays for profiling chromosomal rearrangements in tumors, as they allow simultaneous detection of copy number and loss of heterozygosity with high resolution. Critical issues such as signal baseline shift due to aneuploidy, normal cell contamination, and the presence of GC content bias have been reported to dramatically alter SNP array signals and complicate accurate identification of aberrations in cancer genomes. To address these issues, we propose a novel Global Parameter Hidden Markov Model (GPHMM) to unravel tangled genotyping data generated from tumor samples. In contrast to other HMM methods, a distinct feature of GPHMM is that the issues mentioned above are quantitatively modeled by global parameters and integrated within the statistical framework. We developed an efficient EM algorithm for parameter estimation. We evaluated performance on three data sets and show that GPHMM can correctly identify chromosomal aberrations in tumor samples containing as few as 10% cancer cells. Furthermore, we demonstrated that the estimation of global parameters in GPHMM provides information about the biological characteristics of tumor samples and the quality of genotyping signal from SNP array experiments, which is helpful for data quality control and outlier detection in cohort studies. PMID:21398628

New color-shifting security devices

NASA Astrophysics Data System (ADS)

Moia, Franco

2004-06-01

The unbroken global increase of forgery and counterfeiting of valuable documents and products steadily requires improved types of optical security devices. Hence, the "security world" is actively seeking for new features which meet high security standards, look attractively and allow easy recognition. One special smart security device created by ROLIC's technology represents a cholesteric device combined with a phase image. On tilting, such devices reveal strong color shifts which are clearly visible to the naked eye. The additional latent image is invisible under normal lighting conditions but can be revealed to human eyes by means of a simple, commercially available linear sheet polarizer. Based on our earlier work, first published in 1981, we now have developed phase change guest-host devices combined with dye-doped cholesteric material for application in new security features. ROLIC has developed sophisticated material systems of cross-linkable cholesteric liquid crystals and suitable cross-linkable dyes which allow to create outstanding cholesteric color-shifting effects not only on light absorbing dark backgrounds but also on bright or even white backgrounds preserving the circularly polarizing state. The new security devices combine unambiguously 1st and 2nd level inspection features and show brilliant colors on black as well as on white substrates. On tilting, the security devices exhibit remarkable color shifts while the integrated hidden images can be revealed by use of a sheet polarizer. Furthermore, due to its very thin material layers, even demanding applications, such as on banknotes can be considered.

The Physiological Bases of Hidden Noise-Induced Hearing Loss: Protocol for a Functional Neuroimaging Study

PubMed Central

Hall, Deborah A; Guest, Hannah; Prendergast, Garreth; Plack, Christopher J; Francis, Susan T

2018-01-01

Background Rodent studies indicate that noise exposure can cause permanent damage to synapses between inner hair cells and high-threshold auditory nerve fibers, without permanently altering threshold sensitivity. These demonstrations of what is commonly known as hidden hearing loss have been confirmed in several rodent species, but the implications for human hearing are unclear. Objective Our Medical Research Council–funded program aims to address this unanswered question, by investigating functional consequences of the damage to the human peripheral and central auditory nervous system that results from cumulative lifetime noise exposure. Behavioral and neuroimaging techniques are being used in a series of parallel studies aimed at detecting hidden hearing loss in humans. The planned neuroimaging study aims to (1) identify central auditory biomarkers associated with hidden hearing loss; (2) investigate whether there are any additive contributions from tinnitus or diminished sound tolerance, which are often comorbid with hearing problems; and (3) explore the relation between subcortical functional magnetic resonance imaging (fMRI) measures and the auditory brainstem response (ABR). Methods Individuals aged 25 to 40 years with pure tone hearing thresholds ≤20 dB hearing level over the range 500 Hz to 8 kHz and no contraindications for MRI or signs of ear disease will be recruited into the study. Lifetime noise exposure will be estimated using an in-depth structured interview. Auditory responses throughout the central auditory system will be recorded using ABR and fMRI. Analyses will focus predominantly on correlations between lifetime noise exposure and auditory response characteristics. Results This paper reports the study protocol. The funding was awarded in July 2013. Enrollment for the study described in this protocol commenced in February 2017 and was completed in December 2017. Results are expected in 2018. Conclusions This challenging and comprehensive study will have the potential to impact diagnostic procedures for hidden hearing loss, enabling early identification of noise-induced auditory damage via the detection of changes in central auditory processing. Consequently, this will generate the opportunity to give personalized advice regarding provision of ear defense and monitoring of further damage, thus reducing the incidence of noise-induced hearing loss. PMID:29523503

Algorithm 937: MINRES-QLP for Symmetric and Hermitian Linear Equations and Least-Squares Problems.

PubMed

Choi, Sou-Cheng T; Saunders, Michael A

2014-02-01

We describe algorithm MINRES-QLP and its FORTRAN 90 implementation for solving symmetric or Hermitian linear systems or least-squares problems. If the system is singular, MINRES-QLP computes the unique minimum-length solution (also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes a potential instability in the original MINRES algorithm. A positive-definite pre-conditioner may be supplied. Our FORTRAN 90 implementation illustrates a design pattern that allows users to make problem data known to the solver but hidden and secure from other program units. In particular, we circumvent the need for reverse communication. Example test programs input and solve real or complex problems specified in Matrix Market format. While we focus here on a FORTRAN 90 implementation, we also provide and maintain MATLAB versions of MINRES and MINRES-QLP.

The secret art of managing healthcare expenses: investigating implicit rationing and autonomy in public healthcare systems.

PubMed

Lauridsen, S M R; Norup, M S; Rossel, P J H

2007-12-01

Rationing healthcare is a difficult task, which includes preventing patients from accessing potentially beneficial treatments. Proponents of implicit rationing argue that politicians cannot resist pressure from strong patient groups for treatments and conclude that physicians should ration without informing patients or the public. The authors subdivide this specific programme of implicit rationing, or "hidden rationing", into local hidden rationing, unsophisticated global hidden rationing and sophisticated global hidden rationing. They evaluate the appropriateness of these methods of rationing from the perspectives of individual and political autonomy and conclude that local hidden rationing and unsophisticated global hidden rationing clearly violate patients' individual autonomy, that is, their right to participate in medical decision-making. While sophisticated global hidden rationing avoids this charge, the authors point out that it nonetheless violates the political autonomy of patients, that is, their right to engage in public affairs as citizens. A defence of any of the forms of hidden rationing is therefore considered to be incompatible with a defence of autonomy.

Clinical Holistic Medicine: A Psychological Theory of Dependency to Improve Quality of Life

PubMed Central

Ventegodt, Søren; Morad, Mohammed; Kandel, Isack; Merrick, Joav

2004-01-01

In this paper, we suggest a psychological theory of dependency as an escape from feeling existential suffering and a poor quality of life. The ways in which human beings escape hidden existential pains are multiple. The wide range of dependency states seems to be the most common escape strategy used. If the patient can be guided into the hidden existential pain to feel, understand, and integrate it, we believe that dependency can be cured. The problem is that the patient must be highly motivated, sufficiently resourceful, and supported to want such a treatment that is inherently painful. Often, the family and surrounding world is suffering more than the dependent person himself, because the pattern of behavior the patient is dependent on makes him or her rather insensitive and unable to feel. If the patient is motivated, resourceful, and trusts his physician, recovery from even a severe state of dependency is not out of reach, if the holistic medical tools are applied wisely. The patient must find hidden resources to take action, then in therapy confront and feel old emotional pain, understand the source and inner logic of it, and finally learn to let go of negative attitudes and beliefs. In this way, the person can be healed and released of the emotional suffering and no longer be a slave to the dependency pattern. PMID:15349506

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

Vongehr, Sascha, E-mail: vongehr@usc.edu

There are increasingly suggestions for computer simulations of quantum statistics which try to violate Bell type inequalities via classical, common cause correlations. The Clauser–Horne–Shimony–Holt (CHSH) inequality is very robust. However, we argue that with the Einstein–Podolsky–Rosen setup, the CHSH is inferior to the Bell inequality, although and because the latter must assume anti-correlation of entangled photon singlet states. We simulate how often quantum behavior violates both inequalities, depending on the number of photons. Violating Bell 99% of the time is argued to be an ideal benchmark. We present hidden variables that violate the Bell and CHSH inequalities with 50% probability,more » and ones which violate Bell 85% of the time when missing 13% anti-correlation. We discuss how to present the quantum correlations to a wide audience and conclude that, when defending against claims of hidden classicality, one should demand numerical simulations and insist on anti-correlation and the full amount of Bell violation. -- Highlights: •The widely assumed superiority of the CHSH fails in the EPR problem. •We simulate Bell type inequalities behavior depending on the number of photons. •The core of Bell’s theorem in the EPR setup is introduced in a simple way understandable to a wide audience. •We present hidden variables that violate both inequalities with 50% probability. •Algorithms have been supplied in form of Mathematica programs.« less

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine

PubMed Central

Liu, Yongxiang; Huo, Kai; Zhang, Zhongshuai

2018-01-01

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available. PMID:29320453

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.

PubMed

Zhao, Feixiang; Liu, Yongxiang; Huo, Kai; Zhang, Shuanghui; Zhang, Zhongshuai

2018-01-10

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available.

The ``Folk Theorem'' on effective field theory: How does it fare in nuclear physics?

NASA Astrophysics Data System (ADS)

Rho, Mannque

2017-10-01

This is a brief history of what I consider as very important, some of which truly seminal, contributions made by young Korean nuclear theorists, mostly graduate students working on PhD thesis in 1990s and early 2000s, to nuclear effective field theory, nowadays heralded as the first-principle approach to nuclear physics. The theoretical framework employed is an effective field theory anchored on a single scale-invariant hidden local symmetric Lagrangian constructed in the spirit of Weinberg's "Folk Theorem" on effective field theory. The problems addressed are the high-precision calculations on the thermal np capture, the solar pp fusion process, the solar hep process — John Bahcall's challenge to nuclear theorists — and the quenching of g A in giant Gamow-Teller resonances and the whopping enhancement of first-forbidden beta transitions relevant in astrophysical processes. Extending adventurously the strategy to a wild uncharted domain in which a systematic implementation of the "theorem" is far from obvious, the same effective Lagrangian is applied to the structure of compact stars. A surprising, unexpected, result on the properties of massive stars, totally different from what has been obtained up to day in the literature, is predicted, such as the precocious onset of conformal sound velocity together with a hint for the possible emergence in dense matter of hidden symmetries such as scale symmetry and hidden local symmetry.

Two fast and accurate heuristic RBF learning rules for data classification.

PubMed

Rouhani, Modjtaba; Javan, Dawood S

2016-03-01

This paper presents new Radial Basis Function (RBF) learning methods for classification problems. The proposed methods use some heuristics to determine the spreads, the centers and the number of hidden neurons of network in such a way that the higher efficiency is achieved by fewer numbers of neurons, while the learning algorithm remains fast and simple. To retain network size limited, neurons are added to network recursively until termination condition is met. Each neuron covers some of train data. The termination condition is to cover all training data or to reach the maximum number of neurons. In each step, the center and spread of the new neuron are selected based on maximization of its coverage. Maximization of coverage of the neurons leads to a network with fewer neurons and indeed lower VC dimension and better generalization property. Using power exponential distribution function as the activation function of hidden neurons, and in the light of new learning approaches, it is proved that all data became linearly separable in the space of hidden layer outputs which implies that there exist linear output layer weights with zero training error. The proposed methods are applied to some well-known datasets and the simulation results, compared with SVM and some other leading RBF learning methods, show their satisfactory and comparable performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lessons Learned from Managing a Petabyte

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

Becla, J

2005-01-20

The amount of data collected and stored by the average business doubles each year. Many commercial databases are already approaching hundreds of terabytes, and at this rate, will soon be managing petabytes. More data enables new functionality and capability, but the larger scale reveals new problems and issues hidden in ''smaller'' terascale environments. This paper presents some of these new problems along with implemented solutions in the framework of a petabyte dataset for a large High Energy Physics experiment. Through experience with two persistence technologies, a commercial database and a file-based approach, we expose format-independent concepts and issues prevalent atmore » this new scale of computing.« less

Quantum learning of classical stochastic processes: The completely positive realization problem

NASA Astrophysics Data System (ADS)

Monràs, Alex; Winter, Andreas

2016-01-01

Among several tasks in Machine Learning, a specially important one is the problem of inferring the latent variables of a system and their causal relations with the observed behavior. A paradigmatic instance of this is the task of inferring the hidden Markov model underlying a given stochastic process. This is known as the positive realization problem (PRP), [L. Benvenuti and L. Farina, IEEE Trans. Autom. Control 49(5), 651-664 (2004)] and constitutes a central problem in machine learning. The PRP and its solutions have far-reaching consequences in many areas of systems and control theory, and is nowadays an important piece in the broad field of positive systems theory. We consider the scenario where the latent variables are quantum (i.e., quantum states of a finite-dimensional system) and the system dynamics is constrained only by physical transformations on the quantum system. The observable dynamics is then described by a quantum instrument, and the task is to determine which quantum instrument — if any — yields the process at hand by iterative application. We take as a starting point the theory of quasi-realizations, whence a description of the dynamics of the process is given in terms of linear maps on state vectors and probabilities are given by linear functionals on the state vectors. This description, despite its remarkable resemblance with the hidden Markov model, or the iterated quantum instrument, is however devoid of any stochastic or quantum mechanical interpretation, as said maps fail to satisfy any positivity conditions. The completely positive realization problem then consists in determining whether an equivalent quantum mechanical description of the same process exists. We generalize some key results of stochastic realization theory, and show that the problem has deep connections with operator systems theory, giving possible insight to the lifting problem in quotient operator systems. Our results have potential applications in quantum machine learning, device-independent characterization and reverse-engineering of stochastic processes and quantum processors, and more generally, of dynamical processes with quantum memory [M. Guţă, Phys. Rev. A 83(6), 062324 (2011); M. Guţă and N. Yamamoto, e-print arXiv:1303.3771(2013)].

A theory of cerebellar cortex and adaptive motor control based on two types of universal function approximation capability.

PubMed

Fujita, Masahiko

2016-03-01

Lesions of the cerebellum result in large errors in movements. The cerebellum adaptively controls the strength and timing of motor command signals depending on the internal and external environments of movements. The present theory describes how the cerebellar cortex can control signals for accurate and timed movements. A model network of the cerebellar Golgi and granule cells is shown to be equivalent to a multiple-input (from mossy fibers) hierarchical neural network with a single hidden layer of threshold units (granule cells) that receive a common recurrent inhibition (from a Golgi cell). The weighted sum of the hidden unit signals (Purkinje cell output) is theoretically analyzed regarding the capability of the network to perform two types of universal function approximation. The hidden units begin firing as the excitatory inputs exceed the recurrent inhibition. This simple threshold feature leads to the first approximation theory, and the network final output can be any continuous function of the multiple inputs. When the input is constant, this output becomes stationary. However, when the recurrent unit activity is triggered to decrease or the recurrent inhibition is triggered to increase through a certain mechanism (metabotropic modulation or extrasynaptic spillover), the network can generate any continuous signals for a prolonged period of change in the activity of recurrent signals, as the second approximation theory shows. By incorporating the cerebellar capability of two such types of approximations to a motor system, in which learning proceeds through repeated movement trials with accompanying corrections, accurate and timed responses for reaching the target can be adaptively acquired. Simple models of motor control can solve the motor error vs. sensory error problem, as well as the structural aspects of credit (or error) assignment problem. Two physiological experiments are proposed for examining the delay and trace conditioning of eyelid responses, as well as saccade adaptation, to investigate this novel idea of cerebellar processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Hidden Curriculum as Emancipatory and Non-Emancipatory Tools.

ERIC Educational Resources Information Center

Kanpol, Barry

Moral values implied in school practices and policies constitute the "hidden curriculum." Because the hidden curriculum may promote certain moral values to students, teachers are partially responsible for the moral education of students. A component of the hidden curriculum, institutional political resistance, concerns teacher opposition to…

Shift Verification and Validation

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

Pandya, Tara M.; Evans, Thomas M.; Davidson, Gregory G

2016-09-07

This documentation outlines the verification and validation of Shift for the Consortium for Advanced Simulation of Light Water Reactors (CASL). Five main types of problems were used for validation: small criticality benchmark problems; full-core reactor benchmarks for light water reactors; fixed-source coupled neutron-photon dosimetry benchmarks; depletion/burnup benchmarks; and full-core reactor performance benchmarks. We compared Shift results to measured data and other simulated Monte Carlo radiation transport code results, and found very good agreement in a variety of comparison measures. These include prediction of critical eigenvalue, radial and axial pin power distributions, rod worth, leakage spectra, and nuclide inventories over amore » burn cycle. Based on this validation of Shift, we are confident in Shift to provide reference results for CASL benchmarking.« less

Chemical shift-based identification of monosaccharide spin-systems with NMR spectroscopy to complement untargeted glycomics.

PubMed

Klukowski, Piotr; Schubert, Mario

2018-06-15

A better understanding of oligosaccharides and their wide-ranging functions in almost every aspect of biology and medicine promises to uncover hidden layers of biology and will support the development of better therapies. Elucidating the chemical structure of an unknown oligosaccharide is still a challenge. Efficient tools are required for non-targeted glycomics. Chemical shifts are a rich source of information about the topology and configuration of biomolecules, whose potential is however not fully explored for oligosaccharides. We hypothesize that the chemical shifts of each monosaccharide are unique for each saccharide type with a certain linkage pattern, so that correlated data measured by NMR spectroscopy can be used to identify the chemical nature of a carbohydrate. We present here an efficient search algorithm, GlycoNMRSearch, that matches either a subset or the entire set of chemical shifts of an unidentified monosaccharide spin system to all spin systems in an NMR database. The search output is much more precise than earlier search functions and highly similar matches suggest the chemical structure of the spin system within the oligosaccharide. Thus searching for connected chemical shift correlations within all electronically available NMR data of oligosaccharides is a very efficient way of identifying the chemical structure of unknown oligosaccharides. With an improved database in the future, GlycoNMRSearch will be even more efficient deducing chemical structures of oligosaccharides and there is a high chance that it becomes an indispensable technique for glycomics. The search algorithm presented here, together with a graphical user interface, is available at http://glyconmrsearch.santos.pwr.edu.pl. Supplementary data are available at Bioinformatics online.

Exploring Initiative as a Signal of Knowledge Co-Construction During Collaborative Problem Solving.

PubMed

Howard, Cynthia; Di Eugenio, Barbara; Jordan, Pamela; Katz, Sandra

2017-08-01

Peer interaction has been found to be conducive to learning in many settings. Knowledge co-construction (KCC) has been proposed as one explanatory mechanism. However, KCC is a theoretical construct that is too abstract to guide the development of instructional software that can support peer interaction. In this study, we present an extensive analysis of a corpus of peer dialogs that we collected in the domain of introductory Computer Science. We show that the notion of task initiative shifts correlates with both KCC and learning. Speakers take task initiative when they contribute new content that advances problem solving and that is not invited by their partner; if initiative shifts between the partners, it indicates they both contribute to problem solving. We found that task initiative shifts occur more frequently within KCC episodes than outside. In addition, task initiative shifts within KCC episodes correlate with learning for low pre-testers, and total task initiative shifts correlate with learning for high pre-testers. As recognizing task initiative shifts does not require as much deep knowledge as recognizing KCC, task initiative shifts as an indicator of productive collaboration are potentially easier to model in instructional software that simulates a peer. Copyright © 2016 Cognitive Science Society, Inc.

Apollo 16: Nothing So Hidden

NASA Technical Reports Server (NTRS)

1972-01-01

This film shows the landing and the three lunar traverses in the highland region of the moon, near the crater descartes. It includes an astronaut's eye view from the rover, lunar grand prix, discovery of the house-sized rock, lunar lift-off and eva 173,000 miles above the earth. Microphones and cameras in mission control record the emergency problem solving during the prelanding crisis and the reactions of scientists on earth as the astronauts explore the moon.

Polsar Land Cover Classification Based on Hidden Polarimetric Features in Rotation Domain and Svm Classifier

NASA Astrophysics Data System (ADS)

Tao, C.-S.; Chen, S.-W.; Li, Y.-Z.; Xiao, S.-P.

2017-09-01

Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR) data utilization. Rollinvariant polarimetric features such as H / Ani / α / Span are commonly adopted in PolSAR land cover classification. However, target orientation diversity effect makes PolSAR images understanding and interpretation difficult. Only using the roll-invariant polarimetric features may introduce ambiguity in the interpretation of targets' scattering mechanisms and limit the followed classification accuracy. To address this problem, this work firstly focuses on hidden polarimetric feature mining in the rotation domain along the radar line of sight using the recently reported uniform polarimetric matrix rotation theory and the visualization and characterization tool of polarimetric coherence pattern. The former rotates the acquired polarimetric matrix along the radar line of sight and fully describes the rotation characteristics of each entry of the matrix. Sets of new polarimetric features are derived to describe the hidden scattering information of the target in the rotation domain. The latter extends the traditional polarimetric coherence at a given rotation angle to the rotation domain for complete interpretation. A visualization and characterization tool is established to derive new polarimetric features for hidden information exploration. Then, a classification scheme is developed combing both the selected new hidden polarimetric features in rotation domain and the commonly used roll-invariant polarimetric features with a support vector machine (SVM) classifier. Comparison experiments based on AIRSAR and multi-temporal UAVSAR data demonstrate that compared with the conventional classification scheme which only uses the roll-invariant polarimetric features, the proposed classification scheme achieves both higher classification accuracy and better robustness. For AIRSAR data, the overall classification accuracy with the proposed classification scheme is 94.91 %, while that with the conventional classification scheme is 93.70 %. Moreover, for multi-temporal UAVSAR data, the averaged overall classification accuracy with the proposed classification scheme is up to 97.08 %, which is much higher than the 87.79 % from the conventional classification scheme. Furthermore, for multitemporal PolSAR data, the proposed classification scheme can achieve better robustness. The comparison studies also clearly demonstrate that mining and utilization of hidden polarimetric features and information in the rotation domain can gain the added benefits for PolSAR land cover classification and provide a new vision for PolSAR image interpretation and application.

Multi-bit wavelength coding phase-shift-keying optical steganography based on amplified spontaneous emission noise

NASA Astrophysics Data System (ADS)

Wang, Cheng; Wang, Hongxiang; Ji, Yuefeng

2018-01-01

In this paper, a multi-bit wavelength coding phase-shift-keying (PSK) optical steganography method is proposed based on amplified spontaneous emission noise and wavelength selection switch. In this scheme, the assignment codes and the delay length differences provide a large two-dimensional key space. A 2-bit wavelength coding PSK system is simulated to show the efficiency of our proposed method. The simulated results demonstrate that the stealth signal after encoded and modulated is well-hidden in both time and spectral domains, under the public channel and noise existing in the system. Besides, even the principle of this scheme and the existence of stealth channel are known to the eavesdropper, the probability of recovering the stealth data is less than 0.02 if the key is unknown. Thus it can protect the security of stealth channel more effectively. Furthermore, the stealth channel will results in 0.48 dB power penalty to the public channel at 1 × 10-9 bit error rate, and the public channel will have no influence on the receiving of the stealth channel.

Crystallographic snapshots of active site metal shift in E. coli fructose 1,6-bisphosphate aldolase.

PubMed

Tran, Huyen-Thi; Lee, Seon-Hwa; Ho, Thien-Hoang; Hong, Seung-Hye; Huynh, Kim-Hung; Ahn, Yeh-Jin; Oh, Deok-Kun; Kang, Lin-Woo

2016-12-01

Fructose 1,6-bisphosphate aldolase (FBA) is important for both glycolysis and gluconeogenesis in life. Class II (zinc dependent) FBA is an attractive target for the development of antibiotics against protozoa, bacteria, and fungi, and is also widely used to produce various high-value stereoisomers in the chemical and pharmaceutical industry. In this study, the crystal structures of class II Escherichia coli FBA (EcFBA) were determined from four different crystals, with resolutions between 1.8 Å and 2.0 Å. Native EcFBA structures showed two separate sites of Zn1 (interior position) and Zn2 (active site surface position) for Zn2＋ ion. Citrate and TRIS bound EcFBA structures showed Zn2＋ position exclusively at Zn2. Crystallographic snapshots of EcFBA structures with and without ligand binding proposed the rationale of metal shift at the active site, which might be a hidden mechanism to keep the trace metal cofactor Zn2＋ within EcFBA without losing it. [BMB Reports 2016; 49(12): 681-686].

Photoacoustic imaging of hidden dental caries by using a fiber-based probing system

NASA Astrophysics Data System (ADS)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2017-04-01

Photoacoustic method to detect hidden dental caries is proposed. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating laser light to occlusal surface of model tooth. By making a map of intensity of these high frequency components, photoacoustic images of hidden caries were successfully obtained. A photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for using clinical application, and clear photoacoustic image of hidden caries was also obtained by this system.

Three computational mise-en-scènes of red- and blue-shifted hydrogen bonding motifs: Concept of negative intramolecular coupling-What else?

NASA Astrophysics Data System (ADS)

Kryachko, Eugene S.

This work is a kind of attempt to rethink some problems which are related to the blue-shifted "hydrogen bonds" and which have been left in the past decade as not yet fully resolved. The impetus for such rethink is originated from the three computational mise-en-scènes on red- and blue-shifted hydrogen bonding motifs, which are aimed to be thoroughly studied in this work, thus resolving the above problems.

--No Title--

Science.gov Websites

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Game-theoretic cooperativity in networks of self-interested units

NASA Astrophysics Data System (ADS)

Barto, Andrew G.

1986-08-01

The behavior of theoretical neural networks is often described in terms of competition and cooperation. I present an approach to network learning that is related to game and team problems in which competition and cooperation have more technical meanings. I briefly describe the application of stochastic learning automata to game and team problems and then present an adaptive element that is a synthesis of aspects of stochastic learning automata and typical neuron-like adaptive elements. These elements act as self-interested agents that work toward improving their performance with respect to their individual preference orderings. Networks of these elements can solve a variety of team decision problems, some of which take the form of layered networks in which the ``hidden units'' become appropriate functional components as they attempt to improve their own payoffs.

Neural architecture design based on extreme learning machine.

PubMed

Bueno-Crespo, Andrés; García-Laencina, Pedro J; Sancho-Gómez, José-Luis

2013-12-01

Selection of the optimal neural architecture to solve a pattern classification problem entails to choose the relevant input units, the number of hidden neurons and its corresponding interconnection weights. This problem has been widely studied in many research works but their solutions usually involve excessive computational cost in most of the problems and they do not provide a unique solution. This paper proposes a new technique to efficiently design the MultiLayer Perceptron (MLP) architecture for classification using the Extreme Learning Machine (ELM) algorithm. The proposed method provides a high generalization capability and a unique solution for the architecture design. Moreover, the selected final network only retains those input connections that are relevant for the classification task. Experimental results show these advantages. Copyright © 2013 Elsevier Ltd. All rights reserved.

Natural hidden antibodies reacting with DNA or cardiolipin bind to thymocytes and evoke their death.

PubMed

Zamulaeva, I A; Lekakh, I V; Kiseleva, V I; Gabai, V L; Saenko, A S; Shevchenko, A S; Poverenny, A M

1997-08-18

Both free and hidden natural antibodies to DNA or cardiolipin were obtained from immunoglobulins of a normal donor. The free antibodies reacting with DNA or cardiolipin were isolated by means of affinity chromatography. Antibodies occurring in an hidden state were disengaged from the depleted immunoglobulins by ion-exchange chromatography and were then affinity-isolated on DNA or cardiolipin sorbents. We used flow cytometry to study the ability of free and hidden antibodies to bind to rat thymocytes. Simultaneously, plasma membrane integrity was tested by propidium iodide (PI) exclusion. The hidden antibodies reacted with 65.2 +/- 10.9% of the thymocytes and caused a fast plasma membrane disruption. Cells (28.7 +/- 7.1%) were stained with PI after incubation with the hidden antibodies for 1 h. The free antibodies bound to a very small fraction of the thymocytes and did not evoke death as compared to control without antibodies. The possible reason for the observed effects is difference in reactivity of the free and hidden antibodies to phospholipids. While free antibodies reacted preferentially with phosphotidylcholine, hidden antibodies reacted with cardiolipin and phosphotidylserine.

Raising awareness of the hidden curriculum in veterinary medical education: a review and call for research.

PubMed

Whitcomb, Tiffany L

2014-01-01

The hidden curriculum is characterized by information that is tacitly conveyed to and among students about the cultural and moral environment in which they find themselves. Although the hidden curriculum is often defined as a distinct entity, tacit information is conveyed to students throughout all aspects of formal and informal curricula. This unconsciously communicated knowledge has been identified across a wide spectrum of educational environments and is known to have lasting and powerful impacts, both positive and negative. Recently, medical education research on the hidden curriculum of becoming a doctor has come to the forefront as institutions struggle with inconsistencies between formal and hidden curricula that hinder the practice of patient-centered medicine. Similarly, the complex ethical questions that arise during the practice and teaching of veterinary medicine have the potential to cause disagreement between what the institution sets out to teach and what is actually learned. However, the hidden curriculum remains largely unexplored for this field. Because the hidden curriculum is retained effectively by students, elucidating its underlying messages can be a key component of program refinement. A review of recent literature about the hidden curriculum in a variety of fields, including medical education, will be used to explore potential hidden curricula in veterinary medicine and draw attention to the need for further investigation.

Smart aircraft fastener evaluation (SAFE) system: a condition-based corrosion detection system for aging aircraft

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg; Paul, Clare A.

1996-05-01

The smart aircraft fastener evaluation (SAFE) system is an advanced structural health monitoring effort to detect and characterize corrosion in hidden and inaccessible locations of aircraft structures. Hidden corrosion is the number one logistics problem for the U.S. Air Force, with an estimated maintenance cost of $700M per year in 1990 dollars. The SAFE system incorporates a solid-state electrochemical microsensor and smart sensor electronics in the body of a Hi-Lok aircraft fastener to process and autonomously report corrosion status to aircraft maintenance personnel. The long-term payoff for using SAFE technology will be in predictive maintenance for aging aircraft and rotorcraft systems, fugitive emissions applications such as control valves, chemical pipeline vessels, and industrial boilers. Predictive maintenance capability, service, and repair will replace the current practice of scheduled maintenance to substantially reduce operational costs. A summary of the SAFE concept, laboratory test results, and future field test plans is presented.

Hamiltonian dynamics of a quantum of space: hidden symmetries and spectrum of the volume operator, and discrete orthogonal polynomials

NASA Astrophysics Data System (ADS)

Aquilanti, Vincenzo; Marinelli, Dimitri; Marzuoli, Annalisa

2013-05-01

The action of the quantum mechanical volume operator, introduced in connection with a symmetric representation of the three-body problem and recently recognized to play a fundamental role in discretized quantum gravity models, can be given as a second-order difference equation which, by a complex phase change, we turn into a discrete Schrödinger-like equation. The introduction of discrete potential-like functions reveals the surprising crucial role here of hidden symmetries, first discovered by Regge for the quantum mechanical 6j symbols; insight is provided into the underlying geometric features. The spectrum and wavefunctions of the volume operator are discussed from the viewpoint of the Hamiltonian evolution of an elementary ‘quantum of space’, and a transparent asymptotic picture of the semiclassical and classical regimes emerges. The definition of coordinates adapted to the Regge symmetry is exploited for the construction of a novel set of discrete orthogonal polynomials, characterizing the oscillatory components of torsion-like modes.

Maximum mutual information estimation of a simplified hidden MRF for offline handwritten Chinese character recognition

NASA Astrophysics Data System (ADS)

Xiong, Yan; Reichenbach, Stephen E.

1999-01-01

Understanding of hand-written Chinese characters is at such a primitive stage that models include some assumptions about hand-written Chinese characters that are simply false. So Maximum Likelihood Estimation (MLE) may not be an optimal method for hand-written Chinese characters recognition. This concern motivates the research effort to consider alternative criteria. Maximum Mutual Information Estimation (MMIE) is an alternative method for parameter estimation that does not derive its rationale from presumed model correctness, but instead examines the pattern-modeling problem in automatic recognition system from an information- theoretic point of view. The objective of MMIE is to find a set of parameters in such that the resultant model allows the system to derive from the observed data as much information as possible about the class. We consider MMIE for recognition of hand-written Chinese characters using on a simplified hidden Markov Random Field. MMIE provides improved performance improvement over MLE in this application.

Utterance independent bimodal emotion recognition in spontaneous communication

NASA Astrophysics Data System (ADS)

Tao, Jianhua; Pan, Shifeng; Yang, Minghao; Li, Ya; Mu, Kaihui; Che, Jianfeng

2011-12-01

Emotion expressions sometimes are mixed with the utterance expression in spontaneous face-to-face communication, which makes difficulties for emotion recognition. This article introduces the methods of reducing the utterance influences in visual parameters for the audio-visual-based emotion recognition. The audio and visual channels are first combined under a Multistream Hidden Markov Model (MHMM). Then, the utterance reduction is finished by finding the residual between the real visual parameters and the outputs of the utterance related visual parameters. This article introduces the Fused Hidden Markov Model Inversion method which is trained in the neutral expressed audio-visual corpus to solve the problem. To reduce the computing complexity the inversion model is further simplified to a Gaussian Mixture Model (GMM) mapping. Compared with traditional bimodal emotion recognition methods (e.g., SVM, CART, Boosting), the utterance reduction method can give better results of emotion recognition. The experiments also show the effectiveness of our emotion recognition system when it was used in a live environment.

Integrating Decision Tree and Hidden Markov Model (HMM) for Subtype Prediction of Human Influenza A Virus

NASA Astrophysics Data System (ADS)

Attaluri, Pavan K.; Chen, Zhengxin; Weerakoon, Aruna M.; Lu, Guoqing

Multiple criteria decision making (MCDM) has significant impact in bioinformatics. In the research reported here, we explore the integration of decision tree (DT) and Hidden Markov Model (HMM) for subtype prediction of human influenza A virus. Infection with influenza viruses continues to be an important public health problem. Viral strains of subtype H3N2 and H1N1 circulates in humans at least twice annually. The subtype detection depends mainly on the antigenic assay, which is time-consuming and not fully accurate. We have developed a Web system for accurate subtype detection of human influenza virus sequences. The preliminary experiment showed that this system is easy-to-use and powerful in identifying human influenza subtypes. Our next step is to examine the informative positions at the protein level and extend its current functionality to detect more subtypes. The web functions can be accessed at http://glee.ist.unomaha.edu/.

Passive acoustic leak detection for sodium cooled fast reactors using hidden Markov models

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

Riber Marklund, A.; Kishore, S.; Prakash, V.

2015-07-01

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970's and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), themore » proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control. (authors)« less

Identifying influential user communities on the social network

NASA Astrophysics Data System (ADS)

Hu, Weishu; Gong, Zhiguo; Hou U, Leong; Guo, Jingzhi

2015-10-01

Nowadays social network services have been popularly used in electronic commerce systems. Users on the social network can develop different relationships based on their common interests and activities. In order to promote the business, it is interesting to explore hidden relationships among users developed on the social network. Such knowledge can be used to locate target users for different advertisements and to provide effective product recommendations. In this paper, we define and study a novel community detection problem that is to discover the hidden community structure in large social networks based on their common interests. We observe that the users typically pay more attention to those users who share similar interests, which enable a way to partition the users into different communities according to their common interests. We propose two algorithms to detect influential communities using common interests in large social networks efficiently and effectively. We conduct our experimental evaluation using a data set from Epinions, which demonstrates that our method achieves 4-11.8% accuracy improvement over the state-of-the-art method.

Making better decisions in groups

PubMed Central

Frith, Chris D.

2017-01-01

We review the literature to identify common problems of decision-making in individuals and groups. We are guided by a Bayesian framework to explain the interplay between past experience and new evidence, and the problem of exploring the space of hypotheses about all the possible states that the world could be in and all the possible actions that one could take. There are strong biases, hidden from awareness, that enter into these psychological processes. While biases increase the efficiency of information processing, they often do not lead to the most appropriate action. We highlight the advantages of group decision-making in overcoming biases and searching the hypothesis space for good models of the world and good solutions to problems. Diversity of group members can facilitate these achievements, but diverse groups also face their own problems. We discuss means of managing these pitfalls and make some recommendations on how to make better group decisions. PMID:28878973

Pre-service teachers’ challenges in presenting mathematical problems

NASA Astrophysics Data System (ADS)

Desfitri, R.

2018-01-01

The purpose of this study was to analyzed how pre-service teachers prepare and assigned tasks or assignments in teaching practice situations. This study was also intended to discuss about kind of tasks or assignments they gave to students. Participants of this study were 15 selected pre-service mathematics teachers from mathematics education department who took part on microteaching class as part of teaching preparation program. Based on data obtained, it was occasionally found that there were hidden errors on questions or tasks assigned by pre-service teachers which might lead their students not to be able to reach a logical or correct answer. Although some answers might seem to be true, they were illogical or unfavourable. It is strongly recommended that pre-service teachers be more careful when posing mathematical problems so that students do not misunderstand the problems or the concepts, since both teachers and students were sometimes unaware of errors in problems being worked on.

What if ? On alternative conceptual models and the problem of their implementation

NASA Astrophysics Data System (ADS)

Neuberg, Jurgen

2015-04-01

Seismic and other monitoring techniques rely on a set of conceptual models on the base of which data sets can be interpreted. In order to do this on an operational level in volcano observatories these models need to be tested and ready for an interpretation in a timely manner. Once established, scientists in charge advising stakeholders and decision makers often stick firmly to these models to avoid confusion by giving alternative versions of interpretations to non-experts. This talk gives an overview of widely accepted conceptual models to interpret seismic and deformation data, and highlights in a few case studies some of the arising problems. Aspects covered include knowledge transfer between research institutions and observatories, data sharing, the problem of up-taking advice, and some hidden problems which turn out to be much more critical in assessing volcanic hazard than the actual data interpretation.

Learning and optimization with cascaded VLSI neural network building-block chips

NASA Technical Reports Server (NTRS)

Duong, T.; Eberhardt, S. P.; Tran, M.; Daud, T.; Thakoor, A. P.

1992-01-01

To demonstrate the versatility of the building-block approach, two neural network applications were implemented on cascaded analog VLSI chips. Weights were implemented using 7-b multiplying digital-to-analog converter (MDAC) synapse circuits, with 31 x 32 and 32 x 32 synapses per chip. A novel learning algorithm compatible with analog VLSI was applied to the two-input parity problem. The algorithm combines dynamically evolving architecture with limited gradient-descent backpropagation for efficient and versatile supervised learning. To implement the learning algorithm in hardware, synapse circuits were paralleled for additional quantization levels. The hardware-in-the-loop learning system allocated 2-5 hidden neurons for parity problems. Also, a 7 x 7 assignment problem was mapped onto a cascaded 64-neuron fully connected feedback network. In 100 randomly selected problems, the network found optimal or good solutions in most cases, with settling times in the range of 7-100 microseconds.

Algorithm 937: MINRES-QLP for Symmetric and Hermitian Linear Equations and Least-Squares Problems

PubMed Central

Choi, Sou-Cheng T.; Saunders, Michael A.

2014-01-01

We describe algorithm MINRES-QLP and its FORTRAN 90 implementation for solving symmetric or Hermitian linear systems or least-squares problems. If the system is singular, MINRES-QLP computes the unique minimum-length solution (also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes a potential instability in the original MINRES algorithm. A positive-definite pre-conditioner may be supplied. Our FORTRAN 90 implementation illustrates a design pattern that allows users to make problem data known to the solver but hidden and secure from other program units. In particular, we circumvent the need for reverse communication. Example test programs input and solve real or complex problems specified in Matrix Market format. While we focus here on a FORTRAN 90 implementation, we also provide and maintain MATLAB versions of MINRES and MINRES-QLP. PMID:25328255

Research Paradigm Shifts and Their Bibliographic Consequences for English Composition Researchers.

ERIC Educational Resources Information Center

Scott, Patrick

There are four problems in modern composition bibliography that result directly from the continuing research paradigm instability in the field. The first problem is that of definition. Composition is a hybrid, practical sort of field, with very ill-defined and shifting boundaries. The recent extension of composition from "formal writing…

Heating up the Galaxy with hidden photons

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

Dubovsky, Sergei; Hernández-Chifflet, Guzmán, E-mail: dubovsky@nyu.edu, E-mail: ghc236@nyu.edu

2015-12-01

We elaborate on the dynamics of ionized interstellar medium in the presence of hidden photon dark matter. Our main focus is the ultra-light regime, where the hidden photon mass is smaller than the plasma frequency in the Milky Way. We point out that as a result of the Galactic plasma shielding direct detection of ultra-light photons in this mass range is especially challenging. However, we demonstrate that ultra-light hidden photon dark matter provides a powerful heating source for the ionized interstellar medium. This results in a strong bound on the kinetic mixing between hidden and regular photons all the waymore » down to the hidden photon masses of order 10{sup −20} eV.« less

Heating up the Galaxy with hidden photons

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

Dubovsky, Sergei; Hernández-Chifflet, Guzmán; Instituto de Física, Facultad de Ingeniería, Universidad de la República,Montevideo, 11300

2015-12-29

We elaborate on the dynamics of ionized interstellar medium in the presence of hidden photon dark matter. Our main focus is the ultra-light regime, where the hidden photon mass is smaller than the plasma frequency in the Milky Way. We point out that as a result of the Galactic plasma shielding direct detection of ultra-light photons in this mass range is especially challenging. However, we demonstrate that ultra-light hidden photon dark matter provides a powerful heating source for the ionized interstellar medium. This results in a strong bound on the kinetic mixing between hidden and regular photons all the waymore » down to the hidden photon masses of order 10{sup −20} eV.« less

Comparison of the oral health problems and behavior of male daytime-only and night-shift office workers: An Internet survey

PubMed Central

Ishizuka, Yoichi; Yoshino, Koichi; Takayanagi, Atsushi; Sugihara, Naoki; Maki, Yoshinobu; Kamijyo, Hideyuki

2016-01-01

Objective: The aim of this study was to compare the oral health problems and behavior of full-time male daytime-only and night shift office workers. Methods: The participants were recruited by applying screening procedures to a pool of Japanese registrants in an online database. During the period of 20 February 2015 to 11 March 2015, participants were asked to complete a questionnaire about their oral health. A total of 325 daytime-only workers and 351 workers who sometimes worked night shifts, ages 30 to 69, were analyzed in this study. Results: Overall, the mean number of teeth of the night shift workers was lower than that of the daytime-only workers (p=0.002). When analyzed by age group, a significant difference was seen in the 50-69 age group (p=0.016). The percentage of night shift workers with decayed teeth was higher than that of the daytime-only workers (p<0.001). The night shift workers were more likely to report gingival bleeding (p=0.015) and stomatitis (p=0.025) than the daytime-only workers. The percentage of night shift workers reporting frequent brushing behavior was lower than that of the daytime-only workers (p=0.040). The independent variables found to correlate significantly with tooth decay were night shift work (OR, 1.79; 95% CI, 1.20-2.67), current smoking habit (OR, 1.66; 95% CI, 1.13-2.46), and BMI of ≥25 (OR, 1.56; 95% CI, 1.02-2.39). Conclusions: These results indicate a relationship between night shift work and oral health problems. Night shift workers may require additional support for oral health maintenance. PMID:27010087

Comparison of the oral health problems and behavior of male daytime-only and night-shift office workers: An Internet survey.

PubMed

Ishizuka, Yoichi; Yoshino, Koichi; Takayanagi, Atsushi; Sugihara, Naoki; Maki, Yoshinobu; Kamijyo, Hideyuki

2016-05-25

The aim of this study was to compare the oral health problems and behavior of full-time male daytime-only and night shift office workers. The participants were recruited by applying screening procedures to a pool of Japanese registrants in an online database. During the period of 20 February 2015 to 11 March 2015, participants were asked to complete a questionnaire about their oral health. A total of 325 daytime-only workers and 351 workers who sometimes worked night shifts, ages 30 to 69, were analyzed in this study. Overall, the mean number of teeth of the night shift workers was lower than that of the daytime-only workers (p=0.002). When analyzed by age group, a significant difference was seen in the 50-69 age group (p=0.016). The percentage of night shift workers with decayed teeth was higher than that of the daytime-only workers (p<0.001). The night shift workers were more likely to report gingival bleeding (p=0.015) and stomatitis (p=0.025) than the daytime-only workers. The percentage of night shift workers reporting frequent brushing behavior was lower than that of the daytime-only workers (p=0.040). The independent variables found to correlate significantly with tooth decay were night shift work (OR, 1.79; 95% CI, 1.20-2.67), current smoking habit (OR, 1.66; 95% CI, 1.13-2.46), and BMI of ≥25 (OR, 1.56; 95% CI, 1.02-2.39). These results indicate a relationship between night shift work and oral health problems. Night shift workers may require additional support for oral health maintenance.

Spyware.

PubMed

Bergren, Martha Dewey

2004-10-01

School nurses access an enormous amount of information through the Internet. Although most avid computer users are savvy to the threat of viruses to the integrity of data, many who surf the Web do not know that their data and the functioning of their computer is at risk to another hidden threat--spyware. This article will describe spyware, why it is a problem, how it is transmitted to a personal or business computer, how to prevent spyware infestation, and how to delete it.

Connectionism and Compositional Semantics

DTIC Science & Technology

1989-05-01

can use their hidden layers to learn difficult discriminations. such as panty or the Penzias two clumps/three clumps problem, where the output is...sauce." For novel sentences that are similar to the training sentences (e.g., train on "the girl hit the boy," test on -the boy hit the girl "), the...overridden by semantic considerations. as in this example from Wendy Lehnert (personal communicanon): (5) John saw the girl with the telescope in a red

Eating disorders: a hidden phenomenon in outpatient mental health?

PubMed

Fursland, Anthea; Watson, Hunna J

2014-05-01

Eating disorders are common but underdiagnosed illnesses. Help-seeking for co-occurring issues, such as anxiety and depression, are common. To identify the prevalence of eating problems, using the SCOFF, and eating disorders when screening positive on the SCOFF (i.e., ≥2), among patients seeking help for anxiety and depression at a community-based mental health service. Patients (N = 260) consecutively referred and assessed for anxiety and depression treatment were administered the SCOFF screening questionnaire and a semi-structured standardized diagnostic interview during routine intake. 18.5% (48/260) scored ≥2 on the SCOFF, indicating eating problems. Of these, 41% (19/48) met criteria for an eating disorder. Thus, overall, 7.3% (19/260) of the sample met criteria for a DSM-IV eating disorder. Those scoring ≥2 on the SCOFF were more likely to: be female (p = 0.001), younger (p = 0.003), and have a history of self-harm (p < 0.001). This study confirms that eating disorders are a hidden phenomenon in general outpatient mental health. By using a standardized diagnostic interview to establish diagnosis rather than self- or staff-report, the study builds on limited previous findings. The naturalistic study setting shows that screening for eating disorders can be easily built into routine intake practice, and successfully identifies treatment need. Copyright © 2013 Wiley Periodicals, Inc.

Improved Leg Tracking Considering Gait Phase and Spline-Based Interpolation during Turning Motion in Walk Tests.

PubMed

Yorozu, Ayanori; Moriguchi, Toshiki; Takahashi, Masaki

2015-09-04

Falling is a common problem in the growing elderly population, and fall-risk assessment systems are needed for community-based fall prevention programs. In particular, the timed up and go test (TUG) is the clinical test most often used to evaluate elderly individual ambulatory ability in many clinical institutions or local communities. This study presents an improved leg tracking method using a laser range sensor (LRS) for a gait measurement system to evaluate the motor function in walk tests, such as the TUG. The system tracks both legs and measures the trajectory of both legs. However, both legs might be close to each other, and one leg might be hidden from the sensor. This is especially the case during the turning motion in the TUG, where the time that a leg is hidden from the LRS is longer than that during straight walking and the moving direction rapidly changes. These situations are likely to lead to false tracking and deteriorate the measurement accuracy of the leg positions. To solve these problems, a novel data association considering gait phase and a Catmull-Rom spline-based interpolation during the occlusion are proposed. From the experimental results with young people, we confirm   that the proposed methods can reduce the chances of false tracking. In addition, we verify the measurement accuracy of the leg trajectory compared to a three-dimensional motion analysis system (VICON).

Modeling volatility using state space models.

PubMed

Timmer, J; Weigend, A S

1997-08-01

In time series problems, noise can be divided into two categories: dynamic noise which drives the process, and observational noise which is added in the measurement process, but does not influence future values of the system. In this framework, we show that empirical volatilities (the squared relative returns of prices) exhibit a significant amount of observational noise. To model and predict their time evolution adequately, we estimate state space models that explicitly include observational noise. We obtain relaxation times for shocks in the logarithm of volatility ranging from three weeks (for foreign exchange) to three to five months (for stock indices). In most cases, a two-dimensional hidden state is required to yield residuals that are consistent with white noise. We compare these results with ordinary autoregressive models (without a hidden state) and find that autoregressive models underestimate the relaxation times by about two orders of magnitude since they do not distinguish between observational and dynamic noise. This new interpretation of the dynamics of volatility in terms of relaxators in a state space model carries over to stochastic volatility models and to GARCH models, and is useful for several problems in finance, including risk management and the pricing of derivative securities. Data sets used: Olsen & Associates high frequency DEM/USD foreign exchange rates (8 years). Nikkei 225 index (40 years). Dow Jones Industrial Average (25 years).

Ethical violations in the clinical setting: the hidden curriculum learning experience of Pakistani nurses.

PubMed

Jafree, Sara Rizvi; Zakar, Rubeena; Fischer, Florian; Zakar, Muhammad Zakria

2015-03-19

The importance of the hidden curriculum is recognised as a practical training ground for the absorption of medical ethics by healthcare professionals. Pakistan's healthcare sector is hampered by the exclusion of ethics from medical and nursing education curricula and the absence of monitoring of ethical violations in the clinical setting. Nurses have significant knowledge of the hidden curriculum taught during clinical practice, due to long working hours in the clinic and front-line interaction with patients and other practitioners. The means of inquiry for this study was qualitative, with 20 interviews and four focus group discussions used to identify nurses' clinical experiences of ethical violations. Content analysis was used to discover sub-categories of ethical violations, as perceived by nurses, within four pre-defined categories of nursing codes of ethics: 1) professional guidelines and integrity, 2) patient informed consent, 3) patient rights, and 4) co-worker coordination for competency, learning and patient safety. Ten sub-categories of ethical violations were found: nursing students being used as adjunct staff, nurses having to face frequent violence in the hospital setting, patient reluctance to receive treatment from nurses, the near-absence of consent taken from patients for most non-surgical medical procedures, the absence of patient consent taking for receiving treatment from student nurses, the practice of patient discrimination on the basis of a patient's socio-demographic status, nurses withdrawing treatment out of fear for their safety, a non-learning culture and, finally, blame-shifting and non-reportage of errors. Immediate and urgent attention is required to reduce ethical violations in the healthcare sector in Pakistan through collaborative efforts by the government, the healthcare sector, and ethics regulatory bodies. Also, changes in socio-cultural values in hospital organisation, public awareness of how to conveniently report ethical violations by practitioners and public perceptions of nurse identity are needed.

Deep history impacts present-day ecology and biodiversity

PubMed Central

Vitt, Laurie J.; Pianka, Eric R.

2005-01-01

Lizards and snakes putatively arose between the early Jurassic and late Triassic; they diversified worldwide and now occupy many different ecological niches, making them ideal for testing theories on the origin of ecological traits. We propose and test the “deep history hypothesis,” which claims that differences in ecological traits among species arose early in evolutionary history of major clades, and that present-day assemblages are structured largely because of ancient, preexisting differences. We combine phylogenetic data with ecological data collected over nearly 40 years to reconstruct the evolution of dietary shifts in squamate reptiles. Data on diets of 184 lizard species in 12 families from 4 continents reveal significant dietary shifts at 6 major divergence points, reducing variation by 79.8%. The most striking dietary divergence (27.6%) occurred in the late Triassic, when Iguania and Scleroglossa split. These two clades occupy different regions of dietary niche space. Acquisition of chemical prey discrimination, jaw prehension, and wide foraging provided scleroglossans access to sedentary and hidden prey that are unavailable to iguanians. This cladogenic event may have profoundly influenced subsequent evolutionary history and diversification. We suggest the hypothesis that ancient events in squamate cladogenesis, rather than present-day competition, caused dietary shifts in major clades such that some lizard clades gained access to new resources, which in turn led to much of the biodiversity observed today. PMID:15867150

"It's Not Always What It Seems": Exploring the Hidden Curriculum within a Doctoral Program

ERIC Educational Resources Information Center

Foot, Rachel Elizabeth

2017-01-01

The purpose of this qualitative, naturalistic study was to explore the ways in which hidden curriculum might influence doctoral student success. Two questions guided the study: (a) How do doctoral students experience the hidden curriculum? (b) What forms of hidden curricula can be identified in a PhD program? Data were collected from twelve…

The hidden and informal curriculum across the continuum of training: A cross-sectional qualitative study.

PubMed

Doja, Asif; Bould, M Dylan; Clarkin, Chantalle; Eady, Kaylee; Sutherland, Stephanie; Writer, Hilary

2016-04-01

The hidden and informal curricula refer to learning in response to unarticulated processes and constraints, falling outside the formal medical curriculum. The hidden curriculum has been identified as requiring attention across all levels of learning. We sought to assess the knowledge and perceptions of the hidden and informal curricula across the continuum of learning at a single institution. Focus groups were held with undergraduate and postgraduate learners and faculty to explore knowledge and perceptions relating to the hidden and informal curricula. Thematic analysis was conducted both inductively by research team members and deductively using questions structured by the existing literature. Participants highlighted several themes related to the presence of the hidden and informal curricula in medical training and practice, including: the privileging of some specialties over others; the reinforcement of hierarchies within medicine; and a culture of tolerance towards unprofessional behaviors. Participants acknowledged the importance of role modeling in the development of professional identities and discussed the deterioration in idealism that occurs. Common issues pertaining to the hidden curriculum exist across all levels of learners, including faculty. Increased awareness of these issues could allow for the further development of methods to address learning within the hidden curriculum.

The hidden and informal curriculum across the continuum of training: A cross-sectional qualitative study.

PubMed

Doja, Asif; Bould, M Dylan; Clarkin, Chantalle; Eady, Kaylee; Sutherland, Stephanie; Writer, Hilary

2016-01-01

The hidden and informal curricula refer to learning in response to unarticulated processes and constraints, falling outside the formal medical curriculum. The hidden curriculum has been identified as requiring attention across all levels of learning. We sought to assess the knowledge and perceptions of the hidden and informal curricula across the continuum of learning at a single institution. Focus groups were held with undergraduate and postgraduate learners and faculty to explore knowledge and perceptions relating to the hidden and informal curricula. Thematic analysis was conducted both inductively by research team members and deductively using questions structured by the existing literature. Participants highlighted several themes related to the presence of the hidden and informal curricula in medical training and practice, including: the privileging of some specialties over others; the reinforcement of hierarchies within medicine; and a culture of tolerance towards unprofessional behaviors. Participants acknowledged the importance of role modeling in the development of professional identities and discussed the deterioration in idealism that occurs. Common issues pertaining to the hidden curriculum exist across all levels of learners, including faculty. Increased awareness of these issues could allow for the further development of methods to address learning within the hidden curriculum.

Hidden Farmworker Labor Camps in North Carolina: An Indicator of Structural Vulnerability

PubMed Central

Summers, Phillip; Quandt, Sara A.; Talton, Jennifer W.; Galván, Leonardo

2015-01-01

Objectives. We used geographic information systems (GIS) to delineate whether farmworker labor camps were hidden and to determine whether hidden camps differed from visible camps in terms of physical and resident characteristics. Methods. We collected data using observation, interview, and public domain GIS data for 180 farmworker labor camps in east central North Carolina. A hidden camp was defined as one that was at least 0.15 miles from an all-weather road or located behind natural or manufactured objects. Hidden camps were compared with visible camps in terms of physical and resident characteristics. Results. More than one third (37.8%) of the farmworker labor camps were hidden. Hidden camps were significantly larger (42.7% vs 17.0% with 21 or more residents; P ≤ .001; and 29.4% vs 13.5% with 3 or more dwellings; P = .002) and were more likely to include barracks (50% vs 19.6%; P ≤ .001) than were visible camps. Conclusions. Poor housing conditions in farmworker labor camps often go unnoticed because they are hidden in the rural landscape, increasing farmworker vulnerability. Policies that promote greater community engagement with farmworker labor camp residents to reduce structural vulnerability should be considered. PMID:26469658

Sleep disturbances among offshore fleet workers: a questionnaire-based survey.

PubMed

Hansen, Jakob Hønborg; Holmen, Ingunn Marie

2011-01-01

BACKGROUND. Shift work is related to fatigue and desynchronization with the external environment. This study investigates how 6-h shifts and 12-h shifts affects sleep and safety in workers onboard offshore supply vessels, and if any differences exist between the two working schedules. MATERIAL AND METHODS. A questionnaire study was carried out in the North Sea, Australia, Africa, South America, and the Far East, with 577 participants. The offshore fleet workers gave information on parameters related to sleep disturbances, causes of sleep disturbances, and safety. Regional differences in these parameters were also investigated. RESULTS. Workers on 6-hour shifts reported significantly more sleep problems than 12-hour shift workers did (p 〈 0.01). The 6-hour workers were more affected by noise (p 〈 0.01) and shift-work itself (p 〈 0.01). CONCLUSIONS. Those working 6-hour shifts suffer more from sleep disturbances than those on 12-hour shifts, but this is not reflected in the perception of safety within the individual. Noise and shift-work itself is more of a problem in the 12-hour workers. Differences in safety culture and work morale are likely to cause the differences between regions.

Influence of OPD in wavelength-shifting interferometry

NASA Astrophysics Data System (ADS)

Wang, Hongjun; Tian, Ailing; Liu, Bingcai; Dang, Juanjuan

2009-12-01

Phase-shifting interferometry is a powerful tool for high accuracy optical measurement. It operates by change the optical path length in the reference arm or test arm. This method practices by move optical device. So it has much problem when the optical device is very large and heavy. For solve this problem, the wavelength-shifting interferometry was put forwarded. In wavelength-shifting interferometry, the phase shifting angle was achieved by change the wavelength of optical source. The phase shifting angle was decided by wavelength and OPD (Optical Path Difference) between test and reference wavefront. So the OPD is an important factor to measure results. But in measurement, because the positional error and profile error of under testing optical element is exist, the phase shifting angle is different in different test point when wavelength scanning, it will introduce phase shifting angle error, so it will introduce optical surface measure error. For analysis influence of OPD on optical surface error, the relation between surface error and OPD was researched. By simulation, the relation between phase shifting error and OPD was established. By analysis, the error compensation method was put forward. After error compensation, the measure results can be improved to great extend.

Influence of OPD in wavelength-shifting interferometry

NASA Astrophysics Data System (ADS)

Wang, Hongjun; Tian, Ailing; Liu, Bingcai; Dang, Juanjuan

2010-03-01

Phase-shifting interferometry is a powerful tool for high accuracy optical measurement. It operates by change the optical path length in the reference arm or test arm. This method practices by move optical device. So it has much problem when the optical device is very large and heavy. For solve this problem, the wavelength-shifting interferometry was put forwarded. In wavelength-shifting interferometry, the phase shifting angle was achieved by change the wavelength of optical source. The phase shifting angle was decided by wavelength and OPD (Optical Path Difference) between test and reference wavefront. So the OPD is an important factor to measure results. But in measurement, because the positional error and profile error of under testing optical element is exist, the phase shifting angle is different in different test point when wavelength scanning, it will introduce phase shifting angle error, so it will introduce optical surface measure error. For analysis influence of OPD on optical surface error, the relation between surface error and OPD was researched. By simulation, the relation between phase shifting error and OPD was established. By analysis, the error compensation method was put forward. After error compensation, the measure results can be improved to great extend.

Basics of identification measurement technology

NASA Astrophysics Data System (ADS)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

How virtue ethics informs medical professionalism.

PubMed

McCammon, Susan D; Brody, Howard

2012-12-01

We argue that a turn toward virtue ethics as a way of understanding medical professionalism represents both a valuable corrective and a missed opportunity. We look at three ways in which a closer appeal to virtue ethics could help address current problems or issues in professionalism education-first, balancing professionalism training with demands for professional virtues as a prerequisite; second, preventing demands for the demonstrable achievement of competencies from working against ideal professionalism education as lifelong learning; and third, avoiding temptations to dismiss moral distress as a mere "hidden curriculum" problem. As a further demonstration of how best to approach a lifelong practice of medical virtue, we will examine altruism as a mean between the extremes of self-sacrifice and selfishness.

Infrared thermographic detection of buried grave sites

NASA Astrophysics Data System (ADS)

Weil, Gary J.; Graf, Richard J.

1992-04-01

Since time began, people have been born and people have died. For a variety of reasons grave sites have had to be located and investigated. These reasons have included legal, criminal, religious, construction and even simple curiosity problems. Destructive testing methods such as shovels and backhoes, have traditionally been used to determine grave site locations in fields, under pavements, and behind hidden locations. These existing techniques are slow, inconvenient, dirty, destructive, visually obtrusive, irritating to relatives, explosive to the media and expensive. A new, nondestructive, non-contact technique, infrared thermography has been developed to address these problems. This paper will describe how infrared thermography works and will be illustrated by several case histories.

Emoticon-Based Ambivalent Expression: A Hidden Indicator for Unusual Behaviors in Weibo

PubMed Central

Hu, Yue; Zhao, Jichang; Wu, Junjie

2016-01-01

Recent decades have witnessed online social media being a big-data window for testifying conventional social theories quantitatively and exploring much detailed human behavioral patterns. In this paper, by tracing the emoticon use in Weibo, a group of hidden “ambivalent users” are disclosed for frequently posting ambivalent tweets containing both positive and negative emotions. Further investigation reveals that this ambivalent expression could be a novel indicator of many unusual social behaviors. For instance, ambivalent users with the female as the majority like to make a sound in midnights and at weekends. They mention their close friends frequently in ambivalent tweets, which attract more replies and serve as a more private communication way. Ambivalent users also respond differently to public affairs from others and demonstrate more interests in entertainment and sports events. Moreover, the sentiment shift in ambivalent tweets is more evident than usual and exhibits a clear “negative to positive” pattern. The above observations, though being promiscuous seemingly, actually point to the self-regulation of negative mood in Weibo, which could find its basis from the traditional emotion management theories in sociology but makes an important extension to the online environment in this study. Finally, as an interesting corollary, ambivalent users are found connected with compulsive buyers and turn out to be perfect targets for online marketing. PMID:26800119

Orientation of lizards in a Morris water-maze: roles of the sun compass and the parietal eye.

PubMed

Foà, Augusto; Basaglia, Francesca; Beltrami, Giulia; Carnacina, Margherita; Moretto, Elisa; Bertolucci, Cristiano

2009-09-15

The present study examined for the first time whether a Morris water-maze can be used to explore compass and other orientation mechanisms in the ruin lizard Podarcis sicula. In the open field, during sunny days, lizards were individually trained to swim from the center of the water maze onto a hidden platform (the goal), positioned at the periphery of the maze in a single compass direction. The goal was invisible because it was placed just beneath the water surface and the water was rendered opaque. The results showed that lizards learn to swim directly towards the hidden goal under the sun in the absence of visual feature cues. We further examined whether the observed orientation response would be due to lizards learning the spatial position of the goal relative to the sun's azimuth, i.e. to the use of a time-compensated sun compass. Lizards reaching learning criteria were subjected to 6 h clock-shift (fast or slow), and tested for goal orientation in the Morris water-maze. Results demonstrated that the learned orientation response is mediated by a time-compensated sun compass. Further investigations provided direct evidence that in ruin lizards an intact parietal eye is required to perform goal orientation under the sun inside a Morris water-maze, and that other brain photoreceptors, like the pineal or deep brain photoreceptors, are not involved in orientation.

Homodyne impulse radar hidden object locator

DOEpatents

McEwan, T.E.

1996-04-30

An electromagnetic detector is designed to locate an object hidden behind a separator or a cavity within a solid object. The detector includes a PRF generator for generating 2 MHz pulses, a homodyne oscillator for generating a 2 kHz square wave, and for modulating the pulses from the PRF generator. A transmit antenna transmits the modulated pulses through the separator, and a receive antenna receives the signals reflected off the object. The receiver path of the detector includes a sample and hold circuit, an AC coupled amplifier which filters out DC bias level shifts in the sample and hold circuit, and a rectifier circuit connected to the homodyne oscillator and to the AC coupled amplifier, for synchronously rectifying the modulated pulses transmitted over the transmit antenna. The homodyne oscillator modulates the signal from the PRF generator with a continuous wave (CW) signal, and the AC coupled amplifier operates with a passband centered on that CW signal. The present detector can be used in several applications, including the detection of metallic and non-metallic objects, such as pipes, studs, joists, nails, rebars, conduits and electrical wiring, behind wood wall, ceiling, plywood, particle board, dense hardwood, masonry and cement structure. The detector is portable, light weight, simple to use, inexpensive, and has a low power emission which facilitates the compliance with Part 15 of the FCC rules. 15 figs.

Homodyne impulse radar hidden object locator

DOEpatents

McEwan, Thomas E.

1996-01-01

An electromagnetic detector is designed to locate an object hidden behind a separator or a cavity within a solid object. The detector includes a PRF generator for generating 2 MHz pulses, a homodyne oscillator for generating a 2 kHz square wave, and for modulating the pulses from the PRF generator. A transmit antenna transmits the modulated pulses through the separator, and a receive antenna receives the signals reflected off the object. The receiver path of the detector includes a sample and hold circuit, an AC coupled amplifier which filters out DC bias level shifts in the sample and hold circuit, and a rectifier circuit connected to the homodyne oscillator and to the AC coupled amplifier, for synchronously rectifying the modulated pulses transmitted over the transmit antenna. The homodyne oscillator modulates the signal from the PRF generator with a continuous wave (CW) signal, and the AC coupled amplifier operates with a passband centered on that CW signal. The present detector can be used in several applications, including the detection of metallic and non-metallic objects, such as pipes, studs, joists, nails, rebars, conduits and electrical wiring, behind wood wall, ceiling, plywood, particle board, dense hardwood, masonry and cement structure. The detector is portable, light weight, simple to use, inexpensive, and has a low power emission which facilitates the compliance with Part 15 of the FCC rules.

TASK COMPLEXITY MODIFIES THE SEARCH STRATEGY OF RATS.

PubMed

Ruprecht, Chad M; Taylor, C Drew; Wolf, Joshua E; Leising, Kenneth J

2013-10-25

Human and non-human animals exhibit a variety of response strategies (e.g., place responding) when searching for a familiar place or evading predators. We still know little about the conditions that support the use of each strategy. We trained rats to locate a hidden food reward in a small-scale spatial search task. The complexity of the search task was manipulated by reducing the number of search locations (25, 4, and 2) within an open-field apparatus and by comparison to a path-based apparatus (plus maze). After rats were trained to reliably locate the hidden food, each apparatus was shifted to gauge whether rats were searching at the location of the goal relative to extramaze cues (i.e., place responding), or searching in the direction of the goal relative to a combination of intramaze and extramaze cues (i.e., directional responding). The results indicate that the open field supported place responding when more than two response locations were present, whereas, the four-arm plus-maze supported strong directional responding. These results extend prior research into the role of task demands on search strategy, as well as support the use of the four-choice open field as an analog to the Morris water task for future studies targeting the neural underpinnings of place responding. Copyright © 2013 Elsevier B.V. All rights reserved.

A hidden curriculum: gambling and problem gambling among high school students in Auckland.

PubMed

Sullivan, Sean

2005-12-01

Participation in gambling by young people aged 13-18 years. During 2001, prior to the passing of legislation to minimise gambling harm, more than 500 students from six high schools completed a survey of their participation in gambling during the previous 12 months, and completed three problem gambling screens. Gambling, including under-age gambling, was a common event. Up to one in five were identified as at risk for problem gambling on at least one screen. Students who were non-European, or were from low socioeconomic areas, were more likely to be at risk for problem gambling. Help for gambling problems was preferred from friends and family rather than others, while inclusion of information in the education curriculum about risk of gambling problems was supported. The survey provided evidence for pre-legislation baseline gambling behaviour, and risk for problem gambling, of students attending high schools in Auckland. Levels of risk for problem gambling paralleled the elevated risk found for youth in many countries. Raising awareness, through a school curriculum, of risk for gambling problems among adolescents may be explored as a strategy to reduce the high levels of risk for gambling problems identified.

Zipf exponent of trajectory distribution in the hidden Markov model

NASA Astrophysics Data System (ADS)

Bochkarev, V. V.; Lerner, E. Yu

2014-03-01

This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different.

Identification of related gene/protein names based on an HMM of name variations.

PubMed

Yeganova, L; Smith, L; Wilbur, W J

2004-04-01

Gene and protein names follow few, if any, true naming conventions and are subject to great variation in different occurrences of the same name. This gives rise to two important problems in natural language processing. First, can one locate the names of genes or proteins in free text, and second, can one determine when two names denote the same gene or protein? The first of these problems is a special case of the problem of named entity recognition, while the second is a special case of the problem of automatic term recognition (ATR). We study the second problem, that of gene or protein name variation. Here we describe a system which, given a query gene or protein name, identifies related gene or protein names in a large list. The system is based on a dynamic programming algorithm for sequence alignment in which the mutation matrix is allowed to vary under the control of a fully trainable hidden Markov model.

Problem of intraoperative anatomical shift in image-guided surgery

NASA Astrophysics Data System (ADS)

Nauta, Haring J.; Bonnen, J. G.

1998-06-01

Experience with image guided, frameless stereotactic neurosurgery shows that intraoperative brain position shifts can be large enough to be problematic, and can occur in different directions at different directions at different stages of an operation. An understanding of the behavior of shifts will allow the surgeon to make the most appropriate use of the image guidance by first minimizing the shift itself, and then anticipating and compensating for any influence the remaining shift will have on the accuracy of the guidance. Three types of shift are described. Type I shift is a local outward bulging that occurs after the skull and dura are opened but before a mass lesion is resected. Type II shift is a local collapse of the brain tissue into the space previously occupied by the tumor. Type III shift is related to loss of cerebrospinal fluid or brain dehydration and is a generalized, more symmetric loss of brain volume. Strategies to minimize these types of shift include appropriate use of medical measures to reduce brain swelling early in the procedure without producing so much brain dehydration that Type II shift is accentuated later in the procedure. Other strategies include mechanical stabilization of brain position with retractors. Anticipating shift, the neurosurgeon should use the guidance as far as possible to map key boundaries early in the procedure before shift becomes more pronounced. Ultimately, however, the correction for the problem of intraoperative brain shift will require the ability to update the imaging data during the surgery.

Biased Dropout and Crossmap Dropout: Learning towards effective Dropout regularization in convolutional neural network.

PubMed

Poernomo, Alvin; Kang, Dae-Ki

2018-08-01

Training a deep neural network with a large number of parameters often leads to overfitting problem. Recently, Dropout has been introduced as a simple, yet effective regularization approach to combat overfitting in such models. Although Dropout has shown remarkable results on many deep neural network cases, its actual effect on CNN has not been thoroughly explored. Moreover, training a Dropout model will significantly increase the training time as it takes longer time to converge than a non-Dropout model with the same architecture. To deal with these issues, we address Biased Dropout and Crossmap Dropout, two novel approaches of Dropout extension based on the behavior of hidden units in CNN model. Biased Dropout divides the hidden units in a certain layer into two groups based on their magnitude and applies different Dropout rate to each group appropriately. Hidden units with higher activation value, which give more contributions to the network final performance, will be retained by a lower Dropout rate, while units with lower activation value will be exposed to a higher Dropout rate to compensate the previous part. The second approach is Crossmap Dropout, which is an extension of the regular Dropout in convolution layer. Each feature map in a convolution layer has a strong correlation between each other, particularly in every identical pixel location in each feature map. Crossmap Dropout tries to maintain this important correlation yet at the same time break the correlation between each adjacent pixel with respect to all feature maps by applying the same Dropout mask to all feature maps, so that all pixels or units in equivalent positions in each feature map will be either dropped or active during training. Our experiment with various benchmark datasets shows that our approaches provide better generalization than the regular Dropout. Moreover, our Biased Dropout takes faster time to converge during training phase, suggesting that assigning noise appropriately in hidden units can lead to an effective regularization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Using parallel banded linear system solvers in generalized eigenvalue problems

NASA Technical Reports Server (NTRS)

Zhang, Hong; Moss, William F.

1993-01-01

Subspace iteration is a reliable and cost effective method for solving positive definite banded symmetric generalized eigenproblems, especially in the case of large scale problems. This paper discusses an algorithm that makes use of two parallel banded solvers in subspace iteration. A shift is introduced to decompose the banded linear systems into relatively independent subsystems and to accelerate the iterations. With this shift, an eigenproblem is mapped efficiently into the memories of a multiprocessor and a high speed-up is obtained for parallel implementations. An optimal shift is a shift that balances total computation and communication costs. Under certain conditions, we show how to estimate an optimal shift analytically using the decay rate for the inverse of a banded matrix, and how to improve this estimate. Computational results on iPSC/2 and iPSC/860 multiprocessors are presented.

The effect of chronotype on sleepiness, fatigue, and psychomotor vigilance of ICU nurses during the night shift.

PubMed

Reinke, Laurens; Özbay, Yusuf; Dieperink, Willem; Tulleken, Jaap E

2015-04-01

In general, sleeping and activity patterns vary between individuals. This attribute, known as chronotype, may affect night shift performance. In the intensive care unit (ICR), night shift performance may impact patient safety. We have investigated the effect of chronotype and social demographics on sleepiness, fatigue, and night shift on the performance of nurses. This was a prospective observational cohort study which assessed the performance of 96 ICU night shift nurses during the day and night shifts in a mixed medical-surgical ICU in the Netherlands. We determined chronotype and assessed sleeping behaviour for each nurse prior to starting shift work and before free days. The level of sleepiness and fatigue of nurses during the day and night shifts was determined, as was the effect of these conditions on psychomotor vigilance and mathematical problem-solving. The majority of ICU nurses had a preference for early activity (morning chronotype). Compared to their counterparts (i.e. evening chronotypes), they were more likely to nap before commencing night shifts and more likely to have young children living at home. Despite increased sleepiness and fatigue during night shifts, no effect on psychomotor vigilance was observed during night shifts. Problem-solving accuracy remained high during night shifts, at the cost of productivity. Most of the ICU night shift nurses assessed here appeared to have adapted well to night shift work, despite the high percentage of morning chronotypes, possibly due to their 8-h shift duration. Parental responsibilities may, however, influence shift work tolerance.

Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series

NASA Astrophysics Data System (ADS)

Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.

2017-12-01

Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.

Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

PubMed

Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

2017-03-01

Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Visual one-shot learning as an 'anti-camouflage device': a novel morphing paradigm.

PubMed

Ishikawa, Tetsuo; Mogi, Ken

2011-09-01

Once people perceive what is in the hidden figure such as Dallenbach's cow and Dalmatian, they seldom seem to come back to the previous state when they were ignorant of the answer. This special type of learning process can be accomplished in a short time, with the effect of learning lasting for a long time (visual one-shot learning). Although it is an intriguing cognitive phenomenon, the lack of the control of difficulty of stimuli presented has been a problem in research. Here we propose a novel paradigm to create new hidden figures systematically by using a morphing technique. Through gradual changes from a blurred and binarized two-tone image to a blurred grayscale image of the original photograph including objects in a natural scene, spontaneous one-shot learning can occur at a certain stage of morphing when a sufficient amount of information is restored to the degraded image. A negative correlation between confidence levels and reaction times is observed, giving support to the fluency theory of one-shot learning. The correlation between confidence ratings and correct recognition rates indicates that participants had an accurate introspective ability (metacognition). The learning effect could be tested later by verifying whether or not the target object was recognized quicker in the second exposure. The present method opens a way for a systematic production of "good" hidden figures, which can be used to demystify the nature of visual one-shot learning.

The Physiological Bases of Hidden Noise-Induced Hearing Loss: Protocol for a Functional Neuroimaging Study.

PubMed

Dewey, Rebecca Susan; Hall, Deborah A; Guest, Hannah; Prendergast, Garreth; Plack, Christopher J; Francis, Susan T

2018-03-09

Rodent studies indicate that noise exposure can cause permanent damage to synapses between inner hair cells and high-threshold auditory nerve fibers, without permanently altering threshold sensitivity. These demonstrations of what is commonly known as hidden hearing loss have been confirmed in several rodent species, but the implications for human hearing are unclear. Our Medical Research Council-funded program aims to address this unanswered question, by investigating functional consequences of the damage to the human peripheral and central auditory nervous system that results from cumulative lifetime noise exposure. Behavioral and neuroimaging techniques are being used in a series of parallel studies aimed at detecting hidden hearing loss in humans. The planned neuroimaging study aims to (1) identify central auditory biomarkers associated with hidden hearing loss; (2) investigate whether there are any additive contributions from tinnitus or diminished sound tolerance, which are often comorbid with hearing problems; and (3) explore the relation between subcortical functional magnetic resonance imaging (fMRI) measures and the auditory brainstem response (ABR). Individuals aged 25 to 40 years with pure tone hearing thresholds ≤20 dB hearing level over the range 500 Hz to 8 kHz and no contraindications for MRI or signs of ear disease will be recruited into the study. Lifetime noise exposure will be estimated using an in-depth structured interview. Auditory responses throughout the central auditory system will be recorded using ABR and fMRI. Analyses will focus predominantly on correlations between lifetime noise exposure and auditory response characteristics. This paper reports the study protocol. The funding was awarded in July 2013. Enrollment for the study described in this protocol commenced in February 2017 and was completed in December 2017. Results are expected in 2018. This challenging and comprehensive study will have the potential to impact diagnostic procedures for hidden hearing loss, enabling early identification of noise-induced auditory damage via the detection of changes in central auditory processing. Consequently, this will generate the opportunity to give personalized advice regarding provision of ear defense and monitoring of further damage, thus reducing the incidence of noise-induced hearing loss. ©Rebecca Susan Dewey, Deborah A Hall, Hannah Guest, Garreth Prendergast, Christopher J Plack, Susan T Francis. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 09.03.2018.

A composite model for the 750 GeV diphoton excess

DOE PAGES

Harigaya, Keisuke; Nomura, Yasunori

2016-03-14

We study a simple model in which the recently reported 750 GeV diphoton excess arises from a composite pseudo Nambu-Goldstone boson — hidden pion — produced by gluon fusion and decaying into two photons. The model only introduces an extra hidden gauge group at the TeV scale with a vectorlike quark in the bifundamental representation of the hidden and standard model gauge groups. We calculate the masses of all the hidden pions and analyze their experimental signatures and constraints. We find that two colored hidden pions must be near the current experimental limits, and hence are probed in the nearmore » future. We study physics of would-be stable particles — the composite states that do not decay purely by the hidden and standard model gauge dynamics — in detail, including constraints from cosmology. We discuss possible theoretical structures above the TeV scale, e.g. conformal dynamics and supersymmetry, and their phenomenological implications. We also discuss an extension of the minimal model in which there is an extra hidden quark that is singlet under the standard model and has a mass smaller than the hidden dynamical scale. This provides two standard model singlet hidden pions that can both be viewed as diphoton/diboson resonances produced by gluon fusion. We discuss several scenarios in which these (and other) resonances can be used to explain various excesses seen in the LHC data.« less

Radio for hidden-photon dark matter detection

DOE PAGES

Chaudhuri, Saptarshi; Graham, Peter W.; Irwin, Kent; ...

2015-10-08

We propose a resonant electromagnetic detector to search for hidden-photon dark matter over an extensive range of masses. Hidden-photon dark matter can be described as a weakly coupled “hidden electric field,” oscillating at a frequency fixed by the mass, and able to penetrate any shielding. At low frequencies (compared to the inverse size of the shielding), we find that the observable effect of the hidden photon inside any shielding is a real, oscillating magnetic field. We outline experimental setups designed to search for hidden-photon dark matter, using a tunable, resonant LC circuit designed to couple to this magnetic field. Ourmore » “straw man” setups take into consideration resonator design, readout architecture and noise estimates. At high frequencies, there is an upper limit to the useful size of a single resonator set by 1/ν. However, many resonators may be multiplexed within a hidden-photon coherence length to increase the sensitivity in this regime. Hidden-photon dark matter has an enormous range of possible frequencies, but current experiments search only over a few narrow pieces of that range. As a result, we find the potential sensitivity of our proposal is many orders of magnitude beyond current limits over an extensive range of frequencies, from 100 Hz up to 700 GHz and potentially higher.« less

PCSYS: The optimal design integration system picture drawing system with hidden line algorithm capability for aerospace vehicle configurations

NASA Technical Reports Server (NTRS)

Hague, D. S.; Vanderburg, J. D.

1977-01-01

A vehicle geometric definition based upon quadrilateral surface elements to produce realistic pictures of an aerospace vehicle. The PCSYS programs can be used to visually check geometric data input, monitor geometric perturbations, and to visualize the complex spatial inter-relationships between the internal and external vehicle components. PCSYS has two major component programs. The between program, IMAGE, draws a complex aerospace vehicle pictorial representation based on either an approximate but rapid hidden line algorithm or without any hidden line algorithm. The second program, HIDDEN, draws a vehicle representation using an accurate but time consuming hidden line algorithm.

The reported effects of bullying on burn-surviving children.

PubMed

Rimmer, Ruth B; Foster, Kevin N; Bay, Curtis R; Floros, Jim; Rutter, Cindy; Bosch, Jim; Wadsworth, Michelle M; Caruso, Daniel M

2007-01-01

There is a trend of increasing childhood aggression in America, which has been tied to bullying. Although there is growing research concerning bullying in the general pediatric population, there are limited data on bullying and its effects on children with disfigurements and physical limitations. This study was conducted to assess burned children's experience with bullying. A pretest was administered regarding experience with bullying and teasing. A curriculum regarding bullying, which incorporated the Harry Potter and the Sorcerer's Stone movie, was presented. After reviewing bullying depicted in the film and participating in a class regarding bullying, children were invited to complete a survey regarding their experience with bullying. A total of 61% of these children reported being bullied at school; 25% reported experiencing headaches or stomachaches due to bullying, and 12% reported staying home from school. Nearly 25% reported bullying as a big problem. Of those with visible scars (55%), a full 68% reported bullying as a problem, versus 54% with hidden scars (P < .05). However, those with visible scars were no more likely to tell an adult (54%) than those without (56%). Children were much more willing to disclose personal bullying experiences after participating in the class (57%) than before (45%) (P < .01). This study revealed that bullying impacts many burn-injured children and has negative effects on their physical and mental well-being. Many children (with visible or hidden scars) did not seek adult intervention for the problem. Participation in a bullying course appears to give children a forum that increases their willingness to disclose personal bullying experiences and can provide them with prevention information and a safe place to seek help.

On shifted Jacobi spectral method for high-order multi-point boundary value problems

NASA Astrophysics Data System (ADS)

Doha, E. H.; Bhrawy, A. H.; Hafez, R. M.

2012-10-01

This paper reports a spectral tau method for numerically solving multi-point boundary value problems (BVPs) of linear high-order ordinary differential equations. The construction of the shifted Jacobi tau approximation is based on conventional differentiation. This use of differentiation allows the imposition of the governing equation at the whole set of grid points and the straight forward implementation of multiple boundary conditions. Extension of the tau method for high-order multi-point BVPs with variable coefficients is treated using the shifted Jacobi Gauss-Lobatto quadrature. Shifted Jacobi collocation method is developed for solving nonlinear high-order multi-point BVPs. The performance of the proposed methods is investigated by considering several examples. Accurate results and high convergence rates are achieved.

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

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector ismore » cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.« less

Phases of cannibal dark matter

NASA Astrophysics Data System (ADS)

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.; Trevisan, Gabriele

2016-12-01

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector is cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.

Phases of cannibal dark matter

DOE PAGES

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.; ...

2016-12-13

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector ismore » cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.« less

Generalization and capacity of extensively large two-layered perceptrons.

PubMed

Rosen-Zvi, Michal; Engel, Andreas; Kanter, Ido

2002-09-01

The generalization ability and storage capacity of a treelike two-layered neural network with a number of hidden units scaling as the input dimension is examined. The mapping from the input to the hidden layer is via Boolean functions; the mapping from the hidden layer to the output is done by a perceptron. The analysis is within the replica framework where an order parameter characterizing the overlap between two networks in the combined space of Boolean functions and hidden-to-output couplings is introduced. The maximal capacity of such networks is found to scale linearly with the logarithm of the number of Boolean functions per hidden unit. The generalization process exhibits a first-order phase transition from poor to perfect learning for the case of discrete hidden-to-output couplings. The critical number of examples per input dimension, alpha(c), at which the transition occurs, again scales linearly with the logarithm of the number of Boolean functions. In the case of continuous hidden-to-output couplings, the generalization error decreases according to the same power law as for the perceptron, with the prefactor being different.

Sound Science: Taking Action with Acoustics

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

Sinha, Dipen

2014-07-16

From tin whistles to sonic booms, sound waves interact with each other and with the medium through which they travel. By observing these interactions, we can identify substances that are hidden in sealed containers and obtain images of buried objects. By manipulating the ability of sound to push matter around, we can create novel structures and unique materials. Join the Lab's own sound hound, Dipen Sinha, as he describes how he uses fundamental research in acoustics for solving problems in industry, security and health.

Sound Science: Taking Action with Acoustics

ScienceCinema

Sinha, Dipen

2018-01-16

From tin whistles to sonic booms, sound waves interact with each other and with the medium through which they travel. By observing these interactions, we can identify substances that are hidden in sealed containers and obtain images of buried objects. By manipulating the ability of sound to push matter around, we can create novel structures and unique materials. Join the Lab's own sound hound, Dipen Sinha, as he describes how he uses fundamental research in acoustics for solving problems in industry, security and health.

Inference of Stochastic Nonlinear Oscillators with Applications to Physiological Problems

NASA Technical Reports Server (NTRS)

Smelyanskiy, Vadim N.; Luchinsky, Dmitry G.

2004-01-01

A new method of inferencing of coupled stochastic nonlinear oscillators is described. The technique does not require extensive global optimization, provides optimal compensation for noise-induced errors and is robust in a broad range of dynamical models. We illustrate the main ideas of the technique by inferencing a model of five globally and locally coupled noisy oscillators. Specific modifications of the technique for inferencing hidden degrees of freedom of coupled nonlinear oscillators is discussed in the context of physiological applications.

Effect of design selection on response surface performance

NASA Technical Reports Server (NTRS)

Carpenter, William C.

1993-01-01

Artificial neural nets and polynomial approximations were used to develop response surfaces for several test problems. Based on the number of functional evaluations required to build the approximations and the number of undetermined parameters associated with the approximations, the performance of the two types of approximations was found to be comparable. A rule of thumb is developed for determining the number of nodes to be used on a hidden layer of an artificial neural net and the number of designs needed to train an approximation is discussed.

Development and application of deep convolutional neural network in target detection

NASA Astrophysics Data System (ADS)

Jiang, Xiaowei; Wang, Chunping; Fu, Qiang

2018-04-01

With the development of big data and algorithms, deep convolution neural networks with more hidden layers have more powerful feature learning and feature expression ability than traditional machine learning methods, making artificial intelligence surpass human level in many fields. This paper first reviews the development and application of deep convolutional neural networks in the field of object detection in recent years, then briefly summarizes and ponders some existing problems in the current research, and the future development of deep convolutional neural network is prospected.

Hidden order in crackling noise during peeling of an adhesive tape.

PubMed

Kumar, Jagadish; Ciccotti, M; Ananthakrishna, G

2008-04-01

We address the longstanding problem of recovering dynamical information from noisy acoustic emission signals arising from peeling of an adhesive tape subject to constant traction velocity. Using the phase space reconstruction procedure we demonstrate the deterministic chaotic dynamics by establishing the existence of correlation dimension as also a positive Lyapunov exponent in a midrange of traction velocities. The results are explained on the basis of the model that also emphasizes the deterministic origin of acoustic emission by clarifying its connection to stick-slip dynamics.

Out of Reach, Out of Mind? Infants' Comprehension of References to Hidden Inaccessible Objects.

PubMed

Osina, Maria A; Saylor, Megan M; Ganea, Patricia A

2017-09-01

This study investigated the nature of infants' difficulty understanding references to hidden inaccessible objects. Twelve-month-old infants (N = 32) responded to the mention of objects by looking at, pointing at, or approaching them when the referents were visible or accessible, but not when they were hidden and inaccessible (Experiment I). Twelve-month-olds (N = 16) responded robustly when a container with the hidden referent was moved from a previously inaccessible position to an accessible position before the request, but failed to respond when the reverse occurred (Experiment II). This suggests that infants might be able to track the hidden object's dislocations and update its accessibility as it changes. Knowing the hidden object is currently inaccessible inhibits their responding. Older, 16-month-old (N = 17) infants' performance was not affected by object accessibility. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

[A way of helping "Mr. Minotaur" and "Ms. Ariadne" to exit from the multiple morbidity labyrinth: the "master problems"].

PubMed

Turabián, J L; Pérez Franco, B

2016-01-01

Multiple morbidity seems to be "infinite" and so is not easy to make useful decisions. A new concept is introduced: the "master problems", as a qualitative method to facilitate the exit from this maze of multiple morbidity. Metaphors from the art world have been used to teach this concept. These "master problems" generally remain hidden and can only "unravel" between the interstices of multiple morbidity, when the details of the system that defines the problem are explained. A problem with "energy" or a "master problem" is complex, multiple and dramatic or theatrical--everything in the clinical history history make us look into that particular question. It is what gives us a blow to the stomach, which causes our hearts to beat faster, that moves us on many levels, which has a high "density of emotions", human elements, social symbols, and opens solutions in a patient. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Shift work in nursing: is it really a risk factor for nurses' health and patients' safety?

PubMed

Admi, Hanna; Tzischinsky, Orna; Epstein, Rachel; Herer, Paula; Lavie, Peretz

2008-01-01

There is evidence in the scientific literature of the adverse physiological and psychological effects of shift work, including disruption to biological rhythm, sleep disorders, health problems, diminished performance at work, job dissatisfaction, and social isolation. In this study, the results of health problems and sleep disorders between female and male nurses, between daytime and shift nurses, and between sleep-adjusted and non-sleep-adjusted shift nurses were compared. Also the relationship between adjustment to shift work and organizational outcomes (errors and incidents and absenteeism from work) was analyzed. Gender, age, and weight were more significant factors than shift work in determining the well-being of nurses. Shift work by itself was not found to be a risk factor for nurses' health and organizational outcomes in this study. Moreover, nurses who were identified as being "non-adaptive" to shift work were found to work as effectively and safely as their adaptive colleagues in terms of absenteeism from work and involvement in professional errors and accidents. This research adds two additional findings to the field of shift work studies. The first finding is that female shift workers complain significantly more about sleep disorders than male shift workers. Second, although high rates of nurses whose sleep was not adapted to shift work were found, this did not have a more adverse impact on their health, absenteeism rates, or performance (reported errors and incidents), compared to their "adaptive" and "daytime" colleagues.

Quantum learning of classical stochastic processes: The completely positive realization problem

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

Monràs, Alex; Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543; Winter, Andreas

2016-01-15

Among several tasks in Machine Learning, a specially important one is the problem of inferring the latent variables of a system and their causal relations with the observed behavior. A paradigmatic instance of this is the task of inferring the hidden Markov model underlying a given stochastic process. This is known as the positive realization problem (PRP), [L. Benvenuti and L. Farina, IEEE Trans. Autom. Control 49(5), 651–664 (2004)] and constitutes a central problem in machine learning. The PRP and its solutions have far-reaching consequences in many areas of systems and control theory, and is nowadays an important piece inmore » the broad field of positive systems theory. We consider the scenario where the latent variables are quantum (i.e., quantum states of a finite-dimensional system) and the system dynamics is constrained only by physical transformations on the quantum system. The observable dynamics is then described by a quantum instrument, and the task is to determine which quantum instrument — if any — yields the process at hand by iterative application. We take as a starting point the theory of quasi-realizations, whence a description of the dynamics of the process is given in terms of linear maps on state vectors and probabilities are given by linear functionals on the state vectors. This description, despite its remarkable resemblance with the hidden Markov model, or the iterated quantum instrument, is however devoid of any stochastic or quantum mechanical interpretation, as said maps fail to satisfy any positivity conditions. The completely positive realization problem then consists in determining whether an equivalent quantum mechanical description of the same process exists. We generalize some key results of stochastic realization theory, and show that the problem has deep connections with operator systems theory, giving possible insight to the lifting problem in quotient operator systems. Our results have potential applications in quantum machine learning, device-independent characterization and reverse-engineering of stochastic processes and quantum processors, and more generally, of dynamical processes with quantum memory [M. Guţă, Phys. Rev. A 83(6), 062324 (2011); M. Guţă and N. Yamamoto, e-print http://arxiv.org/abs/1303.3771 (2013)].« less

Cover song identification by sequence alignment algorithms

NASA Astrophysics Data System (ADS)

Wang, Chih-Li; Zhong, Qian; Wang, Szu-Ying; Roychowdhury, Vwani

2011-10-01

Content-based music analysis has drawn much attention due to the rapidly growing digital music market. This paper describes a method that can be used to effectively identify cover songs. A cover song is a song that preserves only the crucial melody of its reference song but different in some other acoustic properties. Hence, the beat/chroma-synchronous chromagram, which is insensitive to the variation of the timber or rhythm of songs but sensitive to the melody, is chosen. The key transposition is achieved by cyclically shifting the chromatic domain of the chromagram. By using the Hidden Markov Model (HMM) to obtain the time sequences of songs, the system is made even more robust. Similar structure or length between the cover songs and its reference are not necessary by the Smith-Waterman Alignment Algorithm.

Learning and inference in a nonequilibrium Ising model with hidden nodes.

PubMed

Dunn, Benjamin; Roudi, Yasser

2013-02-01

We study inference and reconstruction of couplings in a partially observed kinetic Ising model. With hidden spins, calculating the likelihood of a sequence of observed spin configurations requires performing a trace over the configurations of the hidden ones. This, as we show, can be represented as a path integral. Using this representation, we demonstrate that systematic approximate inference and learning rules can be derived using dynamical mean-field theory. Although naive mean-field theory leads to an unstable learning rule, taking into account Gaussian corrections allows learning the couplings involving hidden nodes. It also improves learning of the couplings between the observed nodes compared to when hidden nodes are ignored.

Performance of Multi-chaotic PSO on a shifted benchmark functions set

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

Pluhacek, Michal; Senkerik, Roman; Zelinka, Ivan

2015-03-10

In this paper the performance of Multi-chaotic PSO algorithm is investigated using two shifted benchmark functions. The purpose of shifted benchmark functions is to simulate the time-variant real-world problems. The results of chaotic PSO are compared with canonical version of the algorithm. It is concluded that using the multi-chaotic approach can lead to better results in optimization of shifted functions.

Efficient reversible data hiding in encrypted image with public key cryptosystem

NASA Astrophysics Data System (ADS)

Xiang, Shijun; Luo, Xinrong

2017-12-01

This paper proposes a new reversible data hiding scheme for encrypted images by using homomorphic and probabilistic properties of Paillier cryptosystem. The proposed method can embed additional data directly into encrypted image without any preprocessing operations on original image. By selecting two pixels as a group for encryption, data hider can retrieve the absolute differences of groups of two pixels by employing a modular multiplicative inverse method. Additional data can be embedded into encrypted image by shifting histogram of the absolute differences by using the homomorphic property in encrypted domain. On the receiver side, legal user can extract the marked histogram in encrypted domain in the same way as data hiding procedure. Then, the hidden data can be extracted from the marked histogram and the encrypted version of original image can be restored by using inverse histogram shifting operations. Besides, the marked absolute differences can be computed after decryption for extraction of additional data and restoration of original image. Compared with previous state-of-the-art works, the proposed scheme can effectively avoid preprocessing operations before encryption and can efficiently embed and extract data in encrypted domain. The experiments on the standard image files also certify the effectiveness of the proposed scheme.

Low home ventilation rate in combination with moldy odor from the building structure increase the risk for allergic symptoms in children.

PubMed

Hägerhed-Engman, L; Sigsgaard, T; Samuelson, I; Sundell, J; Janson, S; Bornehag, C-G

2009-06-01

There are consistent findings on associations between asthma and allergy symptoms and residential mold and moisture. However, definitions of 'dampness' in studies are diverse because of differences in climate and building construction. Few studies have estimated mold problems inside the building structure by odor assessments. In a nested case-control study of 400 Swedish children, observations and measurements were performed in their homes by inspectors, and the children were examined by physicians for diagnoses of asthma, eczema, and rhinitis. In conclusion, we found an association between moldy odor along the skirting board and allergic symptoms among children, mainly rhinitis. No associations with any of the allergic symptoms were found for discoloured stains, 'floor dampness' or a general mold odor in the room. A moldy odor along the skirting board can be a proxy for hidden moisture problem inside the outer wall construction or in the foundation construction. There are indications that such dampness problems increase the risk for sensitization but the interpretation of data in respect of sensitization is difficult as about 80% of the children with rhinitis were sensitized. Furthermore, low ventilation rate in combination with moldy odor along the skirting board further increased the risk for three out of four studied outcomes, indicating that the ventilation rate is an effect modifier for indoor pollutants. This study showed that mold odor at the skirting board level is strongly associated with allergic symptoms among children. Such odor at that specific place can be seen as a proxy for some kind of hidden moisture or mold problem in the building structure, such as the foundation or wooden ground beam. In houses with odor along the skirting board, dismantling of the structure is required for an investigation of possible moisture damage, measurements, and choice of actions. In homes with low ventilation in combination with mold odor along the skirting board, there was even a higher risk of health effects. This emphasizes the need for the appropriate remediation as this is an ever increasing problem in poorly ventilated houses that are damp.

Life imitating art: depictions of the hidden curriculum in medical television programs.

PubMed

Stanek, Agatha; Clarkin, Chantalle; Bould, M Dylan; Writer, Hilary; Doja, Asif

2015-09-26

The hidden curriculum represents influences occurring within the culture of medicine that indirectly alter medical professionals' interactions, beliefs and clinical practices throughout their training. One approach to increase medical student awareness of the hidden curriculum is to provide them with readily available examples of how it is enacted in medicine; as such the purpose of this study was to examine depictions of the hidden curriculum in popular medical television programs. One full season of ER, Grey's Anatomy and Scrubs were selected for review. A summative content analysis was performed to ascertain the presence of depictions of the hidden curriculum, as well as to record the type, frequency and quality of examples. A second reviewer also viewed a random selection of episodes from each series to establish coding reliability. The most prevalent themes across all television programs were: the hierarchical nature of medicine; challenges during transitional stages in medicine; the importance of role modeling; patient dehumanization; faking or overstating one's capabilities; unprofessionalism; the loss of idealism; and difficulties with work-life balance. The hidden curriculum is frequently depicted in popular medical television shows. These examples of the hidden curriculum could serve as a valuable teaching resource in undergraduate medical programs.

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

Solving the quantum many-body problem with artificial neural networks

NASA Astrophysics Data System (ADS)

Carleo, Giuseppe; Troyer, Matthias

2017-02-01

The challenge posed by the many-body problem in quantum physics originates from the difficulty of describing the nontrivial correlations encoded in the exponential complexity of the many-body wave function. Here we demonstrate that systematic machine learning of the wave function can reduce this complexity to a tractable computational form for some notable cases of physical interest. We introduce a variational representation of quantum states based on artificial neural networks with a variable number of hidden neurons. A reinforcement-learning scheme we demonstrate is capable of both finding the ground state and describing the unitary time evolution of complex interacting quantum systems. Our approach achieves high accuracy in describing prototypical interacting spins models in one and two dimensions.

On integrability of the Killing equation

NASA Astrophysics Data System (ADS)

Houri, Tsuyoshi; Tomoda, Kentaro; Yasui, Yukinori

2018-04-01

Killing tensor fields have been thought of as describing the hidden symmetry of space(-time) since they are in one-to-one correspondence with polynomial first integrals of geodesic equations. Since many problems in classical mechanics can be formulated as geodesic problems in curved space and spacetime, solving the defining equation for Killing tensor fields (the Killing equation) is a powerful way to integrate equations of motion. Thus it has been desirable to formulate the integrability conditions of the Killing equation, which serve to determine the number of linearly independent solutions and also to restrict the possible forms of solutions tightly. In this paper, we show the prolongation for the Killing equation in a manner that uses Young symmetrizers. Using the prolonged equations, we provide the integrability conditions explicitly.

Mathematical characterization of mechanical behavior of porous frictional granular media

NASA Technical Reports Server (NTRS)

Chung, T. J.; Lee, J. K.

1972-01-01

A new definition of loading and unloading along the yield surface of Roscoe and Burland is introduced. This is achieved by noting that the strain-hardening parameter in the plastic potential function is deduced from the yield locus equation of Roscoe and Burland. The analytical results are compared with the experimental results for plate-bearing and cone-penetrometer problems and close agreements are demonstrated. The wheel-soil interaction is studied under dynamic loading. The rate-dependent plasticity or viscoelastoplastic behavior is considered. This is accomplished by the internal (hidden) variables associated with time-dependent viscous properties directly superimposed with inelastic behavior governed by the yield criteria of Roscoe and Burland. Effects of inertia and energy dissipation are properly accounted for. Example problems are presented.

Complexity in pH-Dependent Ribozyme Kinetics: Dark pKa Shifts and Wavy Rate-pH Profiles.

PubMed

Frankel, Erica A; Bevilacqua, Philip C

2018-02-06

Charged bases occur in RNA enzymes, or ribozymes, where they play key roles in catalysis. Cationic bases donate protons and perform electrostatic catalysis, while anionic bases accept protons. We previously published simulations of rate-pH profiles for ribozymes in terms of species plots for the general acid and general base that have been useful for understanding how ribozymes respond to pH. In that study, we did not consider interaction between the general acid and general base or interaction with other species on the RNA. Since that report, diverse small ribozyme classes have been discovered, many of which have charged nucleobases or metal ions in the active site that can either directly interact and participate in catalysis or indirectly interact as "influencers". Herein, we simulate experimental rate-pH profiles in terms of species plots in which reverse protonated charged nucleobases interact. These analyses uncover two surprising features of pH-dependent enzyme kinetics. (1) Cooperativity between the general acid and general base enhances population of the functional forms of a ribozyme and manifests itself as hidden or "dark" pK a shifts, real pK a shifts that accelerate the reaction but are not readily observed by standard experimental approaches, and (2) influencers favorably shift the pK a s of proton-transferring nucleobases and manifest themselves as "wavy" rate-pH profiles. We identify parallels with the protein enzyme literature, including reverse protonation and wavelike behavior, while pointing out that RNA is more prone to reverse protonation. The complexities uncovered, which arise from simple pairwise interactions, should aid deconvolution of complex rate-pH profiles for RNA and protein enzymes and suggest veiled catalytic devices for promoting catalysis that can be tested by experiment and calculation.

Domestic horses send signals to humans when they face with an unsolvable task.

PubMed

Ringhofer, Monamie; Yamamoto, Shinya

2017-05-01

Some domestic animals are thought to be skilled at social communication with humans due to the process of domestication. Horses, being in close relationship with humans, similar to dogs, might be skilled at communication with humans. Previous studies have indicated that they are sensitive to bodily signals and the attentional state of humans; however, there are few studies that investigate communication with humans and responses to the knowledge state of humans. Our first question was whether and how horses send signals to their potentially helpful but ignorant caretakers in a problem-solving situation where a food item was hidden in a bucket that was accessible only to the caretakers. We then examined whether horses alter their behaviours on the basis of the caretakers' knowledge of where the food was hidden. We found that horses communicated to their caretakers using visual and tactile signals. The signalling behaviour of the horses significantly increased in conditions where the caretakers had not seen the hiding of the food. These results suggest that horses alter their communicative behaviour towards humans in accordance with humans' knowledge state.

Variables in psychology: a critique of quantitative psychology.

PubMed

Toomela, Aaro

2008-09-01

Mind is hidden from direct observation; it can be studied only by observing behavior. Variables encode information about behaviors. There is no one-to-one correspondence between behaviors and mental events underlying the behaviors, however. In order to understand mind it would be necessary to understand exactly what information is represented in variables. This aim cannot be reached after variables are already encoded. Therefore, statistical data analysis can be very misleading in studies aimed at understanding mind that underlies behavior. In this article different kinds of information that can be represented in variables are described. It is shown how informational ambiguity of variables leads to problems of theoretically meaningful interpretation of the results of statistical data analysis procedures in terms of hidden mental processes. Reasons are provided why presence of dependence between variables does not imply causal relationship between events represented by variables and absence of dependence between variables cannot rule out the causal dependence of events represented by variables. It is concluded that variable-psychology has a very limited range of application for the development of a theory of mind-psychology.

Speakable and Unspeakable in Quantum Mechanics

NASA Astrophysics Data System (ADS)

Bell, J. S.; Aspect, Introduction by Alain

2004-06-01

List of papers on quantum philosophy by J. S. Bell; Preface; Acknowledgements; Introduction by Alain Aspect; 1. On the problem of hidden variables in quantum mechanics; 2. On the Einstein-Rosen-Podolsky paradox; 3. The moral aspects of quantum mechanics; 4. Introduction to the hidden-variable question; 5. Subject and object; 6. On wave packet reduction in the Coleman-Hepp model; 7. The theory of local beables; 8. Locality in quantum mechanics: reply to critics; 9. How to teach special relativity; 10. Einstein-Podolsky-Rosen experiments; 11. The measurement theory of Everett and de Broglie's pilot wave; 12. Free variables and local causality; 13. Atomic-cascade photons and quantum-mechanical nonlocality; 14. de Broglie-Bohm delayed choice double-slit experiments and density matrix; 15. Quantum mechanics for cosmologists; 16. Bertlmann's socks and the nature of reality; 17. On the impossible pilot wave; 18. Speakable and unspeakable in quantum mechanics; 19. Beables for quantum field theory; 20. Six possible worlds of quantum mechanics; 21. EPR correlations and EPR distributions; 22. Are there quantum jumps?; 23. Against 'measurement'; 24. La Nouvelle cuisine.

Short-term prediction of chaotic time series by using RBF network with regression weights.

PubMed

Rojas, I; Gonzalez, J; Cañas, A; Diaz, A F; Rojas, F J; Rodriguez, M

2000-10-01

We propose a framework for constructing and training a radial basis function (RBF) neural network. The structure of the gaussian functions is modified using a pseudo-gaussian function (PG) in which two scaling parameters sigma are introduced, which eliminates the symmetry restriction and provides the neurons in the hidden layer with greater flexibility with respect to function approximation. We propose a modified PG-BF (pseudo-gaussian basis function) network in which the regression weights are used to replace the constant weights in the output layer. For this purpose, a sequential learning algorithm is presented to adapt the structure of the network, in which it is possible to create a new hidden unit and also to detect and remove inactive units. A salient feature of the network systems is that the method used for calculating the overall output is the weighted average of the output associated with each receptive field. The superior performance of the proposed PG-BF system over the standard RBF are illustrated using the problem of short-term prediction of chaotic time series.

A new learning paradigm: learning using privileged information.

PubMed

Vapnik, Vladimir; Vashist, Akshay

2009-01-01

In the Afterword to the second edition of the book "Estimation of Dependences Based on Empirical Data" by V. Vapnik, an advanced learning paradigm called Learning Using Hidden Information (LUHI) was introduced. This Afterword also suggested an extension of the SVM method (the so called SVM(gamma)+ method) to implement algorithms which address the LUHI paradigm (Vapnik, 1982-2006, Sections 2.4.2 and 2.5.3 of the Afterword). See also (Vapnik, Vashist, & Pavlovitch, 2008, 2009) for further development of the algorithms. In contrast to the existing machine learning paradigm where a teacher does not play an important role, the advanced learning paradigm considers some elements of human teaching. In the new paradigm along with examples, a teacher can provide students with hidden information that exists in explanations, comments, comparisons, and so on. This paper discusses details of the new paradigm and corresponding algorithms, introduces some new algorithms, considers several specific forms of privileged information, demonstrates superiority of the new learning paradigm over the classical learning paradigm when solving practical problems, and discusses general questions related to the new ideas.

Biological energy sources: the surface energy and the physical chemistry of water. Examples from studies on muscle contraction.

PubMed

Widdas, W F; Baker, G F

2004-01-01

The physical chemistry of water at nanometre dimensions was used to explain the conformational changes and water breaking properties of the glucose transporter protein (GLUTI) in human erythrocytes more than ten years ago. The energy for this hidden work arises from cycles of evaporation and condensation of water within the cells but was several times larger than resting metabolism. Physical chemical principles can quantify the hidden work done and demonstrate that a significant source of energy is available, which is free of the metabolic energy derived from the hydrolysis of ATP. Therefore, a more widespread biological use of this "free" energy source was probable and a working hypothesis, which applied this energy to supplement the work derived from ATP hydrolysis in muscle, was proposed. The scheme gives a complete explanation for the unexpected and novel findings in skeletal muscle reported from Italy. The problem of using two energy sources and the novel properties of water at nanometer dimensions as they would apply in muscle are briefly discussed but they merit further interdisciplinary studies.

Online Sequential Projection Vector Machine with Adaptive Data Mean Update

PubMed Central

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM. PMID:27143958

Forecasting daily streamflow using online sequential extreme learning machines

NASA Astrophysics Data System (ADS)

Lima, Aranildo R.; Cannon, Alex J.; Hsieh, William W.

2016-06-01

While nonlinear machine methods have been widely used in environmental forecasting, in situations where new data arrive continually, the need to make frequent model updates can become cumbersome and computationally costly. To alleviate this problem, an online sequential learning algorithm for single hidden layer feedforward neural networks - the online sequential extreme learning machine (OSELM) - is automatically updated inexpensively as new data arrive (and the new data can then be discarded). OSELM was applied to forecast daily streamflow at two small watersheds in British Columbia, Canada, at lead times of 1-3 days. Predictors used were weather forecast data generated by the NOAA Global Ensemble Forecasting System (GEFS), and local hydro-meteorological observations. OSELM forecasts were tested with daily, monthly or yearly model updates. More frequent updating gave smaller forecast errors, including errors for data above the 90th percentile. Larger datasets used in the initial training of OSELM helped to find better parameters (number of hidden nodes) for the model, yielding better predictions. With the online sequential multiple linear regression (OSMLR) as benchmark, we concluded that OSELM is an attractive approach as it easily outperformed OSMLR in forecast accuracy.

A substantial amount of hidden magnetic energy in the quiet Sun.

PubMed

Bueno, J Trujillo; Shchukina, N; Ramos, A Asensio

2004-07-15

Deciphering and understanding the small-scale magnetic activity of the quiet solar photosphere should help to solve many of the key problems of solar and stellar physics, such as the magnetic coupling to the outer atmosphere and the coronal heating. At present, we can see only approximately 1 per cent of the complex magnetism of the quiet Sun, which highlights the need to develop a reliable way to investigate the remaining 99 per cent. Here we report three-dimensional radiative transfer modelling of scattering polarization in atomic and molecular lines that indicates the presence of hidden, mixed-polarity fields on subresolution scales. Combining this modelling with recent observational data, we find a ubiquitous tangled magnetic field with an average strength of approximately 130 G, which is much stronger in the intergranular regions of solar surface convection than in the granular regions. So the average magnetic energy density in the quiet solar photosphere is at least two orders of magnitude greater than that derived from simplistic one-dimensional investigations, and sufficient to balance radiative energy losses from the solar chromosphere.

Variance Estimation, Design Effects, and Sample Size Calculations for Respondent-Driven Sampling

PubMed Central

2006-01-01

Hidden populations, such as injection drug users and sex workers, are central to a number of public health problems. However, because of the nature of these groups, it is difficult to collect accurate information about them, and this difficulty complicates disease prevention efforts. A recently developed statistical approach called respondent-driven sampling improves our ability to study hidden populations by allowing researchers to make unbiased estimates of the prevalence of certain traits in these populations. Yet, not enough is known about the sample-to-sample variability of these prevalence estimates. In this paper, we present a bootstrap method for constructing confidence intervals around respondent-driven sampling estimates and demonstrate in simulations that it outperforms the naive method currently in use. We also use simulations and real data to estimate the design effects for respondent-driven sampling in a number of situations. We conclude with practical advice about the power calculations that are needed to determine the appropriate sample size for a study using respondent-driven sampling. In general, we recommend a sample size twice as large as would be needed under simple random sampling. PMID:16937083

Online Sequential Projection Vector Machine with Adaptive Data Mean Update.

PubMed

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.

The Politics of the Hidden Curriculum

ERIC Educational Resources Information Center

Giroux, Henry A.

1977-01-01

Schools teach much more than the traditional curriculum. They also teach a "hidden curriculum"--those unstated norms, values, and beliefs promoting hierarchic and authoritarian social relations that are transmitted to students through the underlying educational structure. Discusses the effects of the "hidden curriculum" on the…

Birefringence and hidden photons

NASA Astrophysics Data System (ADS)

Arza, Ariel; Gamboa, J.

2018-05-01

We study a model where photons interact with hidden photons and millicharged particles through a kinetic mixing term. Particularly, we focus on vacuum birefringence effects and we find a bound for the millicharged parameter assuming that hidden photons are a piece of the local dark matter density.

Hidden vorticity in binary Bose-Einstein condensates

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

Brtka, Marijana; Gammal, Arnaldo; Malomed, Boris A.

We consider a binary Bose-Einstein condensate (BEC) described by a system of two-dimensional (2D) Gross-Pitaevskii equations with the harmonic-oscillator trapping potential. The intraspecies interactions are attractive, while the interaction between the species may have either sign. The same model applies to the copropagation of bimodal beams in photonic-crystal fibers. We consider a family of trapped hidden-vorticity (HV) modes in the form of bound states of two components with opposite vorticities S{sub 1,2}={+-}1, the total angular momentum being zero. A challenging problem is the stability of the HV modes. By means of a linear-stability analysis and direct simulations, stability domains aremore » identified in a relevant parameter plane. In direct simulations, stable HV modes feature robustness against large perturbations, while unstable ones split into fragments whose number is identical to the azimuthal index of the fastest growing perturbation eigenmode. Conditions allowing for the creation of the HV modes in the experiment are discussed too. For comparison, a similar but simpler problem is studied in an analytical form, viz., the modulational instability of an HV state in a one-dimensional (1D) system with periodic boundary conditions (this system models a counterflow in a binary BEC mixture loaded into a toroidal trap or a bimodal optical beam coupled into a cylindrical shell). We demonstrate that the stabilization of the 1D HV modes is impossible, which stresses the significance of the stabilization of the HV modes in the 2D setting.« less

A Solution Method of Job-shop Scheduling Problems by the Idle Time Shortening Type Genetic Algorithm

NASA Astrophysics Data System (ADS)

Ida, Kenichi; Osawa, Akira

In this paper, we propose a new idle time shortening method for Job-shop scheduling problems (JSPs). We insert its method into a genetic algorithm (GA). The purpose of JSP is to find a schedule with the minimum makespan. We suppose that it is effective to reduce idle time of a machine in order to improve the makespan. The left shift is a famous algorithm in existing algorithms for shortening idle time. The left shift can not arrange the work to idle time. For that reason, some idle times are not shortened by the left shift. We propose two kinds of algorithms which shorten such idle time. Next, we combine these algorithms and the reversal of a schedule. We apply GA with its algorithm to benchmark problems and we show its effectiveness.

Implications of the measured angular anisotropy at the hidden order transition of URu2Si2

NASA Astrophysics Data System (ADS)

Chandra, P.; Coleman, P.; Flint, R.; Trinh, J.; Ramirez, A. P.

2018-05-01

The heavy fermion compound URu2Si2 continues to attract great interest due to the long-unidentified nature of the hidden order that develops below 17.5 K. Here we discuss the implications of an angular survey of the linear and nonlinear susceptibility of URu2Si2 in the vicinity of the hidden order transition [1]. While the anisotropic nature of spin fluctuations and low-temperature quasiparticles was previously established, our recent results suggest that the order parameter itself has intrinsic Ising anisotropy, and that moreover this anisotropy extends far above the hidden order transition. Consistency checks and subsequent questions for future experimental and theoretical studies of hidden order are discussed.

Optimal satisfaction degree in energy harvesting cognitive radio networks

NASA Astrophysics Data System (ADS)

Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui

2015-12-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).

Securing the User's Work Environment

NASA Technical Reports Server (NTRS)

Cardo, Nicholas P.

2004-01-01

High performance computing at the Numerical Aerospace Simulation Facility at NASA Ames Research Center includes C90's, J90's and Origin 2000's. Not only is it necessary to protect these systems from outside attacks, but also to provide a safe working environment on the systems. With the right tools, security anomalies in the user s work environment can be deleted and corrected. Validating proper ownership of files against user s permissions, will reduce the risk of inadvertent data compromise. The detection of extraneous directories and files hidden amongst user home directories is important for identifying potential compromises. The first runs of these utilities detected over 350,000 files with problems. With periodic scans, automated correction of problems takes only minutes. Tools for detecting these types of problems as well as their development techniques will be discussed with emphasis on consistency, portability and efficiency for both UNICOS and IRIX.

Health impacts and research ethics in female trafficking.

PubMed

Dhital, S R; Aro, R A; Sapkota, K

2011-04-01

Female trafficking is a social and public health problem, associated with physical and sexual abuse, psychological trauma, injuries from violence, sexually transmitted infections, adverse reproductive outcomes and substance misuse. It faces several challenges ranging from the hidden nature of the problem to ethical and human rights issues. The objectives of this paper are to analyze health impact of trafficking; ethical and research issues and anti-trafficking strategies in the Nepalese context. We collected published and unpublished data assessing the public health, ethical burden and research needs from different sources. Trafficked female involved in sex-industry that face grave situation as depicted and it might a reservoir of sexually transmitted diseases. Ethical issues related to survey of assessing the burden are difficult to carry out. The best ways to prevent and control these problems are to enhance anti- trafficking laws and raise awareness, empower and mobilize females and establish organizational capacity.

Sleep-related problems and minor psychiatric disorders among Brazilian shift workers.

PubMed

Olinto, Maria Teresa Anselmo; Garcez, Anderson; Henn, Ruth Liane; Macagnan, Jamile Block Araldi; Paniz, Vera Maria Vieira; Pattussi, Marcos Pascoal

2017-11-01

The aim of this study was to explore the association between sleep-related problems with the occurrence of minor psychiatric disorders in shift workers of southern Brazil. A cross-sectional study with 1202 workers (785 females) aged 18-50 years was carried out. Minor psychiatric disorders were assessed using the Self-Reporting Questionnaire (SRQ-20), and four sleep problems were collected and analyzed: sleep deprivation (≤ 5h), difficulty falling asleep, waking up during sleep, and sleep medication use. Results show that the overall prevalence of minor psychiatric disorders was 26.8%, but it was more prevalent among females than males (30.2% vs. 20.4%). Nightshift work was significantly associated with the occurrence of sleep-related problems. After adjusting for confounding factors, the number of sleep-related problems showed a positive linear trend with psychiatric disorders in both sexes. Having two or more sleep-related problems was associated with increased probability of psychiatric disorders approximately three-fold among males and two-fold among females, when compared with those without sleep problems. In conclusion, this study demonstrated that sleep-related problems have a strong and independent association with psychiatric disorders among shift workers. Furthermore, the prevalence of both conditions was higher among females than males; however, the strength of these associations was higher in males. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating replicate time shifts using Gaussian process regression

PubMed Central

Liu, Qiang; Andersen, Bogi; Smyth, Padhraic; Ihler, Alexander

2010-01-01

Motivation: Time-course gene expression datasets provide important insights into dynamic aspects of biological processes, such as circadian rhythms, cell cycle and organ development. In a typical microarray time-course experiment, measurements are obtained at each time point from multiple replicate samples. Accurately recovering the gene expression patterns from experimental observations is made challenging by both measurement noise and variation among replicates' rates of development. Prior work on this topic has focused on inference of expression patterns assuming that the replicate times are synchronized. We develop a statistical approach that simultaneously infers both (i) the underlying (hidden) expression profile for each gene, as well as (ii) the biological time for each individual replicate. Our approach is based on Gaussian process regression (GPR) combined with a probabilistic model that accounts for uncertainty about the biological development time of each replicate. Results: We apply GPR with uncertain measurement times to a microarray dataset of mRNA expression for the hair-growth cycle in mouse back skin, predicting both profile shapes and biological times for each replicate. The predicted time shifts show high consistency with independently obtained morphological estimates of relative development. We also show that the method systematically reduces prediction error on out-of-sample data, significantly reducing the mean squared error in a cross-validation study. Availability: Matlab code for GPR with uncertain time shifts is available at http://sli.ics.uci.edu/Code/GPRTimeshift/ Contact: ihler@ics.uci.edu PMID:20147305

Air Force Shift Worker Fatigue Survey

DTIC Science & Technology

2005-08-01

ensuring that health care and counseling services are available to employees who work non-traditional schedules. "* " Employees may consider various ways for...responded: Shift workers 1stSgt/CC Environmental (noise, lighting, temp., etc.): 35% 35% Family: 15% 14% Health factors (diet, stress, insomnia): 8% 14...fatigue and equity problems reported by the shift workers . 14. An automated shift work scheduling tool is needed’°. Sleep Hygiene and Health Issues

[The social hygiene problems in the operator work of hydroelectric power station workers and the means for enhancing work capacity].

PubMed

Karakashian, A N; Lepeshkina, T R; Ratushnaia, A N; Glushchenko, S S; Zakharenko, M I; Lastovchenko, V B; Diordichuk, T I

1993-01-01

Weight, tension and harmfulness of professional activity, peculiarities of labour conditions and characteristics of work, shift dynamics of operative personnel's working capacity were studied in the course of 8-hour working day currently accepted at hydroelectric power stations (HEPS) and experimental 12-hour schedule. Working conditions classified as "admissible", positive dynamics of operators' state, their social and material contentment were a basis for 12-hour two-shift schedule to be recommended as more appropriate. At the same time, problem of optimal shift schedules for operative personnel of HEPS remains unsolved and needs to be further explored.

The effect of parents' joint work schedules on infants' behavior over the first two years of life: evidence from the ECLSB.

PubMed

Rosenbaum, Emily; Morett, Christopher R

2009-11-01

We test whether infants living with employed, co-resident parents where at least one parent works a non-standard work shift exhibit significantly more behavior problems than children whose parents both work traditional day shifts. We use a sample of infants living with employed, co-resident parents and two waves of data from the Early Childhood Longitudinal Survey, Birth Cohort (ECLSB) to test whether infants' scores on the Infant-Toddler Symptom Checklist (ITSC) at the second wave (average age of 24.3 months) is affected by parents' shift work at the baseline (average age 10.3 months). Infants with at least one parent who works nonstandard hours have significantly more behavior problems than do infants with parents who both work regular day shifts. This relationship is partly accounted for by shift work's negative association with father-child interaction, marital quality, the frequency of shared family dinners, and parental health, including paternal depression. The results also indicate that shift work has larger effects on children's behavior when mothers, rather than fathers, work nonstandard shifts, and when mothers' day shifts regularly oppose fathers' evenings/night shifts. Policy should focus on giving individuals more choice in their work shift as well as more flexibility in when they start and stop working for the day. Given the importance of mediating factors, we should also focus on ameliorating the negative impacts of shift work when they do arise. This includes addressing issues of employee health and stress, and relationship conflict within couples where one or both partners work a non-standard shift.

Shifting Attention

ERIC Educational Resources Information Center

Ingram, Jenni

2014-01-01

This article examines the shifts in attention and focus as one teacher introduces and explains an image that represents the processes involved in a numeric problem that his students have been working on. This paper takes a micro-analytic approach to examine how the focus of attention shifts through what the teacher and students do and say in the…

Physiological and Psychological Aspects of Night and Shift Work.

ERIC Educational Resources Information Center

Wojtczak-Jaroszowa, Jadwiga

Results of physiological and psychological studies related to night and shift work are reviewed from the standpoint of their possible use by industry in understanding the problems of shift work and finding solutions. (New research data that has appeared since original preparation of the manuscript is presented in a three-part addendum with…

Systematic review of the relationship between quick returns in rotating shift work and health-related outcomes.

PubMed

Vedaa, Øystein; Harris, Anette; Bjorvatn, Bjørn; Waage, Siri; Sivertsen, Børge; Tucker, Philip; Pallesen, Ståle

2016-01-01

A systematic literature search was carried out to investigate the relationship between quick returns (i.e., 11.0 hours or less between two consecutive shifts) and outcome measures of health, sleep, functional ability and work-life balance. A total of 22 studies published in 21 articles were included. Three types of quick returns were differentiated (from evening to morning/day, night to evening, morning/day to night shifts) where sleep duration and sleepiness appeared to be differently affected depending on which shifts the quick returns occurred between. There were some indications of detrimental effects of quick returns on proximate problems (e.g., sleep, sleepiness and fatigue), although the evidence of associations with more chronic outcome measures (physical and mental health and work-life balance) was inconclusive. Modern societies are dependent on people working shifts. This study systematically reviews literature on the consequences of quick returns (11.0 hours or less between two shifts). Quick returns have detrimental effects on acute health problems. However, the evidence regarding effects on chronic health is inconclusive.

Acid and alkaline solubilization (pH shift) process: a better approach for the utilization of fish processing waste and by-products.

PubMed

Surasani, Vijay Kumar Reddy

2018-05-22

Several technologies and methods have been developed over the years to address the environmental pollution and nutritional losses associated with the dumping of fish processing waste and low-cost fish and by-products. Despite the continuous efforts put in this field, none of the developed technologies was successful in addressing the issues due to various technical problems. To solve the problems associated with the fish processing waste and low-value fish and by-products, a process called pH shift/acid and alkaline solubilization process was developed. In this process, proteins are first solubilized using acid and alkali followed by precipitating them at their isoelectric pH to recover functional and stable protein isolates from underutilized fish species and by-products. Many studies were conducted using pH shift process to recover proteins from fish and fish by-products and found to be most successful in recovering proteins with increased yields than conventional surimi (three cycle washing) process and with good functional properties. In this paper, problems associated with conventional processing, advantages and principle of pH shift processing, effect of pH shift process on the quality and storage stability of recovered isolates, applications protein isolates, etc. are discussed in detail for better understanding.

Equations of motion for the gravitational two-body problem

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

Whitney, C.K.

1988-01-01

This paper reinvestigates the well-known gravitational two-body problem, in light of new information concerning the electrodynamic version of the problem. The well-known Lienard-Wiechert potentials, and the fields derived from them, are suspected to be time-shifted, anticipating the true potentials and fields by the time required for signal propagation from the source to the observer. This time shift is significant because it implies field directions different to first order in v/c. In the gravitational problem, the resulting observer accelerations become correlated with retarded source positions, rather than with present, unretarded source positions as was previously believed. This means there exist previouslymore » unrecognized first-order effects in gravitational systems.« less

A simulation study of gene-by-environment interactions in GWAS implies ample hidden effects

PubMed Central

Marigorta, Urko M.; Gibson, Greg

2014-01-01

The switch to a modern lifestyle in recent decades has coincided with a rapid increase in prevalence of obesity and other diseases. These shifts in prevalence could be explained by the release of genetic susceptibility for disease in the form of gene-by-environment (GxE) interactions. Yet, the detection of interaction effects requires large sample sizes, little replication has been reported, and a few studies have demonstrated environmental effects only after summing the risk of GWAS alleles into genetic risk scores (GRSxE). We performed extensive simulations of a quantitative trait controlled by 2500 causal variants to inspect the feasibility to detect gene-by-environment interactions in the context of GWAS. The simulated individuals were assigned either to an ancestral or a modern setting that alters the phenotype by increasing the effect size by 1.05–2-fold at a varying fraction of perturbed SNPs (from 1 to 20%). We report two main results. First, for a wide range of realistic scenarios, highly significant GRSxE is detected despite the absence of individual genotype GxE evidence at the contributing loci. Second, an increase in phenotypic variance after environmental perturbation reduces the power to discover susceptibility variants by GWAS in mixed cohorts with individuals from both ancestral and modern environments. We conclude that a pervasive presence of gene-by-environment effects can remain hidden even though it contributes to the genetic architecture of complex traits. PMID:25101110

New colored optical security elements using Rolic's LPP/LCP technology: devices for first- to third-level inspection

NASA Astrophysics Data System (ADS)

Moia, Franco

2002-04-01

With linear photo-polymerization (LPP) ROLIC has invented a photo-patternable technology enabling to align not only conventional liquid crystals but also liquid crystals polymers (LCP). ROLIC's optical security device technology derives from its LPP/LCP technology. LPP/LCP security devices are created by structured photo-alignment of an LPP layer through phot-masks, thus generating a high resolution, photo-patterned aligning layer which carries the aligning information of the image to be created. The subsequent LCP layer transforms the aligning information into an optical phase image with low and/or very high information content, such as invisible photographic pictures. The building block capability of the LPP/LCP technology allows the manufacturing of cholesteric and non-cholesteric LPP/LCP devices which cover 1st and/or 2nd level applications. Apart from black/white security devices colored information zones can be integrated. Moreover, we have developed an LPP/LCP security device which covers all three- 1st, 2nd and 3rd- inspection levels in one and the same authentication device: besides a color shift by tilting the device (1st level) and the detection of normally hidden information by use of a simple sheet polarizer (2nd level) the new device contains encrypted hidden information which can be visualized only by superimposing an LPP/LCP inspection tool (key) for decryption (3rd level). This optical key is also based on the LPP/LCP technology and is itself a 3rd level security device.

The Hidden Curriculum in Distance Education: An Updated View.

ERIC Educational Resources Information Center

Anderson, Terry

2001-01-01

Addressing recent criticism of distance education, explores the distinctive hidden curriculum (supposed "real" agenda) of distance education, focusing on both its positive and negative expressions. Also offers an updated view of the hidden curriculum of traditional, campus-based education, grounded in an emerging worldwide context of broadening…

77 FR 8253 - Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-14

... ENVIRONMENTAL PROTECTION AGENCY [FRL-9631-3] Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill Superfund Site ACTION: Notice. SUMMARY: In accordance... (``DOJ'') on behalf of EPA, in connection with the Hidden Lane Landfill Superfund Site, Sterling, Loudoun...

Hidden Curriculum as One of Current Issue of Curriculum

ERIC Educational Resources Information Center

Alsubaie, Merfat Ayesh

2015-01-01

There are several issues in the education system, especially in the curriculum field that affect education. Hidden curriculum is one of current controversial curriculum issues. Many hidden curricular issues are the result of assumptions and expectations that are not formally communicated, established, or conveyed within the learning environment.…

Hidden Variable Theories and Quantum Nonlocality

ERIC Educational Resources Information Center

Boozer, A. D.

2009-01-01

We clarify the meaning of Bell's theorem and its implications for the construction of hidden variable theories by considering an example system consisting of two entangled spin-1/2 particles. Using this example, we present a simplified version of Bell's theorem and describe several hidden variable theories that agree with the predictions of…

Building Simple Hidden Markov Models. Classroom Notes

ERIC Educational Resources Information Center

Ching, Wai-Ki; Ng, Michael K.

2004-01-01

Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.

Seuss's Butter Battle Book: Is There Hidden Harm?

ERIC Educational Resources Information Center

Van Cleaf, David W.; Martin, Rita J.

1986-01-01

Examines whether elementary school children relate to the "harmful hidden message" about nuclear war in Dr. Seuss's THE BUTTER BATTLE BOOK. After ascertaining the children's cognitive level, they participated in activities to find hidden meanings in stories, including Seuss's book. Students failed to identify the nuclear war message in…

Comment on 'All quantum observables in a hidden-variable model must commute simultaneously'

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

Nagata, Koji

Malley discussed [Phys. Rev. A 69, 022118 (2004)] that all quantum observables in a hidden-variable model for quantum events must commute simultaneously. In this comment, we discuss that Malley's theorem is indeed valid for the hidden-variable theoretical assumptions, which were introduced by Kochen and Specker. However, we give an example that the local hidden-variable (LHV) model for quantum events preserves noncommutativity of quantum observables. It turns out that Malley's theorem is not related to the LHV model for quantum events, in general.

Night shift and rotating shift in association with sleep problems, burnout and minor mental disorder in male and female employees.

PubMed

Cheng, Wan-Ju; Cheng, Yawen

2017-07-01

Shift work is associated with adverse physical and psychological health outcomes. However, the independent health effects of night work and rotating shift on workers' sleep and mental health risks and the potential gender differences have not been fully evaluated. We used data from a nationwide survey of representative employees of Taiwan in 2013, consisting of 16 440 employees. Participants reported their work shift patterns 1 week prior to the survey, which were classified into the four following shift types: fixed day, rotating day, fixed night and rotating night shifts. Also obtained were self-reported sleep duration, presence of insomnia, burnout and mental disorder assessed by the Brief Symptom Rating Scale. Among all shift types, workers with fixed night shifts were found to have the shortest duration of sleep, highest level of burnout score, and highest prevalence of insomnia and minor mental disorders. Gender-stratified regression analyses with adjustment of age, education and psychosocial work conditions showed that both in male and female workers, fixed night shifts were associated with greater risks for short sleep duration (<7 hours per day) and insomnia. In female workers, fixed night shifts were also associated with increased risks for burnout and mental disorders, but after adjusting for insomnia, the associations between fixed night shifts and poor mental health were no longer significant. The findings of this study suggested that a fixed night shift was associated with greater risks for sleep and mental health problems, and the associations might be mediated by sleep disturbance. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Insomnia in shift work.

PubMed

Vallières, Annie; Azaiez, Aïda; Moreau, Vincent; LeBlanc, Mélanie; Morin, Charles M

2014-12-01

Shift work disorder involves insomnia and/or excessive sleepiness associated with the work schedule. The present study examined the impact of insomnia on the perceived physical and psychological health of adults working on night and rotating shift schedules compared to day workers. A total of 418 adults (51% women, mean age 41.4 years), including 51 night workers, 158 rotating shift workers, and 209 day workers were selected from an epidemiological study. An algorithm was used to classify each participant of the two groups (working night or rotating shifts) according to the presence or absence of insomnia symptoms. Each of these individuals was paired with a day worker according to gender, age, and income. Participants completed several questionnaires measuring sleep, health, and psychological variables. Night and rotating shift workers with insomnia presented a sleep profile similar to that of day workers with insomnia. Sleep time was more strongly related to insomnia than to shift work per se. Participants with insomnia in the three groups complained of anxiety, depression, and fatigue, and reported consuming equal amounts of sleep-aid medication. Insomnia also contributed to chronic pain and otorhinolaryngology problems, especially among rotating shift workers. Work productivity and absenteeism were more strongly related to insomnia. The present study highlights insomnia as an important component of the sleep difficulties experienced by shift workers. Insomnia may exacerbate certain physical and mental health problems of shift workers, and impair their quality of life. Copyright © 2014 Elsevier B.V. All rights reserved.

Mothers’ Night Work and Children’s Behavior Problems

PubMed Central

Dunifon, Rachel; Kalil, Ariel; Crosby, Danielle; Su, Jessica Houston

2013-01-01

Many mothers work in jobs with nonstandard schedules (i.e., schedules that involve work outside of the traditional 9–5, Monday through Friday schedule); this is particularly true for economically disadvantaged mothers. The present paper uses longitudinal data from the Fragile Families and Child Wellbeing Survey (n = 2,367 mothers of children ages 3–5) to examine the associations between maternal nonstandard work and children’s behavior problems, with a particular focus on mothers’ night shift work. We employ three analytic strategies that take various approaches to adjusting for observed and unobserved selection factors; these approaches provide an upper and lower bound on the true relationship between night shift work and children’s behavior. Taken together, the results provide suggestive evidence for modest associations between exposure to maternal night shift work and higher levels of aggressive and anxious/depressed behavior in children compared to mothers who are not working, those whose mothers work other types of nonstandard shifts, and, for aggressive behavior, those whose mothers work standard shifts. PMID:23294148

Mothers' night work and children's behavior problems.

PubMed

Dunifon, Rachel; Kalil, Ariel; Crosby, Danielle A; Su, Jessica Houston

2013-10-01

Many mothers work in jobs with nonstandard schedules (i.e., schedules that involve work outside of the traditional 9-5, Monday through Friday schedule); this is particularly true for economically disadvantaged mothers. In the present article, we used longitudinal data from the Fragile Families and Child Wellbeing Survey (n = 2,367 mothers of children ages 3-5 years) to examine the associations between maternal nonstandard work and children's behavior problems, with a particular focus on mothers' night shift work. We employed 3 analytic strategies with various approaches to adjusting for observed and unobserved selection factors; these approaches provided an upper and lower bound on the true relationship between night shift work and children's behavior. Taken together, the results provide suggestive evidence for modest associations between exposure to maternal night shift work and higher levels of aggressive and anxious or depressed behavior in children compared with children whose mothers who are not working, those whose mothers work other types of nonstandard shifts, and, for aggressive behavior, those whose mothers work standard shifts.

A primary shift rotation nurse scheduling using zero-one linear goal programming.

PubMed

Huarng, F

1999-01-01

In this study, the author discusses the effect of nurse shift schedules on circadian rhythm and some important ergonomics criteria. The author also reviews and compares different nurse shift scheduling methods via the criteria of flexibility, fairness, continuity in shift assignments, nurses' preferences, and ergonomics principles. In this article, a primary shift rotation system is proposed to provide better continuity in shift assignments to satisfy nurses' preferences. The primary shift rotation system is modeled as a zero-one linear goal programming (LGP) problem. To generate the shift assignment for a unit with 13 nurses, the zero-one LGP model takes less than 3 minutes on average, whereas the head nurses spend approximately 2 to 3 hours on shift scheduling. This study reports the process of implementing the primary shift rotation system.

Analysis of Household Electricity Consumption Patterns and Economy of Water Heating Shifting and Saving Bulbs

NASA Astrophysics Data System (ADS)

Rosin, Argo; Moller, Taavi; Lehtla, Madis; Hoimoja, Hardi

2010-01-01

This article analyses household electricity consumption based on an object in Estonia. Energy consumption of workday and holiday by loads (including high and low tariff energy consumption) is discussed. The final part describes the evaluation of profitability of common investments of consumption shifting and replacing inefficient devices with more efficient ones. Additionally it describes shifting problems and shifting equipment profitability in real-time tariff system.

Surgical management of cutaneous infection caused by atypical mycobacteria after penetrating injury: the hidden dangers of horticulture.

PubMed

Holland, J; Smith, C; Childs, P A; Holland, A J

1997-02-01

We identified two patients in a 12-month period who presented with cutaneous infection and secondary lymph node involvement from atypical mycobacterial infection after minor gardening injuries. One patient had a coinfection with Nocardia asteroides. Both patients required multiple surgical interventions, despite appropriate antibiotic therapy, before resolution of the disease. The course of the infection was characterized by chronic relapses with complete healing at 12 to 18 months after the original injury. The identification and management of this clinical problem are reviewed.

A comparison of polynomial approximations and artificial neural nets as response surfaces

NASA Technical Reports Server (NTRS)

Carpenter, William C.; Barthelemy, Jean-Francois M.

1992-01-01

Artificial neural nets and polynomial approximations were used to develop response surfaces for several test problems. Based on the number of functional evaluations required to build the approximations and the number of undetermined parameters associated with the approximations, the performance of the two types of approximations was found to be comparable. A rule of thumb is developed for determining the number of nodes to be used on a hidden layer of an artificial neural net, and the number of designs needed to train an approximation is discussed.

Protecting the axion with local baryon number

NASA Astrophysics Data System (ADS)

Duerr, Michael; Schmidt-Hoberg, Kai; Unwin, James

2018-05-01

The Peccei-Quinn (PQ) solution to the Strong CP Problem is expected to fail unless the global symmetry U(1)PQ is protected from Planck-scale operators up to high mass dimension. Suitable protection can be achieved if the PQ symmetry is an automatic consequence of some gauge symmetry. We highlight that if baryon number is promoted to a gauge symmetry, the exotic fermions needed for anomaly cancellation can elegantly provide an implementation of the Kim-Shifman-Vainshtein-Zakharov 'hidden axion' mechanism with a PQ symmetry protected from Planck-scale physics.

What Is Going on Inside the Arrows? Discovering the Hidden Springs in Causal Models

PubMed Central

Murray-Watters, Alexander; Glymour, Clark

2016-01-01

Using Gebharter's (2014) representation, we consider aspects of the problem of discovering the structure of unmeasured sub-mechanisms when the variables in those sub-mechanisms have not been measured. Exploiting an early insight of Sober's (1998), we provide a correct algorithm for identifying latent, endogenous structure—sub-mechanisms—for a restricted class of structures. The algorithm can be merged with other methods for discovering causal relations among unmeasured variables, and feedback relations between measured variables and unobserved causes can sometimes be learned. PMID:27313331

Increased taxon sampling reveals thousands of hidden orthologs in flatworms

PubMed Central

2017-01-01

Gains and losses shape the gene complement of animal lineages and are a fundamental aspect of genomic evolution. Acquiring a comprehensive view of the evolution of gene repertoires is limited by the intrinsic limitations of common sequence similarity searches and available databases. Thus, a subset of the gene complement of an organism consists of hidden orthologs, i.e., those with no apparent homology to sequenced animal lineages—mistakenly considered new genes—but actually representing rapidly evolving orthologs or undetected paralogs. Here, we describe Leapfrog, a simple automated BLAST pipeline that leverages increased taxon sampling to overcome long evolutionary distances and identify putative hidden orthologs in large transcriptomic databases by transitive homology. As a case study, we used 35 transcriptomes of 29 flatworm lineages to recover 3427 putative hidden orthologs, some unidentified by OrthoFinder and HaMStR, two common orthogroup inference algorithms. Unexpectedly, we do not observe a correlation between the number of putative hidden orthologs in a lineage and its “average” evolutionary rate. Hidden orthologs do not show unusual sequence composition biases that might account for systematic errors in sequence similarity searches. Instead, gene duplication with divergence of one paralog and weak positive selection appear to underlie hidden orthology in Platyhelminthes. By using Leapfrog, we identify key centrosome-related genes and homeodomain classes previously reported as absent in free-living flatworms, e.g., planarians. Altogether, our findings demonstrate that hidden orthologs comprise a significant proportion of the gene repertoire in flatworms, qualifying the impact of gene losses and gains in gene complement evolution. PMID:28400424

A Rose By Other Names: Some General Musings on Lawrence and Colleagues' Hidden Curriculum Scoping Review.

PubMed

Hafferty, Frederic W; Martimianakis, Maria Athina

2017-11-07

In this Commentary, the authors explore the scoping review by Lawrence and colleagues by challenging their conclusion that with over 25 years' worth of "ambiguous and seemingly ubiquitous use" of the hidden curriculum construct in health professions education scholarship, it is time to either move to a more uniform definitional foundation or abandon the term altogether. The commentary authors counter these remedial propositions by foregrounding the importance of theoretical diversity and the conceptual richness afforded when the hidden curriculum construct is used as an entry point for studying the interstitial space between the formal and a range of other-than-formal domains of learning. Further, they document how tightly-delimited scoping strategies fail to capture the wealth of educational scholarship that operates within a hidden curriculum framework, including "hidden" hidden curriculum articles, studies that employ alternative constructs, and investigations that target important tacit socio-cultural influences on learners and faculty without formally deploying the term. They offer examples of how the hidden curriculum construct, while undergoing significant transformation in its application within the field of health professions education, has created the conceptual foundation for the application of a number of critical perspectives that make visible the field's political investments in particular forms of knowing and associated practices. Finally, the commentary authors invite readers to consider the methodological promise afforded by conceptual heterogeneity, particularly strands of scholarship that resituate the hidden curriculum concept within the magically expansive dance of social relationships, social learning, and social life that form the learning environments of health professions education.

FIMP dark matter freeze-in gauge mediation and hidden sector

NASA Astrophysics Data System (ADS)

Tsao, Kuo-Hsing

2018-07-01

We explore the dark matter freeze-in mechanism within the gauge mediation framework, which involves a hidden feebly interacting massive particle (FIMP) coupling feebly with the messenger fields while the messengers are still in the thermal bath. The FIMP is the fermionic component of the pseudo-moduli in a generic metastable supersymmetry (SUSY) breaking model and resides in the hidden sector. The relic abundance and the mass of the FIMP are determined by the SUSY breaking scale and the feeble coupling. The gravitino, which is the canonical dark matter candidate in the gauge mediation framework, contributes to the dark matter relic abundance along with the freeze-in of the FIMP. The hidden sector thus becomes two-component with both the FIMP and gravitino lodging in the SUSY breaking hidden sector. We point out that the ratio between the FIMP and the gravitino is determined by how SUSY breaking is communicated to the messengers. In particular when the FIMP dominates the hidden sector, the gravitino becomes the minor contributor in the hidden sector. Meanwhile, the neutralino is assumed to be both the weakly interacting massive particle dark matter candidate in the freeze-out mechanism and the lightest observable SUSY particle. We further find out the neutralino has the sub-leading contribution to the current dark matter relic density in the parameter space of our freeze-in gauge mediation model. Our result links the SUSY breaking scale in the gauge mediation framework with the FIMP freeze-in production rate leading to a natural and predicting scenario for the studies of the dark matter in the hidden sector.

What Should We Do With a Hidden Curriculum When We Fine One?

ERIC Educational Resources Information Center

Martin, Jane R.

1976-01-01

A hidden curriculum consists of those learning states of a setting that are either unintended or intended but not openly acknowledged to the learners in the setting unless the learners are aware of them. Consciousness-raising may be the best weapon of individuals who are subject to hidden curricula. (Author/MLF)

Manifestations of Hidden Curriculum in a Community College Online Opticianry Program: An Ecological Approach

ERIC Educational Resources Information Center

Hubbard, Barry

2010-01-01

Understanding the influential factors at work within an online learning environment is a growing area of interest. Hidden or implicit expectations, skill sets, knowledge, and social process can help or hinder student achievement, belief systems, and persistence. This qualitative study investigated how hidden curricular issues transpired in an…

The Hidden Reason Behind Children's Misbehavior.

ERIC Educational Resources Information Center

Nystul, Michael S.

1986-01-01

Discusses hidden reason theory based on the assumptions that: (1) the nature of people is positive; (2) a child's most basic psychological need is involvement; and (3) a child has four possible choices in life (good somebody, good nobody, bad somebody, or severely mentally ill.) A three step approach for implementing hidden reason theory is…

Student Teaching: A Hidden Wholeness

ERIC Educational Resources Information Center

Bowman, Richard F.

2007-01-01

Productive student teachers lead learning by emergently sensing and honoring the hidden wholeness of life in classrooms. That hidden wholeness mirrors seven contextual concerns which learners reflect upon in the everydayness of classroom life: What are we going to do in class today? What am I going to have to do in class? What counts in today's…

Environmental Assessment for the Expansion of Permitted Land and Operations at the 9940 Complex and Thunder Range at Sandia National Laboratories/New Mexico

DTIC Science & Technology

2008-03-01

vivipara Hidden flower Cryptantha crassisepala Hidden flower Cryptantha fulvocanescens James’s hidden flower Cryptantha jamesii Buffalo gourd...pumila Bigbract verbena ta Verbena bractea Banana yucca ta Yucca bacca Soapweed yucca Yucca glauca Rocky Mountain zinnia Zinnia grandiflora A-9

Driving style recognition method using braking characteristics based on hidden Markov model

PubMed Central

Wu, Chaozhong; Lyu, Nengchao; Huang, Zhen

2017-01-01

Since the advantage of hidden Markov model in dealing with time series data and for the sake of identifying driving style, three driving style (aggressive, moderate and mild) are modeled reasonably through hidden Markov model based on driver braking characteristics to achieve efficient driving style. Firstly, braking impulse and the maximum braking unit area of vacuum booster within a certain time are collected from braking operation, and then general braking and emergency braking characteristics are extracted to code the braking characteristics. Secondly, the braking behavior observation sequence is used to describe the initial parameters of hidden Markov model, and the generation of the hidden Markov model for differentiating and an observation sequence which is trained and judged by the driving style is introduced. Thirdly, the maximum likelihood logarithm could be implied from the observable parameters. The recognition accuracy of algorithm is verified through experiments and two common pattern recognition algorithms. The results showed that the driving style discrimination based on hidden Markov model algorithm could realize effective discriminant of driving style. PMID:28837580

A possible loophole in the theorem of Bell.

PubMed

Hess, K; Philipp, W

2001-12-04

The celebrated inequalities of Bell are based on the assumption that local hidden parameters exist. When combined with conflicting experimental results, these inequalities appear to prove that local hidden parameters cannot exist. This contradiction suggests to many that only instantaneous action at a distance can explain the Einstein, Podolsky, and Rosen type of experiments. We show that, in addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions that contribute to his being able to obtain the desired contradiction. For instance, Bell assumes that the hidden parameters do not depend on time and are governed by a single probability measure independent of the analyzer settings. We argue that the exclusion of time has neither a physical nor a mathematical basis but is based on Bell's translation of the concept of Einstein locality into the language of probability theory. Our additional set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does not permit Bell-type proofs to go forward.

Magnetic excitations in Kondo liquid: superconductivity and hidden magnetic quantum critical fluctuations

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

Yang, Yifeng; Urbano, Ricardo; Nicholas, Curro

2009-01-01

We report Knight shift experiments on the superconducting heavy electron material CeCoIn{sub 5} that allow one to track with some precision the behavior of the heavy electron Kondo liquid in the superconducting state with results in agreement with BCS theory. An analysis of the {sup 115}In nuclear quadrupole resonance (NQR) spin-lattice relaxation rate T{sub 1}{sup -1} measurements under pressure reveals the presence of 2d magnetic quantum critical fluctuations in the heavy electron component that are a promising candidate for the pairing mechanism in this material. Our results are consistent with an antiferromagnetic quantum critical point (QCP) located at slightly negativemore » pressure in CeCoIn{sub 5} and provide additional evidence for significant similarities between the heavy electron materials and the high T{sub c} cuprates.« less

The Child as Econometrician: A Rational Model of Preference Understanding in Children

PubMed Central

Lucas, Christopher G.; Griffiths, Thomas L.; Xu, Fei; Fawcett, Christine; Gopnik, Alison; Kushnir, Tamar; Markson, Lori; Hu, Jane

2014-01-01

Recent work has shown that young children can learn about preferences by observing the choices and emotional reactions of other people, but there is no unified account of how this learning occurs. We show that a rational model, built on ideas from economics and computer science, explains the behavior of children in several experiments, and offers new predictions as well. First, we demonstrate that when children use statistical information to learn about preferences, their inferences match the predictions of a simple econometric model. Next, we show that this same model can explain children's ability to learn that other people have preferences similar to or different from their own and use that knowledge to reason about the desirability of hidden objects. Finally, we use the model to explain a developmental shift in preference understanding. PMID:24667309

Moral panic versus the risk society: the implications of the changing sites of social anxiety.

PubMed

Ungar, S

2001-06-01

This paper compares moral panic with the potential political catastrophes of a risk society. The aim of the comparison is threefold: 1. to establish the position of risk society threats alongside more conventional moral panics; 2. to examine the conceptual shifts that accompany the new types of threats; and 3. to outline the changing research agenda. The paper suggests that as new sites of social anxiety have emerged around environmental, nuclear, chemical and medical threats, the questions motivating moral panic research have lost much of their utility. Conceptually, it examines how the roulette dynamics of the risk society accidents expose hidden institutional violations that redound into 'hot potatoes' that are passed among and fumbled by various actors. Changing conceptions of folk devils, claims making activities, and of a safety are also discussed.

The child as econometrician: a rational model of preference understanding in children.

PubMed

Lucas, Christopher G; Griffiths, Thomas L; Xu, Fei; Fawcett, Christine; Gopnik, Alison; Kushnir, Tamar; Markson, Lori; Hu, Jane

2014-01-01

Recent work has shown that young children can learn about preferences by observing the choices and emotional reactions of other people, but there is no unified account of how this learning occurs. We show that a rational model, built on ideas from economics and computer science, explains the behavior of children in several experiments, and offers new predictions as well. First, we demonstrate that when children use statistical information to learn about preferences, their inferences match the predictions of a simple econometric model. Next, we show that this same model can explain children's ability to learn that other people have preferences similar to or different from their own and use that knowledge to reason about the desirability of hidden objects. Finally, we use the model to explain a developmental shift in preference understanding.

Evidence-based medicine and quality of care.

PubMed

Dickenson, Donna; Vineis, Paolo

2002-01-01

In this paper we set out to examine the arguments for and against the claim that Evidence-Based Medicine (EBM) will improve the quality of care. In particular, we examine the following issues: 1. Are there hidden ethical assumptions in the methodology of EBM? 2. Is there a tension between the duty of care and EBM? 3. How can patient preferences be incorporated into quality guidelines and effectiveness studies? 4. Is there a tension between the quality of a particular intervention and overall quality of care? 5. Are certain branches of medicine and patient groups innately or prima facie disadvantaged by a shift to EBM? In addition we consider a case study in the ethics of EBM, on a clinical trial concerning the collection of umbilical cord blood in utero and ex utero, during or after labour in childbirth.

Changes in the respiratory microbiome during acute exacerbations of idiopathic pulmonary fibrosis.

PubMed

Molyneaux, Philip L; Cox, Michael J; Wells, Athol U; Kim, Ho Cheol; Ji, Wonjun; Cookson, William O C; Moffatt, Miriam F; Kim, Dong Soon; Maher, Toby M

2017-02-01

Acute exacerbations of idiopathic pulmonary fibrosis (AE-IPF) have been defined as events of clinically significant respiratory deterioration with an unidentifiable cause. They carry a significant mortality and morbidity and while their exact pathogenesis remains unclear, the possibility remains that hidden infection may play a role. The aim of this pilot study was to determine whether changes in the respiratory microbiota occur during an AE-IPF. Bacterial DNA was extracted from bronchoalveolar lavage from patients with stable IPF and those experiencing an AE-IPF. A hyper-variable region of the 16S ribosomal RNA gene (16S rRNA) was amplified, quantified and pyrosequenced. Culture independent techniques demonstrate AE-IPF is associated with an increased BAL bacterial burden compared to stable disease and highlight shifts in the composition of the respiratory microbiota during an AE-IPF.

Photoacoustic imaging of hidden dental caries by using a bundle of hollow optical fibers

NASA Astrophysics Data System (ADS)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2018-02-01

Photoacoustic imaging system using a bundle of hollow-optical fibers to detect hidden dental caries is proposed. Firstly, we fabricated a hidden caries model with a brown pigment simulating a common color of caries lesion. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating Nd:YAG laser light with a 532 nm wavelength to occlusal surface of model tooth. We calculated by Fourier transform and found that the waveform from the carious part provides frequency components of approximately from 0.5 to 1.2 MHz. Then a photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for clinical applications. From intensity map of frequency components in 0.5-1.2 MHz, photoacoustic images of hidden caries in the simulated samples were successfully obtained.

On the LHC sensitivity for non-thermalised hidden sectors

NASA Astrophysics Data System (ADS)

Kahlhoefer, Felix

2018-04-01

We show under rather general assumptions that hidden sectors that never reach thermal equilibrium in the early Universe are also inaccessible for the LHC. In other words, any particle that can be produced at the LHC must either have been in thermal equilibrium with the Standard Model at some point or must be produced via the decays of another hidden sector particle that has been in thermal equilibrium. To reach this conclusion, we parametrise the cross section connecting the Standard Model to the hidden sector in a very general way and use methods from linear programming to calculate the largest possible number of LHC events compatible with the requirement of non-thermalisation. We find that even the HL-LHC cannot possibly produce more than a few events with energy above 10 GeV involving states from a non-thermalised hidden sector.

Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

NASA Astrophysics Data System (ADS)

Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

2018-03-01

This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).

Hidden charged dark matter and chiral dark radiation

NASA Astrophysics Data System (ADS)

Ko, P.; Nagata, Natsumi; Tang, Yong

2017-10-01

In the light of recent possible tensions in the Hubble constant H0 and the structure growth rate σ8 between the Planck and other measurements, we investigate a hidden-charged dark matter (DM) model where DM interacts with hidden chiral fermions, which are charged under the hidden SU(N) and U(1) gauge interactions. The symmetries in this model assure these fermions to be massless. The DM in this model, which is a Dirac fermion and singlet under the hidden SU(N), is also assumed to be charged under the U(1) gauge symmetry, through which it can interact with the chiral fermions. Below the confinement scale of SU(N), the hidden quark condensate spontaneously breaks the U(1) gauge symmetry such that there remains a discrete symmetry, which accounts for the stability of DM. This condensate also breaks a flavor symmetry in this model and Nambu-Goldstone bosons associated with this flavor symmetry appear below the confinement scale. The hidden U(1) gauge boson and hidden quarks/Nambu-Goldstone bosons are components of dark radiation (DR) above/below the confinement scale. These light fields increase the effective number of neutrinos by δNeff ≃ 0.59 above the confinement scale for N = 2, resolving the tension in the measurements of the Hubble constant by Planck and Hubble Space Telescope if the confinement scale is ≲1 eV. DM and DR continuously scatter with each other via the hidden U(1) gauge interaction, which suppresses the matter power spectrum and results in a smaller structure growth rate. The DM sector couples to the Standard Model sector through the exchange of a real singlet scalar mixing with the Higgs boson, which makes it possible to probe our model in DM direct detection experiments. Variants of this model are also discussed, which may offer alternative ways to investigate this scenario.

Efficient Jacobi-Gauss collocation method for solving initial value problems of Bratu type

NASA Astrophysics Data System (ADS)

Doha, E. H.; Bhrawy, A. H.; Baleanu, D.; Hafez, R. M.

2013-09-01

In this paper, we propose the shifted Jacobi-Gauss collocation spectral method for solving initial value problems of Bratu type, which is widely applicable in fuel ignition of the combustion theory and heat transfer. The spatial approximation is based on shifted Jacobi polynomials J {/n (α,β)}( x) with α, β ∈ (-1, ∞), x ∈ [0, 1] and n the polynomial degree. The shifted Jacobi-Gauss points are used as collocation nodes. Illustrative examples have been discussed to demonstrate the validity and applicability of the proposed technique. Comparing the numerical results of the proposed method with some well-known results show that the method is efficient and gives excellent numerical results.

TRIZ: A Bridge Between Applied and Industrial Physics

NASA Astrophysics Data System (ADS)

Savransky, Semyon

1997-03-01

TRIZ provides a methodology for creative engineering design. TRIZ was founded by Genrich S. Altshuller in Russia, whose with co-workers analyses about 1,500,000 worldwide patents. The major TRIZ principles are [1,2]: 1. All engineering systems have uniform evolution. Many other systems (economic, educational, etc.) have the same evolution trends. 2. Any inventive problem represents a conflict between new requirements and old system. TRIZ comprises various systematically techniques to find an quasi-ideal answer to the inventive problem through solve the conflict based on the knowledge of a system evolution. Usually the hidden root of technical problem is physical contradictions that is possible to resolve using the lists of effects. TRIZ experts use a knowledge base of applied physics to provide solutions of industrial problems . Many companies around the world cite a phenomenal increase in the producti-vity and quality of solutions to tough engineering problems through the use of TRIZ. [1]. G. S. Altshuller, B.L. Zlotin, A.V. Zusman and V.I. Filatov, The new ideas search: From intuition to technology. (in Russian) Kishinev, 1989, 381p. [2]. S.D. Savransky, and C. Stephan, TRIZ: Methodology of Inventive Problem Solving. The Indust-rial Physicist (December 1996).

Real life working shift assignment problem

NASA Astrophysics Data System (ADS)

Sze, San-Nah; Kwek, Yeek-Ling; Tiong, Wei-King; Chiew, Kang-Leng

2017-07-01

This study concerns about the working shift assignment in an outlet of Supermarket X in Eastern Mall, Kuching. The working shift assignment needs to be solved at least once in every month. Current approval process of working shifts is too troublesome and time-consuming. Furthermore, the management staff cannot have an overview of manpower and working shift schedule. Thus, the aim of this study is to develop working shift assignment simulation and propose a working shift assignment solution. The main objective for this study is to fulfill manpower demand at minimum operation cost. Besides, the day off and meal break policy should be fulfilled accordingly. Demand based heuristic is proposed to assign working shift and the quality of the solution is evaluated by using the real data.

Constructive autoassociative neural network for facial recognition.

PubMed

Fernandes, Bruno J T; Cavalcanti, George D C; Ren, Tsang I

2014-01-01

Autoassociative artificial neural networks have been used in many different computer vision applications. However, it is difficult to define the most suitable neural network architecture because this definition is based on previous knowledge and depends on the problem domain. To address this problem, we propose a constructive autoassociative neural network called CANet (Constructive Autoassociative Neural Network). CANet integrates the concepts of receptive fields and autoassociative memory in a dynamic architecture that changes the configuration of the receptive fields by adding new neurons in the hidden layer, while a pruning algorithm removes neurons from the output layer. Neurons in the CANet output layer present lateral inhibitory connections that improve the recognition rate. Experiments in face recognition and facial expression recognition show that the CANet outperforms other methods presented in the literature.

Correlation Research of Medical Security Management System Network Platform in Medical Practice

NASA Astrophysics Data System (ADS)

Jie, Wang; Fan, Zhang; Jian, Hao; Li-nong, Yu; Jun, Fei; Ping, Hao; Ya-wei, Shen; Yue-jin, Chang

Objective-The related research of medical security management system network in medical practice. Methods-Establishing network platform of medical safety management system, medical security network host station, medical security management system(C/S), medical security management system of departments and sections, comprehensive query, medical security disposal and examination system. Results-In medical safety management, medical security management system can reflect the hospital medical security problem, and can achieve real-time detection and improve the medical security incident detection rate. Conclusion-The application of the research in the hospital management implementation, can find hospital medical security hidden danger and the problems of medical disputes, and can help in resolving medical disputes in time and achieve good work efficiency, which is worth applying in the hospital practice.

Estimation of Faults in DC Electrical Power System

NASA Technical Reports Server (NTRS)

Gorinevsky, Dimitry; Boyd, Stephen; Poll, Scott

2009-01-01

This paper demonstrates a novel optimization-based approach to estimating fault states in a DC power system. Potential faults changing the circuit topology are included along with faulty measurements. Our approach can be considered as a relaxation of the mixed estimation problem. We develop a linear model of the circuit and pose a convex problem for estimating the faults and other hidden states. A sparse fault vector solution is computed by using 11 regularization. The solution is computed reliably and efficiently, and gives accurate diagnostics on the faults. We demonstrate a real-time implementation of the approach for an instrumented electrical power system testbed, the ADAPT testbed at NASA ARC. The estimates are computed in milliseconds on a PC. The approach performs well despite unmodeled transients and other modeling uncertainties present in the system.

[Internet research methods: advantages and challenges].

PubMed

Liu, Yi; Tien, Yueh-Hsuan

2009-12-01

Compared to traditional research methods, using the Internet to conduct research offers a number of advantages to the researcher, which include increased access to sensitive issues and vulnerable / hidden populations; decreased data entry time requirements; and enhanced data accuracy. However, Internet research also presents certain challenges to the researcher. In this article, the advantages and challenges of Internet research methods are discussed in four principle issue areas: (a) recruitment, (b) data quality, (c) practicality, and (d) ethics. Nursing researchers can overcome problems related to sampling bias and data truthfulness using creative methods; resolve technical problems through collaboration with other disciplines; and protect participant's privacy, confidentiality and data security by maintaining a high level of vigilance. Once such issues have been satisfactorily addressed, the Internet should open a new window for Taiwan nursing research.

A look at scalable dense linear algebra libraries

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

Dongarra, J.J.; Van de Geijn, R.A.; Walker, D.W.

1992-01-01

We discuss the essential design features of a library of scalable software for performing dense linear algebra computations on distributed memory concurrent computers. The square block scattered decomposition is proposed as a flexible and general-purpose way of decomposing most, if not all, dense matrix problems. An object- oriented interface to the library permits more portable applications to be written, and is easy to learn and use, since details of the parallel implementation are hidden from the user. Experiments on the Intel Touchstone Delta system with a prototype code that uses the square block scattered decomposition to perform LU factorization aremore » presented and analyzed. It was found that the code was both scalable and efficient, performing at about 14 GFLOPS (double precision) for the largest problem considered.« less

A look at scalable dense linear algebra libraries

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

Dongarra, J.J.; Van de Geijn, R.A.; Walker, D.W.

1992-08-01

We discuss the essential design features of a library of scalable software for performing dense linear algebra computations on distributed memory concurrent computers. The square block scattered decomposition is proposed as a flexible and general-purpose way of decomposing most, if not all, dense matrix problems. An object- oriented interface to the library permits more portable applications to be written, and is easy to learn and use, since details of the parallel implementation are hidden from the user. Experiments on the Intel Touchstone Delta system with a prototype code that uses the square block scattered decomposition to perform LU factorization aremore » presented and analyzed. It was found that the code was both scalable and efficient, performing at about 14 GFLOPS (double precision) for the largest problem considered.« less

A Hidden Markov Model Approach to the Problem of Heuristic Selection in Hyper-Heuristics with a Case Study in High School Timetabling Problems.

PubMed

Kheiri, Ahmed; Keedwell, Ed

2017-01-01

Operations research is a well-established field that uses computational systems to support decisions in business and public life. Good solutions to operations research problems can make a large difference to the efficient running of businesses and organisations and so the field often searches for new methods to improve these solutions. The high school timetabling problem is an example of an operations research problem and is a challenging task which requires assigning events and resources to time slots subject to a set of constraints. In this article, a new sequence-based selection hyper-heuristic is presented that produces excellent results on a suite of high school timetabling problems. In this study, we present an easy-to-implement, easy-to-maintain, and effective sequence-based selection hyper-heuristic to solve high school timetabling problems using a benchmark of unified real-world instances collected from different countries. We show that with sequence-based methods, it is possible to discover new best known solutions for a number of the problems in the timetabling domain. Through this investigation, the usefulness of sequence-based selection hyper-heuristics has been demonstrated and the capability of these methods has been shown to exceed the state of the art.

State Space Model with hidden variables for reconstruction of gene regulatory networks.

PubMed

Wu, Xi; Li, Peng; Wang, Nan; Gong, Ping; Perkins, Edward J; Deng, Youping; Zhang, Chaoyang

2011-01-01

State Space Model (SSM) is a relatively new approach to inferring gene regulatory networks. It requires less computational time than Dynamic Bayesian Networks (DBN). There are two types of variables in the linear SSM, observed variables and hidden variables. SSM uses an iterative method, namely Expectation-Maximization, to infer regulatory relationships from microarray datasets. The hidden variables cannot be directly observed from experiments. How to determine the number of hidden variables has a significant impact on the accuracy of network inference. In this study, we used SSM to infer Gene regulatory networks (GRNs) from synthetic time series datasets, investigated Bayesian Information Criterion (BIC) and Principle Component Analysis (PCA) approaches to determining the number of hidden variables in SSM, and evaluated the performance of SSM in comparison with DBN. True GRNs and synthetic gene expression datasets were generated using GeneNetWeaver. Both DBN and linear SSM were used to infer GRNs from the synthetic datasets. The inferred networks were compared with the true networks. Our results show that inference precision varied with the number of hidden variables. For some regulatory networks, the inference precision of DBN was higher but SSM performed better in other cases. Although the overall performance of the two approaches is compatible, SSM is much faster and capable of inferring much larger networks than DBN. This study provides useful information in handling the hidden variables and improving the inference precision.

On the anatomy of a chain shift1

PubMed Central

Dinnsen, Daniel A.; Green, Christopher R.; Gierut, Judith A.; Morrisette, Michele L.

2012-01-01

Phonological chain shifts have been the focus of many theoretical, developmental, and clinical concerns. This paper considers an overlooked property of the problem by focusing on the typological properties of the widely attested ‘s > θ > f’ chain shift involving the processes of Labialization and Dentalization in early phonological development. Findings are reported from a cross-sectional study of 234 children (ages 3 years; 0 months–7;9) with functional (nonorganic) phonological delays. The results reveal some unexpected gaps in the predicted interactions of these processes and are brought to bear on the evaluation of recent optimality theoretic proposals for the characterization of phonological interactions. A developmental modification to the theory is proposed that has the desired effect of precluding certain early-stage grammars. The proposal is further evaluated against the facts of another widely cited developmental chain shift known as the ‘puzzle > puddle > pickle’ problem (Smith 1973). PMID:22389522

Scheduling IT Staff at a Bank: A Mathematical Programming Approach

PubMed Central

Labidi, M.; Mrad, M.; Gharbi, A.; Louly, M. A.

2014-01-01

We address a real-world optimization problem: the scheduling of a Bank Information Technologies (IT) staff. This problem can be defined as the process of constructing optimized work schedules for staff. In a general sense, it requires the allocation of suitably qualified staff to specific shifts to meet the demands for services of an organization while observing workplace regulations and attempting to satisfy individual work preferences. A monthly shift schedule is prepared to determine the shift duties of each staff considering shift coverage requirements, seniority-based workload rules, and staff work preferences. Due to the large number of conflicting constraints, a multiobjective programming model has been proposed to automate the schedule generation process. The suggested mathematical model has been implemented using Lingo software. The results indicate that high quality solutions can be obtained within a few seconds compared to the manually prepared schedules. PMID:24772032

Scheduling IT staff at a bank: a mathematical programming approach.

PubMed

Labidi, M; Mrad, M; Gharbi, A; Louly, M A

2014-01-01

We address a real-world optimization problem: the scheduling of a Bank Information Technologies (IT) staff. This problem can be defined as the process of constructing optimized work schedules for staff. In a general sense, it requires the allocation of suitably qualified staff to specific shifts to meet the demands for services of an organization while observing workplace regulations and attempting to satisfy individual work preferences. A monthly shift schedule is prepared to determine the shift duties of each staff considering shift coverage requirements, seniority-based workload rules, and staff work preferences. Due to the large number of conflicting constraints, a multiobjective programming model has been proposed to automate the schedule generation process. The suggested mathematical model has been implemented using Lingo software. The results indicate that high quality solutions can be obtained within a few seconds compared to the manually prepared schedules.

The Hidden Curriculum of Youth Policy: A Dutch Example

ERIC Educational Resources Information Center

Hopman, Marit; de Winter, Micha; Koops, Willem

2014-01-01

Youth policy is more than a mere response to the actual behavior of children, but it is equally influenced by values and beliefs of policy makers. These values are however rarely made explicit and, therefore, the authors refer to them as "the hidden curriculum" of youth policy. The study investigation explicates this hidden curriculum by…

Hidden School Dropout among Immigrant Students: A Cross-Sectional Study

ERIC Educational Resources Information Center

Makarova, Elena; Herzog, Walter

2013-01-01

Actual school dropout among immigrant youth has been addressed in a number of studies, but research on hidden school dropout among immigrant students is rare. Thus, the objective of this paper is to analyze hidden school dropout among primary school students with an immigrant background. The analyses were performed using survey data of 1186…

Secret Codes: The Hidden Curriculum of Semantic Web Technologies

ERIC Educational Resources Information Center

Edwards, Richard; Carmichael, Patrick

2012-01-01

There is a long tradition in education of examination of the hidden curriculum, those elements which are implicit or tacit to the formal goals of education. This article draws upon that tradition to open up for investigation the hidden curriculum and assumptions about students and knowledge that are embedded in the coding undertaken to facilitate…

Hidden Costs of Hospital Based Delivery from Two Tertiary Hospitals in Western Nepal.

PubMed

Acharya, Jeevan; Kaehler, Nils; Marahatta, Sujan Babu; Mishra, Shiva Raj; Subedi, Sudarshan; Adhikari, Bipin

2016-01-01

Hospital based delivery has been an expensive experience for poor households because of hidden costs which are usually unaccounted in hospital costs. The main aim of this study was to estimate the hidden costs of hospital based delivery and determine the factors associated with the hidden costs. A hospital based cross-sectional study was conducted among 384 post-partum mothers with their husbands/house heads during the discharge time in Manipal Teaching Hospital and Western Regional Hospital, Pokhara, Nepal. A face to face interview with each respondent was conducted using a structured questionnaire. Hidden costs were calculated based on the price rate of the market during the time of the study. The total hidden costs for normal delivery and C-section delivery were 243.4 USD (US Dollar) and 321.6 USD respectively. Of the total maternity care expenditures; higher mean expenditures were found for food & drinking (53.07%), clothes (9.8%) and transport (7.3%). For postpartum women with their husband or house head, the total mean opportunity cost of "days of work loss" were 84.1 USD and 81.9 USD for normal delivery and C-section respectively. Factors such as literate mother (p = 0.007), employed house head (p = 0.011), monthly family income more than 25,000 NRs (Nepalese Rupees) (p = 0.014), private hospital as a place of delivery (p = 0.0001), C-section as a mode of delivery (p = 0.0001), longer duration (>5days) of stay in hospital (p = 0.0001), longer distance (>15km) from house to hospital (p = 0.0001) and longer travel time (>240 minutes) from house to hospital (p = 0.007) showed a significant association with the higher hidden costs (>25000 NRs). Experiences of hidden costs on hospital based delivery and opportunity costs of days of work loss were found high. Several socio-demographic factors, delivery related factors (place and mode of delivery, length of stay, distance from hospital and travel time) were associated with hidden costs. Hidden costs can be a critical factor for many poor and remote households who attend the hospital for delivery. Current remuneration (10-15 USD for normal delivery, 30 USD for complicated delivery and 70 USD for caesarean section delivery) for maternity incentive needs to account the hidden costs by increasing it to 250 USD for normal delivery and 350 USD for C-section. Decentralization of the obstetric care to remote and under-privileged population might reduce the economic burden of pregnant women and can facilitate their attendance at the health care centers.

Occupational Health Screenings of the Virtual Warrior: Distributed Common Ground System Intelligence Operators Compared with Non-Combatant Support Personnel

DTIC Science & Technology

2014-02-01

long hours , shift work , relational conflict...reasons for an increase in medication. Such sleep problems were often explained in textual responses to be the result of long work hours , shift work ...to be operational in nature [1]. Specifically, long hours , shift work , organizational and leadership challenges, nature of work , additional

Night-shift work, sleep duration, daytime napping, and breast cancer risk.

PubMed

Wang, Pan; Ren, Fang-Mei; Lin, Ying; Su, Feng-Xi; Jia, Wei-Hua; Su, Xue-Fen; Tang, Lu-Ying; Ren, Ze-Fang

2015-04-01

Sleep habits vary among different countries, and sleep problems may cause various health problems. The aim of our study was to evaluate the separate and combined associations of night-shift work, sleep duration, and daytime napping with breast cancer risk among the Chinese population. This study conducted face-to-face interviews with 712 women diagnosed with incident invasive breast cancer before treatment and 742 age-matched controls. Information on sleep habits, demographic characteristics, and suspected or established risk factors of breast cancer were collected from the two groups. Multivariate logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs). Night-shift work was associated with an increased risk of breast cancer [OR (95% CI): 1.34 (1.05-1.72)]. Compared to women with a sleep duration of 6.1-8.9 h/day, women who had shorter [(≤6.0 h/day) (OR (95% CI): 1.53 (1.10-2.12)] and longer (≥9.0 h/day) sleep duration [(OR (95% CI): 1.59 (1.17-2.17)] had an increased risk of breast cancer. In addition, daytime napping was associated with a reduced risk of breast cancer among night-shift workers [OR (95% CI): 0.57 (0.36-0.90)], but no association was found among women who never had night-shift work [OR (95% CI): 1.01 (0.75-1.35)] (P for interaction = 0.054). Night-shift work and longer sleep duration also synergistically increased breast cancer risk [OR (95% CI): 3.69 (1.94-7.02)] (P for interaction = 0.009). Sleep problems, including night-shift work, and shorter and longer sleep duration, are associated with an increased breast cancer risk. In particular, the combined effects of night-shift work with no daytime napping or longer sleep duration are greater than the independent effects. Copyright © 2014 Elsevier B.V. All rights reserved.

Dopamine reward prediction errors reflect hidden state inference across time

PubMed Central

Starkweather, Clara Kwon; Babayan, Benedicte M.; Uchida, Naoshige; Gershman, Samuel J.

2017-01-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a ‘belief state’). In this work, we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling exhibited a striking difference between two tasks that differed only with respect to whether reward was delivered deterministically. Our results favor an associative learning rule that combines cached values with hidden state inference. PMID:28263301