Microstructural study of the nickel-base alloy WAZ-20 using qualitative and quantitative electron optical techniques

NASA Technical Reports Server (NTRS)

Young, S. G.

1973-01-01

The NASA nickel-base alloy WAZ-20 was analyzed by advanced metallographic techniques to qualitatively and quantitatively characterize its phases and stability. The as-cast alloy contained primary gamma-prime, a coarse gamma-gamma prime eutectic, a gamma-fine gamma prime matrix, and MC carbides. A specimen aged at 870 C for 1000 hours contained these same constituents and a few widely scattered high W particles. No detrimental phases (such as sigma or mu) were observed. Scanning electron microscope, light metallography, and replica electron microscope methods are compared. The value of quantitative electron microprobe techniques such as spot and area analysis is demonstrated.

Local coding based matching kernel method for image classification.

PubMed

Song, Yan; McLoughlin, Ian Vince; Dai, Li-Rong

2014-01-01

This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV) techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK) method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

Kruskal-Wallis-based computationally efficient feature selection for face recognition.

PubMed

Ali Khan, Sajid; Hussain, Ayyaz; Basit, Abdul; Akram, Sheeraz

2014-01-01

Face recognition in today's technological world, and face recognition applications attain much more importance. Most of the existing work used frontal face images to classify face image. However these techniques fail when applied on real world face images. The proposed technique effectively extracts the prominent facial features. Most of the features are redundant and do not contribute to representing face. In order to eliminate those redundant features, computationally efficient algorithm is used to select the more discriminative face features. Extracted features are then passed to classification step. In the classification step, different classifiers are ensemble to enhance the recognition accuracy rate as single classifier is unable to achieve the high accuracy. Experiments are performed on standard face database images and results are compared with existing techniques.

Feature-based alert correlation in security systems using self organizing maps

NASA Astrophysics Data System (ADS)

Kumar, Munesh; Siddique, Shoaib; Noor, Humera

2009-04-01

The security of the networks has been an important concern for any organization. This is especially important for the defense sector as to get unauthorized access to the sensitive information of an organization has been the prime desire for cyber criminals. Many network security techniques like Firewall, VPN Concentrator etc. are deployed at the perimeter of network to deal with attack(s) that occur(s) from exterior of network. But any vulnerability that causes to penetrate the network's perimeter of defense, can exploit the entire network. To deal with such vulnerabilities a system has been evolved with the purpose of generating an alert for any malicious activity triggered against the network and its resources, termed as Intrusion Detection System (IDS). The traditional IDS have still some deficiencies like generating large number of alerts, containing both true and false one etc. By automatically classifying (correlating) various alerts, the high-level analysis of the security status of network can be identified and the job of network security administrator becomes much easier. In this paper we propose to utilize Self Organizing Maps (SOM); an Artificial Neural Network for correlating large amount of logged intrusion alerts based on generic features such as Source/Destination IP Addresses, Port No, Signature ID etc. The different ways in which alerts can be correlated by Artificial Intelligence techniques are also discussed. . We've shown that the strategy described in the paper improves the efficiency of IDS by better correlating the alerts, leading to reduced false positives and increased competence of network administrator.

Feature-based attention: it is all bottom-up priming.

PubMed

Theeuwes, Jan

2013-10-19

Feature-based attention (FBA) enhances the representation of image characteristics throughout the visual field, a mechanism that is particularly useful when searching for a specific stimulus feature. Even though most theories of visual search implicitly or explicitly assume that FBA is under top-down control, we argue that the role of top-down processing in FBA may be limited. Our review of the literature indicates that all behavioural and neuro-imaging studies investigating FBA suffer from the shortcoming that they cannot rule out an effect of priming. The mere attending to a feature enhances the mandatory processing of that feature across the visual field, an effect that is likely to occur in an automatic, bottom-up way. Studies that have investigated the feasibility of FBA by means of cueing paradigms suggest that the role of top-down processing in FBA is limited (e.g. prepare for red). Instead, the actual processing of the stimulus is needed to cause the mandatory tuning of responses throughout the visual field. We conclude that it is likely that all FBA effects reported previously are the result of bottom-up priming.

Feature-based attention: it is all bottom-up priming

PubMed Central

Theeuwes, Jan

2013-01-01

Feature-based attention (FBA) enhances the representation of image characteristics throughout the visual field, a mechanism that is particularly useful when searching for a specific stimulus feature. Even though most theories of visual search implicitly or explicitly assume that FBA is under top-down control, we argue that the role of top-down processing in FBA may be limited. Our review of the literature indicates that all behavioural and neuro-imaging studies investigating FBA suffer from the shortcoming that they cannot rule out an effect of priming. The mere attending to a feature enhances the mandatory processing of that feature across the visual field, an effect that is likely to occur in an automatic, bottom-up way. Studies that have investigated the feasibility of FBA by means of cueing paradigms suggest that the role of top-down processing in FBA is limited (e.g. prepare for red). Instead, the actual processing of the stimulus is needed to cause the mandatory tuning of responses throughout the visual field. We conclude that it is likely that all FBA effects reported previously are the result of bottom-up priming. PMID:24018717

How to switch on and switch off semantic priming effects for natural and artifactual categories: activation processes in category memory depend on focusing specific feature dimensions.

PubMed

Bermeitinger, Christina; Wentura, Dirk; Frings, Christian

2011-06-01

"Semantic priming" refers to the phenomenon that people react faster to target words preceded by semantically related rather than semantically unrelated words. We wondered whether momentary mind sets modulate semantic priming for natural versus artifactual categories. We interspersed a category priming task with a second task that required participants to react to either the perceptual or action features of simple geometric shapes. Focusing on perceptual features enhanced semantic priming effects for natural categories, whereas focusing on action features enhanced semantic priming effects for artifactual categories. In fact, significant priming effects emerged only for those categories thought to rely on the features activated by the second task. This result suggests that (a) priming effects depend on momentary mind set and (b) features can be weighted flexibly in concept representations; it is also further evidence for sensory-functional accounts of concept and category representation.

Issues and Methods Concerning the Evaluation of Hypersingular and Near-Hypersingular Integrals in BEM Formulations

NASA Technical Reports Server (NTRS)

Fink, P. W.; Khayat, M. A.; Wilton, D. R.

2005-01-01

It is known that higher order modeling of the sources and the geometry in Boundary Element Modeling (BEM) formulations is essential to highly efficient computational electromagnetics. However, in order to achieve the benefits of hIgher order basis and geometry modeling, the singular and near-singular terms arising in BEM formulations must be integrated accurately. In particular, the accurate integration of near-singular terms, which occur when observation points are near but not on source regions of the scattering object, has been considered one of the remaining limitations on the computational efficiency of integral equation methods. The method of singularity subtraction has been used extensively for the evaluation of singular and near-singular terms. Piecewise integration of the source terms in this manner, while manageable for bases of constant and linear orders, becomes unwieldy and prone to error for bases of higher order. Furthermore, we find that the singularity subtraction method is not conducive to object-oriented programming practices, particularly in the context of multiple operators. To extend the capabilities, accuracy, and maintainability of general-purpose codes, the subtraction method is being replaced in favor of the purely numerical quadrature schemes. These schemes employ singularity cancellation methods in which a change of variables is chosen such that the Jacobian of the transformation cancels the singularity. An example of the sin,oularity cancellation approach is the Duffy method, which has two major drawbacks: 1) In the resulting integrand, it produces an angular variation about the singular point that becomes nearly-singular for observation points close to an edge of the parent element, and 2) it appears not to work well when applied to nearly-singular integrals. Recently, the authors have introduced the transformation u(x(prime))= sinh (exp -1) x(prime)/Square root of ((y prime (exp 2))+ z(exp 2) for integrating functions of the form I = Integral of (lambda(r(prime))((e(exp -jkR))/(4 pi R) d D where A (r (prime)) is a vector or scalar basis function and R = Square root of( (x(prime)(exp2) + (y(prime)(exp2) + z(exp 2)) is the distance between source and observation points. This scheme has all of the advantages of the Duffy method while avoiding the disadvantages listed above. In this presentation we will survey similar approaches for handling singular and near-singular terms for kernels with 1/R(exp 2) type behavior, addressing potential pitfalls and offering techniques to efficiently handle special cases.

A novel co-occurrence-based approach to predict pure associative and semantic priming.

PubMed

Roelke, Andre; Franke, Nicole; Biemann, Chris; Radach, Ralph; Jacobs, Arthur M; Hofmann, Markus J

2018-03-15

The theoretical "difficulty in separating association strength from [semantic] feature overlap" has resulted in inconsistent findings of either the presence or absence of "pure" associative priming in recent literature (Hutchison, 2003, Psychonomic Bulletin & Review, 10(4), p. 787). The present study used co-occurrence statistics of words in sentences to provide a full factorial manipulation of direct association (strong/no) and the number of common associates (many/no) of the prime and target words. These common associates were proposed to serve as semantic features for a recent interactive activation model of semantic processing (i.e., the associative read-out model; Hofmann & Jacobs, 2014). With stimulus onset asynchrony (SOA) as an additional factor, our findings indicate that associative and semantic priming are indeed dissociable. Moreover, the effect of direct association was strongest at a long SOA (1,000 ms), while many common associates facilitated lexical decisions primarily at a short SOA (200 ms). This response pattern is consistent with previous performance-based accounts and suggests that associative and semantic priming can be evoked by computationally determined direct and common associations.

Effective gene prediction by high resolution frequency estimator based on least-norm solution technique

PubMed Central

2014-01-01

Linear algebraic concept of subspace plays a significant role in the recent techniques of spectrum estimation. In this article, the authors have utilized the noise subspace concept for finding hidden periodicities in DNA sequence. With the vast growth of genomic sequences, the demand to identify accurately the protein-coding regions in DNA is increasingly rising. Several techniques of DNA feature extraction which involves various cross fields have come up in the recent past, among which application of digital signal processing tools is of prime importance. It is known that coding segments have a 3-base periodicity, while non-coding regions do not have this unique feature. One of the most important spectrum analysis techniques based on the concept of subspace is the least-norm method. The least-norm estimator developed in this paper shows sharp period-3 peaks in coding regions completely eliminating background noise. Comparison of proposed method with existing sliding discrete Fourier transform (SDFT) method popularly known as modified periodogram method has been drawn on several genes from various organisms and the results show that the proposed method has better as well as an effective approach towards gene prediction. Resolution, quality factor, sensitivity, specificity, miss rate, and wrong rate are used to establish superiority of least-norm gene prediction method over existing method. PMID:24386895

The stage of priming: are intertrial repetition effects attentional or decisional?

PubMed

Becker, Stefanie I

2008-02-01

In a visual search task, reaction times to a target are shorter when its features are repeated than when they switch. The present study investigated whether these priming effects affect the attentional stage of target selection, as proposed by the priming of pop-out account, or whether they modulate performance at a later, post-selectional stage, as claimed by the episodic retrieval view. Secondly, to test whether priming affects only the target-defining feature, or whether priming can apply to all target-features in a holistic fashion, two presentation conditions were invoked, that either promoted encoding of only the target-defining feature or holistic encoding of all target features. Results from four eye tracking experiments involving a size and colour singleton target showed that, first, priming modulates selectional processes concerned with guiding attention. Second, there were traces of holistic priming effects, which however were not modulated by the displays, but by expectation and task difficulty.

Priming thoughts about extravagance: implications for consumer decisions about luxury products.

PubMed

Park, Jongwon; Kim, Kyeongheui; Kwak, Junsik; Wyer, Robert S

2014-03-01

If a semantic concept is accessible in memory, it can direct attention to the attributes of a target that exemplify this concept. When these attributes have both affective and utilitarian implications that are evaluatively opposite, the relative impact of these different implications depends on an individual's ability and motivation to expend the cognitive effort required to evaluate them. These assumptions were confirmed in six experiments on the impact of priming the concept of extravagance on attention to a product's luxury-related features and consequent reactions to it. Priming this concept decreased the choice of a luxury product if participants were both motivated and able to construe the utilitarian implications of the product's extravagance-related features. When participants were either distracted from deliberating on their choices or were asked to recommend a product to others, however, priming extravagance led them to base their judgments on the affective reactions that the features spontaneously elicited and consequently increased their choice of the product. © 2013 American Psychological Association

Motorcyclists safety system to avoid rear end collisions based on acoustic signatures

NASA Astrophysics Data System (ADS)

Muzammel, M.; Yusoff, M. Zuki; Malik, A. Saeed; Mohamad Saad, M. Naufal; Meriaudeau, F.

2017-03-01

In many Asian countries, motorcyclists have a higher fatality rate as compared to other vehicles. Among many other factors, rear end collisions are also contributing for these fatalities. Collision detection systems can be useful to minimize these accidents. However, the designing of efficient and cost effective collision detection system for motorcyclist is still a major challenge. In this paper, an acoustic information based, cost effective and efficient collision detection system is proposed for motorcycle applications. The proposed technique uses the Short time Fourier Transform (STFT) to extract the features from the audio signal and Principal component analysis (PCA) has been used to reduce the feature vector length. The reduction of feature length, further increases the performance of this technique. The proposed technique has been tested on self recorded dataset and gives accuracy of 97.87%. We believe that this method can help to reduce a significant number of motorcycle accidents.

Real estate value prediction using multivariate regression models

NASA Astrophysics Data System (ADS)

Manjula, R.; Jain, Shubham; Srivastava, Sharad; Rajiv Kher, Pranav

2017-11-01

The real estate market is one of the most competitive in terms of pricing and the same tends to vary significantly based on a lot of factors, hence it becomes one of the prime fields to apply the concepts of machine learning to optimize and predict the prices with high accuracy. Therefore in this paper, we present various important features to use while predicting housing prices with good accuracy. We have described regression models, using various features to have lower Residual Sum of Squares error. While using features in a regression model some feature engineering is required for better prediction. Often a set of features (multiple regressions) or polynomial regression (applying a various set of powers in the features) is used for making better model fit. For these models are expected to be susceptible towards over fitting ridge regression is used to reduce it. This paper thus directs to the best application of regression models in addition to other techniques to optimize the result.

Elucidating the charge carrier separation and working mechanism of CH3NH3PbI(3-x)Cl(x) perovskite solar cells.

PubMed

Edri, Eran; Kirmayer, Saar; Mukhopadhyay, Sabyasachi; Gartsman, Konstantin; Hodes, Gary; Cahen, David

2014-03-11

Developments in organic-inorganic lead halide-based perovskite solar cells have been meteoric over the last 2 years, with small-area efficiencies surpassing 15%. We address the fundamental issue of how these cells work by applying a scanning electron microscopy-based technique to cell cross-sections. By mapping the variation in efficiency of charge separation and collection in the cross-sections, we show the presence of two prime high efficiency locations, one at/near the absorber/hole-blocking-layer, and the second at/near the absorber/electron-blocking-layer interfaces, with the former more pronounced. This 'twin-peaks' profile is characteristic of a p-i-n solar cell, with a layer of low-doped, high electronic quality semiconductor, between a p- and an n-layer. If the electron blocker is replaced by a gold contact, only a heterojunction at the absorber/hole-blocking interface remains.

Top-k similar graph matching using TraM in biological networks.

PubMed

Amin, Mohammad Shafkat; Finley, Russell L; Jamil, Hasan M

2012-01-01

Many emerging database applications entail sophisticated graph-based query manipulation, predominantly evident in large-scale scientific applications. To access the information embedded in graphs, efficient graph matching tools and algorithms have become of prime importance. Although the prohibitively expensive time complexity associated with exact subgraph isomorphism techniques has limited its efficacy in the application domain, approximate yet efficient graph matching techniques have received much attention due to their pragmatic applicability. Since public domain databases are noisy and incomplete in nature, inexact graph matching techniques have proven to be more promising in terms of inferring knowledge from numerous structural data repositories. In this paper, we propose a novel technique called TraM for approximate graph matching that off-loads a significant amount of its processing on to the database making the approach viable for large graphs. Moreover, the vector space embedding of the graphs and efficient filtration of the search space enables computation of approximate graph similarity at a throw-away cost. We annotate nodes of the query graphs by means of their global topological properties and compare them with neighborhood biased segments of the datagraph for proper matches. We have conducted experiments on several real data sets, and have demonstrated the effectiveness and efficiency of the proposed method

Fracture of single crystals of the nickel-base superalloy PWA 1480E in helium at 22 C

NASA Technical Reports Server (NTRS)

Chen, P. S.; Wilcox, R. C.

1991-01-01

The fracture behavior and deformation of He-charged (at 22 C) single crystals of PWA 1480E Ni-base superalloy were investigated using SEM and TEM techniques to observe the behavior of tensile fractures in notched single crystals with seven different crystal growth orientations: 100-line, 110-line, 111-line, 013-line, 112-line, 123-line, and 223-line. To identify the cleavage plane orientation, a stereoscopic technique, combined with the use of planar gamma-prime morphologies, was applied. It was found that gamma-prime particles were orderly and closely aligned with edges along the 100-line, 010-line, and 001-line-oriented directions of the gamma matrix. Different crystal growth orientations were found not to affect the morphology of gamma-prime particles. The accumulation of dislocations around gamma/gamma-prime interfaces formed strong barriers to subsequent dislocation movement and was the primary strengthening mechanism at room temperature.

It's what's on the outside that matters: an advantage for external features in children's word recognition.

PubMed

Webb, Tessa M; Beech, John R; Mayall, Kate M; Andrews, Antony S

2006-06-01

The relative importance of internal and external letter features of words in children's developing reading was investigated to clarify further the nature of early featural analysis. In Experiment 1, 72 6-, 8-, and 10-year-olds read aloud words displayed as wholes, external features only (central features missing, thereby preserving word shape information), or internal features only (central features preserved). There was an improvement in the processing of external features compared with internal features as reading experience increased. Experiment 2 examined the processing of the internal and external features of words employing a forward priming paradigm with 60 8-, 10-, and 12-year-olds. Reaction times to internal feature primes were equivalent to a nonprime blank condition, whereas responses to external feature primes were faster than those to the other two prime types. This advantage for the external features of words is discussed in terms of an early and enduring role for processing the external visual features in words during reading development.

Utilization of satellite data for inventorying prairie ponds and lakes

USGS Publications Warehouse

Work, E.A.; Gilmer, D.S.

1976-01-01

By using data acquired by LANDSAT-1 (formerly ERTS- 1), studies were conducted in extracting information necessary for formulating management decisions relating to migratory waterfowl. Management decisions are based in part on an assessment ofhabitat characteristics, specifically numbers, distribution, and quality of ponds and lakes in the prime breeding range. This paper reports on a study concerned with mapping open surface water features in the glaciated prairies. Emphasis was placed on the recognition of these features based upon water's uniquely low radiance in a single nearinfrared waveband. The results of this recognition were thematic maps and statistics relating to open surface water. In a related effort, the added information content of multiple spectral wavebands was used for discriminating surface water at a level of detail finer than the virtual resolution of the data. The basic theory of this technique and some preliminary results are described.

Classification of pulmonary nodules in lung CT images using shape and texture features

NASA Astrophysics Data System (ADS)

Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Dutta, Anirvan; Garg, Mandeep; Khandelwal, Niranjan; Kumar, Prafulla

2016-03-01

Differentiation of malignant and benign pulmonary nodules is important for prognosis of lung cancer. In this paper, benign and malignant nodules are classified using support vector machine. Several shape-based and texture-based features are used to represent the pulmonary nodules in the feature space. A semi-automated technique is used for nodule segmentation. Relevant features are selected for efficient representation of nodules in the feature space. The proposed scheme and the competing technique are evaluated on a data set of 542 nodules of Lung Image Database Consortium and Image Database Resource Initiative. The nodules with composite rank of malignancy "1","2" are considered as benign and "4","5" are considered as malignant. Area under the receiver operating characteristics curve is 0:9465 for the proposed method. The proposed method outperforms the competing technique.

Impaired distractor inhibition on a selective attention task in unmedicated, depressed subjects.

PubMed

MacQueen, G M; Tipper, S P; Young, L T; Joffe, R T; Levitt, A J

2000-05-01

Impaired distractor inhibition may contribute to the selective attention deficits observed in depressed patients, but studies to date have not tested the distractor inhibition theory against the possibility that processes such as transient memory review processes may account for the observed deficits. A negative priming paradigm can dissociate inhibition from such a potentially confounding process called object review. The negative priming task also isolates features of the distractor such as colour and location for independent examination. A computerized negative priming task was used in which colour, identification and location features of a stimulus and distractor were systematically manipulated across successive prime and probe trials. Thirty-two unmedicated subjects with DSM-IV diagnoses of non-psychotic unipolar depression were compared with 32 age, sex and IQ matched controls. Depressed subjects had reduced levels of negative priming for conditions where the colour feature of the stimulus was repeated across prime and probe trials but not when identity or location was the repeated feature. When both the colour and location feature were the repeated feature across trials, facilitation in response was apparent. The pattern of results supports studies that found reduced distractor inhibition in depressed subjects, and suggests that object review is intact in these subjects. Greater impairment in negative priming for colour versus location suggests that subjects may have greater impairment in the visual stream associated with processing colour features.

Modeling global scene factors in attention

NASA Astrophysics Data System (ADS)

Torralba, Antonio

2003-07-01

Models of visual attention have focused predominantly on bottom-up approaches that ignored structured contextual and scene information. I propose a model of contextual cueing for attention guidance based on the global scene configuration. It is shown that the statistics of low-level features across the whole image can be used to prime the presence or absence of objects in the scene and to predict their location, scale, and appearance before exploring the image. In this scheme, visual context information can become available early in the visual processing chain, which allows modulation of the saliency of image regions and provides an efficient shortcut for object detection and recognition. 2003 Optical Society of America

Face (and Nose) Priming for Book: The Malleability of Semantic Memory

PubMed Central

Coane, Jennifer H.; Balota, David A.

2010-01-01

There are two general classes of models of semantic structure that support semantic priming effects. Feature-overlap models of semantic priming assume that shared features between primes and targets are critical (e.g., cat-DOG). Associative accounts assume that contextual co-occurrence is critical and that the system is organized along associations independent of featural overlap (e.g., leash-DOG). If unrelated concepts can become related as a result of contextual co-occurrence, this would be more supportive of associative accounts and provide insight into the nature of the network underlying “semantic” priming effects. Naturally co-occurring recent associations (e.g., face-BOOK) were tested under conditions that minimize strategic influences (i.e., short stimulus onset asynchrony, low relatedness proportion) in a semantic priming paradigm. Priming for new associations did not differ from the priming found for pre-existing relations (e.g., library-BOOK). Mediated priming (e.g., nose-BOOK) was also found. These results suggest that contextual associations can result in the reorganization of the network that subserves “semantic” priming effects. PMID:20494866

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

PubMed

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

2004-10-01

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

Predictive information processing in music cognition. A critical review.

PubMed

Rohrmeier, Martin A; Koelsch, Stefan

2012-02-01

Expectation and prediction constitute central mechanisms in the perception and cognition of music, which have been explored in theoretical and empirical accounts. We review the scope and limits of theoretical accounts of musical prediction with respect to feature-based and temporal prediction. While the concept of prediction is unproblematic for basic single-stream features such as melody, it is not straight-forward for polyphonic structures or higher-order features such as formal predictions. Behavioural results based on explicit and implicit (priming) paradigms provide evidence of priming in various domains that may reflect predictive behaviour. Computational learning models, including symbolic (fragment-based), probabilistic/graphical, or connectionist approaches, provide well-specified predictive models of specific features and feature combinations. While models match some experimental results, full-fledged music prediction cannot yet be modelled. Neuroscientific results regarding the early right-anterior negativity (ERAN) and mismatch negativity (MMN) reflect expectancy violations on different levels of processing complexity, and provide some neural evidence for different predictive mechanisms. At present, the combinations of neural and computational modelling methodologies are at early stages and require further research. Copyright © 2012 Elsevier B.V. All rights reserved.

Independent and additive repetition priming of motion direction and color in visual search.

PubMed

Kristjánsson, Arni

2009-03-01

Priming of visual search for Gabor patch stimuli, varying in color and local drift direction, was investigated. The task relevance of each feature varied between the different experimental conditions compared. When the target defining dimension was color, a large effect of color repetition was seen as well as a smaller effect of the repetition of motion direction. The opposite priming pattern was seen when motion direction defined the target--the effect of motion direction repetition was this time larger than for color repetition. Finally, when neither was task relevant, and the target defining dimension was the spatial frequency of the Gabor patch, priming was seen for repetition of both color and motion direction, but the effects were smaller than in the previous two conditions. These results show that features do not necessarily have to be task relevant for priming to occur. There is little interaction between priming following repetition of color and motion, these two features show independent and additive priming effects, most likely reflecting that the two features are processed at separate processing sites in the nervous system, consistent with previous findings from neuropsychology & neurophysiology. The implications of the findings for theoretical accounts of priming in visual search are discussed.

Sharing One Biographical Detail Elicits Priming between Famous Names: Empirical and Computational Approaches

PubMed Central

Ihrke, Matthias; Brennen, Tim

2011-01-01

In this paper three experiments and corresponding model simulations are reported that investigate the priming of famous name recognition in order to explore the structure of the part of the semantic system dealing with people. Consistent with empirical findings, novel computational simulations using Burton et al.’s interactive activation and competition model point to a conceptual distinction between how priming is initiated in single- and double-familiarity tasks, indicating that priming should be weaker or non-existent for the single-familiarity task. Experiment 1 demonstrates that, within a double-familiarity framework using famous names, categorical, and associative priming are reliable effects. Pushing the model to the limit, it predicts that pairs of celebrities who are neither associatively nor categorically related but who share single biographical features, both died in a car crash for example, should prime each other. Experiment 2 investigated this in a double-familiarity task but the effect was not observed. We therefore simulated and realized a pairwise learning task that was conceptually similar to the double-familiarity-decision task but allowed to strengthen the underlying connections. Priming based on a single biographical feature could be found both in simulations and the experiment. The effect was not due to visual or name similarity which were controlled for and participants did not report using the biographical links between the people to learn the pairs. The results are interpreted to lend further support to structural models of the memory for persons. Furthermore, the results are consistent with the idea that episodic features known about people are stored in semantic memory and are automatically activated when encountering that person. PMID:21687446

Glioma grading using cell nuclei morphologic features in digital pathology images

NASA Astrophysics Data System (ADS)

Reza, Syed M. S.; Iftekharuddin, Khan M.

2016-03-01

This work proposes a computationally efficient cell nuclei morphologic feature analysis technique to characterize the brain gliomas in tissue slide images. In this work, our contributions are two-fold: 1) obtain an optimized cell nuclei segmentation method based on the pros and cons of the existing techniques in literature, 2) extract representative features by k-mean clustering of nuclei morphologic features to include area, perimeter, eccentricity, and major axis length. This clustering based representative feature extraction avoids shortcomings of extensive tile [1] [2] and nuclear score [3] based methods for brain glioma grading in pathology images. Multilayer perceptron (MLP) is used to classify extracted features into two tumor types: glioblastoma multiforme (GBM) and low grade glioma (LGG). Quantitative scores such as precision, recall, and accuracy are obtained using 66 clinical patients' images from The Cancer Genome Atlas (TCGA) [4] dataset. On an average ~94% accuracy from 10 fold crossvalidation confirms the efficacy of the proposed method.

Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality.

PubMed

Li, Zhongyu; Butler, Erik; Li, Kang; Lu, Aidong; Ji, Shuiwang; Zhang, Shaoting

2018-02-12

Recently released large-scale neuron morphological data has greatly facilitated the research in neuroinformatics. However, the sheer volume and complexity of these data pose significant challenges for efficient and accurate neuron exploration. In this paper, we propose an effective retrieval framework to address these problems, based on frontier techniques of deep learning and binary coding. For the first time, we develop a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i.e., stacked convolutional autoencoders (SCAEs). The deep features are subsequently fused with the hand-crafted features for more accurate representation. Considering the exhaustive search is usually very time-consuming in large-scale databases, we employ a novel binary coding method to compress feature vectors into short binary codes. Our framework is validated on a public data set including 58,000 neurons, showing promising retrieval precision and efficiency compared with state-of-the-art methods. In addition, we develop a novel neuron visualization program based on the techniques of augmented reality (AR), which can help users take a deep exploration of neuron morphologies in an interactive and immersive manner.

Transient tissue priming via ROCK inhibition uncouples pancreatic cancer progression, sensitivity to chemotherapy, and metastasis.

PubMed

Vennin, Claire; Chin, Venessa T; Warren, Sean C; Lucas, Morghan C; Herrmann, David; Magenau, Astrid; Melenec, Pauline; Walters, Stacey N; Del Monte-Nieto, Gonzalo; Conway, James R W; Nobis, Max; Allam, Amr H; McCloy, Rachael A; Currey, Nicola; Pinese, Mark; Boulghourjian, Alice; Zaratzian, Anaiis; Adam, Arne A S; Heu, Celine; Nagrial, Adnan M; Chou, Angela; Steinmann, Angela; Drury, Alison; Froio, Danielle; Giry-Laterriere, Marc; Harris, Nathanial L E; Phan, Tri; Jain, Rohit; Weninger, Wolfgang; McGhee, Ewan J; Whan, Renee; Johns, Amber L; Samra, Jaswinder S; Chantrill, Lorraine; Gill, Anthony J; Kohonen-Corish, Maija; Harvey, Richard P; Biankin, Andrew V; Evans, T R Jeffry; Anderson, Kurt I; Grey, Shane T; Ormandy, Christopher J; Gallego-Ortega, David; Wang, Yingxiao; Samuel, Michael S; Sansom, Owen J; Burgess, Andrew; Cox, Thomas R; Morton, Jennifer P; Pajic, Marina; Timpson, Paul

2017-04-05

The emerging standard of care for patients with inoperable pancreatic cancer is a combination of cytotoxic drugs gemcitabine and Abraxane, but patient response remains moderate. Pancreatic cancer development and metastasis occur in complex settings, with reciprocal feedback from microenvironmental cues influencing both disease progression and drug response. Little is known about how sequential dual targeting of tumor tissue tension and vasculature before chemotherapy can affect tumor response. We used intravital imaging to assess how transient manipulation of the tumor tissue, or "priming," using the pharmaceutical Rho kinase inhibitor Fasudil affects response to chemotherapy. Intravital Förster resonance energy transfer imaging of a cyclin-dependent kinase 1 biosensor to monitor the efficacy of cytotoxic drugs revealed that priming improves pancreatic cancer response to gemcitabine/Abraxane at both primary and secondary sites. Transient priming also sensitized cells to shear stress and impaired colonization efficiency and fibrotic niche remodeling within the liver, three important features of cancer spread. Last, we demonstrate a graded response to priming in stratified patient-derived tumors, indicating that fine-tuned tissue manipulation before chemotherapy may offer opportunities in both primary and metastatic targeting of pancreatic cancer. Copyright © 2017, American Association for the Advancement of Science.

Transient tissue priming via ROCK inhibition uncouples pancreatic cancer progression, sensitivity to chemotherapy, and metastasis

PubMed Central

Vennin, Claire; Chin, Venessa T.; Warren, Sean C.; Lucas, Morghan C.; Herrmann, David; Magenau, Astrid; Melenec, Pauline; Walters, Stacey N.; del Monte-Nieto, Gonzalo; Conway, James R. W.; Nobis, Max; Allam, Amr H.; McCloy, Rachael A.; Currey, Nicola; Pinese, Mark; Boulghourjian, Alice; Zaratzian, Anaiis; Adam, Arne A. S.; Heu, Celine; Nagrial, Adnan M.; Chou, Angela; Steinmann, Angela; Drury, Alison; Froio, Danielle; Giry-Laterriere, Marc; Harris, Nathanial L. E.; Phan, Tri; Jain, Rohit; Weninger, Wolfgang; McGhee, Ewan J.; Whan, Renee; Johns, Amber L; Samra, Jaswinder S.; Chantrill, Lorraine; Gill, Anthony J.; Kohonen-Corish, Maija; Harvey, Richard P.; Biankin, Andrew V.; Jeffry Evans, T. R.; Anderson, Kurt I.; Grey, Shane T.; Ormandy, Christopher J.; Gallego-Ortega, David; Wang, Yingxiao; Samuel, Michael S.; Sansom, Owen J.; Burgess, Andrew; Cox, Thomas R.; Morton, Jennifer P.; Pajic, Marina; Timpson, Paul

2018-01-01

The emerging standard of care for patients with inoperable pancreatic cancer is a combination of cytotoxic drugs gemcitabine and Abraxane, but patient response remains moderate. Pancreatic cancer development and metastasis occur in complex settings, with reciprocal feedback from microenvironmental cues influencing both disease progression and drug response. Little is known about how sequential dual targeting of tumor tissue tension and vasculature before chemotherapy can affect tumor response. We used intravital imaging to assess how transient manipulation of the tumor tissue, or “priming,” using the pharmaceutical Rho kinase inhibitor Fasudil affects response to chemotherapy. Intravital Förster resonance energy transfer imaging of a cyclin-dependent kinase 1 biosensor to monitor the efficacy of cytotoxic drugs revealed that priming improves pancreatic cancer response to gemcitabine/Abraxane at both primary and secondary sites. Transient priming also sensitized cells to shear stress and impaired colonization efficiency and fibrotic niche remodeling within the liver, three important features of cancer spread. Last, we demonstrate a graded response to priming in stratified patient-derived tumors, indicating that fine-tuned tissue manipulation before chemotherapy may offer opportunities in both primary and metastatic targeting of pancreatic cancer. PMID:28381539

Regression-Based Approach For Feature Selection In Classification Issues. Application To Breast Cancer Detection And Recurrence

NASA Astrophysics Data System (ADS)

Belciug, Smaranda; Serbanescu, Mircea-Sebastian

2015-09-01

Feature selection is considered a key factor in classifications/decision problems. It is currently used in designing intelligent decision systems to choose the best features which allow the best performance. This paper proposes a regression-based approach to select the most important predictors to significantly increase the classification performance. Application to breast cancer detection and recurrence using publically available datasets proved the efficiency of this technique.

Pseudo-random number generator for the Sigma 5 computer

NASA Technical Reports Server (NTRS)

Carroll, S. N.

1983-01-01

A technique is presented for developing a pseudo-random number generator based on the linear congruential form. The two numbers used for the generator are a prime number and a corresponding primitive root, where the prime is the largest prime number that can be accurately represented on a particular computer. The primitive root is selected by applying Marsaglia's lattice test. The technique presented was applied to write a random number program for the Sigma 5 computer. The new program, named S:RANDOM1, is judged to be superior to the older program named S:RANDOM. For applications requiring several independent random number generators, a table is included showing several acceptable primitive roots. The technique and programs described can be applied to any computer having word length different from that of the Sigma 5.

Priming mortality salience: supraliminal, subliminal and "double-death" priming techniques.

PubMed

Mahoney, Melissa B; Saunders, Benjamin A; Cain, Nicole M

2014-01-01

The study examined whether successively presented subliminal and supraliminal morality salience primes ("double death" prime) would have a stronger influence on death thought accessibility than subliminal or supraliminal primes alone. A between-subjects 2 (subliminal prime/control) × 2 (supraliminal prime/control) design was used. The supraliminal prime prompted participants to answer questions about death. For the subliminal prime, the word death was presented outside of awareness. Both priming techniques differed significantly from a control in ability to elicit mortality salience. There was an interactive influence of both primes. Implications for unconscious neutral networks relating to death are discussed.

On the effect of subliminal priming on subjective perception of images: a machine learning approach.

PubMed

Kumar, Parmod; Mahmood, Faisal; Mohan, Dhanya Menoth; Wong, Ken; Agrawal, Abhishek; Elgendi, Mohamed; Shukla, Rohit; Dauwels, Justin; Chan, Alice H D

2014-01-01

The research presented in this article investigates the influence of subliminal prime words on peoples' judgment about images, through electroencephalograms (EEGs). In this cross domain priming paradigm, the participants are asked to rate how much they like the stimulus images, on a 7-point Likert scale, after being subliminally exposed to masked lexical prime words, with EEG recorded simultaneously. Statistical analysis tools are used to analyze the effect of priming on behavior, and machine learning techniques to infer the primes from EEGs. The experiment reveals strong effects of subliminal priming on the participants' explicit rating of images. The subjective judgment affected by the priming makes visible change in event-related potentials (ERPs); results show larger ERP amplitude for the negative primes compared with positive and neutral primes. In addition, Support Vector Machine (SVM) based classifiers are proposed to infer the prime types from the average ERPs, which yields a classification rate of 70%.

Towards fully spray coated organic light emitting devices

NASA Astrophysics Data System (ADS)

Gilissen, Koen; Stryckers, Jeroen; Manca, Jean; Deferme, Wim

2014-10-01

Pi-conjugated polymer light emitting devices have the potential to be the next generation of solid state lighting. In order to achieve this goal, a low cost, efficient and large area production process is essential. Polymer based light emitting devices are generally deposited using techniques based on solution processing e.g.: spin coating, ink jet printing. These techniques are not well suited for cost-effective, high throughput, large area mass production of these organic devices. Ultrasonic spray deposition however, is a deposition technique that is fast, efficient and roll to roll compatible which can be easily scaled up for the production of large area polymer light emitting devices (PLEDs). This deposition technique has already successfully been employed to produce organic photovoltaic devices (OPV)1. Recently the electron blocking layer PEDOT:PSS2 and metal top contact3 have been successfully spray coated as part of the organic photovoltaic device stack. In this study, the effects of ultrasonic spray deposition of polymer light emitting devices are investigated. For the first time - to our knowledge -, spray coating of the active layer in PLED is demonstrated. Different solvents are tested to achieve the best possible spray-able dispersion. The active layer morphology is characterized and optimized to produce uniform films with optimal thickness. Furthermore these ultrasonic spray coated films are incorporated in the polymer light emitting device stack to investigate the device characteristics and efficiency. Our results show that after careful optimization of the active layer, ultrasonic spray coating is prime candidate as deposition technique for mass production of PLEDs.

Perceptual Discrimination of Basic Object Features Is Not Facilitated When Priming Stimuli Are Prevented From Reaching Awareness by Means of Visual Masking

PubMed Central

Peel, Hayden J.; Sperandio, Irene; Laycock, Robin; Chouinard, Philippe A.

2018-01-01

Our understanding of how form, orientation and size are processed within and outside of awareness is limited and requires further investigation. Therefore, we investigated whether or not the visual discrimination of basic object features can be influenced by subliminal processing of stimuli presented beforehand. Visual masking was used to render stimuli perceptually invisible. Three experiments examined if visible and invisible primes could facilitate the subsequent feature discrimination of visible targets. The experiments differed in the kind of perceptual discrimination that participants had to make. Namely, participants were asked to discriminate visual stimuli on the basis of their form, orientation, or size. In all three experiments, we demonstrated reliable priming effects when the primes were visible but not when the primes were made invisible. Our findings underscore the importance of conscious awareness in facilitating the perceptual discrimination of basic object features. PMID:29725292

Perceptual Discrimination of Basic Object Features Is Not Facilitated When Priming Stimuli Are Prevented From Reaching Awareness by Means of Visual Masking.

PubMed

Peel, Hayden J; Sperandio, Irene; Laycock, Robin; Chouinard, Philippe A

2018-01-01

Our understanding of how form, orientation and size are processed within and outside of awareness is limited and requires further investigation. Therefore, we investigated whether or not the visual discrimination of basic object features can be influenced by subliminal processing of stimuli presented beforehand. Visual masking was used to render stimuli perceptually invisible. Three experiments examined if visible and invisible primes could facilitate the subsequent feature discrimination of visible targets. The experiments differed in the kind of perceptual discrimination that participants had to make. Namely, participants were asked to discriminate visual stimuli on the basis of their form, orientation, or size. In all three experiments, we demonstrated reliable priming effects when the primes were visible but not when the primes were made invisible. Our findings underscore the importance of conscious awareness in facilitating the perceptual discrimination of basic object features.

Fatigue properties of MA 6000E, a gamma-prime strengthened ODS alloy. [Oxide Dispersion Strengthened Ni-base alloy for gas turbine blade applications

NASA Technical Reports Server (NTRS)

Kim, Y. G.; Merrick, H. F.

1980-01-01

MA 6000E is a corrosion resistant, gamma-prime strengthened ODS alloy under development for advanced turbine blade applications. The high temperature, 1093 C, rupture strength is superior to conventional nickel-base alloys. This paper addresses the fatigue behavior of the alloy. Excellent properties are exhibited in low and high cycle fatigue and also thermal fatigue. This is attributed to a unique combination of microstructural features, i.e., a fine distribution of dispersed oxides and other nonmetallics, and the highly elongated grain structure which advantageously modify the deformation characteristics and crack initiation and propagation modes from that characteristic of conventional gamma-prime hardened superalloys.

Automatic generation of randomized trial sequences for priming experiments.

PubMed

Ihrke, Matthias; Behrendt, Jörg

2011-01-01

In most psychological experiments, a randomized presentation of successive displays is crucial for the validity of the results. For some paradigms, this is not a trivial issue because trials are interdependent, e.g., priming paradigms. We present a software that automatically generates optimized trial sequences for (negative-) priming experiments. Our implementation is based on an optimization heuristic known as genetic algorithms that allows for an intuitive interpretation due to its similarity to natural evolution. The program features a graphical user interface that allows the user to generate trial sequences and to interactively improve them. The software is based on freely available software and is released under the GNU General Public License.

A Sequence-Independent Strategy for Detection and Cloning of Circular DNA Virus Genomes by Using Multiply Primed Rolling-Circle Amplification

PubMed Central

Rector, Annabel; Tachezy, Ruth; Van Ranst, Marc

2004-01-01

The discovery of novel viruses has often been accomplished by using hybridization-based methods that necessitate the availability of a previously characterized virus genome probe or knowledge of the viral nucleotide sequence to construct consensus or degenerate PCR primers. In their natural replication cycle, certain viruses employ a rolling-circle mechanism to propagate their circular genomes, and multiply primed rolling-circle amplification (RCA) with φ29 DNA polymerase has recently been applied in the amplification of circular plasmid vectors used in cloning. We employed an isothermal RCA protocol that uses random hexamer primers to amplify the complete genomes of papillomaviruses without the need for prior knowledge of their DNA sequences. We optimized this RCA technique with extracted human papillomavirus type 16 (HPV-16) DNA from W12 cells, using a real-time quantitative PCR assay to determine amplification efficiency, and obtained a 2.4 × 104-fold increase in HPV-16 DNA concentration. We were able to clone the complete HPV-16 genome from this multiply primed RCA product. The optimized protocol was subsequently applied to a bovine fibropapillomatous wart tissue sample. Whereas no papillomavirus DNA could be detected by restriction enzyme digestion of the original sample, multiply primed RCA enabled us to obtain a sufficient amount of papillomavirus DNA for restriction enzyme analysis, cloning, and subsequent sequencing of a novel variant of bovine papillomavirus type 1. The multiply primed RCA method allows the discovery of previously unknown papillomaviruses, and possibly also other circular DNA viruses, without a priori sequence information. PMID:15113879

Multi-Level Sequential Pattern Mining Based on Prime Encoding

NASA Astrophysics Data System (ADS)

Lianglei, Sun; Yun, Li; Jiang, Yin

Encoding is not only to express the hierarchical relationship, but also to facilitate the identification of the relationship between different levels, which will directly affect the efficiency of the algorithm in the area of mining the multi-level sequential pattern. In this paper, we prove that one step of division operation can decide the parent-child relationship between different levels by using prime encoding and present PMSM algorithm and CROSS-PMSM algorithm which are based on prime encoding for mining multi-level sequential pattern and cross-level sequential pattern respectively. Experimental results show that the algorithm can effectively extract multi-level and cross-level sequential pattern from the sequence database.

Efficient brain lesion segmentation using multi-modality tissue-based feature selection and support vector machines.

PubMed

Fiot, Jean-Baptiste; Cohen, Laurent D; Raniga, Parnesh; Fripp, Jurgen

2013-09-01

Support vector machines (SVM) are machine learning techniques that have been used for segmentation and classification of medical images, including segmentation of white matter hyper-intensities (WMH). Current approaches using SVM for WMH segmentation extract features from the brain and classify these followed by complex post-processing steps to remove false positives. The method presented in this paper combines advanced pre-processing, tissue-based feature selection and SVM classification to obtain efficient and accurate WMH segmentation. Features from 125 patients, generated from up to four MR modalities [T1-w, T2-w, proton-density and fluid attenuated inversion recovery(FLAIR)], differing neighbourhood sizes and the use of multi-scale features were compared. We found that although using all four modalities gave the best overall classification (average Dice scores of 0.54  ±  0.12, 0.72  ±  0.06 and 0.82  ±  0.06 respectively for small, moderate and severe lesion loads); this was not significantly different (p = 0.50) from using just T1-w and FLAIR sequences (Dice scores of 0.52  ±  0.13, 0.71  ±  0.08 and 0.81  ±  0.07). Furthermore, there was a negligible difference between using 5 × 5 × 5 and 3 × 3 × 3 features (p = 0.93). Finally, we show that careful consideration of features and pre-processing techniques not only saves storage space and computation time but also leads to more efficient classification, which outperforms the one based on all features with post-processing. Copyright © 2013 John Wiley & Sons, Ltd.

Analysis of recovery efficiency in high-temperature aquifer thermal energy storage: a Rayleigh-based method

NASA Astrophysics Data System (ADS)

Schout, Gilian; Drijver, Benno; Gutierrez-Neri, Mariene; Schotting, Ruud

2014-01-01

High-temperature aquifer thermal energy storage (HT-ATES) is an important technique for energy conservation. A controlling factor for the economic feasibility of HT-ATES is the recovery efficiency. Due to the effects of density-driven flow (free convection), HT-ATES systems applied in permeable aquifers typically have lower recovery efficiencies than conventional (low-temperature) ATES systems. For a reliable estimation of the recovery efficiency it is, therefore, important to take the effect of density-driven flow into account. A numerical evaluation of the prime factors influencing the recovery efficiency of HT-ATES systems is presented. Sensitivity runs evaluating the effects of aquifer properties, as well as operational variables, were performed to deduce the most important factors that control the recovery efficiency. A correlation was found between the dimensionless Rayleigh number (a measure of the relative strength of free convection) and the calculated recovery efficiencies. Based on a modified Rayleigh number, two simple analytical solutions are proposed to calculate the recovery efficiency, each one covering a different range of aquifer thicknesses. The analytical solutions accurately reproduce all numerically modeled scenarios with an average error of less than 3 %. The proposed method can be of practical use when considering or designing an HT-ATES system.

Magnetron magnetic priming for rapid startup and noise reduction

NASA Astrophysics Data System (ADS)

Neculaes, Vasile Bogdan

The magnetron is a vacuum electronics crossed-field device: perpendicular electric and magnetic fields determine the electron dynamics. Compactness, efficiency and reliability make magnetrons suitable for a wide range of military and civilian applications: radar, industrial heating, plasma sources, and medical accelerators. The most ubiquitous use of magnetrons is as the microwave power source in microwave ovens, operating at 2.45 GHz and delivering about 800--1000 W. University of Michigan and several other research programs are actively pursuing the development of GW range relativistic magnetrons. This dissertation presents experimental and computational results concerning innovative techniques to improve magnetron noise, startup and mode stability. The DC-operated oven magnetron studies performed at University of Michigan opened new directions by utilizing azimuthally varying magnetic fields (magnetic priming). Magnetic priming for rapid startup in an N-cavity magnetron operating in the pi-mode is based on implementation of an axial magnetic field with N/2 azimuthal periods, to prebunch the electrons in the desired number of spokes (N/2). Experiments with magnetic priming on DC oven magnetrons using perturbing magnets added on the upper existing magnet of the magnetron showed rapid startup (pi-mode oscillation observed at low currents) and up to 35 dB noise reduction (close to the carrier and in sidebands). A complex 3-dimensional (3D) ICEPIC computational model recovered the oven magnetron magnetic priming experimental results: rapid electron prebunching due to presence of perturbing magnets, fast startup and tendency towards a lower noise state. Simulations in 6-cavity relativistic magnetrons show that ideal magnetic priming causes fast startup, rapid mode growth (with radial electron diffusion) and suppression of mode competition. A highly idealized model (planar, crossed-field, non-resonant, non-relativistic structure) using single particle dynamics showed that magnetic priming causes rapid electron prebunching, specific symmetries in the electron cloud and an orbital parametric instability (radial exponential growth).

Relatively fast! Efficiency advantages of comparative thinking.

PubMed

Mussweiler, Thomas; Epstude, Kai

2009-02-01

Comparisons are a ubiquitous process in information processing. Seven studies examine whether, how, and when comparative thinking increases the efficiency of judgment and choice. Studies 1-4 demonstrate that procedurally priming participants to engage in more vs. less comparison influences how they process information about a target. Specifically, they retrieve less information about the target (Studies 1A, 1B), think more about an information-rich standard (Study 2) about which they activate judgment-relevant information (Study 3), and use this information to compensate for missing target information (Study 4). Studies 2-5 demonstrate the ensuing efficiency advantages. Participants who are primed on comparative thinking are faster in making a target judgment (Studies 2A, 2B, 4, 5) and have more residual processing capacities for a secondary task (Study 5). Studies 6 and 7 establish two boundary conditions by demonstrating that comparative thinking holds efficiency advantages only if target and standard are partly characterized by alignable features (Study 6) that are difficult to evaluate in isolation (Study 7). These findings indicate that comparative thinking may often constitute a useful mechanism to simplify information processing. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Low-level awareness accompanies "unconscious" high-level processing during continuous flash suppression.

PubMed

Gelbard-Sagiv, Hagar; Faivre, Nathan; Mudrik, Liad; Koch, Christof

2016-01-01

The scope and limits of unconscious processing are a matter of ongoing debate. Lately, continuous flash suppression (CFS), a technique for suppressing visual stimuli, has been widely used to demonstrate surprisingly high-level processing of invisible stimuli. Yet, recent studies showed that CFS might actually allow low-level features of the stimulus to escape suppression and be consciously perceived. The influence of such low-level awareness on high-level processing might easily go unnoticed, as studies usually only probe the visibility of the feature of interest, and not that of lower-level features. For instance, face identity is held to be processed unconsciously since subjects who fail to judge the identity of suppressed faces still show identity priming effects. Here we challenge these results, showing that such high-level priming effects are indeed induced by faces whose identity is invisible, but critically, only when a lower-level feature, such as color or location, is visible. No evidence for identity processing was found when subjects had no conscious access to any feature of the suppressed face. These results suggest that high-level processing of an image might be enabled by-or co-occur with-conscious access to some of its low-level features, even when these features are not relevant to the processed dimension. Accordingly, they call for further investigation of lower-level awareness during CFS, and reevaluation of other unconscious high-level processing findings.

Optimal Non-Invasive Fault Classification Model for Packaged Ceramic Tile Quality Monitoring Using MMW Imaging

NASA Astrophysics Data System (ADS)

Agarwal, Smriti; Singh, Dharmendra

2016-04-01

Millimeter wave (MMW) frequency has emerged as an efficient tool for different stand-off imaging applications. In this paper, we have dealt with a novel MMW imaging application, i.e., non-invasive packaged goods quality estimation for industrial quality monitoring applications. An active MMW imaging radar operating at 60 GHz has been ingeniously designed for concealed fault estimation. Ceramic tiles covered with commonly used packaging cardboard were used as concealed targets for undercover fault classification. A comparison of computer vision-based state-of-the-art feature extraction techniques, viz, discrete Fourier transform (DFT), wavelet transform (WT), principal component analysis (PCA), gray level co-occurrence texture (GLCM), and histogram of oriented gradient (HOG) has been done with respect to their efficient and differentiable feature vector generation capability for undercover target fault classification. An extensive number of experiments were performed with different ceramic tile fault configurations, viz., vertical crack, horizontal crack, random crack, diagonal crack along with the non-faulty tiles. Further, an independent algorithm validation was done demonstrating classification accuracy: 80, 86.67, 73.33, and 93.33 % for DFT, WT, PCA, GLCM, and HOG feature-based artificial neural network (ANN) classifier models, respectively. Classification results show good capability for HOG feature extraction technique towards non-destructive quality inspection with appreciably low false alarm as compared to other techniques. Thereby, a robust and optimal image feature-based neural network classification model has been proposed for non-invasive, automatic fault monitoring for a financially and commercially competent industrial growth.

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

PubMed Central

Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

2016-01-01

An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

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

Rana, Vijay Kumar; Department of Chemical Technology, North Maharashtra University Jalgaon-425001; Division of Polymer Science and Engineering, National Chemical Laboratory, Pune-411 008

To achieve a high level of heavy metal adsorption, 1,1 Prime ,1 Double-Prime -(1,3,5-triazine-2,4,6-triyl)tris(3-(3-(triethoxysilyl)propyl)urea) (TTPU) was synthesized as a novel melamine precursor and incorporated on the silica surface of periodic mesoporous organosilica (PMO). The melamine modified PMOs (MPMOs) were synthesized under acidic conditions using TTPU, tetraethylorthosilicate (TEOS) and Pluronic P123 as a template and the modified PMOs were characterized using the relevant instrumental techniques. The characteristic materials were used as adsorbents for the adsorption of Fe(III) ions. Fe(III) adsorption studies revealed MPMO-7.5 to be a good absorbent with higher adsorption efficiency than other MPMOs. - Graphical Abstract: A new organosilicamore » precursor, TTPU, has been successfully synthesized and characterized to incorporate on the silica surface of periodic mesoporous organosilica (PMO). The melamine modified PMOs (MPMOs), in particular, the MPMO-7.5 was found to exhibit good adsorption efficiency for Fe(III). Highlights: Black-Right-Pointing-Pointer Synthesis of new melamine modified periodic mesoporous organosilicas (MPMOs). Black-Right-Pointing-Pointer A new organosilica precursor, TTPU, has been successfully synthesized for the MPMOs. Black-Right-Pointing-Pointer The MPMOs were characterized by the relevant instrumental techniques. Black-Right-Pointing-Pointer MPMO-7.5 exhibits higher adsorption efficiency for Fe(III) ions than other MPMOs.« less

Cathode Priming vs. RF Priming for Relativistic Magnetrons

NASA Astrophysics Data System (ADS)

White, W. M.; Spencer, T. A.; Price, D.

2005-10-01

Magnetron start-oscillation time, pulsewidth and pi-mode locking are experimentally compared for RF priming versus cathode priming on the Michigan-Titan relativistic magnetron (-300 kV, 2-10 kA, 300-500 ns). Cathode priming [1, 2] is an innovative technique first demonstrated experimentally at UM. In this technique, the cathode is fabricated with N/2 emitting strips or N/2-separate cathodes (for an N-cavity magnetron), which generate the desired number of spokes for pi-mode. Cathode priming yields 13% faster startup with more reproducible pi-mode oscillation. Radio Frequency (RF) priming is investigated as the baseline priming technique for magnetrons. The external priming source is a 100kW, 3μs pulsewidth magnetron on loan from AFRL. RF priming reduced startup delay by 15% and increased pulsewidth by 9%. [1] M.C. Jones, V.B. Neculaes, R.M. Gilgenbach, W.M. White, M.R. Lopez, Y.Y. Lau, T.A. Spencer, and D. Price, Rev. Sci. Inst., 75, 2976 (2004) [2] M.C. Jones, Doctoral Dissertation, University of Michigan, 2005

An efficient scheme for automatic web pages categorization using the support vector machine

NASA Astrophysics Data System (ADS)

Bhalla, Vinod Kumar; Kumar, Neeraj

2016-07-01

In the past few years, with an evolution of the Internet and related technologies, the number of the Internet users grows exponentially. These users demand access to relevant web pages from the Internet within fraction of seconds. To achieve this goal, there is a requirement of an efficient categorization of web page contents. Manual categorization of these billions of web pages to achieve high accuracy is a challenging task. Most of the existing techniques reported in the literature are semi-automatic. Using these techniques, higher level of accuracy cannot be achieved. To achieve these goals, this paper proposes an automatic web pages categorization into the domain category. The proposed scheme is based on the identification of specific and relevant features of the web pages. In the proposed scheme, first extraction and evaluation of features are done followed by filtering the feature set for categorization of domain web pages. A feature extraction tool based on the HTML document object model of the web page is developed in the proposed scheme. Feature extraction and weight assignment are based on the collection of domain-specific keyword list developed by considering various domain pages. Moreover, the keyword list is reduced on the basis of ids of keywords in keyword list. Also, stemming of keywords and tag text is done to achieve a higher accuracy. An extensive feature set is generated to develop a robust classification technique. The proposed scheme was evaluated using a machine learning method in combination with feature extraction and statistical analysis using support vector machine kernel as the classification tool. The results obtained confirm the effectiveness of the proposed scheme in terms of its accuracy in different categories of web pages.

Test Sequence Priming in Recognition Memory

ERIC Educational Resources Information Center

Johns, Elizabeth E.; Mewhort, D. J. K.

2009-01-01

The authors examined priming within the test sequence in 3 recognition memory experiments. A probe primed its successor whenever both probes shared a feature with the same studied item ("interjacent priming"), indicating that the study item like the probe is central to the decision. Interjacent priming occurred even when the 2 probes did…

Coaxial prime focus feeds for paraboloidal reflectors

NASA Technical Reports Server (NTRS)

Collin, R. E.; Schilling, H.; Hebert, L.

1982-01-01

A TE11 - TM11 dual mode coaxial feed for use in prime focus paraboloidal antenna systems is investigated. The scattering matrix parameters of the internal bifurcation junction was determined by the residue calculus technique. The scattering parameters and radiation fields of the aperture were found from the Weinstein solution. The optimum modeing ratio for minimum cross-polarization was determined along with the corresponding optimum feed dimensions. A peak cross-polarization level of -58 dB is predicted. The frequency characteristics were also investigated and a bandwidth of 5% is predicted over which the cross-polarization remains below -30 dB, the input VSWR is below 1.15, and the phase error is less than 10 deg. Theoretical radiation patterns and efficiency curves for a paraboloidal reflector illuminated by this feed were computed. The predicted sidelobe level is below -30 dB and aperture efficiencies greater than 70% are possible. Experimental results are also presented that substantiates the theoretical results. In addition, experimental results for a 'short-cup' coaxial feed are given. The report includes extensive design data for the dual-mode feed along with performance curves showing cross-polarization as a function of feed parameters. The feed is useful for low-cost ground based receiving antennas for use in direct television satellite broadcasting service.

The specificity and flexibility of l1 reverse transcription priming at imperfect T-tracts.

PubMed

Monot, Clément; Kuciak, Monika; Viollet, Sébastien; Mir, Ashfaq Ali; Gabus, Caroline; Darlix, Jean-Luc; Cristofari, Gaël

2013-05-01

L1 retrotransposons have a prominent role in reshaping mammalian genomes. To replicate, the L1 ribonucleoprotein particle (RNP) first uses its endonuclease (EN) to nick the genomic DNA. The newly generated DNA end is subsequently used as a primer to initiate reverse transcription within the L1 RNA poly(A) tail, a process known as target-primed reverse transcription (TPRT). Prior studies demonstrated that most L1 insertions occur into sequences related to the L1 EN consensus sequence (degenerate 5'-TTTT/A-3' sites) and frequently preceded by imperfect T-tracts. However, it is currently unclear whether--and to which degree--the liberated 3'-hydroxyl extremity on the genomic DNA needs to be accessible and complementary to the poly(A) tail of the L1 RNA for efficient priming of reverse transcription. Here, we employed a direct assay for the initiation of L1 reverse transcription to define the molecular rules that guide this process. First, efficient priming is detected with as few as 4 matching nucleotides at the primer 3' end. Second, L1 RNP can tolerate terminal mismatches if they are compensated within the 10 last bases of the primer by an increased number of matching nucleotides. All terminal mismatches are not equally detrimental to DNA extension, a C being extended at higher levels than an A or a G. Third, efficient priming in the context of duplex DNA requires a 3' overhang. This suggests the possible existence of additional DNA processing steps, which generate a single-stranded 3' end to allow L1 reverse transcription. Based on these data we propose that the specificity of L1 reverse transcription initiation contributes, together with the specificity of the initial EN cleavage, to the distribution of new L1 insertions within the human genome.

Tn5Prime, a Tn5 based 5' capture method for single cell RNA-seq.

PubMed

Cole, Charles; Byrne, Ashley; Beaudin, Anna E; Forsberg, E Camilla; Vollmers, Christopher

2018-06-01

RNA-sequencing (RNA-seq) is a powerful technique to investigate and quantify entire transcriptomes. Recent advances in the field have made it possible to explore the transcriptomes of single cells. However, most widely used RNA-seq protocols fail to provide crucial information regarding transcription start sites. Here we present a protocol, Tn5Prime, that takes advantage of the Tn5 transposase-based Smart-seq2 protocol to create RNA-seq libraries that capture the 5' end of transcripts. The Tn5Prime method dramatically streamlines the 5' capture process and is both cost effective and reliable. By applying Tn5Prime to bulk RNA and single cell samples, we were able to define transcription start sites as well as quantify transcriptomes at high accuracy and reproducibility. Additionally, similar to 3' end-based high-throughput methods like Drop-seq and 10× Genomics Chromium, the 5' capture Tn5Prime method allows the introduction of cellular identifiers during reverse transcription, simplifying the analysis of large numbers of single cells. In contrast to 3' end-based methods, Tn5Prime also enables the assembly of the variable 5' ends of the antibody sequences present in single B-cell data. Therefore, Tn5Prime presents a robust tool for both basic and applied research into the adaptive immune system and beyond.

DNA polymerase preference determines PCR priming efficiency.

PubMed

Pan, Wenjing; Byrne-Steele, Miranda; Wang, Chunlin; Lu, Stanley; Clemmons, Scott; Zahorchak, Robert J; Han, Jian

2014-01-30

Polymerase chain reaction (PCR) is one of the most important developments in modern biotechnology. However, PCR is known to introduce biases, especially during multiplex reactions. Recent studies have implicated the DNA polymerase as the primary source of bias, particularly initiation of polymerization on the template strand. In our study, amplification from a synthetic library containing a 12 nucleotide random portion was used to provide an in-depth characterization of DNA polymerase priming bias. The synthetic library was amplified with three commercially available DNA polymerases using an anchored primer with a random 3' hexamer end. After normalization, the next generation sequencing (NGS) results of the amplified libraries were directly compared to the unamplified synthetic library. Here, high throughput sequencing was used to systematically demonstrate and characterize DNA polymerase priming bias. We demonstrate that certain sequence motifs are preferred over others as primers where the six nucleotide sequences at the 3' end of the primer, as well as the sequences four base pairs downstream of the priming site, may influence priming efficiencies. DNA polymerases in the same family from two different commercial vendors prefer similar motifs, while another commercially available enzyme from a different DNA polymerase family prefers different motifs. Furthermore, the preferred priming motifs are GC-rich. The DNA polymerase preference for certain sequence motifs was verified by amplification from single-primer templates. We incorporated the observed DNA polymerase preference into a primer-design program that guides the placement of the primer to an optimal location on the template. DNA polymerase priming bias was characterized using a synthetic library amplification system and NGS. The characterization of DNA polymerase priming bias was then utilized to guide the primer-design process and demonstrate varying amplification efficiencies among three commercially available DNA polymerases. The results suggest that the interaction of the DNA polymerase with the primer:template junction during the initiation of DNA polymerization is very important in terms of overall amplification bias and has broader implications for both the primer design process and multiplex PCR.

An efficient ensemble learning method for gene microarray classification.

PubMed

Osareh, Alireza; Shadgar, Bita

2013-01-01

The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

Discriminating Induced-Microearthquakes Using New Seismic Features

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Horton, S.

2016-12-01

We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

[The cognitive paradigm in the rehabilitation of schizophrenia - focusing on cognitive remediation].

PubMed

Muth, Veronika; Gyüre, Támas; Váradi, Enikö

2015-09-01

Neurocognitive deficits are core features of schizophrenia and well known to the specialists, concerning researches in Hungary as well. Significance of the topic derives from the fact that according to our present knowledge this is the prime symptom principally affecting everyday functioning and limits benefit of rehabilitation opportunities. The classic psychiatric rehabilitation toolset, either pharmacological or psychosocial, does not provide effective and specific assistance to alleviate the symptoms of the neurocognitive deficits. Despite the increasing presence of the neurocognitive-oriented rehabilitation in international publications and professional forums, cognitive development is rather neglected topic in the Hungarian literature; while the therapeutic practice - with the exception of one institution - is absent from the repertoire of the Hungarian rehabilitation. The purpose of this study is the multi-faceted presentation of recent results in the field of the cognitive remediation, describing the position of cognitive training and its place in the rehabilitation of schizophrenia, with the aim to gain reputation and promote clinical practice among the Hungarian experts. Cognitive remediation is a behavioral training, based on learning theory, with the aim of extensive and long-lasting improvement of cognitive functions of patients suffering from schizophrenia or other mental disorders. Despite the deceptively similar acronym it is important to distinguish this method from the cognitive behavioral therapy which shows similarity in its learning theory basis, but remediation involves much more educational features. Cognitive remediation is not a unified technique, different settings are known, but regardless of form factors it clearly has a specific and positive effect on the neurocognitive functions. It fits well into the rehabilitation methodology, in fact this embeddedness significantly increases its effectiveness and supports emergence of skills in everyday functioning, helping improving disorder outcomes. The generalizing process is partly related to the fact that with the improvement of patients' neurocognitive functions, they become "more accessible" in other therapeutic modalities, increasing their efficiency. Functional and structural changes in relevant cerebral fields correlating with improving neurocognitive performance is proven by growing number of imaging techniques. In addition cost efficiency considerations also support the applicability of the method, which adaptations - in terms of cognitive paradigm - were used in other psychiatric disorders with promising results.

Conceptual framework for drought phenotyping during molecular breeding.

PubMed

Salekdeh, Ghasem Hosseini; Reynolds, Matthew; Bennett, John; Boyer, John

2009-09-01

Drought is a major threat to agricultural production and drought tolerance is a prime target for molecular approaches to crop improvement. To achieve meaningful results, these approaches must be linked with suitable phenotyping protocols at all stages, such as the screening of germplasm collections, mutant libraries, mapping populations, transgenic lines and breeding materials and the design of OMICS and quantitative trait loci (QTLs) experiments. Here we present a conceptual framework for molecular breeding for drought tolerance based on the Passioura equation of expressing yield as the product of water use (WU), water use efficiency (WUE) and harvest index (HI). We identify phenotyping protocols that address each of these factors, describe their key features and illustrate their integration with different molecular approaches.

Lossless compression techniques for maskless lithography data

NASA Astrophysics Data System (ADS)

Dai, Vito; Zakhor, Avideh

2002-07-01

Future lithography systems must produce more dense chips with smaller feature sizes, while maintaining the throughput of one wafer per sixty seconds per layer achieved by today's optical lithography systems. To achieve this throughput with a direct-write maskless lithography system, using 25 nm pixels for 50 nm feature sizes, requires data rates of about 10 Tb/s. In a previous paper, we presented an architecture which achieves this data rate contingent on consistent 25 to 1 compression of lithography data, and on implementation of a decoder-writer chip with a real-time decompressor fabricated on the same chip as the massively parallel array of lithography writers. In this paper, we examine the compression efficiency of a spectrum of techniques suitable for lithography data, including two industry standards JBIG and JPEG-LS, a wavelet based technique SPIHT, general file compression techniques ZIP and BZIP2, our own 2D-LZ technique, and a simple list-of-rectangles representation RECT. Layouts rasterized both to black-and-white pixels, and to 32 level gray pixels are considered. Based on compression efficiency, JBIG, ZIP, 2D-LZ, and BZIP2 are found to be strong candidates for application to maskless lithography data, in many cases far exceeding the required compression ratio of 25. To demonstrate the feasibility of implementing the decoder-writer chip, we consider the design of a hardware decoder based on ZIP, the simplest of the four candidate techniques. The basic algorithm behind ZIP compression is Lempel-Ziv 1977 (LZ77), and the design parameters of LZ77 decompression are optimized to minimize circuit usage while maintaining compression efficiency.

Neural network-based feature point descriptors for registration of optical and SAR images

NASA Astrophysics Data System (ADS)

Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

2018-04-01

Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

Technological advancement in electrochemical biosensor based detection of Organophosphate pesticide chlorpyrifos in the environment: A review of status and prospects.

PubMed

Uniyal, Shivani; Sharma, Rajesh Kumar

2018-09-30

Chlorpyrifos (CP), an organophosphate insecticide is broadly used in the agricultural and industrial sectors to control a broad-spectrum of insects of economically important crops. CP detection has been gaining prominence due to its widespread contamination in different environmental matrices, high acute toxicity, and potential to cause long-term environmental and ecological damage even at trace levels. Traditional chromatographic methods for CP detection are complex and require sample preparation and highly skilled personnel for their operation. Over the past decades, electrochemical biosensors have emerged as a promising technology for CP detection as these circumvent deficiencies associated with classical chromatographic techniques. The advantageous features such as appreciable detection limit, miniaturization, sensitivity, low-cost and onsite detection potential are the propulsive force towards sustainable growth of electrochemical biosensing platforms. Recent development in enzyme immobilization methods, novel surface modifications, nanotechnology and fabrication techniques signify a foremost possibility for the design of electrochemical biosensing platforms with improved sensitivity and selectivity. The prime objective of this review is to accentuate the recent advances in the design of biosensing platforms based on diverse biomolecules and biomimetic molecules with unique properties, which would potentially fascinate their applicability for detection of CP residues in real samples. The review also covers the sensing principle of the prime biomolecule and biomimetic molecule based electrochemical biosensors along with their analytical performance, advantages and shortcomings. Present challenges and future outlooks in the field of electrochemical biosensors based CP detection are also discussed. This deep analysis of electrochemical biosensors will provide research directions for further approaching towards commercial development of the broad range of organophosphorus compounds. Copyright © 2018 Elsevier B.V. All rights reserved.

Customer Churn Prediction for Broadband Internet Services

NASA Astrophysics Data System (ADS)

Huang, B. Q.; Kechadi, M.-T.; Buckley, B.

Although churn prediction has been an area of research in the voice branch of telecommunications services, more focused studies on the huge growth area of Broadband Internet services are limited. Therefore, this paper presents a new set of features for broadband Internet customer churn prediction, based on Henley segments, the broadband usage, dial types, the spend of dial-up, line-information, bill and payment information, account information. Then the four prediction techniques (Logistic Regressions, Decision Trees, Multilayer Perceptron Neural Networks and Support Vector Machines) are applied in customer churn, based on the new features. Finally, the evaluation of new features and a comparative analysis of the predictors are made for broadband customer churn prediction. The experimental results show that the new features with these four modelling techniques are efficient for customer churn prediction in the broadband service field.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Incidental Learning of S-R Contingencies in the Masked Prime Task

ERIC Educational Resources Information Center

Schlaghecken, Friederike; Blagrove, Elisabeth; Maylor, Elizabeth A.

2007-01-01

Subliminal motor priming effects in the masked prime paradigm can only be obtained when primes are part of the task set. In 2 experiments, the authors investigated whether the relevant task set feature needs to be explicitly instructed or could be extracted automatically in an incidental learning paradigm. Primes and targets were symmetrical…

Neural evidence for a multifaceted model of attachment security.

PubMed

Canterberry, Melanie; Gillath, Omri

2013-06-01

The sense of attachment security has been linked with a host of beneficial outcomes related to personal and relational well-being. Moreover, research has demonstrated that the sense of attachment security can be enhanced via cognitive priming techniques. Studies using such techniques have shown that security priming results with similar outcomes as dispositional attachment security. The way security priming leads to these effects, however, is yet to be unveiled. Using fMRI we took one step in that direction and examined the neural mechanisms underlying enhanced attachment security. Participants were exposed to explicit and implicit security- and insecurity-related words. Security priming led to co-occurring activation in brain areas reflective of cognitive, affective, and behavioral processes (e.g., medial frontal cortex, parahippocampus, BA 6). There were activation differences based on attachment style. This research serves as an important step in mapping out the security process and supports a conceptualization of security as part of a behavioral system with multiple components. Copyright © 2012 Elsevier B.V. All rights reserved.

A Solution Adaptive Technique Using Tetrahedral Unstructured Grids

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2000-01-01

An adaptive unstructured grid refinement technique has been developed and successfully applied to several three dimensional inviscid flow test cases. The method is based on a combination of surface mesh subdivision and local remeshing of the volume grid Simple functions of flow quantities are employed to detect dominant features of the flowfield The method is designed for modular coupling with various error/feature analyzers and flow solvers. Several steady-state, inviscid flow test cases are presented to demonstrate the applicability of the method for solving practical three-dimensional problems. In all cases, accurate solutions featuring complex, nonlinear flow phenomena such as shock waves and vortices have been generated automatically and efficiently.

Characterization of sub-0.18-μm critical dimension pattern collapse for yield improvement

NASA Astrophysics Data System (ADS)

Zhong, Tom X.; Gurer, Emir; Lee, Ed C.; Bai, Hong; Gendron, Bill; Krishna, Murthy S.; Reynolds, Reese M.

1999-09-01

In this study, we demonstrate that surface-resist interface interactions are becoming more crucial in DUV lithography as we enter deep into the sub-wavelength era of smaller critical dimension (CD) size and high aspect ratio. This interaction reveals itself as an adhesion reduction of the resist film due to the smaller contact area between the feature and the substrate. Considerable yield improvements in a manufacturing environment can be realized if pattern collapsing of smaller features is prevented by means of proper priming. In addition, next generation photoresist processing equipments must be able to deliver excellent on-wafer results with minimum chemical consumption as environmental health and safety (EHS) requirements are better appreciated in the marketplace. HMDS is not only highly toxic but it is also a prime threat to CD control of most deep ultra violet (DUV) photoresists used for sub-0.18 micrometer design rules. The by-product NH3 created during priming process with HMDS can neutralize the photo-acid created during the exposure step. There are many technical opportunities in this usually neglected priming process step. In this study, we characterized sub-0.18 micrometer isolated line pattern collapse for UV5 resist on bare Si wafers by using a scanning electron microscope (SEM). The smallest line width printability on wafers primed with different contact angles was analyzed by using both top down and cross section SEM images. Our results show that there is a strong effect of substrate surface and film interface interaction on device yields. More specifically, there is a strong correlation between pattern integrity of features down to 115 nm and vapor prime process conditions. In general, wafers with higher contact angle can support smaller line widths. These results suggest that higher contact angle than the current specification will be required for sub-0.1 micrometer design rule for improved yield. An alternative material to HMDS will probably be needed due to more stringent future requirements and weak bonding characteristics of HMDS. Based on the result of this study, we propose an HMDS consumption reduction scheme for line-widths above 0.2 micrometer. There are many priming-related modular and system level technical enhancements that can be designed in the next generation photoresist processing tools in order to extend 248 nm lithography towards smaller feature sizes.

A novel and efficient technique for identification and classification of GPCRs.

PubMed

Gupta, Ravi; Mittal, Ankush; Singh, Kuldip

2008-07-01

G-protein coupled receptors (GPCRs) play a vital role in different biological processes, such as regulation of growth, death, and metabolism of cells. GPCRs are the focus of significant amount of current pharmaceutical research since they interact with more than 50% of prescription drugs. The dipeptide-based support vector machine (SVM) approach is the most accurate technique to identify and classify the GPCRs. However, this approach has two major disadvantages. First, the dimension of dipeptide-based feature vector is equal to 400. The large dimension makes the classification task computationally and memory wise inefficient. Second, it does not consider the biological properties of protein sequence for identification and classification of GPCRs. In this paper, we present a novel-feature-based SVM classification technique. The novel features are derived by applying wavelet-based time series analysis approach on protein sequences. The proposed feature space summarizes the variance information of seven important biological properties of amino acids in a protein sequence. In addition, the dimension of the feature vector for proposed technique is equal to 35. Experiments were performed on GPCRs protein sequences available at GPCRs Database. Our approach achieves an accuracy of 99.9%, 98.06%, 97.78%, and 94.08% for GPCR superfamily, families, subfamilies, and subsubfamilies (amine group), respectively, when evaluated using fivefold cross-validation. Further, an accuracy of 99.8%, 97.26%, and 97.84% was obtained when evaluated on unseen or recall datasets of GPCR superfamily, families, and subfamilies, respectively. Comparison with dipeptide-based SVM technique shows the effectiveness of our approach.

Associative and repetition priming with the repeated masked prime technique: no priming found.

PubMed

Avons, S E; Russo, Riccardo; Cinel, Caterina; Verolini, Veronica; Glynn, Kevin; McDonald, Rebecca; Cameron, Marie

2009-01-01

Wentura and Frings (2005) reported evidence of subliminal categorical priming on a lexical decision task, using a new method of visual masking in which the prime string consisted of the prime word flanked by random consonants and random letter masks alternated with the prime string on successive refresh cycles. We investigated associative and repetition priming on lexical decision, using the same method of visual masking. Three experiments failed to show any evidence of associative priming, (1) when the prime string was fixed at 10 characters (three to six flanking letters) and (2) when the number of flanking letters were reduced or absent. In all cases, prime detection was at chance level. Strong associative priming was observed with visible unmasked primes, but the addition of flanking letters restricted priming even though prime detection was still high. With repetition priming, no priming effects were found with the repeated masked technique, and prime detection was poor but just above chance levels. We conclude that with repeated masked primes, there is effective visual masking but that associative priming and repetition priming do not occur with experiment-unique prime-target pairs. Explanations for this apparent discrepancy across priming paradigms are discussed. The priming stimuli and prime-target pairs used in this study may be downloaded as supplemental materials from mc.psychonomic-journals.org/content/supplemental.

Principal axes estimation using the vibration modes of physics-based deformable models.

PubMed

Krinidis, Stelios; Chatzis, Vassilios

2008-06-01

This paper addresses the issue of accurate, effective, computationally efficient, fast, and fully automated 2-D object orientation and scaling factor estimation. The object orientation is calculated using object principal axes estimation. The approach relies on the object's frequency-based features. The frequency-based features used by the proposed technique are extracted by a 2-D physics-based deformable model that parameterizes the objects shape. The method was evaluated on synthetic and real images. The experimental results demonstrate the accuracy of the method, both in orientation and the scaling estimations.

g-PRIME: A Free, Windows Based Data Acquisition and Event Analysis Software Package for Physiology in Classrooms and Research Labs.

PubMed

Lott, Gus K; Johnson, Bruce R; Bonow, Robert H; Land, Bruce R; Hoy, Ronald R

2009-01-01

We present g-PRIME, a software based tool for physiology data acquisition, analysis, and stimulus generation in education and research. This software was developed in an undergraduate neurophysiology course and strongly influenced by instructor and student feedback. g-PRIME is a free, stand-alone, windows application coded and "compiled" in Matlab (does not require a Matlab license). g-PRIME supports many data acquisition interfaces from the PC sound card to expensive high throughput calibrated equipment. The program is designed as a software oscilloscope with standard trigger modes, multi-channel visualization controls, and data logging features. Extensive analysis options allow real time and offline filtering of signals, multi-parameter threshold-and-window based event detection, and two-dimensional display of a variety of parameters including event time, energy density, maximum FFT frequency component, max/min amplitudes, and inter-event rate and intervals. The software also correlates detected events with another simultaneously acquired source (event triggered average) in real time or offline. g-PRIME supports parameter histogram production and a variety of elegant publication quality graphics outputs. A major goal of this software is to merge powerful engineering acquisition and analysis tools with a biological approach to studies of nervous system function.

Discrimination in lexical decision

PubMed Central

Feldman, Laurie Beth; Ramscar, Michael; Hendrix, Peter; Baayen, R. Harald

2017-01-01

In this study we present a novel set of discrimination-based indicators of language processing derived from Naive Discriminative Learning (ndl) theory. We compare the effectiveness of these new measures with classical lexical-distributional measures—in particular, frequency counts and form similarity measures—to predict lexical decision latencies when a complete morphological segmentation of masked primes is or is not possible. Data derive from a re-analysis of a large subset of decision latencies from the English Lexicon Project, as well as from the results of two new masked priming studies. Results demonstrate the superiority of discrimination-based predictors over lexical-distributional predictors alone, across both the simple and primed lexical decision tasks. Comparable priming after masked corner and cornea type primes, across two experiments, fails to support early obligatory segmentation into morphemes as predicted by the morpho-orthographic account of reading. Results fit well with ndl theory, which, in conformity with Word and Paradigm theory, rejects the morpheme as a relevant unit of analysis. Furthermore, results indicate that readers with greater spelling proficiency and larger vocabularies make better use of orthographic priors and handle lexical competition more efficiently. PMID:28235015

Discrimination in lexical decision.

PubMed

Milin, Petar; Feldman, Laurie Beth; Ramscar, Michael; Hendrix, Peter; Baayen, R Harald

2017-01-01

In this study we present a novel set of discrimination-based indicators of language processing derived from Naive Discriminative Learning (ndl) theory. We compare the effectiveness of these new measures with classical lexical-distributional measures-in particular, frequency counts and form similarity measures-to predict lexical decision latencies when a complete morphological segmentation of masked primes is or is not possible. Data derive from a re-analysis of a large subset of decision latencies from the English Lexicon Project, as well as from the results of two new masked priming studies. Results demonstrate the superiority of discrimination-based predictors over lexical-distributional predictors alone, across both the simple and primed lexical decision tasks. Comparable priming after masked corner and cornea type primes, across two experiments, fails to support early obligatory segmentation into morphemes as predicted by the morpho-orthographic account of reading. Results fit well with ndl theory, which, in conformity with Word and Paradigm theory, rejects the morpheme as a relevant unit of analysis. Furthermore, results indicate that readers with greater spelling proficiency and larger vocabularies make better use of orthographic priors and handle lexical competition more efficiently.

Efficient and robust model-to-image alignment using 3D scale-invariant features.

PubMed

Toews, Matthew; Wells, William M

2013-04-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

Efficient and Robust Model-to-Image Alignment using 3D Scale-Invariant Features

PubMed Central

Toews, Matthew; Wells, William M.

2013-01-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a-posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. PMID:23265799

RF Priming Experiments and Simulations of Magnetic Priming in Relativistic Magnetrons

NASA Astrophysics Data System (ADS)

White, W. M.; Gilgenbach, R. M.; Jones, M. C.; Neculaes, V. B.; Lau, Y. Y.; Jordan, N.; Pengvanich, P.; Edgar, R.; Hoff, B.; Spencer, T. A.; Price, D.

2004-11-01

We investigate 2 priming techniques in relativistic magnetrons for rapid startup and mode-locking: RF priming experiments with 0.1-1 MW from a 2nd magnetron; Magnetic-priming simulations by azimuthally-varying-axial magnetic field. Experiments utilize MELBA-C with a Titan 6-vane magnetron: V = -300kV, I = 1-10kA, e-beam T = 0.5 μs, microwave power = 100-500 MW, f= 1-1.3 GHz, base vacuum= 8.5 x 10-10 Torr. The AFRL RF priming magnetron is at 0.1-2 MW, 3 μsec, 1.27-1.32 GHz. About 0.2-0.3 MW is injected into 1 of 3 open coupling slots in the relativistic magnetron. Analysis of the relativistic magnetron's microwave output shows a clear effect of RF priming. Simulations of magnetic priming in the pi-mode are run in MAGIC code by imposing N/2 azimuthal-variations in the axial magnetic field of an N-vane magnetron. Faster startup and mode-locking are simulated by rapid-electron spoke formation and excitation of RF fields.

CARSVM: a class association rule-based classification framework and its application to gene expression data.

PubMed

Kianmehr, Keivan; Alhajj, Reda

2008-09-01

In this study, we aim at building a classification framework, namely the CARSVM model, which integrates association rule mining and support vector machine (SVM). The goal is to benefit from advantages of both, the discriminative knowledge represented by class association rules and the classification power of the SVM algorithm, to construct an efficient and accurate classifier model that improves the interpretability problem of SVM as a traditional machine learning technique and overcomes the efficiency issues of associative classification algorithms. In our proposed framework: instead of using the original training set, a set of rule-based feature vectors, which are generated based on the discriminative ability of class association rules over the training samples, are presented to the learning component of the SVM algorithm. We show that rule-based feature vectors present a high-qualified source of discrimination knowledge that can impact substantially the prediction power of SVM and associative classification techniques. They provide users with more conveniences in terms of understandability and interpretability as well. We have used four datasets from UCI ML repository to evaluate the performance of the developed system in comparison with five well-known existing classification methods. Because of the importance and popularity of gene expression analysis as real world application of the classification model, we present an extension of CARSVM combined with feature selection to be applied to gene expression data. Then, we describe how this combination will provide biologists with an efficient and understandable classifier model. The reported test results and their biological interpretation demonstrate the applicability, efficiency and effectiveness of the proposed model. From the results, it can be concluded that a considerable increase in classification accuracy can be obtained when the rule-based feature vectors are integrated in the learning process of the SVM algorithm. In the context of applicability, according to the results obtained from gene expression analysis, we can conclude that the CARSVM system can be utilized in a variety of real world applications with some adjustments.

Reading a standing wave: figure-ground-alternation masking of primes in evaluative priming.

PubMed

Bermeitinger, Christina; Kuhlmann, Michael; Wentura, Dirk

2012-09-01

We propose a new masking technique for masking word stimuli. Drawing on the phenomena of metacontrast and paracontrast, we alternately presented two prime displays of the same word with the background color in one display matching the font color in the other display and vice versa. The sequence of twenty alterations (spanning approx. 267 ms) was sandwich-masked by structure masks. Using this masking technique, we conducted evaluative priming experiments with positive and negative target and prime words. Significant priming effects were found - for primes and targets drawn from the same as well as from different word sets. Priming effects were independent of prime discrimination performance in direct tests and they were still significant after the sample was restricted to those participants who showed random responding in the direct test. Copyright © 2012 Elsevier Inc. All rights reserved.

Edge enhancement and noise suppression for infrared image based on feature analysis

NASA Astrophysics Data System (ADS)

Jiang, Meng

2018-06-01

Infrared images are often suffering from background noise, blurred edges, few details and low signal-to-noise ratios. To improve infrared image quality, it is essential to suppress noise and enhance edges simultaneously. To realize it in this paper, we propose a novel algorithm based on feature analysis in shearlet domain. Firstly, as one of multi-scale geometric analysis (MGA), we introduce the theory and superiority of shearlet transform. Secondly, after analyzing the defects of traditional thresholding technique to suppress noise, we propose a novel feature extraction distinguishing image structures from noise well and use it to improve the traditional thresholding technique. Thirdly, with computing the correlations between neighboring shearlet coefficients, the feature attribute maps identifying the weak detail and strong edges are completed to improve the generalized unsharped masking (GUM). At last, experiment results with infrared images captured in different scenes demonstrate that the proposed algorithm suppresses noise efficiently and enhances image edges adaptively.

Attachment priming and avoidant personality features as predictors of social-evaluation biases.

PubMed

Bowles, David P; Meyer, Björn

2008-02-01

Personality research has shown that negativity in social situations (e.g., negative evaluations of others) can be reduced by the activation of participants' sense of attachment security. Individuals with avoidant personality disorder (APD), however, are theoretically less responsive to context or situational cues because of the inflexible nature of their personality disposition. This idea of individual differences in context-responsiveness was tested in a sample of 169 undergraduates who were assessed for APD features and assigned to positive, negative, or neutral attachment priming conditions. More pronounced APD features were associated with more negative responses to vignettes describing potentially distressing social situations. A significant interaction showed that participants with more avoidant features consistently appraised the vignettes relatively more negatively, regardless of priming condition. Those without APD features, by contrast, did not exhibit negative appraisals/evaluations unless negatively primed (curvilinear effect). This effect could not be explained by depression, current mood, or attachment insecurity, all of which related to negative evaluative biases, but none of which related to situation inflexibility. These findings provide empirical support for the notion that negative information-processing is unusually inflexible and context-unresponsive among individuals with more pronounced features of APD.

Ventromedial Frontal Cortex Is Critical for Guiding Attention to Reward-Predictive Visual Features in Humans.

PubMed

Vaidya, Avinash R; Fellows, Lesley K

2015-09-16

Adaptively interacting with our environment requires extracting information that will allow us to successfully predict reward. This can be a challenge, particularly when there are many candidate cues, and when rewards are probabilistic. Recent work has demonstrated that visual attention is allocated to stimulus features that have been associated with reward on previous trials. The ventromedial frontal lobe (VMF) has been implicated in learning in dynamic environments of this kind, but the mechanism by which this region influences this process is not clear. Here, we hypothesized that the VMF plays a critical role in guiding attention to reward-predictive stimulus features based on feedback. We tested the effects of VMF damage in human subjects on a visual search task in which subjects were primed to attend to task-irrelevant colors associated with different levels of reward, incidental to the search task. Consistent with previous work, we found that distractors had a greater influence on reaction time when they appeared in colors associated with high reward in the previous trial compared with colors associated with low reward in healthy control subjects and patients with prefrontal damage sparing the VMF. However, this reward modulation of attentional priming was absent in patients with VMF damage. Thus, an intact VMF is necessary for directing attention based on experience with cue-reward associations. We suggest that this region plays a role in selecting reward-predictive cues to facilitate future learning. There has been a swell of interest recently in the ventromedial frontal cortex (VMF), a brain region critical to associative learning. However, the underlying mechanism by which this region guides learning is not well understood. Here, we tested the effects of damage to this region in humans on a task in which rewards were linked incidentally to visual features, resulting in trial-by-trial attentional priming. Controls and subjects with prefrontal damage sparing the VMF showed normal reward priming, but VMF-damaged patients did not. This work sheds light on a potential mechanism through which this region influences behavior. We suggest that the VMF is necessary for directing attention to reward-predictive visual features based on feedback, facilitating future learning and decision-making. Copyright © 2015 the authors 0270-6474/15/3512813-11$15.00/0.

Development of a filter regeneration system for advanced spacecraft fluid systems

NASA Technical Reports Server (NTRS)

Behrend, A. F., Jr.; Descamp, V. A.

1974-01-01

The development of a filter regeneration system for efficiently cleaning fluid particulate filters is presented. Based on a backflush/jet impingement technique, the regeneration system demonstrated a cleaning efficiency of 98.7 to 100%. The operating principles and design features are discussed with emphasis on the primary system components that include a regenerable filter, vortex particle separator, and zero-g particle trap. Techniques and equipment used for ground and zero-g performance tests are described. Test results and conclusions, as well as possible areas for commercial application, are included.

The role of expression and race in weapons identification.

PubMed

Kubota, Jennifer T; Ito, Tiffany A

2014-12-01

Emotional expressions can signal intentions and so possess the power to moderate social inferences. Here, we test whether stereotypes implicitly elicited by a stigmatized racial outgroup member are moderated by facial expression. Participants classified pictures of guns and tools that were primed with pictures of Black and White male faces posing angry, happy, and neutral expressions. Across the 3 measures examined--response latencies, error rates, and automatic processing, facial expression modulated implicit stereotyping (Study 1, n = 71; Study 2, n = 166). A Black angry prime elicited implicit stereotyping, while a Black happy prime diminished implicit stereotyping. Responding after neutral primes varied as a function of the expression context. When viewed alongside more threatening expressions (Study 1), neutral Black targets no longer elicited implicit stereotyping, but when viewed alongside more threatening expressions (Study 2), neutral Black targets primed crime and danger-relevant stereotypes. These results demonstrate that an individual can activate different associations based on changes in emotional expression and that a feature present in many everyday encounters (a smile) attenuates implicit racial stereotyping.

Theoretical performance of plasma driven railguns

NASA Astrophysics Data System (ADS)

Thio, Y. C.; McNab, I. R.; Condit, W. C.

1983-07-01

The overall efficiency of a railgun launch system is the product of efficiencies of its subsystems: prime mover, energy storage, pulse forming network, and accelerator. In this paper, the efficiency of the accelerator is examined in terms of the processes occurring in the accelerator. The principal loss mechanisms include Joule heating in the plasma, in the rails, kinetic energy of the driving plasma and magnetic energy remaining in the accelerator after projectile exit. The mass of the plasma and the atomic weight of the ionic species are important parameters in determining the energy loss in the plasma. Techniques are developed for selecting these parameters of minimize this loss.

Near-infrared spectral image analysis of pork marbling based on Gabor filter and wide line detector techniques.

PubMed

Huang, Hui; Liu, Li; Ngadi, Michael O; Gariépy, Claude; Prasher, Shiv O

2014-01-01

Marbling is an important quality attribute of pork. Detection of pork marbling usually involves subjective scoring, which raises the efficiency costs to the processor. In this study, the ability to predict pork marbling using near-infrared (NIR) hyperspectral imaging (900-1700 nm) and the proper image processing techniques were studied. Near-infrared images were collected from pork after marbling evaluation according to current standard chart from the National Pork Producers Council. Image analysis techniques-Gabor filter, wide line detector, and spectral averaging-were applied to extract texture, line, and spectral features, respectively, from NIR images of pork. Samples were grouped into calibration and validation sets. Wavelength selection was performed on calibration set by stepwise regression procedure. Prediction models of pork marbling scores were built using multiple linear regressions based on derivatives of mean spectra and line features at key wavelengths. The results showed that the derivatives of both texture and spectral features produced good results, with correlation coefficients of validation of 0.90 and 0.86, respectively, using wavelengths of 961, 1186, and 1220 nm. The results revealed the great potential of the Gabor filter for analyzing NIR images of pork for the effective and efficient objective evaluation of pork marbling.

Reliable Early Classification on Multivariate Time Series with Numerical and Categorical Attributes

DTIC Science & Technology

2015-05-22

design a procedure of feature extraction in REACT named MEG (Mining Equivalence classes with shapelet Generators) based on the concept of...Equivalence Classes Mining [12, 15]. MEG can efficiently and effectively generate the discriminative features. In addition, several strategies are proposed...technique of parallel computing [4] to propose a process of pa- rallel MEG for substantially reducing the computational overhead of discovering shapelet

NASA-NIAC 2001 Phase I Research Grant on Aneutronic Fusion Spacecraft Architecture

NASA Technical Reports Server (NTRS)

Tarditi, Alfonso G. (Principal Investigator); Scott, John H.; Miley, George H.

2012-01-01

This study was developed because the recognized need of defining of a new spacecraft architecture suitable for aneutronic fusion and featuring game-changing space travel capabilities. The core of this architecture is the definition of a new kind of fusion-based space propulsion system. This research is not about exploring a new fusion energy concept, it actually assumes the availability of an aneutronic fusion energy reactor. The focus is on providing the best (most efficient) utilization of fusion energy for propulsion purposes. The rationale is that without a proper architecture design even the utilization of a fusion reactor as a prime energy source for spacecraft propulsion is not going to provide the required performances for achieving a substantial change of current space travel capabilities.

On the Automaticity of the Evaluative Priming Effect in the Valent/Non-Valent Categorization Task

PubMed Central

Spruyt, Adriaan; Tibboel, Helen

2015-01-01

It has previously been argued (a) that automatic evaluative stimulus processing is critically dependent upon feature-specific attention allocation and (b) that evaluative priming effects can arise in the absence of dimensional overlap between the prime set and the response set. In line with both claims, research conducted at our lab revealed that the evaluative priming effect replicates in the valent/non-valent categorization task. This research was criticized, however, because non-automatic, strategic processes may have contributed to the emergence of this effect. We now report the results of a replication study in which the operation of non-automatic, strategic processes was controlled for. A clear-cut evaluative priming effect emerged, thus supporting initial claims concerning feature-specific attention allocation and dimensional overlap. PMID:25803444

On the automaticity of the evaluative priming effect in the valent/non-valent categorization task.

PubMed

Spruyt, Adriaan; Tibboel, Helen

2015-01-01

It has previously been argued (a) that automatic evaluative stimulus processing is critically dependent upon feature-specific attention allocation and (b) that evaluative priming effects can arise in the absence of dimensional overlap between the prime set and the response set. In line with both claims, research conducted at our lab revealed that the evaluative priming effect replicates in the valent/non-valent categorization task. This research was criticized, however, because non-automatic, strategic processes may have contributed to the emergence of this effect. We now report the results of a replication study in which the operation of non-automatic, strategic processes was controlled for. A clear-cut evaluative priming effect emerged, thus supporting initial claims concerning feature-specific attention allocation and dimensional overlap.

Increasing energy efficiency level of building production based on applying modern mechanization facilities

NASA Astrophysics Data System (ADS)

Prokhorov, Sergey

2017-10-01

Building industry in a present day going through the hard times. Machine and mechanism exploitation cost, on a field of construction and installation works, takes a substantial part in total building construction expenses. There is a necessity to elaborate high efficient method, which allows not only to increase production, but also to reduce direct costs during machine fleet exploitation, and to increase its energy efficiency. In order to achieve the goal we plan to use modern methods of work production, hi-tech and energy saving machine tools and technologies, and use of optimal mechanization sets. As the optimization criteria there are exploitation prime cost and set efficiency. During actual task-solving process we made a conclusion, which shows that mechanization works, energy audit with production juxtaposition, prime prices and costs for energy resources allow to make complex machine fleet supply, improve ecological level and increase construction and installation work quality.

Content Based Image Retrieval by Using Color Descriptor and Discrete Wavelet Transform.

PubMed

Ashraf, Rehan; Ahmed, Mudassar; Jabbar, Sohail; Khalid, Shehzad; Ahmad, Awais; Din, Sadia; Jeon, Gwangil

2018-01-25

Due to recent development in technology, the complexity of multimedia is significantly increased and the retrieval of similar multimedia content is a open research problem. Content-Based Image Retrieval (CBIR) is a process that provides a framework for image search and low-level visual features are commonly used to retrieve the images from the image database. The basic requirement in any image retrieval process is to sort the images with a close similarity in term of visually appearance. The color, shape and texture are the examples of low-level image features. The feature plays a significant role in image processing. The powerful representation of an image is known as feature vector and feature extraction techniques are applied to get features that will be useful in classifying and recognition of images. As features define the behavior of an image, they show its place in terms of storage taken, efficiency in classification and obviously in time consumption also. In this paper, we are going to discuss various types of features, feature extraction techniques and explaining in what scenario, which features extraction technique will be better. The effectiveness of the CBIR approach is fundamentally based on feature extraction. In image processing errands like object recognition and image retrieval feature descriptor is an immense among the most essential step. The main idea of CBIR is that it can search related images to an image passed as query from a dataset got by using distance metrics. The proposed method is explained for image retrieval constructed on YCbCr color with canny edge histogram and discrete wavelet transform. The combination of edge of histogram and discrete wavelet transform increase the performance of image retrieval framework for content based search. The execution of different wavelets is additionally contrasted with discover the suitability of specific wavelet work for image retrieval. The proposed algorithm is prepared and tried to implement for Wang image database. For Image Retrieval Purpose, Artificial Neural Networks (ANN) is used and applied on standard dataset in CBIR domain. The execution of the recommended descriptors is assessed by computing both Precision and Recall values and compared with different other proposed methods with demonstrate the predominance of our method. The efficiency and effectiveness of the proposed approach outperforms the existing research in term of average precision and recall values.

Analysis to feature-based video stabilization/registration techniques within application of traffic data collection

NASA Astrophysics Data System (ADS)

Sadat, Mojtaba T.; Viti, Francesco

2015-02-01

Machine vision is rapidly gaining popularity in the field of Intelligent Transportation Systems. In particular, advantages are foreseen by the exploitation of Aerial Vehicles (AV) in delivering a superior view on traffic phenomena. However, vibration on AVs makes it difficult to extract moving objects on the ground. To partly overcome this issue, image stabilization/registration procedures are adopted to correct and stitch multiple frames taken of the same scene but from different positions, angles, or sensors. In this study, we examine the impact of multiple feature-based techniques for stabilization, and we show that SURF detector outperforms the others in terms of time efficiency and output similarity.

Inverse target- and cue-priming effects of masked stimuli.

PubMed

Mattler, Uwe

2007-02-01

The processing of a visual target that follows a briefly presented prime stimulus can be facilitated if prime and target stimuli are similar. In contrast to these positive priming effects, inverse priming effects (or negative compatibility effects) have been found when a mask follows prime stimuli before the target stimulus is presented: Responses are facilitated after dissimilar primes. Previous studies on inverse priming effects examined target-priming effects, which arise when the prime and the target stimuli share features that are critical for the response decision. In contrast, 3 experiments of the present study demonstrate inverse priming effects in a nonmotor cue-priming paradigm. Inverse cue-priming effects exhibited time courses comparable to inverse target-priming effects. Results suggest that inverse priming effects do not arise from specific processes of the response system but follow from operations that are more general.

Efficient random access high resolution region-of-interest (ROI) image retrieval using backward coding of wavelet trees (BCWT)

NASA Astrophysics Data System (ADS)

Corona, Enrique; Nutter, Brian; Mitra, Sunanda; Guo, Jiangling; Karp, Tanja

2008-03-01

Efficient retrieval of high quality Regions-Of-Interest (ROI) from high resolution medical images is essential for reliable interpretation and accurate diagnosis. Random access to high quality ROI from codestreams is becoming an essential feature in many still image compression applications, particularly in viewing diseased areas from large medical images. This feature is easier to implement in block based codecs because of the inherent spatial independency of the code blocks. This independency implies that the decoding order of the blocks is unimportant as long as the position for each is properly identified. In contrast, wavelet-tree based codecs naturally use some interdependency that exploits the decaying spectrum model of the wavelet coefficients. Thus one must keep track of the decoding order from level to level with such codecs. We have developed an innovative multi-rate image subband coding scheme using "Backward Coding of Wavelet Trees (BCWT)" which is fast, memory efficient, and resolution scalable. It offers far less complexity than many other existing codecs including both, wavelet-tree, and block based algorithms. The ROI feature in BCWT is implemented through a transcoder stage that generates a new BCWT codestream containing only the information associated with the user-defined ROI. This paper presents an efficient technique that locates a particular ROI within the BCWT coded domain, and decodes it back to the spatial domain. This technique allows better access and proper identification of pathologies in high resolution images since only a small fraction of the codestream is required to be transmitted and analyzed.

Visual Processing in Rapid-Chase Systems: Image Processing, Attention, and Awareness

PubMed Central

Schmidt, Thomas; Haberkamp, Anke; Veltkamp, G. Marina; Weber, Andreas; Seydell-Greenwald, Anna; Schmidt, Filipp

2011-01-01

Visual stimuli can be classified so rapidly that their analysis may be based on a single sweep of feedforward processing through the visuomotor system. Behavioral criteria for feedforward processing can be evaluated in response priming tasks where speeded pointing or keypress responses are performed toward target stimuli which are preceded by prime stimuli. We apply this method to several classes of complex stimuli. (1) When participants classify natural images into animals or non-animals, the time course of their pointing responses indicates that prime and target signals remain strictly sequential throughout all processing stages, meeting stringent behavioral criteria for feedforward processing (rapid-chase criteria). (2) Such priming effects are boosted by selective visual attention for positions, shapes, and colors, in a way consistent with bottom-up enhancement of visuomotor processing, even when primes cannot be consciously identified. (3) Speeded processing of phobic images is observed in participants specifically fearful of spiders or snakes, suggesting enhancement of feedforward processing by long-term perceptual learning. (4) When the perceived brightness of primes in complex displays is altered by means of illumination or transparency illusions, priming effects in speeded keypress responses can systematically contradict subjective brightness judgments, such that one prime appears brighter than the other but activates motor responses as if it was darker. We propose that response priming captures the output of the first feedforward pass of visual signals through the visuomotor system, and that this output lacks some characteristic features of more elaborate, recurrent processing. This way, visuomotor measures may become dissociated from several aspects of conscious vision. We argue that “fast” visuomotor measures predominantly driven by feedforward processing should supplement “slow” psychophysical measures predominantly based on visual awareness. PMID:21811484

The Specificity and Flexibility of L1 Reverse Transcription Priming at Imperfect T-Tracts

PubMed Central

Viollet, Sébastien; Mir, Ashfaq Ali; Gabus, Caroline; Darlix, Jean-Luc; Cristofari, Gaël

2013-01-01

L1 retrotransposons have a prominent role in reshaping mammalian genomes. To replicate, the L1 ribonucleoprotein particle (RNP) first uses its endonuclease (EN) to nick the genomic DNA. The newly generated DNA end is subsequently used as a primer to initiate reverse transcription within the L1 RNA poly(A) tail, a process known as target-primed reverse transcription (TPRT). Prior studies demonstrated that most L1 insertions occur into sequences related to the L1 EN consensus sequence (degenerate 5′-TTTT/A-3′ sites) and frequently preceded by imperfect T-tracts. However, it is currently unclear whether—and to which degree—the liberated 3′-hydroxyl extremity on the genomic DNA needs to be accessible and complementary to the poly(A) tail of the L1 RNA for efficient priming of reverse transcription. Here, we employed a direct assay for the initiation of L1 reverse transcription to define the molecular rules that guide this process. First, efficient priming is detected with as few as 4 matching nucleotides at the primer 3′ end. Second, L1 RNP can tolerate terminal mismatches if they are compensated within the 10 last bases of the primer by an increased number of matching nucleotides. All terminal mismatches are not equally detrimental to DNA extension, a C being extended at higher levels than an A or a G. Third, efficient priming in the context of duplex DNA requires a 3′ overhang. This suggests the possible existence of additional DNA processing steps, which generate a single-stranded 3′ end to allow L1 reverse transcription. Based on these data we propose that the specificity of L1 reverse transcription initiation contributes, together with the specificity of the initial EN cleavage, to the distribution of new L1 insertions within the human genome. PMID:23675310

Is goal-directed attentional guidance just intertrial priming? A review.

PubMed

Lamy, Dominique F; Kristjánsson, Arni

2013-07-01

According to most models of selective visual attention, our goals at any given moment and saliency in the visual field determine attentional priority. But selection is not carried out in isolation--we typically track objects through space and time. This is not well captured within the distinction between goal-directed and saliency-based attentional guidance. Recent studies have shown that selection is strongly facilitated when the characteristics of the objects to be attended and of those to be ignored remain constant between consecutive selections. These studies have generated the proposal that goal-directed or top-down effects are best understood as intertrial priming effects. Here, we provide a detailed overview and critical appraisal of the arguments, experimental strategies, and findings that have been used to promote this idea, along with a review of studies providing potential counterarguments. We divide this review according to different types of attentional control settings that observers are thought to adopt during visual search: feature-based settings, dimension-based settings, and singleton detection mode. We conclude that priming accounts for considerable portions of effects attributed to top-down guidance, but that top-down guidance can be independent of intertrial priming.

Unconscious semantic activation depends on feature-specific attention allocation.

PubMed

Spruyt, Adriaan; De Houwer, Jan; Everaert, Tom; Hermans, Dirk

2012-01-01

We examined whether semantic activation by subliminally presented stimuli is dependent upon the extent to which participants assign attention to specific semantic stimulus features and stimulus dimensions. Participants pronounced visible target words that were preceded by briefly presented, masked prime words. Both affective and non-affective semantic congruence of the prime-target pairs were manipulated under conditions that either promoted selective attention for affective stimulus information or selective attention for non-affective semantic stimulus information. In line with our predictions, results showed that affective congruence had a clear impact on word pronunciation latencies only if participants were encouraged to assign attention to the affective stimulus dimension. In contrast, non-affective semantic relatedness of the prime-target pairs produced no priming at all. Our findings are consistent with the hypothesis that unconscious activation of (affective) semantic information is modulated by feature-specific attention allocation. Copyright © 2011 Elsevier B.V. All rights reserved.

Exploring the impact of visual and movement based priming on a motor intervention in the acute phase post-stroke in persons with severe hemiparesis of the upper extremity

PubMed Central

Patel, Jigna; Qiu, Qinyin; Yarossi, Mathew; Merians, Alma; Massood, Supriya; Tunik, Eugene; Adamovich, Sergei; Fluet, Gerard

2016-01-01

Purpose Explore the potential benefits of using priming methods prior to an active hand task in the acute phase post-stroke in persons with severe upper extremity hemiparesis. Methods Five individuals were trained using priming techniques including virtual reality (VR) based visual mirror feedback and contralaterally controlled passive movement strategies prior to training with an active pinch force modulation task. Clinical, kinetic, and neurophysiological measurements were taken pre and post the training period. Clinical measures were taken at six months post training. Results The two priming simulations and active training were well tolerated early after stroke. Priming effects were suggested by increased maximal pinch force immediately after visual and movement based priming. Despite having no clinically observable movement distally, the subjects were able to volitionally coordinate isometric force and muscle activity (EMG) in a pinch tracing task. The Root Mean Square Error (RMSE) of force during the pinch trace task gradually decreased over the training period suggesting learning may have occurred. Changes in motor cortical neurophysiology were seen in the unaffected hemisphere using Transcranial Magnetic Stimulation (TMS) mapping. Significant improvements in motor recovery as measured by the Action Research Arm Test (ARAT) and the Upper Extremity Fugl Meyer Assessment (UEFMA) were demonstrated at six months post training by three of the five subjects. Conclusion This study suggests that an early hand-based intervention using visual and movement based priming activities and a scaled motor task allows participation by persons without the motor control required for traditionally presented rehabilitation and testing. PMID:27636200

Positive Affective Priming: A Behavioral Technique to Facilitate Therapeutic Engagement by Families, Caregivers, and Teachers

ERIC Educational Resources Information Center

Evans, Ian M.

2010-01-01

Affective priming is a technique used in experimental psychology to investigate the organization of emotional schemata not fully available to conscious awareness. The presentation of stimuli (the prime) with strong positive emotional valence alters the accessibility of positive stimuli within the individual's emotionally encoded cognitive system.…

The Effects of Feature-Based Priming and Visual Working Memory on Oculomotor Capture.

PubMed

Silvis, Jeroen D; Belopolsky, Artem V; Murris, Jozua W I; Donk, Mieke

2015-01-01

Recently, it has been demonstrated that objects held in working memory can influence rapid oculomotor selection. This has been taken as evidence that perceptual salience can be modified by active working memory representations. The goal of the present study was to examine whether these results could also be caused by feature-based priming. In two experiments, participants were asked to saccade to a target line segment of a certain orientation that was presented together with a to-be-ignored distractor. Both objects were given a task-irrelevant color that varied per trial. In a secondary task, a color had to be memorized, and that color could either match the color of the target, match the color of the distractor, or it did not match the color of any of the objects in the search task. The memory task was completed either after the search task (Experiment 1), or before it (Experiment 2). The results showed that in both experiments the memorized color biased oculomotor selection. Eye movements were more frequently drawn towards objects that matched the memorized color, irrespective of whether the memory task was completed after (Experiment 1) or before (Experiment 2) the search task. This bias was particularly prevalent in short-latency saccades. The results show that early oculomotor selection performance is not only affected by properties that are actively maintained in working memory but also by those previously memorized. Both working memory and feature priming can cause early biases in oculomotor selection.

The Effects of Feature-Based Priming and Visual Working Memory on Oculomotor Capture

PubMed Central

Silvis, Jeroen D.; Belopolsky, Artem V.; Murris, Jozua W. I.; Donk, Mieke

2015-01-01

Recently, it has been demonstrated that objects held in working memory can influence rapid oculomotor selection. This has been taken as evidence that perceptual salience can be modified by active working memory representations. The goal of the present study was to examine whether these results could also be caused by feature-based priming. In two experiments, participants were asked to saccade to a target line segment of a certain orientation that was presented together with a to-be-ignored distractor. Both objects were given a task-irrelevant color that varied per trial. In a secondary task, a color had to be memorized, and that color could either match the color of the target, match the color of the distractor, or it did not match the color of any of the objects in the search task. The memory task was completed either after the search task (Experiment 1), or before it (Experiment 2). The results showed that in both experiments the memorized color biased oculomotor selection. Eye movements were more frequently drawn towards objects that matched the memorized color, irrespective of whether the memory task was completed after (Experiment 1) or before (Experiment 2) the search task. This bias was particularly prevalent in short-latency saccades. The results show that early oculomotor selection performance is not only affected by properties that are actively maintained in working memory but also by those previously memorized. Both working memory and feature priming can cause early biases in oculomotor selection. PMID:26566137

Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

PubMed Central

Abdulameer, Mohammed Hasan; Othman, Zulaiha Ali

2014-01-01

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

Implicit integration in a case of integrative visual agnosia.

PubMed

Aviezer, Hillel; Landau, Ayelet N; Robertson, Lynn C; Peterson, Mary A; Soroker, Nachum; Sacher, Yaron; Bonneh, Yoram; Bentin, Shlomo

2007-05-15

We present a case (SE) with integrative visual agnosia following ischemic stroke affecting the right dorsal and the left ventral pathways of the visual system. Despite his inability to identify global hierarchical letters [Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. Cognitive Psychology, 9, 353-383], and his dense object agnosia, SE showed normal global-to-local interference when responding to local letters in Navon hierarchical stimuli and significant picture-word identity priming in a semantic decision task for words. Since priming was absent if these features were scrambled, it stands to reason that these effects were not due to priming by distinctive features. The contrast between priming effects induced by coherent and scrambled stimuli is consistent with implicit but not explicit integration of features into a unified whole. We went on to show that possible/impossible object decisions were facilitated by words in a word-picture priming task, suggesting that prompts could activate perceptually integrated images in a backward fashion. We conclude that the absence of SE's ability to identify visual objects except through tedious serial construction reflects a deficit in accessing an integrated visual representation through bottom-up visual processing alone. However, top-down generated images can help activate these visual representations through semantic links.

a New Approach for Progressive Dense Reconstruction from Consecutive Images Based on Prior Low-Density 3d Point Clouds

NASA Astrophysics Data System (ADS)

Lari, Z.; El-Sheimy, N.

2017-09-01

In recent years, the increasing incidence of climate-related disasters has tremendously affected our environment. In order to effectively manage and reduce dramatic impacts of such events, the development of timely disaster management plans is essential. Since these disasters are spatial phenomena, timely provision of geospatial information is crucial for effective development of response and management plans. Due to inaccessibility of the affected areas and limited budget of first-responders, timely acquisition of the required geospatial data for these applications is usually possible only using low-cost imaging and georefencing sensors mounted on unmanned platforms. Despite rapid collection of the required data using these systems, available processing techniques are not yet capable of delivering geospatial information to responders and decision makers in a timely manner. To address this issue, this paper introduces a new technique for dense 3D reconstruction of the affected scenes which can deliver and improve the needed geospatial information incrementally. This approach is implemented based on prior 3D knowledge of the scene and employs computationally-efficient 2D triangulation, feature descriptor, feature matching and point verification techniques to optimize and speed up 3D dense scene reconstruction procedure. To verify the feasibility and computational efficiency of the proposed approach, an experiment using a set of consecutive images collected onboard a UAV platform and prior low-density airborne laser scanning over the same area is conducted and step by step results are provided. A comparative analysis of the proposed approach and an available image-based dense reconstruction technique is also conducted to prove the computational efficiency and competency of this technique for delivering geospatial information with pre-specified accuracy.

Autonomous facial recognition system inspired by human visual system based logarithmical image visualization technique

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.

Masked Inhibitory Priming in English: Evidence for Lexical Inhibition

ERIC Educational Resources Information Center

Davis, Colin J.; Lupker, Stephen J.

2006-01-01

Predictions derived from the interactive activation (IA) model were tested in 3 experiments using the masked priming technique in the lexical decision task. Experiment 1 showed a strong effect of prime lexicality: Classifications of target words were facilitated by orthographically related nonword primes (relative to unrelated nonword primes) but…

New precursors for direct synthesis of single phase Na- and K-{beta}{double_prime}-aluminas for use in AMTEC systems

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

Cook, R.L.; MacQueen, D.B.; Bader, K.E.

1997-12-31

Alkali Metal Thermoelectric Converters (AMTEC) are efficient direct energy conversion devices that depend on the use of highly conductive beta-alumina membranes for their operation. The key component of the AMTEC system is a highly conductive Na-{beta}{double_prime}-alumina solid electrolyte which conducts sodium ions from the high to low temperature zone, thereby generating electricity. AMTEC cells convert thermal to electrical energy by using heat to produce and maintain an alkali metal concentration gradient across the ion transporting BASE membrane. They have developed a method for producing pure phase Na-{beta}{double_prime}-alumina and K-{beta}{double_prime}-alumina powders from single phase nano-sized carboxylato-alumoxanes precursors. Sodium or potassium ionsmore » (the mobile ions) and either Mg{sup 2+} or Li{sup +} ions (which stabilize the {beta}{double_prime}-alumina structure) can be atomically dispersed into the carboxylato-alumoxane lattice at low (< 100 C) temperature. Calculation of the carboxylato-alumoxane precursors at 1,200--1,500 C produces pure phase {beta}{double_prime}-alumina powders.« less

Neutrophils with protumor potential could efficiently suppress tumor growth after cytokine priming and in presence of normal NK cells.

PubMed

Sun, Rui; Luo, Jing; Li, Dong; Shu, Yu; Luo, Chao; Wang, Shan-Shan; Qin, Jian; Zhang, Gui-Mei; Feng, Zuo-Hua

2014-12-30

In tumor-bearing state, the function of neutrophils is converted from tumor-suppressing to tumor-promoting. Here we report that priming with IFN-γ and TNF-α could convert the potential of neutrophils from tumor-promoting to tumor-suppressing. The neutrophils with protumor potential have not lost their responsiveness to IFN-γ and TNF-α. After priming with IFN-γ and TNF-α, the potential of the neutrophils to express Bv8 and Mmp9 genes was reduced. Conversely, the tumor-promotional neutrophils recovered the expression of Rab27a and Trail, resumed the activation levels of PI3K and p38 MAPK pathways in response to stimuli, and expressed higher levels of IL-18 and NK-activating ligands such as RAE-1, MULT-1, and H60. Therefore, the anti-tumor function of the neutrophils was augmented, including the cytotoxicity to tumor cells, the capability of degranulation, and the capacity to activate NK cells. Since the function of NK cells is impaired in tumor-bearing state, the administration of normal NK cells could significantly augment the efficiency of tumor therapy based on neutrophil priming. These findings highlight the reversibility of neutrophil function in tumor-bearing state, and suggest that neutrophil priming by IFN-γ/TNF-α might be a potential approach to eliminate residual tumor cells in comprehensive strategy for tumor therapy.

Grouping principles in direct competition.

PubMed

Schmidt, Filipp; Schmidt, Thomas

2013-08-09

We (1) introduce a primed flanker task as an objective method to measure perceptual grouping, and (2) use it to directly compare the efficiency of different grouping cues in rapid visuomotor processing. In two experiments, centrally presented primes were succeeded by flanking targets with varying stimulus-onset asynchronies (SOAs). Primes and targets were grouped by the same or by different grouping cues (Exp. 1: brightness/shape, Exp. 2: brightness/size) and were consistent or inconsistent with respect to the required response. Subjective grouping strength was varied to identify its influence on overall response times, error rates, and priming effects, that served as a measure of visual feedforward processing. Our results show that stronger grouping in the targets enhanced overall response times while stronger grouping in the primes enhanced priming effects in motor responses. Also, we obtained differences between rapid visuomotor processing and the subjective impression with cues of brightness and shape but not with cues of brightness and size. Our findings establish the primed flanker task as an objective method to study the speeded visuomotor processing of grouping cues, making it a useful method for the comparative study of feedforward-transmitted base groupings (Roelfsema & Houtkamp, 2011). Copyright © 2013 Elsevier Ltd. All rights reserved.

Fast and robust generation of feature maps for region-based visual attention.

PubMed

Aziz, Muhammad Zaheer; Mertsching, Bärbel

2008-05-01

Visual attention is one of the important phenomena in biological vision which can be followed to achieve more efficiency, intelligence, and robustness in artificial vision systems. This paper investigates a region-based approach that performs pixel clustering prior to the processes of attention in contrast to late clustering as done by contemporary methods. The foundation steps of feature map construction for the region-based attention model are proposed here. The color contrast map is generated based upon the extended findings from the color theory, the symmetry map is constructed using a novel scanning-based method, and a new algorithm is proposed to compute a size contrast map as a formal feature channel. Eccentricity and orientation are computed using the moments of obtained regions and then saliency is evaluated using the rarity criteria. The efficient design of the proposed algorithms allows incorporating five feature channels while maintaining a processing rate of multiple frames per second. Another salient advantage over the existing techniques is the reusability of the salient regions in the high-level machine vision procedures due to preservation of their shapes and precise locations. The results indicate that the proposed model has the potential to efficiently integrate the phenomenon of attention into the main stream of machine vision and systems with restricted computing resources such as mobile robots can benefit from its advantages.

Modulation of Automatic Semantic Priming by Feature-Specific Attention Allocation

ERIC Educational Resources Information Center

Spruyt, Adriaan; De Houwer, Jan; Hermans, Dirk

2009-01-01

We argue that the semantic analysis of task-irrelevant stimuli is modulated by feature-specific attention allocation. In line with this hypothesis, we found semantic priming of pronunciation responses to depend upon the extent to which participants focused their attention upon specific semantic stimulus dimensions. In Experiment 1, we examined the…

Comparison of l₁-Norm SVR and Sparse Coding Algorithms for Linear Regression.

PubMed

Zhang, Qingtian; Hu, Xiaolin; Zhang, Bo

2015-08-01

Support vector regression (SVR) is a popular function estimation technique based on Vapnik's concept of support vector machine. Among many variants, the l1-norm SVR is known to be good at selecting useful features when the features are redundant. Sparse coding (SC) is a technique widely used in many areas and a number of efficient algorithms are available. Both l1-norm SVR and SC can be used for linear regression. In this brief, the close connection between the l1-norm SVR and SC is revealed and some typical algorithms are compared for linear regression. The results show that the SC algorithms outperform the Newton linear programming algorithm, an efficient l1-norm SVR algorithm, in efficiency. The algorithms are then used to design the radial basis function (RBF) neural networks. Experiments on some benchmark data sets demonstrate the high efficiency of the SC algorithms. In particular, one of the SC algorithms, the orthogonal matching pursuit is two orders of magnitude faster than a well-known RBF network designing algorithm, the orthogonal least squares algorithm.

Parallel Key Frame Extraction for Surveillance Video Service in a Smart City.

PubMed

Zheng, Ran; Yao, Chuanwei; Jin, Hai; Zhu, Lei; Zhang, Qin; Deng, Wei

2015-01-01

Surveillance video service (SVS) is one of the most important services provided in a smart city. It is very important for the utilization of SVS to provide design efficient surveillance video analysis techniques. Key frame extraction is a simple yet effective technique to achieve this goal. In surveillance video applications, key frames are typically used to summarize important video content. It is very important and essential to extract key frames accurately and efficiently. A novel approach is proposed to extract key frames from traffic surveillance videos based on GPU (graphics processing units) to ensure high efficiency and accuracy. For the determination of key frames, motion is a more salient feature in presenting actions or events, especially in surveillance videos. The motion feature is extracted in GPU to reduce running time. It is also smoothed to reduce noise, and the frames with local maxima of motion information are selected as the final key frames. The experimental results show that this approach can extract key frames more accurately and efficiently compared with several other methods.

Individual differences in automatic semantic priming.

PubMed

Andrews, Sally; Lo, Steson; Xia, Violet

2017-05-01

This research investigated whether masked semantic priming in a semantic categorization task that required classification of words as animals or nonanimals was modulated by individual differences in lexical proficiency. A sample of 89 skilled readers, assessed on reading comprehension, vocabulary and spelling ability, classified target words preceded by brief (50 ms) masked primes that were either congruent or incongruent with the category of the target. Congruent primes were also selected to be either high (e.g., hawk EAGLE, pistol RIFLE) or low (e.g., mole EAGLE, boots RIFLE) in semantic feature overlap with the target. "Overall proficiency," indexed by high performance on both a "semantic composite" measure of reading comprehension and vocabulary and a "spelling composite," was associated with stronger congruence priming from both high and low feature overlap primes for animal exemplars, but only predicted priming from low overlap primes for nonexemplars. Classification of high frequency nonexemplars was also significantly modulated by an independent "spelling-meaning" factor, indexed by the discrepancy between the semantic and spelling composites, because relatively higher scores on the semantic than the spelling composite were associated with stronger semantic priming. These findings show that higher lexical proficiency is associated with stronger evidence of automatic semantic priming and suggest that individual differences in lexical quality modulate the division of labor between orthographic and semantic processing in early lexical retrieval. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Binding of nickel /II/ to 5-prime-nucleoside monophosphates and related compounds. [role in origin of life

NASA Technical Reports Server (NTRS)

Orenberg, J. B.; Kjos, K. M.; Winkler, R.; Link, J.; Lawless, J. G.

1982-01-01

The interactions of Ni(II) cation with a representative suite of purine bases and the respective nucleosides and nucleotides have been studied by ultraviolet difference spectroscopy. Apparent association constants were determined for each system at pH 7.0, using computer linear regression coupled with an iteration technique. The specificity of binding of Ni(2+) for the purine nucleotides studied at pH 7.0 was 5-prime-GMP greater than 5-prime-AMP; a similar ordering was also found for the respective nucleosides and bases. In this study binding was not observed for the suite of pyramidines used, although an Ni(2+) -cytidine complex has been observed (Fiskin and Beer, 1965). It was also found that Ni(2+) bound more strongly to the purine 5-prime-nucleotides than to the respective nucleosides and bases. These trends are explained in terms of metal-ligand bonds and available bonding positions on the ligands. A role for metal-ion-nucleotide types of complexes is suggested in the processes that might have given rise to the origin of life.

Rotation covariant image processing for biomedical applications.

PubMed

Skibbe, Henrik; Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences.

MultiMiTar: a novel multi objective optimization based miRNA-target prediction method.

PubMed

Mitra, Ramkrishna; Bandyopadhyay, Sanghamitra

2011-01-01

Machine learning based miRNA-target prediction algorithms often fail to obtain a balanced prediction accuracy in terms of both sensitivity and specificity due to lack of the gold standard of negative examples, miRNA-targeting site context specific relevant features and efficient feature selection process. Moreover, all the sequence, structure and machine learning based algorithms are unable to distribute the true positive predictions preferentially at the top of the ranked list; hence the algorithms become unreliable to the biologists. In addition, these algorithms fail to obtain considerable combination of precision and recall for the target transcripts that are translationally repressed at protein level. In the proposed article, we introduce an efficient miRNA-target prediction system MultiMiTar, a Support Vector Machine (SVM) based classifier integrated with a multiobjective metaheuristic based feature selection technique. The robust performance of the proposed method is mainly the result of using high quality negative examples and selection of biologically relevant miRNA-targeting site context specific features. The features are selected by using a novel feature selection technique AMOSA-SVM, that integrates the multi objective optimization technique Archived Multi-Objective Simulated Annealing (AMOSA) and SVM. MultiMiTar is found to achieve much higher Matthew's correlation coefficient (MCC) of 0.583 and average class-wise accuracy (ACA) of 0.8 compared to the others target prediction methods for a completely independent test data set. The obtained MCC and ACA values of these algorithms range from -0.269 to 0.155 and 0.321 to 0.582, respectively. Moreover, it shows a more balanced result in terms of precision and sensitivity (recall) for the translationally repressed data set as compared to all the other existing methods. An important aspect is that the true positive predictions are distributed preferentially at the top of the ranked list that makes MultiMiTar reliable for the biologists. MultiMiTar is now available as an online tool at www.isical.ac.in/~bioinfo_miu/multimitar.htm. MultiMiTar software can be downloaded from www.isical.ac.in/~bioinfo_miu/multimitar-download.htm.

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

PubMed

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

2011-11-24

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

Online Condition Monitoring of Bearings to Support Total Productive Maintenance in the Packaging Materials Industry.

PubMed

Gligorijevic, Jovan; Gajic, Dragoljub; Brkovic, Aleksandar; Savic-Gajic, Ivana; Georgieva, Olga; Di Gennaro, Stefano

2016-03-01

The packaging materials industry has already recognized the importance of Total Productive Maintenance as a system of proactive techniques for improving equipment reliability. Bearing faults, which often occur gradually, represent one of the foremost causes of failures in the industry. Therefore, detection of their faults in an early stage is quite important to assure reliable and efficient operation. We present a new automated technique for early fault detection and diagnosis in rolling-element bearings based on vibration signal analysis. Following the wavelet decomposition of vibration signals into a few sub-bands of interest, the standard deviation of obtained wavelet coefficients is extracted as a representative feature. Then, the feature space dimension is optimally reduced to two using scatter matrices. In the reduced two-dimensional feature space the fault detection and diagnosis is carried out by quadratic classifiers. Accuracy of the technique has been tested on four classes of the recorded vibrations signals, i.e., normal, with the fault of inner race, outer race, and ball operation. The overall accuracy of 98.9% has been achieved. The new technique can be used to support maintenance decision-making processes and, thus, to increase reliability and efficiency in the industry by preventing unexpected faulty operation of bearings.

Online Condition Monitoring of Bearings to Support Total Productive Maintenance in the Packaging Materials Industry

PubMed Central

Gligorijevic, Jovan; Gajic, Dragoljub; Brkovic, Aleksandar; Savic-Gajic, Ivana; Georgieva, Olga; Di Gennaro, Stefano

2016-01-01

The packaging materials industry has already recognized the importance of Total Productive Maintenance as a system of proactive techniques for improving equipment reliability. Bearing faults, which often occur gradually, represent one of the foremost causes of failures in the industry. Therefore, detection of their faults in an early stage is quite important to assure reliable and efficient operation. We present a new automated technique for early fault detection and diagnosis in rolling-element bearings based on vibration signal analysis. Following the wavelet decomposition of vibration signals into a few sub-bands of interest, the standard deviation of obtained wavelet coefficients is extracted as a representative feature. Then, the feature space dimension is optimally reduced to two using scatter matrices. In the reduced two-dimensional feature space the fault detection and diagnosis is carried out by quadratic classifiers. Accuracy of the technique has been tested on four classes of the recorded vibrations signals, i.e., normal, with the fault of inner race, outer race, and ball operation. The overall accuracy of 98.9% has been achieved. The new technique can be used to support maintenance decision-making processes and, thus, to increase reliability and efficiency in the industry by preventing unexpected faulty operation of bearings. PMID:26938541

Active site specificity profiling of the matrix metalloproteinase family: Proteomic identification of 4300 cleavage sites by nine MMPs explored with structural and synthetic peptide cleavage analyses.

PubMed

Eckhard, Ulrich; Huesgen, Pitter F; Schilling, Oliver; Bellac, Caroline L; Butler, Georgina S; Cox, Jennifer H; Dufour, Antoine; Goebeler, Verena; Kappelhoff, Reinhild; Keller, Ulrich Auf dem; Klein, Theo; Lange, Philipp F; Marino, Giada; Morrison, Charlotte J; Prudova, Anna; Rodriguez, David; Starr, Amanda E; Wang, Yili; Overall, Christopher M

2016-01-01

Secreted and membrane tethered matrix metalloproteinases (MMPs) are key homeostatic proteases regulating the extracellular signaling and structural matrix environment of cells and tissues. For drug targeting of proteases, selectivity for individual molecules is highly desired and can be met by high yield active site specificity profiling. Using the high throughput Proteomic Identification of protease Cleavage Sites (PICS) method to simultaneously profile both the prime and non-prime sides of the cleavage sites of nine human MMPs, we identified more than 4300 cleavages from P6 to P6' in biologically diverse human peptide libraries. MMP specificity and kinetic efficiency were mainly guided by aliphatic and aromatic residues in P1' (with a ~32-93% preference for leucine depending on the MMP), and basic and small residues in P2' and P3', respectively. A wide differential preference for the hallmark P3 proline was found between MMPs ranging from 15 to 46%, yet when combined in the same peptide with the universally preferred P1' leucine, an unexpected negative cooperativity emerged. This was not observed in previous studies, probably due to the paucity of approaches that profile both the prime and non-prime sides together, and the masking of subsite cooperativity effects by global heat maps and iceLogos. These caveats make it critical to check for these biologically highly important effects by fixing all 20 amino acids one-by-one in the respective subsites and thorough assessing of the inferred specificity logo changes. Indeed an analysis of bona fide MEROPS physiological substrate cleavage data revealed that of the 37 natural substrates with either a P3-Pro or a P1'-Leu only 5 shared both features, confirming the PICS data. Upon probing with several new quenched-fluorescent peptides, rationally designed on our specificity data, the negative cooperativity was explained by reduced non-prime side flexibility constraining accommodation of the rigidifying P3 proline with leucine locked in S1'. Similar negative cooperativity between P3 proline and the novel preference for asparagine in P1 cements our conclusion that non-prime side flexibility greatly impacts MMP binding affinity and cleavage efficiency. Thus, unexpected sequence cooperativity consequences were revealed by PICS that uniquely encompasses both the non-prime and prime sides flanking the proteomic-pinpointed scissile bond. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Support vector machine for automatic pain recognition

NASA Astrophysics Data System (ADS)

Monwar, Md Maruf; Rezaei, Siamak

2009-02-01

Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

The Role of Expression and Race in Weapons Identification

PubMed Central

Kubota, Jennifer T.; Ito, Tiffany A.

2014-01-01

Emotional expressions can signal intentions and so possess the power to moderate social inferences. Here we test whether stereotypes implicitly elicited by a stigmatized racial outgroup member are moderated by facial expression. Participants classified pictures of guns and tools that were primed with pictures of Black and White male faces posing angry, happy, and neutral expressions. Across the three measures examined—response latencies, error rates, and automatic processing— facial expression modulated implicit stereotyping (study 1, n=71; study 2, n=166). A Black angry prime elicited implicit stereotyping while a Black happy prime diminished implicit stereotyping. Responding after neutral primes varied as a function of the expression context. When viewed alongside more threatening expressions (study 1), neutral Black targets no longer elicited implicit stereotyping; but when viewed alongside more threatening expressions (study 2), neutral Black targets primed crime and danger-relevant stereotypes. These results demonstrate that an individual can activate different associations based on changes in emotional expression, and that a feature present in many everyday encounters (a smile) attenuates implicit racial stereotyping. PMID:25401289

NMR studies of two spliced leader RNAs using isotope labeling

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

Lapham, J.; Crothers, D.M.

1994-12-01

Spliced leader RNAs are a class of RNA molecules (<200 nts) involved in the trans splicing of messenger RNA found in trypanosomes, nematodes, and other lower eukaryotes. The spliced leader RNA from the trypanosome Leptomonas Collosoma exists in two alternate structural forms with similar thermal stabilities. The 54 nucleotides on the 5{prime} end of the SL molecule is structurally independent from the 3{prime} half of the RNA, and displays the two structural forms. Furthermore, the favored of the two structures was shown to contain anomalous nuclease sensitivity and thermal stability features, which suggests that there may be tertiary interactions betweenmore » the splice site and other nucleotides in the 5{prime} end. Multidimensional NMR studies are underway to elucidate the structural elements present in the SL RNAs that give rise to their physical properties. Two spliced leader sequences have been studied. The first, the 54 nucleotides on the 5{prime} end of the L. Collosoma sequence, was selected because of earlier studies in our laboratory. The second sequence is the 5{prime} end of the trypanosome Crithidia Fasciculata, which was chosen because of its greater sequence homology to other SL sequences. Given the complexity of the NMR spectra for RNA molecules of this size, we have incorporated {sup 15}N/{sup 13}C-labeled nucleotides into the RNA. One of the techniques we have developed to simplify the spectra of these RNA molecules is isotope labeling of specific regions of the RNA. This has been especially helpful in assigning the secondary structure of molecules that may be able to adopt multiple conformations. Using this technique one can examine a part of the molecule without spectral interference from the unlabeled portion. We hope this approach will promote an avenue for studying the structure of larger RNAs in their native surroundings.« less

Implicit Processing of the Eyes and Mouth: Evidence from Human Electrophysiology.

PubMed

Pesciarelli, Francesca; Leo, Irene; Sarlo, Michela

2016-01-01

The current study examined the time course of implicit processing of distinct facial features and the associate event-related potential (ERP) components. To this end, we used a masked priming paradigm to investigate implicit processing of the eyes and mouth in upright and inverted faces, using a prime duration of 33 ms. Two types of prime-target pairs were used: 1. congruent (e.g., open eyes only in both prime and target or open mouth only in both prime and target); 2. incongruent (e.g., open mouth only in prime and open eyes only in target or open eyes only in prime and open mouth only in target). The identity of the faces changed between prime and target. Participants pressed a button when the target face had the eyes open and another button when the target face had the mouth open. The behavioral results showed faster RTs for the eyes in upright faces than the eyes in inverted faces, the mouth in upright and inverted faces. Moreover they also revealed a congruent priming effect for the mouth in upright faces. The ERP findings showed a face orientation effect across all ERP components studied (P1, N1, N170, P2, N2, P3) starting at about 80 ms, and a congruency/priming effect on late components (P2, N2, P3), starting at about 150 ms. Crucially, the results showed that the orientation effect was driven by the eye region (N170, P2) and that the congruency effect started earlier (P2) for the eyes than for the mouth (N2). These findings mark the time course of the processing of internal facial features and provide further evidence that the eyes are automatically processed and that they are very salient facial features that strongly affect the amplitude, latency, and distribution of neural responses to faces.

Implicit Processing of the Eyes and Mouth: Evidence from Human Electrophysiology

PubMed Central

Pesciarelli, Francesca; Leo, Irene; Sarlo, Michela

2016-01-01

The current study examined the time course of implicit processing of distinct facial features and the associate event-related potential (ERP) components. To this end, we used a masked priming paradigm to investigate implicit processing of the eyes and mouth in upright and inverted faces, using a prime duration of 33 ms. Two types of prime-target pairs were used: 1. congruent (e.g., open eyes only in both prime and target or open mouth only in both prime and target); 2. incongruent (e.g., open mouth only in prime and open eyes only in target or open eyes only in prime and open mouth only in target). The identity of the faces changed between prime and target. Participants pressed a button when the target face had the eyes open and another button when the target face had the mouth open. The behavioral results showed faster RTs for the eyes in upright faces than the eyes in inverted faces, the mouth in upright and inverted faces. Moreover they also revealed a congruent priming effect for the mouth in upright faces. The ERP findings showed a face orientation effect across all ERP components studied (P1, N1, N170, P2, N2, P3) starting at about 80 ms, and a congruency/priming effect on late components (P2, N2, P3), starting at about 150 ms. Crucially, the results showed that the orientation effect was driven by the eye region (N170, P2) and that the congruency effect started earlier (P2) for the eyes than for the mouth (N2). These findings mark the time course of the processing of internal facial features and provide further evidence that the eyes are automatically processed and that they are very salient facial features that strongly affect the amplitude, latency, and distribution of neural responses to faces. PMID:26790153

Intelligent Traffic Quantification System

NASA Astrophysics Data System (ADS)

Mohanty, Anita; Bhanja, Urmila; Mahapatra, Sudipta

2017-08-01

Currently, city traffic monitoring and controlling is a big issue in almost all cities worldwide. Vehicular ad-hoc Network (VANET) technique is an efficient tool to minimize this problem. Usually, different types of on board sensors are installed in vehicles to generate messages characterized by different vehicle parameters. In this work, an intelligent system based on fuzzy clustering technique is developed to reduce the number of individual messages by extracting important features from the messages of a vehicle. Therefore, the proposed fuzzy clustering technique reduces the traffic load of the network. The technique also reduces congestion and quantifies congestion.

Priming Dental Pulp Stem Cells With Fibroblast Growth Factor-2 Increases Angiogenesis of Implanted Tissue-Engineered Constructs Through Hepatocyte Growth Factor and Vascular Endothelial Growth Factor Secretion

PubMed Central

Gorin, Caroline; Rochefort, Gael Y.; Bascetin, Rumeyza; Ying, Hanru; Lesieur, Julie; Sadoine, Jérémy; Beckouche, Nathan; Berndt, Sarah; Novais, Anita; Lesage, Matthieu; Hosten, Benoit; Vercellino, Laetitia; Merlet, Pascal; Le-Denmat, Dominique; Marchiol, Carmen; Letourneur, Didier; Nicoletti, Antonino; Vital, Sibylle Opsahl; Poliard, Anne; Salmon, Benjamin; Germain, Stéphane

2016-01-01

Tissue engineering strategies based on implanting cellularized biomaterials are promising therapeutic approaches for the reconstruction of large tissue defects. A major hurdle for the reliable establishment of such therapeutic approaches is the lack of rapid blood perfusion of the tissue construct to provide oxygen and nutrients. Numerous sources of mesenchymal stem cells (MSCs) displaying angiogenic potential have been characterized in the past years, including the adult dental pulp. Establishment of efficient strategies for improving angiogenesis in tissue constructs is nevertheless still an important challenge. Hypoxia was proposed as a priming treatment owing to its capacity to enhance the angiogenic potential of stem cells through vascular endothelial growth factor (VEGF) release. The present study aimed to characterize additional key factors regulating the angiogenic capacity of such MSCs, namely, dental pulp stem cells derived from deciduous teeth (SHED). We identified fibroblast growth factor-2 (FGF-2) as a potent inducer of the release of VEGF and hepatocyte growth factor (HGF) by SHED. We found that FGF-2 limited hypoxia-induced downregulation of HGF release. Using three-dimensional culture models of angiogenesis, we demonstrated that VEGF and HGF were both responsible for the high angiogenic potential of SHED through direct targeting of endothelial cells. In addition, FGF-2 treatment increased the fraction of Stro-1+/CD146+ progenitor cells. We then applied in vitro FGF-2 priming to SHED before encapsulation in hydrogels and in vivo subcutaneous implantation. Our results showed that FGF-2 priming is more efficient than hypoxia at increasing SHED-induced vascularization compared with nonprimed controls. Altogether, these data demonstrate that FGF-2 priming enhances the angiogenic potential of SHED through the secretion of both HGF and VEGF. Significance The results from the present study show that fibroblast growth factor-2 (FGF-2) priming is more efficient than hypoxia at increasing dental pulp stem cells derived from deciduous teeth (SHED)-induced vascularization compared with nonprimed controls. Together, these data demonstrate that FGF-2 priming enhances the angiogenic potential of SHED through the secretion of both hepatocyte growth factor and vascular endothelial growth factor. PMID:26798059

An expert botanical feature extraction technique based on phenetic features for identifying plant species.

PubMed

Kolivand, Hoshang; Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

2018-01-01

In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost.

An expert botanical feature extraction technique based on phenetic features for identifying plant species

PubMed Central

Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

2018-01-01

In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost. PMID:29420568

Localized contourlet features in vehicle make and model recognition

NASA Astrophysics Data System (ADS)

Zafar, I.; Edirisinghe, E. A.; Acar, B. S.

2009-02-01

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic Number Plate Recognition (ANPR) systems. Several vehicle MMR systems have been proposed in literature. In parallel to this, the usefulness of multi-resolution based feature analysis techniques leading to efficient object classification algorithms have received close attention from the research community. To this effect, Contourlet transforms that can provide an efficient directional multi-resolution image representation has recently been introduced. Already an attempt has been made in literature to use Curvelet/Contourlet transforms in vehicle MMR. In this paper we propose a novel localized feature detection method in Contourlet transform domain that is capable of increasing the classification rates up to 4%, as compared to the previously proposed Contourlet based vehicle MMR approach in which the features are non-localized and thus results in sub-optimal classification. Further we show that the proposed algorithm can achieve the increased classification accuracy of 96% at significantly lower computational complexity due to the use of Two Dimensional Linear Discriminant Analysis (2DLDA) for dimensionality reduction by preserving the features with high between-class variance and low inter-class variance.

Visuoperceptual repetition priming and progression of parkinsonian signs in aging

PubMed Central

Fleischman, Debra A.; Buchman, Aron S.; Bienias, Julia L.; Bennett, David A.

2009-01-01

Parkinsonian signs in older persons are associated with numerous adverse health outcomes, however there is limited information about factors which predict progression of these signs. Using generalized linear models, we examined the association between efficiency in visuoperceptual and conceptual processing, measured by repetition priming, and rate of change in parkinsonian signs in a large sample of older persons without cognitive impairment or Parkinson’s disease. Subjects with better visuoperceptual priming, measured by threshold word-identification and word-stem completion, at study baseline, progressed more slowly during follow-up of up to 11 years. Conceptual priming was not associated with change in parkinsonian signs. The findings demonstrate that individual differences in visuoperceptual efficiency, measured by repetition priming, occur in older persons without cognitive impairment and predict important changes in motor function. Reduced visuoperceptual priming in aging may be an early signal of vulnerability in a corticostrial circuit that contributes to sensorimotor integration. PMID:17709154

Exploring the impact of visual and movement based priming on a motor intervention in the acute phase post-stroke in persons with severe hemiparesis of the upper extremity.

PubMed

Patel, Jigna; Qiu, Qinyin; Yarossi, Mathew; Merians, Alma; Massood, Supriya; Tunik, Eugene; Adamovich, Sergei; Fluet, Gerard

2017-07-01

Explore the potential benefits of using priming methods prior to an active hand task in the acute phase post-stroke in persons with severe upper extremity hemiparesis. Five individuals were trained using priming techniques including virtual reality (VR) based visual mirror feedback and contralaterally controlled passive movement strategies prior to training with an active pinch force modulation task. Clinical, kinetic, and neurophysiological measurements were taken pre and post the training period. Clinical measures were taken at six months post training. The two priming simulations and active training were well tolerated early after stroke. Priming effects were suggested by increased maximal pinch force immediately after visual and movement based priming. Despite having no clinically observable movement distally, the subjects were able to volitionally coordinate isometric force and muscle activity (EMG) in a pinch tracing task. The Root Mean Square Error (RMSE) of force during the pinch trace task gradually decreased over the training period suggesting learning may have occurred. Changes in motor cortical neurophysiology were seen in the unaffected hemisphere using Transcranial Magnetic Stimulation (TMS) mapping. Significant improvements in motor recovery as measured by the Action Research Arm Test (ARAT) and the Upper Extremity Fugl Meyer Assessment (UEFMA) were demonstrated at six months post training by three of the five subjects. This study suggests that an early hand-based intervention using visual and movement based priming activities and a scaled motor task allows participation by persons without the motor control required for traditionally presented rehabilitation and testing. Implications for Rehabilitation Rehabilitation of individuals with severely paretic upper extremities after stroke is challenging due to limited movement capacity and few options for therapeutic training. Long-term functional recovery of the arm after stroke depends on early return of active hand control, establishing a need for acute training methods focused distally. This study demonstrates the feasibility of an early hand-based intervention using virtual reality based priming and scaled motor activities which can allow for participation by persons without the motor control required for traditionally presented rehabilitation and testing.

GST-PRIME: an algorithm for genome-wide primer design.

PubMed

Leister, Dario; Varotto, Claudio

2007-01-01

The profiling of mRNA expression based on DNA arrays has become a powerful tool to study genome-wide transcription of genes in a number of organisms. GST-PRIME is a software package created to facilitate large-scale primer design for the amplification of probes to be immobilized on arrays for transcriptome analyses, even though it can be also applied in low-throughput approaches. GST-PRIME allows highly efficient, direct amplification of gene-sequence tags (GSTs) from genomic DNA (gDNA), starting from annotated genome or transcript sequences. GST-PRIME provides a customer-friendly platform for automatic primer design, and despite the relative simplicity of the algorithm, experimental tests in the model plant species Arabidopsis thaliana confirmed the reliability of the software. This chapter describes the algorithm used for primer design, its input and output files, and the installation of the standalone package and its use.

Nitrogen availability drives priming effect by altering microbial carbon-use efficiency after permafrost thaw

NASA Astrophysics Data System (ADS)

Chen, L.; Liu, L.; Zhang, Q.; Mao, C.; Liu, F.; Yang, Y.

2017-12-01

Enhanced vegetation growth can potentially aggravate soil C loss by accelerating the decomposition of soil organic matter (SOM) ("priming effect"), thereby reinforcing the positive C-climate feedback in permafrost ecosystems. However, the degree to which priming effect alters permafrost C dynamics is expected to be modified by nitrogen (N) availability after permafrost thaw. Despite this recognition, experimental evidence for the linkage between priming effect and post-thaw N availability is still lacking. Particularly, the microbial mechanisms involved remain unknown. Here, using a thermokarst-induced natural N gradient combined with an isotope-labeled glucose and N addition experiment, we presented a strong linkage between soil N availability and priming effect in Tibetan permafrost. We observed that the magnitude of priming effect along the thaw gradient was negatively associated with soil total dissolved nitrogen (TDN) concentration. This negative effect of post-thaw N availability was further proved by a sharply reduced priming effect following mineral N supply. These two lines of evidence jointly illustrated that the priming effect along the thaw chronosequence was controlled by N availability, supporting the `N mining theory'. In contrast to the prevailing assumption, this N-regulated priming effect was independent from changes in C- or N-acquiring enzyme activities, but positively associated with the change in metabolic quotients (△SOM-qCO2), highlighting that decreased microbial metabolism efficiency rather than increased enzyme activities account for greater priming effect under reduced N availability. Taken together, these findings demonstrate that C dynamics in melting permafrost largely depends on post-thaw N availability due to its effect of retarding SOM mineralization. This C-N interaction and the relevant microbial metabolic efficiency should be considered in Earth System Models for a better understanding of soil C dynamics after permafrost thaw.

Subsurface Mapping: A Question of Position and Interpretation

ERIC Educational Resources Information Center

Kellie, Andrew C.

2009-01-01

This paper discusses the character and challenges inherent in the graphical portrayal of features in subsurface mapping. Subsurface structures are, by their nature, hidden and must be mapped based on drilling and/or geophysical data. Efficient use of graphical techniques is central to effectively communicating the results of expensive exploration…

Current state of the art of vision based SLAM

NASA Astrophysics Data System (ADS)

Muhammad, Naveed; Fofi, David; Ainouz, Samia

2009-02-01

The ability of a robot to localise itself and simultaneously build a map of its environment (Simultaneous Localisation and Mapping or SLAM) is a fundamental characteristic required for autonomous operation of the robot. Vision Sensors are very attractive for application in SLAM because of their rich sensory output and cost effectiveness. Different issues are involved in the problem of vision based SLAM and many different approaches exist in order to solve these issues. This paper gives a classification of state-of-the-art vision based SLAM techniques in terms of (i) imaging systems used for performing SLAM which include single cameras, stereo pairs, multiple camera rigs and catadioptric sensors, (ii) features extracted from the environment in order to perform SLAM which include point features and line/edge features, (iii) initialisation of landmarks which can either be delayed or undelayed, (iv) SLAM techniques used which include Extended Kalman Filtering, Particle Filtering, biologically inspired techniques like RatSLAM, and other techniques like Local Bundle Adjustment, and (v) use of wheel odometry information. The paper also presents the implementation and analysis of stereo pair based EKF SLAM for synthetic data. Results prove the technique to work successfully in the presence of considerable amounts of sensor noise. We believe that state of the art presented in the paper can serve as a basis for future research in the area of vision based SLAM. It will permit further research in the area to be carried out in an efficient and application specific way.

Classification of damage in structural systems using time series analysis and supervised and unsupervised pattern recognition techniques

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr; de Lautour, Oliver R.

2010-04-01

Developed for studying long, periodic records of various measured quantities, time series analysis methods are inherently suited and offer interesting possibilities for Structural Health Monitoring (SHM) applications. However, their use in SHM can still be regarded as an emerging application and deserves more studies. In this research, Autoregressive (AR) models were used to fit experimental acceleration time histories from two experimental structural systems, a 3- storey bookshelf-type laboratory structure and the ASCE Phase II SHM Benchmark Structure, in healthy and several damaged states. The coefficients of the AR models were chosen as damage sensitive features. Preliminary visual inspection of the large, multidimensional sets of AR coefficients to check the presence of clusters corresponding to different damage severities was achieved using Sammon mapping - an efficient nonlinear data compression technique. Systematic classification of damage into states based on the analysis of the AR coefficients was achieved using two supervised classification techniques: Nearest Neighbor Classification (NNC) and Learning Vector Quantization (LVQ), and one unsupervised technique: Self-organizing Maps (SOM). This paper discusses the performance of AR coefficients as damage sensitive features and compares the efficiency of the three classification techniques using experimental data.

Syntactic priming in Chinese sentence comprehension: evidence from event-related potentials.

PubMed

Chen, Qingrong; Xu, Xiaodong; Tan, Dingliang; Zhang, Jingjing; Zhong, Yuan

2013-10-01

Using the event-related potential (ERP) technique, this study examined the nature of syntactic priming effects in Chinese. Participants were required to read prime-target sentence pairs each embedding an ambiguous relative clause (RC) containing either the same verb or a synonymous verb. In Chinese, the word de serves as a relative clause marker. During reading a potential Chinese RC structure (either the prime or the target sentence), Chinese readers initially expect to read an subject-verb-object (SVO) structure but the encounter of a relative clause marker de would make readers abandon the initial strategy and reanalyze the structure as a relative clause. A reduced P600 effect was elicited by the critical word de in the target sentence containing the same initial verb as in the prime sentence. No significant reduction of the P600 was observed in the target sentences in the synonymous condition. The results demonstrated that verb repetition but not similarity in meaning produced a syntactic priming effect in Chinese. The constraint-based lexicalist hypothesis and the argument structure theory were adopted to explain the syntactic priming effect obtained in the current study. Copyright © 2013 Elsevier Inc. All rights reserved.

Transforming reflectance spectra into Munsell color space by using prime colors.

PubMed

Romney, A Kimball; Fulton, James T

2006-10-17

Independent researchers have proved mathematically that, given a set of color-matching functions, there exists a unique set of three monochromatic spectral lights that optimizes luminous efficiency and color gamut. These lights are called prime colors. We present a method for transforming reflectance spectra into Munsell color space by using hypothetical absorbance curves based on Gaussian approximations of the prime colors and a simplified version of opponent process theory. The derived color appearance system is represented as a 3D color system that is qualitatively similar to a conceptual representation of the Munsell color system. We illustrate the application of the model and compare it with existing models by using reflectance spectra obtained from 1,269 Munsell color samples.

Prime-boost BCG vaccination with DNA vaccines based in β-defensin-2 and mycobacterial antigens ESAT6 or Ag85B improve protection in a tuberculosis experimental model

PubMed Central

Cervantes-Villagrana, Alberto R.; Hernández-Pando, Rogelio; Biragyn, Arya; Castañeda-Delgado, Julio; Bodogai, Monica; Martínez-Fierro, Margarita; Sada, Eduardo; Trujillo, Valentin; Enciso-Moreno, Antonio; Rivas-Santiago, Bruno

2018-01-01

The World Health Organization (WHO) has estimated that there are about 8 million new cases annually of active Tuberculosis (TB). Despite its irregular effectiveness (0–89%), the Bacillus Calmette-Guérin) BCG is the only vaccine available worldwide for prevention of TB; thus, the design is important of novel and more efficient vaccination strategies. Considering that β-defensin-2 is an antimicrobial peptide that induces dendritic cell maturation through the TLR-4 receptor and that both ESAT-6 and Ag85B are immunodominant mycobacterial antigens and efficient activators of the protective immune response, we constructed two DNA vaccines by the fusion of the gene encoding β-defensin-2 and antigens ESAT6 (pDE) and 85B (pDA). After confirming efficient local antigen expression that induced high and stable Interferon gamma (IFN-γ) production in intramuscular (i.m.) vaccinated Balb/c mice, groups of mice were vaccinated with DNA vaccines in a prime-boost regimen with BCG and with BCG alone, and 2 months later were challenged with the mild virulence reference strain H37Rv and the highly virulent clinical isolate LAM 5186. The level of protection was evaluated by survival, lung bacilli burdens, and extension of tissue damage (pneumonia). Vaccination with both DNA vaccines showed similar protection to that of BCG. After the challenge with the highly virulent Mycobacterium tuberculosis strain, animals that were prime-boosted with BCG and then boosted with both DNA vaccines showed significant higher survival and less tissue damage than mice vaccinated only with BCG. These results suggest that improvement of BCG vaccination, such as the prime-boost DNA vaccine, represents a more efficient vaccination scheme against TB. PMID:23196205

Analgesic effect of Facebook: Priming with online social networking may boost felt relatedness that buffers against physical pain.

PubMed

Ho, Liang-Chu; Wu, Wen-Hsiung; Chiou, Wen-Bin

2016-10-01

Social networking sites (SNSs) are extremely popular for providing users with a convenient platform for acquiring social connections and thereby feeling relatedness. Plenty of literature has shown that mental representations of social support can reduce the perception of physical pain. The current study tested whether thinking about SNS would interfere with users' perceptions of experimentally induced pain. Ninety-six undergraduate Facebook users were recruited to participate in a priming-based experiment. They were randomly assigned to one of the three study conditions (SNS prime, neutral prime, or no prime) via rating the aesthetics of logos. The results showed that participants exposed to SNS primes reported less pain of immersion in hot water than did both control groups (neutral- and no-prime). Felt relatedness mediated the link between SNS primes and diminished pain perceptions. This research provides the first demonstration that thinking about SNS can lower experienced physical pain among Facebook users. Online social networking may serve as an analgesic buffer against pain experience than previously thought. The SNS-enabled analgesia has far reaching implications for pain relief applications and the enhancement of well-being in human-interaction techniques. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

A subliminal inhibitory mechanism for the negative compatibility effect: a continuous versus threshold mechanism.

PubMed

Liu, Peng; Chen, Xuhai; Dai, Dongyang; Wang, Yongchun; Wang, Yonghui

2014-07-01

The current study investigated the mechanism underlying subliminal inhibition using the negative compatibility effect (NCE) paradigm. We hypothesized that a decrease in prime activation affects the subsequent inhibitory process, delaying onset of inhibition and reducing its strength. Two experiments tested this hypothesis using arrow stimuli as primes and targets. Two different irrelevant masks (i.e., a mask sharing no prime features) were presented in succession in each trial to not only ensure that primes were processed subliminally, but also avoid feature updating between primes and masks. Prime/target compatibility and prime background density were manipulated in Experiment 1. Results showed that under subliminal inhibitory condition, the NCE disappears when the density increases (i.e., pixel density in the prime's background of 25 %) in Experiment 1. However, when we fixed the prime's background at the density of 25 % and manipulated prime/target compatibility as well as inter-stimuli-interval (ISI) between mask and target in Experiment 2, behavioral results showed marginally significant NCEs in the 150-ms ISI condition. Electrophysiological evidence showed the lateralized readiness potential for compatible trials was significantly more positive than that for incompatible trials during the two consecutive time windows (i.e., 400-450 and 450-500 ms) in the 150-ms ISI condition. In addition, the NCE size was significant smaller in Experiment 2 than in Experiment 1. All of the results support predictions of the continuous subliminal inhibitory mechanism hypothesis which posits that decreases in prime activation strength lead to delay in inhibitory onset and decline in inhibitory strength.

2D DOST based local phase pattern for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.

Priming of microglia in a DNA-repair deficient model of accelerated aging.

PubMed

Raj, Divya D A; Jaarsma, Dick; Holtman, Inge R; Olah, Marta; Ferreira, Filipa M; Schaafsma, Wandert; Brouwer, Nieske; Meijer, Michel M; de Waard, Monique C; van der Pluijm, Ingrid; Brandt, Renata; Kreft, Karim L; Laman, Jon D; de Haan, Gerald; Biber, Knut P H; Hoeijmakers, Jan H J; Eggen, Bart J L; Boddeke, Hendrikus W G M

2014-09-01

Aging is associated with reduced function, degenerative changes, and increased neuroinflammation of the central nervous system (CNS). Increasing evidence suggests that changes in microglia cells contribute to the age-related deterioration of the CNS. The most prominent age-related change of microglia is enhanced sensitivity to inflammatory stimuli, referred to as priming. It is unclear if priming is due to intrinsic microglia ageing or induced by the ageing neural environment. We have studied this in Ercc1 mutant mice, a DNA repair-deficient mouse model that displays features of accelerated aging in multiple tissues including the CNS. In Ercc1 mutant mice, microglia showed hallmark features of priming such as an exaggerated response to peripheral lipopolysaccharide exposure in terms of cytokine expression and phagocytosis. Specific targeting of the Ercc1 deletion to forebrain neurons resulted in a progressive priming response in microglia exemplified by phenotypic alterations. Summarizing, these data show that neuronal genotoxic stress is sufficient to switch microglia from a resting to a primed state. Copyright © 2014 Elsevier Inc. All rights reserved.

Algorithms for computing solvents of unilateral second-order matrix polynomials over prime finite fields using lambda-matrices

NASA Astrophysics Data System (ADS)

Burtyka, Filipp

2018-01-01

The paper considers algorithms for finding diagonalizable and non-diagonalizable roots (so called solvents) of monic arbitrary unilateral second-order matrix polynomial over prime finite field. These algorithms are based on polynomial matrices (lambda-matrices). This is an extension of existing general methods for computing solvents of matrix polynomials over field of complex numbers. We analyze how techniques for complex numbers can be adapted for finite field and estimate asymptotic complexity of the obtained algorithms.

MATERIALS SCIENCE: New Tigers in the Fuel Cell Tank.

PubMed

Service, R F

2000-06-16

After decades of incremental advances, a spurt of findings suggests that fuel cells that run on good old fossil fuels are almost ready for prime time. Although conventional ceramic cells, known as solid oxide fuel cells, require expensive heat-resistant materials, a new generation of SOFCs, including one featured on page 2031, converts hydrocarbons directly into electricity at lower temperatures. And a recent demonstration of a system of standard SOFCs large enough to light up more than 200 homes showed that it is the most efficient large-scale electrical generator ever designed.

Temporal parameters and time course of perceptual latency priming.

PubMed

Scharlau, Ingrid; Neumann, Odmar

2003-06-01

Visual stimuli (primes) reduce the perceptual latency of a target appearing at the same location (perceptual latency priming, PLP). Three experiments assessed the time course of PLP by masked and, in Experiment 3, unmasked primes. Experiments 1 and 2 investigated the temporal parameters that determine the size of priming. Stimulus onset asynchrony was found to exert the main influence accompanied by a small effect of prime duration. Experiment 3 used a large range of priming onset asynchronies. We suggest to explain PLP by the Asynchronous Updating Model which relates it to the asynchrony of 2 central coding processes, preattentive coding of basic visual features and attentional orienting as a prerequisite for perceptual judgments and conscious perception.

STUDIES ON THE SENSITIZATION OF ANIMALS WITH SIMPLE CHEMICAL COMPOUNDS

PubMed Central

Maguire, Henry C.; Chase, Merrill W.

1972-01-01

A method of establishing regular and intense sensitivity to picric acid is described, based upon an initial sensitization by a "split-adjuvant" technique in which the intradermal injection of mycobacteria in paraffin oil precedes or follows the administration of allergen to the same sites. When subsequent contact applications of picric acid are later made, the degree of sensitivity rises in steps such that reactivity occurs in tests made with low concentrations of picric acid, in the range of 0.06–0.006% but varying somewhat from one experiment to another. This heightening of picric acid reactivity represents an anamnestic response in the area of delayed hypersensitivity. The characteristics of contact reactions to the weak allergen, picric acid, differ from those encountered with covalently binding haptens, PCI and DNCB. A slow evolution from an initial micropapular reaction to full reaction requires about 3 days, leading often to a micaceous scale, with histological evidence of vesiculation even while the reaction is still feeble, and to an infiltrate containing a significant number of polymorphonuclear leukocytes. Substitution of an emulsion of picric acid in complete Freund's adjuvant as a priming experience proved to be much less efficient. The split-adjuvant technique offers a general plan for sensitizing with weak allergens. Indeed, technically, sensitization can be acquired even when, for priming, the allergen is applied topically over intradermal depots of mycobacteria in paraffin oil. Compatibility between sensitizer and adjuvant is not required. PMID:5060294

Improved tolerance to post-anthesis drought stress by pre-drought priming at vegetative stages in drought-tolerant and -sensitive wheat cultivars.

PubMed

Abid, Muhammad; Tian, Zhongwei; Ata-Ul-Karim, Syed Tahir; Liu, Yang; Cui, Yakun; Zahoor, Rizwan; Jiang, Dong; Dai, Tingbo

2016-09-01

Wheat crop endures a considerable penalty of yield reduction to escape the drought events during post-anthesis period. Drought priming under a pre-drought stress can enhance the crop potential to tolerate the subsequent drought stress by triggering a faster and stronger defense mechanism. Towards these understandings, a set of controlled moderate drought stress at 55-60% field capacity (FC) was developed to prime the plants of two wheat cultivars namely Luhan-7 (drought tolerant) and Yangmai-16 (drought sensitive) during tillering (Feekes 2 stage) and jointing (Feekes 6 stage), respectively. The comparative response of primed and non-primed plants, cultivars and priming stages was evaluated by applying a subsequent severe drought stress at 7 days after anthesis. The results showed that primed plants of both cultivars showed higher potential to tolerate the post-anthesis drought stress through improved leaf water potential, more chlorophyll, and ribulose-1, 5-bisphosphate carboxylase/oxygenase contents, enhanced photosynthesis, better photoprotection and efficient enzymatic antioxidant system leading to less yield reductions. The primed plants of Luhan-7 showed higher capability to adapt the drought stress events than Yangmai-16. The positive effects of drought priming to sustain higher grain yield were pronounced in plants primed at tillering than those primed at jointing. In consequence, upregulated functioning of photosynthetic apparatus and efficient enzymatic antioxidant activities in primed plants indicated their superior potential to alleviate a subsequently occurring drought stress, which contributed to lower yield reductions than non-primed plants. However, genotypic and priming stages differences in response to drought stress also contributed to affect the capability of primed plants to tolerate the post-anthesis drought stress conditions in wheat. Copyright © 2016. Published by Elsevier Masson SAS.

Advances in Alkenone Paleotemperature Proxies: Analytical Methods, Novel Structures and Haptophyte Species, Biosynthesis, New indices and Ecological Aspects

NASA Astrophysics Data System (ADS)

Huang, Y.; Longo, W. M.; Zheng, Y.; Richter, N.; Dillon, J. T.; Theroux, S.; D'Andrea, W. J.; Toney, J. L.; Wang, L.; Amaral-Zettler, L. A.

2017-12-01

Alkenones are mature, well-established paleo-sea surface temperature proxies that have been widely applied for more than three decades. However, recent advances across a broad range of alkenone-related topics at Brown University are inviting new paleoclimate and paleo-environmental applications for these classic biomarkers. In this presentation, I will summarize our progress in the following areas: (1) Discovery of a freshwater alkenone-producing haptophyte species and structural elucidation of novel alkenone structures unique to the species, performing in-situ temperature calibrations, and classifying alkenone-producing haptophytes into three groups based on molecular ecological approaches (with the new species belonging to Group I Isochrysidales); (2) A global survey of Group I haptophyte distributions and environmental conditions favoring the presence of this alga, as well as examples of using Group I alkenones for paleotemperature reconstructions; (3) New gas chromatographic columns that allow unprecedented resolution of alkenones and alkenoates and associated structural isomers, and development of a new suite of paleotemperature and paleoenvironmental proxies; (4) A new liquid chromatographic separation technique that allows efficient cleanup of alkenones and alkenoates (without the need for saponification) for subsequent coelution-free gas chromatographic analysis; (5) Novel structural features revealed by new analytical methods that now allow a comprehensive re-assessment of taxonomic features of various haptophyte species, with principal component analysis capable of fully resolving species biomarker distributions; (6) Development of UK37 double prime (UK37'') for Group II haptophytes (e.g., those occurring in saline lakes and estuaries), that differs from the traditional unsaturation indices used for SST reconstructions; (7) New assessment of how mixed inputs from different alkenone groups may affect SST reconstructions in marginal ocean environments and possible approaches to solving the problem; and, (8) Optimization of analytical methods for determining the double-bond positions of alkenones and alkenoates, and subsequent discovery of new structural features of short-chain alkenones and the proposal of new biosynthetic pathways.

Next Day Building Load Predictions based on Limited Input Features Using an On-Line Laterally Primed Adaptive Resonance Theory Artificial Neural Network.

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

Jones, Christian Birk; Robinson, Matt; Yasaei, Yasser

Optimal integration of thermal energy storage within commercial building applications requires accurate load predictions. Several methods exist that provide an estimate of a buildings future needs. Methods include component-based models and data-driven algorithms. This work implemented a previously untested algorithm for this application that is called a Laterally Primed Adaptive Resonance Theory (LAPART) artificial neural network (ANN). The LAPART algorithm provided accurate results over a two month period where minimal historical data and a small amount of input types were available. These results are significant, because common practice has often overlooked the implementation of an ANN. ANN have often beenmore » perceived to be too complex and require large amounts of data to provide accurate results. The LAPART neural network was implemented in an on-line learning manner. On-line learning refers to the continuous updating of training data as time occurs. For this experiment, training began with a singe day and grew to two months of data. This approach provides a platform for immediate implementation that requires minimal time and effort. The results from the LAPART algorithm were compared with statistical regression and a component-based model. The comparison was based on the predictions linear relationship with the measured data, mean squared error, mean bias error, and cost savings achieved by the respective prediction techniques. The results show that the LAPART algorithm provided a reliable and cost effective means to predict the building load for the next day.« less

High-efficiency single cell encapsulation and size selective capture of cells in picoliter droplets based on hydrodynamic micro-vortices.

PubMed

Kamalakshakurup, Gopakumar; Lee, Abraham P

2017-12-05

Single cell analysis has emerged as a paradigm shift in cell biology to understand the heterogeneity of individual cells in a clone for pathological interrogation. Microfluidic droplet technology is a compelling platform to perform single cell analysis by encapsulating single cells inside picoliter-nanoliter (pL-nL) volume droplets. However, one of the primary challenges for droplet based single cell assays is single cell encapsulation in droplets, currently achieved either randomly, dictated by Poisson statistics, or by hydrodynamic techniques. In this paper, we present an interfacial hydrodynamic technique which initially traps the cells in micro-vortices, and later releases them one-to-one into the droplets, controlled by the width of the outer streamline that separates the vortex from the flow through the streaming passage adjacent to the aqueous-oil interface (d gap ). One-to-one encapsulation is achieved at a d gap equal to the radius of the cell, whereas complete trapping of the cells is realized at a d gap smaller than the radius of the cell. The unique feature of this technique is that it can perform 1. high efficiency single cell encapsulations and 2. size-selective capturing of cells, at low cell loading densities. Here we demonstrate these two capabilities with a 50% single cell encapsulation efficiency and size selective separation of platelets, RBCs and WBCs from a 10× diluted blood sample (WBC capture efficiency at 70%). The results suggest a passive, hydrodynamic micro-vortex based technique capable of performing high-efficiency single cell encapsulation for cell based assays.

News video story segmentation method using fusion of audio-visual features

NASA Astrophysics Data System (ADS)

Wen, Jun; Wu, Ling-da; Zeng, Pu; Luan, Xi-dao; Xie, Yu-xiang

2007-11-01

News story segmentation is an important aspect for news video analysis. This paper presents a method for news video story segmentation. Different form prior works, which base on visual features transform, the proposed technique uses audio features as baseline and fuses visual features with it to refine the results. At first, it selects silence clips as audio features candidate points, and selects shot boundaries and anchor shots as two kinds of visual features candidate points. Then this paper selects audio feature candidates as cues and develops different fusion method, which effectively using diverse type visual candidates to refine audio candidates, to get story boundaries. Experiment results show that this method has high efficiency and adaptability to different kinds of news video.

[Does Emotional Context Affect Subliminal and Supraliminal Priming?].

PubMed

Baran, Zeynel; Cangöz, Banu; Salman, Funda

2016-01-01

Emotions are complex psychophysiological changes experienced during the interactions of internal and external processes. The stimuli that have emotional value have processing efficiency both in encoding and retrieval processes with respect to the neutral stimuli. Processing advantage is present also for implicit memory. Priming effect does not require conscious recollection and leads to changes in responding due to previous exposure to the stimulus. In this study, it was aimed to investigate the effect of presentation type and different emotional contexts on the priming. Sixty-volunteered-university-students were (Female: n=40, X age=19.03±1.23; Male: n=20, X age=19.70±1.92) randomly assigned to the experimental conditions. Presentation type (Subliminal and Supraliminal) was between subject and Emotional Context (pleasant, neutral, and unpleasant pictures) was within subject independent variables. Dependent variables were Word Stem Completion score and completion latencies. Unpleasant emotional context had more capacity to create priming effect than the other emotional contexts. Both Subliminal and Supraliminal conditions favored the priming. Controversially to the transfer appropriate processing approach, the priming effect that was produced by supraliminal condition significantly higher than the priming created by the subliminal condition. Unpleasant picture context produced more priming due to reason that evolutionarily important, i.e. thread-related, stimuli have processing priority and they capture the attention, utilize other cognitive resources easily. Even in priming, that is a phenomenon based heavily on data driven processes, concept driven processes are also effectual as indicated by levels-of-processing approach.

Selecting Feature Subsets Based on SVM-RFE and the Overlapping Ratio with Applications in Bioinformatics.

PubMed

Lin, Xiaohui; Li, Chao; Zhang, Yanhui; Su, Benzhe; Fan, Meng; Wei, Hai

2017-12-26

Feature selection is an important topic in bioinformatics. Defining informative features from complex high dimensional biological data is critical in disease study, drug development, etc. Support vector machine-recursive feature elimination (SVM-RFE) is an efficient feature selection technique that has shown its power in many applications. It ranks the features according to the recursive feature deletion sequence based on SVM. In this study, we propose a method, SVM-RFE-OA, which combines the classification accuracy rate and the average overlapping ratio of the samples to determine the number of features to be selected from the feature rank of SVM-RFE. Meanwhile, to measure the feature weights more accurately, we propose a modified SVM-RFE-OA (M-SVM-RFE-OA) algorithm that temporally screens out the samples lying in a heavy overlapping area in each iteration. The experiments on the eight public biological datasets show that the discriminative ability of the feature subset could be measured more accurately by combining the classification accuracy rate with the average overlapping degree of the samples compared with using the classification accuracy rate alone, and shielding the samples in the overlapping area made the calculation of the feature weights more stable and accurate. The methods proposed in this study can also be used with other RFE techniques to define potential biomarkers from big biological data.

A generative, probabilistic model of local protein structure.

PubMed

Boomsma, Wouter; Mardia, Kanti V; Taylor, Charles C; Ferkinghoff-Borg, Jesper; Krogh, Anders; Hamelryck, Thomas

2008-07-01

Despite significant progress in recent years, protein structure prediction maintains its status as one of the prime unsolved problems in computational biology. One of the key remaining challenges is an efficient probabilistic exploration of the structural space that correctly reflects the relative conformational stabilities. Here, we present a fully probabilistic, continuous model of local protein structure in atomic detail. The generative model makes efficient conformational sampling possible and provides a framework for the rigorous analysis of local sequence-structure correlations in the native state. Our method represents a significant theoretical and practical improvement over the widely used fragment assembly technique by avoiding the drawbacks associated with a discrete and nonprobabilistic approach.

Soil moisture sensing via swept frequency based microwave sensors

USDA-ARS?s Scientific Manuscript database

Accurate measurement of moisture content is a prime requirement in hydrological, geophysical, and biogeochemical research as well as for material characterization, process control, and irrigation efficiency in water limited regions. Within these areas, consideration of the surface area and associate...

Perceiving age and gender in unfamiliar faces: brain potential evidence for implicit and explicit person categorization.

PubMed

Wiese, Holger; Schweinberger, Stefan R; Neumann, Markus F

2008-11-01

We used repetition priming to investigate implicit and explicit processes of unfamiliar face categorization. During prime and test phases, participants categorized unfamiliar faces according to either age or gender. Faces presented at test were either new or primed in a task-congruent (same task during priming and test) or incongruent (different tasks) condition. During age categorization, reaction times revealed significant priming for both priming conditions, and event-related potentials yielded an increased N170 over the left hemisphere as a result of priming. During gender categorization, congruent faces elicited priming and a latency decrease in the right N170. Accordingly, information about age is extracted irrespective of processing demands, and priming facilitates the extraction of feature information reflected in the left N170 effect. By contrast, priming of gender categorization may depend on whether the task at initial presentation requires configural processing.

What's in a face? The role of skin tone, facial physiognomy, and color presentation mode of facial primes in affective priming effects.

PubMed

Stepanova, Elena V; Strube, Michael J

2012-01-01

Participants (N = 106) performed an affective priming task with facial primes that varied in their skin tone and facial physiognomy, and, which were presented either in color or in gray-scale. Participants' racial evaluations were more positive for Eurocentric than for Afrocentric physiognomy faces. Light skin tone faces were evaluated more positively than dark skin tone faces, but the magnitude of this effect depended on the mode of color presentation. The results suggest that in affective priming tasks, faces might not be processed holistically, and instead, visual features of facial priming stimuli independently affect implicit evaluations.

Structural priming is a useful but imperfect technique for studying all linguistic representations, including those of pragmatics.

PubMed

Rees, Alice; Bott, Lewis

2017-01-01

Structural priming is a useful tool for investigating linguistics representations. We argue that structural priming can be extended to the investigation of pragmatic representations such as Gricean enrichments. That is not to say priming is without its limitations, however. Interpreting a failure to observe priming may not be as simple as Branigan & Pickering (B&P) imply.

Hemispheric Inference Priming during Comprehension of Conversations and Narratives

ERIC Educational Resources Information Center

Powers, Chivon; Bencic, Rachel; Horton, William S.; Beeman, Mark

2012-01-01

In this study we examined asymmetric semantic activation patterns as people listened to conversations and narratives that promoted causal inferences. Based on the hypothesis that understanding the unique features of conversational input may benefit from or require a modified pattern of conceptual activation during conversation, we compared…

The Role of Trustworthiness in Teaching: An Examination of "The Prime of Miss Jean Brodie"

ERIC Educational Resources Information Center

Katz, Michael S.

2014-01-01

The purpose of this paper is to examine the role that trustworthiness plays in the ability of teachers to function as moral role models. Through exploration of Muriel Spark's novel, "The Prime of Miss Jean Brodie," I explain some of the central features of trustworthiness as a moral virtue and suggest how these features are critical…

The Effect of Priming on Referential Communication in Four Year Olds.

ERIC Educational Resources Information Center

Foorman, Barbara R.

A study was conducted in light of a neo-Piagetian theory of cognitive development to interpret the effect of priming executive schemes for describing relevant features in a referential communication task. Forty-eight 4-year-old children were divided into primed and nonprimed groups and were asked to describe in isolation a black and white…

Long-Term Priming of Visual Search Prevails against the Passage of Time and Counteracting Instructions

ERIC Educational Resources Information Center

Kruijne, Wouter; Meeter, Martijn

2016-01-01

Studies on "intertrial priming" have shown that in visual search experiments, the preceding trial automatically affects search performance: facilitating it when the target features repeat and giving rise to switch costs when they change--so-called (short-term) intertrial priming. These effects also occur at longer time scales: When 1 of…

Independent priming of location and color in identification of briefly presented letters.

PubMed

Ásgeirsson, Árni Gunnar; Kristjánsson, Árni; Bundesen, Claus

2014-01-01

Attention shifts are facilitated if the items to be attended remain the same across trials. Some researchers argue that this priming effect is perceptual, whereas others propose that priming is postperceptual, involving facilitated response selection. The experimental findings have not been consistent regarding the roles of variables such as task difficulty, response repetition, expectancies, and decision-making. Position priming, when repetition of a target position facilitates responses on a subsequent trial, is another source of disagreement among researchers. Experimental results have likewise been inconsistent as to whether position priming is dependent on the repetition of target features or has an independent effect on attention shifts. We attempted to isolate the perceptual components of priming by presenting brief (10-180 ms) search arrays to eight healthy observers. The task was to identify a color-singleton letter among distractors. All stimulus presentation contingencies were randomized, and responses were unspeeded, to avoid effects of observer expectation and postperceptual effects. Repeating target color and/or position strongly improved performance. The effects of color and position repetition were independent of one another and were stable across participants. The results argue for a strong perceptual component in priming, which biases selection toward recent target features and positions, showing that perceptual mechanisms are sufficient to produce priming in visual search and that such effects can be elicited with limited sensory evidence. The results are the first to demonstrate independent priming of color and position in the identification of briefly presented, postmasked stimuli.

iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space.

PubMed

Akbar, Shahid; Hayat, Maqsood; Iqbal, Muhammad; Jan, Mian Ahmad

2017-06-01

Cancer is a fatal disease, responsible for one-quarter of all deaths in developed countries. Traditional anticancer therapies such as, chemotherapy and radiation, are highly expensive, susceptible to errors and ineffective techniques. These conventional techniques induce severe side-effects on human cells. Due to perilous impact of cancer, the development of an accurate and highly efficient intelligent computational model is desirable for identification of anticancer peptides. In this paper, evolutionary intelligent genetic algorithm-based ensemble model, 'iACP-GAEnsC', is proposed for the identification of anticancer peptides. In this model, the protein sequences are formulated, using three different discrete feature representation methods, i.e., amphiphilic Pseudo amino acid composition, g-Gap dipeptide composition, and Reduce amino acid alphabet composition. The performance of the extracted feature spaces are investigated separately and then merged to exhibit the significance of hybridization. In addition, the predicted results of individual classifiers are combined together, using optimized genetic algorithm and simple majority technique in order to enhance the true classification rate. It is observed that genetic algorithm-based ensemble classification outperforms than individual classifiers as well as simple majority voting base ensemble. The performance of genetic algorithm-based ensemble classification is highly reported on hybrid feature space, with an accuracy of 96.45%. In comparison to the existing techniques, 'iACP-GAEnsC' model has achieved remarkable improvement in terms of various performance metrics. Based on the simulation results, it is observed that 'iACP-GAEnsC' model might be a leading tool in the field of drug design and proteomics for researchers. Copyright © 2017 Elsevier B.V. All rights reserved.

Image detection and compression for memory efficient system analysis

NASA Astrophysics Data System (ADS)

Bayraktar, Mustafa

2015-02-01

The advances in digital signal processing have been progressing towards efficient use of memory and processing. Both of these factors can be utilized efficiently by using feasible techniques of image storage by computing the minimum information of image which will enhance computation in later processes. Scale Invariant Feature Transform (SIFT) can be utilized to estimate and retrieve of an image. In computer vision, SIFT can be implemented to recognize the image by comparing its key features from SIFT saved key point descriptors. The main advantage of SIFT is that it doesn't only remove the redundant information from an image but also reduces the key points by matching their orientation and adding them together in different windows of image [1]. Another key property of this approach is that it works on highly contrasted images more efficiently because it`s design is based on collecting key points from the contrast shades of image.

Low Power LDPC Code Decoder Architecture Based on Intermediate Message Compression Technique

NASA Astrophysics Data System (ADS)

Shimizu, Kazunori; Togawa, Nozomu; Ikenaga, Takeshi; Goto, Satoshi

Reducing the power dissipation for LDPC code decoder is a major challenging task to apply it to the practical digital communication systems. In this paper, we propose a low power LDPC code decoder architecture based on an intermediate message-compression technique which features as follows: (i) An intermediate message compression technique enables the decoder to reduce the required memory capacity and write power dissipation. (ii) A clock gated shift register based intermediate message memory architecture enables the decoder to decompress the compressed messages in a single clock cycle while reducing the read power dissipation. The combination of the above two techniques enables the decoder to reduce the power dissipation while keeping the decoding throughput. The simulation results show that the proposed architecture improves the power efficiency up to 52% and 18% compared to that of the decoder based on the overlapped schedule and the rapid convergence schedule without the proposed techniques respectively.

Rotation Covariant Image Processing for Biomedical Applications

PubMed Central

Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences. PMID:23710255

Steganography based on pixel intensity value decomposition

NASA Astrophysics Data System (ADS)

Abdulla, Alan Anwar; Sellahewa, Harin; Jassim, Sabah A.

2014-05-01

This paper focuses on steganography based on pixel intensity value decomposition. A number of existing schemes such as binary, Fibonacci, Prime, Natural, Lucas, and Catalan-Fibonacci (CF) are evaluated in terms of payload capacity and stego quality. A new technique based on a specific representation is proposed to decompose pixel intensity values into 16 (virtual) bit-planes suitable for embedding purposes. The proposed decomposition has a desirable property whereby the sum of all bit-planes does not exceed the maximum pixel intensity value, i.e. 255. Experimental results demonstrate that the proposed technique offers an effective compromise between payload capacity and stego quality of existing embedding techniques based on pixel intensity value decomposition. Its capacity is equal to that of binary and Lucas, while it offers a higher capacity than Fibonacci, Prime, Natural, and CF when the secret bits are embedded in 1st Least Significant Bit (LSB). When the secret bits are embedded in higher bit-planes, i.e., 2nd LSB to 8th Most Significant Bit (MSB), the proposed scheme has more capacity than Natural numbers based embedding. However, from the 6th bit-plane onwards, the proposed scheme offers better stego quality. In general, the proposed decomposition scheme has less effect in terms of quality on pixel value when compared to most existing pixel intensity value decomposition techniques when embedding messages in higher bit-planes.

Inhibitory control efficiency in a Piaget-like class-inclusion task in school-age children and adults: a developmental negative priming study.

PubMed

Borst, G; Poirel, N; Pineau, A; Cassotti, M; Houdé, O

2013-07-01

Most children under 7 years of age presented with 10 daisies and 2 roses fail to indicate that there are more flowers than daisies. Instead of the appropriate comparison of the relative numerosities of the superordinate class (flowers) to its subordinate class (daisies), they perform a direct perceptual comparison of the extensions of the 2 subordinate classes (daisies vs. roses). In our experiment, we investigated whether increasing efficiency in solving the Piagetian class-inclusion task is related to increasing efficiency in the ability to resist (inhibit) this direct comparison of the subordinate classes' extensions. Ten-year-old and young adult participants performed a computerized priming version of a Piaget-like class-inclusion task. The experimental design was such that the misleading perceptual strategy to inhibit on the prime (in which a superordinate class had to be compared with a subordinate class) became a congruent strategy to activate on the probe (in which the two subordinate classes' extensions were directly compared). We found a negative priming effect of 291 ms in children and 129 ms in adults. These results provide evidence for the first time (a) that adults still need to inhibit the comparison of the subordinate classes' extensions in class-inclusion tasks and (b) that the ability to inhibit this heuristic increases with age (resulting in a lower executive cost). Taken together, these findings provide additional support for the neo-Piagetian approach of cognitive development that suggests that the acquisition of increasingly complex knowledge is based on the ability to resist (inhibit) heuristics and previously acquired knowledge.

An ERP investigation of visual word recognition in syllabary scripts.

PubMed

Okano, Kana; Grainger, Jonathan; Holcomb, Phillip J

2013-06-01

The bimodal interactive-activation model has been successfully applied to understanding the neurocognitive processes involved in reading words in alphabetic scripts, as reflected in the modulation of ERP components in masked repetition priming. In order to test the generalizability of this approach, in the present study we examined word recognition in a different writing system, the Japanese syllabary scripts hiragana and katakana. Native Japanese participants were presented with repeated or unrelated pairs of Japanese words in which the prime and target words were both in the same script (within-script priming, Exp. 1) or were in the opposite script (cross-script priming, Exp. 2). As in previous studies with alphabetic scripts, in both experiments the N250 (sublexical processing) and N400 (lexical-semantic processing) components were modulated by priming, although the time course was somewhat delayed. The earlier N/P150 effect (visual feature processing) was present only in "Experiment 1: Within-script priming", in which the prime and target words shared visual features. Overall, the results provide support for the hypothesis that visual word recognition involves a generalizable set of neurocognitive processes that operate in similar manners across different writing systems and languages, as well as pointing to the viability of the bimodal interactive-activation framework for modeling such processes.

Scheduling Algorithm for the Large Synoptic Survey Telescope

NASA Astrophysics Data System (ADS)

Ichharam, Jaimal; Stubbs, Christopher

2015-01-01

The Large Synoptic Survey Telescope (LSST) is a wide-field telescope currently under construction and scheduled to be deployed in Chile by 2022 and operate for a ten-year survey. As a ground-based telescope with the largest etendue ever constructed, and the ability to take images approximately once every eighteen seconds, the LSST will be able to capture the entirety of the observable sky every few nights in six different band passes. With these remarkable features, LSST is primed to provide the scientific community with invaluable data in numerous areas of astronomy, including the observation of near-Earth asteroids, the detection of transient optical events such as supernovae, and the study of dark matter and energy through weak gravitational lensing.In order to maximize the utility that LSST will provide toward achieving these scientific objectives, it proves necessary to develop a flexible scheduling algorithm for the telescope which both optimizes its observational efficiency and allows for adjustment based on the evolving needs of the astronomical community.This work defines a merit function that incorporates the urgency of observing a particular field in the sky as a function of time elapsed since last observed, dynamic viewing conditions (in particular transparency and sky brightness), and a measure of scientific interest in the field. The problem of maximizing this merit function, summed across the entire observable sky, is then reduced to a classic variant of the dynamic traveling salesman problem. We introduce a new approximation technique that appears particularly well suited for this situation. We analyze its effectiveness in resolving this problem, obtaining some promising initial results.

Efficacy Evaluation of Different Wavelet Feature Extraction Methods on Brain MRI Tumor Detection

NASA Astrophysics Data System (ADS)

Nabizadeh, Nooshin; John, Nigel; Kubat, Miroslav

2014-03-01

Automated Magnetic Resonance Imaging brain tumor detection and segmentation is a challenging task. Among different available methods, feature-based methods are very dominant. While many feature extraction techniques have been employed, it is still not quite clear which of feature extraction methods should be preferred. To help improve the situation, we present the results of a study in which we evaluate the efficiency of using different wavelet transform features extraction methods in brain MRI abnormality detection. Applying T1-weighted brain image, Discrete Wavelet Transform (DWT), Discrete Wavelet Packet Transform (DWPT), Dual Tree Complex Wavelet Transform (DTCWT), and Complex Morlet Wavelet Transform (CMWT) methods are applied to construct the feature pool. Three various classifiers as Support Vector Machine, K Nearest Neighborhood, and Sparse Representation-Based Classifier are applied and compared for classifying the selected features. The results show that DTCWT and CMWT features classified with SVM, result in the highest classification accuracy, proving of capability of wavelet transform features to be informative in this application.

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Priming and the guidance by visual and categorical templates in visual search.

PubMed

Wilschut, Anna; Theeuwes, Jan; Olivers, Christian N L

2014-01-01

Visual search is thought to be guided by top-down templates that are held in visual working memory. Previous studies have shown that a search-guiding template can be rapidly and strongly implemented from a visual cue, whereas templates are less effective when based on categorical cues. Direct visual priming from cue to target may underlie this difference. In two experiments we first asked observers to remember two possible target colors. A postcue then indicated which of the two would be the relevant color. The task was to locate a briefly presented and masked target of the cued color among irrelevant distractor items. Experiment 1 showed that overall search accuracy improved more rapidly on the basis of a direct visual postcue that carried the target color, compared to a neutral postcue that pointed to the memorized color. However, selectivity toward the target feature, i.e., the extent to which observers searched selectively among items of the cued vs. uncued color, was found to be relatively unaffected by the presence of the visual signal. In Experiment 2 we compared search that was based on either visual or categorical information, but now controlled for direct visual priming. This resulted in no differences in overall performance nor selectivity. Altogether the results suggest that perceptual processing of visual search targets is facilitated by priming from visual cues, whereas attentional selectivity is enhanced by a working memory template that can formed from both visual and categorical input. Furthermore, if the priming is controlled for, categorical- and visual-based templates similarly enhance search guidance.

Visual Priming of Inverted and Rotated Objects

ERIC Educational Resources Information Center

Knowlton, Barbara J.; McAuliffe, Sean P.; Coelho, Chase J.; Hummel, John E.

2009-01-01

Object images are identified more efficiently after prior exposure. Here, the authors investigated shape representations supporting object priming. The dependent measure in all experiments was the minimum exposure duration required to correctly identify an object image in a rapid serial visual presentation stream. Priming was defined as the change…

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

PubMed

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities

NASA Astrophysics Data System (ADS)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

Coding visual features extracted from video sequences.

PubMed

Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2014-05-01

Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.

A robust indicator based on singular value decomposition for flaw feature detection from noisy ultrasonic signals

NASA Astrophysics Data System (ADS)

Cui, Ximing; Wang, Zhe; Kang, Yihua; Pu, Haiming; Deng, Zhiyang

2018-05-01

Singular value decomposition (SVD) has been proven to be an effective de-noising tool for flaw echo signal feature detection in ultrasonic non-destructive evaluation (NDE). However, the uncertainty in the arbitrary manner of the selection of an effective singular value weakens the robustness of this technique. Improper selection of effective singular values will lead to bad performance of SVD de-noising. What is more, the computational complexity of SVD is too large for it to be applied in real-time applications. In this paper, to eliminate the uncertainty in SVD de-noising, a novel flaw indicator, named the maximum singular value indicator (MSI), based on short-time SVD (STSVD), is proposed for flaw feature detection from a measured signal in ultrasonic NDE. In this technique, the measured signal is first truncated into overlapping short-time data segments to put feature information of a transient flaw echo signal in local field, and then the MSI can be obtained from the SVD of each short-time data segment. Research shows that this indicator can clearly indicate the location of ultrasonic flaw signals, and the computational complexity of this STSVD-based indicator is significantly reduced with the algorithm proposed in this paper. Both simulation and experiments show that this technique is very efficient for real-time application in flaw detection from noisy data.

Machine learning based sample extraction for automatic speech recognition using dialectal Assamese speech.

PubMed

Agarwalla, Swapna; Sarma, Kandarpa Kumar

2016-06-01

Automatic Speaker Recognition (ASR) and related issues are continuously evolving as inseparable elements of Human Computer Interaction (HCI). With assimilation of emerging concepts like big data and Internet of Things (IoT) as extended elements of HCI, ASR techniques are found to be passing through a paradigm shift. Oflate, learning based techniques have started to receive greater attention from research communities related to ASR owing to the fact that former possess natural ability to mimic biological behavior and that way aids ASR modeling and processing. The current learning based ASR techniques are found to be evolving further with incorporation of big data, IoT like concepts. Here, in this paper, we report certain approaches based on machine learning (ML) used for extraction of relevant samples from big data space and apply them for ASR using certain soft computing techniques for Assamese speech with dialectal variations. A class of ML techniques comprising of the basic Artificial Neural Network (ANN) in feedforward (FF) and Deep Neural Network (DNN) forms using raw speech, extracted features and frequency domain forms are considered. The Multi Layer Perceptron (MLP) is configured with inputs in several forms to learn class information obtained using clustering and manual labeling. DNNs are also used to extract specific sentence types. Initially, from a large storage, relevant samples are selected and assimilated. Next, a few conventional methods are used for feature extraction of a few selected types. The features comprise of both spectral and prosodic types. These are applied to Recurrent Neural Network (RNN) and Fully Focused Time Delay Neural Network (FFTDNN) structures to evaluate their performance in recognizing mood, dialect, speaker and gender variations in dialectal Assamese speech. The system is tested under several background noise conditions by considering the recognition rates (obtained using confusion matrices and manually) and computation time. It is found that the proposed ML based sentence extraction techniques and the composite feature set used with RNN as classifier outperform all other approaches. By using ANN in FF form as feature extractor, the performance of the system is evaluated and a comparison is made. Experimental results show that the application of big data samples has enhanced the learning of the ASR system. Further, the ANN based sample and feature extraction techniques are found to be efficient enough to enable application of ML techniques in big data aspects as part of ASR systems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Letters in time and retinotopic space.

PubMed

Adelman, James S

2011-10-01

Various phenomena in tachistoscopic word identification and priming (WRODS and LTRS are confused with and prime WORDS and LETTERS) suggest that position-specific channels are not used in the processing of letters in words. Previous approaches to this issue have sought alternative matching rules because they have assumed that these phenomena reveal which stimuli are good but imperfect matches to a particular word-such imperfect matches being taken by the word recognition system as partial evidence for that word. The new Letters in Time and Retinotopic Space model (LTRS) makes the alternative assumption that these phenomena reveal the rates at which different features of the stimulus are extracted, because the stimulus is ambiguous when some features are missing from the percept. LTRS is successfully applied to tachistoscopic identification and form priming data with manipulations of duration and target-foil and prime-target relationships. © 2011 American Psychological Association

Instructional Design for Advanced Learners: Training Recognition Skills to Hasten Expertise

ERIC Educational Resources Information Center

Fadde, Peter Jae

2009-01-01

Expertise in domains ranging from sports to surgery involves a process of recognition-primed decision-making (RPD) in which experts make rapid, intuitive decisions based on recognizing critical features of dynamic performance situations. While the development of expert RPD is assumed to require years of domain experience, the transition from…

Optimal visual simulation of the self-tracking combustion of the infrared decoy based on the particle system

NASA Astrophysics Data System (ADS)

Hu, Qi; Duan, Jin; Wang, LiNing; Zhai, Di

2016-09-01

The high-efficiency simulation test of military weapons has a very important effect on the high cost of the actual combat test and the very demanding operational efficiency. Especially among the simulative emulation methods of the explosive smoke, the simulation method based on the particle system has generated much attention. In order to further improve the traditional simulative emulation degree of the movement process of the infrared decoy during the real combustion cycle, this paper, adopting the virtual simulation platform of OpenGL and Vega Prime and according to their own radiation characteristics and the aerodynamic characteristics of the infrared decoy, has simulated the dynamic fuzzy characteristics of the infrared decoy during the real combustion cycle by using particle system based on the double depth peeling algorithm and has solved key issues such as the interface, coordinate conversion and the retention and recovery of the Vega Prime's status. The simulation experiment has basically reached the expected improvement purpose, effectively improved the simulation fidelity and provided theoretical support for improving the performance of the infrared decoy.

Innovative Language-Based & Object-Oriented Structured AMR Using Fortran 90 and OpenMP

NASA Technical Reports Server (NTRS)

Norton, C.; Balsara, D.

1999-01-01

Parallel adaptive mesh refinement (AMR) is an important numerical technique that leads to the efficient solution of many physical and engineering problems. In this paper, we describe how AMR programing can be performed in an object-oreinted way using the modern aspects of Fortran 90 combined with the parallelization features of OpenMP.

Computer aided detection of tumor and edema in brain FLAIR magnetic resonance image using ANN

NASA Astrophysics Data System (ADS)

Pradhan, Nandita; Sinha, A. K.

2008-03-01

This paper presents an efficient region based segmentation technique for detecting pathological tissues (Tumor & Edema) of brain using fluid attenuated inversion recovery (FLAIR) magnetic resonance (MR) images. This work segments FLAIR brain images for normal and pathological tissues based on statistical features and wavelet transform coefficients using k-means algorithm. The image is divided into small blocks of 4×4 pixels. The k-means algorithm is used to cluster the image based on the feature vectors of blocks forming different classes representing different regions in the whole image. With the knowledge of the feature vectors of different segmented regions, supervised technique is used to train Artificial Neural Network using fuzzy back propagation algorithm (FBPA). Segmentation for detecting healthy tissues and tumors has been reported by several researchers by using conventional MRI sequences like T1, T2 and PD weighted sequences. This work successfully presents segmentation of healthy and pathological tissues (both Tumors and Edema) using FLAIR images. At the end pseudo coloring of segmented and classified regions are done for better human visualization.

New preparation method of {beta}{double_prime}-alumina and application for AMTEC

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

Nishi, Toshiro; Tsuru, Yasuhiko; Yamamoto, Hirokazu

1995-12-31

The Alkali Metal Thermo-Electric Converter(AMTEC) is an energy conversion system that converts heat to electrical energy with high efficiency. The {beta}{double_prime}-alumina solid electrolyte (BASE) is the most important component in the AMTEC system. In this paper, the relationship among the conduction property, the microstructure and the amount of chemical component for BASE is studied. As an analysis of the chemical reaction for each component, the authors established a new BASE preparation method rather than using the conventional method. They also report the AMTFC cell performance using this electrolyte tube on which Mo or TiC electrode is filmed by the screenmore » printing method. Then, an electrochemical analysis and a heat cycle test of AMTEC cell are studied.« less

High-efficiency solar cells fabricated by vacuum MO-CVD

NASA Technical Reports Server (NTRS)

Fraas, L. M.; Cape, J. A.; Partain, L. D.; Mcleod, P. S.

1984-01-01

High-efficiency, monolithic, two-color, three-terminal solar cells were fabricated by a novel growth technique, vacuum metal-organic chemical vapor deposition. The technique uses the expensive metal alkyls efficiently and toxic gases sparingly. The fact that the outer chamber is constructed of nonbreakable stainless steel is an attractive safety feature associated with this deposition system.

LDRD final report :

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

Brost, Randolph C.; McLendon, William Clarence,

2013-01-01

Modeling geospatial information with semantic graphs enables search for sites of interest based on relationships between features, without requiring strong a priori models of feature shape or other intrinsic properties. Geospatial semantic graphs can be constructed from raw sensor data with suitable preprocessing to obtain a discretized representation. This report describes initial work toward extending geospatial semantic graphs to include temporal information, and initial results applying semantic graph techniques to SAR image data. We describe an efficient graph structure that includes geospatial and temporal information, which is designed to support simultaneous spatial and temporal search queries. We also report amore » preliminary implementation of feature recognition, semantic graph modeling, and graph search based on input SAR data. The report concludes with lessons learned and suggestions for future improvements.« less

Feature generation using genetic programming with application to fault classification.

PubMed

Guo, Hong; Jack, Lindsay B; Nandi, Asoke K

2005-02-01

One of the major challenges in pattern recognition problems is the feature extraction process which derives new features from existing features, or directly from raw data in order to reduce the cost of computation during the classification process, while improving classifier efficiency. Most current feature extraction techniques transform the original pattern vector into a new vector with increased discrimination capability but lower dimensionality. This is conducted within a predefined feature space, and thus, has limited searching power. Genetic programming (GP) can generate new features from the original dataset without prior knowledge of the probabilistic distribution. In this paper, a GP-based approach is developed for feature extraction from raw vibration data recorded from a rotating machine with six different conditions. The created features are then used as the inputs to a neural classifier for the identification of six bearing conditions. Experimental results demonstrate the ability of GP to discover autimatically the different bearing conditions using features expressed in the form of nonlinear functions. Furthermore, four sets of results--using GP extracted features with artificial neural networks (ANN) and support vector machines (SVM), as well as traditional features with ANN and SVM--have been obtained. This GP-based approach is used for bearing fault classification for the first time and exhibits superior searching power over other techniques. Additionaly, it significantly reduces the time for computation compared with genetic algorithm (GA), therefore, makes a more practical realization of the solution.

On the use of INS to improve Feature Matching

NASA Astrophysics Data System (ADS)

Masiero, A.; Guarnieri, A.; Vettore, A.; Pirotti, F.

2014-11-01

The continuous technological improvement of mobile devices opens the frontiers of Mobile Mapping systems to very compact systems, i.e. a smartphone or a tablet. This motivates the development of efficient 3D reconstruction techniques based on the sensors typically embedded in such devices, i.e. imaging sensors, GPS and Inertial Navigation System (INS). Such methods usually exploits photogrammetry techniques (structure from motion) to provide an estimation of the geometry of the scene. Actually, 3D reconstruction techniques (e.g. structure from motion) rely on use of features properly matched in different images to compute the 3D positions of objects by means of triangulation. Hence, correct feature matching is of fundamental importance to ensure good quality 3D reconstructions. Matching methods are based on the appearance of features, that can change as a consequence of variations of camera position and orientation, and environment illumination. For this reason, several methods have been developed in recent years in order to provide feature descriptors robust (ideally invariant) to such variations, e.g. Scale-Invariant Feature Transform (SIFT), Affine SIFT, Hessian affine and Harris affine detectors, Maximally Stable Extremal Regions (MSER). This work deals with the integration of information provided by the INS in the feature matching procedure: a previously developed navigation algorithm is used to constantly estimate the device position and orientation. Then, such information is exploited to estimate the transformation of feature regions between two camera views. This allows to compare regions from different images but associated to the same feature as seen by the same point of view, hence significantly easing the comparison of feature characteristics and, consequently, improving matching. SIFT-like descriptors are used in order to ensure good matching results in presence of illumination variations and to compensate the approximations related to the estimation process.

Attention, awareness of contingencies, and control in spatial localization: a qualitative difference approach.

PubMed

Vaquero, Joaquín M M; Fiacconi, Chris; Milliken, Bruce

2010-12-01

The qualitative difference method for distinguishing between aware and unaware processes was applied here to a spatial priming task. Participants were asked simply to locate a target stimulus that appeared in one of four locations, and this target stimulus was preceded by a prime in one of the same four locations. The prime location predicted the location of the target with high probability (p = .75), but prime and target mismatched on a task-relevant feature (identity, color). Across 5 experiments, we observed repetition costs in the absence of awareness of the contingency, and repetition benefits in the presence of awareness of the contingency. These results were particularly clear-cut in Experiment 4, in which awareness was defined by reference to self-reported strategy use. Finally, Experiment 5 showed that frequency-based implicit learning effects were present in our experiments but that these implicit learning effects were not strong enough to override repetition costs that pushed performance in the opposite direction. The results of these experiments constitute a novel application of the qualitative difference method to the study of awareness, learning of contingencies, and strategic control.

BRAIN TUMOR SEGMENTATION WITH SYMMETRIC TEXTURE AND SYMMETRIC INTENSITY-BASED DECISION FORESTS.

PubMed

Bianchi, Anthony; Miller, James V; Tan, Ek Tsoon; Montillo, Albert

2013-04-01

Accurate automated segmentation of brain tumors in MR images is challenging due to overlapping tissue intensity distributions and amorphous tumor shape. However, a clinically viable solution providing precise quantification of tumor and edema volume would enable better pre-operative planning, treatment monitoring and drug development. Our contributions are threefold. First, we design efficient gradient and LBPTOP based texture features which improve classification accuracy over standard intensity features. Second, we extend our texture and intensity features to symmetric texture and symmetric intensity which further improve the accuracy for all tissue classes. Third, we demonstrate further accuracy enhancement by extending our long range features from 100mm to a full 200mm. We assess our brain segmentation technique on 20 patients in the BraTS 2012 dataset. Impact from each contribution is measured and the combination of all the features is shown to yield state-of-the-art accuracy and speed.

Subliminal speech perception and auditory streaming.

PubMed

Dupoux, Emmanuel; de Gardelle, Vincent; Kouider, Sid

2008-11-01

Current theories of consciousness assume a qualitative dissociation between conscious and unconscious processing: while subliminal stimuli only elicit a transient activity, supraliminal stimuli have long-lasting influences. Nevertheless, the existence of this qualitative distinction remains controversial, as past studies confounded awareness and stimulus strength (energy, duration). Here, we used a masked speech priming method in conjunction with a submillisecond interaural delay manipulation to contrast subliminal and supraliminal processing at constant prime, mask and target strength. This delay induced a perceptual streaming effect, with the prime popping out in the supraliminal condition. By manipulating the prime-target interval (ISI), we show a qualitatively distinct profile of priming longevity as a function of prime awareness. While subliminal priming disappeared after half a second, supraliminal priming was independent of ISI. This shows that the distinction between conscious and unconscious processing depends on high-level perceptual streaming factors rather than low-level features (energy, duration).

Reflective small angle electron scattering to characterize nanostructures on opaque substrates

NASA Astrophysics Data System (ADS)

Friedman, Lawrence H.; Wu, Wen-Li; Fu, Wei-En; Chien, Yunsan

2017-09-01

Feature sizes in integrated circuits (ICs) are often at the scale of 10 nm and are ever shrinking. ICs appearing in today's computers and hand held devices are perhaps the most prominent examples. These smaller feature sizes demand equivalent advances in fast and accurate dimensional metrology for both development and manufacturing. Techniques in use and continuing to be developed include X-ray based techniques, optical scattering, and of course the electron and scanning probe microscopy techniques. Each of these techniques has their advantages and limitations. Here, the use of small angle electron beam scattering measurements in a reflection mode (RSAES) to characterize the dimensions and the shape of nanostructures on flat and opaque substrates is demonstrated using both experimental and theoretical evidence. In RSAES, focused electrons are scattered at angles smaller than 1 ° with the assistance of electron optics typically used in transmission electron microscopy. A proof-of-concept experiment is combined with rigorous electron reflection simulations to demonstrate the efficiency and accuracy of RSAES as a method of non-destructive measurement of shapes of features less than 10 nm in size on flat and opaque substrates.

Reflective Small Angle Electron Scattering to Characterize Nanostructures on Opaque Substrates.

PubMed

Friedman, Lawrence H; Wu, Wen-Li; Fu, Wei-En; Chien, Yunsan

2017-09-01

Features sizes in integrated circuits (ICs) are often at the scale of 10 nm and are ever shrinking. ICs appearing in today's computers and hand held devices are perhaps the most prominent examples. These smaller feature sizes demand equivalent advances in fast and accurate dimensional metrology for both development and manufacturing. Techniques in use and continuing to be developed include X-ray based techniques, optical scattering and of course the electron and scanning probe microscopy techniques. Each of these techniques have their advantages and limitations. Here the use of small angle electron beam scattering measurements in a reflection mode (RSAES) to characterize the dimensions and the shape of nanostructures on flat and opaque substrates is demonstrated using both experimental and theoretical evidence. In RSAES, focused electrons are scattered at angles smaller than 1° with the assistance of electron optics typically used in transmission electron microscopy. A proof-of-concept experiment is combined with rigorous electron reflection simulations to demonstrate the efficiency and accuracy of RSAES as a method of non-destructive measurement of shapes of features less than 10 nm in size on flat and opaque substrates.

Emotional and neutral scenes in competition: orienting, efficiency, and identification.

PubMed

Calvo, Manuel G; Nummenmaa, Lauri; Hyönä, Jukka

2007-12-01

To investigate preferential processing of emotional scenes competing for limited attentional resources with neutral scenes, prime pictures were presented briefly (450 ms), peripherally (5.2 degrees away from fixation), and simultaneously (one emotional and one neutral scene) versus singly. Primes were followed by a mask and a probe for recognition. Hit rate was higher for emotional than for neutral scenes in the dual- but not in the single-prime condition, and A' sensitivity decreased for neutral but not for emotional scenes in the dual-prime condition. This preferential processing involved both selective orienting and efficient encoding, as revealed, respectively, by a higher probability of first fixation on--and shorter saccade latencies to--emotional scenes and by shorter fixation time needed to accurately identify emotional scenes, in comparison with neutral scenes.

Efficient iris texture analysis method based on Gabor ordinal measures

NASA Astrophysics Data System (ADS)

Tajouri, Imen; Aydi, Walid; Ghorbel, Ahmed; Masmoudi, Nouri

2017-07-01

With the remarkably increasing interest directed to the security dimension, the iris recognition process is considered to stand as one of the most versatile technique critically useful for the biometric identification and authentication process. This is mainly due to every individual's unique iris texture. A modestly conceived efficient approach relevant to the feature extraction process is proposed. In the first place, iris zigzag "collarette" is extracted from the rest of the image by means of the circular Hough transform, as it includes the most significant regions lying in the iris texture. In the second place, the linear Hough transform is used for the eyelids' detection purpose while the median filter is applied for the eyelashes' removal. Then, a special technique combining the richness of Gabor features and the compactness of ordinal measures is implemented for the feature extraction process, so that a discriminative feature representation for every individual can be achieved. Subsequently, the modified Hamming distance is used for the matching process. Indeed, the advanced procedure turns out to be reliable, as compared to some of the state-of-the-art approaches, with a recognition rate of 99.98%, 98.12%, and 95.02% on CASIAV1.0, CASIAV3.0, and IIT Delhi V1 iris databases, respectively.

Advanced CO2 removal process control and monitor instrumentation development

NASA Technical Reports Server (NTRS)

Heppner, D. B.; Dalhausen, M. J.; Klimes, R.

1982-01-01

A progam to evaluate, design and demonstrate major advances in control and monitor instrumentation was undertaken. A carbon dioxide removal process, one whose maturity level makes it a prime candidate for early flight demonstration was investigated. The instrumentation design incorporates features which are compatible with anticipated flight requirements. Current electronics technology and projected advances are included. In addition, the program established commonality of components for all advanced life support subsystems. It was concluded from the studies and design activities conducted under this program that the next generation of instrumentation will be greatly smaller than the prior one. Not only physical size but weight, power and heat rejection requirements were reduced in the range of 80 to 85% from the former level of research and development instrumentation. Using a microprocessor based computer, a standard computer bus structure and nonvolatile memory, improved fabrication techniques and aerospace packaging this instrumentation will greatly enhance overall reliability and total system availability.

Leishmania major Infection Activates NF-κB and Interferon Regulatory Factors 1 and 8 in Human Dendritic Cells▿

PubMed Central

Jayakumar, Asha; Donovan, Michael J.; Tripathi, Vinita; Ramalho-Ortigao, Marcelo; McDowell, Mary Ann

2008-01-01

The salient feature of dendritic cells (DC) is the initiation of appropriate adaptive immune responses by discriminating between pathogens. Using a prototypic model of intracellular infection, we previously showed that Leishmania major parasites prime human DC for efficient interleukin-12 (IL-12) secretion. L. major infection is associated with self-limiting cutaneous disease and powerful immunity. In stark contrast, the causative agent of visceral leishmaniasis, Leishmania donovani, does not prime human DC for IL-12 production. Here, we report that DC priming by L. major infection results in the early activation of NF-κB transcription factors and the up-regulation and nuclear translocation of interferon regulatory factor 1 (IRF-1) and IRF-8. The inhibition of NF-κB activation by the pretreatment of DC with caffeic acid phenethyl ester blocks L. major-induced IRF-1 and IRF-8 activation and IL-12 expression. We further demonstrate that IRF-1 and IRF-8 obtained from L. major-infected human DC specifically bind to their consensus binding sites on the IL-12p35 promoter, indicating that L. major infection either directly stimulates a signaling cascade or induces an autocrine pathway that activates IRF-1 and IRF-8, ultimately resulting in IL-12 transcription. PMID:18316378

Design of Ultrathin Pt-Based Multimetallic Nanostructures for Efficient Oxygen Reduction Electrocatalysis.

PubMed

Lai, Jianping; Guo, Shaojun

2017-12-01

Nanocatalysts with high platinum (Pt) utilization efficiency are attracting extensive attention for oxygen reduction reactions (ORR) conducted at the cathode of fuel cells. Ultrathin Pt-based multimetallic nanostructures show obvious advantages in accelerating the sluggish cathodic ORR due to their ultrahigh Pt utilization efficiency. A focus on recent important developments is provided in using wet chemistry techniques for making/tuning the multimetallic nanostructures with high Pt utilization efficiency for boosting ORR activity and durability. First, new synthetic methods for multimetallic core/shell nanoparticles with ultrathin shell sizes for achieving highly efficient ORR catalysts are reviewed. To obtain better ORR activity and stability, multimetallic nanowires or nanosheets with well-defined structure and surface are further highlighted. Furthermore, ultrathin Pt-based multimetallic nanoframes that feature 3D molecularly accessible surfaces for achieving more efficient ORR catalysis are discussed. Finally, the remaining challenges and outlooks for the future will be provided for this promising research field. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Efficient G-XML Data Management Method using XML Spatial Index for Mobile Devices

NASA Astrophysics Data System (ADS)

Tamada, Takashi; Momma, Kei; Seo, Kazuo; Hijikata, Yoshinori; Nishida, Shogo

This paper presents an efficient G-XML data management method for mobile devices. G-XML is XML based encoding for the transport of geographic information. Mobile devices, such as PDA and mobile-phone, performance trail desktop machines, so some techniques are needed for processing G-XML data on mobile devices. In this method, XML-format spatial index file is used to improve an initial display time of G-XML data. This index file contains XML pointer of each feature in G-XML data and classifies these features by multi-dimensional data structures. From the experimental result, we can prove this method speed up about 3-7 times an initial display time of G-XML data on mobile devices.

Diagnostic methodology for incipient system disturbance based on a neural wavelet approach

NASA Astrophysics Data System (ADS)

Won, In-Ho

Since incipient system disturbances are easily mixed up with other events or noise sources, the signal from the system disturbance can be neglected or identified as noise. Thus, as available knowledge and information is obtained incompletely or inexactly from the measurements; an exploration into the use of artificial intelligence (AI) tools to overcome these uncertainties and limitations was done. A methodology integrating the feature extraction efficiency of the wavelet transform with the classification capabilities of neural networks is developed for signal classification in the context of detecting incipient system disturbances. The synergistic effects of wavelets and neural networks present more strength and less weakness than either technique taken alone. A wavelet feature extractor is developed to form concise feature vectors for neural network inputs. The feature vectors are calculated from wavelet coefficients to reduce redundancy and computational expense. During this procedure, the statistical features based on the fractal concept to the wavelet coefficients play a role as crucial key in the wavelet feature extractor. To verify the proposed methodology, two applications are investigated and successfully tested. The first involves pump cavitation detection using dynamic pressure sensor. The second pertains to incipient pump cavitation detection using signals obtained from a current sensor. Also, through comparisons between three proposed feature vectors and with statistical techniques, it is shown that the variance feature extractor provides a better approach in the performed applications.

A neural signature of food semantics is associated with body-mass index.

PubMed

Pergola, Giulio; Foroni, Francesco; Mengotti, Paola; Argiris, Georgette; Rumiati, Raffaella Ida

2017-10-01

Visual recognition of objects may rely on different features depending on the category to which they belong. Recognizing natural objects, such as fruits and plants, weighs more on their perceptual attributes, whereas recognizing man-made objects, such as tools or vehicles, weighs more upon the functions and actions they enable. Edible objects are perceptually rich but also prepared for specific functions, therefore it is unclear how perceptual and functional attributes affect their recognition. Two event-related potentials experiments investigated: (i) whether food categorization in the brain is differentially modulated by sensory and functional attributes, depending on whether the food is natural or transformed; (ii) whether these processes are modulated by participants' body mass index. In experiment 1, healthy normal-weight participants were presented with a sentence (prime) and a photograph of a food. Primes described either a sensory feature ('It tastes sweet') or a functional feature ('It is suitable for a wedding party') of the food, while photographs depicted either a natural (e.g., cherry) or a transformed food (e.g., pizza). Prime-feature pairs were either congruent or incongruent. This design aimed at modulating N400-like components elicited by semantic processing. In experiment 1, N400-like amplitude was significantly larger for transformed food than for natural food with sensory primes, and vice versa with functional primes. In experiment 2, underweight and obese women performed the same semantic task. We found that, while the N400-like component in obese participants was modulated by sensory-functional primes only for transformed food, the same modulation was found in underweight participants only for natural food. These findings suggest that the level of food transformation interacts with participants' body mass index in modulating food perception and the underlying brain processing. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Indexing and retrieval of MPEG compressed video

NASA Astrophysics Data System (ADS)

Kobla, Vikrant; Doermann, David S.

1998-04-01

To keep pace with the increased popularity of digital video as an archival medium, the development of techniques for fast and efficient analysis of ideo streams is essential. In particular, solutions to the problems of storing, indexing, browsing, and retrieving video data from large multimedia databases are necessary to a low access to these collections. Given that video is often stored efficiently in a compressed format, the costly overhead of decompression can be reduced by analyzing the compressed representation directly. In earlier work, we presented compressed domain parsing techniques which identified shots, subshots, and scenes. In this article, we present efficient key frame selection, feature extraction, indexing, and retrieval techniques that are directly applicable to MPEG compressed video. We develop a frame type independent representation which normalizes spatial and temporal features including frame type, frame size, macroblock encoding, and motion compensation vectors. Features for indexing are derived directly from this representation and mapped to a low- dimensional space where they can be accessed using standard database techniques. Spatial information is used as primary index into the database and temporal information is used to rank retrieved clips and enhance the robustness of the system. The techniques presented enable efficient indexing, querying, and retrieval of compressed video as demonstrated by our system which typically takes a fraction of a second to retrieve similar video scenes from a database, with over 95 percent recall.

Co-occurrence frequency evaluated with large language corpora boosts semantic priming effects.

PubMed

Brunellière, Angèle; Perre, Laetitia; Tran, ThiMai; Bonnotte, Isabelle

2017-09-01

In recent decades, many computational techniques have been developed to analyse the contextual usage of words in large language corpora. The present study examined whether the co-occurrence frequency obtained from large language corpora might boost purely semantic priming effects. Two experiments were conducted: one with conscious semantic priming, the other with subliminal semantic priming. Both experiments contrasted three semantic priming contexts: an unrelated priming context and two related priming contexts with word pairs that are semantically related and that co-occur either frequently or infrequently. In the conscious priming presentation (166-ms stimulus-onset asynchrony, SOA), a semantic priming effect was recorded in both related priming contexts, which was greater with higher co-occurrence frequency. In the subliminal priming presentation (66-ms SOA), no significant priming effect was shown, regardless of the related priming context. These results show that co-occurrence frequency boosts pure semantic priming effects and are discussed with reference to models of semantic network.

Ultrasonic mixing of epoxy curing agents

NASA Technical Reports Server (NTRS)

Hodges, W. T.; St.clair, T. L.

1983-01-01

A new technique for mixing solid curing agents into liquid epoxy resins using ultrasonic energy was developed. This procedure allows standard curing agents such as 4,4 prime-diaminodiphenyl sulfone (4,4 prime-DDS) and its 3,3 prime-isomer, (3,3 prime-DDS) to be mixed without prior melting of the curing agent. It also allows curing agents such as 4,4 prime-diaminodiphenyl sulfone (4,4 prime-DDS) and its 3,3 prime-isomer, (3,3 prime-DDS) to be mixed without prior melting of the curing agent. It also allows curing agents with very high melt temperatures such as 4,4 prime-diaminobenzophenone (4,4 prime-DABP) (242 C) to be mixed without premature curing. Four aromatic diamines were ultrasonically blended into MY-720 epoxy resin. These were 4,4 prime-DDS; 3,3 prime-DDA; 4,4 prime-DABP and 3,3 prime-DABP. Unfilled moldings were cast and cured for each system and their physical and mechanical properties compared.

Electrophysiological differences in the processing of affect misattribution.

PubMed

Hashimoto, Yohei; Minami, Tetsuto; Nakauchi, Shigeki

2012-01-01

The affect misattribution procedure (AMP) was proposed as a technique to measure an implicit attitude to a prime image [1]. In the AMP, neutral symbols (e.g., a Chinese pictograph, called the target) are presented, following an emotional stimulus (known as the prime). Participants often misattribute the positive or negative affect of the priming images to the targets in spite of receiving an instruction to ignore the primes. The AMP effect has been investigated using behavioral measures; however, it is difficult to identify when the AMP effect occurs in emotional processing-whether the effect may occur in the earlier attention allocation stage or in the later evaluation stage. In this study, we examined the neural correlates of affect misattribution, using event-related potential (ERP) dividing the participants into two groups based on their tendency toward affect misattribution. The ERP results showed that the amplitude of P2 was larger for the prime at the parietal location in participants showing a low tendency to misattribution than for those showing a high tendency, while the effect of judging neutral targets amiss according to the primes was reflected in the late processing of targets (LPP). In addition, the topographic pattern analysis revealed that EPN-like component to targets was correlated with the difference of AMP tendency as well as P2 to primes and LPP to targets. Taken together, the mechanism of the affective misattribution was closely related to the attention allocation processing. Our findings provide neural evidence that evaluations of neutral targets are misattributed to emotional primes.

Prime-boost BCG vaccination with DNA vaccines based in β-defensin-2 and mycobacterial antigens ESAT6 or Ag85B improve protection in a tuberculosis experimental model.

PubMed

Cervantes-Villagrana, Alberto R; Hernández-Pando, Rogelio; Biragyn, Arya; Castañeda-Delgado, Julio; Bodogai, Monica; Martínez-Fierro, Margarita; Sada, Eduardo; Trujillo, Valentin; Enciso-Moreno, Antonio; Rivas-Santiago, Bruno

2013-01-11

The World Health Organization (WHO) has estimated that there are about 8 million new cases annually of active Tuberculosis (TB). Despite its irregular effectiveness (0-89%), the Bacillus Calmette-Guérin) BCG is the only vaccine available worldwide for prevention of TB; thus, the design is important of novel and more efficient vaccination strategies. Considering that β-defensin-2 is an antimicrobial peptide that induces dendritic cell maturation through the TLR-4 receptor and that both ESAT-6 and Ag85B are immunodominant mycobacterial antigens and efficient activators of the protective immune response, we constructed two DNA vaccines by the fusion of the gene encoding β-defensin-2 and antigens ESAT6 (pDE) and 85B (pDA). After confirming efficient local antigen expression that induced high and stable Interferon gamma (IFN-γ) production in intramuscular (i.m.) vaccinated Balb/c mice, groups of mice were vaccinated with DNA vaccines in a prime-boost regimen with BCG and with BCG alone, and 2 months later were challenged with the mild virulence reference strain H37Rv and the highly virulent clinical isolate LAM 5186. The level of protection was evaluated by survival, lung bacilli burdens, and extension of tissue damage (pneumonia). Vaccination with both DNA vaccines showed similar protection to that of BCG. After the challenge with the highly virulent Mycobacterium tuberculosis strain, animals that were prime-boosted with BCG and then boosted with both DNA vaccines showed significant higher survival and less tissue damage than mice vaccinated only with BCG. These results suggest that improvement of BCG vaccination, such as the prime-boost DNA vaccine, represents a more efficient vaccination scheme against TB. Copyright © 2012 Elsevier Ltd. All rights reserved.

Translation priming between the native language and a second language: new evidence from Dutch-French bilinguals.

PubMed

Duyck, Wouter; Warlop, Nele

2009-01-01

During the last two decades, bilingual research has adopted the masked translation priming paradigm as a tool to investigate the architecture of the bilingual language system. Although there is now a consensus about the existence of forward translation priming (from native language primes (L1) to second language (L2) translation equivalent targets), the backward translation priming effect (from L2 to L1) has only been reported in studies with bilinguals living in an L2 dominant environment. In a lexical decision experiment, we obtained significant translation priming in both directions, with unbalanced Dutch-French bilinguals living in an L1 dominant environment. Also, we demonstrated that these priming effects do not interact with a low-level visual prime feature such as font size. The obtained backward translation priming effect is consistent with the model of bilingual lexicosemantic organization of Duyck and Brysbaert (2004), which assumes strong mappings between L2 word forms and underlying semantic representations.

Oriented modulation for watermarking in direct binary search halftone images.

PubMed

Guo, Jing-Ming; Su, Chang-Cheng; Liu, Yun-Fu; Lee, Hua; Lee, Jiann-Der

2012-09-01

In this paper, a halftoning-based watermarking method is presented. This method enables high pixel-depth watermark embedding, while maintaining high image quality. This technique is capable of embedding watermarks with pixel depths up to 3 bits without causing prominent degradation to the image quality. To achieve high image quality, the parallel oriented high-efficient direct binary search (DBS) halftoning is selected to be integrated with the proposed orientation modulation (OM) method. The OM method utilizes different halftone texture orientations to carry different watermark data. In the decoder, the least-mean-square-trained filters are applied for feature extraction from watermarked images in the frequency domain, and the naïve Bayes classifier is used to analyze the extracted features and ultimately to decode the watermark data. Experimental results show that the DBS-based OM encoding method maintains a high degree of image quality and realizes the processing efficiency and robustness to be adapted in printing applications.

Knowledge-based segmentation and feature analysis of hand and wrist radiographs

NASA Astrophysics Data System (ADS)

Efford, Nicholas D.

1993-07-01

The segmentation of hand and wrist radiographs for applications such as skeletal maturity assessment is best achieved by model-driven approaches incorporating anatomical knowledge. The reasons for this are discussed, and a particular frame-based or 'blackboard' strategy for the simultaneous segmentation of the hand and estimation of bone age via the TW2 method is described. The new approach is structured for optimum robustness and computational efficiency: features of interest are detected and analyzes in order of their size and prominence in the image, the largest and most distinctive being dealt with first, and the evidence generated by feature analysis is used to update a model of hand anatomy and hence guide later stages of the segmentation. Closed bone boundaries are formed by a hybrid technique combining knowledge-based, one-dimensional edge detection with model-assisted heuristic tree searching.

Location-Driven Image Retrieval for Images Collected by a Mobile Robot

NASA Astrophysics Data System (ADS)

Tanaka, Kanji; Hirayama, Mitsuru; Okada, Nobuhiro; Kondo, Eiji

Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well images taken by the mobile robot are visualized to the user. To enhance the efficiency and flexibility of the visualization, an image retrieval system on such a robot’s image database would be very useful. The main difference of the robot’s image database from standard image databases is that various relevant images exist due to variety of viewing conditions. The main contribution of this paper is to propose an efficient retrieval approach, named location-driven approach, utilizing correlation between visual features and real world locations of images. Combining the location-driven approach with the conventional feature-driven approach, our goal can be viewed as finding an optimal classifier between relevant and irrelevant feature-location pairs. An active learning technique based on support vector machine is extended for this aim.

Spatial and identity negative priming in audition: evidence of feature binding in auditory spatial memory.

PubMed

Mayr, Susanne; Buchner, Axel; Möller, Malte; Hauke, Robert

2011-08-01

Two experiments are reported with identical auditory stimulation in three-dimensional space but with different instructions. Participants localized a cued sound (Experiment 1) or identified a sound at a cued location (Experiment 2). A distractor sound at another location had to be ignored. The prime distractor and the probe target sound were manipulated with respect to sound identity (repeated vs. changed) and location (repeated vs. changed). The localization task revealed a symmetric pattern of partial repetition costs: Participants were impaired on trials with identity-location mismatches between the prime distractor and probe target-that is, when either the sound was repeated but not the location or vice versa. The identification task revealed an asymmetric pattern of partial repetition costs: Responding was slowed down when the prime distractor sound was repeated as the probe target, but at another location; identity changes at the same location were not impaired. Additionally, there was evidence of retrieval of incompatible prime responses in the identification task. It is concluded that feature binding of auditory prime distractor information takes place regardless of whether the task is to identify or locate a sound. Instructions determine the kind of identity-location mismatch that is detected. Identity information predominates over location information in auditory memory.

An ERP Investigation of Visual Word Recognition in Syllabary Scripts

PubMed Central

Okano, Kana; Grainger, Jonathan; Holcomb, Phillip J.

2013-01-01

The bi-modal interactive-activation model has been successfully applied to understanding the neuro-cognitive processes involved in reading words in alphabetic scripts, as reflected in the modulation of ERP components in masked repetition priming. In order to test the generalizability of this approach, the current study examined word recognition in a different writing system, the Japanese syllabary scripts Hiragana and Katakana. Native Japanese participants were presented with repeated or unrelated pairs of Japanese words where the prime and target words were both in the same script (within-script priming, Experiment 1) or were in the opposite script (cross-script priming, Experiment 2). As in previous studies with alphabetic scripts, in both experiments the N250 (sub-lexical processing) and N400 (lexical-semantic processing) components were modulated by priming, although the time-course was somewhat delayed. The earlier N/P150 effect (visual feature processing) was present only in Experiment 1 where prime and target words shared visual features. Overall, the results provide support for the hypothesis that visual word recognition involves a generalizable set of neuro-cognitive processes that operate in a similar manner across different writing systems and languages, as well as pointing to the viability of the bi-modal interactive activation framework for modeling such processes. PMID:23378278

Lateralized semantic priming: modulation by levodopa, semantic distance, and participants’ magical beliefs

PubMed Central

Mohr, Christine; Landis, Theodor; Brugger, Peter

2006-01-01

We tested levodopa effects on lateralized direct and indirect semantic priming in 40 healthy right-handed men in a placebo-controlled, double-blind procedure. Crucially, priming was also analyzed as a function of participants’ positive schizotypal features (magical ideation, MI), previously found to be associated with an enhanced semantic spreading activation (SSA) within the right hemisphere. Across both priming conditions, we observed increased semantic priming in the levodopa group 1) specifically after right visual field stimulations and 2) in high MI scorers. In both instances, increased semantic priming emerged from exceedingly long reaction times to unrelated targets reflecting 1) the left hemisphere’s specialization for closely related concepts and 2) an opposite association between MI and SSA in the levodopa as compared with the placebo group. As a final finding, low MI scorers under levodopa performed like high MI scorers under placebo. Our findings speak against a general dopaminergic focusing of SSA, but one that respects each hemisphere’s specialization. They also suggest that individuals’ schizotypal features are important determinants of dopamine-induced changes in hemispheric functioning. We note that, in psychiatric patients, dopamine antagonists reportedly restore unusual lateralization. We discuss this dissociation between schizotypy and schizophrenia as supporting previous notions of protective brain mechanisms operating in the healthy “psychosis-prone” brain. PMID:19412448

Synthetic aperture radar target detection, feature extraction, and image formation techniques

NASA Technical Reports Server (NTRS)

Li, Jian

1994-01-01

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

SMALL SCALE BIOMASS FUELED GAS TURBINE ENGINE

EPA Science Inventory

A new generation of small scale (less than 20 MWe) biomass fueled, power plants are being developed based on a gas turbine (Brayton cycle) prime mover. These power plants are expected to increase the efficiency and lower the cost of generating power from fuels such as wood. The n...

Three-dimensional finite volume modelling of blood flow in simulated angular neck abdominal aortic aneurysm

NASA Astrophysics Data System (ADS)

Algabri, Y. A.; Rookkapan, S.; Chatpun, S.

2017-09-01

An abdominal aortic aneurysm (AAA) is considered a deadly cardiovascular disease that defined as a focal dilation of blood artery. The healthy aorta size is between 15 and 24 mm based on gender, bodyweight, and age. When the diameter increased to 30 mm or more, the rupture can occur if it is kept growing or untreated. Moreover, the proximal angular neck of aneurysm is categorized as a significant morphological feature with prime harmful effects on endovascular aneurysm repair (EVAR). Flow pattern in pathological vessel can influence the vascular intervention. The aim of this study is to investigate the blood flow behaviours in angular neck abdominal aortic aneurysm with simulated geometry based on patient’s information using computational fluid dynamics (CFD). The 3D angular neck AAA models have been designed by using SolidWorks Software. Consequently, CFD tools are used for simulating these 3D models of angular neck AAA in ANSYS FLUENT Software. Eventually, based on the results, we summarized that the CFD techniques have shown high performance in explaining and investigating the flow patterns for angular neck abdominal aortic aneurysm.

Hybridization between multi-objective genetic algorithm and support vector machine for feature selection in walker-assisted gait.

PubMed

Martins, Maria; Costa, Lino; Frizera, Anselmo; Ceres, Ramón; Santos, Cristina

2014-03-01

Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Accelerating image recognition on mobile devices using GPGPU

NASA Astrophysics Data System (ADS)

Bordallo López, Miguel; Nykänen, Henri; Hannuksela, Jari; Silvén, Olli; Vehviläinen, Markku

2011-01-01

The future multi-modal user interfaces of battery-powered mobile devices are expected to require computationally costly image analysis techniques. The use of Graphic Processing Units for computing is very well suited for parallel processing and the addition of programmable stages and high precision arithmetic provide for opportunities to implement energy-efficient complete algorithms. At the moment the first mobile graphics accelerators with programmable pipelines are available, enabling the GPGPU implementation of several image processing algorithms. In this context, we consider a face tracking approach that uses efficient gray-scale invariant texture features and boosting. The solution is based on the Local Binary Pattern (LBP) features and makes use of the GPU on the pre-processing and feature extraction phase. We have implemented a series of image processing techniques in the shader language of OpenGL ES 2.0, compiled them for a mobile graphics processing unit and performed tests on a mobile application processor platform (OMAP3530). In our contribution, we describe the challenges of designing on a mobile platform, present the performance achieved and provide measurement results for the actual power consumption in comparison to using the CPU (ARM) on the same platform.

Wavelet-based energy features for glaucomatous image classification.

PubMed

Dua, Sumeet; Acharya, U Rajendra; Chowriappa, Pradeep; Sree, S Vinitha

2012-01-01

Texture features within images are actively pursued for accurate and efficient glaucoma classification. Energy distribution over wavelet subbands is applied to find these important texture features. In this paper, we investigate the discriminatory potential of wavelet features obtained from the daubechies (db3), symlets (sym3), and biorthogonal (bio3.3, bio3.5, and bio3.7) wavelet filters. We propose a novel technique to extract energy signatures obtained using 2-D discrete wavelet transform, and subject these signatures to different feature ranking and feature selection strategies. We have gauged the effectiveness of the resultant ranked and selected subsets of features using a support vector machine, sequential minimal optimization, random forest, and naïve Bayes classification strategies. We observed an accuracy of around 93% using tenfold cross validations to demonstrate the effectiveness of these methods.

Relevant Sex Appeals in Advertising: Gender and Commitment Context Differences

PubMed Central

Lanseng, Even J.

2016-01-01

This research investigates differences in men's and women's attitudes toward ads featuring product-relevant sex appeals. It is found that women, but not men, were more negative toward an ad featuring an attractive opposite-sex model when their commitment thoughts were heightened. Women were also more negative toward an ad with an attractive same-sex model in the presence of commitment thoughts, but only when they scored high on sociosexuality. Men appeared unaffected, regardless of their level of sociosexuality. Commitment thoughts were manipulated by two types of prime, a parenting prime (study1) and a romantic prime (study 2). Results are explained by differences in how men and women react to sexual material and by differences in men's and women's evolved mating preferences. PMID:27746749

Relevant Sex Appeals in Advertising: Gender and Commitment Context Differences.

PubMed

Lanseng, Even J

2016-01-01

This research investigates differences in men's and women's attitudes toward ads featuring product-relevant sex appeals. It is found that women, but not men, were more negative toward an ad featuring an attractive opposite-sex model when their commitment thoughts were heightened. Women were also more negative toward an ad with an attractive same-sex model in the presence of commitment thoughts, but only when they scored high on sociosexuality. Men appeared unaffected, regardless of their level of sociosexuality. Commitment thoughts were manipulated by two types of prime, a parenting prime (study1) and a romantic prime (study 2). Results are explained by differences in how men and women react to sexual material and by differences in men's and women's evolved mating preferences.

Selection and response bias as determinants of priming of pop-out search: Revelations from diffusion modeling.

PubMed

Burnham, Bryan R

2018-05-03

During visual search, both top-down factors and bottom-up properties contribute to the guidance of visual attention, but selection history can influence attention independent of bottom-up and top-down factors. For example, priming of pop-out (PoP) is the finding that search for a singleton target is faster when the target and distractor features repeat than when those features trade roles between trials. Studies have suggested that such priming (selection history) effects on pop-out search manifest either early, by biasing the selection of the preceding target feature, or later in processing, by facilitating response and target retrieval processes. The present study was designed to examine the influence of selection history on pop-out search by introducing a speed-accuracy trade-off manipulation in a pop-out search task. Ratcliff diffusion modeling (RDM) was used to examine how selection history influenced both attentional bias and response execution processes. The results support the hypothesis that selection history biases attention toward the preceding target's features on the current trial and also influences selection of the response to the target.

Accurate low-cost methods for performance evaluation of cache memory systems

NASA Technical Reports Server (NTRS)

Laha, Subhasis; Patel, Janak H.; Iyer, Ravishankar K.

1988-01-01

Methods of simulation based on statistical techniques are proposed to decrease the need for large trace measurements and for predicting true program behavior. Sampling techniques are applied while the address trace is collected from a workload. This drastically reduces the space and time needed to collect the trace. Simulation techniques are developed to use the sampled data not only to predict the mean miss rate of the cache, but also to provide an empirical estimate of its actual distribution. Finally, a concept of primed cache is introduced to simulate large caches by the sampling-based method.

Emotion potentiates response activation and inhibition in masked priming

PubMed Central

Bocanegra, Bruno R.; Zeelenberg, René

2012-01-01

Previous studies have shown that emotion can have 2-fold effects on perception. At the object-level, emotional stimuli benefit from a stimulus-specific boost in visual attention at the relative expense of competing stimuli. At the visual feature-level, recent findings indicate that emotion may inhibit the processing of small visual details and facilitate the processing of coarse visual features. In the present study, we investigated whether emotion can boost the activation and inhibition of automatic motor responses that are generated prior to overt perception. To investigate this, we tested whether an emotional cue affects covert motor responses in a masked priming task. We used a masked priming paradigm in which participants responded to target arrows that were preceded by invisible congruent or incongruent prime arrows. In the standard paradigm, participants react faster, and commit fewer errors responding to the directionality of target arrows, when they are preceded by congruent vs. incongruent masked prime arrows (positive congruency effect, PCE). However, as prime-target SOAs increase, this effect reverses (negative congruency effect, NCE). These findings have been explained as evidence for an initial activation and a subsequent inhibition of a partial response elicited by the masked prime arrow. Our results show that the presentation of fearful face cues, compared to neutral face cues, increased the size of both the PCE and NCE, despite the fact that the primes were invisible. This is the first demonstration that emotion prepares an individual's visuomotor system for automatic activation and inhibition of motor responses in the absence of visual awareness. PMID:23162447

Emotion potentiates response activation and inhibition in masked priming.

PubMed

Bocanegra, Bruno R; Zeelenberg, René

2012-01-01

Previous studies have shown that emotion can have 2-fold effects on perception. At the object-level, emotional stimuli benefit from a stimulus-specific boost in visual attention at the relative expense of competing stimuli. At the visual feature-level, recent findings indicate that emotion may inhibit the processing of small visual details and facilitate the processing of coarse visual features. In the present study, we investigated whether emotion can boost the activation and inhibition of automatic motor responses that are generated prior to overt perception. To investigate this, we tested whether an emotional cue affects covert motor responses in a masked priming task. We used a masked priming paradigm in which participants responded to target arrows that were preceded by invisible congruent or incongruent prime arrows. In the standard paradigm, participants react faster, and commit fewer errors responding to the directionality of target arrows, when they are preceded by congruent vs. incongruent masked prime arrows (positive congruency effect, PCE). However, as prime-target SOAs increase, this effect reverses (negative congruency effect, NCE). These findings have been explained as evidence for an initial activation and a subsequent inhibition of a partial response elicited by the masked prime arrow. Our results show that the presentation of fearful face cues, compared to neutral face cues, increased the size of both the PCE and NCE, despite the fact that the primes were invisible. This is the first demonstration that emotion prepares an individual's visuomotor system for automatic activation and inhibition of motor responses in the absence of visual awareness.

Score-Level Fusion of Phase-Based and Feature-Based Fingerprint Matching Algorithms

NASA Astrophysics Data System (ADS)

Ito, Koichi; Morita, Ayumi; Aoki, Takafumi; Nakajima, Hiroshi; Kobayashi, Koji; Higuchi, Tatsuo

This paper proposes an efficient fingerprint recognition algorithm combining phase-based image matching and feature-based matching. In our previous work, we have already proposed an efficient fingerprint recognition algorithm using Phase-Only Correlation (POC), and developed commercial fingerprint verification units for access control applications. The use of Fourier phase information of fingerprint images makes it possible to achieve robust recognition for weakly impressed, low-quality fingerprint images. This paper presents an idea of improving the performance of POC-based fingerprint matching by combining it with feature-based matching, where feature-based matching is introduced in order to improve recognition efficiency for images with nonlinear distortion. Experimental evaluation using two different types of fingerprint image databases demonstrates efficient recognition performance of the combination of the POC-based algorithm and the feature-based algorithm.

A Novel Image Recuperation Approach for Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image

PubMed Central

2015-01-01

Retinal fundus images are widely used in diagnosing and providing treatment for several eye diseases. Prior works using retinal fundus images detected the presence of exudation with the aid of publicly available dataset using extensive segmentation process. Though it was proved to be computationally efficient, it failed to create a diabetic retinopathy feature selection system for transparently diagnosing the disease state. Also the diagnosis of diseases did not employ machine learning methods to categorize candidate fundus images into true positive and true negative ratio. Several candidate fundus images did not include more detailed feature selection technique for diabetic retinopathy. To apply machine learning methods and classify the candidate fundus images on the basis of sliding window a method called, Diabetic Fundus Image Recuperation (DFIR) is designed in this paper. The initial phase of DFIR method select the feature of optic cup in digital retinal fundus images based on Sliding Window Approach. With this, the disease state for diabetic retinopathy is assessed. The feature selection in DFIR method uses collection of sliding windows to obtain the features based on the histogram value. The histogram based feature selection with the aid of Group Sparsity Non-overlapping function provides more detailed information of features. Using Support Vector Model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy diseases. The ranking of disease level for each candidate set provides a much promising result for developing practically automated diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, specificity rate, ranking efficiency and feature selection time. PMID:25974230

Dynamic frame resizing with convolutional neural network for efficient video compression

NASA Astrophysics Data System (ADS)

Kim, Jaehwan; Park, Youngo; Choi, Kwang Pyo; Lee, JongSeok; Jeon, Sunyoung; Park, JeongHoon

2017-09-01

In the past, video codecs such as vc-1 and H.263 used a technique to encode reduced-resolution video and restore original resolution from the decoder for improvement of coding efficiency. The techniques of vc-1 and H.263 Annex Q are called dynamic frame resizing and reduced-resolution update mode, respectively. However, these techniques have not been widely used due to limited performance improvements that operate well only under specific conditions. In this paper, video frame resizing (reduced/restore) technique based on machine learning is proposed for improvement of coding efficiency. The proposed method features video of low resolution made by convolutional neural network (CNN) in encoder and reconstruction of original resolution using CNN in decoder. The proposed method shows improved subjective performance over all the high resolution videos which are dominantly consumed recently. In order to assess subjective quality of the proposed method, Video Multi-method Assessment Fusion (VMAF) which showed high reliability among many subjective measurement tools was used as subjective metric. Moreover, to assess general performance, diverse bitrates are tested. Experimental results showed that BD-rate based on VMAF was improved by about 51% compare to conventional HEVC. Especially, VMAF values were significantly improved in low bitrate. Also, when the method is subjectively tested, it had better subjective visual quality in similar bit rate.

Priming Dental Pulp Stem Cells With Fibroblast Growth Factor-2 Increases Angiogenesis of Implanted Tissue-Engineered Constructs Through Hepatocyte Growth Factor and Vascular Endothelial Growth Factor Secretion.

PubMed

Gorin, Caroline; Rochefort, Gael Y; Bascetin, Rumeyza; Ying, Hanru; Lesieur, Julie; Sadoine, Jérémy; Beckouche, Nathan; Berndt, Sarah; Novais, Anita; Lesage, Matthieu; Hosten, Benoit; Vercellino, Laetitia; Merlet, Pascal; Le-Denmat, Dominique; Marchiol, Carmen; Letourneur, Didier; Nicoletti, Antonino; Vital, Sibylle Opsahl; Poliard, Anne; Salmon, Benjamin; Muller, Laurent; Chaussain, Catherine; Germain, Stéphane

2016-03-01

Tissue engineering strategies based on implanting cellularized biomaterials are promising therapeutic approaches for the reconstruction of large tissue defects. A major hurdle for the reliable establishment of such therapeutic approaches is the lack of rapid blood perfusion of the tissue construct to provide oxygen and nutrients. Numerous sources of mesenchymal stem cells (MSCs) displaying angiogenic potential have been characterized in the past years, including the adult dental pulp. Establishment of efficient strategies for improving angiogenesis in tissue constructs is nevertheless still an important challenge. Hypoxia was proposed as a priming treatment owing to its capacity to enhance the angiogenic potential of stem cells through vascular endothelial growth factor (VEGF) release. The present study aimed to characterize additional key factors regulating the angiogenic capacity of such MSCs, namely, dental pulp stem cells derived from deciduous teeth (SHED). We identified fibroblast growth factor-2 (FGF-2) as a potent inducer of the release of VEGF and hepatocyte growth factor (HGF) by SHED. We found that FGF-2 limited hypoxia-induced downregulation of HGF release. Using three-dimensional culture models of angiogenesis, we demonstrated that VEGF and HGF were both responsible for the high angiogenic potential of SHED through direct targeting of endothelial cells. In addition, FGF-2 treatment increased the fraction of Stro-1+/CD146+ progenitor cells. We then applied in vitro FGF-2 priming to SHED before encapsulation in hydrogels and in vivo subcutaneous implantation. Our results showed that FGF-2 priming is more efficient than hypoxia at increasing SHED-induced vascularization compared with nonprimed controls. Altogether, these data demonstrate that FGF-2 priming enhances the angiogenic potential of SHED through the secretion of both HGF and VEGF. ©AlphaMed Press.

Frontier-based techniques in measuring hospital efficiency in Iran: a systematic review and meta-regression analysis

PubMed Central

2013-01-01

Background In recent years, there has been growing interest in measuring the efficiency of hospitals in Iran and several studies have been conducted on the topic. The main objective of this paper was to review studies in the field of hospital efficiency and examine the estimated technical efficiency (TE) of Iranian hospitals. Methods Persian and English databases were searched for studies related to measuring hospital efficiency in Iran. Ordinary least squares (OLS) regression models were applied for statistical analysis. The PRISMA guidelines were followed in the search process. Results A total of 43 efficiency scores from 29 studies were retrieved and used to approach the research question. Data envelopment analysis was the principal frontier efficiency method in the estimation of efficiency scores. The pooled estimate of mean TE was 0.846 (±0.134). There was a considerable variation in the efficiency scores between the different studies performed in Iran. There were no differences in efficiency scores between data envelopment analysis (DEA) and stochastic frontier analysis (SFA) techniques. The reviewed studies are generally similar and suffer from similar methodological deficiencies, such as no adjustment for case mix and quality of care differences. The results of OLS regression revealed that studies that included more variables and more heterogeneous hospitals generally reported higher TE. Larger sample size was associated with reporting lower TE. Conclusions The features of frontier-based techniques had a profound impact on the efficiency scores among Iranian hospital studies. These studies suffer from major methodological deficiencies and were of sub-optimal quality, limiting their validity and reliability. It is suggested that improving data collection and processing in Iranian hospital databases may have a substantial impact on promoting the quality of research in this field. PMID:23945011

Robust infrared target tracking using discriminative and generative approaches

NASA Astrophysics Data System (ADS)

Asha, C. S.; Narasimhadhan, A. V.

2017-09-01

The process of designing an efficient tracker for thermal infrared imagery is one of the most challenging tasks in computer vision. Although a lot of advancement has been achieved in RGB videos over the decades, textureless and colorless properties of objects in thermal imagery pose hard constraints in the design of an efficient tracker. Tracking of an object using a single feature or a technique often fails to achieve greater accuracy. Here, we propose an effective method to track an object in infrared imagery based on a combination of discriminative and generative approaches. The discriminative technique makes use of two complementary methods such as kernelized correlation filter with spatial feature and AdaBoost classifier with pixel intesity features to operate in parallel. After obtaining optimized locations through discriminative approaches, the generative technique is applied to determine the best target location using a linear search method. Unlike the baseline algorithms, the proposed method estimates the scale of the target by Lucas-Kanade homography estimation. To evaluate the proposed method, extensive experiments are conducted on 17 challenging infrared image sequences obtained from LTIR dataset and a significant improvement of mean distance precision and mean overlap precision is accomplished as compared with the existing trackers. Further, a quantitative and qualitative assessment of the proposed approach with the state-of-the-art trackers is illustrated to clearly demonstrate an overall increase in performance.

Automatic system for radar echoes filtering based on textural features and artificial intelligence

NASA Astrophysics Data System (ADS)

Hedir, Mehdia; Haddad, Boualem

2017-10-01

Among the very popular Artificial Intelligence (AI) techniques, Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been retained to process Ground Echoes (GE) on meteorological radar images taken from Setif (Algeria) and Bordeaux (France) with different climates and topologies. To achieve this task, AI techniques were associated with textural approaches. We used Gray Level Co-occurrence Matrix (GLCM) and Completed Local Binary Pattern (CLBP); both methods were largely used in image analysis. The obtained results show the efficiency of texture to preserve precipitations forecast on both sites with the accuracy of 98% on Bordeaux and 95% on Setif despite the AI technique used. 98% of GE are suppressed with SVM, this rate is outperforming ANN skills. CLBP approach associated to SVM eliminates 98% of GE and preserves precipitations forecast on Bordeaux site better than on Setif's, while it exhibits lower accuracy with ANN. SVM classifier is well adapted to the proposed application since the average filtering rate is 95-98% with texture and 92-93% with CLBP. These approaches allow removing Anomalous Propagations (APs) too with a better accuracy of 97.15% with texture and SVM. In fact, textural features associated to AI techniques are an efficient tool for incoherent radars to surpass spurious echoes.

Multi-talker background and semantic priming effect

PubMed Central

Dekerle, Marie; Boulenger, Véronique; Hoen, Michel; Meunier, Fanny

2014-01-01

The reported studies have aimed to investigate whether informational masking in a multi-talker background relies on semantic interference between the background and target using an adapted semantic priming paradigm. In 3 experiments, participants were required to perform a lexical decision task on a target item embedded in backgrounds composed of 1–4 voices. These voices were Semantically Consistent (SC) voices (i.e., pronouncing words sharing semantic features with the target) or Semantically Inconsistent (SI) voices (i.e., pronouncing words semantically unrelated to each other and to the target). In the first experiment, backgrounds consisted of 1 or 2 SC voices. One and 2 SI voices were added in Experiments 2 and 3, respectively. The results showed a semantic priming effect only in the conditions where the number of SC voices was greater than the number of SI voices, suggesting that semantic priming depended on prime intelligibility and strategic processes. However, even if backgrounds were composed of 3 or 4 voices, reducing intelligibility, participants were able to recognize words from these backgrounds, although no semantic priming effect on the targets was observed. Overall this finding suggests that informational masking can occur at a semantic level if intelligibility is sufficient. Based on the Effortfulness Hypothesis, we also suggest that when there is an increased difficulty in extracting target signals (caused by a relatively high number of voices in the background), more cognitive resources were allocated to formal processes (i.e., acoustic and phonological), leading to a decrease in available resources for deeper semantic processing of background words, therefore preventing semantic priming from occurring. PMID:25400572

Automated Ground-based Time-lapse Camera Monitoring of West Greenland ice sheet outlet Glaciers: Challenges and Solutions

NASA Astrophysics Data System (ADS)

Ahn, Y.; Box, J. E.; Balog, J.; Lewinter, A.

2008-12-01

Monitoring Greenland outlet glaciers using remotely sensed data has drawn a great attention in earth science communities for decades and time series analysis of sensory data has provided important variability information of glacier flow by detecting speed and thickness changes, tracking features and acquiring model input. Thanks to advancements of commercial digital camera technology and increased solid state storage, we activated automatic ground-based time-lapse camera stations with high spatial/temporal resolution in west Greenland outlet and collected one-hour interval data continuous for more than one year at some but not all sites. We believe that important information of ice dynamics are contained in these data and that terrestrial mono-/stereo-photogrammetry can provide theoretical/practical fundamentals in data processing along with digital image processing techniques. Time-lapse images over periods in west Greenland indicate various phenomenon. Problematic is rain, snow, fog, shadows, freezing of water on camera enclosure window, image over-exposure, camera motion, sensor platform drift, and fox chewing of instrument cables, and the pecking of plastic window by ravens. Other problems include: feature identification, camera orientation, image registration, feature matching in image pairs, and feature tracking. Another obstacle is that non-metric digital camera contains large distortion to be compensated for precise photogrammetric use. Further, a massive number of images need to be processed in a way that is sufficiently computationally efficient. We meet these challenges by 1) identifying problems in possible photogrammetric processes, 2) categorizing them based on feasibility, and 3) clarifying limitation and alternatives, while emphasizing displacement computation and analyzing regional/temporal variability. We experiment with mono and stereo photogrammetric techniques in the aide of automatic correlation matching for efficiently handling the enormous data volumes.

Symmetric digit sets for elliptic curve scalar multiplication without precomputation

PubMed Central

Heuberger, Clemens; Mazzoli, Michela

2014-01-01

We describe a method to perform scalar multiplication on two classes of ordinary elliptic curves, namely E:y2=x3+Ax in prime characteristic p≡1mod4, and E:y2=x3+B in prime characteristic p≡1mod3. On these curves, the 4-th and 6-th roots of unity act as (computationally efficient) endomorphisms. In order to optimise the scalar multiplication, we consider a width-w-NAF (Non-Adjacent Form) digit expansion of positive integers to the complex base of τ, where τ is a zero of the characteristic polynomial x2−tx+p of the Frobenius endomorphism associated to the curve. We provide a precomputationless algorithm by means of a convenient factorisation of the unit group of residue classes modulo τ in the endomorphism ring, whereby we construct a digit set consisting of powers of subgroup generators, which are chosen as efficient endomorphisms of the curve. PMID:25190900

No negative priming without cognitive control.

PubMed

de Fockert, Jan W; Mizon, Guy A; D'Ubaldo, Mariangela

2010-12-01

There is evidence that the efficiency of selective attention depends on the availability of cognitive control mechanisms as distractor processing has been found to increase with high load on working memory or dual task coordination (Lavie, Hirst, de Fockert, & Viding, 2004). We tested the prediction that cognitive control load would also affect the negative priming effect produced when a distractor from 1 trial appears as a target on the next trial. We measured priming on trials that involved either high or low cognitive control load, and found that under high control load, negative priming was eliminated, and could even be reversed to positive priming, suggesting that the negative priming effect depends on the availability of cognitive control resources.

Gas/vapour separation using ultra-microporous metal-organic frameworks: insights into the structure/separation relationship.

PubMed

Adil, Karim; Belmabkhout, Youssef; Pillai, Renjith S; Cadiau, Amandine; Bhatt, Prashant M; Assen, Ayalew H; Maurin, Guillaume; Eddaoudi, Mohamed

2017-06-06

The separation of related molecules with similar physical/chemical properties is of prime industrial importance and practically entails a substantial energy penalty, typically necessitating the operation of energy-demanding low temperature fractional distillation techniques. Certainly research efforts, in academia and industry alike, are ongoing with the main aim to develop advanced functional porous materials to be adopted as adsorbents for the effective and energy-efficient separation of various important commodities. Of special interest is the subclass of metal-organic frameworks (MOFs) with pore aperture sizes below 5-7 Å, namely ultra-microporous MOFs, which in contrast to conventional zeolites and activated carbons show great prospects for addressing key challenges in separations pertaining to energy and environmental sustainability, specifically materials for carbon capture and separation of olefin/paraffin, acetylene/ethylene, linear/branched alkanes, xenon/krypton, etc. In this tutorial review we discuss the latest developments in ultra-microporous MOF adsorbents and their use as separating agents via thermodynamics and/or kinetics and molecular sieving. Appreciably, we provide insights into the distinct microscopic mechanisms governing the resultant separation performances, and suggest a plausible correlation between the inherent structural features/topology of MOFs and the associated gas/vapour separation performance.

Meta-analyses are no substitute for registered replications: a skeptical perspective on religious priming

PubMed Central

van Elk, Michiel; Matzke, Dora; Gronau, Quentin F.; Guan, Maime; Vandekerckhove, Joachim; Wagenmakers, Eric-Jan

2015-01-01

According to a recent meta-analysis, religious priming has a positive effect on prosocial behavior (Shariff et al., 2015). We first argue that this meta-analysis suffers from a number of methodological shortcomings that limit the conclusions that can be drawn about the potential benefits of religious priming. Next we present a re-analysis of the religious priming data using two different meta-analytic techniques. A Precision-Effect Testing–Precision-Effect-Estimate with Standard Error (PET-PEESE) meta-analysis suggests that the effect of religious priming is driven solely by publication bias. In contrast, an analysis using Bayesian bias correction suggests the presence of a religious priming effect, even after controlling for publication bias. These contradictory statistical results demonstrate that meta-analytic techniques alone may not be sufficiently robust to firmly establish the presence or absence of an effect. We argue that a conclusive resolution of the debate about the effect of religious priming on prosocial behavior – and about theoretically disputed effects more generally – requires a large-scale, preregistered replication project, which we consider to be the sole remedy for the adverse effects of experimenter bias and publication bias. PMID:26441741

Research on facial expression simulation based on depth image

NASA Astrophysics Data System (ADS)

Ding, Sha-sha; Duan, Jin; Zhao, Yi-wu; Xiao, Bo; Wang, Hao

2017-11-01

Nowadays, face expression simulation is widely used in film and television special effects, human-computer interaction and many other fields. Facial expression is captured by the device of Kinect camera .The method of AAM algorithm based on statistical information is employed to detect and track faces. The 2D regression algorithm is applied to align the feature points. Among them, facial feature points are detected automatically and 3D cartoon model feature points are signed artificially. The aligned feature points are mapped by keyframe techniques. In order to improve the animation effect, Non-feature points are interpolated based on empirical models. Under the constraint of Bézier curves we finish the mapping and interpolation. Thus the feature points on the cartoon face model can be driven if the facial expression varies. In this way the purpose of cartoon face expression simulation in real-time is came ture. The experiment result shows that the method proposed in this text can accurately simulate the facial expression. Finally, our method is compared with the previous method. Actual data prove that the implementation efficiency is greatly improved by our method.

Effects of stimulus font and size on masked repetition priming: An event-related potentials (ERP) investigation.

PubMed

Chauncey, Krysta; Holcomb, Phillip J; Grainger, Jonathan

2008-01-01

The size and font of target words were manipulated in a masked repetition priming paradigm with ERP recordings. Repetition priming effects were found in four ERP components: the N/P150, N250, P325, and N400. Neither a change in font nor a change in size across prime and target were found to affect repetition priming in the N250, P325, and N400 components. Changing font was, however, found to affect repetition priming in the N/P150 component, while the interaction between repetition priming and size was not significant in this component. These results confirm our interpretation of the N/P150 as a component sensitive to feature-level processing, and suggest that the type of prelexical and lexical processing reflected in the N250, P325, and N400 components is performed on representations that are invariant to changes in both font and size.

PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine

PubMed Central

Manavalan, Balachandran; Shin, Tae H.; Lee, Gwang

2018-01-01

Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs) prior to in vitro experimentation is needed. Here, we describe a support vector machine (SVM)-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features. A feature selection protocol was employed to identify the optimal features from a large set that included amino acid composition, dipeptide composition, atomic composition, physicochemical properties, and chain-transition-distribution. PVP-SVM achieved an accuracy of 0.870 during leave-one-out cross-validation, which was 6% higher than control SVM predictors trained with all features, indicating the efficiency of the feature selection method. Furthermore, PVP-SVM displayed superior performance compared to the currently available method, PVPred, and two other machine-learning methods developed in this study when objectively evaluated with an independent dataset. For the convenience of the scientific community, a user-friendly and publicly accessible web server has been established at www.thegleelab.org/PVP-SVM/PVP-SVM.html. PMID:29616000

PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine.

PubMed

Manavalan, Balachandran; Shin, Tae H; Lee, Gwang

2018-01-01

Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs) prior to in vitro experimentation is needed. Here, we describe a support vector machine (SVM)-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features. A feature selection protocol was employed to identify the optimal features from a large set that included amino acid composition, dipeptide composition, atomic composition, physicochemical properties, and chain-transition-distribution. PVP-SVM achieved an accuracy of 0.870 during leave-one-out cross-validation, which was 6% higher than control SVM predictors trained with all features, indicating the efficiency of the feature selection method. Furthermore, PVP-SVM displayed superior performance compared to the currently available method, PVPred, and two other machine-learning methods developed in this study when objectively evaluated with an independent dataset. For the convenience of the scientific community, a user-friendly and publicly accessible web server has been established at www.thegleelab.org/PVP-SVM/PVP-SVM.html.

Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

PubMed

Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

2016-04-01

Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.

Sequential congruency effects: disentangling priming and conflict adaptation.

PubMed

Puccioni, Olga; Vallesi, Antonino

2012-09-01

Responding to the color of a word is slower and less accurate if the word refers to a different color (incongruent condition) than if it refers to the same color (congruent condition). This phenomenon, known as the Stroop effect, is modulated by sequential effects: it is bigger when the current trial is preceded by a congruent condition than by an incongruent one in the previous trial. Whether this phenomenon is due to priming mechanisms or to cognitive control is still debated. To disentangle the contribution of priming with respect to conflict adaptation mechanisms in determining sequential effects, two experiments were designed here with a four-alternative forced choice (4-AFC) Stroop task: in the first one only trials with complete alternations of features were used, while in the second experiment all possible types of repetitions were presented. Both response times (RTs) and errors were evaluated. Conflict adaptation effects on RTs were limited to congruent trials and were exclusively due to priming: they disappeared in the priming-free experiment and, in the second experiment, they occurred in sequences with feature repetitions but not in complete alternation sequences. Error results, instead, support the presence of conflict adaptation effects in incongruent trials. In priming-free sequences (experiment 1 and complete alternation sequences of experiment 2) with incongruent previous trials there was no error Stroop effect, while this effect was significant with congruent previous trials. These results indicate that cognitive control may modulate performance above and beyond priming effects.

Priming of plant resistance by natural compounds. Hexanoic acid as a model

PubMed Central

Aranega-Bou, Paz; de la O Leyva, Maria; Finiti, Ivan; García-Agustín, Pilar; González-Bosch, Carmen

2014-01-01

Some alternative control strategies of currently emerging plant diseases are based on the use of resistance inducers. This review highlights the recent advances made in the characterization of natural compounds that induce resistance by a priming mechanism. These include vitamins, chitosans, oligogalacturonides, volatile organic compounds, azelaic and pipecolic acid, among others. Overall, other than providing novel disease control strategies that meet environmental regulations, natural priming agents are valuable tools to help unravel the complex mechanisms underlying the induced resistance (IR) phenomenon. The data presented in this review reflect the novel contributions made from studying these natural plant inducers, with special emphasis placed on hexanoic acid (Hx), proposed herein as a model tool for this research field. Hx is a potent natural priming agent of proven efficiency in a wide range of host plants and pathogens. It can early activate broad-spectrum defenses by inducing callose deposition and the salicylic acid (SA) and jasmonic acid (JA) pathways. Later it can prime pathogen-specific responses according to the pathogen’s lifestyle. Interestingly, Hx primes redox-related genes to produce an anti-oxidant protective effect, which might be critical for limiting the infection of necrotrophs. Our Hx-IR findings also strongly suggest that it is an attractive tool for the molecular characterization of the plant alarmed state, with the added advantage of it being a natural compound. PMID:25324848

Sequence determinants of improved CRISPR sgRNA design.

PubMed

Xu, Han; Xiao, Tengfei; Chen, Chen-Hao; Li, Wei; Meyer, Clifford A; Wu, Qiu; Wu, Di; Cong, Le; Zhang, Feng; Liu, Jun S; Brown, Myles; Liu, X Shirley

2015-08-01

The CRISPR/Cas9 system has revolutionized mammalian somatic cell genetics. Genome-wide functional screens using CRISPR/Cas9-mediated knockout or dCas9 fusion-mediated inhibition/activation (CRISPRi/a) are powerful techniques for discovering phenotype-associated gene function. We systematically assessed the DNA sequence features that contribute to single guide RNA (sgRNA) efficiency in CRISPR-based screens. Leveraging the information from multiple designs, we derived a new sequence model for predicting sgRNA efficiency in CRISPR/Cas9 knockout experiments. Our model confirmed known features and suggested new features including a preference for cytosine at the cleavage site. The model was experimentally validated for sgRNA-mediated mutation rate and protein knockout efficiency. Tested on independent data sets, the model achieved significant results in both positive and negative selection conditions and outperformed existing models. We also found that the sequence preference for CRISPRi/a is substantially different from that for CRISPR/Cas9 knockout and propose a new model for predicting sgRNA efficiency in CRISPRi/a experiments. These results facilitate the genome-wide design of improved sgRNA for both knockout and CRISPRi/a studies. © 2015 Xu et al.; Published by Cold Spring Harbor Laboratory Press.

Is attention enough? A re-examination of the impact of feature-specific attention allocation on semantic priming effects in the pronunciation task.

PubMed

Becker, Manuel; Klauer, Karl Christoph; Spruyt, Adriaan

2016-02-01

In a series of articles, Spruyt and colleagues have developed the Feature-Specific Attention Allocation framework, stating that the semantic analysis of task-irrelevant stimuli is critically dependent upon dimension-specific attention allocation. In an adversarial collaboration, we replicate one experiment supporting this theory (Spruyt, de Houwer, & Hermans, 2009; Exp. 3), in which semantic priming effects in the pronunciation task were found to be restricted to stimulus dimensions that were task-relevant on induction trials. Two pilot studies showed the capability of our laboratory to detect priming effects in the pronunciation task, but also suggested that the original effect may be difficult to replicate. In this study, we tried to replicate the original experiment while ensuring adequate statistical power. Results show little evidence for dimension-specific priming effects. The present results provide further insight into the malleability of early semantic encoding processes, but also show the need for further research on this topic.

Ab Initio-Based Predictions of Hydrocarbon Combustion Chemistry

DTIC Science & Technology

2015-07-15

There are two prime objectives of the research. One is to develop and apply efficient methods for using ab initio potential energy surfaces (PESs...31-Mar-2015 Approved for Public Release; Distribution Unlimited Final Report: Ab Initio -Based Predictions of Hydrocarbon Combustion Chemistry The...Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 hydrocarbon combustion, ab initio quantum chemistry, potential energy surfaces, chemical

A fast and fully automatic registration approach based on point features for multi-source remote-sensing images

NASA Astrophysics Data System (ADS)

Yu, Le; Zhang, Dengrong; Holden, Eun-Jung

2008-07-01

Automatic registration of multi-source remote-sensing images is a difficult task as it must deal with the varying illuminations and resolutions of the images, different perspectives and the local deformations within the images. This paper proposes a fully automatic and fast non-rigid image registration technique that addresses those issues. The proposed technique performs a pre-registration process that coarsely aligns the input image to the reference image by automatically detecting their matching points by using the scale invariant feature transform (SIFT) method and an affine transformation model. Once the coarse registration is completed, it performs a fine-scale registration process based on a piecewise linear transformation technique using feature points that are detected by the Harris corner detector. The registration process firstly finds in succession, tie point pairs between the input and the reference image by detecting Harris corners and applying a cross-matching strategy based on a wavelet pyramid for a fast search speed. Tie point pairs with large errors are pruned by an error-checking step. The input image is then rectified by using triangulated irregular networks (TINs) to deal with irregular local deformations caused by the fluctuation of the terrain. For each triangular facet of the TIN, affine transformations are estimated and applied for rectification. Experiments with Quickbird, SPOT5, SPOT4, TM remote-sensing images of the Hangzhou area in China demonstrate the efficiency and the accuracy of the proposed technique for multi-source remote-sensing image registration.

How Different Types of Conceptual Relations Modulate Brain Activation during Semantic Priming

ERIC Educational Resources Information Center

Sachs, Olga; Weis, Susanne; Zellagui, Nadia; Sass, Katharina; Huber, Walter; Zvyagintsev, Mikhail; Mathiak, Klaus; Kircher, Tilo

2011-01-01

Semantic priming, a well-established technique to study conceptual representation, has thus far produced variable fMRI results, both regarding the type of priming effects and their correlation with brain activation. The aims of the current study were (a) to investigate two types of semantic relations--categorical versus associative--under…

The 'prime-ome': towards a holistic approach to priming.

PubMed

Balmer, Andrea; Pastor, Victoria; Gamir, Jordi; Flors, Victor; Mauch-Mani, Brigitte

2015-07-01

Plants can be primed to respond faster and more strongly to stress and multiple pathways, specific for the encountered challenge, are involved in priming. This adaptability of priming makes it difficult to pinpoint an exact mechanism: the same phenotypic observation might be the consequence of unrelated underlying events. Recently, details of the molecular aspects of establishing a primed state and its transfer to offspring have come to light. Advances in techniques for detection and quantification of elements spanning the fields of transcriptomics, proteomics, and metabolomics, together with adequate bioinformatics tools, will soon allow us to take a holistic approach to plant defence. This review highlights the state of the art of new strategies to study defence priming in plants and provides perspectives towards 'prime-omics'. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ab initio simulations of scanning-tunneling-microscope images with embedding techniques and application to C58-dimers on Au(111).

PubMed

Wilhelm, Jan; Walz, Michael; Stendel, Melanie; Bagrets, Alexei; Evers, Ferdinand

2013-05-14

We present a modification of the standard electron transport methodology based on the (non-equilibrium) Green's function formalism to efficiently simulate STM-images. The novel feature of this method is that it employs an effective embedding technique that allows us to extrapolate properties of metal substrates with adsorbed molecules from quantum-chemical cluster calculations. To illustrate the potential of this approach, we present an application to STM-images of C58-dimers immobilized on Au(111)-surfaces that is motivated by recent experiments.

Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

PubMed Central

Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

2014-01-01

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727

Orthographic and phonological processing in developing readers revealed by ERPs

PubMed Central

EDDY, MARIANNA D.; GRAINGER, JONATHAN; HOLCOMB, PHILLIP J.; GABRIELI, JOHN D. E.

2018-01-01

The development of neurocognitive mechanisms in single word reading was studied in children ages 8–10 years using ERPs combined with priming manipulations aimed at dissociating orthographic and phonological processes. Transposed-letter (TL) priming (barin–BRAIN vs. bosin–BRAIN) was used to assess orthographic processing, and pseudohomophone (PH) priming (brane–BRAIN vs. brant–BRAIN) was used to assess phonological processing. Children showed TL and PH priming effects on both the N250 and N400 ERP components, and the magnitude of TL priming correlated positively with reading ability, with better readers showing larger TL priming effects. Phonological priming, on the other hand, did not correlate with reading ability. The positive correlations between TL priming and reading ability in children points to a key role for flexible sublexical orthographic representations in reading development, in line with their hypothesized role in the efficient mapping of orthographic information onto semantic information in skilled readers. PMID:27671210

Ramses-GPU: Second order MUSCL-Handcock finite volume fluid solver

NASA Astrophysics Data System (ADS)

Kestener, Pierre

2017-10-01

RamsesGPU is a reimplementation of RAMSES (ascl:1011.007) which drops the adaptive mesh refinement (AMR) features to optimize 3D uniform grid algorithms for modern graphics processor units (GPU) to provide an efficient software package for astrophysics applications that do not need AMR features but do require a very large number of integration time steps. RamsesGPU provides an very efficient C++/CUDA/MPI software implementation of a second order MUSCL-Handcock finite volume fluid solver for compressible hydrodynamics as a magnetohydrodynamics solver based on the constraint transport technique. Other useful modules includes static gravity, dissipative terms (viscosity, resistivity), and forcing source term for turbulence studies, and special care was taken to enhance parallel input/output performance by using state-of-the-art libraries such as HDF5 and parallel-netcdf.

On the Prognostic Efficiency of Topological Descriptors for Magnetograms of Active Regions

NASA Astrophysics Data System (ADS)

Knyazeva, I. S.; Urtiev, F. A.; Makarenko, N. G.

2017-12-01

Solar flare prediction remains an important practical task of space weather. An increase in the amount and quality of observational data and the development of machine-learning methods has led to an improvement in prediction techniques. Additional information has been retrieved from the vector magnetograms; these have been recently supplemented by traditional line-of-sight (LOS) magnetograms. In this work, the problem of the comparative prognostic efficiency of features obtained on the basis of vector data and LOS magnetograms is discussed. Invariants obtained from a topological analysis of LOS magnetograms are used as complexity characteristics of magnetic patterns. Alternatively, the so-called SHARP parameters were used; they were calculated by the data analysis group of the Stanford University Laboratory on the basis of HMI/SDO vector magnetograms and are available online at the website (http://jsoc.stanford.edu/) with the solar dynamics observatory (SDO) database for the entire history of SDO observations. It has been found that the efficiency of large-flare prediction based on topological descriptors of LOS magnetograms in epignosis mode is at least s no worse than the results of prognostic schemes based on vector features. The advantages of the use of topological invariants based on LOS data are discussed.

[Marketing mix in a radiology department: challenges for future radiologists in management].

PubMed

Claikens, B

1998-08-01

Radiology has gained an enviable position among medial specialities. Developments in new technology expand its horizons and the volume of radiologic imaging techniques and procedures increase far more than the overall growth in health care services. In this position radiology has become a prime target for restrictions, cutbacks, controlled financing in an area of managed care and new national health care policy based on partially fixed budgets. Future health care takers have to choose the best available diagnostic and therapeutic techniques. Evidence based medicine, cost-utility analysis, diagnostic performance analysis, patient outcome analysis, technology assessment and guidelines for practice are means to guide us through our obligatory choice. Our major objective is to use the most performant available imaging technique or intervention to achieve the best possible outcome for our patient at lower possible costs. A strategic response from radiologists is required to meet the imperatives of this new management situation. They must do far more than interpret imaging procedures. They must work as efficient managers of imaging resources, organise their practices and define their marketing-strategies using the different, so-called, marketing-mix elements. The challenges will be great but the rewards are worth our best efforts. In this article we highlight the marketing responsibilities of future radiologists and their clinical practice in this new socio-economic environment and we present different useful marketing tools.

Electrophysiological Differences in the Processing of Affect Misattribution

PubMed Central

Hashimoto, Yohei; Minami, Tetsuto; Nakauchi, Shigeki

2012-01-01

The affect misattribution procedure (AMP) was proposed as a technique to measure an implicit attitude to a prime image [1]. In the AMP, neutral symbols (e.g., a Chinese pictograph, called the target) are presented, following an emotional stimulus (known as the prime). Participants often misattribute the positive or negative affect of the priming images to the targets in spite of receiving an instruction to ignore the primes. The AMP effect has been investigated using behavioral measures; however, it is difficult to identify when the AMP effect occurs in emotional processing—whether the effect may occur in the earlier attention allocation stage or in the later evaluation stage. In this study, we examined the neural correlates of affect misattribution, using event-related potential (ERP) dividing the participants into two groups based on their tendency toward affect misattribution. The ERP results showed that the amplitude of P2 was larger for the prime at the parietal location in participants showing a low tendency to misattribution than for those showing a high tendency, while the effect of judging neutral targets amiss according to the primes was reflected in the late processing of targets (LPP). In addition, the topographic pattern analysis revealed that EPN-like component to targets was correlated with the difference of AMP tendency as well as P2 to primes and LPP to targets. Taken together, the mechanism of the affective misattribution was closely related to the attention allocation processing. Our findings provide neural evidence that evaluations of neutral targets are misattributed to emotional primes. PMID:23145097

A novel methodology for querying web images

NASA Astrophysics Data System (ADS)

Prabhakara, Rashmi; Lee, Ching Cheng

2005-01-01

Ever since the advent of Internet, there has been an immense growth in the amount of image data that is available on the World Wide Web. With such a magnitude of image availability, an efficient and effective image retrieval system is required to make use of this information. This research presents an effective image matching and indexing technique that improvises on existing integrated image retrieval methods. The proposed technique follows a two-phase approach, integrating query by topic and query by example specification methods. The first phase consists of topic-based image retrieval using an improved text information retrieval (IR) technique that makes use of the structured format of HTML documents. It consists of a focused crawler that not only provides for the user to enter the keyword for the topic-based search but also, the scope in which the user wants to find the images. The second phase uses the query by example specification to perform a low-level content-based image match for the retrieval of smaller and relatively closer results of the example image. Information related to the image feature is automatically extracted from the query image by the image processing system. A technique that is not computationally intensive based on color feature is used to perform content-based matching of images. The main goal is to develop a functional image search and indexing system and to demonstrate that better retrieval results can be achieved with this proposed hybrid search technique.

A novel methodology for querying web images

NASA Astrophysics Data System (ADS)

Prabhakara, Rashmi; Lee, Ching Cheng

2004-12-01

Ever since the advent of Internet, there has been an immense growth in the amount of image data that is available on the World Wide Web. With such a magnitude of image availability, an efficient and effective image retrieval system is required to make use of this information. This research presents an effective image matching and indexing technique that improvises on existing integrated image retrieval methods. The proposed technique follows a two-phase approach, integrating query by topic and query by example specification methods. The first phase consists of topic-based image retrieval using an improved text information retrieval (IR) technique that makes use of the structured format of HTML documents. It consists of a focused crawler that not only provides for the user to enter the keyword for the topic-based search but also, the scope in which the user wants to find the images. The second phase uses the query by example specification to perform a low-level content-based image match for the retrieval of smaller and relatively closer results of the example image. Information related to the image feature is automatically extracted from the query image by the image processing system. A technique that is not computationally intensive based on color feature is used to perform content-based matching of images. The main goal is to develop a functional image search and indexing system and to demonstrate that better retrieval results can be achieved with this proposed hybrid search technique.

Improved EEG Event Classification Using Differential Energy.

PubMed

Harati, A; Golmohammadi, M; Lopez, S; Obeid, I; Picone, J

2015-12-01

Feature extraction for automatic classification of EEG signals typically relies on time frequency representations of the signal. Techniques such as cepstral-based filter banks or wavelets are popular analysis techniques in many signal processing applications including EEG classification. In this paper, we present a comparison of a variety of approaches to estimating and postprocessing features. To further aid in discrimination of periodic signals from aperiodic signals, we add a differential energy term. We evaluate our approaches on the TUH EEG Corpus, which is the largest publicly available EEG corpus and an exceedingly challenging task due to the clinical nature of the data. We demonstrate that a variant of a standard filter bank-based approach, coupled with first and second derivatives, provides a substantial reduction in the overall error rate. The combination of differential energy and derivatives produces a 24 % absolute reduction in the error rate and improves our ability to discriminate between signal events and background noise. This relatively simple approach proves to be comparable to other popular feature extraction approaches such as wavelets, but is much more computationally efficient.

Nanofiber quantum photonics

NASA Astrophysics Data System (ADS)

Nayak, Kali P.; Sadgrove, Mark; Yalla, Ramachandrarao; Le Kien, Fam; Hakuta, Kohzo

2018-07-01

Recent advances in the coherent control of single quanta of light, photons, is a topic of prime interest, and is discussed under the banner of quantum photonics. In the last decade, the subwavelength diameter waist of a tapered optical fiber, referred to as an optical nanofiber, has opened promising new avenues in the field of quantum optics, paving the way toward a versatile platform for quantum photonics applications. The key feature of the technique is that the optical field can be tightly confined in the transverse direction while propagating over long distances as a guided mode and enabling strong interaction with the surrounding medium in the evanescent region. This feature has led to surprising possibilities to manipulate single atoms and fiber-guided photons, e.g. the efficient channeling of emission from single atoms and solid-state quantum emitters into the fiber-guided modes, high optical depth with a few atoms around the nanofiber, trapping atoms around a nanofiber, and atomic memories for fiber-guided photons. Furthermore, implementing a moderate longitudinal confinement in nanofiber cavities has enabled the strong coupling regime of cavity quantum electrodynamics to be reached, and the long-range dipole–dipole interaction between quantum emitters mediated by the nanofiber offers a platform for quantum nonlinear optics with an ensemble of atoms. In addition, the presence of a longitudinal component of the guided field has led to unique capabilities for chiral light–matter interactions on nanofibers. In this article, we review the key developments of the nanofiber technology toward a vision for quantum photonics on an all-fiber interface.

Seasonal and regional diversity of maple sap microbiota revealed using community PCR fingerprinting and 16S rRNA gene clone libraries.

PubMed

Filteau, Marie; Lagacé, Luc; LaPointe, Gisèle; Roy, Denis

2010-04-01

An arbitrary primed community PCR fingerprinting technique based on capillary electrophoresis was developed to study maple sap microbial community characteristics among 19 production sites in Québec over the tapping season. Presumptive fragment identification was made with corresponding fingerprint profiles of bacterial isolate cultures. Maple sap microbial communities were subsequently compared using a representative subset of 13 16S rRNA gene clone libraries followed by gene sequence analysis. Results from both methods indicated that all maple sap production sites and flow periods shared common microbiota members, but distinctive features also existed. Changes over the season in relative abundance of predominant populations showed evidence of a common pattern. Pseudomonas (64%) and Rahnella (8%) were the most abundantly and frequently represented genera of the 2239 sequences analyzed. Janthinobacterium, Leuconostoc, Lactococcus, Weissella, Epilithonimonas and Sphingomonas were revealed as occasional contaminants in maple sap. Maple sap microbiota showed a low level of deep diversity along with a high variation of similar 16S rRNA gene sequences within the Pseudomonas genus. Predominance of Pseudomonas is suggested as a typical feature of maple sap microbiota across geographical regions, production sites, and sap flow periods.

A series connection architecture for large-area organic photovoltaic modules with a 7.5% module efficiency.

PubMed

Hong, Soonil; Kang, Hongkyu; Kim, Geunjin; Lee, Seongyu; Kim, Seok; Lee, Jong-Hoon; Lee, Jinho; Yi, Minjin; Kim, Junghwan; Back, Hyungcheol; Kim, Jae-Ryoung; Lee, Kwanghee

2016-01-05

The fabrication of organic photovoltaic modules via printing techniques has been the greatest challenge for their commercial manufacture. Current module architecture, which is based on a monolithic geometry consisting of serially interconnecting stripe-patterned subcells with finite widths, requires highly sophisticated patterning processes that significantly increase the complexity of printing production lines and cause serious reductions in module efficiency due to so-called aperture loss in series connection regions. Herein we demonstrate an innovative module structure that can simultaneously reduce both patterning processes and aperture loss. By using a charge recombination feature that occurs at contacts between electron- and hole-transport layers, we devise a series connection method that facilitates module fabrication without patterning the charge transport layers. With the successive deposition of component layers using slot-die and doctor-blade printing techniques, we achieve a high module efficiency reaching 7.5% with area of 4.15 cm(2).

Diagnosing and ranking retinopathy disease level using diabetic fundus image recuperation approach.

PubMed

Somasundaram, K; Rajendran, P Alli

2015-01-01

Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.

Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach

PubMed Central

Somasundaram, K.; Alli Rajendran, P.

2015-01-01

Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time. PMID:25945362

A Query Expansion Framework in Image Retrieval Domain Based on Local and Global Analysis

PubMed Central

Rahman, M. M.; Antani, S. K.; Thoma, G. R.

2011-01-01

We present an image retrieval framework based on automatic query expansion in a concept feature space by generalizing the vector space model of information retrieval. In this framework, images are represented by vectors of weighted concepts similar to the keyword-based representation used in text retrieval. To generate the concept vocabularies, a statistical model is built by utilizing Support Vector Machine (SVM)-based classification techniques. The images are represented as “bag of concepts” that comprise perceptually and/or semantically distinguishable color and texture patches from local image regions in a multi-dimensional feature space. To explore the correlation between the concepts and overcome the assumption of feature independence in this model, we propose query expansion techniques in the image domain from a new perspective based on both local and global analysis. For the local analysis, the correlations between the concepts based on the co-occurrence pattern, and the metrical constraints based on the neighborhood proximity between the concepts in encoded images, are analyzed by considering local feedback information. We also analyze the concept similarities in the collection as a whole in the form of a similarity thesaurus and propose an efficient query expansion based on the global analysis. The experimental results on a photographic collection of natural scenes and a biomedical database of different imaging modalities demonstrate the effectiveness of the proposed framework in terms of precision and recall. PMID:21822350

Distractor-based stimulus-response bindings retrieve decisions independent of motor programs.

PubMed

Nett, Nadine; Bröder, Arndt; Frings, Christian

2016-11-01

Research on the distractor response binding (DRB) effect (Frings, Rothermund, & Wentura, 2007) suggests that distractors are integrated with target responses into an event file or stimulus-response (SR) episode. The whole event file is retrieved when the distractor is repeated and as a consequence distractors can retrieve previous responses. Nett, Bröder, and Frings (2015) argued that even decisions under uncertainty are integrated into event files and can later on be retrieved by distractors. However, their paradigm did not allow disentangling the retrieval of decisions from the retrieval of motor programs. Here we disentangled the retrieval of decisions and motor programs by assuring that retrieved decisions were not confounded by the repetitions of motor programs. In particular, in two experiments using a sequential prime-probe distractor priming task participants used other keys or other effectors for prime and probe responses; nevertheless repeated task-irrelevant distractors increased the probability that participants repeated the prime decision irrespective of motor programs. Thus, decision features can become part of an event-file and directly be retrieved by irrelevant information suggesting that bindings have an even higher flexibility and ubiquity than previously assumed. Copyright © 2016 Elsevier B.V. All rights reserved.

A feature selection approach towards progressive vector transmission over the Internet

NASA Astrophysics Data System (ADS)

Miao, Ru; Song, Jia; Feng, Min

2017-09-01

WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet.

Evaluation of mathematical algorithms for automatic patient alignment in radiosurgery.

PubMed

Williams, Kenneth M; Schulte, Reinhard W; Schubert, Keith E; Wroe, Andrew J

2015-06-01

Image registration techniques based on anatomical features can serve to automate patient alignment for intracranial radiosurgery procedures in an effort to improve the accuracy and efficiency of the alignment process as well as potentially eliminate the need for implanted fiducial markers. To explore this option, four two-dimensional (2D) image registration algorithms were analyzed: the phase correlation technique, mutual information (MI) maximization, enhanced correlation coefficient (ECC) maximization, and the iterative closest point (ICP) algorithm. Digitally reconstructed radiographs from the treatment planning computed tomography scan of a human skull were used as the reference images, while orthogonal digital x-ray images taken in the treatment room were used as the captured images to be aligned. The accuracy of aligning the skull with each algorithm was compared to the alignment of the currently practiced procedure, which is based on a manual process of selecting common landmarks, including implanted fiducials and anatomical skull features. Of the four algorithms, three (phase correlation, MI maximization, and ECC maximization) demonstrated clinically adequate (ie, comparable to the standard alignment technique) translational accuracy and improvements in speed compared to the interactive, user-guided technique; however, the ICP algorithm failed to give clinically acceptable results. The results of this work suggest that a combination of different algorithms may provide the best registration results. This research serves as the initial groundwork for the translation of automated, anatomy-based 2D algorithms into a real-world system for 2D-to-2D image registration and alignment for intracranial radiosurgery. This may obviate the need for invasive implantation of fiducial markers into the skull and may improve treatment room efficiency and accuracy. © The Author(s) 2014.

Attention please: evaluative priming effects in a valent/non-valent categorisation task (reply to Werner & Rothermund, 2013).

PubMed

Spruyt, Adriaan

2014-04-01

It has previously been argued (a) that automatic evaluative stimulus processing is dependent upon feature-specific attention allocation (FSAA) and (b) that evaluative priming effects can arise in the absence of dimensional overlap between the prime set and the response set. In opposition to these claims, Werner and Rothermund (2013) recently reported that they were unable to replicate the evaluative priming effect in a valent/non-valent categorisation task. In this manuscript, I report the results of a conceptual replication of the studies by Werner and Rothermund (2013). A clear-cut evaluative priming effect was found, thus supporting the initial claims about FSAA and dimensional overlap. An explanation for these divergent findings is discussed.

Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Wismüller, Axel

2015-01-01

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns.

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

PubMed

Rahman, Md Mostafizur; Fattah, Shaikh Anowarul

2017-01-01

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

Emulsion based cast booster - a priming system

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

Gupta, R.N.; Mishra, A.K.

2005-07-01

This paper explores the potential of emulsion based cast booster to be used as primer to initiate bulk delivered emulsion explosives used in mines. An attempt has been made for comparative study between conventional cast booster and emulsion based cast booster in terms of the initiation process developed and their capability to develop and maintain the stable detonation process in the column explosives. The study has been conducted using a continuous velocity of detonation (VOD) measuring instrument. During this study three blasts have been monitored. In each blast two holes have been selected for study, the first hole being initiatedmore » with conventional cast booster while the other one with emulsion based cast booster. The findings of the study advocates that emulsion based cast booster is capable of efficient priming of bulk delivered column explosive with stable detonation process in the column. Further, the booster had advantages over the conventional PETN/TNT based cast booster. 5 refs., 2 figs., 1 tab., 1 photo.« less

Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

PubMed

Sabooh, M Fazli; Iqbal, Nadeem; Khan, Mukhtaj; Khan, Muslim; Maqbool, H F

2018-05-01

This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (m 5 C) plays a vital role in a number of biological processes. For better comprehension of the biological functions and mechanism it is necessary to recognize m 5 C sites in RNA precisely. The laboratory techniques and procedures are available to identify m 5 C sites in RNA, but these procedures require a lot of time and resources. This study develops a new computational method for extracting the features of RNA sequence. In this method, first the RNA sequence is encoded via composite feature vector, then, for the selection of discriminate features, the minimum-redundancy-maximum-relevance algorithm was used. Secondly, the classification method used has been based on a support vector machine by using jackknife cross validation test. The suggested method efficiently identifies m 5 C sites from non- m 5 C sites and the outcome of the suggested algorithm is 93.33% with sensitivity of 90.0 and specificity of 96.66 on bench mark datasets. The result exhibits that proposed algorithm shown significant identification performance compared to the existing computational techniques. This study extends the knowledge about the occurrence sites of RNA modification which paves the way for better comprehension of the biological uses and mechanism. Copyright © 2018 Elsevier Ltd. All rights reserved.

Rapid modulation of spoken word recognition by visual primes.

PubMed

Okano, Kana; Grainger, Jonathan; Holcomb, Phillip J

2016-02-01

In a masked cross-modal priming experiment with ERP recordings, spoken Japanese words were primed with words written in one of the two syllabary scripts of Japanese. An early priming effect, peaking at around 200ms after onset of the spoken word target, was seen in left lateral electrode sites for Katakana primes, and later effects were seen for both Hiragana and Katakana primes on the N400 ERP component. The early effect is thought to reflect the efficiency with which words in Katakana script make contact with sublexical phonological representations involved in spoken language comprehension, due to the particular way this script is used by Japanese readers. This demonstrates fast-acting influences of visual primes on the processing of auditory target words, and suggests that briefly presented visual primes can influence sublexical processing of auditory target words. The later N400 priming effects, on the other hand, most likely reflect cross-modal influences on activity at the level of whole-word phonology and semantics.

Rapid modulation of spoken word recognition by visual primes

PubMed Central

Okano, Kana; Grainger, Jonathan; Holcomb, Phillip J.

2015-01-01

In a masked cross-modal priming experiment with ERP recordings, spoken Japanese words were primed with words written in one of the two syllabary scripts of Japanese. An early priming effect, peaking at around 200ms after onset of the spoken word target, was seen in left lateral electrode sites for Katakana primes, and later effects were seen for both Hiragana and Katakana primes on the N400 ERP component. The early effect is thought to reflect the efficiency with which words in Katakana script make contact with sublexical phonological representations involved in spoken language comprehension, due to the particular way this script is used by Japanese readers. This demonstrates fast-acting influences of visual primes on the processing of auditory target words, and suggests that briefly presented visual primes can influence sublexical processing of auditory target words. The later N400 priming effects, on the other hand, most likely reflect cross-modal influences on activity at the level of whole-word phonology and semantics. PMID:26516296

Immunization Route Dictates Cross-Priming Efficiency and Impacts the Optimal Timing of Adjuvant Delivery

PubMed Central

Bouvier, Isabelle; Jusforgues-Saklani, Hélène; Lim, Annick; Lemaître, Fabrice; Lemercier, Brigitte; Auriau, Charlotte; Nicola, Marie-Anne; Leroy, Sandrine; Law, Helen K.; Bandeira, Antonio; Moon, James J.; Bousso, Philippe; Albert, Matthew L.

2011-01-01

Delivery of cell-associated antigen represents an important strategy for vaccination. While many experimental models have been developed in order to define the critical parameters for efficient cross-priming, few have utilized quantitative methods that permit the study of the endogenous repertoire. Comparing different strategies of immunization, we report that local delivery of cell-associated antigen results in delayed T cell cross-priming due to the increased time required for antigen capture and presentation. In comparison, delivery of disseminated antigen resulted in rapid T cell priming. Surprisingly, local injection of cell-associated antigen, while slower, resulted in the differentiation of a more robust, polyfunctional, effector response. We also evaluated the combination of cell-associated antigen with poly I:C delivery and observed an immunization route-specific effect regarding the optimal timing of innate immune stimulation. These studies highlight the importance of considering the timing and persistence of antigen presentation, and suggest that intradermal injection with delayed adjuvant delivery is the optimal strategy for achieving CD8+ T cell cross-priming. PMID:22566860

Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method.

PubMed

Batres-Mendoza, Patricia; Ibarra-Manzano, Mario A; Guerra-Hernandez, Erick I; Almanza-Ojeda, Dora L; Montoro-Sanjose, Carlos R; Romero-Troncoso, Rene J; Rostro-Gonzalez, Horacio

2017-01-01

We present an improvement to the quaternion-based signal analysis (QSA) technique to extract electroencephalography (EEG) signal features with a view to developing real-time applications, particularly in motor imagery (IM) cognitive processes. The proposed methodology (iQSA, improved QSA) extracts features such as the average, variance, homogeneity, and contrast of EEG signals related to motor imagery in a more efficient manner (i.e., by reducing the number of samples needed to classify the signal and improving the classification percentage) compared to the original QSA technique. Specifically, we can sample the signal in variable time periods (from 0.5 s to 3 s, in half-a-second intervals) to determine the relationship between the number of samples and their effectiveness in classifying signals. In addition, to strengthen the classification process a number of boosting-technique-based decision trees were implemented. The results show an 82.30% accuracy rate for 0.5 s samples and 73.16% for 3 s samples. This is a significant improvement compared to the original QSA technique that offered results from 33.31% to 40.82% without sampling window and from 33.44% to 41.07% with sampling window, respectively. We can thus conclude that iQSA is better suited to develop real-time applications.

Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method

PubMed Central

Batres-Mendoza, Patricia; Guerra-Hernandez, Erick I.; Almanza-Ojeda, Dora L.; Montoro-Sanjose, Carlos R.

2017-01-01

We present an improvement to the quaternion-based signal analysis (QSA) technique to extract electroencephalography (EEG) signal features with a view to developing real-time applications, particularly in motor imagery (IM) cognitive processes. The proposed methodology (iQSA, improved QSA) extracts features such as the average, variance, homogeneity, and contrast of EEG signals related to motor imagery in a more efficient manner (i.e., by reducing the number of samples needed to classify the signal and improving the classification percentage) compared to the original QSA technique. Specifically, we can sample the signal in variable time periods (from 0.5 s to 3 s, in half-a-second intervals) to determine the relationship between the number of samples and their effectiveness in classifying signals. In addition, to strengthen the classification process a number of boosting-technique-based decision trees were implemented. The results show an 82.30% accuracy rate for 0.5 s samples and 73.16% for 3 s samples. This is a significant improvement compared to the original QSA technique that offered results from 33.31% to 40.82% without sampling window and from 33.44% to 41.07% with sampling window, respectively. We can thus conclude that iQSA is better suited to develop real-time applications. PMID:29348744

Predicting lymph node output efficiency using systems biology

PubMed Central

Gong, Chang; Mattila, Joshua T.; Miller, Mark; Flynn, JoAnne L.; Linderman, Jennifer J.; Kirschner, D.

2013-01-01

Dendritic cells (DCs) capture pathogens and foreign antigen (Ag) in peripheral tissues and migrate to secondary lymphoid tissues, such as lymph nodes (LNs), where they present processed Ag as MHC-bound peptide (pMHC) to naïve T cells. Interactions between DCs and T cells result, over periods of hours, in activation, clonal expansion and differentiation of antigen-specific T cells, leading to primed cells that can now participate in immune responses. Two-photon microscopy (2PM) has been widely adopted to analyze lymphocyte dynamics and can serve as a powerful in vivo assay for cell trafficking and activation over short length and time scales. Linking biological phenomena between vastly different spatiotemporal scales can be achieved using a systems biology approach. We developed a 3D agent-based cellular model of a LN that allows for the simultaneous in silico simulation of T cell trafficking, activation and production of effector cells under different antigen (Ag) conditions. The model anatomy is based on in situ analysis of LN sections (from primates and mice) and cell dynamics based on quantitative measurements from 2PM imaging of mice. Our simulations make three important predictions. First, T cell encounters by DCs and T cell receptor (TCR) repertoire scanning are more efficient in a 3D model compared with 2D, suggesting that a 3D model is needed to analyze LN function. Second, LNs are able to produce primed CD4+T cells at the same efficiency over broad ranges of cognate frequencies (from 10−5 to 10−2). Third, reducing the time that naïve T cells are required to bind DCs before becoming activated will increase the rate at which effector cells are produced. This 3D model provides a robust platform to study how T cell trafficking and activation dynamics relate to the efficiency of T cell priming and clonal expansion. We envision that this systems biology approach will provide novel insights for guiding vaccine development and understanding immune responses to infection. PMID:23816876

Perceptual latency priming by masked and unmasked stimuli: evidence for an attentional interpretation.

PubMed

Scharlau, Ingrid; Neumann, Odmar

2003-08-01

Four experiments investigated the influence of a metacontrast-masked prime on temporal order judgments. The main results were (1) that a masked prime reduced the latency of the mask's conscious perception (perceptual latency priming), (2) that this effect was independent of whether the prime suffered strong or weak masking, (3) that it was unaffected by the degree of visual similarity between the prime and the mask, and that (4) there was no difference between congruent and incongruent primes. Finding (1) suggests that location cueing affects not only response times but also the latency of conscious perception. (2) The finding that priming was unaffected by the prime's detectability argues against a response bias interpretation of this effect. (3) Since visual similarity had no effect on the prime's efficiency, it is unlikely that sensory priming was involved. (4) The lack of a divergence between the effects of congruent and incongruent primes implies a functional difference between the judgments in the temporal order judgment task and speeded responses that have demonstrated differential effects of congruent and incongruent primes (e.g., Klotz & Neumann, 1999). These results can best be interpreted by assuming that the prime affects perceptual latency by initiating a shift of attention, as suggested by the Asynchronous Updating Model (AUM; Neumann 1978, 1982).

Compressing random microstructures via stochastic Wang tilings.

PubMed

Novák, Jan; Kučerová, Anna; Zeman, Jan

2012-10-01

This Rapid Communication presents a stochastic Wang tiling-based technique to compress or reconstruct disordered microstructures on the basis of given spatial statistics. Unlike the existing approaches based on a single unit cell, it utilizes a finite set of tiles assembled by a stochastic tiling algorithm, thereby allowing to accurately reproduce long-range orientation orders in a computationally efficient manner. Although the basic features of the method are demonstrated for a two-dimensional particulate suspension, the present framework is fully extensible to generic multidimensional media.

In-vivo study of blood flow in capillaries using μPIV method

NASA Astrophysics Data System (ADS)

Kurochkin, Maxim A.; Fedosov, Ivan V.; Tuchin, Valery V.

2014-01-01

A digital optical system for intravital capillaroscopy has been developed. It implements the particle image velocimetry (PIV) based approach for measurements of red blood cells velocity in individual capillary of human nailfold. We propose to use a digital real time stabilization technique for compensation of impact of involuntary movements of a finger on results of measurements. Image stabilization algorithm is based on correlation of feature tracking. The efficiency of designed image stabilization algorithm was experimentally demonstrated.

Attention has memory: priming for the size of the attentional focus.

PubMed

Fuggetta, Giorgio; Lanfranchi, Silvia; Campana, Gianluca

2009-01-01

Repeating the same target's features or spatial position, as well as repeating the same context (e.g. distractor sets) in visual search leads to a decrease of reaction times. This modulation can occur on a trial by trial basis (the previous trial primes the following one), but can also occur across multiple trials (i.e. performance in the current trial can benefit from features, position or context seen several trials earlier), and includes inhibition of different features, position or contexts besides facilitation of the same ones. Here we asked whether a similar implicit memory mechanism exists for the size of the attentional focus. By manipulating the size of the attentional focus with the repetition of search arrays with the same vs. different size, we found both facilitation for the same array size and inhibition for a different array size, as well as a progressive improvement in performance with increasing the number of repetition of search arrays with the same size. These results show that implicit memory for the size of the attentional focus can guide visual search even in the absence of feature or position priming, or distractor's contextual effects.

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

A Wideband Satcom Based Avionics Network with CDMA Uplink and TDM Downlink

NASA Technical Reports Server (NTRS)

Agrawal, D.; Johnson, B. S.; Madhow, U.; Ramchandran, K.; Chun, K. S.

2000-01-01

The purpose of this paper is to describe some key technical ideas behind our vision of a future satcom based digital communication network for avionics applications The key features of our design are as follows: (a) Packetized transmission to permit efficient use of system resources for multimedia traffic; (b) A time division multiplexed (TDM) satellite downlink whose physical layer is designed to operate the satellite link at maximum power efficiency. We show how powerful turbo codes (invented originally for linear modulation) can be used with nonlinear constant envelope modulation, thus permitting the satellite amplifier to operate in a power efficient nonlinear regime; (c) A code division multiple access (CDMA) satellite uplink, which permits efficient access to the satellite from multiple asynchronous users. Closed loop power control is difficult for bursty packetized traffic, especially given the large round trip delay to the satellite. We show how adaptive interference suppression techniques can be used to deal with the ensuing near-far problem; (d) Joint source-channel coding techniques are required both at the physical and the data transport layer to optimize the end-to-end performance. We describe a novel approach to multiple description image encoding at the data transport layer in this paper.

Radiation Hardened, Modulator ASIC for High Data Rate Communications

NASA Technical Reports Server (NTRS)

McCallister, Ron; Putnam, Robert; Andro, Monty; Fujikawa, Gene

2000-01-01

Satellite-based telecommunication services are challenged by the need to generate down-link power levels adequate to support high quality (BER approx. equals 10(exp 12)) links required for modem broadband data services. Bandwidth-efficient Nyquist signaling, using low values of excess bandwidth (alpha), can exhibit large peak-to-average-power ratio (PAPR) values. High PAPR values necessitate high-power amplifier (HPA) backoff greater than the PAPR, resulting in unacceptably low HPA efficiency. Given the high cost of on-board prime power, this inefficiency represents both an economical burden, and a constraint on the rates and quality of data services supportable from satellite platforms. Constant-envelope signals offer improved power-efficiency, but only by imposing a severe bandwidth-efficiency penalty. This paper describes a radiation- hardened modulator which can improve satellite-based broadband data services by combining the bandwidth-efficiency of low-alpha Nyquist signals with high power-efficiency (negligible HPA backoff).

Driving profile modeling and recognition based on soft computing approach.

PubMed

Wahab, Abdul; Quek, Chai; Tan, Chin Keong; Takeda, Kazuya

2009-04-01

Advancements in biometrics-based authentication have led to its increasing prominence and are being incorporated into everyday tasks. Existing vehicle security systems rely only on alarms or smart card as forms of protection. A biometric driver recognition system utilizing driving behaviors is a highly novel and personalized approach and could be incorporated into existing vehicle security system to form a multimodal identification system and offer a greater degree of multilevel protection. In this paper, detailed studies have been conducted to model individual driving behavior in order to identify features that may be efficiently and effectively used to profile each driver. Feature extraction techniques based on Gaussian mixture models (GMMs) are proposed and implemented. Features extracted from the accelerator and brake pedal pressure were then used as inputs to a fuzzy neural network (FNN) system to ascertain the identity of the driver. Two fuzzy neural networks, namely, the evolving fuzzy neural network (EFuNN) and the adaptive network-based fuzzy inference system (ANFIS), are used to demonstrate the viability of the two proposed feature extraction techniques. The performances were compared against an artificial neural network (NN) implementation using the multilayer perceptron (MLP) network and a statistical method based on the GMM. Extensive testing was conducted and the results show great potential in the use of the FNN for real-time driver identification and verification. In addition, the profiling of driver behaviors has numerous other potential applications for use by law enforcement and companies dealing with buses and truck drivers.

Efficacy of Web-Based Collection of Strength-Based Testimonials for Text Message Extension of Youth Suicide Prevention Program: Randomized Controlled Experiment.

PubMed

Thiha, Phyo; Pisani, Anthony R; Gurditta, Kunali; Cherry, Erin; Peterson, Derick R; Kautz, Henry; Wyman, Peter A

2016-11-09

Equipping members of a target population to deliver effective public health messaging to peers is an established approach in health promotion. The Sources of Strength program has demonstrated the promise of this approach for "upstream" youth suicide prevention. Text messaging is a well-established medium for promoting behavior change and is the dominant communication medium for youth. In order for peer 'opinion leader' programs like Sources of Strength to use scalable, wide-reaching media such as text messaging to spread peer-to-peer messages, they need techniques for assisting peer opinion leaders in creating effective testimonials to engage peers and match program goals. We developed a Web interface, called Stories of Personal Resilience in Managing Emotions (StoryPRIME), which helps peer opinion leaders write effective, short-form messages that can be delivered to the target population in youth suicide prevention program like Sources of Strength. To determine the efficacy of StoryPRIME, a Web-based interface for remotely eliciting high school peer leaders, and helping them produce high-quality, personal testimonials for use in a text messaging extension of an evidence-based, peer-led suicide prevention program. In a double-blind randomized controlled experiment, 36 high school students wrote testimonials with or without eliciting from the StoryPRIME interface. The interface was created in the context of Sources of Strength-an evidence-based youth suicide prevention program-and 24 ninth graders rated these testimonials on relatability, usefulness/relevance, intrigue, and likability. Testimonials written with the StoryPRIME interface were rated as more relatable, useful/relevant, intriguing, and likable than testimonials written without StoryPRIME, P=.054. StoryPRIME is a promising way to elicit high-quality, personal testimonials from youth for prevention programs that draw on members of a target population to spread public health messages. ©Phyo Thiha, Anthony R Pisani, Kunali Gurditta, Erin Cherry, Derick R Peterson, Henry Kautz, Peter A Wyman. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 09.11.2016.

Priming for new associations in animacy decision: evidence for context dependency.

PubMed

Pecher, Diane; Raaijmakers, Jeroen

2004-10-01

In four experiments we investigated the context-dependent nature of semantic memory by looking at priming effects in animacy decision for newly formed associations. The first experiment investigated whether the priming effect depended on the nature of the prior relation between the word pairs. The results showed no such effect, replicating earlier findings. Experiments 2, 3, and 4 investigated the role of context overlap between study and test. In Experiment 2 priming for new associations was found only for word pairs that had been presented in the animacy decision task during study. Experiment 3 showed that in order to obtain priming effects for new associations these associations have to be studied in a study task that is aimed at unitized processing of the word pair at a semantic level. Experiment 4 showed that processing the pairs as separate words at an orthographic level cancelled the priming effect. The results are explained by assuming that priming results from the overlap of features that are activated during both study and test.

Sounding Black or White: priming identity and biracial speech

PubMed Central

Gaither, Sarah E.; Cohen-Goldberg, Ariel M.; Gidney, Calvin L.; Maddox, Keith B.

2015-01-01

Research has shown that priming one’s racial identity can alter a biracial individuals’ social behavior, but can such priming also influence their speech? Language is often used as a marker of one’s social group membership and studies have shown that social context can affect the style of language that a person chooses to use, but this work has yet to be extended to the biracial population. Audio clips were extracted from a previous study involving biracial Black/White participants who had either their Black or White racial identity primed. Condition-blind coders rated Black-primed biracial participants as sounding significantly more Black and White-primed biracial participants as sounding significantly more White, both when listening to whole (Study 1a) and thin-sliced (Study 1b) clips. Further linguistic analyses (Studies 2a–c) were inconclusive regarding the features that differed between the two groups. Future directions regarding the need to investigate the intersections between social identity priming and language behavior with a biracial lens are discussed. PMID:25941505

Scalable graphene production from ethanol decomposition by microwave argon plasma torch

NASA Astrophysics Data System (ADS)

Melero, C.; Rincón, R.; Muñoz, J.; Zhang, G.; Sun, S.; Perez, A.; Royuela, O.; González-Gago, C.; Calzada, M. D.

2018-01-01

A fast, efficient and simple method is presented for the production of high quality graphene on a large scale by using an atmospheric pressure plasma-based technique. This technique allows to obtain high quality graphene in powder in just one step, without the use of neither metal catalysts and nor specific substrate during the process. Moreover, the cost for graphene production is significantly reduced since the ethanol used as carbon source can be obtained from the fermentation of agricultural industries. The process provides an additional benefit contributing to the revalorization of waste in the production of a high-value added product like graphene. Thus, this work demonstrates the features of plasma technology as a low cost, efficient, clean and environmentally friendly route for production of high-quality graphene.

In situ measurement of gold nanoparticle production

NASA Astrophysics Data System (ADS)

Affandi, Mohd Syafiq; Bidin, Noriah; Abdullah, Mundzir; Aziz, Muhammad Safuan Abd.; Al-Azawi, Mohammed; Nugroho, Waskito

2015-01-01

The closeness of the experimental and theoretical values enables the development of an in situ characterization technique to monitor and analyze the production of gold nanoparticles (NPs), overcoming the use of high-end and expensive instrumentation. Gold NPs below the radius size of 10 nm were successfully synthesized in accordance with a few working parameters of pulse laser ablation in a liquid technique. In this report, the size, shape, concentration, and aggregation properties of gold NPs were estimated by the Mie-Gans model based on a reliable and interactive real-time absorption spectroscopy. The major features can be an important means toward determination of efficient process measures, productivity of gold NPs generated, and efficiency of the mass ablation rate. The accuracy in the measurement is confirmed via transmission electron microscopy analysis.

Drought-Tolerance of Wheat Improved by Rhizosphere Bacteria from Harsh Environments: Enhanced Biomass Production and Reduced Emissions of Stress Volatiles

PubMed Central

Timmusk, Salme; Abd El-Daim, Islam A.; Copolovici, Lucian; Tanilas, Triin; Kännaste, Astrid; Behers, Lawrence; Nevo, Eviatar; Seisenbaeva, Gulaim; Stenström, Elna; Niinemets, Ülo

2014-01-01

Water is the key resource limiting world agricultural production. Although an impressive number of research reports have been published on plant drought tolerance enhancement via genetic modifications during the last few years, progress has been slower than expected. We suggest a feasible alternative strategy by application of rhizospheric bacteria coevolved with plant roots in harsh environments over millions of years, and harboring adaptive traits improving plant fitness under biotic and abiotic stresses. We show the effect of bacterial priming on wheat drought stress tolerance enhancement, resulting in up to 78% greater plant biomass and five-fold higher survivorship under severe drought. We monitored emissions of seven stress-related volatiles from bacterially-primed drought-stressed wheat seedlings, and demonstrated that three of these volatiles are likely promising candidates for a rapid non-invasive technique to assess crop drought stress and its mitigation in early phases of stress development. We conclude that gauging stress by elicited volatiles provides an effectual platform for rapid screening of potent bacterial strains and that priming with isolates of rhizospheric bacteria from harsh environments is a promising, novel way to improve plant water use efficiency. These new advancements importantly contribute towards solving food security issues in changing climates. PMID:24811199

Potential of minicomputer/array-processor system for nonlinear finite-element analysis

NASA Technical Reports Server (NTRS)

Strohkorb, G. A.; Noor, A. K.

1983-01-01

The potential of using a minicomputer/array-processor system for the efficient solution of large-scale, nonlinear, finite-element problems is studied. A Prime 750 is used as the host computer, and a software simulator residing on the Prime is employed to assess the performance of the Floating Point Systems AP-120B array processor. Major hardware characteristics of the system such as virtual memory and parallel and pipeline processing are reviewed, and the interplay between various hardware components is examined. Effective use of the minicomputer/array-processor system for nonlinear analysis requires the following: (1) proper selection of the computational procedure and the capability to vectorize the numerical algorithms; (2) reduction of input-output operations; and (3) overlapping host and array-processor operations. A detailed discussion is given of techniques to accomplish each of these tasks. Two benchmark problems with 1715 and 3230 degrees of freedom, respectively, are selected to measure the anticipated gain in speed obtained by using the proposed algorithms on the array processor.

An Implementation Of Elias Delta Code And ElGamal Algorithm In Image Compression And Security

NASA Astrophysics Data System (ADS)

Rachmawati, Dian; Andri Budiman, Mohammad; Saffiera, Cut Amalia

2018-01-01

In data transmission such as transferring an image, confidentiality, integrity, and efficiency of data storage aspects are highly needed. To maintain the confidentiality and integrity of data, one of the techniques used is ElGamal. The strength of this algorithm is found on the difficulty of calculating discrete logs in a large prime modulus. ElGamal belongs to the class of Asymmetric Key Algorithm and resulted in enlargement of the file size, therefore data compression is required. Elias Delta Code is one of the compression algorithms that use delta code table. The image was first compressed using Elias Delta Code Algorithm, then the result of the compression was encrypted by using ElGamal algorithm. Prime test was implemented using Agrawal Biswas Algorithm. The result showed that ElGamal method could maintain the confidentiality and integrity of data with MSE and PSNR values 0 and infinity. The Elias Delta Code method generated compression ratio and space-saving each with average values of 62.49%, and 37.51%.

Remote catalyzation for direct formation of graphene layers on oxides.

PubMed

Teng, Po-Yuan; Lu, Chun-Chieh; Akiyama-Hasegawa, Kotone; Lin, Yung-Chang; Yeh, Chao-Hui; Suenaga, Kazu; Chiu, Po-Wen

2012-03-14

Direct deposition of high-quality graphene layers on insulating substrates such as SiO(2) paves the way toward the development of graphene-based high-speed electronics. Here, we describe a novel growth technique that enables the direct deposition of graphene layers on SiO(2) with crystalline quality potentially comparable to graphene grown on Cu foils using chemical vapor deposition (CVD). Rather than using Cu foils as substrates, our approach uses them to provide subliming Cu atoms in the CVD process. The prime feature of the proposed technique is remote catalyzation using floating Cu and H atoms for the decomposition of hydrocarbons. This allows for the direct graphitization of carbon radicals on oxide surfaces, forming isolated low-defect graphene layers without the need for postgrowth etching or evaporation of the metal catalyst. The defect density of the resulting graphene layers can be significantly reduced by tuning growth parameters such as the gas ratios, Cu surface areas, and substrate-to-Cu distance. Under optimized conditions, graphene layers with nondiscernible Raman D peaks can be obtained when predeposited graphite flakes are used as seeds for extended growth. © 2012 American Chemical Society

Nanobiotechnology: soft lithography.

PubMed

Mele, Elisa; Pisignano, Dario

2009-01-01

An entirely new scientific and technological area has been born from the combination of nanotechnology and biology: nanobiotechnology. Such a field is primed especially by the strong potential synergy enabled by the integration of technologies, protocols, and investigation methods, since, while biomolecules represent functional nanosystems interesting for nanotechnology, micro- and nano-devices can be very useful instruments for studying biological materials. In particular, the research of new approaches for manipulating matter and fabricating structures with micrometre- and sub-micrometre resolution has determined the development of soft lithography, a new set of non-photolithographic patterning techniques applied to the realization of selective proteins and cells attachment, microfluidic circuits for protein and DNA chips, and 3D scaffolds for tissue engineering. Today, soft lithographies have become an asset of nanobiotechnology. This Chapter examines the biological applications of various soft lithographic techniques, with particular attention to the main general features of soft lithography and of materials commonly employed with these methods. We present approaches particularly suitable for biological materials, such as microcontact printing (muCP) and microfluidic lithography, and some key micro- and nanobiotechnology applications, such as the patterning of protein and DNA microarrays and the realization of microfluidic-based analytical devices.

A survey of mass analyzers. [characteristics and features of various instruments and techniques

NASA Technical Reports Server (NTRS)

Moore, W. W., Jr.; Tashbar, P. W.

1973-01-01

With the increasing applications of mass spectrometry technology to diverse services areas, a need has developed for a consolidated survey of the essential characteristics and features of the various instruments and techniques. This report is one approach to satisfying this need. Information has been collected and consolidated into a format which includes for each approach: (1) a general technique description, (2) instrument features information, and (3) a summary of pertinent advantages and disadvantages. With this information, the potential mass spectrometer user should be able to more efficiently select the most appropriate instrument.

Single Crystal Membranes

NASA Technical Reports Server (NTRS)

Stormont, R. W.; Morrison, A.

1974-01-01

Single crystal a- and c-axis tubes and ribbons of sodium beta-alumina and sodium magnesium beta-alumina were grown from sodium oxide rich melts. Additional experiments grew ribbon crystals containing sodium magnesium beta, beta double prime, beta triple prime, and beta quadruple prime. A high pressure crystal growth chamber, sodium oxide rich melts, and iridium for all surfaces in contact with the melt were combined with the edge-defined, film-fed growth technique to grow the single crystal beta-alumina tubes and ribbons. The crystals were characterized using metallographic and X-ray diffraction techniques, and wet chemical analysis was used to determine the sodium, magnesium, and aluminum content of the grown crystals.

Evaluation and Applications of the Prediction of Intensity Model Error (PRIME) Model

NASA Astrophysics Data System (ADS)

Bhatia, K. T.; Nolan, D. S.; Demaria, M.; Schumacher, A.

2015-12-01

Forecasters and end users of tropical cyclone (TC) intensity forecasts would greatly benefit from a reliable expectation of model error to counteract the lack of consistency in TC intensity forecast performance. As a first step towards producing error predictions to accompany each TC intensity forecast, Bhatia and Nolan (2013) studied the relationship between synoptic parameters, TC attributes, and forecast errors. In this study, we build on previous results of Bhatia and Nolan (2013) by testing the ability of the Prediction of Intensity Model Error (PRIME) model to forecast the absolute error and bias of four leading intensity models available for guidance in the Atlantic basin. PRIME forecasts are independently evaluated at each 12-hour interval from 12 to 120 hours during the 2007-2014 Atlantic hurricane seasons. The absolute error and bias predictions of PRIME are compared to their respective climatologies to determine their skill. In addition to these results, we will present the performance of the operational version of PRIME run during the 2015 hurricane season. PRIME verification results show that it can reliably anticipate situations where particular models excel, and therefore could lead to a more informed protocol for hurricane evacuations and storm preparations. These positive conclusions suggest that PRIME forecasts also have the potential to lower the error in the original intensity forecasts of each model. As a result, two techniques are proposed to develop a post-processing procedure for a multimodel ensemble based on PRIME. The first approach is to inverse-weight models using PRIME absolute error predictions (higher predicted absolute error corresponds to lower weights). The second multimodel ensemble applies PRIME bias predictions to each model's intensity forecast and the mean of the corrected models is evaluated. The forecasts of both of these experimental ensembles are compared to those of the equal-weight ICON ensemble, which currently provides the most reliable forecasts in the Atlantic basin.

An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

PubMed

Siddiqui, Muhammad Faisal; Reza, Ahmed Wasif; Kanesan, Jeevan

2015-01-01

A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the individual subjects, therefore, it can be used as a significant tool in clinical practice.

Enhancing magnetic nanoparticle-based DNA transfection: Intracellular-active cassette features

NASA Astrophysics Data System (ADS)

Vernon, Matthew Martin

Efficient plasmid DNA transfection of embryonic stem cells, mesenchymal stem cells, neural cell lines and the majority of primary cell lines is a current challenge in gene therapy research. Magnetic nanoparticle-based DNA transfection is a gene vectoring technique that is promising because it is capable of outperforming most other non-viral transfection methods in terms of both transfection efficiency and cell viability. The nature of the DNA vector implemented depends on the target cell phenotype, where the particle surface chemistry and DNA binding/unbinding kinetics of the DNA carrier molecule play a critical role in the many steps required for successful gene transfection. Accordingly, Neuromag, an iron oxide/polymer nanoparticle optimized for transfection of neural phenotypes, outperforms many other nanoparticles and lipidbased DNA carriers. Up to now, improvements to nanomagnetic transfection techniques have focused mostly on particle functionalization and transfection parameter optimization (cell confluence, growth media, serum starvation, magnet oscillation parameters, etc.). None of these parameters are capable of assisting the nuclear translocation of delivered plasmid DNA once the particle-DNA complex is released from the endosome and dissociates in the cell's cytoplasm. In this study, incorporation of a DNA targeting sequence (DTS) feature in the transfecting plasmid DNA confers improved nuclear translocation, demonstrating significant improvement in nanomagnetic transfection efficiency in differentiated SH-SY5Y neuroblastoma cells. Other parameters, such as days in vitro, are also found to play a role and represent potential targets for further optimization.

Skin image retrieval using Gabor wavelet texture feature.

PubMed

Ou, X; Pan, W; Zhang, X; Xiao, P

2016-12-01

Skin imaging plays a key role in many clinical studies. We have used many skin imaging techniques, including the recently developed capacitive contact skin imaging based on fingerprint sensors. The aim of this study was to develop an effective skin image retrieval technique using Gabor wavelet transform, which can be used on different types of skin images, but with a special focus on skin capacitive contact images. Content-based image retrieval (CBIR) is a useful technology to retrieve stored images from database by supplying query images. In a typical CBIR, images are retrieved based on colour, shape, texture, etc. In this study, texture feature is used for retrieving skin images, and Gabor wavelet transform is used for texture feature description and extraction. The results show that the Gabor wavelet texture features can work efficiently on different types of skin images. Although Gabor wavelet transform is slower compared with other image retrieval techniques, such as principal component analysis (PCA) and grey-level co-occurrence matrix (GLCM), Gabor wavelet transform is the best for retrieving skin capacitive contact images and facial images with different orientations. Gabor wavelet transform can also work well on facial images with different expressions and skin cancer/disease images. We have developed an effective skin image retrieval method based on Gabor wavelet transform, that it is useful for retrieving different types of images, namely digital colour face images, digital colour skin cancer and skin disease images, and particularly greyscale skin capacitive contact images. Gabor wavelet transform can also be potentially useful for face recognition (with different orientation and expressions) and skin cancer/disease diagnosis. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Case Assignment in Typically Developing English-Speaking Children: A Paired Priming Study

ERIC Educational Resources Information Center

Wisman Weil, Lisa Marie

2013-01-01

This study utilized a paired priming paradigm to examine the influence of input features on case assignment in typically developing English-speaking children. The Input Ambiguity Hypothesis (Pelham, 2011) was experimentally tested to help explain why children produce subject pronoun case errors. Analyses of third singular "-s" marking on…

The Detection and Primed Production of Novel Constructions

ERIC Educational Resources Information Center

McDonough, Kim; Fulga, Angelica

2015-01-01

Situated within second language (L2) research about the acquisition of morphosyntax, this study investigated English L2 speakers' detection and primed production of a novel construction with morphological and structural features. We report on two experiments with Thai (n = 69) and Farsi (n = 70) English L2 speakers, respectively, carried out an…

The Role of Task Repetition in Learning Word-Stress Patterns through Auditory Priming Tasks

ERIC Educational Resources Information Center

Jung, YeonJoo; Kim, YouJin; Murphy, John

2017-01-01

This study focused on an instructional component often neglected when teaching the pronunciation of English as either a second, foreign, or international language--namely, the suprasegmental feature of lexical stress. Extending previous research on collaborative priming tasks and task repetition, the study investigated the impact of task and…

Prime-Time Television: Assessing Violence during the Most Popular Viewing Hours.

ERIC Educational Resources Information Center

Smith, Stacy L.; Nathanson, Amy I.; Wilson, Barbara J.

2002-01-01

Assesses the prevalence and context of violence in prime-time television programming using a random, representative sample. Shows that, regardless of the time of day, viewers are likely to encounter violence in roughly 2 out of 3 programs. Identifies specific channel types and genres that feature potentially harmful depictions of violence during…

Priming Contour-Deleted Images: Evidence for Immediate Representations in Visual Object Recognition.

ERIC Educational Resources Information Center

Biederman, Irving; Cooper, Eric E.

1991-01-01

Speed and accuracy of identification of pictures of objects are facilitated by prior viewing. Contributions of image features, convex or concave components, and object models in a repetition priming task were explored in 2 studies involving 96 college students. Results provide evidence of intermediate representations in visual object recognition.…

Visual consciousness and intertrial feature priming.

PubMed

Peremen, Ziv; Hilo, Rinat; Lamy, Dominique

2013-04-01

Intertrial repetition priming plays a striking role in visual search. For instance, when searching for a target with a unique color, performance is substantially better when the specific color of the target repeats on successive trials (Maljkovic & Nakayama, 1994). Recent research has relied on objective measures of performance to show that priming improves the perceptual quality of the repeated target. Here, we examined the relation between priming and conscious perception of the target by adding a subjective measure of perception. We used backward masking to create liminal perception, that is, different levels of subjectively conscious perception of the target using exactly the same stimulus conditions. The displays in either probe trials (in which priming benefits are measured, experiment 1) or in prime trials (in which memory traces are laid down, experiment 2) were masked. The results showed that intertrial priming improves full access to awareness of the repeated target but only for targets that already achieved partial access to awareness. In addition, they show that full awareness of the target is necessary in both the prime and probe trials for intertrial priming effects to emerge. Implications for the role of implicit short-term memory in visual search are discussed.

Thermopriming triggers splicing memory in Arabidopsis.

PubMed

Ling, Yu; Serrano, Natalia; Gao, Ge; Atia, Mohamed; Mokhtar, Morad; Woo, Yong H; Bazin, Jeremie; Veluchamy, Alaguraj; Benhamed, Moussa; Crespi, Martin; Gehring, Christoph; Reddy, A S N; Mahfouz, Magdy M

2018-04-27

Abiotic and biotic stresses limit crop productivity. Exposure to a non-lethal stress, referred to as priming, can allow plants to survive subsequent and otherwise lethal conditions; the priming effect persists even after a prolonged stress-free period. However, the molecular mechanisms underlying priming are not fully understood. Here, we investigated the molecular basis of heat-shock memory and the role of priming in Arabidopsis thaliana. Comprehensive analysis of transcriptome-wide changes in gene expression and alternative splicing in primed and non-primed plants revealed that alternative splicing functions as a novel component of heat-shock memory. We show that priming of plants with a non-lethal heat stress results in de-repression of splicing after a second exposure to heat stress. By contrast, non-primed plants showed significant repression of splicing. These observations link 'splicing memory' to the ability of plants to survive subsequent and otherwise lethal heat stress. This newly discovered priming-induced splicing memory may represent a general feature of heat-stress responses in plants and other organisms as many of the key components are conserved among eukaryotes. Furthermore, this finding could facilitate the development of novel approaches to improve plant survival under extreme heat stress.

Feature-based Approach in Product Design with Energy Efficiency Consideration

NASA Astrophysics Data System (ADS)

Li, D. D.; Zhang, Y. J.

2017-10-01

In this paper, a method to measure the energy efficiency and ecological footprint metrics of features is proposed for product design. First the energy consumption models of various manufacturing features, like cutting feature, welding feature, etc. are studied. Then, the total energy consumption of a product is modeled and estimated according to its features. Finally, feature chains that combined by several sequence features based on the producing operation orders are defined and analyzed to calculate global optimal solution. The corresponding assessment model is also proposed to estimate their energy efficiency and ecological footprint. Finally, an example is given to validate the proposed approach in the improvement of sustainability.

Segmentation of remotely sensed data using parallel region growing

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Cox, S. C.

1983-01-01

The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.

A New Superalloy Enabling Heavy Duty Gas Turbine Wheels for Improved Combined Cycle Efficiency

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

Detor, Andrew; DiDomizio, Richard; McAllister, Don

The drive to increase combined cycle turbine efficiency from 62% to 65% for the next-generation advanced cycle requires a new heavy duty gas turbine wheel material capable of operating at 1200°F and above. Current wheel materials are limited by the stability of their major strengthening phase (gamma double prime), which coarsens at temperatures approaching 1200°F, resulting in a substantial reduction in strength. More advanced gamma prime superalloys, such as those used in jet engine turbine disks, are also not suitable due to size constraints; the gamma prime phase overages during the slow cooling rates inherent in processing thick-section turbine wheels.more » The current program addresses this need by screening two new alloy design concepts. The first concept exploits a gamma prime/gamma double prime coprecipitation reaction. Through manipulation of alloy chemistry, coprecipitation is controlled such that gamma double prime is used only to slow the growth of gamma prime during slow cooling, preventing over-aging, and allowing for subsequent heat treatment to maximize strength. In parallel, phase field modeling provides fundamental understanding of the coprecipitation reaction. The second concept uses oxide dispersion strengthening to improve on two existing alloys that exhibit excellent hold time fatigue crack growth resistance, but have insufficient strength to be considered for gas turbine wheels. Mechanical milling forces the dissolution of starting oxide powders into a metal matrix allowing for solid state precipitation of new, nanometer scale oxides that are effective at dispersion strengthening.« less

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Analysis of the Source Physics Experiment SPE4 Prime Using State-Of Parallel Numerical Tools.

NASA Astrophysics Data System (ADS)

Vorobiev, O.; Ezzedine, S. M.; Antoun, T.; Glenn, L.

2015-12-01

This work describes a methodology used for large scale modeling of wave propagation from underground chemical explosions conducted at the Nevada National Security Site (NNSS) fractured granitic rock. We show that the discrete natures of rock masses as well as the spatial variability of the fabric of rock properties are very important to understand ground motions induced by underground explosions. In order to build a credible conceptual model of the subsurface we integrated the geological, geomechanical and geophysical characterizations conducted during recent test at the NNSS as well as historical data from the characterization during the underground nuclear test conducted at the NNSS. Because detailed site characterization is limited, expensive and, in some instances, impossible we have numerically investigated the effects of the characterization gaps on the overall response of the system. We performed several computational studies to identify the key important geologic features specific to fractured media mainly the joints characterized at the NNSS. We have also explored common key features to both geological environments such as saturation and topography and assess which characteristics affect the most the ground motion in the near-field and in the far-field. Stochastic representation of these features based on the field characterizations has been implemented into LLNL's Geodyn-L hydrocode. Simulations were used to guide site characterization efforts in order to provide the essential data to the modeling community. We validate our computational results by comparing the measured and computed ground motion at various ranges for the recently executed SPE4 prime experiment. We have also conducted a comparative study between SPE4 prime and previous experiments SPE1 and SPE3 to assess similarities and differences and draw conclusions on designing SPE5.

Coding Local and Global Binary Visual Features Extracted From Video Sequences.

PubMed

Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2015-11-01

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the bag-of-visual word model. Several applications, including, for example, visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget while attaining a target level of efficiency. In this paper, we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can conveniently be adopted to support the analyze-then-compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs the visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the compress-then-analyze (CTA) paradigm. In this paper, we experimentally compare the ATC and the CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: 1) homography estimation and 2) content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with the CTA, especially in bandwidth limited scenarios.

Coding Local and Global Binary Visual Features Extracted From Video Sequences

NASA Astrophysics Data System (ADS)

Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2015-11-01

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks, while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the Bag-of-Visual-Word (BoVW) model. Several applications, including for example visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget, while attaining a target level of efficiency. In this paper we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can be conveniently adopted to support the Analyze-Then-Compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the Compress-Then-Analyze (CTA) paradigm. In this paper we experimentally compare ATC and CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: homography estimation and content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with CTA, especially in bandwidth limited scenarios.

Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA

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

Thimmisetty, Charanraj A.; Zhao, Wenju; Chen, Xiao

2017-10-18

Performing stochastic inversion on a computationally expensive forward simulation model with a high-dimensional uncertain parameter space (e.g. a spatial random field) is computationally prohibitive even when gradient information can be computed efficiently. Moreover, the ‘nonlinear’ mapping from parameters to observables generally gives rise to non-Gaussian posteriors even with Gaussian priors, thus hampering the use of efficient inversion algorithms designed for models with Gaussian assumptions. In this paper, we propose a novel Bayesian stochastic inversion methodology, which is characterized by a tight coupling between the gradient-based Langevin Markov Chain Monte Carlo (LMCMC) method and a kernel principal component analysis (KPCA). Thismore » approach addresses the ‘curse-of-dimensionality’ via KPCA to identify a low-dimensional feature space within the high-dimensional and nonlinearly correlated parameter space. In addition, non-Gaussian posterior distributions are estimated via an efficient LMCMC method on the projected low-dimensional feature space. We will demonstrate this computational framework by integrating and adapting our recent data-driven statistics-on-manifolds constructions and reduction-through-projection techniques to a linear elasticity model.« less

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours

NASA Astrophysics Data System (ADS)

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-01

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours.

PubMed

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-07

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

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

Liu, C.; Kewisch, J.; Huang, H.

At RHIC, the spin polarization is preserved with a pair of Siberian snakes on the oppo- site sides in each ring. The polarized proton beam with finite spin tune spread might cross spin resonances multiple times in two cases, one is when beam going through strong spin intrinsic resonances during acceleration, the other is when sweeping spin flipper’ frequency across the spin tune to flip the direction of spin polarization. The consequence is loss of spin polarization in both cases. Therefore, a scheme of min- imizing the spin tune spread by matching the dispersion primes at the two snakes wasmore » introduced based on the fact that the spin tune spread is proportional to the difference of dispersion primes at the two snakes. The scheme was implemented at fixed energies for the spin flipper study and during beam acceleration for better spin polarization transmission efficiency. The effect of minimizing the spin tune spread by matching the dispersion primes was observed and confirmed experimentally. The principle of minimizing the spin tune spread by matching the dispersion primes, the impact on the beam optics, and the effect of a narrower spin tune spread are presented in this report.« less

Stratified Diffractive Optic Approach for Creating High Efficiency Gratings

NASA Technical Reports Server (NTRS)

Chambers, Diana M.; Nordin, Gregory P.

1998-01-01

Gratings with high efficiency in a single diffracted order can be realized with both volume holographic and diffractive optical elements. However, each method has limitations that restrict the applications in which they can be used. For example, high efficiency volume holographic gratings require an appropriate combination of thickness and permittivity modulation throughout the bulk of the material. Possible combinations of those two characteristics are limited by properties of currently available materials, thus restricting the range of applications for volume holographic gratings. Efficiency of a diffractive optic grating is dependent on its approximation of an ideal analog profile using discrete features. The size of constituent features and, consequently, the number that can be used within a required grating period restricts the applications in which diffractive optic gratings can be used. These limitations imply that there are applications which cannot be addressed by either technology. In this paper we propose to address a number of applications in this category with a new method of creating high efficiency gratings which we call stratified diffractive optic gratings. In this approach diffractive optic techniques are used to create an optical structure that emulates volume grating behavior. To illustrate the stratified diffractive optic grating concept we consider a specific application, a scanner for a space-based coherent wind lidar, with requirements that would be difficult to meet by either volume holographic or diffractive optic methods. The lidar instrument design specifies a transmissive scanner element with the input beam normally incident and the exiting beam deflected at a fixed angle from the optical axis. The element will be rotated about the optical axis to produce a conical scan pattern. The wavelength of the incident beam is 2.06 microns and the required deflection angle is 30 degrees, implying a grating period of approximately 4 microns. Creating a high efficiency volume grating with these parameters would require a grating thickness that cannot be attained with current photosensitive materials. For a diffractive optic grating, the number of binary steps necessary to produce high efficiency combined with the grating period requires feature sizes and alignment tolerances that are also unattainable with current techniques. Rotation of the grating and integration into a space-based lidar system impose the additional requirements that it be insensitive to polarization orientation, that its mass be minimized and that it be able to withstand launch and space environments.

Integrating Dimension Reduction and Out-of-Sample Extension in Automated Classification of Ex Vivo Human Patellar Cartilage on Phase Contrast X-Ray Computed Tomography

PubMed Central

Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Diemoz, Paul C.; Wismüller, Axel

2015-01-01

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns. PMID:25710875

Constriction of the mitochondrial inner compartment is a priming event for mitochondrial division

PubMed Central

Cho, Bongki; Cho, Hyo Min; Jo, Youhwa; Kim, Hee Dae; Song, Myungjae; Moon, Cheil; Kim, Hyongbum; Kim, Kyungjin; Sesaki, Hiromi; Rhyu, Im Joo; Kim, Hyun; Sun, Woong

2017-01-01

Mitochondrial division is critical for the maintenance and regulation of mitochondrial function, quality and distribution. This process is controlled by cytosolic actin-based constriction machinery and dynamin-related protein 1 (Drp1) on mitochondrial outer membrane (OMM). Although mitochondrial physiology, including oxidative phosphorylation, is also important for efficient mitochondrial division, morphological alterations of the mitochondrial inner-membrane (IMM) have not been clearly elucidated. Here we report spontaneous and repetitive constriction of mitochondrial inner compartment (CoMIC) associated with subsequent division in neurons. Although CoMIC is potentiated by inhibition of Drp1 and occurs at the potential division spots contacting the endoplasmic reticulum, it appears on IMM independently of OMM. Intra-mitochondrial influx of Ca2+ induces and potentiates CoMIC, and leads to K+-mediated mitochondrial bulging and depolarization. Synergistically, optic atrophy 1 (Opa1) also regulates CoMIC via controlling Mic60-mediated OMM–IMM tethering. Therefore, we propose that CoMIC is a priming event for efficient mitochondrial division. PMID:28598422

A hierarchical fuzzy rule-based approach to aphasia diagnosis.

PubMed

Akbarzadeh-T, Mohammad-R; Moshtagh-Khorasani, Majid

2007-10-01

Aphasia diagnosis is a particularly challenging medical diagnostic task due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. To efficiently address this diagnostic process, a hierarchical fuzzy rule-based structure is proposed here that considers the effect of different features of aphasia by statistical analysis in its construction. This approach can be efficient for diagnosis of aphasia and possibly other medical diagnostic applications due to its fuzzy and hierarchical reasoning construction. Initially, the symptoms of the disease which each consists of different features are analyzed statistically. The measured statistical parameters from the training set are then used to define membership functions and the fuzzy rules. The resulting two-layered fuzzy rule-based system is then compared with a back propagating feed-forward neural network for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. In order to reduce the number of required inputs, the technique is applied and compared on both comprehensive and spontaneous speech tests. Statistical t-test analysis confirms that the proposed approach uses fewer Aphasia features while also presenting a significant improvement in terms of accuracy.

Ballistics projectile image analysis for firearm identification.

PubMed

Li, Dongguang

2006-10-01

This paper is based upon the observation that, when a bullet is fired, it creates characteristic markings on the cartridge case and projectile. From these markings, over 30 different features can be distinguished, which, in combination, produce a "fingerprint" for a firearm. By analyzing features within such a set of firearm fingerprints, it will be possible to identify not only the type and model of a firearm, but also each and every individual weapon just as effectively as human fingerprint identification. A new analytic system based on the fast Fourier transform for identifying projectile specimens by the line-scan imaging technique is proposed in this paper. This paper develops optical, photonic, and mechanical techniques to map the topography of the surfaces of forensic projectiles for the purpose of identification. Experiments discussed in this paper are performed on images acquired from 16 various weapons. Experimental results show that the proposed system can be used for firearm identification efficiently and precisely through digitizing and analyzing the fired projectiles specimens.

A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection.

PubMed

Iliyasu, Abdullah M; Fatichah, Chastine

2017-12-19

A quantum hybrid (QH) intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO) method with the intuitionistic rationality of traditional fuzzy k -nearest neighbours (Fuzzy k -NN) algorithm (known simply as the Q-Fuzzy approach) is proposed for efficient feature selection and classification of cells in cervical smeared (CS) images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles) that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection) and another hybrid technique combining the standard PSO algorithm with the Fuzzy k -NN technique (P-Fuzzy approach). In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k -NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

Integrating environmental gap analysis with spatial conservation prioritization: a case study from Victoria, Australia.

PubMed

Sharafi, Seyedeh Mahdieh; Moilanen, Atte; White, Matt; Burgman, Mark

2012-12-15

Gap analysis is used to analyse reserve networks and their coverage of biodiversity, thus identifying gaps in biodiversity representation that may be filled by additional conservation measures. Gap analysis has been used to identify priorities for species and habitat types. When it is applied to identify gaps in the coverage of environmental variables, it embodies the assumption that combinations of environmental variables are effective surrogates for biodiversity attributes. The question remains of how to fill gaps in conservation systems efficiently. Conservation prioritization software can identify those areas outside existing conservation areas that contribute to the efficient covering of gaps in biodiversity features. We show how environmental gap analysis can be implemented using high-resolution information about environmental variables and ecosystem condition with the publicly available conservation prioritization software, Zonation. Our method is based on the conversion of combinations of environmental variables into biodiversity features. We also replicated the analysis by using Species Distribution Models (SDMs) as biodiversity features to evaluate the robustness and utility of our environment-based analysis. We apply the technique to a planning case study of the state of Victoria, Australia. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dynamic detection-rate-based bit allocation with genuine interval concealment for binary biometric representation.

PubMed

Lim, Meng-Hui; Teoh, Andrew Beng Jin; Toh, Kar-Ann

2013-06-01

Biometric discretization is a key component in biometric cryptographic key generation. It converts an extracted biometric feature vector into a binary string via typical steps such as segmentation of each feature element into a number of labeled intervals, mapping of each interval-captured feature element onto a binary space, and concatenation of the resulted binary output of all feature elements into a binary string. Currently, the detection rate optimized bit allocation (DROBA) scheme is one of the most effective biometric discretization schemes in terms of its capability to assign binary bits dynamically to user-specific features with respect to their discriminability. However, we learn that DROBA suffers from potential discriminative feature misdetection and underdiscretization in its bit allocation process. This paper highlights such drawbacks and improves upon DROBA based on a novel two-stage algorithm: 1) a dynamic search method to efficiently recapture such misdetected features and to optimize the bit allocation of underdiscretized features and 2) a genuine interval concealment technique to alleviate crucial information leakage resulted from the dynamic search. Improvements in classification accuracy on two popular face data sets vindicate the feasibility of our approach compared with DROBA.

An improved wrapper-based feature selection method for machinery fault diagnosis

PubMed Central

2017-01-01

A major issue of machinery fault diagnosis using vibration signals is that it is over-reliant on personnel knowledge and experience in interpreting the signal. Thus, machine learning has been adapted for machinery fault diagnosis. The quantity and quality of the input features, however, influence the fault classification performance. Feature selection plays a vital role in selecting the most representative feature subset for the machine learning algorithm. In contrast, the trade-off relationship between capability when selecting the best feature subset and computational effort is inevitable in the wrapper-based feature selection (WFS) method. This paper proposes an improved WFS technique before integration with a support vector machine (SVM) model classifier as a complete fault diagnosis system for a rolling element bearing case study. The bearing vibration dataset made available by the Case Western Reserve University Bearing Data Centre was executed using the proposed WFS and its performance has been analysed and discussed. The results reveal that the proposed WFS secures the best feature subset with a lower computational effort by eliminating the redundancy of re-evaluation. The proposed WFS has therefore been found to be capable and efficient to carry out feature selection tasks. PMID:29261689

Event generators for {{\\eta }}/{{{\\eta }}}^{^{\\prime} } decays at BESIII

NASA Astrophysics Data System (ADS)

Qin, Nian; Zhang, Zhen-Yu; Fang, Shuang-Shi; Zhou, Xiang; Du, Lin-Lin; Qiao, Hao-Xue

2018-01-01

The light unflavoured meson {{η }}/{{{η }}}^{\\prime } decays are valuable for testing non-perturbative quantum chromodynamics and exploring new physics beyond the Standard Model. This paper describes a series of event generators, including {{η }}/{{{η }}}^{\\prime }\\to {{γ }}{{{l}}}+{{{l}}}-, {{η }}/{{{η }}}^{\\prime }\\to {{γ }}{{{π }}}+{{{π }}}-, {{{η }}}^{\\prime }\\to {{ω }}{{{e}}}+{{{e}}}-, {{η }}\\to {{{π }}}+{{{π }}}-{{{π }}}0, {{η }}/{{{η }}}^{\\prime }\\to {{{π }}}0{{{π }}}0{{{π }}}0, {{{η }}}^{\\prime }\\to {{η }}{{π }}{{π }} and {{{η }}}^{\\prime }\\to {{{π }}}+{{{π }}}-{{{π }}}+{{{π }}}-/{{{π }}}+{{{π }}}-{{{π }}}0{{{π }}}0, which have been developed for investigating {{η }}/{{{η }}}^{\\prime } decay dynamics. For most of these generators, their usability has been validated in BESIII analyses for determining the detection efficiency, and background studies. The consistency between data and Monte Carlo shows that these generators work well in the BESIII simulation, and will also be useful for ongoing BESIII analyses and other experiments for studying {{η }}/{{{η }}}^{\\prime } physics. Supported by National Natural Science Foundation of China (NSFC) (11205117, 11575133, 11675184), the China Scholarship Council (201506275156), the Wuhan University PhD Short-time Mobility Program 2016, the Joint Funds of the NSFC and Henan Province (U1504112)

Subliminal Priming-State of the Art and Future Perspectives.

PubMed

Elgendi, Mohamed; Kumar, Parmod; Barbic, Skye; Howard, Newton; Abbott, Derek; Cichocki, Andrzej

2018-05-30

The influence of subliminal priming (behavior outside of awareness) in humans is an interesting phenomenon and its understanding is crucial as it can impact behavior, choices, and actions. Given this, research about the impact of priming continues to be an area of investigative interest, and this paper provides a technical overview of research design strengths and issues in subliminal priming research. Efficient experiments and protocols, as well as associated electroencephalographic and eye movement data analyses, are discussed in detail. We highlight the strengths and weaknesses of different priming experiments that have measured affective (emotional) and cognitive responses. Finally, very recent approaches and findings are described to summarize and emphasize state-of-the-art methods and potential future directions in research marketing and other commercial applications.

[A study of culture-based easy identification system for Malassezia].

PubMed

Kaneko, Takamasa

2011-01-01

Most species of this genus are lipid-dependent yeasts, which colonize the seborrheic part of the skin, and they have been reported to be associated with pityriasis versicolor, Malassezia folliculitis, seborrheic dermatitis, and atopic dermatitis. Malassezia have been re-classified into 7 species based on molecular biological analysis of nuclear ribosomal DNA/RNA and new Malassezia species were reported. As members of the genus Malassezia share similar morphological and biochemical characteristics, it was thought to be difficult to differentiate between them based on phenotypic features. While molecular biological techniques are the most reliable methods for identification of Malassezia, they are not available in most clinical laboratories. We studied ( i ) development of an efficient isolation media and culture based easy identification system, ( ii ) the incidence of atypical biochemical features in Malassezia species and propose a culture-based easy identification system for clinically important Malassezia species, M. globosa, M. restricta, and M. furfur.

An iris recognition algorithm based on DCT and GLCM

NASA Astrophysics Data System (ADS)

Feng, G.; Wu, Ye-qing

2008-04-01

With the enlargement of mankind's activity range, the significance for person's status identity is becoming more and more important. So many different techniques for person's status identity were proposed for this practical usage. Conventional person's status identity methods like password and identification card are not always reliable. A wide variety of biometrics has been developed for this challenge. Among those biologic characteristics, iris pattern gains increasing attention for its stability, reliability, uniqueness, noninvasiveness and difficult to counterfeit. The distinct merits of the iris lead to its high reliability for personal identification. So the iris identification technique had become hot research point in the past several years. This paper presents an efficient algorithm for iris recognition using gray-level co-occurrence matrix(GLCM) and Discrete Cosine transform(DCT). To obtain more representative iris features, features from space and DCT transformation domain are extracted. Both GLCM and DCT are applied on the iris image to form the feature sequence in this paper. The combination of GLCM and DCT makes the iris feature more distinct. Upon GLCM and DCT the eigenvector of iris extracted, which reflects features of spatial transformation and frequency transformation. Experimental results show that the algorithm is effective and feasible with iris recognition.

Case Assignment in English-Speaking Children: A Paired Priming Paradigm

ERIC Educational Resources Information Center

Weil, Lisa Wisman; Leonard, Laurence B.

2017-01-01

This study employed a paired priming paradigm to ask whether input features influence a child's propensity to use non-nominative versus nominative case in subject position, and to use non-nominative forms even when verbs are marked for agreement. Thirty English-speaking children (ages 2;6 to 3;7) heard sentences with pronouns that had…

The technique of entropy optimization in motor current signature analysis and its application in the fault diagnosis of gear transmission

NASA Astrophysics Data System (ADS)

Chen, Xiaoguang; Liang, Lin; Liu, Fei; Xu, Guanghua; Luo, Ailing; Zhang, Sicong

2012-05-01

Nowadays, Motor Current Signature Analysis (MCSA) is widely used in the fault diagnosis and condition monitoring of machine tools. However, although the current signal has lower SNR (Signal Noise Ratio), it is difficult to identify the feature frequencies of machine tools from complex current spectrum that the feature frequencies are often dense and overlapping by traditional signal processing method such as FFT transformation. With the study in the Motor Current Signature Analysis (MCSA), it is found that the entropy is of importance for frequency identification, which is associated with the probability distribution of any random variable. Therefore, it plays an important role in the signal processing. In order to solve the problem that the feature frequencies are difficult to be identified, an entropy optimization technique based on motor current signal is presented in this paper for extracting the typical feature frequencies of machine tools which can effectively suppress the disturbances. Some simulated current signals were made by MATLAB, and a current signal was obtained from a complex gearbox of an iron works made in Luxembourg. In diagnosis the MCSA is combined with entropy optimization. Both simulated and experimental results show that this technique is efficient, accurate and reliable enough to extract the feature frequencies of current signal, which provides a new strategy for the fault diagnosis and the condition monitoring of machine tools.

Towards human behavior recognition based on spatio temporal features and support vector machines

NASA Astrophysics Data System (ADS)

Ghabri, Sawsen; Ouarda, Wael; Alimi, Adel M.

2017-03-01

Security and surveillance are vital issues in today's world. The recent acts of terrorism have highlighted the urgent need for efficient surveillance. There is indeed a need for an automated system for video surveillance which can detect identity and activity of person. In this article, we propose a new paradigm to recognize an aggressive human behavior such as boxing action. Our proposed system for human activity detection includes the use of a fusion between Spatio Temporal Interest Point (STIP) and Histogram of Oriented Gradient (HoG) features. The novel feature called Spatio Temporal Histogram Oriented Gradient (STHOG). To evaluate the robustness of our proposed paradigm with a local application of HoG technique on STIP points, we made experiments on KTH human action dataset based on Multi Class Support Vector Machines classification. The proposed scheme outperforms basic descriptors like HoG and STIP to achieve 82.26% us an accuracy value of classification rate.

Feature Selection and Parameters Optimization of SVM Using Particle Swarm Optimization for Fault Classification in Power Distribution Systems.

PubMed

Cho, Ming-Yuan; Hoang, Thi Thom

2017-01-01

Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO) based support vector machine (SVM) classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR) method with a pseudorandom binary sequence (PRBS) stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.

Impairments in multisensory processing are not universal to the autism spectrum: no evidence for crossmodal priming deficits in Asperger syndrome.

PubMed

David, Nicole; R Schneider, Till; Vogeley, Kai; Engel, Andreas K

2011-10-01

Individuals suffering from autism spectrum disorders (ASD) often show a tendency for detail- or feature-based perception (also referred to as "local processing bias") instead of more holistic stimulus processing typical for unaffected people. This local processing bias has been demonstrated for the visual and auditory domains and there is evidence that multisensory processing may also be affected in ASD. Most multisensory processing paradigms used social-communicative stimuli, such as human speech or faces, probing the processing of simultaneously occuring sensory signals. Multisensory processing, however, is not limited to simultaneous stimulation. In this study, we investigated whether multisensory processing deficits in ASD persist when semantically complex but nonsocial stimuli are presented in succession. Fifteen adult individuals with Asperger syndrome and 15 control persons participated in a visual-audio priming task, which required the classification of sounds that were either primed by semantically congruent or incongruent preceding pictures of objects. As expected, performance on congruent trials was faster and more accurate compared with incongruent trials (crossmodal priming effect). The Asperger group, however, did not differ significantly from the control group. Our results do not support a general multisensory processing deficit, which is universal to the entire autism spectrum. Copyright © 2011, International Society for Autism Research, Wiley-Liss, Inc.

PPO-ethanol system as wavelength shifter for the Cherenkov counting technique using a liquid scintillation counter

NASA Astrophysics Data System (ADS)

Takiue, Makoto; Fujii, Haruo; Ishikawa, Hiroaki

1984-12-01

2, 5-diphenyloxazole (PPO) has been proposed as a wavelength shifter for Cherenkov counting. Since PPO is not incorporated with water, we have introduced the fluor into water in the form of micelle using a PPO-ethanol system. This technique makes it possible to obtain a high Cherenkov counting efficiency under stable sample conditions, attributed to the proper spectrometric features of the PPO. The 32P Cherenkov counting efficiency (68.4%) obtained from this technique is large as that measured with a conventional Cherenkov technique.

Engineering and testing of prime focus fiber feeds on the William Herschel Telescope

NASA Astrophysics Data System (ADS)

Worswick, Susan P.; Gellatly, David W.; Ferneyhough, Nicholas K.; Terry, Percy; Weise, Andrew J.; Bingham, Richard G.; Jenkins, Charles R.; Watson, Frederick G.

1994-06-01

The prime focus of the William Herschel telescope provides a wide field (one degree) for fiber spectroscopy. The production of the fiber feeds, which run from the prime focus to one of the Nasymyth platforms, has required the development of a multiple fiber to fiber connector together with techniques for mounting micro-lenses at the input to the spectrography. The protection of the fibers on the telescope, coupled with careful routing, has led to good focal ratio degradation (FRD) performance. A system for measuring the variation in transmission of the fibers on the telescope has been produced; the technique allows these measurements to be made under normal daytime lighting conditions.

User-assisted video segmentation system for visual communication

NASA Astrophysics Data System (ADS)

Wu, Zhengping; Chen, Chun

2002-01-01

Video segmentation plays an important role for efficient storage and transmission in visual communication. In this paper, we introduce a novel video segmentation system using point tracking and contour formation techniques. Inspired by the results from the study of the human visual system, we intend to solve the video segmentation problem into three separate phases: user-assisted feature points selection, feature points' automatic tracking, and contour formation. This splitting relieves the computer of ill-posed automatic segmentation problems, and allows a higher level of flexibility of the method. First, the precise feature points can be found using a combination of user assistance and an eigenvalue-based adjustment. Second, the feature points in the remaining frames are obtained using motion estimation and point refinement. At last, contour formation is used to extract the object, and plus a point insertion process to provide the feature points for next frame's tracking.

Content-Based Image Retrieval System for Pulmonary Nodules: Assisting Radiologists in Self-Learning and Diagnosis of Lung Cancer.

PubMed

Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Dutta, Anirvan; Garg, Mandeep; Khandelwal, Niranjan

2017-02-01

Visual information of similar nodules could assist the budding radiologists in self-learning. This paper presents a content-based image retrieval (CBIR) system for pulmonary nodules, observed in lung CT images. The reported CBIR systems of pulmonary nodules cannot be put into practice as radiologists need to draw the boundary of nodules during query formation and feature database creation. In the proposed retrieval system, the pulmonary nodules are segmented using a semi-automated technique, which requires a seed point on the nodule from the end-user. The involvement of radiologists in feature database creation is also reduced, as only a seed point is expected from radiologists instead of manual delineation of the boundary of the nodules. The performance of the retrieval system depends on the accuracy of the segmentation technique. Several 3D features are explored to improve the performance of the proposed retrieval system. A set of relevant shape and texture features are considered for efficient representation of the nodules in the feature space. The proposed CBIR system is evaluated for three configurations such as configuration-1 (composite rank of malignancy "1","2" as benign and "4","5" as malignant), configuration-2 (composite rank of malignancy "1","2", "3" as benign and "4","5" as malignant), and configuration-3 (composite rank of malignancy "1","2" as benign and "3","4","5" as malignant). Considering top 5 retrieved nodules and Euclidean distance metric, the precision achieved by the proposed method for configuration-1, configuration-2, and configuration-3 are 82.14, 75.91, and 74.27 %, respectively. The performance of the proposed CBIR system is close to the most recent technique, which is dependent on radiologists for manual segmentation of nodules. A computer-aided diagnosis (CAD) system is also developed based on CBIR paradigm. Performance of the proposed CBIR-based CAD system is close to performance of the CAD system using support vector machine.

Neural network classification of sweet potato embryos

NASA Astrophysics Data System (ADS)

Molto, Enrique; Harrell, Roy C.

1993-05-01

Somatic embryogenesis is a process that allows for the in vitro propagation of thousands of plants in sub-liter size vessels and has been successfully applied to many significant species. The heterogeneity of maturity and quality of embryos produced with this technique requires sorting to obtain a uniform product. An automated harvester is being developed at the University of Florida to sort embryos in vitro at different stages of maturation in a suspension culture. The system utilizes machine vision to characterize embryo morphology and a fluidic based separation device to isolate embryos associated with a pre-defined, targeted morphology. Two different backpropagation neural networks (BNN) were used to classify embryos based on information extracted from the vision system. One network utilized geometric features such as embryo area, length, and symmetry as inputs. The alternative network utilized polar coordinates of an embryo's perimeter with respect to its centroid as inputs. The performances of both techniques were compared with each other and with an embryo classification method based on linear discriminant analysis (LDA). Similar results were obtained with all three techniques. Classification efficiency was improved by reducing the dimension of the feature vector trough a forward stepwise analysis by LDA. In order to enhance the purity of the sample selected as harvestable, a reject to classify option was introduced in the model and analyzed. The best classifier performances (76% overall correct classifications, 75% harvestable objects properly classified, homogeneity improvement ratio 1.5) were obtained using 8 features in a BNN.

node2vec: Scalable Feature Learning for Networks

PubMed Central

Grover, Aditya; Leskovec, Jure

2016-01-01

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

DROP: Detecting Return-Oriented Programming Malicious Code

NASA Astrophysics Data System (ADS)

Chen, Ping; Xiao, Hai; Shen, Xiaobin; Yin, Xinchun; Mao, Bing; Xie, Li

Return-Oriented Programming (ROP) is a new technique that helps the attacker construct malicious code mounted on x86/SPARC executables without any function call at all. Such technique makes the ROP malicious code contain no instruction, which is different from existing attacks. Moreover, it hides the malicious code in benign code. Thus, it circumvents the approaches that prevent control flow diversion outside legitimate regions (such as W ⊕ X ) and most malicious code scanning techniques (such as anti-virus scanners). However, ROP has its own intrinsic feature which is different from normal program design: (1) uses short instruction sequence ending in "ret", which is called gadget, and (2) executes the gadgets contiguously in specific memory space, such as standard GNU libc. Based on the features of the ROP malicious code, in this paper, we present a tool DROP, which is focused on dynamically detecting ROP malicious code. Preliminary experimental results show that DROP can efficiently detect ROP malicious code, and have no false positives and negatives.

Nonlinear model-order reduction for compressible flow solvers using the Discrete Empirical Interpolation Method

NASA Astrophysics Data System (ADS)

Fosas de Pando, Miguel; Schmid, Peter J.; Sipp, Denis

2016-11-01

Nonlinear model reduction for large-scale flows is an essential component in many fluid applications such as flow control, optimization, parameter space exploration and statistical analysis. In this article, we generalize the POD-DEIM method, introduced by Chaturantabut & Sorensen [1], to address nonlocal nonlinearities in the equations without loss of performance or efficiency. The nonlinear terms are represented by nested DEIM-approximations using multiple expansion bases based on the Proper Orthogonal Decomposition. These extensions are imperative, for example, for applications of the POD-DEIM method to large-scale compressible flows. The efficient implementation of the presented model-reduction technique follows our earlier work [2] on linearized and adjoint analyses and takes advantage of the modular structure of our compressible flow solver. The efficacy of the nonlinear model-reduction technique is demonstrated to the flow around an airfoil and its acoustic footprint. We could obtain an accurate and robust low-dimensional model that captures the main features of the full flow.

Combining knowledge discovery from databases (KDD) and case-based reasoning (CBR) to support diagnosis of medical images

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.

How visual working memory contents influence priming of visual attention.

PubMed

Carlisle, Nancy B; Kristjánsson, Árni

2017-04-12

Recent evidence shows that when the contents of visual working memory overlap with targets and distractors in a pop-out search task, intertrial priming is inhibited (Kristjánsson, Sævarsson & Driver, Psychon Bull Rev 20(3):514-521, 2013, Experiment 2, Psychonomic Bulletin and Review). This may reflect an interesting interaction between implicit short-term memory-thought to underlie intertrial priming-and explicit visual working memory. Evidence from a non-pop-out search task suggests that it may specifically be holding distractors in visual working memory that disrupts intertrial priming (Cunningham & Egeth, Psychol Sci 27(4):476-485, 2016, Experiment 2, Psychological Science). We examined whether the inhibition of priming depends on whether feature values in visual working memory overlap with targets or distractors in the pop-out search, and we found that the inhibition of priming resulted from holding distractors in visual working memory. These results are consistent with separate mechanisms of target and distractor effects in intertrial priming, and support the notion that the impact of implicit short-term memory and explicit visual working memory can interact when each provides conflicting attentional signals.

NREL-Prime Next-Generation Drivetrain Dynamometer Test Report

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

Keller, Jonathan; Erdman, Bill; Blodgett, Douglas

2016-08-01

Advances in wind turbine drivetrain technologies are necessary to improve reliability and reduce the cost of energy for land-based and offshore wind turbines. The NREL-Prime Next-Generation Drivetrain team developed a geared, medium-speed drivetrain that is lighter, more reliable and more efficient than existing designs. One of the objectives of Phase II of the project was to complete the detailed design, fabrication, and dynamometer testing of a 750 kilowatt (kW) drivetrain that includes the key gearbox innovations designed by Romax Technology and power converter innovations designed by DNV Kema Renewables. The purpose of this document is to summarize these tests completedmore » in NREL's National Wind Technology Center 2.5 megawatt (MW) dynamometer.« less

Imaging trace element distributions in single organelles and subcellular features

NASA Astrophysics Data System (ADS)

Kashiv, Yoav; Austin, Jotham R.; Lai, Barry; Rose, Volker; Vogt, Stefan; El-Muayed, Malek

2016-02-01

The distributions of chemical elements within cells are of prime importance in a wide range of basic and applied biochemical research. An example is the role of the subcellular Zn distribution in Zn homeostasis in insulin producing pancreatic beta cells and the development of type 2 diabetes mellitus. We combined transmission electron microscopy with micro- and nano-synchrotron X-ray fluorescence to image unequivocally for the first time, to the best of our knowledge, the natural elemental distributions, including those of trace elements, in single organelles and other subcellular features. Detected elements include Cl, K, Ca, Co, Ni, Cu, Zn and Cd (which some cells were supplemented with). Cell samples were prepared by a technique that minimally affects the natural elemental concentrations and distributions, and without using fluorescent indicators. It could likely be applied to all cell types and provide new biochemical insights at the single organelle level not available from organelle population level studies.

Implementation of real-time digital signal processing systems

NASA Technical Reports Server (NTRS)

Narasimha, M.; Peterson, A.; Narayan, S.

1978-01-01

Special purpose hardware implementation of DFT Computers and digital filters is considered in the light of newly introduced algorithms and IC devices. Recent work by Winograd on high-speed convolution techniques for computing short length DFT's, has motivated the development of more efficient algorithms, compared to the FFT, for evaluating the transform of longer sequences. Among these, prime factor algorithms appear suitable for special purpose hardware implementations. Architectural considerations in designing DFT computers based on these algorithms are discussed. With the availability of monolithic multiplier-accumulators, a direct implementation of IIR and FIR filters, using random access memories in place of shift registers, appears attractive. The memory addressing scheme involved in such implementations is discussed. A simple counter set-up to address the data memory in the realization of FIR filters is also described. The combination of a set of simple filters (weighting network) and a DFT computer is shown to realize a bank of uniform bandpass filters. The usefulness of this concept in arriving at a modular design for a million channel spectrum analyzer, based on microprocessors, is discussed.

Mixing Metaphors in the Cerebral Hemispheres: What Happens When Careers Collide?

PubMed Central

Chettih, Selmaan; Durgin, Frank H.; Grodner, Daniel J.

2014-01-01

Are processes of figurative comparison and figurative categorization different? An experiment combining alternative-sense and matched-sense metaphor priming with a divided visual field assessment technique sought to isolate processes of comparison and categorization in the two cerebral hemispheres. For target metaphors presented in the RVF/LH, only matched-sense primes were facilitative. Literal primes and alternative-sense primes had no effect on comprehension time compared to the unprimed baseline. The effects of matched-sense primes were additive with the rated conventionality of the targets. For target metaphors presented to the LVF/RH, matched-sense primes were again additively facilitative. However, alternative-sense primes, though facilitative overall, seemed to eliminate the pre-existing advantages of conventional target metaphor senses in the LVF/RH in favor of metaphoric senses similar to those of the primes. These findings are consistent with tightly controlled categorical coding in the LH and coarse, and flexible, context dependent coding in the RH. PMID:22103787

A series connection architecture for large-area organic photovoltaic modules with a 7.5% module efficiency

PubMed Central

Hong, Soonil; Kang, Hongkyu; Kim, Geunjin; Lee, Seongyu; Kim, Seok; Lee, Jong-Hoon; Lee, Jinho; Yi, Minjin; Kim, Junghwan; Back, Hyungcheol; Kim, Jae-Ryoung; Lee, Kwanghee

2016-01-01

The fabrication of organic photovoltaic modules via printing techniques has been the greatest challenge for their commercial manufacture. Current module architecture, which is based on a monolithic geometry consisting of serially interconnecting stripe-patterned subcells with finite widths, requires highly sophisticated patterning processes that significantly increase the complexity of printing production lines and cause serious reductions in module efficiency due to so-called aperture loss in series connection regions. Herein we demonstrate an innovative module structure that can simultaneously reduce both patterning processes and aperture loss. By using a charge recombination feature that occurs at contacts between electron- and hole-transport layers, we devise a series connection method that facilitates module fabrication without patterning the charge transport layers. With the successive deposition of component layers using slot-die and doctor-blade printing techniques, we achieve a high module efficiency reaching 7.5% with area of 4.15 cm2. PMID:26728507

Contextual Constraint Treatment for coarse coding deficit in adults with right hemisphere brain damage: Generalization to narrative discourse comprehension

PubMed Central

Blake, Margaret Lehman; Tompkins, Connie A.; Scharp, Victoria L.; Meigh, Kimberly M.; Wambaugh, Julie

2014-01-01

Coarse coding is the activation of broad semantic fields that can include multiple word meanings and a variety of features, including those peripheral to a word’s core meaning. It is a partially domain-general process related to general discourse comprehension and contributes to both literal and non-literal language processing. Adults with damage to the right cerebral hemisphere (RHD) and a coarse coding deficit are particularly slow to activate features of words that are relatively distant or peripheral. This manuscript reports a pre-efficacy study of Contextual Constraint Treatment (CCT), a novel, implicit treatment designed to increase the efficiency of coarse coding with the goal of improving narrative comprehension and other language performance that relies on coarse coding. Participants were four adults with RHD. The study used a single-subject controlled experimental design across subjects and behaviors. The treatment involves pre-stimulation, using a hierarchy of strong- and moderately-biased contexts, to prime the intended distantly-related features of critical stimulus words. Three of the four participants exhibited gains in auditory narrative discourse comprehension, the primary outcome measure. All participants exhibited generalization to untreated items. No strong generalization to processing nonliteral language was evident. The results indicate that CCT yields both improved efficiency of the coarse coding process and generalization to narrative comprehension. PMID:24983133

Homogeneous catalysts for stereoregular olefin polymerization

DOEpatents

Marks, T.J.; Eisen, M.S.; Giardello, M.A.

1995-10-03

The synthesis, and use as precatalysts of chiral organozirconium complexes for olefin polymerization are disclosed, having the structure (C{sub 5}R{prime}{sub 4{minus}x}R*{sub x})A(C{sub 5}R{double_prime}{sub 4{minus}y}R{double_prime}{prime}{sub y})MQ{sub p}, where x and y represent the number of unsubstituted locations on the cyclopentadienyl ring; R{prime}, R{double_prime}, R{double_prime}{prime}, and R* represent substituted and unsubstituted alkyl groups having 1--30 carbon atoms and R* is a chiral ligand; A is a fragment containing a Group 13, 14, 15, or 16 element of the Periodic Table; M is a Group 3, 4, or 5 metal of the Periodic Table; and Q is a hydrocarbyl radical, or halogen radical, with 3{>=}p{>=}0. Related complexes may be prepared by alkylation of the corresponding dichlorides. In the presence of methylalumoxane or triarylborane cocatalysts, these complexes form ``cation-like`` species which are highly active for olefin polymerization. In combination with a Lewis acid cocatalyst, propylene or other {alpha}-olefin polymerization can be effected with very high efficiency and isospecificity. 1 fig.

Homogeneous catalysts for stereoregular olefin polymerization

DOEpatents

Marks, T.J.; Eisen, M.S.; Giardello, M.A.

1994-07-19

The synthesis, and use as precatalysts of chiral organozirconium complexes for olefin polymerization are disclosed, having the structure (C[sub 5]R[prime][sub 4[minus]x]R*[sub x])-A-(C[sub 5]R[double prime][sub 4[minus]y]R[prime][double prime][sub y])-M-Q[sub p], where x and y represent the number of unsubstituted locations on the cyclopentadienyl ring; R[prime], R[double prime], R[prime][double prime], and R* represent substituted and unsubstituted alkyl groups having 1--30 carbon atoms and R* is a chiral ligand; A is a fragment containing a Group 13, 14, 15, or 16 element of the Periodic Table; M is a Group 3, 4, or 5 metal of the Periodic Table; and Q is a hydrocarbyl radical, or halogen radical, with 3 [<=] p [<=] 0. Related complexes may be prepared by alkylation of the corresponding dichlorides. In the presence of methylalumoxane or triarylborane cocatalysts, these complexes form cation-like'' species which are highly active for olefin polymerization. In combination with a Lewis acid cocatalyst, propylene or other [alpha]-olefin polymerization can be effected with very high efficiency and isospecificity. 1 fig.

Mm-Wave Spectroscopic Sensors, Catalogs, and Uncatalogued Lines

NASA Astrophysics Data System (ADS)

Medvedev, Ivan; Neese, Christopher F.; De Lucia, Frank C.

2014-06-01

Analytical chemical sensing based on high resolution rotational molecular spectra has been recognized as a viable technique for decades. We recently demonstrated a compact implementation of such a sensor. Future generations of these sensors will rely on automated algorithms for quantification of chemical dilutions based on their spectral libraries, as well as identification of spectral features not present in spectral catalogs. Here we present an algorithm aimed at detection of unidentified lines in complex molecular species based on spectroscopic libraries developed in our previous projects. We will discuss the approaches suitable for data mining in feature-rich rotational molecular spectra. Neese, C.F., I.R. Medvedev, G.M. Plummer, A.J. Frank, C.D. Ball, and F.C. De Lucia, "A Compact Submillimeter/Terahertz Gas Sensor with Efficient Gas Collection, Preconcentration, and ppt Sensitivity." Sensors Journal, IEEE, 2012. 12(8): p. 2565-2574

A new technique for solving puzzles.

PubMed

Makridis, Michael; Papamarkos, Nikos

2010-06-01

This paper proposes a new technique for solving jigsaw puzzles. The novelty of the proposed technique is that it provides an automatic jigsaw puzzle solution without any initial restriction about the shape of pieces, the number of neighbor pieces, etc. The proposed technique uses both curve- and color-matching similarity features. A recurrent procedure is applied, which compares and merges puzzle pieces in pairs, until the original puzzle image is reformed. Geometrical and color features are extracted on the characteristic points (CPs) of the puzzle pieces. CPs, which can be considered as high curvature points, are detected by a rotationally invariant corner detection algorithm. The features which are associated with color are provided by applying a color reduction technique using the Kohonen self-organized feature map. Finally, a postprocessing stage checks and corrects the relative position between puzzle pieces to improve the quality of the resulting image. Experimental results prove the efficiency of the proposed technique, which can be further extended to deal with even more complex jigsaw puzzle problems.

Copy-move forgery detection utilizing Fourier-Mellin transform log-polar features

NASA Astrophysics Data System (ADS)

Dixit, Rahul; Naskar, Ruchira

2018-03-01

In this work, we address the problem of region duplication or copy-move forgery detection in digital images, along with detection of geometric transforms (rotation and rescale) and postprocessing-based attacks (noise, blur, and brightness adjustment). Detection of region duplication, following conventional techniques, becomes more challenging when an intelligent adversary brings about such additional transforms on the duplicated regions. In this work, we utilize Fourier-Mellin transform with log-polar mapping and a color-based segmentation technique using K-means clustering, which help us to achieve invariance to all the above forms of attacks in copy-move forgery detection of digital images. Our experimental results prove the efficiency of the proposed method and its superiority to the current state of the art.

Automatic Beam Path Analysis of Laser Wakefield Particle Acceleration Data

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

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

2009-10-19

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

Fast and effective characterization of 3D region of interest in medical image data

NASA Astrophysics Data System (ADS)

Kontos, Despina; Megalooikonomou, Vasileios

2004-05-01

We propose a framework for detecting, characterizing and classifying spatial Regions of Interest (ROIs) in medical images, such as tumors and lesions in MRI or activation regions in fMRI. A necessary step prior to classification is efficient extraction of discriminative features. For this purpose, we apply a characterization technique especially designed for spatial ROIs. The main idea of this technique is to extract a k-dimensional feature vector using concentric spheres in 3D (or circles in 2D) radiating out of the ROI's center of mass. These vectors form characterization signatures that can be used to represent the initial ROIs. We focus on classifying fMRI ROIs obtained from a study that explores neuroanatomical correlates of semantic processing in Alzheimer's disease (AD). We detect a ROI highly associated with AD and apply the feature extraction technique with different experimental settings. We seek to distinguish control from patient samples. We study how classification can be performed using the extracted signatures as well as how different experimental parameters affect classification accuracy. The obtained classification accuracy ranged from 82% to 87% (based on the selected ROI) suggesting that the proposed classification framework can be potentially useful in supporting medical decision-making.

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

Guo, Wei, E-mail: wguo2@ncsu.edu; Kirste, Ronny; Bryan, Zachary

Enhanced light extraction efficiency was demonstrated on nanostructure patterned GaN and AlGaN/AlN Multiple-Quantum-Well (MQW) structures using mass production techniques including natural lithography and interference lithography with feature size as small as 100 nm. Periodic nanostructures showed higher light extraction efficiency and modified emission profile compared to non-periodic structures based on integral reflection and angular-resolved transmission measurement. Light extraction mechanism of macroscopic and microscopic nanopatterning is discussed, and the advantage of using periodic nanostructure patterning is provided. An enhanced photoluminescence emission intensity was observed on nanostructure patterned AlGaN/AlN MQW compared to as-grown structure, demonstrating a large-scale and mass-producible pathway to higher lightmore » extraction efficiency in deep-ultra-violet light-emitting diodes.« less

Learner-Centred Pedagogy for Swim Coaching: A Complex Learning Theory-Informed Approach

ERIC Educational Resources Information Center

Light, Richard

2014-01-01

While constructivist theories of learning have been widely drawn on to understand and explain learning in games when using game-based approaches their use to inform pedagogy beyond games is limited. In particular, there has been little interest in applying constructivist perspectives on learning to sports in which technique is of prime importance.…

Classification of weld defect based on information fusion technology for radiographic testing system

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

Jiang, Hongquan; Liang, Zeming, E-mail: heavenlzm@126.com; Gao, Jianmin

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster–Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defectmore » feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.« less

Classification of weld defect based on information fusion technology for radiographic testing system.

PubMed

Jiang, Hongquan; Liang, Zeming; Gao, Jianmin; Dang, Changying

2016-03-01

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

Robust immunity to an auxotrophic Mycobacterium bovis BCG-VLP prime-boost HIV vaccine candidate in a nonhuman primate model.

PubMed

Chege, Gerald K; Burgers, Wendy A; Stutz, Helen; Meyers, Ann E; Chapman, Rosamund; Kiravu, Agano; Bunjun, Rubina; Shephard, Enid G; Jacobs, William R; Rybicki, Edward P; Williamson, Anna-Lise

2013-05-01

We previously reported that a recombinant pantothenate auxotroph of Mycobacterium bovis BCG expressing human immunodeficiency virus type 1 (HIV-1) subtype C Gag (rBCGpan-Gag) efficiently primes the mouse immune system for a boost with a recombinant modified vaccinia virus Ankara (rMVA) vaccine. In this study, we further evaluated the immunogenicity of rBCGpan-Gag in a nonhuman primate model. Two groups of chacma baboons were primed or mock primed twice with either rBCGpan-Gag or a control BCG. Both groups were boosted with HIV-1 Pr55(gag) virus-like particles (Gag VLPs). The magnitude and breadth of HIV-specific cellular responses were measured using a gamma interferon (IFN-γ) enzyme-linked immunosorbent spot (ELISPOT) assay, and the cytokine profiles and memory phenotypes of T cells were evaluated by polychromatic flow cytometry. Gag-specific responses were detected in all animals after the second inoculation with rBCGpan-Gag. Boosting with Gag VLPs significantly increased the magnitude and breadth of the responses in the baboons that were primed with rBCGpan-Gag. These responses targeted an average of 12 Gag peptides per animal, compared to an average of 3 peptides per animal for the mock-primed controls. Robust responses of Gag-specific polyfunctional T cells capable of simultaneously producing IFN-γ, tumor necrosis alpha (TNF-α), and interleukin-2 (IL-2) were detected in the rBCGpan-Gag-primed animals. Gag-specific memory T cells were skewed toward a central memory phenotype in both CD4(+) and CD8(+) T cell populations. These data show that the rBCGpan-Gag prime and Gag VLP boost vaccine regimen is highly immunogenic, inducing a broad and polyfunctional central memory T cell response. This report further indicates the feasibility of developing a BCG-based HIV vaccine that is safe for childhood HIV immunization.

Neutrophil priming: Implications in periodontal disease

PubMed Central

Shah, Rucha; Thomas, Raison; Mehta, Dhoom Singh

2017-01-01

Periodontal disease is a well-regulated response to bacterial infection directed by the inflammatory cells of the host immune system. The host response to injury or insult is implicated to be a vital feature of the majority of periodontal diseases. The excessive activation of neutrophils plays a role in the pathogenesis in diseases such as acute respiratory distress syndrome, rheumatoid arthritis, and periodontitis by contributing to inflammatory tissue injury. In the recent times, there has been a shift of paradigm from a hypo- to hyper-responsive/primed model of neutrophil dysfunction in periodontal etiopathogenesis. The aim of this review is to outline the mechanisms and effects of neutrophil priming, and thereafter, discuss the current controversy that exists regarding the role of primed neutrophils in periodontal etiopathogenesis. PMID:29440782

Snack intake is reduced using an implicit, high-level construal cue.

PubMed

Price, Menna; Higgs, Suzanne; Lee, Michelle

2016-08-01

Priming a high level construal has been shown to enhance self-control and reduce preference for indulgent food. Subtle visual cues have been shown to enhance the effects of a priming procedure. The current study therefore examined the combined impact of construal level and a visual cue reminder on the consumption of energy-dense snacks. A student and community-based adult sample with a wide age and body mass index (BMI) range (N = 176) were randomly assigned to a high or low construal condition in which a novel symbol was embedded. Afterward participants completed a taste test of ad libitum snack foods in the presence or absence of the symbol. The high (vs. the low) construal level prime successfully generated more abstract responses (p < .0001) and reduced intake when the cue-reminder was present (p = .02) but not when it was absent (p = .40). Priming high construal level thinking reduces consumption of high energy dense snacks in the presence of a visual cue-reminder. This may be a practical technique for reducing overeating and has the potential to be extended to other unhealthy behaviors. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Sentence Syntax and Content in the Human Temporal Lobe: An fMRI Adaptation Study in Auditory and Visual Modalities

ERIC Educational Resources Information Center

Devauchelle, Anne-Dominique; Oppenheim, Catherine; Rizzi, Luigi; Dehaene, Stanislas; Pallier, Christophe

2009-01-01

Priming effects have been well documented in behavioral psycholinguistics experiments: The processing of a word or a sentence is typically facilitated when it shares lexico-semantic or syntactic features with a previously encountered stimulus. Here, we used fMRI priming to investigate which brain areas show adaptation to the repetition of a…

Transposed-letter priming of prelexical orthographic representations.

PubMed

Kinoshita, Sachiko; Norris, Dennis

2009-01-01

A prime generated by transposing two internal letters (e.g., jugde) produces strong priming of the original word (judge). In lexical decision, this transposed-letter (TL) priming effect is generally weak or absent for nonword targets; thus, it is unclear whether the origin of this effect is lexical or prelexical. The authors describe the Bayesian Reader theory of masked priming (D. Norris & S. Kinoshita, 2008), which explains why nonwords do not show priming in lexical decision but why they do in the cross-case same-different task. This analysis is followed by 3 experiments that show that priming in this task is not based on low-level perceptual similarity between the prime and target, or on phonology, to make the case that priming is based on prelexical orthographic representation. The authors then use this task to demonstrate equivalent TL priming effects for nonwords and words. The results are interpreted as the first reliable evidence based on the masked priming procedure that letter position is not coded absolutely within the prelexical, orthographic representation. The implications of the results for current letter position coding schemes are discussed.

Comprehensive study of the dynamics of a classical Kitaev Spin Liquid

NASA Astrophysics Data System (ADS)

Samarakoon, Anjana; Banerjee, Arnab; Batista, Cristian; Kamiya, Yoshitomo; Tennant, Alan; Nagler, Stephen

Quantum spin liquids (QSLs) have achieved great interest in both theoretical and experimental condensed matter physics due to their remarkable topological properties. Among many different candidates, the Kitaev model on the honeycomb lattice is a 2D prototypical QSL which can be experimentally studied in materials based on iridium or ruthenium.Here we study the spin-1/2 Kitaev model using classical Monte-Carlo and semiclassical spin dynamics of classical spins on a honeycomb lattice. Both real and reciprocal space pictures highlighting the differences and similarities of the results to the linear spin wave theory will be discussed in terms dispersion relations of the pure-Kitaev limit and beyond. Interestingly, this technique could capture some of the salient features of the exact quantum solution of the Kitaev model, such as features resembling the Majorana-like mode comparable to the Kitaev energy, which is spectrally narrowed compared to the quantum result, can be explained by magnon excitations on fluctuating onedimensional manifolds (loops). Hence the difference from the classical limit to the quantum limit can be understood by the fractionalization of a magnon to Majorana fermions. The calculations will be directly compared with our neutron scattering data on α-RuCl3 which is a prime candidate for experimental realization of Kitaev physics.

Do different perceptual task sets modulate electrophysiological correlates of masked visuomotor priming? Attention to shape and color put to the test.

PubMed

Zovko, Monika; Kiefer, Markus

2013-02-01

According to classical theories, automatic processes operate independently of attention. Recent evidence, however, shows that masked visuomotor priming, an example of an automatic process, depends on attention to visual form versus semantics. In a continuation of this approach, we probed feature-specific attention within the perceptual domain and tested in two event-related potential (ERP) studies whether masked visuomotor priming in a shape decision task specifically depends on attentional sensitization of visual pathways for shape in contrast to color. Prior to the masked priming procedure, a shape or a color decision task served to induce corresponding task sets. ERP analyses revealed visuomotor priming effects over the occipitoparietal scalp only after the shape, but not after the color induction task. Thus, top-down control coordinates automatic processing streams in congruency with higher-level goals even at a fine-grained level. Copyright © 2012 Society for Psychophysiological Research.

Affective priming effects of musical sounds on the processing of word meaning.

PubMed

Steinbeis, Nikolaus; Koelsch, Stefan

2011-03-01

Recent studies have shown that music is capable of conveying semantically meaningful concepts. Several questions have subsequently arisen particularly with regard to the precise mechanisms underlying the communication of musical meaning as well as the role of specific musical features. The present article reports three studies investigating the role of affect expressed by various musical features in priming subsequent word processing at the semantic level. By means of an affective priming paradigm, it was shown that both musically trained and untrained participants evaluated emotional words congruous to the affect expressed by a preceding chord faster than words incongruous to the preceding chord. This behavioral effect was accompanied by an N400, an ERP typically linked with semantic processing, which was specifically modulated by the (mis)match between the prime and the target. This finding was shown for the musical parameter of consonance/dissonance (Experiment 1) and then extended to mode (major/minor) (Experiment 2) and timbre (Experiment 3). Seeing that the N400 is taken to reflect the processing of meaning, the present findings suggest that the emotional expression of single musical features is understood by listeners as such and is probably processed on a level akin to other affective communications (i.e., prosody or vocalizations) because it interferes with subsequent semantic processing. There were no group differences, suggesting that musical expertise does not have an influence on the processing of emotional expression in music and its semantic connotations.

Influence of Temporal Expectations on Response Priming by Subliminal Faces

PubMed Central

Guex, Raphael; Vuilleumier, Patrik

2016-01-01

Unconscious processes are often assumed immune from attention influence. Recent behavioral studies suggest however that the processing of subliminal information can be influenced by temporal attention. To examine the neural mechanisms underlying these effects, we used a stringent masking paradigm together with fMRI to investigate how temporal attention modulates the processing of unseen (masked) faces. Participants performed a gender decision task on a visible neutral target face, preceded by a masked prime face that could vary in gender (same or different than target) and emotion expression (neutral or fearful). We manipulated temporal attention by instructing participants to expect targets to appear either early or late during the stimulus sequence. Orienting temporal attention to subliminal primes influenced response priming by masked faces, even when gender was incongruent. In addition, gender-congruent primes facilitated responses regardless of attention while gender-incongruent primes reduced accuracy when attended. Emotion produced no differential effects. At the neural level, incongruent and temporally unexpected primes increased brain response in regions of the fronto-parietal attention network, reflecting greater recruitment of executive control and reorienting processes. Congruent and expected primes produced higher activations in fusiform cortex, presumably reflecting facilitation of perceptual processing. These results indicate that temporal attention can influence subliminal processing of face features, and thus facilitate information integration according to task-relevance regardless of conscious awareness. They also suggest that task-congruent information between prime and target may facilitate response priming even when temporal attention is not selectively oriented to the prime onset time. PMID:27764124

Influence of Temporal Expectations on Response Priming by Subliminal Faces.

PubMed

Pichon, Swann; Guex, Raphael; Vuilleumier, Patrik

2016-01-01

Unconscious processes are often assumed immune from attention influence. Recent behavioral studies suggest however that the processing of subliminal information can be influenced by temporal attention. To examine the neural mechanisms underlying these effects, we used a stringent masking paradigm together with fMRI to investigate how temporal attention modulates the processing of unseen (masked) faces. Participants performed a gender decision task on a visible neutral target face, preceded by a masked prime face that could vary in gender (same or different than target) and emotion expression (neutral or fearful). We manipulated temporal attention by instructing participants to expect targets to appear either early or late during the stimulus sequence. Orienting temporal attention to subliminal primes influenced response priming by masked faces, even when gender was incongruent. In addition, gender-congruent primes facilitated responses regardless of attention while gender-incongruent primes reduced accuracy when attended. Emotion produced no differential effects. At the neural level, incongruent and temporally unexpected primes increased brain response in regions of the fronto-parietal attention network, reflecting greater recruitment of executive control and reorienting processes. Congruent and expected primes produced higher activations in fusiform cortex, presumably reflecting facilitation of perceptual processing. These results indicate that temporal attention can influence subliminal processing of face features, and thus facilitate information integration according to task-relevance regardless of conscious awareness. They also suggest that task-congruent information between prime and target may facilitate response priming even when temporal attention is not selectively oriented to the prime onset time.

Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection.

PubMed

Al-Jarrah, Omar Y; Alhussein, Omar; Yoo, Paul D; Muhaidat, Sami; Taha, Kamal; Kim, Kwangjo

2016-08-01

Botnets, which consist of remotely controlled compromised machines called bots, provide a distributed platform for several threats against cyber world entities and enterprises. Intrusion detection system (IDS) provides an efficient countermeasure against botnets. It continually monitors and analyzes network traffic for potential vulnerabilities and possible existence of active attacks. A payload-inspection-based IDS (PI-IDS) identifies active intrusion attempts by inspecting transmission control protocol and user datagram protocol packet's payload and comparing it with previously seen attacks signatures. However, the PI-IDS abilities to detect intrusions might be incapacitated by packet encryption. Traffic-based IDS (T-IDS) alleviates the shortcomings of PI-IDS, as it does not inspect packet payload; however, it analyzes packet header to identify intrusions. As the network's traffic grows rapidly, not only the detection-rate is critical, but also the efficiency and the scalability of IDS become more significant. In this paper, we propose a state-of-the-art T-IDS built on a novel randomized data partitioned learning model (RDPLM), relying on a compact network feature set and feature selection techniques, simplified subspacing and a multiple randomized meta-learning technique. The proposed model has achieved 99.984% accuracy and 21.38 s training time on a well-known benchmark botnet dataset. Experiment results demonstrate that the proposed methodology outperforms other well-known machine-learning models used in the same detection task, namely, sequential minimal optimization, deep neural network, C4.5, reduced error pruning tree, and randomTree.

Reduced-order modeling of piezoelectric energy harvesters with nonlinear circuits under complex conditions

NASA Astrophysics Data System (ADS)

Xiang, Hong-Jun; Zhang, Zhi-Wei; Shi, Zhi-Fei; Li, Hong

2018-04-01

A fully coupled modeling approach is developed for piezoelectric energy harvesters in this work based on the use of available robust finite element packages and efficient reducing order modeling techniques. At first, the harvester is modeled using finite element packages. The dynamic equilibrium equations of harvesters are rebuilt by extracting system matrices from the finite element model using built-in commands without any additional tools. A Krylov subspace-based scheme is then applied to obtain a reduced-order model for improving simulation efficiency but preserving the key features of harvesters. Co-simulation of the reduced-order model with nonlinear energy harvesting circuits is achieved in a system level. Several examples in both cases of harmonic response and transient response analysis are conducted to validate the present approach. The proposed approach allows to improve the simulation efficiency by several orders of magnitude. Moreover, the parameters used in the equivalent circuit model can be conveniently obtained by the proposed eigenvector-based model order reduction technique. More importantly, this work establishes a methodology for modeling of piezoelectric energy harvesters with any complicated mechanical geometries and nonlinear circuits. The input load may be more complex also. The method can be employed by harvester designers to optimal mechanical structures or by circuit designers to develop novel energy harvesting circuits.

Protein fold recognition using geometric kernel data fusion.

PubMed

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

Capillary electrophoresis in two-dimensional separation systems: Techniques and applications.

PubMed

Kohl, Felix J; Sánchez-Hernández, Laura; Neusüß, Christian

2015-01-01

The analysis of complex samples requires powerful separation techniques. Here, 2D chromatographic separation techniques (e.g. LC-LC, GC-GC) are increasingly applied in many fields. Electrophoretic separation techniques show a different selectivity in comparison to LC and GC and very high separation efficiency. Thus, 2D separation systems containing at least one CE-based separation technique are an interesting alternative featuring potentially a high degree of orthogonality. However, the generally small volumes and strong electrical fields in CE require special coupling techniques. These technical developments are reviewed in this work, discussing benefits and drawbacks of offline and online systems. Emphasis is placed on the design of the systems, their coupling, and the detector used. Moreover, the employment of strategies to improve peak capacity, resolution, or sensitivity is highlighted. Various applications of 2D separations with CE are summarized. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ID-based encryption scheme with revocation

NASA Astrophysics Data System (ADS)

Othman, Hafizul Azrie; Ismail, Eddie Shahril

2017-04-01

In 2015, Meshram proposed an efficient ID-based cryptographic encryption based on the difficulty of solving discrete logarithm and integer-factoring problems. The scheme was pairing free and claimed to be secure against adaptive chosen plaintext attacks (CPA). Later, Tan et al. proved that the scheme was insecure by presenting a method to recover the secret master key and to obtain prime factorization of modulo n. In this paper, we propose a new pairing-free ID-based encryption scheme with revocation based on Meshram's ID-based encryption scheme, which is also secure against Tan et al.'s attacks.

A novel approach for fire recognition using hybrid features and manifold learning-based classifier

NASA Astrophysics Data System (ADS)

Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

2018-03-01

Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

The effect of analytic and experiential modes of thought on moral judgment.

PubMed

Kvaran, Trevor; Nichols, Shaun; Sanfey, Alan

2013-01-01

According to dual-process theories, moral judgments are the result of two competing processes: a fast, automatic, affect-driven process and a slow, deliberative, reason-based process. Accordingly, these models make clear and testable predictions about the influence of each system. Although a small number of studies have attempted to examine each process independently in the context of moral judgment, no study has yet tried to experimentally manipulate both processes within a single study. In this chapter, a well-established "mode-of-thought" priming technique was used to place participants in either an experiential/emotional or analytic mode while completing a task in which participants provide judgments about a series of moral dilemmas. We predicted that individuals primed analytically would make more utilitarian responses than control participants, while emotional priming would lead to less utilitarian responses. Support was found for both of these predictions. Implications of these findings for dual-process theories of moral judgment will be discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Efficient Computer Implementations of Fast Fourier Transforms.

DTIC Science & Technology

1980-12-01

fit in computer? Yes, continue (9) Determine fastest algorithm between WFTA and PFA from Table 4.6. For N=420, WFTA PFA Mult 1296 2528 Add 11352 10956...real adds = 24tN/4 + 2(3tN/4) = 15tN/2 (G.8) 260 All odd prime C<ictors ciual to or (,rater than 5 iso the general transform section. Based on the

Progressively expanded neural network for automatic material identification in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Paheding, Sidike

The science of hyperspectral remote sensing focuses on the exploitation of the spectral signatures of various materials to enhance capabilities including object detection, recognition, and material characterization. Hyperspectral imagery (HSI) has been extensively used for object detection and identification applications since it provides plenty of spectral information to uniquely identify materials by their reflectance spectra. HSI-based object detection algorithms can be generally classified into stochastic and deterministic approaches. Deterministic approaches are comparatively simple to apply since it is usually based on direct spectral similarity such as spectral angles or spectral correlation. In contrast, stochastic algorithms require statistical modeling and estimation for target class and non-target class. Over the decades, many single class object detection methods have been proposed in the literature, however, deterministic multiclass object detection in HSI has not been explored. In this work, we propose a deterministic multiclass object detection scheme, named class-associative spectral fringe-adjusted joint transform correlation. Human brain is capable of simultaneously processing high volumes of multi-modal data received every second of the day. In contrast, a machine sees input data simply as random binary numbers. Although machines are computationally efficient, they are inferior when comes to data abstraction and interpretation. Thus, mimicking the learning strength of human brain has been current trend in artificial intelligence. In this work, we present a biological inspired neural network, named progressively expanded neural network (PEN Net), based on nonlinear transformation of input neurons to a feature space for better pattern differentiation. In PEN Net, discrete fixed excitations are disassembled and scattered in the feature space as a nonlinear line. Each disassembled element on the line corresponds to a pattern with similar features. Unlike the conventional neural network where hidden neurons need to be iteratively adjusted to achieve better accuracy, our proposed PEN Net does not require hidden neurons tuning which achieves better computational efficiency, and it has also shown superior performance in HSI classification tasks compared to the state-of-the-arts. Spectral-spatial features based HSI classification framework has shown stronger strength compared to spectral-only based methods. In our lastly proposed technique, PEN Net is incorporated with multiscale spatial features (i.e., multiscale complete local binary pattern) to perform a spectral-spatial classification of HSI. Several experiments demonstrate excellent performance of our proposed technique compared to the more recent developed approaches.

The Word Shape Hypothesis Re-Examined: Evidence for an External Feature Advantage in Visual Word Recognition

ERIC Educational Resources Information Center

Beech, John R.; Mayall, Kate A.

2005-01-01

This study investigates the relative roles of internal and external letter features in word recognition. In Experiment 1 the efficacy of outer word fragments (words with all their horizontal internal features removed) was compared with inner word fragments (words with their outer features removed) as primes in a forward masking paradigm. These…

A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

PubMed

Li, Liqi; Luo, Qifa; Xiao, Weidong; Li, Jinhui; Zhou, Shiwen; Li, Yongsheng; Zheng, Xiaoqi; Yang, Hua

2017-02-01

Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, organelle localization, and functions, therefore plays an important role in a variety of cell biological processes. Identification of palmitoylation sites is necessary for understanding protein-protein interaction, protein stability, and activity. Since conventional experimental techniques to determine palmitoylation sites in proteins are both labor intensive and costly, a fast and accurate computational approach to predict palmitoylation sites from protein sequences is in urgent need. In this study, a support vector machine (SVM)-based method was proposed through integrating PSI-BLAST profile, physicochemical properties, [Formula: see text]-mer amino acid compositions (AACs), and [Formula: see text]-mer pseudo AACs into the principal feature vector. A recursive feature selection scheme was subsequently implemented to single out the most discriminative features. Finally, an SVM method was implemented to predict palmitoylation sites in proteins based on the optimal features. The proposed method achieved an accuracy of 99.41% and Matthews Correlation Coefficient of 0.9773 for a benchmark dataset. The result indicates the efficiency and accuracy of our method in prediction of palmitoylation sites based on protein sequences.

A prime-boost vaccination strategy using attenuated Salmonella typhimurium and a replication-deficient recombinant adenovirus vector elicits protective immunity against human respiratory syncytial virus.

PubMed

Fu, Yuan-Hui; He, Jin-Sheng; Wang, Xiao-Bo; Zheng, Xian-Xian; Wu, Qiang; Xie, Can; Zhang, Mei; Wei, Wei; Tang, Qian; Song, Jing-Dong; Qu, Jian-Guo; Hong, Tao

2010-04-23

Human respiratory syncytial virus (RSV), for which no clinically approved vaccine is available yet, is globally a serious pediatric pathogen of the lower respiratory tract. Several approaches have been used to develop vaccines against RSV, but none of these have been approved for use in humans. An efficient vaccine-enhancing strategy for RSV is still urgently needed. We found previously that oral SL7207/pcDNA3.1/F and intranasal FGAd/F were able to induce an effective protective immune response against RSV. The heterologous prime-boost immunization regime has been reported recently to be an efficient vaccine-enhancing strategy. Therefore, we investigated the ability of an oral SL7207/pcDNA3.1/F prime and intranasal (i.n.) FGAd/F boost regimen to generate immune responses to RSV. The SL7207/pcDNA3.1/F prime-FGAd/F boost regimen generated stronger RSV-specific humoral and mucosal immune responses in BALB/c mice than the oral SL7207/pcDNA3.1/F regimen alone, and stronger specific cellular immune responses than the i.n. FGAd/F regimen alone. Histopathological analysis showed an increased efficacy against RSV challenge by the heterologous prime-boost regimen. These results suggest that such a heterologous prime-boost strategy can enhance the efficacy of either the SL7207 or the FGAd vector regimen in generating immune responses in BALB/c mice. 2010 Elsevier Inc. All rights reserved.

Electrophysiological evidence for attentional guidance by the contents of working memory.

PubMed

Kumar, Sanjay; Soto, David; Humphreys, Glyn W

2009-07-01

The deployment of visual attention can be strongly modulated by stimuli matching the contents of working memory (WM), even when WM contents are detrimental to performance and salient bottom-up cues define the critical target [D. Soto et al. (2006)Vision Research, 46, 1010-1018]. Here we investigated the electrophysiological correlates of this early guidance of attention by WM in humans. Observers were presented with a prime to either identify or hold in memory. Subsequently, they had to search for a target line amongst different distractor lines. Each line was embedded within one of four objects and one of the distractor objects could match the stimulus held in WM. Behavioural data showed that performance was more strongly affected by the prime when it was held in memory than when it was merely identified. An electrophysiological measure of the efficiency of target selection (the N2pc) was also affected by the match between the item in WM and the location of the target in the search task. The N2pc was enhanced when the target fell in the same visual field as the re-presented (invalid) prime, compared with when the prime did not reappear in the search display (on neutral trials) and when the prime was contralateral to the target. Merely identifying the prime produced no effect on the N2pc component. The evidence suggests that WM modulates competitive interactions between the items in the visual field to determine the efficiency of target selection.

Rapid calibrated high-resolution hyperspectral imaging using tunable laser source

NASA Astrophysics Data System (ADS)

Nguyen, Lam K.; Margalith, Eli

2009-05-01

We present a novel hyperspectral imaging technique based on tunable laser technology. By replacing the broadband source and tunable filters of a typical NIR imaging instrument, several advantages are realized, including: high spectral resolution, highly variable field-of-views, fast scan-rates, high signal-to-noise ratio, and the ability to use optical fiber for efficient and flexible sample illumination. With this technique, high-resolution, calibrated hyperspectral images over the NIR range can be acquired in seconds. The performance of system features will be demonstrated on two example applications: detecting melamine contamination in wheat gluten and separating bovine protein from wheat protein in cattle feed.

Micropropagation systems of Feijoa (Acca sellowiana (O. Berg) Burret).

PubMed

Guerra, Miguel Pedro; Cangahuala-Inocente, Gabriela Claudia; Vesco, Lirio Luiz Dal; Pescador, Rosete; Caprestano, Clarissa Alves

2013-01-01

Acca sellowiana (O. Berg) Burret sin. Feijoa sellowiana (Myrtaceae) is a semiwoody fruit species native to South Brazil, Uruguay, and Argentina; edible fruits are tasty. The naturally occurring populations in Santa Catarina State show high variability in fruit size, color, and other features. A breeding program launched in 1990 resulted in the release of four Brazilian commercial varieties. The conventional clonal propagation methods of this species, such as cutting and grafting, have shown low efficiency. Therefore, tissue culture techniques were developed for mass propagation. This chapter describes several protocols based on organogenesis and somatic embryogenesis. Additional techniques including synthetic seed technology and temporary immersion system are also described.

Highly efficient and stable ultraviolet photocathode based on nanodiamond particles

NASA Astrophysics Data System (ADS)

Velardi, L.; Valentini, A.; Cicala, G.

2016-02-01

Nanodiamond (ND) layers on silicon substrate are deposited by the pulsed spray technique starting from nanoparticles of about 250 nm dispersed in 1,2-dichloroethane solvent. The aim of this letter is to investigate the quantum efficiency (QE) of photocathodes based on ND particles in the vacuum ultraviolet spectral range. Various ND layers are examined employing as-received and hydrogenated nanoparticles. As expected, the hydrogen plasma treatment improves strongly the photoemission of the layer giving a QE of 22% at 146 nm. Indeed, this efficiency value is achieved only if the particles are treated in H2 microwave plasma before the growth of the sprayed layer rather than to hydrogenate the already formed one. These QE values are higher than those of photocathodes based on plasma chemical vapor deposition diamond films, but with the advantage of being much stable, too. The highest QE values are explained to be due to the intrinsic chemical and structural features of utilized ND particles.

Mathematical morphology-based shape feature analysis for Chinese character recognition systems

NASA Astrophysics Data System (ADS)

Pai, Tun-Wen; Shyu, Keh-Hwa; Chen, Ling-Fan; Tai, Gwo-Chin

1995-04-01

This paper proposes an efficient technique of shape feature extraction based on the application of mathematical morphology theory. A new shape complexity index for preclassification of machine printed Chinese Character Recognition (CCR) is also proposed. For characters represented in different fonts/sizes or in a low resolution environment, a more stable local feature such as shape structure is preferred for character recognition. Morphological valley extraction filters are applied to extract the protrusive strokes from four sides of an input Chinese character. The number of extracted local strokes reflects the shape complexity of each side. These shape features of characters are encoded as corresponding shape complexity indices. Based on the shape complexity index, data base is able to be classified into 16 groups prior to recognition procedures. The performance of associating with shape feature analysis reclaims several characters from misrecognized character sets and results in an average of 3.3% improvement of recognition rate from an existing recognition system. In addition to enhance the recognition performance, the extracted stroke information can be further analyzed and classified its own stroke type. Therefore, the combination of extracted strokes from each side provides a means for data base clustering based on radical or subword components. It is one of the best solutions for recognizing high complexity characters such as Chinese characters which are divided into more than 200 different categories and consist more than 13,000 characters.

An investigation of time course of category and semantic priming.

PubMed

Ray, Suchismita

2008-04-01

Low semantically similar exemplars in a category demonstrate the category-priming effect through priming of the category (i.e., exemplar-category-exemplar), whereas high semantically similar exemplars in the same category demonstrate the semantic-priming effect (i.e., direct activation of one high semantically similar exemplar by another). The author asked whether the category- and semantic-priming effects are based on a common memory process. She examined this question by testing the time courses of category- and semantic-priming effects. She tested participants on either category- or semantic-priming paradigm at 2 different time intervals (6 min and 42 min) by using a lexical decision task using exemplars from categories. Results showed that the time course of category priming was different from that of semantic priming. The author concludes that these 2 priming effects are based on 2 separate memory processes.

QUANTITATIVE TESTS OF ELMS AS INTERMEDIATE N PEELING-BALLOONING MODES

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

LAO, LL; SNYDER, PB; LEONARD, AW

2002-07-01

OAK A271 QUANTITATIVE TESTS OF ELMS AS INTERMEDIATE N PEELING-BALLOONING MODES. Two of the major issues crucial for the design of the next generation tokamak burning plasma devices are the predictability of the edge pedestal height and control of the divertor heat load in H-mode configurations. Both of these are strongly impacted by edge localized modes (ELMs) and their size. A working model for ELMs is that they are intermediate toroidal mode number, n {approx} 5-30, peeling-ballooning modes driven by the large edge pedestal pressure gradient P{prime} and the associated large edge bootstrap current density J{sub BS}. the interplay betweenmore » P{prime} and J{sub BS} as a discharge evolves can excite peeling-ballooning modes over a wide spectrum of n. The pedestal current density plays a dual role by stabilizing the high n ballooning modes via opening access to second stability but providing free energy to drive the intermediate n peeling modes. This makes a systematic evaluation of this model particularly challenging. This paper describes recent quantitative tests of this model using experimental data from the DIII-D and the JT-60U tokamaks. These tests are made possible by recent improvements to the ELITE MHD stability code, which allow an efficient evaluation of the unstable peeling-ballooning modes, as well as by improvements to other diagnostic and analysis techniques. Some of the key testable features of this model are: (1) ELMs are triggered when the growth rates of intermediate n MHD modes become significantly large; (2) ELM sizes are related to the radial widths of the unstable modes; (3) the unstable modes have a strong ballooning character localized in the outboard bad curvature region; (4) at high collisionality, ELM size generally becomes smaller because J{sub BS} is reduced.« less

A Framework for Final Drive Simultaneous Failure Diagnosis Based on Fuzzy Entropy and Sparse Bayesian Extreme Learning Machine

PubMed Central

Ye, Qing; Pan, Hao; Liu, Changhua

2015-01-01

This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction module, adopt wavelet package transform and fuzzy entropy to reduce noise interference and extract representative features of failure mode. Use single failure sample to construct probability classifiers based on paired sparse Bayesian extreme learning machine which is trained only by single failure modes and have high generalization and sparsity of sparse Bayesian learning approach. To generate optimal decision threshold which can convert probability output obtained from classifiers into final simultaneous failure modes, this research proposes using samples containing both single and simultaneous failure modes and Grid search method which is superior to traditional techniques in global optimization. Compared with other frequently used diagnostic approaches based on support vector machine and probability neural networks, experiment results based on F 1-measure value verify that the diagnostic accuracy and efficiency of the proposed framework which are crucial for simultaneous failure diagnosis are superior to the existing approach. PMID:25722717

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

2018-04-01

Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

Men, Sex and Money in Recent Family Melodramas.

ERIC Educational Resources Information Center

Seiter, Ellen

1983-01-01

Today's melodramas reveal significant trends in terms of gender, class, and the nature of tribulations. This article surveys the dominant features of family melodramas including soap operas, prime time serials such as "Dallas" and "Dynasty," and theatrical feature films. (PD)

Affect of the unconscious: visually suppressed angry faces modulate our decisions.

PubMed

Almeida, Jorge; Pajtas, Petra E; Mahon, Bradford Z; Nakayama, Ken; Caramazza, Alfonso

2013-03-01

Emotional and affective processing imposes itself over cognitive processes and modulates our perception of the surrounding environment. In two experiments, we addressed the issue of whether nonconscious processing of affect can take place even under deep states of unawareness, such as those induced by interocular suppression techniques, and can elicit an affective response that can influence our understanding of the surrounding environment. In Experiment 1, participants judged the likeability of an unfamiliar item--a Chinese character--that was preceded by a face expressing a particular emotion (either happy or angry). The face was rendered invisible through an interocular suppression technique (continuous flash suppression; CFS). In Experiment 2, backward masking (BM), a less robust masking technique, was used to render the facial expressions invisible. We found that despite equivalent phenomenological suppression of the visual primes under CFS and BM, different patterns of affective processing were obtained with the two masking techniques. Under BM, nonconscious affective priming was obtained for both happy and angry invisible facial expressions. However, under CFS, nonconscious affective priming was obtained only for angry facial expressions. We discuss an interpretation of this dissociation between affective processing and visual masking techniques in terms of distinct routes from the retina to the amygdala.

Priming Processes in the Simon Task: More Evidence from the Lexical Decision Task for a Third Route in the Simon Effect

ERIC Educational Resources Information Center

Metzker, Manja; Dreisbach, Gesine

2011-01-01

Recently, it was proposed that the Simon effect would result not only from two interfering processes, as classical dual-route models assume, but from three processes. It was argued that priming from the spatial code to the nonspatial code might facilitate the identification of the nonspatial stimulus feature in congruent Simon trials. In the…

Target selection biases from recent experience transfer across effectors.

PubMed

Moher, Jeff; Song, Joo-Hyun

2016-02-01

Target selection is often biased by an observer's recent experiences. However, not much is known about whether these selection biases influence behavior across different effectors. For example, does looking at a red object make it easier to subsequently reach towards another red object? In the current study, we asked observers to find the uniquely colored target object on each trial. Randomly intermixed pre-trial cues indicated the mode of action: either an eye movement or a visually guided reach movement to the target. In Experiment 1, we found that priming of popout, reflected in faster responses following repetition of the target color on consecutive trials, occurred regardless of whether the effector was repeated from the previous trial or not. In Experiment 2, we examined whether an inhibitory selection bias away from a feature could transfer across effectors. While priming of popout reflects both enhancement of the repeated target features and suppression of the repeated distractor features, the distractor previewing effect isolates a purely inhibitory component of target selection in which a previewed color is presented in a homogenous display and subsequently inhibited. Much like priming of popout, intertrial suppression biases in the distractor previewing effect transferred across effectors. Together, these results suggest that biases for target selection driven by recent trial history transfer across effectors. This indicates that representations in memory that bias attention towards or away from specific features are largely independent from their associated actions.

Faster than classical quantum algorithm for dense formulas of exact satisfiability and occupation problems

NASA Astrophysics Data System (ADS)

Mandrà, Salvatore; Giacomo Guerreschi, Gian; Aspuru-Guzik, Alán

2016-07-01

We present an exact quantum algorithm for solving the Exact Satisfiability problem, which belongs to the important NP-complete complexity class. The algorithm is based on an intuitive approach that can be divided into two parts: the first step consists in the identification and efficient characterization of a restricted subspace that contains all the valid assignments of the Exact Satisfiability; while the second part performs a quantum search in such restricted subspace. The quantum algorithm can be used either to find a valid assignment (or to certify that no solution exists) or to count the total number of valid assignments. The query complexities for the worst-case are respectively bounded by O(\\sqrt{{2}n-{M\\prime }}) and O({2}n-{M\\prime }), where n is the number of variables and {M}\\prime the number of linearly independent clauses. Remarkably, the proposed quantum algorithm results to be faster than any known exact classical algorithm to solve dense formulas of Exact Satisfiability. As a concrete application, we provide the worst-case complexity for the Hamiltonian cycle problem obtained after mapping it to a suitable Occupation problem. Specifically, we show that the time complexity for the proposed quantum algorithm is bounded by O({2}n/4) for 3-regular undirected graphs, where n is the number of nodes. The same worst-case complexity holds for (3,3)-regular bipartite graphs. As a reference, the current best classical algorithm has a (worst-case) running time bounded by O({2}31n/96). Finally, when compared to heuristic techniques for Exact Satisfiability problems, the proposed quantum algorithm is faster than the classical WalkSAT and Adiabatic Quantum Optimization for random instances with a density of constraints close to the satisfiability threshold, the regime in which instances are typically the hardest to solve. The proposed quantum algorithm can be straightforwardly extended to the generalized version of the Exact Satisfiability known as Occupation problem. The general version of the algorithm is presented and analyzed.

A scale space feature based registration technique for fusion of satellite imagery

NASA Technical Reports Server (NTRS)

Raghavan, Srini; Cromp, Robert F.; Campbell, William C.

1997-01-01

Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.

Efficient three-dimensional resist profile-driven source mask optimization optical proximity correction based on Abbe-principal component analysis and Sylvester equation

NASA Astrophysics Data System (ADS)

Lin, Pei-Chun; Yu, Chun-Chang; Chen, Charlie Chung-Ping

2015-01-01

As one of the critical stages of a very large scale integration fabrication process, postexposure bake (PEB) plays a crucial role in determining the final three-dimensional (3-D) profiles and lessening the standing wave effects. However, the full 3-D chemically amplified resist simulation is not widely adopted during the postlayout optimization due to the long run-time and huge memory usage. An efficient simulation method is proposed to simulate the PEB while considering standing wave effects and resolution enhancement techniques, such as source mask optimization and subresolution assist features based on the Sylvester equation and Abbe-principal component analysis method. Simulation results show that our algorithm is 20× faster than the conventional Gaussian convolution method.

Investigation of KDP crystal surface based on an improved bidimensional empirical mode decomposition method

NASA Astrophysics Data System (ADS)

Lu, Lei; Yan, Jihong; Chen, Wanqun; An, Shi

2018-03-01

This paper proposed a novel spatial frequency analysis method for the investigation of potassium dihydrogen phosphate (KDP) crystal surface based on an improved bidimensional empirical mode decomposition (BEMD) method. Aiming to eliminate end effects of the BEMD method and improve the intrinsic mode functions (IMFs) for the efficient identification of texture features, a denoising process was embedded in the sifting iteration of BEMD method. With removing redundant information in decomposed sub-components of KDP crystal surface, middle spatial frequencies of the cutting and feeding processes were identified. Comparative study with the power spectral density method, two-dimensional wavelet transform (2D-WT), as well as the traditional BEMD method, demonstrated that the method developed in this paper can efficiently extract texture features and reveal gradient development of KDP crystal surface. Furthermore, the proposed method was a self-adaptive data driven technique without prior knowledge, which overcame shortcomings of the 2D-WT model such as the parameters selection. Additionally, the proposed method was a promising tool for the application of online monitoring and optimal control of precision machining process.

Effects of surface features on word-fragment completion in amnesic subjects.

PubMed

Kinoshita, S; Wayland, S V

1993-01-01

Patients with amnesia resulting from alcoholic Korsakoff syndrome and elderly control patients studied a list of words in two typographies (typed and handwritten) and then received a word-fragment completion test (e.g., -ys-e-y for mystery) in which the test cues also varied in typography. Unlike the elderly control patients, the amnesic patients did not show greater priming effect when the typography at test matched that at study. The amount of typography-dependent priming was positively correlated with the score on the Wechsler Memory Scale. These results suggest that the effects of typography change on repetition priming in word-fragment completion reflect explicit recollection, and that the representation that supports repetition priming effects observed with amnesic subjects in the word-fragment completion task does not code typography information.

Identity salience and the influence of differential activation of the social self-schema on advertising response.

PubMed

Forehand, Mark R; Deshpandé, Rohit; Reed, Americus

2002-12-01

The authors examined how identity primes and social distinctiveness influence identity salience (i.e., the activation of a social identity within an individual's social self-schema) and subsequent responses to targeted advertising. Across 2 studies, individuals who were exposed to an identity prime (an ad element that directs attention to the individual's social identity) and who were socially distinctive (minorities in the immediate social context) expressed systematically different evaluations of spokespersons and the advertisements that featured them. Specifically, Asian (Caucasian) participants responded most positively (negatively) to Asian spokespeople and Asian-targeted advertising when the participants were both primed and socially distinctive. No main effects of identity primes or social distinctiveness were found. The implications of these findings for identity theory, advertising practice, and intervention communications are discussed.

[Inhibition and resource capacity during normal aging: a confrontation of the dorsal-ventral and frontal models in a modified version of negative priming].

PubMed

Martin, S; Brouillet, D; Guerdoux, E; Tarrago, R

2006-01-01

Over the past decades, cognitive psychology contribution to our understanding of aging relies on two major perspectives, focusing on the selective impact of age on either cognitive multiple-systems or global factors of cognition: slowing, working memory and inhibition. In the latter, reduction in inhibitory control during aging (in its access, deletion or restraint functions) is associated with poorer performance on a variety of tasks referring to memory, comprehension or language [Hasher, Zacks and May (16)]. The attractiveness of inhibition as an explanatory factor results in part in the absence of negative priming during aging. Negative priming refers to the slow down of latencies when individuals have to respond to recently ignored informations, compared to unrelated informations. The dissociation, between a preserved location negative priming and an absence of identity negative priming during aging, supports the dorsal-ventral model of inhibition which suggests that spatial and identity inhibition are supported by different and independent visual pathways. An alternative model, directly at odds, is that inhibitory mechanisms are supported by the frontal lobe. In this perspective, inhibition is not a central process responsible for the control of working memory contents, but an automatic and local mechanism whose triggering depends on controlled attention. Therefore, working memory drives efficient inhibition by sustaining task instructions and appropriate responses throughout task execution. This hypothesis is consistent with Houghton and Tipper's (17) architecture of selective attention. According to the authors, the presence or absence of automatic inhibition is very closely linked to a Match/Mismatch field whose function is to compare the present stimulus to an internal self-generated internal template. When an information fails to match the subject's current goals, the match/mismatch field causes an automatic inhibitory imbalance which reduces the to-be-ignored properties' responsiveness. In contrast, information matching subjects' goal is enhanced through an automatic excitatory imbalance. The accurate functioning of the Match/Mismatch field requires efficient executive functioning responsible for the uphold of goals and correct responses. In the case of negative priming, manipulating the efficiency of working memory is of interest as it should affect the triggering of slowing, ie, an indirect inhibitory deficit, when the task is resource demanding [Conwayet al. (6)]. Moreover, if inhibition, as reflected by negative priming, is mediated by individual resource capacity, then NP should disappear during aging only when individuals are engaged in a resource-demanding task. To address this issue, we examine whether cognitive control load in a gender decision task contributed to the presence or absence of NP during aging. According to the dorsal-ventral model, task complexity should not have any impact on performance, since gender decision task relies on a conceptual analysis of information. In turn, the frontal model predicts that age differences in performance profile will only differ when individual resource capacity is overloaded. Sixty-four participants (32 young and 32 older adults) performed a gender categorisation task through two experiments. Trials involved two stimuli presented successively at the same location. A word served as a prime and a word as a target. Both prime and target could be male or female. When prime and target matched on gender, we talked about VALID pairs (or compatible). When prime and target mismatched on the manipulated features, we talked about INVALID pairs (or incompatible). Participants' task was to identify the gender of the target. They were explicitly instructed not to respond to primes but to read them silently. Our interest was in response latencies for valid versus invalid pairs. We manipulated task complexity by the absence (experiment 1) or presence (experiment 2) of a distractor during probe trials. For younger adults, primes presented before targets gave rise to behavioural costs when pairs were mapped to the same response compared to pairs that were mapped to opposite ones. This slowing, called Negative Compatibility Effect (NCE), was independent of the presence or absence of a distractor. NCE was reliable for the elderly patients only under condition of no interfering information during the probe trial: pattern of performance of older participants was identical to that of young adults (experiment 1). This effect disappeared as task complexity increased (experiment 2). This result suggests that NCE triggering is dependant on the amount of cognitive control engaged by the task, and therefore that the ability to inhibit irrelevant information is secondary to a general capacity of the working memory. The implications of our data are consistent with the level of processing account, as well as the recent neuroimaging contributions which suggest, for example, the involvement of the dorso-lateral prefrontal cortex (sensitive to aging) when task demands are high, and a ventro-lateral prefrontal implication when demands are low [see Eenshuistra et al. for a review (10)].

On the role of attention in generating explicit awareness of contingent relations: evidence from spatial priming.

PubMed

Fiacconi, Chris M; Milliken, Bruce

2011-12-01

In a series of four experiments, we examine the hypothesis that selective attention is crucial for the generation of conscious knowledge of contingency information. We investigated this question using a spatial priming task in which participants were required to localize a target letter in a probe display. In Experiment 1, participants kept track of the frequency with which the predictive letter in the prime appeared in various locations. This manipulation had a negligible impact on contingency awareness. Subsequent experiments requiring participants to attend to features (color, location) of the predictive letter increased contingency awareness somewhat, but there remained a large proportion of individuals who remained unaware of the strong contingency. Together the results of our experiments suggest that the construct of attention does not fully capture the processes that lead to contingency awareness, and suggest a critical role for bottom-up feature integration in explicit contingency learning. Copyright © 2011 Elsevier Inc. All rights reserved.

Double-hit mouse model of cigarette smoke priming for acute lung injury.

PubMed

Sakhatskyy, Pavlo; Wang, Zhengke; Borgas, Diana; Lomas-Neira, Joanne; Chen, Yaping; Ayala, Alfred; Rounds, Sharon; Lu, Qing

2017-01-01

Epidemiological studies indicate that cigarette smoking (CS) increases the risk and severity of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). The mechanism is not understood, at least in part because of lack of animal models that reproduce the key features of the CS priming process. In this study, using two strains of mice, we characterized a double-hit mouse model of ALI induced by CS priming of injury caused by lipopolysaccharide (LPS). C57BL/6 and AKR mice were preexposed to CS briefly (3 h) or subacutely (3 wk) before intratracheal instillation of LPS and ALI was assessed 18 h after LPS administration by measuring lung static compliance, lung edema, vascular permeability, inflammation, and alveolar apoptosis. We found that as little as 3 h of exposure to CS enhanced LPS-induced ALI in both strains of mice. Similar exacerbating effects were observed after 3 wk of preexposure to CS. However, there was a strain difference in susceptibility to CS priming for ALI, with a greater effect in AKR mice. The key features we observed suggest that 3 wk of CS preexposure of AKR mice is a reproducible, clinically relevant animal model that is useful for studying mechanisms and treatment of CS priming for a second-hit-induced ALI. Our data also support the concept that increased susceptibility to ALI/ARDS is an important adverse health consequence of CS exposure that needs to be taken into consideration when treating critically ill individuals.

Double-hit mouse model of cigarette smoke priming for acute lung injury

PubMed Central

Sakhatskyy, Pavlo; Wang, Zhengke; Borgas, Diana; Lomas-Neira, Joanne; Chen, Yaping; Ayala, Alfred; Rounds, Sharon

2016-01-01

Epidemiological studies indicate that cigarette smoking (CS) increases the risk and severity of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). The mechanism is not understood, at least in part because of lack of animal models that reproduce the key features of the CS priming process. In this study, using two strains of mice, we characterized a double-hit mouse model of ALI induced by CS priming of injury caused by lipopolysaccharide (LPS). C57BL/6 and AKR mice were preexposed to CS briefly (3 h) or subacutely (3 wk) before intratracheal instillation of LPS and ALI was assessed 18 h after LPS administration by measuring lung static compliance, lung edema, vascular permeability, inflammation, and alveolar apoptosis. We found that as little as 3 h of exposure to CS enhanced LPS-induced ALI in both strains of mice. Similar exacerbating effects were observed after 3 wk of preexposure to CS. However, there was a strain difference in susceptibility to CS priming for ALI, with a greater effect in AKR mice. The key features we observed suggest that 3 wk of CS preexposure of AKR mice is a reproducible, clinically relevant animal model that is useful for studying mechanisms and treatment of CS priming for a second-hit-induced ALI. Our data also support the concept that increased susceptibility to ALI/ARDS is an important adverse health consequence of CS exposure that needs to be taken into consideration when treating critically ill individuals. PMID:27864287

Unconscious Processing of Facial Emotional Valence Relation: Behavioral Evidence of Integration between Subliminally Perceived Stimuli.

PubMed

Liu, Chengzhen; Sun, Zhiyi; Jou, Jerwen; Cui, Qian; Zhao, Guang; Qiu, Jiang; Tu, Shen

2016-01-01

Although a few studies have investigated the integration between some types of unconscious stimuli, no research has yet explored the integration between unconscious emotional stimuli. This study was designed to provide behavioral evidence for the integration between unconsciously perceived emotional faces (same or different valence relation) using a modified priming paradigm. In two experiments, participants were asked to decide whether two faces in the target, which followed two subliminally presented faces of same or different emotional expressions, were of the same or different emotional valence. The interstimulus interval (ISI) between the prime and the target was manipulated (0, 53, 163 ms). In Experiment 1, prime visibility was assessed post-experiment. In Experiment 2, it was assessed on each trial. Interestingly, in both experiments, unconsciously processed valence relation of the two faces in the prime generated a negative priming effect in the response to the supraliminally presented target, independent of the length of ISI. Further analyses suggested that the negative priming was probably caused by a motor response incongruent relation between the subliminally perceived prime and the supraliminally perceived target. The visual feature incongruent relation across the prime and target was not found to play a role in the negative priming. Because the negative priming was found at short ISI, an attention mechanism as well as a motor inhibition mechanism were proposed in the generation of the negative priming effect. Overall, this study indicated that the subliminal valence relation was processed, and that integration between different unconsciously perceived stimuli could occur.

Unconscious Processing of Facial Emotional Valence Relation: Behavioral Evidence of Integration between Subliminally Perceived Stimuli

PubMed Central

Jou, Jerwen; Cui, Qian; Zhao, Guang; Qiu, Jiang; Tu, Shen

2016-01-01

Although a few studies have investigated the integration between some types of unconscious stimuli, no research has yet explored the integration between unconscious emotional stimuli. This study was designed to provide behavioral evidence for the integration between unconsciously perceived emotional faces (same or different valence relation) using a modified priming paradigm. In two experiments, participants were asked to decide whether two faces in the target, which followed two subliminally presented faces of same or different emotional expressions, were of the same or different emotional valence. The interstimulus interval (ISI) between the prime and the target was manipulated (0, 53, 163 ms). In Experiment 1, prime visibility was assessed post-experiment. In Experiment 2, it was assessed on each trial. Interestingly, in both experiments, unconsciously processed valence relation of the two faces in the prime generated a negative priming effect in the response to the supraliminally presented target, independent of the length of ISI. Further analyses suggested that the negative priming was probably caused by a motor response incongruent relation between the subliminally perceived prime and the supraliminally perceived target. The visual feature incongruent relation across the prime and target was not found to play a role in the negative priming. Because the negative priming was found at short ISI, an attention mechanism as well as a motor inhibition mechanism were proposed in the generation of the negative priming effect. Overall, this study indicated that the subliminal valence relation was processed, and that integration between different unconsciously perceived stimuli could occur. PMID:27622600

Efficient seeding and defragmentation of curvature streamlines for colonic polyp detection

NASA Astrophysics Data System (ADS)

Zhao, Lingxiao; Botha, Charl P.; Truyen, Roel; Vos, Frans M.; Post, Frits H.

2008-03-01

Many computer aided diagnosis (CAD) schemes have been developed for colon cancer detection using Virtual Colonoscopy (VC). In earlier work, we developed an automatic polyp detection method integrating flow visualization techniques, that forms part of the CAD functionality of an existing Virtual Colonoscopy pipeline. Curvature streamlines were used to characterize polyp surface shape. Features derived from curvature streamlines correlated highly with true polyp detections. During testing with a large number of patient data sets, we found that the correlation between streamline features and true polyps could be affected by noise and our streamline generation technique. The seeding and spacing constraints and CT noise could lead to streamline fragmentation, which reduced the discriminating power of our streamline features. In this paper, we present two major improvements of our curvature streamline generation. First, we adapted our streamline seeding strategy to the local surface properties and made the streamline generation faster. It generates a significantly smaller number of seeds but still results in a comparable and suitable streamline distribution. Second, based on our observation that longer streamlines are better surface shape descriptors, we improved our streamline tracing algorithm to produce longer streamlines. Our improved techniques are more effcient and also guide the streamline geometry to correspond better to colonic surface shape. These two adaptations support a robust and high correlation between our streamline features and true positive detections and lead to better polyp detection results.

Subliminal speech priming.

PubMed

Kouider, Sid; Dupoux, Emmanuel

2005-08-01

We present a novel subliminal priming technique that operates in the auditory modality. Masking is achieved by hiding a spoken word within a stream of time-compressed speechlike sounds with similar spectral characteristics. Participants were unable to consciously identify the hidden words, yet reliable repetition priming was found. This effect was unaffected by a change in the speaker's voice and remained restricted to lexical processing. The results show that the speech modality, like the written modality, involves the automatic extraction of abstract word-form representations that do not include nonlinguistic details. In both cases, priming operates at the level of discrete and abstract lexical entries and is little influenced by overlap in form or semantics.

An efficient CU partition algorithm for HEVC based on improved Sobel operator

NASA Astrophysics Data System (ADS)

Sun, Xuebin; Chen, Xiaodong; Xu, Yong; Sun, Gang; Yang, Yunsheng

2018-04-01

As the latest video coding standard, High Efficiency Video Coding (HEVC) achieves over 50% bit rate reduction with similar video quality compared with previous standards H.264/AVC. However, the higher compression efficiency is attained at the cost of significantly increasing computational load. In order to reduce the complexity, this paper proposes a fast coding unit (CU) partition technique to speed up the process. To detect the edge features of each CU, a more accurate improved Sobel filtering is developed and performed By analyzing the textural features of CU, an early CU splitting termination is proposed to decide whether a CU should be decomposed into four lower-dimensions CUs or not. Compared with the reference software HM16.7, experimental results indicate the proposed algorithm can lessen the encoding time up to 44.09% on average, with a negligible bit rate increase of 0.24%, and quality losses lower 0.03 dB, respectively. In addition, the proposed algorithm gets a better trade-off between complexity and rate-distortion among the other proposed works.

Real-time generation of infrared ocean scene based on GPU

NASA Astrophysics Data System (ADS)

Jiang, Zhaoyi; Wang, Xun; Lin, Yun; Jin, Jianqiu

2007-12-01

Infrared (IR) image synthesis for ocean scene has become more and more important nowadays, especially for remote sensing and military application. Although a number of works present ready-to-use simulations, those techniques cover only a few possible ways of water interacting with the environment. And the detail calculation of ocean temperature is rarely considered by previous investigators. With the advance of programmable features of graphic card, many algorithms previously limited to offline processing have become feasible for real-time usage. In this paper, we propose an efficient algorithm for real-time rendering of infrared ocean scene using the newest features of programmable graphics processors (GPU). It differs from previous works in three aspects: adaptive GPU-based ocean surface tessellation, sophisticated balance equation of thermal balance for ocean surface, and GPU-based rendering for infrared ocean scene. Finally some results of infrared image are shown, which are in good accordance with real images.

E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

NASA Technical Reports Server (NTRS)

Li, Winston; Leung, Henry; Kwan, Chiman; Linnell, Bruce R.

2005-01-01

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Ceria nanocubic-ultrasonication assisted dispersive liquid-liquid microextraction coupled with matrix assisted laser desorption/ionization mass spectrometry for pathogenic bacteria analysis.

PubMed

Abdelhamid, Hani Nasser; Bhaisare, Mukesh L; Wu, Hui-Fen

2014-03-01

A new ceria (CeO2) nanocubic modified surfactant is used as the basis of a novel nano-based microextraction technique for highly sensitive detection of pathogenic bacteria (Pseudomonas aeruginosa and Staphylococcus aureus). The technique uses ultrasound enhanced surfactant-assisted dispersive liquid-liquid microextraction (UESA-DLLME) with and without ceria (CeO2) followed by matrix assisted laser desorption/ionization mass spectrometry (MALDI-MS). In order to achieve high separation efficiency, we investigated the influential parameters, including extraction time of ultrasonication, type and volume of the extraction solvent and surfactant. Among various surfactants, the cationic surfactants can selectively offer better extraction efficiency on bacteria analysis than that of the anionic surfactants due to the negative charges of bacteria cell membranes. Extractions of the bacteria lysate from aqueous samples via UESA-DLLME-MALDI-MS were successfully achieved by using cetyltrimethyl ammonium bromide (CTAB, 10.0 µL, 1.0×10(-3) M) as surfactants in chlorobenzene (10.0 µL) and chloroform (10.0 µL) as the optimal extracting solvent for P. aeruginosa and S. aureus, respectively. Ceria nanocubic was synthesized, and functionalized with CTAB (CeO2@CTAB) and then characterized using transmission electron microscopy (TEM) and optical spectroscopy (UV and FTIR). CeO2@CTAB demonstrates high extraction efficiency, improve peaks ionization, and enhance resolution. The prime reasons for these improvements are due to the large surface area of nanoparticles, and its absorption that coincides with the wavelength of MALDI laser (337 nm, N2 laser). CeO2@CTAB-based microextraction offers lowest detectable concentrations tenfold lower than that of without nanoceria. The present approach has been successfully applied to detect pathogenic bacteria at low concentrations of 10(4)-10(5) cfu/mL (without ceria) and at 10(3)-10(4) cfu/mL (with ceria) from bacteria suspensions. Finally, the current approach was applied for analyzing the pathogenic bacteria in biological samples (blood and serum). Ceria assist surfactant (CeO2@CTAB) liquid-liquid microextraction (LLME) offers better extraction efficiency than that of using the surfactant in LLME alone. © 2013 Elsevier B.V. All rights reserved.

A hybrid LIBS-Raman system combined with chemometrics: an efficient tool for plastic identification and sorting.

PubMed

Shameem, K M Muhammed; Choudhari, Khoobaram S; Bankapur, Aseefhali; Kulkarni, Suresh D; Unnikrishnan, V K; George, Sajan D; Kartha, V B; Santhosh, C

2017-05-01

Classification of plastics is of great importance in the recycling industry as the littering of plastic wastes increases day by day as a result of its extensive use. In this paper, we demonstrate the efficacy of a combined laser-induced breakdown spectroscopy (LIBS)-Raman system for the rapid identification and classification of post-consumer plastics. The atomic information and molecular information of polyethylene terephthalate, polyethylene, polypropylene, and polystyrene were studied using plasma emission spectra and scattered signal obtained in the LIBS and Raman technique, respectively. The collected spectral features of the samples were analyzed using statistical tools (principal component analysis, Mahalanobis distance) to categorize the plastics. The analyses of the data clearly show that elemental information and molecular information obtained from these techniques are efficient for classification of plastics. In addition, the molecular information collected via Raman spectroscopy exhibits clearly distinct features for the transparent plastics (100% discrimination), whereas the LIBS technique shows better spectral feature differences for the colored samples. The study shows that the information obtained from these complementary techniques allows the complete classification of the plastic samples, irrespective of the color or additives. This work further throws some light on the fact that the potential limitations of any of these techniques for sample identification can be overcome by the complementarity of these two techniques. Graphical Abstract ᅟ.

Is nevtral NEUTRAL? Visual similarity effects in the early phases of written-word recognition.

PubMed

Marcet, Ana; Perea, Manuel

2017-08-01

For simplicity, contemporary models of written-word recognition and reading have unspecified feature/letter levels-they predict that the visually similar substituted-letter nonword PEQPLE is as effective at activating the word PEOPLE as the visually dissimilar substituted-letter nonword PEYPLE. Previous empirical evidence on the effects of visual similarly across letters during written-word recognition is scarce and nonconclusive. To examine whether visual similarity across letters plays a role early in word processing, we conducted two masked priming lexical decision experiments (stimulus-onset asynchrony = 50 ms). The substituted-letter primes were visually very similar to the target letters (u/v in Experiment 1 and i/j in Experiment 2; e.g., nevtral-NEUTRAL). For comparison purposes, we included an identity prime condition (neutral-NEUTRAL) and a dissimilar-letter prime condition (neztral-NEUTRAL). Results showed that the similar-letter prime condition produced faster word identification times than the dissimilar-letter prime condition. We discuss how models of written-word recognition should be amended to capture visual similarity effects across letters.

User-guided segmentation for volumetric retinal optical coherence tomography images

PubMed Central

Yin, Xin; Chao, Jennifer R.; Wang, Ruikang K.

2014-01-01

Abstract. Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method. PMID:25147962

User-guided segmentation for volumetric retinal optical coherence tomography images.

PubMed

Yin, Xin; Chao, Jennifer R; Wang, Ruikang K

2014-08-01

Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method.

Motor Priming in Neurorehabilitation

PubMed Central

Stoykov, Mary Ellen; Madhavan, Sangeetha

2014-01-01

Priming is a type of implicit learning wherein a stimulus prompts a change in behavior. Priming has been long studied in the field of psychology. More recently, rehabilitation researchers have studied motor priming as a possible way to facilitate motor learning. For example, priming of the motor cortex is associated with changes in neuroplasticity that are associated with improvements in motor performance. Of the numerous motor priming paradigms under investigation, only a few are practical for the current clinical environment, and the optimal priming modalities for specific clinical presentations are not known. Accordingly, developing an understanding of the various types of motor priming paradigms and their underlying neural mechanisms is an important step for therapists in neurorehabilitation. Most importantly, an understanding of the methods and their underlying mechanisms is essential for optimizing rehabilitation outcomes. The future of neurorehabilitation is likely to include these priming methods, which are delivered prior to or in conjunction with primary neurorehabilitation therapies. In this Special Interest article we discuss those priming paradigms that are supported by the greatest amount of evidence including: (i) stimulation-based priming, (ii) motor imagery and action observation, (iii) sensory priming, (iv) movement-based priming, and (v) pharmacological priming. PMID:25415551

The two-photon absorptivity of rotational transitions in the A2 Sigma hyperon + (v prime = O) - X-2 pion (v prime prime = O) gamma band of nitric oxide

NASA Technical Reports Server (NTRS)

Gross, K. P.; Mckenzie, R. L.

1982-01-01

A predominantly single-mode pulsed dye laser system giving a well characterized spatial and temporal output suitable for absolute two-photon absorptivity measurements was used to study the NO gamma(0,0) S11 + R21 (J double prime = 7-1/2) transition. Using a calibrated induced-fluorescence technique, an absorptivity parameter of 2.8 + or - 1.4 x 10 to the minus 51st power cm to the 6th power was obtained. Relative strengths of other rotational transitions in the gamma(0,0) band were also measured and shown to compare well with predicted values in all cases except the O12 (J double prime = 10-1/2) transition.

A Robust Linear Feature-Based Procedure for Automated Registration of Point Clouds

PubMed Central

Poreba, Martyna; Goulette, François

2015-01-01

With the variety of measurement techniques available on the market today, fusing multi-source complementary information into one dataset is a matter of great interest. Target-based, point-based and feature-based methods are some of the approaches used to place data in a common reference frame by estimating its corresponding transformation parameters. This paper proposes a new linear feature-based method to perform accurate registration of point clouds, either in 2D or 3D. A two-step fast algorithm called Robust Line Matching and Registration (RLMR), which combines coarse and fine registration, was developed. The initial estimate is found from a triplet of conjugate line pairs, selected by a RANSAC algorithm. Then, this transformation is refined using an iterative optimization algorithm. Conjugates of linear features are identified with respect to a similarity metric representing a line-to-line distance. The efficiency and robustness to noise of the proposed method are evaluated and discussed. The algorithm is valid and ensures valuable results when pre-aligned point clouds with the same scale are used. The studies show that the matching accuracy is at least 99.5%. The transformation parameters are also estimated correctly. The error in rotation is better than 2.8% full scale, while the translation error is less than 12.7%. PMID:25594589

Theory building, replication, and behavioral priming: where do we need to go from here?

PubMed

Locke, Edwin A

2015-05-01

This article suggests that the field of behavioral priming, which is basically a technique, is in need of theory building. Guidelines from successful theory building by induction in the realm of conscious motivation (namely, goal setting and self-efficacy) are suggested. The process would include replication with variation, identifying the logical relation between a given prime and the action in question, discovering moderators and mediators, and clarifying the relationship between the conscious mind and the subconscious. © The Author(s) 2015.

Subsurface damage distribution in the lapping process.

PubMed

Wang, Zhuo; Wu, Yulie; Dai, Yifan; Li, Shengyi

2008-04-01

To systematically investigate the influence of lapping parameters on subsurface damage (SSD) depth and characterize the damage feature comprehensively, maximum depth and distribution of SSD generated in the optical lapping process were measured with the magnetorheological finishing wedge technique. Then, an interaction of adjacent indentations was applied to interpret the generation of maximum depth of SSD. Eventually, the lapping procedure based on the influence of lapping parameters on the material removal rate and SSD depth was proposed to improve the lapping efficiency.

Current trends in geomorphological mapping

NASA Astrophysics Data System (ADS)

Seijmonsbergen, A. C.

2012-04-01

Geomorphological mapping is a world currently in motion, driven by technological advances and the availability of new high resolution data. As a consequence, classic (paper) geomorphological maps which were the standard for more than 50 years are rapidly being replaced by digital geomorphological information layers. This is witnessed by the following developments: 1. the conversion of classic paper maps into digital information layers, mainly performed in a digital mapping environment such as a Geographical Information System, 2. updating the location precision and the content of the converted maps, by adding more geomorphological details, taken from high resolution elevation data and/or high resolution image data, 3. (semi) automated extraction and classification of geomorphological features from digital elevation models, broadly separated into unsupervised and supervised classification techniques and 4. New digital visualization / cartographic techniques and reading interfaces. Newly digital geomorphological information layers can be based on manual digitization of polygons using DEMs and/or aerial photographs, or prepared through (semi) automated extraction and delineation of geomorphological features. DEMs are often used as basis to derive Land Surface Parameter information which is used as input for (un) supervised classification techniques. Especially when using high-res data, object-based classification is used as an alternative to traditional pixel-based classifications, to cluster grid cells into homogeneous objects, which can be classified as geomorphological features. Classic map content can also be used as training material for the supervised classification of geomorphological features. In the classification process, rule-based protocols, including expert-knowledge input, are used to map specific geomorphological features or entire landscapes. Current (semi) automated classification techniques are increasingly able to extract morphometric, hydrological, and in the near future also morphogenetic information. As a result, these new opportunities have changed the workflows for geomorphological mapmaking, and their focus have shifted from field-based techniques to using more computer-based techniques: for example, traditional pre-field air-photo based maps are now replaced by maps prepared in a digital mapping environment, and designated field visits using mobile GIS / digital mapping devices now focus on gathering location information and attribute inventories and are strongly time efficient. The resulting 'modern geomorphological maps' are digital collections of geomorphological information layers consisting of georeferenced vector, raster and tabular data which are stored in a digital environment such as a GIS geodatabase, and are easily visualized as e.g. 'birds' eye' views, as animated 3D displays, on virtual globes, or stored as GeoPDF maps in which georeferenced attribute information can be easily exchanged over the internet. Digital geomorphological information layers are increasingly accessed via web-based services distributed through remote servers. Information can be consulted - or even build using remote geoprocessing servers - by the end user. Therefore, it will not only be the geomorphologist anymore, but also the professional end user that dictates the applied use of digital geomorphological information layers.

Emotion recognition from EEG using higher order crossings.

PubMed

Petrantonakis, Panagiotis C; Hadjileontiadis, Leontios J

2010-03-01

Electroencephalogram (EEG)-based emotion recognition is a relatively new field in the affective computing area with challenging issues regarding the induction of the emotional states and the extraction of the features in order to achieve optimum classification performance. In this paper, a novel emotion evocation and EEG-based feature extraction technique is presented. In particular, the mirror neuron system concept was adapted to efficiently foster emotion induction by the process of imitation. In addition, higher order crossings (HOC) analysis was employed for the feature extraction scheme and a robust classification method, namely HOC-emotion classifier (HOC-EC), was implemented testing four different classifiers [quadratic discriminant analysis (QDA), k-nearest neighbor, Mahalanobis distance, and support vector machines (SVMs)], in order to accomplish efficient emotion recognition. Through a series of facial expression image projection, EEG data have been collected by 16 healthy subjects using only 3 EEG channels, namely Fp1, Fp2, and a bipolar channel of F3 and F4 positions according to 10-20 system. Two scenarios were examined using EEG data from a single-channel and from combined-channels, respectively. Compared with other feature extraction methods, HOC-EC appears to outperform them, achieving a 62.3% (using QDA) and 83.33% (using SVM) classification accuracy for the single-channel and combined-channel cases, respectively, differentiating among the six basic emotions, i.e., happiness, surprise, anger, fear, disgust, and sadness. As the emotion class-set reduces its dimension, the HOC-EC converges toward maximum classification rate (100% for five or less emotions), justifying the efficiency of the proposed approach. This could facilitate the integration of HOC-EC in human machine interfaces, such as pervasive healthcare systems, enhancing their affective character and providing information about the user's emotional status (e.g., identifying user's emotion experiences, recurring affective states, time-dependent emotional trends).

Feature Selection in Classification of Eye Movements Using Electrooculography for Activity Recognition

PubMed Central

Mala, S.; Latha, K.

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition. PMID:25574185

Feature selection in classification of eye movements using electrooculography for activity recognition.

PubMed

Mala, S; Latha, K

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition.

Apollo 16 prime and backup crewmen during geological field trip in New Mexico

NASA Image and Video Library

1971-09-09

Dr. Lee Silver (pointing foregroung), California Institute of Technology, calls a geological feature near Taos, New Mexico, to the attention of Apollo 16 prime and backup crewmen during a geological field trip. The crewmen, from left to right, are Astronauts Charles M. Duke Jr., lunar module pilot; Fred W. Haise Jr., backup commander; Edgar D. Mitchell, backup Lunar Module pilot; and John W. Young, commander.

Brain Potentials Highlight Stronger Implicit Food Memory for Taste than Health and Context Associations

PubMed Central

Hoogeveen, Heleen R.; ter Horst, Gert J.

2016-01-01

Increasingly consumption of healthy foods is advised to improve population health. Reasons people give for choosing one food over another suggest that non-sensory features like health aspects are appreciated as of lower importance than taste. However, many food choices are made in the absence of the actual perception of a food’s sensory properties, and therefore highly rely on previous experiences of similar consumptions stored in memory. In this study we assessed the differential strength of food associations implicitly stored in memory, using an associative priming paradigm. Participants (N = 30) were exposed to a forced-choice picture-categorization task, in which the food or non-food target images were primed with either non-sensory or sensory related words. We observed a smaller N400 amplitude at the parietal electrodes when categorizing food as compared to non-food images. While this effect was enhanced by the presentation of a food-related word prime during food trials, the primes had no effect in the non-food trials. More specifically, we found that sensory associations are stronger implicitly represented in memory as compared to non-sensory associations. Thus, this study highlights the neuronal mechanisms underlying previous observations that sensory associations are important features of food memory, and therefore a primary motive in food choice. PMID:27213567

egs_brachy: a versatile and fast Monte Carlo code for brachytherapy

NASA Astrophysics Data System (ADS)

Chamberland, Marc J. P.; Taylor, Randle E. P.; Rogers, D. W. O.; Thomson, Rowan M.

2016-12-01

egs_brachy is a versatile and fast Monte Carlo (MC) code for brachytherapy applications. It is based on the EGSnrc code system, enabling simulation of photons and electrons. Complex geometries are modelled using the EGSnrc C++ class library and egs_brachy includes a library of geometry models for many brachytherapy sources, in addition to eye plaques and applicators. Several simulation efficiency enhancing features are implemented in the code. egs_brachy is benchmarked by comparing TG-43 source parameters of three source models to previously published values. 3D dose distributions calculated with egs_brachy are also compared to ones obtained with the BrachyDose code. Well-defined simulations are used to characterize the effectiveness of many efficiency improving techniques, both as an indication of the usefulness of each technique and to find optimal strategies. Efficiencies and calculation times are characterized through single source simulations and simulations of idealized and typical treatments using various efficiency improving techniques. In general, egs_brachy shows agreement within uncertainties with previously published TG-43 source parameter values. 3D dose distributions from egs_brachy and BrachyDose agree at the sub-percent level. Efficiencies vary with radionuclide and source type, number of sources, phantom media, and voxel size. The combined effects of efficiency-improving techniques in egs_brachy lead to short calculation times: simulations approximating prostate and breast permanent implant (both with (2 mm)3 voxels) and eye plaque (with (1 mm)3 voxels) treatments take between 13 and 39 s, on a single 2.5 GHz Intel Xeon E5-2680 v3 processor core, to achieve 2% average statistical uncertainty on doses within the PTV. egs_brachy will be released as free and open source software to the research community.

egs_brachy: a versatile and fast Monte Carlo code for brachytherapy.

PubMed

Chamberland, Marc J P; Taylor, Randle E P; Rogers, D W O; Thomson, Rowan M

2016-12-07

egs_brachy is a versatile and fast Monte Carlo (MC) code for brachytherapy applications. It is based on the EGSnrc code system, enabling simulation of photons and electrons. Complex geometries are modelled using the EGSnrc C++ class library and egs_brachy includes a library of geometry models for many brachytherapy sources, in addition to eye plaques and applicators. Several simulation efficiency enhancing features are implemented in the code. egs_brachy is benchmarked by comparing TG-43 source parameters of three source models to previously published values. 3D dose distributions calculated with egs_brachy are also compared to ones obtained with the BrachyDose code. Well-defined simulations are used to characterize the effectiveness of many efficiency improving techniques, both as an indication of the usefulness of each technique and to find optimal strategies. Efficiencies and calculation times are characterized through single source simulations and simulations of idealized and typical treatments using various efficiency improving techniques. In general, egs_brachy shows agreement within uncertainties with previously published TG-43 source parameter values. 3D dose distributions from egs_brachy and BrachyDose agree at the sub-percent level. Efficiencies vary with radionuclide and source type, number of sources, phantom media, and voxel size. The combined effects of efficiency-improving techniques in egs_brachy lead to short calculation times: simulations approximating prostate and breast permanent implant (both with (2 mm) 3 voxels) and eye plaque (with (1 mm) 3 voxels) treatments take between 13 and 39 s, on a single 2.5 GHz Intel Xeon E5-2680 v3 processor core, to achieve 2% average statistical uncertainty on doses within the PTV. egs_brachy will be released as free and open source software to the research community.

Investigating Flow Features Near Abrupt Topography in the Mariana Basin

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Investigating Flow Features Near Abrupt Topography in...waves generated by flow over topography and mesoscale eddies generated by flow past islands. Having identified the prime locations in the region for such

Interference and negative priming effects in adolescents with attention deficit hyperactivity disorder.

PubMed

Pritchard, Verena E; Neumann, Ewald; Rucklidge, Julia J

2007-01-01

Three visual selective attention tasks were used to measure potential differences in susceptibility to interference and inhibitory cognitive control processes in 16 adolescents diagnosed with attention deficit hyperactivity disorder (ADHD) and 45 similar-aged controls. Susceptibility to interference was assessed using the Stroop color and word naming test. Efficiency of distractor inhibition was assessed in two conceptual negative priming tasks. The majority of studies in this area indicate that people with ADHD demonstrate higher levels of interference and lower negative priming effects in comparison with age-matched peers. However, we found that although the ADHD group was consistently slower to name target stimuli than the control group, there were no differences in interference or negative priming between the two groups.

Efficient image enhancement using sparse source separation in the Retinex theory

NASA Astrophysics Data System (ADS)

Yoon, Jongsu; Choi, Jangwon; Choe, Yoonsik

2017-11-01

Color constancy is the feature of the human vision system (HVS) that ensures the relative constancy of the perceived color of objects under varying illumination conditions. The Retinex theory of machine vision systems is based on the HVS. Among Retinex algorithms, the physics-based algorithms are efficient; however, they generally do not satisfy the local characteristics of the original Retinex theory because they eliminate global illumination from their optimization. We apply the sparse source separation technique to the Retinex theory to present a physics-based algorithm that satisfies the locality characteristic of the original Retinex theory. Previous Retinex algorithms have limited use in image enhancement because the total variation Retinex results in an overly enhanced image and the sparse source separation Retinex cannot completely restore the original image. In contrast, our proposed method preserves the image edge and can very nearly replicate the original image without any special operation.

A survey on evolutionary algorithm based hybrid intelligence in bioinformatics.

PubMed

Li, Shan; Kang, Liying; Zhao, Xing-Ming

2014-01-01

With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

The Effect of Self-Referential Expectation on Emotional Face Processing

PubMed Central

McKendrick, Mel; Butler, Stephen H.; Grealy, Madeleine A.

2016-01-01

The role of self-relevance has been somewhat neglected in static face processing paradigms but may be important in understanding how emotional faces impact on attention, cognition and affect. The aim of the current study was to investigate the effect of self-relevant primes on processing emotional composite faces. Sentence primes created an expectation of the emotion of the face before sad, happy, neutral or composite face photos were viewed. Eye movements were recorded and subsequent responses measured the cognitive and affective impact of the emotion expressed. Results indicated that primes did not guide attention, but impacted on judgments of valence intensity and self-esteem ratings. Negative self-relevant primes led to the most negative self-esteem ratings, although the effect of the prime was qualified by salient facial features. Self-relevant expectations about the emotion of a face and subsequent attention to a face that is congruent with these expectations strengthened the affective impact of viewing the face. PMID:27175487

The Effect of Self-Referential Expectation on Emotional Face Processing.

PubMed

McKendrick, Mel; Butler, Stephen H; Grealy, Madeleine A

2016-01-01

The role of self-relevance has been somewhat neglected in static face processing paradigms but may be important in understanding how emotional faces impact on attention, cognition and affect. The aim of the current study was to investigate the effect of self-relevant primes on processing emotional composite faces. Sentence primes created an expectation of the emotion of the face before sad, happy, neutral or composite face photos were viewed. Eye movements were recorded and subsequent responses measured the cognitive and affective impact of the emotion expressed. Results indicated that primes did not guide attention, but impacted on judgments of valence intensity and self-esteem ratings. Negative self-relevant primes led to the most negative self-esteem ratings, although the effect of the prime was qualified by salient facial features. Self-relevant expectations about the emotion of a face and subsequent attention to a face that is congruent with these expectations strengthened the affective impact of viewing the face.

Space Place Prime

NASA Technical Reports Server (NTRS)

Fitzpatrick, Austin J.; Novati, Alexander; Fisher, Diane K.; Leon, Nancy J.; Netting, Ruth

2013-01-01

Space Place Prime is public engagement and education software for use on iPad. It targets a multi-generational audience with news, images, videos, and educational articles from the Space Place Web site and other NASA sources. New content is downloaded daily (or whenever the user accesses the app) via the wireless connection. In addition to the Space Place Web site, several NASA RSS feeds are tapped to provide new content. Content is retained for the previous several days, or some number of editions of each feed. All content is controlled on the server side, so features about the latest news, or changes to any content, can be made without updating the app in the Apple Store. It gathers many popular NASA features into one app. The interface is a boundless, slidable- in-any-direction grid of images, unique for each feature, and iconized as image, video, or article. A tap opens the feature. An alternate list mode presents menus of images, videos, and articles separately. Favorites can be tagged for permanent archive. Face - book, Twitter, and e-mail connections make any feature shareable.

Factorization-based texture segmentation

DOE PAGES

Yuan, Jiangye; Wang, Deliang; Cheriyadat, Anil M.

2015-06-17

This study introduces a factorization-based approach that efficiently segments textured images. We use local spectral histograms as features, and construct an M × N feature matrix using M-dimensional feature vectors in an N-pixel image. Based on the observation that each feature can be approximated by a linear combination of several representative features, we factor the feature matrix into two matrices-one consisting of the representative features and the other containing the weights of representative features at each pixel used for linear combination. The factorization method is based on singular value decomposition and nonnegative matrix factorization. The method uses local spectral histogramsmore » to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries. Finally, the experiments conducted on public segmentation data sets show the promise of this simple yet powerful approach.« less

Marker Registration Technique for Handwritten Text Marker in Augmented Reality Applications

NASA Astrophysics Data System (ADS)

Thanaborvornwiwat, N.; Patanukhom, K.

2018-04-01

Marker registration is a fundamental process to estimate camera poses in marker-based Augmented Reality (AR) systems. We developed AR system that creates correspondence virtual objects on handwritten text markers. This paper presents a new method for registration that is robust for low-content text markers, variation of camera poses, and variation of handwritten styles. The proposed method uses Maximally Stable Extremal Regions (MSER) and polygon simplification for a feature point extraction. The experiment shows that we need to extract only five feature points per image which can provide the best registration results. An exhaustive search is used to find the best matching pattern of the feature points in two images. We also compared performance of the proposed method to some existing registration methods and found that the proposed method can provide better accuracy and time efficiency.

Attention and implicit memory: priming-induced benefits and costs have distinct attentional requirements.

PubMed

Keane, Margaret M; Cruz, Matt E; Verfaellie, Mieke

2015-02-01

Attention at encoding plays a critical and ubiquitous role in explicit memory performance, but its role in implicit memory performance (i.e., priming) is more variable: some, but not all, priming effects are reduced by division of attention at encoding. A wealth of empirical and theoretical work has aimed to define the critical features of priming effects that do or do not require attention at encoding. This work, however, has focused exclusively on priming effects that are beneficial in nature (wherein performance is enhanced by prior exposure to task stimuli), and has overlooked priming effects that are costly in nature (wherein performance is harmed by prior exposure to task stimuli). The present study takes up this question by examining the effect of divided attention on priming-induced costs and benefits in a speeded picture-naming task. Experiment 1 shows that the costs, but not the benefits, are eliminated by division of attention at encoding. Experiment 2 shows that the costs (as well as the benefits) in this task are intact in amnesic participants, demonstrating that the elimination of the cost in the divided attention condition in Experiment 1 was not an artifact of the reduced availability of explicit memory in that condition. We suggest that the differential role of attention in priming-induced performance costs and benefits is linked to differences in response competition associated with these effects. This interpretation situates the present findings within a theoretical framework that has been applied to a broad range of facilitatory priming effects.

Priming within and across modalities: exploring the nature of rCBF increases and decreases.

PubMed

Badgaiyan, R D; Schacter, D L; Alpert, N M

2001-02-01

Neuroimaging studies suggest that within-modality priming is associated with reduced regional cerebral blood flow (rCBF) in the extrastriate area, whereas cross-modality priming is associated with increased rCBF in prefrontal cortex. To characterize the nature of rCBF changes in within- and cross-modality priming, we conducted two neuroimaging experiments using positron emission tomography (PET). In experiment 1, rCBF changes in within-modality auditory priming on a word stem completion task were observed under same- and different-voice conditions. Both conditions were associated with decreased rCBF in extrastriate cortex. In the different-voice condition there were additional rCBF changes in the middle temporal gyrus and prefrontal cortex. Results suggest that the extrastriate involvement in within-modality priming is sensitive to a change in sensory modality of target stimuli between study and test, but not to a change in the feature of a stimulus within the same modality. In experiment 2, we studied cross-modality priming on a visual stem completion test after encoding under full- and divided-attention conditions. Increased rCBF in the anterior prefrontal cortex was observed in the full- but not in the divided-attention condition. Because explicit retrieval is compromised after encoding under the divided-attention condition, prefrontal involvement in cross-modality priming indicates recruitment of an aspect of explicit retrieval mechanism. The aspect of explicit retrieval that is most likely to be involved in cross-modality priming is the familiarity effect. Copyright 2001 Academic Press.

Device reflectivity as a simple rule for predicting the suitability of scattering foils for improved OLED light extraction

NASA Astrophysics Data System (ADS)

Levell, Jack W.; Harkema, Stephan; Pendyala, Raghu K.; Rensing, Peter A.; Senes, Alessia; Bollen, Dirk; MacKerron, Duncan; Wilson, Joanne S.

2013-09-01

A general challenge in Organic Light Emitting Diodes (OLEDs) is to extract the light efficiently from waveguided modes within the device structure. This can be accomplished by applying an additional scattering layer to the substrate which results in outcoupling increases between 0% to <100% in external quantum efficiency. In this work, we aim to address this large variation and show that the reflectivity of the OLED is a simple and useful predictor of the efficiency of substrate scattering techniques without the need for detailed modeling. We show that by optimizing the cathode and anode structure of glass based OLEDs by using silver and an ITO free high conductive Agfa Orgacon™ PEDOT:PSS we are able to increase the external quantum efficiency of OLEDs with the same outcoupling substrates from 2.4% to 5.6%, an increase of 130%. In addition, Holst Centre and partners are developing flexible substrates with integrated light extraction features and roll to roll compatible processing techniques to enable this next step in OLED development both for lighting and display applications. These devices show promise as they are shatterproof substrates and facilitate low cost manufacture.

Tactics, Techniques, and Procedures (TTP) for Migrant Camp Operations

DTIC Science & Technology

1995-04-15

interchangeable and, therefore, usually do not degrade a combat unit if tasked to deploy independently. Also, the Air Force frequently tasks composite...Prime BEEF teams from multiple bases rather than degrade a combat unit’s capabilities. (2) Horizontal construction capabilities, usually airfield or...special understanding and sympathy. They should receive all necessary assistance, and they should not be subject to cruel , inhumane, or degrading

DDC 10 Year Requirements and Planning Study. Interagency Survey Report

DTIC Science & Technology

1975-12-12

RDT&E Management Information Services Traditional bibliographic information storage and retrieval techniques are insufficienL for satisfaction of...a private source. 3.3 Economics and Marketing ERDA’s tradition of absorbing costs for information 1rocessing shows no indication of changing...Libraries. Its products, in addition to traditional library services, include three prime data bases: 0 MEDLINE - journal citations and subject

Improved image retrieval based on fuzzy colour feature vector

NASA Astrophysics Data System (ADS)

Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

2013-03-01

One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

Being forward not backward: lexical limits to masked priming.

PubMed

Davis, Chris; Kim, Jeesun; Forster, Kenneth I

2008-05-01

This study investigated whether masked priming is mediated by existing memory representations by determining whether nonwords targets would show repetition priming. To avoid the potential confound that nonword repetition priming would be obscured by a familiarity response bias, the standard lexical decision and naming tasks were modified to make targets unfamiliar. Participants were required to read a target string from right to left (i.e., "ECAF" should be read as "FACE") and then make a response. To examine if priming was based on lexical representations, repetition primes consisted of words when read forwards or backwards (e.g., "face", "ecaf") and nonwords (e.g., "pame", "emap"). Forward and backward primes were used to test if task instruction affected prime encoding. The lexical decision and naming tasks showed the same pattern of results: priming only occurred for forward primes with word targets (e.g., "face-ECAF"). Additional experiments to test if response priming affected the LDT indicated that the lexical status of the prime per se did not affect target responses. These results showed that the encoding of masked primes was unaffected by the novel task instruction and support the view that masked priming is due to the automatic triggering of pre-established computational processes based on stored information.

On the automatic activation of attitudes: a quarter century of evaluative priming research.

PubMed

Herring, David R; White, Katherine R; Jabeen, Linsa N; Hinojos, Michelle; Terrazas, Gabriela; Reyes, Stephanie M; Taylor, Jennifer H; Crites, Stephen L

2013-09-01

Evaluation is a fundamental concept in psychological science. Limitations of self-report measures of evaluation led to an explosion of research on implicit measures of evaluation. One of the oldest and most frequently used implicit measurement paradigms is the evaluative priming paradigm developed by Fazio, Sanbonmatsu, Powell, and Kardes (1986). This paradigm has received extensive attention in psychology and is used to investigate numerous phenomena ranging from prejudice to depression. The current review provides a meta-analysis of a quarter century of evaluative priming research: 73 studies yielding 125 independent effect sizes from 5,367 participants. Because judgments people make in evaluative priming paradigms can be used to tease apart underlying processes, this meta-analysis examined the impact of different judgments to test the classic encoding and response perspectives of evaluative priming. As expected, evidence for automatic evaluation was found, but the results did not exclusively support either of the classic perspectives. Results suggest that both encoding and response processes likely contribute to evaluative priming but are more nuanced than initially conceptualized by the classic perspectives. Additionally, there were a number of unexpected findings that influenced evaluative priming such as segmenting trials into discrete blocks. We argue that many of the findings of this meta-analysis can be explained with 2 recent evaluative priming perspectives: the attentional sensitization/feature-specific attention allocation and evaluation window perspectives. (c) 2013 APA, all rights reserved.

Activation of response force by self-splitting objects: where are the limits of feedforward Gestalt processing?

PubMed

Schmidt, Filipp; Weber, Andreas; Schmidt, Thomas

2014-08-21

Most objects can be recognized easily even when they are partly occluded. This also holds when several overlapping objects share the same surface features (self-splitting objects) which is an illustration of the grouping principle of Good Gestalt. We employed outline and filled contour stimuli in a primed flanker task to test whether the processing of self-splitting objects is in accordance with a simple feedforward model. We obtained priming effects in response time and response force for both types of stimuli, even when increasing the number of occluders up to three. The results for outline contours were in full accordance with a feedforward account. This was not the case for the results for filled contours (i.e., for self-splitting objects), especially under conditions of strong occlusion. We conclude that the implementation of the Good Gestalt principle is fast but still based on recurrent processing. © 2014 ARVO.

Mapping accuracy via spectrally and structurally based filtering techniques: comparisons through visual observations

NASA Astrophysics Data System (ADS)

Chockalingam, Letchumanan

2005-01-01

The data of Gunung Ledang region of Malaysia acquired through LANDSAT are considered to map certain hydrogeolocial features. To map these significant features, image-processing tools such as contrast enhancement, edge detection techniques are employed. The advantages of these techniques over the other methods are evaluated from the point of their validity in properly isolating features of hydrogeolocial interest are discussed. As these techniques take the advantage of spectral aspects of the images, these techniques have several limitations to meet the objectives. To discuss these limitations, a morphological transformation, which generally considers the structural aspects rather than spectral aspects from the image, are applied to provide comparisons between the results derived from spectral based and the structural based filtering techniques.

Is Neocortical-Hippocampal Connectivity a Better Predictor of Subsequent Recollection than Local Increases in Hippocampal Activity? New Insights on the Role of Priming

ERIC Educational Resources Information Center

Gagnepain, Pierre; Henson, Richard; Chetelat, Gael; Desgranges, Beatrice; Lebreton, Karine; Eustache, Francis

2011-01-01

During memory encoding, increased hippocampal activity--thought to reflect the binding of different types of information into unique episodes--has been shown to correlate with subsequent recollection of those episodes. Repetition priming--thought to induce more efficient perceptual processing of stimuli--is normally associated with decreased…

Novel techniques for data decomposition and load balancing for parallel processing of vision systems: Implementation and evaluation using a motion estimation system

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Computer vision systems employ a sequence of vision algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute such systems exhibit vastly different computational characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. However, since the input data for a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing. Presented here are algorithms for a motion estimation system. The motion estimation is based on the point correspondence between the involved images which are a sequence of stereo image pairs. Researchers propose algorithms to obtain point correspondences by matching feature points among stereo image pairs at any two consecutive time instants. Furthermore, the proposed algorithms employ non-iterative procedures, which results in saving considerable amounts of computation time. The system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from consecutive time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters.

Different effects of religion and God on prosociality with the ingroup and outgroup.

PubMed

Preston, Jesse Lee; Ritter, Ryan S

2013-11-01

Recent studies have found that activating religious cognition by priming techniques can enhance prosocial behavior, arguably because religious concepts carry prosocial associations. But many of these studies have primed multiple concepts simultaneously related to the sacred. We argue here that religion and God are distinct concepts that activate distinct associations. In particular, we examine the effect of God and religion on prosociality toward the ingroup and outgroup. In three studies, we found that religion primes enhanced prosociality toward ingroup members, consistent with ingroup affiliation, whereas, God primes enhanced prosociality toward outgroup member, consistent with concerns of moral impression management. Implications for theory and methodology in religious cognition are discussed.

Robust Feature Selection Technique using Rank Aggregation.

PubMed

Sarkar, Chandrima; Cooley, Sarah; Srivastava, Jaideep

2014-01-01

Although feature selection is a well-developed research area, there is an ongoing need to develop methods to make classifiers more efficient. One important challenge is the lack of a universal feature selection technique which produces similar outcomes with all types of classifiers. This is because all feature selection techniques have individual statistical biases while classifiers exploit different statistical properties of data for evaluation. In numerous situations this can put researchers into dilemma as to which feature selection method and a classifiers to choose from a vast range of choices. In this paper, we propose a technique that aggregates the consensus properties of various feature selection methods to develop a more optimal solution. The ensemble nature of our technique makes it more robust across various classifiers. In other words, it is stable towards achieving similar and ideally higher classification accuracy across a wide variety of classifiers. We quantify this concept of robustness with a measure known as the Robustness Index (RI). We perform an extensive empirical evaluation of our technique on eight data sets with different dimensions including Arrythmia, Lung Cancer, Madelon, mfeat-fourier, internet-ads, Leukemia-3c and Embryonal Tumor and a real world data set namely Acute Myeloid Leukemia (AML). We demonstrate not only that our algorithm is more robust, but also that compared to other techniques our algorithm improves the classification accuracy by approximately 3-4% (in data set with less than 500 features) and by more than 5% (in data set with more than 500 features), across a wide range of classifiers.

A monolithic Lagrangian approach for fluid-structure interaction problems

NASA Astrophysics Data System (ADS)

Ryzhakov, P. B.; Rossi, R.; Idelsohn, S. R.; Oñate, E.

2010-11-01

Current work presents a monolithic method for the solution of fluid-structure interaction problems involving flexible structures and free-surface flows. The technique presented is based upon the utilization of a Lagrangian description for both the fluid and the structure. A linear displacement-pressure interpolation pair is used for the fluid whereas the structure utilizes a standard displacement-based formulation. A slight fluid compressibility is assumed that allows to relate the mechanical pressure to the local volume variation. The method described features a global pressure condensation which in turn enables the definition of a purely displacement-based linear system of equations. A matrix-free technique is used for the solution of such linear system, leading to an efficient implementation. The result is a robust method which allows dealing with FSI problems involving arbitrary variations in the shape of the fluid domain. The method is completely free of spurious added-mass effects.

A modified active appearance model based on an adaptive artificial bee colony.

PubMed

Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali

2014-01-01

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.

Nonideal ultrathin mantle cloak for electrically large conducting cylinders.

PubMed

Liu, Shuo; Zhang, Hao Chi; Xu, He-Xiu; Cui, Tie Jun

2014-09-01

Based on the concept of the scattering cancellation technique, we propose a nonideal ultrathin mantle cloak that can efficiently suppress the total scattering cross sections of an electrically large conducting cylinder (over one free-space wavelength). The cloaking mechanism is investigated in depth based on the Mie scattering theory and is simultaneously interpreted from the perspective of far-field bistatic scattering and near-field distributions. We remark that, unlike the perfect transformation-optics-based cloak, this nonideal cloaking technique is mainly designed to minimize simultaneously several scattering multipoles of a relatively large geometry around considerably broad bandwidth. Numerical simulations and experimental results show that the antiscattering ability of the metasurface gives rise to excellent total scattering reduction of the electrically large cylinder and remarkable electric-field restoration around the cloak. The outstanding cloaking performance together with the good features of and ultralow profile, flexibility, and easy fabrication predict promising applications in the microwave frequencies.

Progress in diode-pumped alexandrite lasers as a new resource for future space lidar missions

NASA Astrophysics Data System (ADS)

Damzen, M. J.; Thomas, G. M.; Teppitaksak, A.; Minassian, A.

2017-11-01

Satellite-based remote sensing using laser-based lidar techniques provides a powerful tool for global 3-D mapping of atmospheric species (e.g. CO2, ozone, clouds, aerosols), physical attributes of the atmosphere (e.g. temperature, wind speed), and spectral indicators of Earth features (e.g. vegetation, water). Such information provides a valuable source for weather prediction, understanding of climate change, atmospheric science and health of the Earth eco-system. Similarly, laser-based altimetry can provide high precision ground topography mapping and more complex 3-D mapping (e.g. canopy height profiling). The lidar technique requires use of cutting-edge laser technologies and engineered designs that are capable of enduring the space environment over the mission lifetime. The laser must operate with suitably high electrical-to-optical efficiency and risk reduction strategy adopted to mitigate against laser failure or excessive operational degradation of laser performance.

New bandwidth selection criterion for Kernel PCA: approach to dimensionality reduction and classification problems.

PubMed

Thomas, Minta; De Brabanter, Kris; De Moor, Bart

2014-05-10

DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history of almost a decade. Disease class predictors can be designed for known disease cases and provide diagnostic confirmation or clarify abnormal cases. The main input to this class predictors are high dimensional data with many variables and few observations. Dimensionality reduction of these features set significantly speeds up the prediction task. Feature selection and feature transformation methods are well known preprocessing steps in the field of bioinformatics. Several prediction tools are available based on these techniques. Studies show that a well tuned Kernel PCA (KPCA) is an efficient preprocessing step for dimensionality reduction, but the available bandwidth selection method for KPCA was computationally expensive. In this paper, we propose a new data-driven bandwidth selection criterion for KPCA, which is related to least squares cross-validation for kernel density estimation. We propose a new prediction model with a well tuned KPCA and Least Squares Support Vector Machine (LS-SVM). We estimate the accuracy of the newly proposed model based on 9 case studies. Then, we compare its performances (in terms of test set Area Under the ROC Curve (AUC) and computational time) with other well known techniques such as whole data set + LS-SVM, PCA + LS-SVM, t-test + LS-SVM, Prediction Analysis of Microarrays (PAM) and Least Absolute Shrinkage and Selection Operator (Lasso). Finally, we assess the performance of the proposed strategy with an existing KPCA parameter tuning algorithm by means of two additional case studies. We propose, evaluate, and compare several mathematical/statistical techniques, which apply feature transformation/selection for subsequent classification, and consider its application in medical diagnostics. Both feature selection and feature transformation perform well on classification tasks. Due to the dynamic selection property of feature selection, it is hard to define significant features for the classifier, which predicts classes of future samples. Moreover, the proposed strategy enjoys a distinctive advantage with its relatively lesser time complexity.

Structural Priming in Spanish as Evidence of Implicit Learning

ERIC Educational Resources Information Center

Gámez, Perla B.; Shimpi, Priya M.

2016-01-01

This study uses a structural priming technique with young Spanish speakers to test whether exposure to a rare syntactic form in Spanish ("fue"-passive) would increase the production and comprehension of that form. In Study 1, 14 six-year-old Spanish speakers described pictures of transitive scenes. This baseline study revealed that…

Unconscious Semantic Activation Depends on Feature-Specific Attention Allocation

ERIC Educational Resources Information Center

Spruyt, Adriaan; De Houwer, Jan; Everaert, Tom; Hermans, Dirk

2012-01-01

We examined whether semantic activation by subliminally presented stimuli is dependent upon the extent to which participants assign attention to specific semantic stimulus features and stimulus dimensions. Participants pronounced visible target words that were preceded by briefly presented, masked prime words. Both affective and non-affective…

Affect of the unconscious: Visually suppressed angry faces modulate our decisions

PubMed Central

Pajtas, Petra E.; Mahon, Bradford Z.; Nakayama, Ken; Caramazza, Alfonso

2016-01-01

Emotional and affective processing imposes itself over cognitive processes and modulates our perception of the surrounding environment. In two experiments, we addressed the issue of whether nonconscious processing of affect can take place even under deep states of unawareness, such as those induced by interocular suppression techniques, and can elicit an affective response that can influence our understanding of the surrounding environment. In Experiment 1, participants judged the likeability of an unfamiliar item—a Chinese character—that was preceded by a face expressing a particular emotion (either happy or angry). The face was rendered invisible through an interocular suppression technique (continuous flash suppression; CFS). In Experiment 2, backward masking (BM), a less robust masking technique, was used to render the facial expressions invisible. We found that despite equivalent phenomenological suppression of the visual primes under CFS and BM, different patterns of affective processing were obtained with the two masking techniques. Under BM, nonconscious affective priming was obtained for both happy and angry invisible facial expressions. However, under CFS, nonconscious affective priming was obtained only for angry facial expressions. We discuss an interpretation of this dissociation between affective processing and visual masking techniques in terms of distinct routes from the retina to the amygdala. PMID:23224765

Carrier priming or suppression: understanding carrier priming enhancement of anti-polysaccharide antibody response to conjugate vaccines.

PubMed

Pobre, Karl; Tashani, Mohamed; Ridda, Iman; Rashid, Harunor; Wong, Melanie; Booy, Robert

2014-03-14

With the availability of newer conjugate vaccines, immunization schedules have become increasingly complex due to the potential for unpredictable immunologic interference such as 'carrier priming' and 'carrier induced epitopic suppression'. Carrier priming refers to an augmented antibody response to a carbohydrate portion of a glycoconjugate vaccine in an individual previously primed with the carrier protein. This review aims to provide a critical evaluation of the available data on carrier priming (and suppression) and conceptualize ways by which this phenomenon can be utilized to strengthen vaccination schedules. We conducted this literature review by searching well-known databases to date to identify relevant studies, then extracted and synthesized the data on carrier priming of widely used conjugate polysaccharide vaccines, such as, pneumococcal conjugate vaccine (PCV), meningococcal conjugate vaccine (MenCV) and Haemophilus influenzae type b conjugate vaccines (HibV). We found evidence of carrier priming with some conjugate vaccines, particularly HibV and PCV, in both animal and human models but controversy surrounds MenCV. This has implications for the immunogenicity of conjugate polysaccharide vaccines following the administration of tetanus-toxoid or diphtheria-toxoid containing vaccine (such as DTP). Available evidence supports a promising role for carrier priming in terms of maximizing the immunogenicity of conjugate vaccines and enhancing immunization schedule by making it more efficient and cost effective. Copyright © 2014 Elsevier Ltd. All rights reserved.