Three-Class Mammogram Classification Based on Descriptive CNN Features

PubMed Central

Zhang, Qianni; Jadoon, Adeel

2017-01-01

In this paper, a novel classification technique for large data set of mammograms using a deep learning method is proposed. The proposed model targets a three-class classification study (normal, malignant, and benign cases). In our model we have presented two methods, namely, convolutional neural network-discrete wavelet (CNN-DW) and convolutional neural network-curvelet transform (CNN-CT). An augmented data set is generated by using mammogram patches. To enhance the contrast of mammogram images, the data set is filtered by contrast limited adaptive histogram equalization (CLAHE). In the CNN-DW method, enhanced mammogram images are decomposed as its four subbands by means of two-dimensional discrete wavelet transform (2D-DWT), while in the second method discrete curvelet transform (DCT) is used. In both methods, dense scale invariant feature (DSIFT) for all subbands is extracted. Input data matrix containing these subband features of all the mammogram patches is created that is processed as input to convolutional neural network (CNN). Softmax layer and support vector machine (SVM) layer are used to train CNN for classification. Proposed methods have been compared with existing methods in terms of accuracy rate, error rate, and various validation assessment measures. CNN-DW and CNN-CT have achieved accuracy rate of 81.83% and 83.74%, respectively. Simulation results clearly validate the significance and impact of our proposed model as compared to other well-known existing techniques. PMID:28191461

Using CNN Newsroom in Advanced Listening Classes.

ERIC Educational Resources Information Center

Vann, Samuel

A university teacher of English as a Second Language describes the use of CNN Newsroom materials to teach listening skills. The basic news broadcast materials, including video and audio tapes, are provided by CNN, and have been developed by the teacher into instructional units. A classroom guide is available on the Internet. The instruction is…

Deformable Image Registration based on Similarity-Steered CNN Regression.

PubMed

Cao, Xiaohuan; Yang, Jianhua; Zhang, Jun; Nie, Dong; Kim, Min-Jeong; Wang, Qian; Shen, Dinggang

2017-09-01

Existing deformable registration methods require exhaustively iterative optimization, along with careful parameter tuning, to estimate the deformation field between images. Although some learning-based methods have been proposed for initiating deformation estimation, they are often template-specific and not flexible in practical use. In this paper, we propose a convolutional neural network (CNN) based regression model to directly learn the complex mapping from the input image pair (i.e., a pair of template and subject) to their corresponding deformation field. Specifically, our CNN architecture is designed in a patch-based manner to learn the complex mapping from the input patch pairs to their respective deformation field. First, the equalized active-points guided sampling strategy is introduced to facilitate accurate CNN model learning upon a limited image dataset. Then, the similarity-steered CNN architecture is designed, where we propose to add the auxiliary contextual cue, i.e., the similarity between input patches, to more directly guide the learning process. Experiments on different brain image datasets demonstrate promising registration performance based on our CNN model. Furthermore, it is found that the trained CNN model from one dataset can be successfully transferred to another dataset, although brain appearances across datasets are quite variable.

Bio-inspired nano-sensor-enhanced CNN visual computer.

PubMed

Porod, Wolfgang; Werblin, Frank; Chua, Leon O; Roska, Tamas; Rodriguez-Vazquez, Angel; Roska, Botond; Fay, Patrick; Bernstein, Gary H; Huang, Yih-Fang; Csurgay, Arpad I

2004-05-01

Nanotechnology opens new ways to utilize recent discoveries in biological image processing by translating the underlying functional concepts into the design of CNN (cellular neural/nonlinear network)-based systems incorporating nanoelectronic devices. There is a natural intersection joining studies of retinal processing, spatio-temporal nonlinear dynamics embodied in CNN, and the possibility of miniaturizing the technology through nanotechnology. This intersection serves as the springboard for our multidisciplinary project. Biological feature and motion detectors map directly into the spatio-temporal dynamics of CNN for target recognition, image stabilization, and tracking. The neural interactions underlying color processing will drive the development of nanoscale multispectral sensor arrays for image fusion. Implementing such nanoscale sensors on a CNN platform will allow the implementation of device feedback control, a hallmark of biological sensory systems. These biologically inspired CNN subroutines are incorporated into the new world of analog-and-logic algorithms and software, containing also many other active-wave computing mechanisms, including nature-inspired (physics and chemistry) as well as PDE-based sophisticated spatio-temporal algorithms. Our goal is to design and develop several miniature prototype devices for target detection, navigation, tracking, and robotics. This paper presents an example illustrating the synergies emerging from the convergence of nanotechnology, biotechnology, and information and cognitive science.

Improving CNN Performance Accuracies With Min-Max Objective.

PubMed

Shi, Weiwei; Gong, Yihong; Tao, Xiaoyu; Wang, Jinjun; Zheng, Nanning

2017-06-09

We propose a novel method for improving performance accuracies of convolutional neural network (CNN) without the need to increase the network complexity. We accomplish the goal by applying the proposed Min-Max objective to a layer below the output layer of a CNN model in the course of training. The Min-Max objective explicitly ensures that the feature maps learned by a CNN model have the minimum within-manifold distance for each object manifold and the maximum between-manifold distances among different object manifolds. The Min-Max objective is general and able to be applied to different CNNs with insignificant increases in computation cost. Moreover, an incremental minibatch training procedure is also proposed in conjunction with the Min-Max objective to enable the handling of large-scale training data. Comprehensive experimental evaluations on several benchmark data sets with both the image classification and face verification tasks reveal that employing the proposed Min-Max objective in the training process can remarkably improve performance accuracies of a CNN model in comparison with the same model trained without using this objective.

Region Based CNN for Foreign Object Debris Detection on Airfield Pavement.

PubMed

Cao, Xiaoguang; Wang, Peng; Meng, Cai; Bai, Xiangzhi; Gong, Guoping; Liu, Miaoming; Qi, Jun

2018-03-01

In this paper, a novel algorithm based on convolutional neural network (CNN) is proposed to detect foreign object debris (FOD) based on optical imaging sensors. It contains two modules, the improved region proposal network (RPN) and spatial transformer network (STN) based CNN classifier. In the improved RPN, some extra select rules are designed and deployed to generate high quality candidates with fewer numbers. Moreover, the efficiency of CNN detector is significantly improved by introducing STN layer. Compared to faster R-CNN and single shot multiBox detector (SSD), the proposed algorithm achieves better result for FOD detection on airfield pavement in the experiment.

Region Based CNN for Foreign Object Debris Detection on Airfield Pavement

PubMed Central

Cao, Xiaoguang; Wang, Peng; Meng, Cai; Gong, Guoping; Liu, Miaoming; Qi, Jun

2018-01-01

In this paper, a novel algorithm based on convolutional neural network (CNN) is proposed to detect foreign object debris (FOD) based on optical imaging sensors. It contains two modules, the improved region proposal network (RPN) and spatial transformer network (STN) based CNN classifier. In the improved RPN, some extra select rules are designed and deployed to generate high quality candidates with fewer numbers. Moreover, the efficiency of CNN detector is significantly improved by introducing STN layer. Compared to faster R-CNN and single shot multiBox detector (SSD), the proposed algorithm achieves better result for FOD detection on airfield pavement in the experiment. PMID:29494524

Continuous Chinese sign language recognition with CNN-LSTM

NASA Astrophysics Data System (ADS)

Yang, Su; Zhu, Qing

2017-07-01

The goal of sign language recognition (SLR) is to translate the sign language into text, and provide a convenient tool for the communication between the deaf-mute and the ordinary. In this paper, we formulate an appropriate model based on convolutional neural network (CNN) combined with Long Short-Term Memory (LSTM) network, in order to accomplish the continuous recognition work. With the strong ability of CNN, the information of pictures captured from Chinese sign language (CSL) videos can be learned and transformed into vector. Since the video can be regarded as an ordered sequence of frames, LSTM model is employed to connect with the fully-connected layer of CNN. As a recurrent neural network (RNN), it is suitable for sequence learning tasks with the capability of recognizing patterns defined by temporal distance. Compared with traditional RNN, LSTM has performed better on storing and accessing information. We evaluate this method on our self-built dataset including 40 daily vocabularies. The experimental results show that the recognition method with CNN-LSTM can achieve a high recognition rate with small training sets, which will meet the needs of real-time SLR system.

BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

PubMed

Kawahara, Jeremy; Brown, Colin J; Miller, Steven P; Booth, Brian G; Chau, Vann; Grunau, Ruth E; Zwicker, Jill G; Hamarneh, Ghassan

2017-02-01

We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is composed of novel edge-to-edge, edge-to-node and node-to-graph convolutional filters that leverage the topological locality of structural brain networks. We apply the BrainNetCNN framework to predict cognitive and motor developmental outcome scores from structural brain networks of infants born preterm. Diffusion tensor images (DTI) of preterm infants, acquired between 27 and 46 weeks gestational age, were used to construct a dataset of structural brain connectivity networks. We first demonstrate the predictive capabilities of BrainNetCNN on synthetic phantom networks with simulated injury patterns and added noise. BrainNetCNN outperforms a fully connected neural-network with the same number of model parameters on both phantoms with focal and diffuse injury patterns. We then apply our method to the task of joint prediction of Bayley-III cognitive and motor scores, assessed at 18 months of age, adjusted for prematurity. We show that our BrainNetCNN framework outperforms a variety of other methods on the same data. Furthermore, BrainNetCNN is able to identify an infant's postmenstrual age to within about 2 weeks. Finally, we explore the high-level features learned by BrainNetCNN by visualizing the importance of each connection in the brain with respect to predicting the outcome scores. These findings are then discussed in the context of the anatomy and function of the developing preterm infant brain. Copyright © 2016 Elsevier Inc. All rights reserved.

CNN-SVM for Microvascular Morphological Type Recognition with Data Augmentation.

PubMed

Xue, Di-Xiu; Zhang, Rong; Feng, Hui; Wang, Ya-Lei

2016-01-01

This paper focuses on the problem of feature extraction and the classification of microvascular morphological types to aid esophageal cancer detection. We present a patch-based system with a hybrid SVM model with data augmentation for intraepithelial papillary capillary loop recognition. A greedy patch-generating algorithm and a specialized CNN named NBI-Net are designed to extract hierarchical features from patches. We investigate a series of data augmentation techniques to progressively improve the prediction invariance of image scaling and rotation. For classifier boosting, SVM is used as an alternative to softmax to enhance generalization ability. The effectiveness of CNN feature representation ability is discussed for a set of widely used CNN models, including AlexNet, VGG-16, and GoogLeNet. Experiments are conducted on the NBI-ME dataset. The recognition rate is up to 92.74% on the patch level with data augmentation and classifier boosting. The results show that the combined CNN-SVM model beats models of traditional features with SVM as well as the original CNN with softmax. The synthesis results indicate that our system is able to assist clinical diagnosis to a certain extent.

A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification

NASA Astrophysics Data System (ADS)

Zhang, Ce; Pan, Xin; Li, Huapeng; Gardiner, Andy; Sargent, Isabel; Hare, Jonathon; Atkinson, Peter M.

2018-06-01

The contextual-based convolutional neural network (CNN) with deep architecture and pixel-based multilayer perceptron (MLP) with shallow structure are well-recognized neural network algorithms, representing the state-of-the-art deep learning method and the classical non-parametric machine learning approach, respectively. The two algorithms, which have very different behaviours, were integrated in a concise and effective way using a rule-based decision fusion approach for the classification of very fine spatial resolution (VFSR) remotely sensed imagery. The decision fusion rules, designed primarily based on the classification confidence of the CNN, reflect the generally complementary patterns of the individual classifiers. In consequence, the proposed ensemble classifier MLP-CNN harvests the complementary results acquired from the CNN based on deep spatial feature representation and from the MLP based on spectral discrimination. Meanwhile, limitations of the CNN due to the adoption of convolutional filters such as the uncertainty in object boundary partition and loss of useful fine spatial resolution detail were compensated. The effectiveness of the ensemble MLP-CNN classifier was tested in both urban and rural areas using aerial photography together with an additional satellite sensor dataset. The MLP-CNN classifier achieved promising performance, consistently outperforming the pixel-based MLP, spectral and textural-based MLP, and the contextual-based CNN in terms of classification accuracy. This research paves the way to effectively address the complicated problem of VFSR image classification.

Ikeda-like chaos on a dynamically filtered supercontinuum light source

NASA Astrophysics Data System (ADS)

Chembo, Yanne K.; Jacquot, Maxime; Dudley, John M.; Larger, Laurent

2016-08-01

We demonstrate temporal chaos in a color-selection mechanism from the visible spectrum of a supercontinuum light source. The color-selection mechanism is governed by an acousto-optoelectronic nonlinear delayed-feedback scheme modeled by an Ikeda-like equation. Initially motivated by the design of a broad audience live demonstrator in the framework of the International Year of Light 2015, the setup also provides a different experimental tool to investigate the dynamical complexity of delayed-feedback dynamics. Deterministic hyperchaos is analyzed here from the experimental time series. A projection method identifies the delay parameter, for which the chaotic strange attractor originally evolving in an infinite-dimensional phase space can be revealed in a two-dimensional subspace.

Diverse Region-Based CNN for Hyperspectral Image Classification.

PubMed

Zhang, Mengmeng; Li, Wei; Du, Qian

2018-06-01

Convolutional neural network (CNN) is of great interest in machine learning and has demonstrated excellent performance in hyperspectral image classification. In this paper, we propose a classification framework, called diverse region-based CNN, which can encode semantic context-aware representation to obtain promising features. With merging a diverse set of discriminative appearance factors, the resulting CNN-based representation exhibits spatial-spectral context sensitivity that is essential for accurate pixel classification. The proposed method exploiting diverse region-based inputs to learn contextual interactional features is expected to have more discriminative power. The joint representation containing rich spectral and spatial information is then fed to a fully connected network and the label of each pixel vector is predicted by a softmax layer. Experimental results with widely used hyperspectral image data sets demonstrate that the proposed method can surpass any other conventional deep learning-based classifiers and other state-of-the-art classifiers.

!CHAOS: A cloud of controls

NASA Astrophysics Data System (ADS)

Angius, S.; Bisegni, C.; Ciuffetti, P.; Di Pirro, G.; Foggetta, L. G.; Galletti, F.; Gargana, R.; Gioscio, E.; Maselli, D.; Mazzitelli, G.; Michelotti, A.; Orrù, R.; Pistoni, M.; Spagnoli, F.; Spigone, D.; Stecchi, A.; Tonto, T.; Tota, M. A.; Catani, L.; Di Giulio, C.; Salina, G.; Buzzi, P.; Checcucci, B.; Lubrano, P.; Piccini, M.; Fattibene, E.; Michelotto, M.; Cavallaro, S. R.; Diana, B. F.; Enrico, F.; Pulvirenti, S.

2016-01-01

The paper is aimed to present the !CHAOS open source project aimed to develop a prototype of a national private Cloud Computing infrastructure, devoted to accelerator control systems and large experiments of High Energy Physics (HEP). The !CHAOS project has been financed by MIUR (Italian Ministry of Research and Education) and aims to develop a new concept of control system and data acquisition framework by providing, with a high level of aaabstraction, all the services needed for controlling and managing a large scientific, or non-scientific, infrastructure. A beta version of the !CHAOS infrastructure will be released at the end of December 2015 and will run on private Cloud infrastructures based on OpenStack.

Going Deeper With Contextual CNN for Hyperspectral Image Classification.

PubMed

Lee, Hyungtae; Kwon, Heesung

2017-10-01

In this paper, we describe a novel deep convolutional neural network (CNN) that is deeper and wider than other existing deep networks for hyperspectral image classification. Unlike current state-of-the-art approaches in CNN-based hyperspectral image classification, the proposed network, called contextual deep CNN, can optimally explore local contextual interactions by jointly exploiting local spatio-spectral relationships of neighboring individual pixel vectors. The joint exploitation of the spatio-spectral information is achieved by a multi-scale convolutional filter bank used as an initial component of the proposed CNN pipeline. The initial spatial and spectral feature maps obtained from the multi-scale filter bank are then combined together to form a joint spatio-spectral feature map. The joint feature map representing rich spectral and spatial properties of the hyperspectral image is then fed through a fully convolutional network that eventually predicts the corresponding label of each pixel vector. The proposed approach is tested on three benchmark data sets: the Indian Pines data set, the Salinas data set, and the University of Pavia data set. Performance comparison shows enhanced classification performance of the proposed approach over the current state-of-the-art on the three data sets.

God's Stuff: The Constructive Powers of Chaos for Teaching Religion

ERIC Educational Resources Information Center

Willhauck, Susan

2010-01-01

Order and organization are valued in the classroom, and there is a prevailing understanding that chaos should be avoided. Yet chaos can also be potent space or a source from which new things spring forth. This article investigates biblical, scientific, and cultural understandings of chaos to discover how these contribute to a revelatory metaphor…

Chaos in the Solar System

NASA Technical Reports Server (NTRS)

Lecar, Myron; Franklin, Fred A.; Holman, Matthew J.; Murray, Norman J.

2001-01-01

The physical basis of chaos in the solar system is now better understood: In all cases investigated so far, chaotic orbits result from overlapping resonances. Perhaps the clearest examples are found in the asteroid belt. Overlapping resonances account for its kirkwood gaps and were used to predict and find evidence for very narrow gaps in the outer belt. Further afield, about one new "short-peroid" comet is discovered each year. They are believed to come from the "Kuiper Belt" (at 40 AU or more) via chaotic orbits produced by mean-motion and secular resonances with Neptune. Finally, the planetary system itself is not immune from chaos. In the inner solar system, overlapping secular resonances have been identified as the possible source of chaos. For example, Mercury in 1012 years, may suffer a close encounter with Venus or plunge into the Sun. In the outer solar system, three-body resonances have been identified as a source of chaos, but on an even longer time scale of 109 times the age of the solar system. On the human time scale, the planets do follow their orbits in a stately procession, and we can predict their trajectories for hundreds of thousands of years. That is because the mavericks, with shorter instability times, have long since been ejected. The solar system is not stable; it is just old!

Outflow channel sources, reactivation, and chaos formation, Xanthe Terra, Mars

USGS Publications Warehouse

Rodriguez, J.A.P.; Sasaki, S.; Kuzmin, R.O.; Dohm, J.M.; Tanaka, K.L.; Miyamoto, H.; Kurita, K.; Komatsu, G.; Fairen, A.G.; Ferris, J.C.

2005-01-01

The undulating, warped, and densely fractured surfaces of highland regions east of Valles Marineris (located north of the eastern Aureum Chaos, east of the Hydraotes Chaos, and south of the Hydaspis Chaos) resulted from extensional surface warping related to ground subsidence, caused when pressurized water confined in subterranean caverns was released to the surface. Water emanations formed crater lakes and resulted in channeling episodes involved in the excavation of Ares, Tiu, and Simud Valles of the eastern part of the circum-Chryse outflow channel system. Progressive surface subsidence and associated reduction of the subsurface cavernous volume, and/or episodes of magmatic-driven activity, led to increases of the hydrostatic pressure, resulting in reactivation of both catastrophic and non-catastrophic outflow activity. Ancient cratered highland and basin materials that underwent large-scale subsidence grade into densely fractured terrains. Collapse of rock materials in these regions resulted in the formation of chaotic terrains, which occur in and near the headwaters of the eastern circum-Chryse outflow channels. The deepest chaotic terrain in the Hydaspis Chaos region resulted from the collapse of pre-existing outflow channel floors. The release of volatiles and related collapse may have included water emanations not necessarily linked to catastrophic outflow. Basal warming related to dike intrusions, thermokarst activity involving wet sediments and/or dissected ice-enriched country rock, permafrost exposed to the atmosphere by extensional tectonism and channel incision, and/or the injection of water into porous floor material, may have enhanced outflow channel floor instability and subsequent collapse. In addition to the possible genetic linkage to outflow channel development dating back to at least the Late Noachian, clear disruption of impact craters with pristine ejecta blankets and rims, as well as preservation of fine tectonic fabrics, suggest that

Tiled architecture of a CNN-mostly IP system

NASA Astrophysics Data System (ADS)

Spaanenburg, Lambert; Malki, Suleyman

2009-05-01

Multi-core architectures have been popularized with the advent of the IBM CELL. On a finer grain the problems in scheduling multi-cores have already existed in the tiled architectures, such as the EPIC and Da Vinci. It is not easy to evaluate the performance of a schedule on such architecture as historical data are not available. One solution is to compile algorithms for which an optimal schedule is known by analysis. A typical example is an algorithm that is already defined in terms of many collaborating simple nodes, such as a Cellular Neural Network (CNN). A simple node with a local register stack together with a 'rotating wheel' internal communication mechanism has been proposed. Though the basic CNN allows for a tiled implementation of a tiled algorithm on a tiled structure, a practical CNN system will have to disturb this regularity by the additional need for arithmetical and logical operations. Arithmetic operations are needed for instance to accommodate for low-level image processing, while logical operations are needed to fork and merge different data streams without use of the external memory. It is found that the 'rotating wheel' internal communication mechanism still handles such mechanisms without the need for global control. Overall the CNN system provides for a practical network size as implemented on a FPGA, can be easily used as embedded IP and provides a clear benchmark for a multi-core compiler.

SIFT Meets CNN: A Decade Survey of Instance Retrieval.

PubMed

Zheng, Liang; Yang, Yi; Tian, Qi

2018-05-01

In the early days, content-based image retrieval (CBIR) was studied with global features. Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively studied for over a decade due to the advantage of SIFT in dealing with image transformations. Recently, image representations based on the convolutional neural network (CNN) have attracted increasing interest in the community and demonstrated impressive performance. Given this time of rapid evolution, this article provides a comprehensive survey of instance retrieval over the last decade. Two broad categories, SIFT-based and CNN-based methods, are presented. For the former, according to the codebook size, we organize the literature into using large/medium-sized/small codebooks. For the latter, we discuss three lines of methods, i.e., using pre-trained or fine-tuned CNN models, and hybrid methods. The first two perform a single-pass of an image to the network, while the last category employs a patch-based feature extraction scheme. This survey presents milestones in modern instance retrieval, reviews a broad selection of previous works in different categories, and provides insights on the connection between SIFT and CNN-based methods. After analyzing and comparing retrieval performance of different categories on several datasets, we discuss promising directions towards generic and specialized instance retrieval.

CNN universal machine as classificaton platform: an art-like clustering algorithm.

PubMed

Bálya, David

2003-12-01

Fast and robust classification of feature vectors is a crucial task in a number of real-time systems. A cellular neural/nonlinear network universal machine (CNN-UM) can be very efficient as a feature detector. The next step is to post-process the results for object recognition. This paper shows how a robust classification scheme based on adaptive resonance theory (ART) can be mapped to the CNN-UM. Moreover, this mapping is general enough to include different types of feed-forward neural networks. The designed analogic CNN algorithm is capable of classifying the extracted feature vectors keeping the advantages of the ART networks, such as robust, plastic and fault-tolerant behaviors. An analogic algorithm is presented for unsupervised classification with tunable sensitivity and automatic new class creation. The algorithm is extended for supervised classification. The presented binary feature vector classification is implemented on the existing standard CNN-UM chips for fast classification. The experimental evaluation shows promising performance after 100% accuracy on the training set.

Centrioles regulate centrosome size by controlling the rate of Cnn incorporation into the PCM.

PubMed

Conduit, Paul T; Brunk, Kathrin; Dobbelaere, Jeroen; Dix, Carly I; Lucas, Eliana P; Raff, Jordan W

2010-12-21

centrosomes are major microtubule organizing centers in animal cells, and they comprise a pair of centrioles surrounded by an amorphous pericentriolar material (PCM). Centrosome size is tightly regulated during the cell cycle, and it has recently been shown that the two centrosomes in certain stem cells are often asymmetric in size. There is compelling evidence that centrioles influence centrosome size, but how centrosome size is set remains mysterious. we show that the conserved Drosophila PCM protein Cnn exhibits an unusual dynamic behavior, because Cnn molecules only incorporate into the PCM closest to the centrioles and then spread outward through the rest of the PCM. Cnn incorporation into the PCM is driven by an interaction with the conserved centriolar proteins Asl (Cep152 in humans) and DSpd-2 (Cep192 in humans). The rate of Cnn incorporation into the PCM is tightly regulated during the cell cycle, and this rate influences the amount of Cnn in the PCM, which in turn is an important determinant of overall centrosome size. Intriguingly, daughter centrioles in syncytial embryos only start to incorporate Cnn as they disengage from their mothers; this generates a centrosome size asymmetry, with mother centrioles always initially organizing more Cnn than their daughters. centrioles can control the amount of PCM they organize by regulating the rate of Cnn incorporation into the PCM. This mechanism can explain how centrosome size is regulated during the cell cycle and also allows mother and daughter centrioles to set centrosome size independently of one another.

The Mps1 kinase modulates the recruitment and activity of Cnn1(CENP-T) at Saccharomyces cerevisiae kinetochores.

PubMed

Thapa, Kriti Shrestha; Oldani, Amanda; Pagliuca, Cinzia; De Wulf, Peter; Hazbun, Tony R

2015-05-01

Kinetochores are conserved protein complexes that bind the replicated chromosomes to the mitotic spindle and then direct their segregation. To better comprehend Saccharomyces cerevisiae kinetochore function, we dissected the phospho-regulated dynamic interaction between conserved kinetochore protein Cnn1(CENP-T), the centromere region, and the Ndc80 complex through the cell cycle. Cnn1 localizes to kinetochores at basal levels from G1 through metaphase but accumulates abruptly at anaphase onset. How Cnn1 is recruited and which activities regulate its dynamic localization are unclear. We show that Cnn1 harbors two kinetochore-localization activities: a C-terminal histone-fold domain (HFD) that associates with the centromere region and a N-terminal Spc24/Spc25 interaction sequence that mediates linkage to the microtubule-binding Ndc80 complex. We demonstrate that the established Ndc80 binding site in the N terminus of Cnn1, Cnn1(60-84), should be extended with flanking residues, Cnn1(25-91), to allow near maximal binding affinity to Ndc80. Cnn1 localization was proposed to depend on Mps1 kinase activity at Cnn1-S74, based on in vitro experiments demonstrating the Cnn1-Ndc80 complex interaction. We demonstrate that from G1 through metaphase, Cnn1 localizes via both its HFD and N-terminal Spc24/Spc25 interaction sequence, and deletion or mutation of either region results in anomalous Cnn1 kinetochore levels. At anaphase onset (when Mps1 activity decreases) Cnn1 becomes enriched mainly via the N-terminal Spc24/Spc25 interaction sequence. In sum, we provide the first in vivo evidence of Cnn1 preanaphase linkages with the kinetochore and enrichment of the linkages during anaphase. Copyright © 2015 by the Genetics Society of America.

Channel One and CNN Newsroom: A Comparative Study of Seven Districts.

ERIC Educational Resources Information Center

Nasstrom, Roy; Gierok, Anne

Many American schools use the televised news programs Channel One and CNN Newsroom. Channel One has received considerable scrutiny, some of it highly unfavorable, while attention to CNN Newsroom has been less extensive and mostly benign. This study compares the two programs within seven school districts in Wisconsin. The study addresses three…

A CNN based Hybrid approach towards automatic image registration

NASA Astrophysics Data System (ADS)

Arun, Pattathal V.; Katiyar, Sunil K.

2013-06-01

Image registration is a key component of various image processing operations which involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however inability to properly model object shape as well as contextual information had limited the attainable accuracy. In this paper, we propose a framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as Vector Machines, Cellular Neural Network (CNN), SIFT, coreset, and Cellular Automata. CNN has found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using corset optimization The salient features of this work are cellular neural network approach based SIFT feature point optimisation, adaptive resampling and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. System has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. Methodology also illustrated to be effective in providing intelligent interpretation and adaptive resampling. Rejestracja obrazu jest kluczowym składnikiem różnych operacji jego przetwarzania. W ostatnich latach do automatycznej rejestracji obrazu wykorzystuje się metody sztucznej inteligencji, których największą wadą, obniżającą dokładność uzyskanych wyników jest brak możliwości dobrego wymodelowania kształtu i informacji kontekstowych. W niniejszej pracy zaproponowano zasady dokładnego modelowania kształtu oraz adaptacyjnego resamplingu z wykorzystaniem zaawansowanych technik, takich jak Vector Machines (VM), komórkowa sieć neuronowa (CNN), przesiewanie (SIFT), Coreset i

Small-size pedestrian detection in large scene based on fast R-CNN

NASA Astrophysics Data System (ADS)

Wang, Shengke; Yang, Na; Duan, Lianghua; Liu, Lu; Dong, Junyu

2018-04-01

Pedestrian detection is a canonical sub-problem of object detection with high demand during recent years. Although recent deep learning object detectors such as Fast/Faster R-CNN have shown excellent performance for general object detection, they have limited success for small size pedestrian detection in large-view scene. We study that the insufficient resolution of feature maps lead to the unsatisfactory accuracy when handling small instances. In this paper, we investigate issues involving Fast R-CNN for pedestrian detection. Driven by the observations, we propose a very simple but effective baseline for pedestrian detection based on Fast R-CNN, employing the DPM detector to generate proposals for accuracy, and training a fast R-CNN style network to jointly optimize small size pedestrian detection with skip connection concatenating feature from different layers to solving coarseness of feature maps. And the accuracy is improved in our research for small size pedestrian detection in the real large scene.

Generalized Synchronization in AN Array of Nonlinear Dynamic Systems with Applications to Chaotic Cnn

NASA Astrophysics Data System (ADS)

Min, Lequan; Chen, Guanrong

This paper establishes some generalized synchronization (GS) theorems for a coupled discrete array of difference systems (CDADS) and a coupled continuous array of differential systems (CCADS). These constructive theorems provide general representations of GS in CDADS and CCADS. Based on these theorems, one can design GS-driven CDADS and CCADS via appropriate (invertible) transformations. As applications, the results are applied to autonomous and nonautonomous coupled Chen cellular neural network (CNN) CDADS and CCADS, discrete bidirectional Lorenz CNN CDADS, nonautonomous bidirectional Chua CNN CCADS, and nonautonomously bidirectional Chen CNN CDADS and CCADS, respectively. Extensive numerical simulations show their complex dynamic behaviors. These theorems provide new means for understanding the GS phenomena of complex discrete and continuously differentiable networks.

Proceedings of the 2nd Experimental Chaos Conference

NASA Astrophysics Data System (ADS)

Ditto, William; Pecora, Lou; Shlesinger, Michael; Spano, Mark; Vohra, Sandeep

1995-02-01

The Table of Contents for the full book PDF is as follows: * Introduction * Spatiotemporal Phenomena * Experimental Studies of Chaotic Mixing * Using Random Maps in the Analysis of Experimental Fluid Flows * Transition to Spatiotemporal Chaos in a Reaction-Diffusion System * Ion-Dynamical Chaos in Plasmas * Optics * Chaos in a Synchronously Driven Optical Resonator * Chaos, Patterns and Defects in Stimulated Scattering Phenomena * Test of the Normal Form for a Subcritical Bifurcation * Observation of Bifurcations and Chaos in a Driven Fiber Optic Coil * Applications -- Communications * Robustness and Signal Recovery in a Synchronized Chaotic System * Synchronizing Nonautonomous Chaotic Circuits * Synchronization of Pulse-Coupled Chaotic Oscillators * Ocean Transmission Effects on Chaotic Signals * Controlling Symbolic Dynamics for Communication * Applications -- Control * Analysis of Nonlinear Actuators Using Chaotic Waveforms * Controlling Chaos in a Quasiperiodic Electronic System * Control of Chaos in a CO2 Laser * General Research * Video-Based Analysis of Bifurcation Phenomena in Radio-Frequency-Excited Inert Gas Plasmas * Transition from Soliton to Chaotic Motion During the Impact of a Nonlinear Structure * Sonoluminescence in a Single Bubble: Periodic, Quasiperiodic and Chaotic Light Source * Quantum Chaos Experiments Using Microwave Cavities * Experiments on Quantum Chaos With and Without Time Reversibility * When Small Noise Imposed on Deterministic Dynamics Becomes Important * Biology * Chaos Control for Cardiac Arrhythmias * Irregularities in Spike Trains of Cat Retinal Ganglion Cells * Broad-Band Synchronization in Monkey Neocortex * Applicability of Correlation Dimension Calculations to Blood Pressure Signal in Rats * Tests for Deterministic Chaos in Noisy Time Series * The Crayfish Mechanoreceptor Cell: A Biological Example of Stochastic Resonance * Chemistry * Chaos During Heterogeneous Chemical Reactions * Stabilizing and Tracking Unstable Periodic

NetVLAD: CNN Architecture for Weakly Supervised Place Recognition.

PubMed

Arandjelovic, Relja; Gronat, Petr; Torii, Akihiko; Pajdla, Tomas; Sivic, Josef

2018-06-01

We tackle the problem of large scale visual place recognition, where the task is to quickly and accurately recognize the location of a given query photograph. We present the following four principal contributions. First, we develop a convolutional neural network (CNN) architecture that is trainable in an end-to-end manner directly for the place recognition task. The main component of this architecture, NetVLAD, is a new generalized VLAD layer, inspired by the "Vector of Locally Aggregated Descriptors" image representation commonly used in image retrieval. The layer is readily pluggable into any CNN architecture and amenable to training via backpropagation. Second, we create a new weakly supervised ranking loss, which enables end-to-end learning of the architecture's parameters from images depicting the same places over time downloaded from Google Street View Time Machine. Third, we develop an efficient training procedure which can be applied on very large-scale weakly labelled tasks. Finally, we show that the proposed architecture and training procedure significantly outperform non-learnt image representations and off-the-shelf CNN descriptors on challenging place recognition and image retrieval benchmarks.

Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update.

PubMed

Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

2016-04-15

Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the "good" models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm.

Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update

PubMed Central

Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

2016-01-01

Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the “good” models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm. PMID:27092505

CNN Newsroom Classroom Guides, September 2001.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of September 2001 provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: shark attacks ignite controversy in some Florida communities,…

CNN Newsroom Classroom Guides. June 1998.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

CNN Newsroom is a daily 15-minute commercial-free news program specifically produced for classroom use and provided free to participating schools. These daily classroom guides present top stories, headlines, environmental news, and other current events, along with suggested class discussion topics and activities to accompany the broadcasts for one…

CNN Newsroom Classroom Guides, June 2001.

ERIC Educational Resources Information Center

Turner Learning, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of June 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: Indonesian President Wahid faces impeachment (June 1); suicide bombing…

CNN Newsroom Classroom Guides, April 2001.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of April 2001 provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: former Yugoslav President Slobodan Milosevic is arrested, a Chinese…

CNN Newsroom Classroom Guides. September 1999.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for September 1-30, 1999, provide program rundowns, suggestions for class activities and discussion, links to relevant World Wide Web sites, and a list of related news terms. Top stories include: Venezuela constitutional crisis, Panama's first female…

CNN Newsroom Classroom Guides, April 2002.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of April 2002, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: Israeli soldiers attack Yasser Arafat's headquarters in Ramallah,…

CNN Newsroom Classroom Guides. March 1999.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

CNN Newsroom is a daily 15-minute commercial-free news program specifically produced for classroom use and provided free to participating schools. These daily classroom guides present top stories, headlines, environmental news, and other current events, along with suggested class discussion topics and activities to accompany the broadcasts for one…

CNN Newsroom Classroom Guides, February 2001.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of February 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: Libyan intelligence agent is convicted of the Lockerbie bombing, and…

CNN Newsroom Classroom Guides. October, 1998.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of October, 1998, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: scientists find trace fossil evidence of billion-year old worms, the…

CNN Newsroom Classroom Guides. September 1998.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of September, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: the reaction of world markets to Russia's Duma rejection of Viktor…

CNN Newsroom Classroom Guides. August 1998.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These Classroom Guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of August, provide program rundowns, suggestions for class activities and discussion, links to pertinent World Wide Web sites, and lists of related news terms. Topics include: meetings over weapons inspections in Iraq could either…

CNN Newsroom Classroom Guides, October 2000.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Newtown, PA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of October 2000, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: Chinese authorities detain Falun Gong protesters on Tiananmen Square…

CNN Newsroom Classroom Guides, January 2002.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of January 2002, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: tensions escalate between Pakistan and India, (January 3-4); the…

CNN Newsroom Classroom Guides, October 2001.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of October 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Stories include: Taliban update/tribal troubles, U.S. officials report progress in the…

CNN Newsroom Classroom Guides, June 2000.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of June 2000, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: President Clinton prepares to visit Germany, and federal court of…

CNN Newsroom Classroom Guides, February 2002.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of February 2002, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: Afghanistan's interim leader is making a global impression (February…

CNN Newsroom Classroom Guides. October 1995.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of October, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: bedroom community business, freedom of expression and…

CNN Newsroom Classroom Guides. November, 1998.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for the month of November, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: Iraq refuses to cooperate with United Nations weapons inspectors, expansion of…

CNN Newsroom Classroom Guides, December 2000.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of December 2000, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: the United States Supreme Court hears the presidential candidates'…

Chaos and Chaos Control of the Frenkel-Kontorova Model with Dichotomous Noise

NASA Astrophysics Data System (ADS)

Lei, Youming; Zheng, Fan; Shao, Xizhen

Chaos and chaos control of the Frenkel-Kontorova (FK) model with dichotomous noise are studied theoretically and numerically. The threshold conditions for the onset of chaos in the FK model are firstly derived by applying the random Melnikov method with a mean-square criterion to the soliton equation, which is a fundamental topological mode of the FK model and accounts for its nonlinear phenomena. We found that dichotomous noise can induce stochastic chaos in the FK model, and the threshold of noise amplitude for the onset of chaos increases with the increase of its transition rate. Then the analytical criterion of chaos control is obtained by means of the time-delay feedback method. Since the time-delay feedback control raises the threshold of noise amplitude for the onset of chaos, chaos in the FK model is effectively suppressed. Through numerical simulations including the mean top Lyapunov exponent and the safe basin, we demonstrate the validity of the analytical predictions of chaos. Furthermore, time histories and phase portraits are utilized to verify the effectiveness of the proposed control.

CNN Newsroom Classroom Guides, November 2001.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of November 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: economic stimulus and U.S. steps up the bombing campaign in…

CNN Newsroom Classroom Guides, August 2000.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of August 2000, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: the GOP opens its 37th national convention in Philadelphia, outraged…

CNN Newsroom Classroom Guides, March 2001.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of March 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: Seattle earthquake and U.S. economy working class communities fear a…

CNN Newsroom Classroom Guides, April 2000.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Newtown, PA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of April 2000, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: failure of settlement talks between Microsoft and the U.S. government,…

CNN Newsroom Classroom Guides, November 2000.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of November 2000, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: independent U.S. oil companies struggle to survive, U.S.…

CNN Newsroom Classroom Guides, August 2001.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of August 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: special series on the teenage brain, and MTV celebrates its 20th…

CNN Newsroom Classroom Guides. June, 1997.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of June, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: France gets a new government and Prime Minister as the Socialist Party defeats the…

CNN Newsroom Classroom Guides. August 1999.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for August 2-31, 1999, provide program rundowns, suggestions for class activities and discussion, links to relevant World Wide Web sites, and a list of related news terms. Top stories include: the drought and heatwave in the northeastern United…

CNN Newsroom Classroom Guides, May 2000.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Newtown, PA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of May 2000, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: U.S. Government files a proposal to split up Microsoft, terrorism source…

CNN Newsroom Classroom Guides. May 1999.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Newtown, PA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of May, provide program rundowns, suggestions for class activities and discussion, links to related World Wide Web sites, and lists of related news terms. Top stories include: Reverend Jesse Jackson secures release of U.S. soldiers…

CNN Newsroom Classroom Guides, January 2001.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of January 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: George W. Bush nominates the last three vacant Cabinet posts,…

CNN Newsroom Classroom Guides, May 2001.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of May 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: President Bush will announce his plans for a missile defense system,…

CNN Newsroom Classroom Guides, June 2002.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of June 2002, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Major topics covered include: the Kashmir conflict; the Pakistan and the Kazahkstan Summit;…

CNN Newsroom Classroom Guides, December 2001.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of December 2001, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: President Bush responds to the recent acts of terrorism in Israel,…

CNN Newsroom Classroom Guides. February 1999.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Newtown, PA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of February, provide program rundowns, suggestions for class activities and discussion, links to related World Wide Web sites, and lists of related news terms. Topics include: Monica Lewinsky scheduled to be deposed for the Senate,…

Interphase centrosome organization by the PLP-Cnn scaffold is required for centrosome function

PubMed Central

Lerit, Dorothy A.; Jordan, Holly A.; Poulton, John S.; Fagerstrom, Carey J.; Galletta, Brian J.; Peifer, Mark

2015-01-01

Pericentriolar material (PCM) mediates the microtubule (MT) nucleation and anchoring activity of centrosomes. A scaffold organized by Centrosomin (Cnn) serves to ensure proper PCM architecture and functional changes in centrosome activity with each cell cycle. Here, we investigate the mechanisms that spatially restrict and temporally coordinate centrosome scaffold formation. Focusing on the mitotic-to-interphase transition in Drosophila melanogaster embryos, we show that the elaboration of the interphase Cnn scaffold defines a major structural rearrangement of the centrosome. We identify an unprecedented role for Pericentrin-like protein (PLP), which localizes to the tips of extended Cnn flares, to maintain robust interphase centrosome activity and promote the formation of interphase MT asters required for normal nuclear spacing, centrosome segregation, and compartmentalization of the syncytial embryo. Our data reveal that Cnn and PLP directly interact at two defined sites to coordinate the cell cycle–dependent rearrangement and scaffolding activity of the centrosome to permit normal centrosome organization, cell division, and embryonic viability. PMID:26150390

Interphase centrosome organization by the PLP-Cnn scaffold is required for centrosome function.

PubMed

Lerit, Dorothy A; Jordan, Holly A; Poulton, John S; Fagerstrom, Carey J; Galletta, Brian J; Peifer, Mark; Rusan, Nasser M

2015-07-06

Pericentriolar material (PCM) mediates the microtubule (MT) nucleation and anchoring activity of centrosomes. A scaffold organized by Centrosomin (Cnn) serves to ensure proper PCM architecture and functional changes in centrosome activity with each cell cycle. Here, we investigate the mechanisms that spatially restrict and temporally coordinate centrosome scaffold formation. Focusing on the mitotic-to-interphase transition in Drosophila melanogaster embryos, we show that the elaboration of the interphase Cnn scaffold defines a major structural rearrangement of the centrosome. We identify an unprecedented role for Pericentrin-like protein (PLP), which localizes to the tips of extended Cnn flares, to maintain robust interphase centrosome activity and promote the formation of interphase MT asters required for normal nuclear spacing, centrosome segregation, and compartmentalization of the syncytial embryo. Our data reveal that Cnn and PLP directly interact at two defined sites to coordinate the cell cycle-dependent rearrangement and scaffolding activity of the centrosome to permit normal centrosome organization, cell division, and embryonic viability.

Research on High Accuracy Detection of Red Tide Hyperspecrral Based on Deep Learning Cnn

NASA Astrophysics Data System (ADS)

Hu, Y.; Ma, Y.; An, J.

2018-04-01

Increasing frequency in red tide outbreaks has been reported around the world. It is of great concern due to not only their adverse effects on human health and marine organisms, but also their impacts on the economy of the affected areas. this paper put forward a high accuracy detection method based on a fully-connected deep CNN detection model with 8-layers to monitor red tide in hyperspectral remote sensing images, then make a discussion of the glint suppression method for improving the accuracy of red tide detection. The results show that the proposed CNN hyperspectral detection model can detect red tide accurately and effectively. The red tide detection accuracy of the proposed CNN model based on original image and filter-image is 95.58 % and 97.45 %, respectively, and compared with the SVM method, the CNN detection accuracy is increased by 7.52 % and 2.25 %. Compared with SVM method base on original image, the red tide CNN detection accuracy based on filter-image increased by 8.62 % and 6.37 %. It also indicates that the image glint affects the accuracy of red tide detection seriously.

CNN Newsroom Classroom Guides. October 1999.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for October 1-29, 1999, provide program rundowns, suggestions for class activities and discussion, links to relevant World Wide Web sites, and a list of related news terms. Top stories include: nuclear accident in Japan (October 1); debate over the nuclear…

CNN Newsroom Classroom Guides, July 2001.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of July 2001 provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: Slobodan Milosevic prepares to go before the U.N. war crimes tribunal,…

CNN Newsroom Classroom Guides. December 1999.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for December 1-17, 1999, provide program rundowns, suggestions for class activities and discussion, links to relevant World Wide Web sites, and a list of related news terms. Top stories include: World AIDS Day, World Trade Organization protests in Seattle,…

CNN Newsroom Classroom Guides. November 1999.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for November 1-30, 1999, provide program rundowns, suggestions for class activities and discussion, links to relevant World Wide Web sites, and a list of related news terms. Top stories include: EgyptAir Flight 990 crash, Oslo summit, India cyclone,…

CNN Newsroom Classroom Guides. January 2000.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for January 3-28, 2000, provide program rundowns, suggestions for class activities and discussion, links to relevant World Wide Web sites, and a list of related news terms. Top stories include: issues of the Millennium, 100 hours of the Millennium, Mideast…

CNN Newsroom Classroom Guides, July 2002.

ERIC Educational Resources Information Center

Turner Learning, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of July 2002, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Lead stories include: authorities arrest a man accused of starting the Rodeo fire in Arizona,…

CNN Newsroom Classroom Guides, March 2002.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of March 2002, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Lead stories include: the U.S. expands the War on Terrorism into the Republic of Georgia and…

CNN Newsroom Classroom Guides. August, 1997.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These guides are designed to accompany CNN Newsroom, a daily 15-minute news program produced for classroom use and provided free to participating schools. Top stories include: peace talks stalled due to a suicide bombing in a Jerusalem market; inauguration of Iran's new president; UPS strike; budget agreement signed into law; news on teenage drug…

CNN Newsroom Classroom Guides. February 2000.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for February 1-29, 2000, provide program rundowns, suggestions for class activities and discussion, links to relevant World Wide Web sites, and a list of related news terms. Top stories include: significance of the New Hampshire Primary, victors in the New…

CNN Newsroom Classroom Guides, March 2000.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Newtown, PA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of March, provide program rundowns, suggestions for class activities and discussion, Web links, and a list of related news terms. Top stories include: primary victories in the Bush campaign and preparations by Gore and Bradley for the…

CNN Newsroom Classroom Guides. June 1999.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for June 1-30, 1999, provide program rundowns, suggestions for class activities and discussion, links to relevant World Wide Web sites, and a list of related news terms. Top stories include: NATO bombings in Belgrade amid peace negotiations, people of South…

CNN Newsroom Classroom Guides. April 1999.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Newtown, PA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of April, provide program rundowns, suggestions for class activities and discussion, links to related World Wide Web sites, and lists of related news terms. Top stories include: NATO includes Belgrade in its targets, three U.S.…

CNN Newsroom Classroom Guides, September 2000.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of September 2000, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: FBI arrests a suspect in the Emulex hoax case (September 1); U.S.…

CNN Newsroom Classroom Guides, July 2000.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of July 2000, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Top stories include: Mexican voters go to polls in a landmark election (July 3); Mexico's…

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising.

PubMed

Zhang, Kai; Zuo, Wangmeng; Chen, Yunjin; Meng, Deyu; Zhang, Lei

2017-07-01

The discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance. In this paper, we take one step forward by investigating the construction of feed-forward denoising convolutional neural networks (DnCNNs) to embrace the progress in very deep architecture, learning algorithm, and regularization method into image denoising. Specifically, residual learning and batch normalization are utilized to speed up the training process as well as boost the denoising performance. Different from the existing discriminative denoising models which usually train a specific model for additive white Gaussian noise at a certain noise level, our DnCNN model is able to handle Gaussian denoising with unknown noise level (i.e., blind Gaussian denoising). With the residual learning strategy, DnCNN implicitly removes the latent clean image in the hidden layers. This property motivates us to train a single DnCNN model to tackle with several general image denoising tasks, such as Gaussian denoising, single image super-resolution, and JPEG image deblocking. Our extensive experiments demonstrate that our DnCNN model can not only exhibit high effectiveness in several general image denoising tasks, but also be efficiently implemented by benefiting from GPU computing.

CNN Newsroom Classroom Guides. July 1999.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for July 1-30, 1999, provide program rundowns, suggestions for class activities and discussion, links to relevant World Wide Web sites, and a list of related new terms. Top stories include: Kosovo after the strikes, and saving the Everglades (July 1-2);…

CNN Newsroom Classroom Guides. July, 1997.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

CNN Newsroom is a daily 15-minute commercial-free news program specifically produced for classroom use and provided free of charge to participating schools. This guide is designed to accompany the program for July 1997. Top stories include the following: Britain's hand over of Hong Kong to the People's Republic of China; regulating business on the…

Chaos, Complexity and Deterrence

DTIC Science & Technology

2000-04-19

populations of adversary countries but which seldom affect their leadership . Conclusion The jury is still out on the applicability of chaos theory to...Advent of Chaos Chaos theory in the West (considerable work on chaos was also conducted in the Soviet Union) developed from the 1960s work of...predicted by his model over time.1 This discovery, sensitivity to initial conditions, is one of the fundamental characteristics of chaos theory . Lorenz

Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis

PubMed Central

Fu, Hongping; Niu, Zhendong; Zhang, Chunxia; Ma, Jing; Chen, Jie

2016-01-01

Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker, and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance. PMID:27471460

Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis.

PubMed

Fu, Hongping; Niu, Zhendong; Zhang, Chunxia; Ma, Jing; Chen, Jie

2016-01-01

Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker, and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance.

A hybrid CNN feature model for pulmonary nodule malignancy risk differentiation.

PubMed

Wang, Huafeng; Zhao, Tingting; Li, Lihong Connie; Pan, Haixia; Liu, Wanquan; Gao, Haoqi; Han, Fangfang; Wang, Yuehai; Qi, Yifan; Liang, Zhengrong

2018-01-01

The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on differentiating the risk level of malignancy among the nodules detected in lung cancer screening. However, the existing CADx schemes tend to detect and analyze characteristics of pulmonary nodules from a statistical perspective according to local features only. Enlightened by the currently prevailing learning ability of convolutional neural network (CNN), which simulates human neural network for target recognition and our previously research on texture features, we present a hybrid model that takes into consideration of both global and local features for pulmonary nodule differentiation using the largest public database founded by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). By comparing three types of CNN models in which two of them were newly proposed by us, we observed that the multi-channel CNN model yielded the best discrimination in capacity of differentiating malignancy risk of the nodules based on the projection of distributions of extracted features. Moreover, CADx scheme using the new multi-channel CNN model outperformed our previously developed CADx scheme using the 3D texture feature analysis method, which increased the computed area under a receiver operating characteristic curve (AUC) from 0.9441 to 0.9702.

a Rough Set Decision Tree Based Mlp-Cnn for Very High Resolution Remotely Sensed Image Classification

NASA Astrophysics Data System (ADS)

Zhang, C.; Pan, X.; Zhang, S. Q.; Li, H. P.; Atkinson, P. M.

2017-09-01

Recent advances in remote sensing have witnessed a great amount of very high resolution (VHR) images acquired at sub-metre spatial resolution. These VHR remotely sensed data has post enormous challenges in processing, analysing and classifying them effectively due to the high spatial complexity and heterogeneity. Although many computer-aid classification methods that based on machine learning approaches have been developed over the past decades, most of them are developed toward pixel level spectral differentiation, e.g. Multi-Layer Perceptron (MLP), which are unable to exploit abundant spatial details within VHR images. This paper introduced a rough set model as a general framework to objectively characterize the uncertainty in CNN classification results, and further partition them into correctness and incorrectness on the map. The correct classification regions of CNN were trusted and maintained, whereas the misclassification areas were reclassified using a decision tree with both CNN and MLP. The effectiveness of the proposed rough set decision tree based MLP-CNN was tested using an urban area at Bournemouth, United Kingdom. The MLP-CNN, well capturing the complementarity between CNN and MLP through the rough set based decision tree, achieved the best classification performance both visually and numerically. Therefore, this research paves the way to achieve fully automatic and effective VHR image classification.

CNN Newsroom Guides. March 1-31, 1995.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily Cable News Network (CNN) Newsroom broadcasts for the month of March provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guide include: (1) investment terminology, Republican presidential nominations, the shuttle…

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

PubMed Central

Hoo-Chang, Shin; Roth, Holger R.; Gao, Mingchen; Lu, Le; Xu, Ziyue; Nogues, Isabella; Yao, Jianhua; Mollura, Daniel

2016-01-01

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets (i.e. ImageNet) and the revival of deep convolutional neural networks (CNN). CNNs enable learning data-driven, highly representative, layered hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a challenge. There are currently three major techniques that successfully employ CNNs to medical image classification: training the CNN from scratch, using off-the-shelf pre-trained CNN features, and conducting unsupervised CNN pre-training with supervised fine-tuning. Another effective method is transfer learning, i.e., fine-tuning CNN models (supervised) pre-trained from natural image dataset to medical image tasks (although domain transfer between two medical image datasets is also possible). In this paper, we exploit three important, but previously understudied factors of employing deep convolutional neural networks to computer-aided detection problems. We first explore and evaluate different CNN architectures. The studied models contain 5 thousand to 160 million parameters, and vary in numbers of layers. We then evaluate the influence of dataset scale and spatial image context on performance. Finally, we examine when and why transfer learning from pre-trained ImageNet (via fine-tuning) can be useful. We study two specific computeraided detection (CADe) problems, namely thoraco-abdominal lymph node (LN) detection and interstitial lung disease (ILD) classification. We achieve the state-of-the-art performance on the mediastinal LN detection, with 85% sensitivity at 3 false positive per patient, and report the first five-fold cross-validation classification results on predicting axial CT slices with ILD categories. Our extensive empirical evaluation, CNN model analysis and valuable insights can be extended to the design of high performance

CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes.

PubMed

White, Clarence; Ismail, Hamid D; Saigo, Hiroto; Kc, Dukka B

2017-12-28

The β-Lactamase (BL) enzyme family is an important class of enzymes that plays a key role in bacterial resistance to antibiotics. As the newly identified number of BL enzymes is increasing daily, it is imperative to develop a computational tool to classify the newly identified BL enzymes into one of its classes. There are two types of classification of BL enzymes: Molecular Classification and Functional Classification. Existing computational methods only address Molecular Classification and the performance of these existing methods is unsatisfactory. We addressed the unsatisfactory performance of the existing methods by implementing a Deep Learning approach called Convolutional Neural Network (CNN). We developed CNN-BLPred, an approach for the classification of BL proteins. The CNN-BLPred uses Gradient Boosted Feature Selection (GBFS) in order to select the ideal feature set for each BL classification. Based on the rigorous benchmarking of CCN-BLPred using both leave-one-out cross-validation and independent test sets, CCN-BLPred performed better than the other existing algorithms. Compared with other architectures of CNN, Recurrent Neural Network, and Random Forest, the simple CNN architecture with only one convolutional layer performs the best. After feature extraction, we were able to remove ~95% of the 10,912 features using Gradient Boosted Trees. During 10-fold cross validation, we increased the accuracy of the classic BL predictions by 7%. We also increased the accuracy of Class A, Class B, Class C, and Class D performance by an average of 25.64%. The independent test results followed a similar trend. We implemented a deep learning algorithm known as Convolutional Neural Network (CNN) to develop a classifier for BL classification. Combined with feature selection on an exhaustive feature set and using balancing method such as Random Oversampling (ROS), Random Undersampling (RUS) and Synthetic Minority Oversampling Technique (SMOTE), CNN-BLPred performs

A CNN Regression Approach for Real-Time 2D/3D Registration.

PubMed

Shun Miao; Wang, Z Jane; Rui Liao

2016-05-01

In this paper, we present a Convolutional Neural Network (CNN) regression approach to address the two major limitations of existing intensity-based 2-D/3-D registration technology: 1) slow computation and 2) small capture range. Different from optimization-based methods, which iteratively optimize the transformation parameters over a scalar-valued metric function representing the quality of the registration, the proposed method exploits the information embedded in the appearances of the digitally reconstructed radiograph and X-ray images, and employs CNN regressors to directly estimate the transformation parameters. An automatic feature extraction step is introduced to calculate 3-D pose-indexed features that are sensitive to the variables to be regressed while robust to other factors. The CNN regressors are then trained for local zones and applied in a hierarchical manner to break down the complex regression task into multiple simpler sub-tasks that can be learned separately. Weight sharing is furthermore employed in the CNN regression model to reduce the memory footprint. The proposed approach has been quantitatively evaluated on 3 potential clinical applications, demonstrating its significant advantage in providing highly accurate real-time 2-D/3-D registration with a significantly enlarged capture range when compared to intensity-based methods.

CNN Newsroom Guides: April 3-28, 1995.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily Cable News Network (CNN) Newsroom broadcasts for the month of April provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guide include: (1) reckless driving, hearing impairment, ancient to modern cities,…

Embrace the Chaos

ERIC Educational Resources Information Center

Huwe, Terence K.

2009-01-01

"Embracing the chaos" is an ongoing challenge for librarians. Embracing the chaos means librarians must have a plan for responding to the flood of new products, widgets, web tools, and gizmos that students use daily. In this article, the author argues that library instruction and access services have been grappling with that chaos with…

An Amino-Terminal Polo Kinase Interaction Motif Acts in the Regulation of Centrosome Formation and Reveals a Novel Function for centrosomin (cnn) in Drosophila

PubMed Central

Eisman, Robert C.; Phelps, Melissa A. S.; Kaufman, Thomas

2015-01-01

The formation of the pericentriolar matrix (PCM) and a fully functional centrosome in syncytial Drosophila melanogaster embryos requires the rapid transport of Cnn during initiation of the centrosome replication cycle. We show a Cnn and Polo kinase interaction is apparently required during embryogenesis and involves the exon 1A-initiating coding exon, suggesting a subset of Cnn splice variants is regulated by Polo kinase. During PCM formation exon 1A Cnn-Long Form proteins likely bind Polo kinase before phosphorylation by Polo for Cnn transport to the centrosome. Loss of either of these interactions in a portion of the total Cnn protein pool is sufficient to remove native Cnn from the pool, thereby altering the normal localization dynamics of Cnn to the PCM. Additionally, Cnn-Short Form proteins are required for polar body formation, a process known to require Polo kinase after the completion of meiosis. Exon 1A Cnn-LF and Cnn-SF proteins, in conjunction with Polo kinase, are required at the completion of meiosis and for the formation of functional centrosomes during early embryogenesis. PMID:26447129

Chaos as a Social Determinant of Child Health: Reciprocal Associations?

PubMed Central

Schmeer, Kammi K.; Taylor, Miles

2013-01-01

This study informs the social determinants of child health by exploring an understudied aspect of children’s social contexts: chaos. Chaos has been conceptualized as crowded, noisy, disorganized, unpredictable settings for child development (Evans et al., 2010). We measure chaos at two levels of children’s ecological environment - the microsystem (household) and the mesosystem (work-family-child care nexus) – and at two points in early childhood (ages 3 and 5). Using data from the Fragile Families and Child Wellbeing Study (N=3288), a study of predominantly low-income women and their partners in large US cities, we develop structural equation models that assess how maternal-rated child health (also assessed at ages 3 and 5) is associated with latent constructs of chaos, and whether there are important reciprocal effects. Autoregressive crosslagged path analysis suggest that increasing chaos (at both the household and maternal work levels) is associated with worse child health, controlling for key confounders like household economic status, family structure, and maternal health status. Child health has little effect on chaos, providing further support for the hypothesis that chaos is an important social determinant of child health in this sample of relatively disadvantaged children. This suggests child health may be improved by supporting families in ways that reduce chaos in their home and work/family environments, and that as researchers move beyond SES, race, and family structure to explore other sources of health inequalities, chaos and its proximate determinants may be a promising avenue for future research. PMID:23541250

Chaos in neurons and its application: perspective of chaos engineering.

PubMed

Hirata, Yoshito; Oku, Makito; Aihara, Kazuyuki

2012-12-01

We review our recent work on chaos in neurons and its application to neural networks from perspective of chaos engineering. Especially, we analyze a dataset of a squid giant axon by newly combining our previous work of identifying Devaney's chaos with surrogate data analysis, and show that an axon can behave chaotically. Based on this knowledge, we use a chaotic neuron model to investigate possible information processing in the brain.

Synthesizing folded band chaos.

PubMed

Corron, Ned J; Hayes, Scott T; Pethel, Shawn D; Blakely, Jonathan N

2007-04-01

A randomly driven linear filter that synthesizes Lorenz-like, reverse-time chaos is shown also to produce Rössler-like folded band wave forms when driven using a different encoding of the random source. The relationship between the topological entropy of the random source, dissipation in the linear filter, and the positive Lyapunov exponent for the reverse-time wave form is exposed. The two drive encodings are viewed as grammar restrictions on a more general encoding that produces a chaotic superset encompassing both the Lorenz butterfly and Rössler folded band paradigms of nonlinear dynamics.

Building CHAOS: An Operating System for Livermore Linux Clusters

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

Garlick, J E; Dunlap, C M

2003-02-21

The Livermore Computing (LC) Linux Integration and Development Project (the Linux Project) produces and supports the Clustered High Availability Operating System (CHAOS), a cluster operating environment based on Red Hat Linux. Each CHAOS release begins with a set of requirements and ends with a formally tested, packaged, and documented release suitable for use on LC's production Linux clusters. One characteristic of CHAOS is that component software packages come from different sources under varying degrees of project control. Some are developed by the Linux Project, some are developed by other LC projects, some are external open source projects, and some aremore » commercial software packages. A challenge to the Linux Project is to adhere to release schedules and testing disciplines in a diverse, highly decentralized development environment. Communication channels are maintained for externally developed packages in order to obtain support, influence development decisions, and coordinate/understand release schedules. The Linux Project embraces open source by releasing locally developed packages under open source license, by collaborating with open source projects where mutually beneficial, and by preferring open source over proprietary software. Project members generally use open source development tools. The Linux Project requires system administrators and developers to work together to resolve problems that arise in production. This tight coupling of production and development is a key strategy for making a product that directly addresses LC's production requirements. It is another challenge to balance support and development activities in such a way that one does not overwhelm the other.« less

Divide and Conquer-Based 1D CNN Human Activity Recognition Using Test Data Sharpening.

PubMed

Cho, Heeryon; Yoon, Sang Min

2018-04-01

Human Activity Recognition (HAR) aims to identify the actions performed by humans using signals collected from various sensors embedded in mobile devices. In recent years, deep learning techniques have further improved HAR performance on several benchmark datasets. In this paper, we propose one-dimensional Convolutional Neural Network (1D CNN) for HAR that employs a divide and conquer-based classifier learning coupled with test data sharpening. Our approach leverages a two-stage learning of multiple 1D CNN models; we first build a binary classifier for recognizing abstract activities, and then build two multi-class 1D CNN models for recognizing individual activities. We then introduce test data sharpening during prediction phase to further improve the activity recognition accuracy. While there have been numerous researches exploring the benefits of activity signal denoising for HAR, few researches have examined the effect of test data sharpening for HAR. We evaluate the effectiveness of our approach on two popular HAR benchmark datasets, and show that our approach outperforms both the two-stage 1D CNN-only method and other state of the art approaches.

Single-image-based Rain Detection and Removal via CNN

NASA Astrophysics Data System (ADS)

Chen, Tianyi; Fu, Chengzhou

2018-04-01

The quality of the image is degraded by rain streaks, which have negative impact when we extract image features for many visual tasks, such as feature extraction for classification and recognition, tracking, surveillance and autonomous navigation. Hence, it is necessary to detect and remove rain streaks from single images, which is a challenging problem since we have no spatial-temporal information of rain streaks compared to the dynamic video stream. Inspired by the priori that the rain streaks have almost the same feature, such as the direction or the thickness, although they are in different types of real-world images. The paper aims at proposing an effective convolutional neural network (CNN) to detect and remove rain streaks from single image. Two models of synthesized rainy image, linear additive composite model (LACM model) and screen blend model (SCM model), are considered in this paper. The main idea is that it is easier for our CNN network to find the mapping between the rainy image and rain streaks than between the rainy image and clean image. The reason is that rain streaks have fixed features, but clean images have various features. The experiments show that the designed CNN network outperforms state-of-the-art approaches on both synthesized and real-world images, which indicates the effectiveness of our proposed framework.

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

PubMed

Ren, Shaoqing; He, Kaiming; Girshick, Ross; Sun, Jian

2017-06-01

State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced the running time of these detection networks, exposing region proposal computation as a bottleneck. In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals. An RPN is a fully convolutional network that simultaneously predicts object bounds and objectness scores at each position. The RPN is trained end-to-end to generate high-quality region proposals, which are used by Fast R-CNN for detection. We further merge RPN and Fast R-CNN into a single network by sharing their convolutional features-using the recently popular terminology of neural networks with 'attention' mechanisms, the RPN component tells the unified network where to look. For the very deep VGG-16 model [3] , our detection system has a frame rate of 5 fps (including all steps) on a GPU, while achieving state-of-the-art object detection accuracy on PASCAL VOC 2007, 2012, and MS COCO datasets with only 300 proposals per image. In ILSVRC and COCO 2015 competitions, Faster R-CNN and RPN are the foundations of the 1st-place winning entries in several tracks. Code has been made publicly available.

Low-Grade Glioma Segmentation Based on CNN with Fully Connected CRF

PubMed Central

Li, Zeju; Shi, Zhifeng; Guo, Yi; Chen, Liang; Mao, Ying

2017-01-01

This work proposed a novel automatic three-dimensional (3D) magnetic resonance imaging (MRI) segmentation method which would be widely used in the clinical diagnosis of the most common and aggressive brain tumor, namely, glioma. The method combined a multipathway convolutional neural network (CNN) and fully connected conditional random field (CRF). Firstly, 3D information was introduced into the CNN which makes more accurate recognition of glioma with low contrast. Then, fully connected CRF was added as a postprocessing step which purposed more delicate delineation of glioma boundary. The method was applied to T2flair MRI images of 160 low-grade glioma patients. With 59 cases of data training and manual segmentation as the ground truth, the Dice similarity coefficient (DSC) of our method was 0.85 for the test set of 101 MRI images. The results of our method were better than those of another state-of-the-art CNN method, which gained the DSC of 0.76 for the same dataset. It proved that our method could produce better results for the segmentation of low-grade gliomas. PMID:29065666

Low-Grade Glioma Segmentation Based on CNN with Fully Connected CRF.

PubMed

Li, Zeju; Wang, Yuanyuan; Yu, Jinhua; Shi, Zhifeng; Guo, Yi; Chen, Liang; Mao, Ying

2017-01-01

This work proposed a novel automatic three-dimensional (3D) magnetic resonance imaging (MRI) segmentation method which would be widely used in the clinical diagnosis of the most common and aggressive brain tumor, namely, glioma. The method combined a multipathway convolutional neural network (CNN) and fully connected conditional random field (CRF). Firstly, 3D information was introduced into the CNN which makes more accurate recognition of glioma with low contrast. Then, fully connected CRF was added as a postprocessing step which purposed more delicate delineation of glioma boundary. The method was applied to T2flair MRI images of 160 low-grade glioma patients. With 59 cases of data training and manual segmentation as the ground truth, the Dice similarity coefficient (DSC) of our method was 0.85 for the test set of 101 MRI images. The results of our method were better than those of another state-of-the-art CNN method, which gained the DSC of 0.76 for the same dataset. It proved that our method could produce better results for the segmentation of low-grade gliomas.

An Amino-Terminal Polo Kinase Interaction Motif Acts in the Regulation of Centrosome Formation and Reveals a Novel Function for centrosomin (cnn) in Drosophila.

PubMed

Eisman, Robert C; Phelps, Melissa A S; Kaufman, Thomas

2015-10-01

The formation of the pericentriolar matrix (PCM) and a fully functional centrosome in syncytial Drosophila melanogaster embryos requires the rapid transport of Cnn during initiation of the centrosome replication cycle. We show a Cnn and Polo kinase interaction is apparently required during embryogenesis and involves the exon 1A-initiating coding exon, suggesting a subset of Cnn splice variants is regulated by Polo kinase. During PCM formation exon 1A Cnn-Long Form proteins likely bind Polo kinase before phosphorylation by Polo for Cnn transport to the centrosome. Loss of either of these interactions in a portion of the total Cnn protein pool is sufficient to remove native Cnn from the pool, thereby altering the normal localization dynamics of Cnn to the PCM. Additionally, Cnn-Short Form proteins are required for polar body formation, a process known to require Polo kinase after the completion of meiosis. Exon 1A Cnn-LF and Cnn-SF proteins, in conjunction with Polo kinase, are required at the completion of meiosis and for the formation of functional centrosomes during early embryogenesis. Copyright © 2015 by the Genetics Society of America.

Chaos in Environmental Education.

ERIC Educational Resources Information Center

Hardy, Joy

1999-01-01

Explores chaos theory, the evolutionary capacity of chaotic systems, and the philosophical implications of chaos theory in general and for education. Compares the relationships between curriculum vision based on chaos theory and critical education for the environment. (Author/CCM)

Using CNN Features to Better Understand What Makes Visual Artworks Special.

PubMed

Brachmann, Anselm; Barth, Erhardt; Redies, Christoph

2017-01-01

One of the goal of computational aesthetics is to understand what is special about visual artworks. By analyzing image statistics, contemporary methods in computer vision enable researchers to identify properties that distinguish artworks from other (non-art) types of images. Such knowledge will eventually allow inferences with regard to the possible neural mechanisms that underlie aesthetic perception in the human visual system. In the present study, we define measures that capture variances of features of a well-established Convolutional Neural Network (CNN), which was trained on millions of images to recognize objects. Using an image dataset that represents traditional Western, Islamic and Chinese art, as well as various types of non-art images, we show that we need only two variance measures to distinguish between the artworks and non-art images with a high classification accuracy of 93.0%. Results for the first variance measure imply that, in the artworks, the subregions of an image tend to be filled with pictorial elements, to which many diverse CNN features respond ( richness of feature responses). Results for the second measure imply that this diversity is tied to a relatively large variability of the responses of individual CNN feature across the subregions of an image. We hypothesize that this combination of richness and variability of CNN feature responses is one of properties that makes traditional visual artworks special. We discuss the possible neural underpinnings of this perceptual quality of artworks and propose to study the same quality also in other types of aesthetic stimuli, such as music and literature.

Using CNN Features to Better Understand What Makes Visual Artworks Special

PubMed Central

Brachmann, Anselm; Barth, Erhardt; Redies, Christoph

2017-01-01

One of the goal of computational aesthetics is to understand what is special about visual artworks. By analyzing image statistics, contemporary methods in computer vision enable researchers to identify properties that distinguish artworks from other (non-art) types of images. Such knowledge will eventually allow inferences with regard to the possible neural mechanisms that underlie aesthetic perception in the human visual system. In the present study, we define measures that capture variances of features of a well-established Convolutional Neural Network (CNN), which was trained on millions of images to recognize objects. Using an image dataset that represents traditional Western, Islamic and Chinese art, as well as various types of non-art images, we show that we need only two variance measures to distinguish between the artworks and non-art images with a high classification accuracy of 93.0%. Results for the first variance measure imply that, in the artworks, the subregions of an image tend to be filled with pictorial elements, to which many diverse CNN features respond (richness of feature responses). Results for the second measure imply that this diversity is tied to a relatively large variability of the responses of individual CNN feature across the subregions of an image. We hypothesize that this combination of richness and variability of CNN feature responses is one of properties that makes traditional visual artworks special. We discuss the possible neural underpinnings of this perceptual quality of artworks and propose to study the same quality also in other types of aesthetic stimuli, such as music and literature. PMID:28588537

Controlling chaos-assisted directed transport via quantum resonance.

PubMed

Tan, Jintao; Zou, Mingliang; Luo, Yunrong; Hai, Wenhua

2016-06-01

We report on the first demonstration of chaos-assisted directed transport of a quantum particle held in an amplitude-modulated and tilted optical lattice, through a resonance-induced double-mean displacement relating to the true classically chaotic orbits. The transport velocity is controlled by the driving amplitude and the sign of tilt, and also depends on the phase of the initial state. The chaos-assisted transport feature can be verified experimentally by using a source of single atoms to detect the double-mean displacement one by one, and can be extended to different scientific fields.

Controlling chaos-assisted directed transport via quantum resonance

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

Tan, Jintao; Zou, Mingliang; Luo, Yunrong

2016-06-15

We report on the first demonstration of chaos-assisted directed transport of a quantum particle held in an amplitude-modulated and tilted optical lattice, through a resonance-induced double-mean displacement relating to the true classically chaotic orbits. The transport velocity is controlled by the driving amplitude and the sign of tilt, and also depends on the phase of the initial state. The chaos-assisted transport feature can be verified experimentally by using a source of single atoms to detect the double-mean displacement one by one, and can be extended to different scientific fields.

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.

PubMed

Shin, Hoo-Chang; Roth, Holger R; Gao, Mingchen; Lu, Le; Xu, Ziyue; Nogues, Isabella; Yao, Jianhua; Mollura, Daniel; Summers, Ronald M

2016-05-01

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly representative, hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a challenge. There are currently three major techniques that successfully employ CNNs to medical image classification: training the CNN from scratch, using off-the-shelf pre-trained CNN features, and conducting unsupervised CNN pre-training with supervised fine-tuning. Another effective method is transfer learning, i.e., fine-tuning CNN models pre-trained from natural image dataset to medical image tasks. In this paper, we exploit three important, but previously understudied factors of employing deep convolutional neural networks to computer-aided detection problems. We first explore and evaluate different CNN architectures. The studied models contain 5 thousand to 160 million parameters, and vary in numbers of layers. We then evaluate the influence of dataset scale and spatial image context on performance. Finally, we examine when and why transfer learning from pre-trained ImageNet (via fine-tuning) can be useful. We study two specific computer-aided detection (CADe) problems, namely thoraco-abdominal lymph node (LN) detection and interstitial lung disease (ILD) classification. We achieve the state-of-the-art performance on the mediastinal LN detection, and report the first five-fold cross-validation classification results on predicting axial CT slices with ILD categories. Our extensive empirical evaluation, CNN model analysis and valuable insights can be extended to the design of high performance CAD systems for other medical imaging tasks.

CNNEDGEPOT: CNN based edge detection of 2D near surface potential field data

NASA Astrophysics Data System (ADS)

Aydogan, D.

2012-09-01

All anomalies are important in the interpretation of gravity and magnetic data because they indicate some important structural features. One of the advantages of using gravity or magnetic data for searching contacts is to be detected buried structures whose signs could not be seen on the surface. In this paper, a general view of the cellular neural network (CNN) method with a large scale nonlinear circuit is presented focusing on its image processing applications. The proposed CNN model is used consecutively in order to extract body and body edges. The algorithm is a stochastic image processing method based on close neighborhood relationship of the cells and optimization of A, B and I matrices entitled as cloning template operators. Setting up a CNN (continues time cellular neural network (CTCNN) or discrete time cellular neural network (DTCNN)) for a particular task needs a proper selection of cloning templates which determine the dynamics of the method. The proposed algorithm is used for image enhancement and edge detection. The proposed method is applied on synthetic and field data generated for edge detection of near-surface geological bodies that mask each other in various depths and dimensions. The program named as CNNEDGEPOT is a set of functions written in MATLAB software. The GUI helps the user to easily change all the required CNN model parameters. A visual evaluation of the outputs due to DTCNN and CTCNN are carried out and the results are compared with each other. These examples demonstrate that in detecting the geological features the CNN model can be used for visual interpretation of near surface gravity or magnetic anomaly maps.

Respiratory motion correction for free-breathing 3D abdominal MRI using CNN-based image registration: a feasibility study.

PubMed

Lv, Jun; Yang, Ming; Zhang, Jue; Wang, Xiaoying

2018-02-01

Free-breathing abdomen imaging requires non-rigid motion registration of unavoidable respiratory motion in three-dimensional undersampled data sets. In this work, we introduce an image registration method based on the convolutional neural network (CNN) to obtain motion-free abdominal images throughout the respiratory cycle. Abdominal data were acquired from 10 volunteers using a 1.5 T MRI system. The respiratory signal was extracted from the central-space spokes, and the acquired data were reordered in three bins according to the corresponding breathing signal. Retrospective image reconstruction of the three near-motion free respiratory phases was performed using non-Cartesian iterative SENSE reconstruction. Then, we trained a CNN to analyse the spatial transform among the different bins. This network could generate the displacement vector field and be applied to perform registration on unseen image pairs. To demonstrate the feasibility of this registration method, we compared the performance of three different registration approaches for accurate image fusion of three bins: non-motion corrected (NMC), local affine registration method (LREG) and CNN. Visualization of coronal images indicated that LREG had caused broken blood vessels, while the vessels of the CNN were sharper and more consecutive. As shown in the sagittal view, compared to NMC and CNN, distorted and blurred liver contours were caused by LREG. At the same time, zoom-in axial images presented that the vessels were delineated more clearly by CNN than LREG. The statistical results of the signal-to-noise ratio, visual score, vessel sharpness and registration time over all volunteers were compared among the NMC, LREG and CNN approaches. The SNR indicated that the CNN acquired the best image quality (207.42 ± 96.73), which was better than NMC (116.67 ± 44.70) and LREG (187.93 ± 96.68). The image visual score agreed with SNR, marking CNN (3.85 ± 0.12) as the best, followed by LREG (3.43 ± 0

Defining chaos.

PubMed

Hunt, Brian R; Ott, Edward

2015-09-01

In this paper, we propose, discuss, and illustrate a computationally feasible definition of chaos which can be applied very generally to situations that are commonly encountered, including attractors, repellers, and non-periodically forced systems. This definition is based on an entropy-like quantity, which we call "expansion entropy," and we define chaos as occurring when this quantity is positive. We relate and compare expansion entropy to the well-known concept of topological entropy to which it is equivalent under appropriate conditions. We also present example illustrations, discuss computational implementations, and point out issues arising from attempts at giving definitions of chaos that are not entropy-based.

CNN Newsroom Classroom Guides. March 1-31, 1997.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of March, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: monkeys cloned in Oregon, Iran suffers massive earthquake, tornados affect…

CNN Newsroom Classroom Guides, May 1-31, 1996.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily Cable News Network (CNN) Newsroom broadcasts for the month of May, provide program rundowns, suggestions for class activities and discussion, student handouts, and lists of related news terms. Topics covered include: United States-Israel anti-terrorism accord, the comeback of baseball…

CNN Newsroom Classroom Guides. November 1-30, 1996.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of November, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: presidential candidates travel the United States searching for votes, FBI…

CNN Newsroom Classroom Guides. December 1-31, 1996.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for December 1-20, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: eighth annual World AIDS Day, protests in Belgrade, Mother Theresa's condition…

Hand pose estimation in depth image using CNN and random forest

NASA Astrophysics Data System (ADS)

Chen, Xi; Cao, Zhiguo; Xiao, Yang; Fang, Zhiwen

2018-03-01

Thanks to the availability of low cost depth cameras, like Microsoft Kinect, 3D hand pose estimation attracted special research attention in these years. Due to the large variations in hand`s viewpoint and the high dimension of hand motion, 3D hand pose estimation is still challenging. In this paper we propose a two-stage framework which joint with CNN and Random Forest to boost the performance of hand pose estimation. First, we use a standard Convolutional Neural Network (CNN) to regress the hand joints` locations. Second, using a Random Forest to refine the joints from the first stage. In the second stage, we propose a pyramid feature which merges the information flow of the CNN. Specifically, we get the rough joints` location from first stage, then rotate the convolutional feature maps (and image). After this, for each joint, we map its location to each feature map (and image) firstly, then crop features at each feature map (and image) around its location, put extracted features to Random Forest to refine at last. Experimentally, we evaluate our proposed method on ICVL dataset and get the mean error about 11mm, our method is also real-time on a desktop.

Divide and Conquer-Based 1D CNN Human Activity Recognition Using Test Data Sharpening †

PubMed Central

Yoon, Sang Min

2018-01-01

Human Activity Recognition (HAR) aims to identify the actions performed by humans using signals collected from various sensors embedded in mobile devices. In recent years, deep learning techniques have further improved HAR performance on several benchmark datasets. In this paper, we propose one-dimensional Convolutional Neural Network (1D CNN) for HAR that employs a divide and conquer-based classifier learning coupled with test data sharpening. Our approach leverages a two-stage learning of multiple 1D CNN models; we first build a binary classifier for recognizing abstract activities, and then build two multi-class 1D CNN models for recognizing individual activities. We then introduce test data sharpening during prediction phase to further improve the activity recognition accuracy. While there have been numerous researches exploring the benefits of activity signal denoising for HAR, few researches have examined the effect of test data sharpening for HAR. We evaluate the effectiveness of our approach on two popular HAR benchmark datasets, and show that our approach outperforms both the two-stage 1D CNN-only method and other state of the art approaches. PMID:29614767

CNN Newsroom Classroom Guides. March 1-31, 1996.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of March, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: negative campaign ads, the end of the Sarajevo siege, alternative medicine in…

CNN Newsroom Classroom Guides. May 2-31, 1994.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of May provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: (1) the Palestinian Liberation Organization (PLO) and Palestine, Hawaiian…

CNN Newsroom Classroom Guides. January 1-31, 1997.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of January, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: U.S. House of Representatives prepares for ethics battle, diplomatic immunity,…

CNN Newsroom Classroom Guides. December 1-31, 1997.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of December, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: Japan hosts the Climate Change Conference, space shuttle is unable to deploy…

CNN Newsroom Classroom Guides. February 1-28, 1998.

ERIC Educational Resources Information Center

Turner Educational Services, Inc., Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of February, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: United States lobbies for support for possible air strike against Iraq,…

CNN Newsroom Classroom Guides. March 14-31, 1994.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of March provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: (1) Bophuthatswana, Best Quest, language immersion, Bosnia diaries, Nepal,…

CNN Newsroom Classroom Guides. September 1-30, 1994.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of August provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: (1) truce in Northern Ireland, school censorship, scientific method, burial…

CNN Newsroom Classroom Guides, November 1-30, 1995.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of November, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: the Bosnia peace talks, hot-air balloons, salt…

CNN Newsroom Classroom Guides. May 1-31, 1997.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of May, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: Chelsea Clinton decides to attend Stanford University, Zaire's president and rebel…

CNN Newsroom Classroom Guides. August 1-31, 1994.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of August provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: (1) Haiti, exploration of Mars, Rwandan refugees, Goodwill Games, Paris…

CNN Newsroom Classroom Guides. February 1-29, 1996.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) broadcasts for the month of February, 1996 provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Each daily guide includes a Black History Month biographical profile. Other topics covered…

CNN Newsroom Classroom Guides. April 1-30, 1998.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

CNN Newsroom is a daily 15-minute commercial-free news program specifically produced for classroom use and provided free to participating schools. These daily Classroom Guides are designed to accompany the broadcast, and contain activities for discussing top stories, headlines, and other current events topics; each guide also includes World Wide…

CNN Newsroom Classroom Guides. April 1-30, 1997.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of April, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Headlines include: Arab League boycott, Zaire peace talks, Russia and Belarus sign agreement,…

CNN Newsroom Classroom Guides, December 1-31, 1995.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the first half of the month of December, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered include: President Clinton's visit to Northern Ireland,…

CNN Newsroom Classroom Guides, October 1-31, 1996.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of October, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: the Middle East peace summit in Washington, DC, Israel's Netanyahu and…

CNN Newsroom Classroom Guides. January 1-31, 1996.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of January, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: teen obesity, the Yangtze River Dam and its hydroelectric…

CNN Newsroom Classroom Guides. June 1-30, 1994.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of June provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: (1) Congressman Dan Rostenkowski, D-Day, cars and Singapore, Rodney King civil…

CNN Newsroom Classroom Guides. October 1-31, 1997.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of October, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: immigrants illegally in the United States try to gain legal status before being…

CNN Newsroom Classroom Guides. September 1-30, 1995.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of September, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: the women's conference in China, "No Man Is an…

CNN Newsroom Classroom Guides. March 1-31, 1998.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of March, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: United Nations (UN) and Iraq interpret their recent deal in different ways,…

CNN Newsroom Classroom Guides. February 1-28, 1997.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of February, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: elections in Pakistan for a new prime minister, U.S. President Clinton unveils…

CNN Newsroom Classroom Guides. July 1-31, 1995.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of July provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: (1) British Prime Minister John Major, trade and Tijuana, sports physics, and…

Gastrointestinal bleeding detection in wireless capsule endoscopy images using handcrafted and CNN features.

PubMed

Xiao Jia; Meng, Max Q-H

2017-07-01

Gastrointestinal (GI) bleeding detection plays an essential role in wireless capsule endoscopy (WCE) examination. In this paper, we present a new approach for WCE bleeding detection that combines handcrafted (HC) features and convolutional neural network (CNN) features. Compared with our previous work, a smaller-scale CNN architecture is constructed to lower the computational cost. In experiments, we show that the proposed strategy is highly capable when training data is limited, and yields comparable or better results than the latest methods.

CNN Newsroom Classroom Guides. April 1-29, 1994.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of April provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: (1) peace in the Middle East, Tom Bradley, and minority superheroes (April 1);…

CNN Newsroom Classroom Guides. May 1-31, 1995.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of May provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guide include: (1) security systems and security at the Olympics, drawing to scale, civil war in…

CNN Newsroom Classroom Guides, November 1-30, 1997.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides, designed to accompany the daily CNN (Cable News Network) Newsroom broadcasts for the month of November 1997, provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics include: U.S. leaders call for the use of force as Iraq refuses to permit access…

CNN Newsroom Classroom Guides. June 1-30, 1995.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of June provide program rundowns, suggestions for class activities and discussions, student handouts, and a list of related news terms. Topics covered by the guides include: (1) amusement park physics, media resources and literacy, and the war in Bosnia…

CNN Newsroom Classroom Guides. July 1-29, 1994.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

These classroom guides for the daily CNN (Cable News Network) Newsroom broadcasts for the month of July provide program rundowns, suggestions for class activities and discussion, student handouts, and a list of related news terms. Topics covered by the guides include: (1) Yasser Arafat and online projects (July 1); (2) Yasser Arafat, athletes as…

Joint atmospheric turbulence detection and adaptive demodulation technique using the CNN for the OAM-FSO communication.

PubMed

Li, Jin; Zhang, Min; Wang, Danshi; Wu, Shaojun; Zhan, Yueying

2018-04-16

A novel joint atmospheric turbulence (AT) detection and adaptive demodulation technique based on convolutional neural network (CNN) are proposed for the OAM-based free-space optical (FSO) communication. The AT detecting accuracy (ATDA) and the adaptive demodulating accuracy (ADA) of the 4-OAM, 8-OAM, 16-OAM FSO communication systems over computer-simulated 1000-m turbulent channels with 4, 6, 10 kinds of classic ATs are investigated, respectively. Compared to previous approaches using the self-organizing mapping (SOM), deep neural network (DNN) and other CNNs, the proposed CNN achieves the highest ATDA and ADA due to the advanced multi-layer representation learning without feature extractors designed carefully by numerous experts. For the AT detection, the ATDA of CNN is near 95.2% for 6 kinds of typical ATs, in cases of both weak and strong ATs. For the adaptive demodulation of optical vortices (OV) carrying OAM modes, the ADA of CNN is about 99.8% for the 8-OAM system over the computer-simulated 1000-m free-space strong turbulent link. In addition, the effects of image resolution, iteration number, activation functions and the structure of the CNN are also studied comprehensively. The proposed technique has the potential to be embedded in charge-coupled device (CCD) cameras deployed at the receiver to improve the reliability and flexibility for the OAM-FSO communication.

CNN Newsroom Classroom Guides. May 1-29, 1998.

ERIC Educational Resources Information Center

Cable News Network, Atlanta, GA.

CNN Newsroom is a daily 15-minute commercial-free news program specifically produced for classroom use and provided free to participating schools. These guides are designed to accompany the program broadcasts for May 1-29, 1998. Top stories include: effects of a labor strike on Denmark's economy (May 1); the new currency of the European Union, the…

Chaos Modeling: An Introduction and Research Application.

ERIC Educational Resources Information Center

Newman, Isadore; And Others

1993-01-01

Introduces the basic concepts of chaos theory and chaos modeling. Relates chaos theory to qualitative research and factor analysis. Describes some current research in education and psychology using chaos theory. Claims that the philosophical implications of chaos theory have been misapplied in practical terms. (KS)

Does chaos assist localization or delocalization?

PubMed

Tan, Jintao; Lu, Gengbiao; Luo, Yunrong; Hai, Wenhua

2014-12-01

We aim at a long-standing contradiction between chaos-assisted tunneling and chaos-related localization study quantum transport of a single particle held in an amplitude-modulated and tilted optical lattice. We find some near-resonant regions crossing chaotic and regular regions in the parameter space, and demonstrate that chaos can heighten velocity of delocalization in the chaos-resonance overlapping regions, while chaos may aid localization in the other chaotic regions. The degree of localization enhances with increasing the distance between parameter points and near-resonant regions. The results could be useful for experimentally manipulating chaos-assisted transport of single particles in optical or solid-state lattices.

Pairwise domain adaptation module for CNN-based 2-D/3-D registration.

PubMed

Zheng, Jiannan; Miao, Shun; Jane Wang, Z; Liao, Rui

2018-04-01

Accurate two-dimensional to three-dimensional (2-D/3-D) registration of preoperative 3-D data and intraoperative 2-D x-ray images is a key enabler for image-guided therapy. Recent advances in 2-D/3-D registration formulate the problem as a learning-based approach and exploit the modeling power of convolutional neural networks (CNN) to significantly improve the accuracy and efficiency of 2-D/3-D registration. However, for surgery-related applications, collecting a large clinical dataset with accurate annotations for training can be very challenging or impractical. Therefore, deep learning-based 2-D/3-D registration methods are often trained with synthetically generated data, and a performance gap is often observed when testing the trained model on clinical data. We propose a pairwise domain adaptation (PDA) module to adapt the model trained on source domain (i.e., synthetic data) to target domain (i.e., clinical data) by learning domain invariant features with only a few paired real and synthetic data. The PDA module is designed to be flexible for different deep learning-based 2-D/3-D registration frameworks, and it can be plugged into any pretrained CNN model such as a simple Batch-Norm layer. The proposed PDA module has been quantitatively evaluated on two clinical applications using different frameworks of deep networks, demonstrating its significant advantages of generalizability and flexibility for 2-D/3-D medical image registration when a small number of paired real-synthetic data can be obtained.

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

PubMed

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

[Shedding light on chaos theory].

PubMed

Chou, Shieu-Ming

2004-06-01

Gleick (1987) said that only three twentieth century scientific theories would be important enough to continue be of use in the twenty-first century: The Theory of Relativity, Quantum Theory, and Chaos Theory. Chaos Theory has become a craze which is being used to forge a new scientific system. It has also been extensively applied in a variety of professions. The purpose of this article is to introduce chaos theory and its nursing applications. Chaos is a sign of regular order. This is to say that chaos theory emphasizes the intrinsic potential for regular order within disordered phenomena. It is to be hoped that this article will inspire more nursing scientists to apply this concept to clinical, research, or administrative fields in our profession.

Death and revival of chaos.

PubMed

Kaszás, Bálint; Feudel, Ulrike; Tél, Tamás

2016-12-01

We investigate the death and revival of chaos under the impact of a monotonous time-dependent forcing that changes its strength with a non-negligible rate. Starting on a chaotic attractor it is found that the complexity of the dynamics remains very pronounced even when the driving amplitude has decayed to rather small values. When after the death of chaos the strength of the forcing is increased again with the same rate of change, chaos is found to revive but with a different history. This leads to the appearance of a hysteresis in the complexity of the dynamics. To characterize these dynamics, the concept of snapshot attractors is used, and the corresponding ensemble approach proves to be superior to a single trajectory description, that turns out to be nonrepresentative. The death (revival) of chaos is manifested in a drop (jump) of the standard deviation of one of the phase-space coordinates of the ensemble; the details of this chaos-nonchaos transition depend on the ratio of the characteristic times of the amplitude change and of the internal dynamics. It is demonstrated that chaos cannot die out as long as underlying transient chaos is present in the parameter space. As a condition for a "quasistatically slow" switch-off, we derive an inequality which cannot be fulfilled in practice over extended parameter ranges where transient chaos is present. These observations need to be taken into account when discussing the implications of "climate change scenarios" in any nonlinear dynamical system.

Noise tolerant spatiotemporal chaos computing.

PubMed

Kia, Behnam; Kia, Sarvenaz; Lindner, John F; Sinha, Sudeshna; Ditto, William L

2014-12-01

We introduce and design a noise tolerant chaos computing system based on a coupled map lattice (CML) and the noise reduction capabilities inherent in coupled dynamical systems. The resulting spatiotemporal chaos computing system is more robust to noise than a single map chaos computing system. In this CML based approach to computing, under the coupled dynamics, the local noise from different nodes of the lattice diffuses across the lattice, and it attenuates each other's effects, resulting in a system with less noise content and a more robust chaos computing architecture.

Noise tolerant spatiotemporal chaos computing

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

Kia, Behnam; Kia, Sarvenaz; Ditto, William L.

We introduce and design a noise tolerant chaos computing system based on a coupled map lattice (CML) and the noise reduction capabilities inherent in coupled dynamical systems. The resulting spatiotemporal chaos computing system is more robust to noise than a single map chaos computing system. In this CML based approach to computing, under the coupled dynamics, the local noise from different nodes of the lattice diffuses across the lattice, and it attenuates each other's effects, resulting in a system with less noise content and a more robust chaos computing architecture.

Relativistic chaos is coordinate invariant.

PubMed

Motter, Adilson E

2003-12-05

The noninvariance of Lyapunov exponents in general relativity has led to the conclusion that chaos depends on the choice of the space-time coordinates. Strikingly, we uncover the transformation laws of Lyapunov exponents under general space-time transformations and we find that chaos, as characterized by positive Lyapunov exponents, is coordinate invariant. As a result, the previous conclusion regarding the noninvariance of chaos in cosmology, a major claim about chaos in general relativity, necessarily involves the violation of hypotheses required for a proper definition of the Lyapunov exponents.

Catalytic transfer hydrogenation with terdentate CNN ruthenium complexes: the influence of the base.

PubMed

Baratta, Walter; Siega, Katia; Rigo, Pierluigi

2007-01-01

The catalytic activity of the terdentate complex [RuCl(CNN)(dppb)] (A) [dppb=Ph(2)P(CH(2))(4)PPh(2); HCNN=6-(4'-methylphenyl)-2-pyridylmethylamine] in the transfer hydrogenation of acetophenone (S) with 2-propanol has been found to be dependent on the base concentration. The limit rate has been observed when NaOiPr is used in high excess (A/base molar ratio > 10). The amino-isopropoxide species [Ru(OiPr)(CNN)(dppb)] (B), which forms by reaction of A with sodium isopropoxide via displacement of the chloride, is catalytically active. The rate of conversion of acetophenone obeys second-order kinetics v=k[S][B] with the rate constants in the range 218+/-8 (40 degrees C) to 3000+/-70 M(-1) s(-1) (80 degrees C). The activation parameters, evaluated from the Eyring equation are DeltaH(++)=14.0+/-0.2 kcal mol(-1) and DeltaS(++)=-3.2 +/-0.5 eu. In a pre-equilibrium reaction with 2-propanol complex B gives the cationic species [Ru(CNN)(dppb)(HOiPr)](+)[OiPr](-) (C) with K approximately 2x10(-5) M. The hydride species [RuH(CNN)(dppb)] (H), which forms from B via beta-hydrogen elimination process, catalyzes the reduction of S and, importantly, its activity increases by addition of base. The catalytic behavior of the hydride H has been compared to that of the system A/NaOiPr (1:1 molar ratio) and indicates that the two systems are equivalent.

Chaos Criminology: A critical analysis

NASA Astrophysics Data System (ADS)

McCarthy, Adrienne L.

There has been a push since the early 1980's for a paradigm shift in criminology from a Newtonian-based ontology to one of quantum physics. Primarily this effort has taken the form of integrating Chaos Theory into Criminology into what this thesis calls 'Chaos Criminology'. However, with the melding of any two fields, terms and concepts need to be translated properly, which has yet to be done. In addition to proving a translation between fields, this thesis also uses a set of criteria to evaluate the effectiveness of the current use of Chaos Theory in Criminology. While the results of the theory evaluation reveal that the current Chaos Criminology work is severely lacking and in need of development, there is some promise in the development of Marx's dialectical materialism with Chaos Theory.

Teaching as Chaos

ERIC Educational Resources Information Center

Moseley, Bryan; Dustin, Daniel

2008-01-01

In this article, the authors advance a metaphor born of chaos theory that views the college classroom as a complex dynamical system. The authors reason further that "teaching as chaos" provides a more accurate representation of the teaching-learning process than the existing linear scientific metaphors on which traditional learning assessments are…

A novel cloning template designing method by using an artificial bee colony algorithm for edge detection of CNN based imaging sensors.

PubMed

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods.

A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors

PubMed Central

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods. PMID:22163903

Boosting CNN performance for lung texture classification using connected filtering

NASA Astrophysics Data System (ADS)

Tarando, Sebastián. Roberto; Fetita, Catalin; Kim, Young-Wouk; Cho, Hyoun; Brillet, Pierre-Yves

2018-02-01

Infiltrative lung diseases describe a large group of irreversible lung disorders requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. This paper presents an original image pre-processing framework based on locally connected filtering applied in multiresolution, which helps improving the learning process and boost the performance of CNN for lung texture classification. By removing the dense vascular network from images used by the CNN for lung classification, locally connected filters provide a better discrimination between different lung patterns and help regularizing the classification output. The approach was tested in a preliminary evaluation on a 10 patient database of various lung pathologies, showing an increase of 10% in true positive rate (on average for all the cases) with respect to the state of the art cascade of CNNs for this task.

Stochastic Estimation via Polynomial Chaos

DTIC Science & Technology

2015-10-01

AFRL-RW-EG-TR-2015-108 Stochastic Estimation via Polynomial Chaos Douglas V. Nance Air Force Research...COVERED (From - To) 20-04-2015 – 07-08-2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Stochastic Estimation via Polynomial Chaos ...This expository report discusses fundamental aspects of the polynomial chaos method for representing the properties of second order stochastic

Aram and Iani Chaos

NASA Technical Reports Server (NTRS)

2003-01-01

MGS MOC Release No. MOC2-344, 28 April 2003

This Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) image mosaic was constructed from data acquired by the MOC red wide angle camera. The large, circular feature in the upper left is Aram Chaos, an ancient impact crater filled with layered sedimentary rock that was later disrupted and eroded to form a blocky, 'chaotic' appearance. To the southeast of Aram Chaos, in the lower right of this picture, is Iani Chaos. The light-toned patches amid the large blocks of Iani Chaos are known from higher-resolution MOC images to be layered, sedimentary rock outcrops. The picture center is near 0.5oN, 20oW. Sunlight illuminates the scene from the left/upper left.

Chaos and noise.

PubMed

He, Temple; Habib, Salman

2013-09-01

Simple dynamical systems--with a small number of degrees of freedom--can behave in a complex manner due to the presence of chaos. Such systems are most often (idealized) limiting cases of more realistic situations. Isolating a small number of dynamical degrees of freedom in a realistically coupled system generically yields reduced equations with terms that can have a stochastic interpretation. In situations where both noise and chaos can potentially exist, it is not immediately obvious how Lyapunov exponents, key to characterizing chaos, should be properly defined. In this paper, we show how to do this in a class of well-defined noise-driven dynamical systems, derived from an underlying Hamiltonian model.

Electroencephalography Based Fusion Two-Dimensional (2D)-Convolution Neural Networks (CNN) Model for Emotion Recognition System.

PubMed

Kwon, Yea-Hoon; Shin, Sae-Byuk; Kim, Shin-Dug

2018-04-30

The purpose of this study is to improve human emotional classification accuracy using a convolution neural networks (CNN) model and to suggest an overall method to classify emotion based on multimodal data. We improved classification performance by combining electroencephalogram (EEG) and galvanic skin response (GSR) signals. GSR signals are preprocessed using by the zero-crossing rate. Sufficient EEG feature extraction can be obtained through CNN. Therefore, we propose a suitable CNN model for feature extraction by tuning hyper parameters in convolution filters. The EEG signal is preprocessed prior to convolution by a wavelet transform while considering time and frequency simultaneously. We use a database for emotion analysis using the physiological signals open dataset to verify the proposed process, achieving 73.4% accuracy, showing significant performance improvement over the current best practice models.

"Chaos Rules" Revisited

ERIC Educational Resources Information Center

Murphy, David

2011-01-01

About 20 years ago, while lost in the midst of his PhD research, the author mused over proposed titles for his thesis. He was pretty pleased with himself when he came up with "Chaos Rules" (the implied double meaning was deliberate), or more completely, "Chaos Rules: An Exploration of the Work of Instructional Designers in Distance Education." He…

CNN pincer ruthenium catalysts for hydrogenation and transfer hydrogenation of ketones: experimental and computational studies.

PubMed

Baratta, Walter; Baldino, Salvatore; Calhorda, Maria José; Costa, Paulo J; Esposito, Gennaro; Herdtweck, Eberhardt; Magnolia, Santo; Mealli, Carlo; Messaoudi, Abdelatif; Mason, Sax A; Veiros, Luis F

2014-10-13

Reaction of [RuCl(CNN)(dppb)] (1-Cl) (HCNN=2-aminomethyl-6-(4-methylphenyl)pyridine; dppb=Ph2 P(CH2 )4 PPh2 ) with NaOCH2 CF3 leads to the amine-alkoxide [Ru(CNN)(OCH2 CF3 )(dppb)] (1-OCH2 CF3 ), whose neutron diffraction study reveals a short RuO⋅⋅⋅HN bond length. Treatment of 1-Cl with NaOEt and EtOH affords the alkoxide [Ru(CNN)(OEt)(dppb)]⋅(EtOH)n (1-OEt⋅n EtOH), which equilibrates with the hydride [RuH(CNN)(dppb)] (1-H) and acetaldehyde. Compound 1-OEt⋅n EtOH reacts reversibly with H2 leading to 1-H and EtOH through dihydrogen splitting. NMR spectroscopic studies on 1-OEt⋅n EtOH and 1-H reveal hydrogen bond interactions and exchange processes. The chloride 1-Cl catalyzes the hydrogenation (5 atm of H2 ) of ketones to alcohols (turnover frequency (TOF) up to 6.5×10(4) h(-1) , 40 °C). DFT calculations were performed on the reaction of [RuH(CNN')(dmpb)] (2-H) (HCNN'=2-aminomethyl-6-(phenyl)pyridine; dmpb=Me2 P(CH2 )4 PMe2 ) with acetone and with one molecule of 2-propanol, in alcohol, with the alkoxide complex being the most stable species. In the first step, the Ru-hydride transfers one hydrogen atom to the carbon of the ketone, whereas the second hydrogen transfer from NH2 is mediated by the alcohol and leads to the key "amide" intermediate. Regeneration of the hydride complex may occur by reaction with 2-propanol or with H2 ; both pathways have low barriers and are alcohol assisted. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A bound on chaos

DOE PAGES

Maldacena, Juan; Shenker, Stephen H.; Stanford, Douglas

2016-08-17

We conjecture a sharp bound on the rate of growth of chaos in thermal quantum systems with a large number of degrees of freedom. Chaos can be diagnosed using an out-of-time-order correlation function closely related to the commutator of operators separated in time. We conjecture that the influence of chaos on this correlator can develop no faster than exponentially, with Lyapunov exponent λ L ≤ 2πk B T/ℏ. We give a precise mathematical argument, based on plausible physical assumptions, establishing this conjecture.

Hazardous gas detection for FTIR-based hyperspectral imaging system using DNN and CNN

NASA Astrophysics Data System (ADS)

Kim, Yong Chan; Yu, Hyeong-Geun; Lee, Jae-Hoon; Park, Dong-Jo; Nam, Hyun-Woo

2017-10-01

Recently, a hyperspectral imaging system (HIS) with a Fourier Transform InfraRed (FTIR) spectrometer has been widely used due to its strengths in detecting gaseous fumes. Even though numerous algorithms for detecting gaseous fumes have already been studied, it is still difficult to detect target gases properly because of atmospheric interference substances and unclear characteristics of low concentration gases. In this paper, we propose detection algorithms for classifying hazardous gases using a deep neural network (DNN) and a convolutional neural network (CNN). In both the DNN and CNN, spectral signal preprocessing, e.g., offset, noise, and baseline removal, are carried out. In the DNN algorithm, the preprocessed spectral signals are used as feature maps of the DNN with five layers, and it is trained by a stochastic gradient descent (SGD) algorithm (50 batch size) and dropout regularization (0.7 ratio). In the CNN algorithm, preprocessed spectral signals are trained with 1 × 3 convolution layers and 1 × 2 max-pooling layers. As a result, the proposed algorithms improve the classification accuracy rate by 1.5% over the existing support vector machine (SVM) algorithm for detecting and classifying hazardous gases.

Relations between distributional and Devaney chaos.

PubMed

Oprocha, Piotr

2006-09-01

Recently, it was proven that chaos in the sense of Devaney and weak mixing both imply chaos in the sense of Li and Yorke. In this article we give explicit examples that any of these two implications do not hold for distributional chaos.

Gullies of Gorgonus Chaos

NASA Technical Reports Server (NTRS)

2002-01-01

above image to get a high-resolution view, and then focus on the trenches at the bottom. Running down the walls of the trough are the thin, dark lines of the gullies. Beneath the grooved, gully channels are faint, softer-looking fans of material. These are called alluvial deposits. Alluvial simply means all of the sand, gravel, and dirt that is carried and deposited by a liquid. On Earth, that liquid is typically water. As the liquid carves the gully, the eroded material from the channels get carried along and deposited below in fan-like shapes. These gully features were initially discovered by Odyssey's sister orbiter, Mars Global Surveyor, and caused quite a bit of emotional chaos in the scientific community when they were announced. Why? If you look closely, you can see that the gullies seem to form from a specific layer in the wall. That is, they all seem to begin at roughly the same point on the wall. That suggests that maybe, just maybe, there's a subsurface source of water at that layer that sometimes leaks out and runs down the walls to form both the gullies and the skirt-like fans of deposits beneath them. Other scientists, however, loudly assert that another liquid besides water could have carved the gullies. The debate sometimes gets so intense, you'd think that the opposing sides would want to turn each other's ideas to stone! But not for long. While the debate rages on, the neat thing is that everyone's really united. The goal is to find out, and the way to find out is to keep proposing different hypotheses and testing them out. That's the excitement of science, where everyone's solid research counts, and divergent views are appreciated for keeping science sound.

SAR image classification based on CNN in real and simulation datasets

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-04-01

Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

3D pulsed chaos lidar system.

PubMed

Cheng, Chih-Hao; Chen, Chih-Ying; Chen, Jun-Da; Pan, Da-Kung; Ting, Kai-Ting; Lin, Fan-Yi

2018-04-30

We develop an unprecedented 3D pulsed chaos lidar system for potential intelligent machinery applications. Benefited from the random nature of the chaos, conventional CW chaos lidars already possess excellent anti-jamming and anti-interference capabilities and have no range ambiguity. In our system, we further employ self-homodyning and time gating to generate a pulsed homodyned chaos to boost the energy-utilization efficiency. Compared to the original chaos, we show that the pulsed homodyned chaos improves the detection SNR by more than 20 dB. With a sampling rate of just 1.25 GS/s that has a native sampling spacing of 12 cm, we successfully achieve millimeter-level accuracy and precision in ranging. Compared with two commercial lidars tested side-by-side, namely the pulsed Spectroscan and the random-modulation continuous-wave Lidar-lite, the pulsed chaos lidar that is in compliance with the class-1 eye-safe regulation shows significantly better precision and a much longer detection range up to 100 m. Moreover, by employing a 2-axis MEMS mirror for active laser scanning, we also demonstrate real-time 3D imaging with errors of less than 4 mm in depth.

Determination of ionization energies of CnN (n=4-12): Vacuum-ultraviolet (VUV) photoionization experiments and theoretical calculations

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

Kostko, Oleg; Zhou, Jia; Sun, Bian Jian

2010-06-10

Results from single photon vacuum ultraviolet photoionization of astrophysically relevant CnN clusters, n = 4 - 12, in the photon energy range of 8.0 eV to 12.8 eV are presented. The experimental photoionization efficiency curves, combined with electronic structure calculations, provide improved ionization energies of the CnN species. A search through numerous nitrogen-terminated CnN isomers for n=4-9 indicates that the linear isomer has the lowest energy, and therefore should be the most abundant isomer in the molecular beam. Comparison with calculated results also shed light on the energetics of the linear CnN clusters, particularly in the trends of the even-carbonmore » and the odd-carbon series. These results can help guide the search of potential astronomical observations of these neutral molecules together with their cations in highly ionized regions or regions with a high UV/VUV photon flux (ranging from the visible to VUV with flux maxima in the Lyman- region) in the interstellar medium.« less

Determination of ionization energies of CnN (n=4-12): Vacuum-ultraviolet (VUV) photoionization experiments and theoretical calculations

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

Kostko, Oleg; Zhou, Jia; Sun, Bian Jian

2010-03-02

Results from single photon vacuum ultraviolet photoionization of astrophysically relevant CnN clusters, n = 4 - 12, in the photon energy range of 8.0 eV to 12.8 eV are presented. The experimental photoionization efficiency curves, combined with electronic structure calculations, provide improved ionization energies of the CnN species. A search through numerous nitrogen-terminated CnN isomers for n=4-9 indicates that the linear isomer has the lowest energy, and therefore should be the most abundant isomer in the molecular beam. Comparison with calculated results also shed light on the energetics of the linear CnN clusters, particularly in the trends of the even-carbonmore » and the odd-carbon series. These results can help guide the search of potential astronomical observations of these neutral molecules together with their cations in highly ionized regions or regions with a high UV/VUV photon flux (ranging from the visible to VUV with flux maxima in the Lyman-a region) in the interstellar medium.« less

Finding Order and Direction from Chaos: A Comparison of Chaos Career Counseling and Trait Matching Counseling

ERIC Educational Resources Information Center

McKay, Hannah; Bright, Jim E. H.; Pryor, Robert G. L.

2005-01-01

Chaos career counseling, based on the Chaos Theory of Careers (R. G. L. Pryor & J. E. H. Bright, 2003a, 2003b), was compared with trait matching career counseling and a wait list control. Sixty university students who attended the Careers Research and Assessment Service seeking career advice were randomly assigned to the chaos intervention, the…

Chaos synchronization in networks of semiconductor superlattices

NASA Astrophysics Data System (ADS)

Li, Wen; Aviad, Yaara; Reidler, Igor; Song, Helun; Huang, Yuyang; Biermann, Klaus; Rosenbluh, Michael; Zhang, Yaohui; Grahn, Holger T.; Kanter, Ido

2015-11-01

Chaos synchronization has been demonstrated as a useful building block for various tasks in secure communications, including a source of all-electronic ultrafast physical random number generators based on room temperature spontaneous chaotic oscillations in a DC-biased weakly coupled GaAs/Al0.45Ga0.55As semiconductor superlattice (SSL). Here, we experimentally demonstrate the emergence of several types of chaos synchronization, e.g. leader-laggard, face-to-face and zero-lag synchronization in network motifs of coupled SSLs consisting of unidirectional and mutual coupling as well as self-feedback coupling. Each type of synchronization clearly reflects the symmetry of the topology of its network motif. The emergence of a chaotic SSL without external feedback and synchronization among different structured SSLs open up the possibility for advanced secure multi-user communication methods based on large networks of coupled SSLs.

Quantum Chaos

NASA Astrophysics Data System (ADS)

Casati, Giulio; Chirikov, Boris

2006-11-01

Preface; Acknowledgments; Introduction: 1. The legacy of chaos in quantum mechanics G. Casati and B. V. Chirikov; Part I. Classical Chaos and Quantum Localization: 2. Stochastic behaviour of a quantum pendulum under a periodic perturbation G. Casati, B. V. Chirikov, F. M. Izrailev and J. Ford; 3. Quantum dynamics of a nonintegrable system D. R. Grempel, R. E. Prange and S. E. Fishman; 4. Excitation of molecular rotation by periodic microwave pulses. A testing ground for Anderson localization R. Blümel, S. Fishman and U. Smilansky; 5. Localization of diffusive excitation in multi-level systems D. K. Shepelyansky; 6. Classical and quantum chaos for a kicked top F. Haake, M. Kus and R. Scharf; 7. Self-similarity in quantum dynamics L. E. Reichl and L. Haoming; 8. Time irreversibility of classically chaotic quantum dynamics K. Ikeda; 9. Effect of noise on time-dependent quantum chaos E. Ott, T. M. Antonsen Jr and J. D. Hanson; 10. Dynamical localization, dissipation and noise R. F. Graham; 11. Maximum entropy models and quantum transmission in disordered systems J.-L. Pichard and M. Sanquer; 12. Solid state 'atoms' in intense oscillating fields M. S. Sherwin; Part II. Atoms in Strong Fields: 13. Localization of classically chaotic diffusion for hydrogen atoms in microwave fields J. E. Bayfield, G. Casati, I. Guarneri and D. W. Sokol; 14. Inhibition of quantum transport due to 'scars' of unstable periodic orbits R. V. Jensen, M. M. Sanders, M. Saraceno and B. Sundaram; 15. Rubidium Rydberg atoms in strong fields G. Benson, G. Raithel and H. Walther; 16. Diamagnetic Rydberg atom: confrontation of calculated and observed spectra C.-H. Iu, G. R. Welch, M. M. Kash, D. Kleppner, D. Delande and J. C. Gay; 17. Semiclassical approximation for the quantum states of a hydrogen atom in a magnetic field near the ionization limit M. Y. Kuchiev and O. P. Sushkov; 18. The semiclassical helium atom D. Wintgen, K. Richter and G. Tanner; 19. Stretched helium: a model for quantum chaos

Quantum Chaos

NASA Astrophysics Data System (ADS)

Casati, Giulio; Chirikov, Boris

1995-04-01

Preface; Acknowledgments; Introduction: 1. The legacy of chaos in quantum mechanics G. Casati and B. V. Chirikov; Part I. Classical Chaos and Quantum Localization: 2. Stochastic behaviour of a quantum pendulum under a periodic perturbation G. Casati, B. V. Chirikov, F. M. Izrailev and J. Ford; 3. Quantum dynamics of a nonintegrable system D. R. Grempel, R. E. Prange and S. E. Fishman; 4. Excitation of molecular rotation by periodic microwave pulses. A testing ground for Anderson localization R. Blümel, S. Fishman and U. Smilansky; 5. Localization of diffusive excitation in multi-level systems D. K. Shepelyansky; 6. Classical and quantum chaos for a kicked top F. Haake, M. Kus and R. Scharf; 7. Self-similarity in quantum dynamics L. E. Reichl and L. Haoming; 8. Time irreversibility of classically chaotic quantum dynamics K. Ikeda; 9. Effect of noise on time-dependent quantum chaos E. Ott, T. M. Antonsen Jr and J. D. Hanson; 10. Dynamical localization, dissipation and noise R. F. Graham; 11. Maximum entropy models and quantum transmission in disordered systems J.-L. Pichard and M. Sanquer; 12. Solid state 'atoms' in intense oscillating fields M. S. Sherwin; Part II. Atoms in Strong Fields: 13. Localization of classically chaotic diffusion for hydrogen atoms in microwave fields J. E. Bayfield, G. Casati, I. Guarneri and D. W. Sokol; 14. Inhibition of quantum transport due to 'scars' of unstable periodic orbits R. V. Jensen, M. M. Sanders, M. Saraceno and B. Sundaram; 15. Rubidium Rydberg atoms in strong fields G. Benson, G. Raithel and H. Walther; 16. Diamagnetic Rydberg atom: confrontation of calculated and observed spectra C.-H. Iu, G. R. Welch, M. M. Kash, D. Kleppner, D. Delande and J. C. Gay; 17. Semiclassical approximation for the quantum states of a hydrogen atom in a magnetic field near the ionization limit M. Y. Kuchiev and O. P. Sushkov; 18. The semiclassical helium atom D. Wintgen, K. Richter and G. Tanner; 19. Stretched helium: a model for quantum chaos

DTU candidate field models for IGRF-12 and the CHAOS-5 geomagnetic field model

NASA Astrophysics Data System (ADS)

Finlay, Christopher C.; Olsen, Nils; Tøffner-Clausen, Lars

2015-07-01

We present DTU's candidate field models for IGRF-12 and the parent field model from which they were derived, CHAOS-5. Ten months of magnetic field observations from ESA's Swarm mission, together with up-to-date ground observatory monthly means, were used to supplement the data sources previously used to construct CHAOS-4. The internal field part of CHAOS-5, from which our IGRF-12 candidate models were extracted, is time-dependent up to spherical harmonic degree 20 and involves sixth-order splines with a 0.5 year knot spacing. In CHAOS-5, compared with CHAOS-4, we update only the low-degree internal field model (degrees 1 to 24) and the associated external field model. The high-degree internal field (degrees 25 to 90) is taken from the same model CHAOS-4h, based on low-altitude CHAMP data, which was used in CHAOS-4. We find that CHAOS-5 is able to consistently fit magnetic field data from six independent low Earth orbit satellites: Ørsted, CHAMP, SAC-C and the three Swarm satellites (A, B and C). It also adequately describes the secular variation measured at ground observatories. CHAOS-5 thus contributes to an initial validation of the quality of the Swarm magnetic data, in particular demonstrating that Huber weighted rms model residuals to Swarm vector field data are lower than those to Ørsted and CHAMP vector data (when either one or two star cameras were operating). CHAOS-5 shows three pulses of secular acceleration at the core surface over the past decade; the 2006 and 2009 pulses have previously been documented, but the 2013 pulse has only recently been identified. The spatial signature of the 2013 pulse at the core surface, under the Atlantic sector where it is strongest, is well correlated with the 2006 pulse, but anti-correlated with the 2009 pulse.

The joy of transient chaos.

PubMed

Tél, Tamás

2015-09-01

We intend to show that transient chaos is a very appealing, but still not widely appreciated, subfield of nonlinear dynamics. Besides flashing its basic properties and giving a brief overview of the many applications, a few recent transient-chaos-related subjects are introduced in some detail. These include the dynamics of decision making, dispersion, and sedimentation of volcanic ash, doubly transient chaos of undriven autonomous mechanical systems, and a dynamical systems approach to energy absorption or explosion.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN.

PubMed

Liu, Chang; Cheng, Gang; Chen, Xihui; Pang, Yusong

2018-05-11

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears.

Experimental Induction of Genome Chaos.

PubMed

Ye, Christine J; Liu, Guo; Heng, Henry H

2018-01-01

Genome chaos, or karyotype chaos, represents a powerful survival strategy for somatic cells under high levels of stress/selection. Since the genome context, not the gene content, encodes the genomic blueprint of the cell, stress-induced rapid and massive reorganization of genome topology functions as a very important mechanism for genome (karyotype) evolution. In recent years, the phenomenon of genome chaos has been confirmed by various sequencing efforts, and many different terms have been coined to describe different subtypes of the chaotic genome including "chromothripsis," "chromoplexy," and "structural mutations." To advance this exciting field, we need an effective experimental system to induce and characterize the karyotype reorganization process. In this chapter, an experimental protocol to induce chaotic genomes is described, following a brief discussion of the mechanism and implication of genome chaos in cancer evolution.

Using chaos theory: the implications for nursing.

PubMed

Haigh, Carol

2002-03-01

The purpose of this paper is to review chaos theory and to examine the role that it may have in the discipline of nursing. In this paper, the fundamental ingredients of chaotic thinking are outlined. The earlier days of chaos thinking were characterized by an almost exclusively physiological focus. By the 21st century, nurse theorists were applying its principles to the organization and evaluation of care delivery with varying levels of success. Whilst the biological use of chaos has focused on pragmatic approaches to knowledge enhancement, nursing has often focused on the mystical aspects of chaos as a concept. The contention that chaos theory has yet to find a niche within nursing theory and practice is examined. The application of chaotic thinking across nursing practice, nursing research and statistical modelling is reviewed. The use of chaos theory as a way of identifying the attractor state of specific systems is considered and the suggestion is made that it is within statistical modelling of services that chaos theory is most effective.

Comparison of hand-craft feature based SVM and CNN based deep learning framework for automatic polyp classification.

PubMed

Younghak Shin; Balasingham, Ilangko

2017-07-01

Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.

Eighth Grade Reading Improvement with CNN Newsroom and "USA Today."

ERIC Educational Resources Information Center

Zamorano, Wanda Jean

A practicum was designed to improve the reading growth and achievement of 60 eighth-grade students who were one or more years behind grade level by utilizing CNN Newsroom and the "USA Today" newspaper as an integral part of the reading program. Pre- and posttests were administered to measure outcomes. The six areas measured were: (1)…

Quantum chaos in nuclear physics

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

Bunakov, V. E., E-mail: bunakov@VB13190.spb.edu

A definition of classical and quantum chaos on the basis of the Liouville–Arnold theorem is proposed. According to this definition, a chaotic quantum system that has N degrees of freedom should have M < N independent first integrals of motion (good quantum numbers) that are determined by the symmetry of the Hamiltonian for the system being considered. Quantitative measures of quantum chaos are established. In the classical limit, they go over to the Lyapunov exponent or the classical stability parameter. The use of quantum-chaos parameters in nuclear physics is demonstrated.

Fractal Patterns and Chaos Games

ERIC Educational Resources Information Center

Devaney, Robert L.

2004-01-01

Teachers incorporate the chaos game and the concept of a fractal into various areas of the algebra and geometry curriculum. The chaos game approach to fractals provides teachers with an opportunity to help students comprehend the geometry of affine transformations.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN

PubMed Central

Cheng, Gang; Chen, Xihui

2018-01-01

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears. PMID:29751671

Scaling of chaos in strongly nonlinear lattices.

PubMed

Mulansky, Mario

2014-06-01

Although it is now understood that chaos in complex classical systems is the foundation of thermodynamic behavior, the detailed relations between the microscopic properties of the chaotic dynamics and the macroscopic thermodynamic observations still remain mostly in the dark. In this work, we numerically analyze the probability of chaos in strongly nonlinear Hamiltonian systems and find different scaling properties depending on the nonlinear structure of the model. We argue that these different scaling laws of chaos have definite consequences for the macroscopic diffusive behavior, as chaos is the microscopic mechanism of diffusion. This is compared with previous results on chaotic diffusion [M. Mulansky and A. Pikovsky, New J. Phys. 15, 053015 (2013)], and a relation between microscopic chaos and macroscopic diffusion is established.

Chaos and wave propagation regimes

NASA Astrophysics Data System (ADS)

Colosi, John

2003-04-01

Ray chaos theory and parabolic equation numerical modeling were two thrusts of Fred Tappert's research that were perpetually in tension. Fred was interested in the problem of identifying wave propagation regimes, most notably the strong focusing caustic regime and its evolution into the saturation regime. On the one hand, chaos theory held the seed of the complexity Fred believed existed in ocean acoustic wavefields; on the other hand ocean acoustic ray chaos theory (which Fred helped to pioneer) was a disdainful approximation to the full wave treatments offered by parabolic equation calculations. Fred was convinced that the saturation limit could not be obtained using ray theory and therefore he examined a new field of inquiry: a blend of chaotic ray insight and full wave dynamics called wave chaos. This talk will discuss some of Fred's insights on this topic and how they relate to observations from basin scale acoustic transmissions.

Wiener Chaos and Nonlinear Filtering

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

Lototsky, S.V.

2006-11-15

The paper discusses two algorithms for solving the Zakai equation in the time-homogeneous diffusion filtering model with possible correlation between the state process and the observation noise. Both algorithms rely on the Cameron-Martin version of the Wiener chaos expansion, so that the approximate filter is a finite linear combination of the chaos elements generated by the observation process. The coefficients in the expansion depend only on the deterministic dynamics of the state and observation processes. For real-time applications, computing the coefficients in advance improves the performance of the algorithms in comparison with most other existing methods of nonlinear filtering. Themore » paper summarizes the main existing results about these Wiener chaos algorithms and resolves some open questions concerning the convergence of the algorithms in the noise-correlated setting. The presentation includes the necessary background on the Wiener chaos and optimal nonlinear filtering.« less

Highly productive CNN pincer ruthenium catalysts for the asymmetric reduction of alkyl aryl ketones.

PubMed

Baratta, Walter; Chelucci, Giorgio; Magnolia, Santo; Siega, Katia; Rigo, Pierluigi

2009-01-01

Chiral pincer ruthenium complexes of formula [RuCl(CNN)(Josiphos)] (2-7; Josiphos = 1-[1-(dicyclohexylphosphano)ethyl]-2-(diarylphosphano)ferrocene) have been prepared by treating [RuCl(2)(PPh(3))(3)] with (S,R)-Josiphos diphosphanes and 1-substituted-1-(6-arylpyridin-2-yl)methanamines (HCNN; substituent = H (1 a), Me (1 b), and tBu (1 c)) with NEt(3). By using 1 b and 1 c as a racemic mixture, complexes 4-7 were obtained through a diastereoselective synthesis promoted by acetic acid. These pincer complexes, which display correctly matched chiral PP and CNN ligands, are remarkably active catalysts for the asymmetric reduction of alkyl aryl ketones in basic alcohol media by both transfer hydrogenation (TH) and hydrogenation (HY), achieving enantioselectivities of up to 99 %. In 2-propanol, the enantioselective TH of ketones was accomplished by using a catalyst loading as low as 0.002 mol % and afforded a turnover frequency (TOF) of 10(5)-10(6) h(-1) (60 and 82 degrees C). In methanol/ethanol mixtures, the CNN pincer complexes catalyzed the asymmetric HY of ketones with H(2) (5 atm) at 0.01 mol % relative to the complex with a TOF of approximately 10(4) h(-1) at 40 degrees C.

Survival and weak chaos.

PubMed

Nee, Sean

2018-05-01

Survival analysis in biology and reliability theory in engineering concern the dynamical functioning of bio/electro/mechanical units. Here we incorporate effects of chaotic dynamics into the classical theory. Dynamical systems theory now distinguishes strong and weak chaos. Strong chaos generates Type II survivorship curves entirely as a result of the internal operation of the system, without any age-independent, external, random forces of mortality. Weak chaos exhibits (a) intermittency and (b) Type III survivorship, defined as a decreasing per capita mortality rate: engineering explicitly defines this pattern of decreasing hazard as 'infant mortality'. Weak chaos generates two phenomena from the normal functioning of the same system. First, infant mortality- sensu engineering-without any external explanatory factors, such as manufacturing defects, which is followed by increased average longevity of survivors. Second, sudden failure of units during their normal period of operation, before the onset of age-dependent mortality arising from senescence. The relevance of these phenomena encompasses, for example: no-fault-found failure of electronic devices; high rates of human early spontaneous miscarriage/abortion; runaway pacemakers; sudden cardiac death in young adults; bipolar disorder; and epilepsy.

Survival and weak chaos

PubMed Central

2018-01-01

Survival analysis in biology and reliability theory in engineering concern the dynamical functioning of bio/electro/mechanical units. Here we incorporate effects of chaotic dynamics into the classical theory. Dynamical systems theory now distinguishes strong and weak chaos. Strong chaos generates Type II survivorship curves entirely as a result of the internal operation of the system, without any age-independent, external, random forces of mortality. Weak chaos exhibits (a) intermittency and (b) Type III survivorship, defined as a decreasing per capita mortality rate: engineering explicitly defines this pattern of decreasing hazard as ‘infant mortality’. Weak chaos generates two phenomena from the normal functioning of the same system. First, infant mortality—sensu engineering—without any external explanatory factors, such as manufacturing defects, which is followed by increased average longevity of survivors. Second, sudden failure of units during their normal period of operation, before the onset of age-dependent mortality arising from senescence. The relevance of these phenomena encompasses, for example: no-fault-found failure of electronic devices; high rates of human early spontaneous miscarriage/abortion; runaway pacemakers; sudden cardiac death in young adults; bipolar disorder; and epilepsy. PMID:29892407

Genome chaos: survival strategy during crisis.

PubMed

Liu, Guo; Stevens, Joshua B; Horne, Steven D; Abdallah, Batoul Y; Ye, Karen J; Bremer, Steven W; Ye, Christine J; Chen, David J; Heng, Henry H

2014-01-01

Genome chaos, a process of complex, rapid genome re-organization, results in the formation of chaotic genomes, which is followed by the potential to establish stable genomes. It was initially detected through cytogenetic analyses, and recently confirmed by whole-genome sequencing efforts which identified multiple subtypes including "chromothripsis", "chromoplexy", "chromoanasynthesis", and "chromoanagenesis". Although genome chaos occurs commonly in tumors, both the mechanism and detailed aspects of the process are unknown due to the inability of observing its evolution over time in clinical samples. Here, an experimental system to monitor the evolutionary process of genome chaos was developed to elucidate its mechanisms. Genome chaos occurs following exposure to chemotherapeutics with different mechanisms, which act collectively as stressors. Characterization of the karyotype and its dynamic changes prior to, during, and after induction of genome chaos demonstrates that chromosome fragmentation (C-Frag) occurs just prior to chaotic genome formation. Chaotic genomes seem to form by random rejoining of chromosomal fragments, in part through non-homologous end joining (NHEJ). Stress induced genome chaos results in increased karyotypic heterogeneity. Such increased evolutionary potential is demonstrated by the identification of increased transcriptome dynamics associated with high levels of karyotypic variance. In contrast to impacting on a limited number of cancer genes, re-organized genomes lead to new system dynamics essential for cancer evolution. Genome chaos acts as a mechanism of rapid, adaptive, genome-based evolution that plays an essential role in promoting rapid macroevolution of new genome-defined systems during crisis, which may explain some unwanted consequences of cancer treatment.

How to test for partially predictable chaos.

PubMed

Wernecke, Hendrik; Sándor, Bulcsú; Gros, Claudius

2017-04-24

For a chaotic system pairs of initially close-by trajectories become eventually fully uncorrelated on the attracting set. This process of decorrelation can split into an initial exponential decrease and a subsequent diffusive process on the chaotic attractor causing the final loss of predictability. Both processes can be either of the same or of very different time scales. In the latter case the two trajectories linger within a finite but small distance (with respect to the overall extent of the attractor) for exceedingly long times and remain partially predictable. Standard tests for chaos widely use inter-orbital correlations as an indicator. However, testing partially predictable chaos yields mostly ambiguous results, as this type of chaos is characterized by attractors of fractally broadened braids. For a resolution we introduce a novel 0-1 indicator for chaos based on the cross-distance scaling of pairs of initially close trajectories. This test robustly discriminates chaos, including partially predictable chaos, from laminar flow. Additionally using the finite time cross-correlation of pairs of initially close trajectories, we are able to identify laminar flow as well as strong and partially predictable chaos in a 0-1 manner solely from the properties of pairs of trajectories.

Minimal-post-processing 320-Gbps true random bit generation using physical white chaos.

PubMed

Wang, Anbang; Wang, Longsheng; Li, Pu; Wang, Yuncai

2017-02-20

Chaotic external-cavity semiconductor laser (ECL) is a promising entropy source for generation of high-speed physical random bits or digital keys. The rate and randomness is unfortunately limited by laser relaxation oscillation and external-cavity resonance, and is usually improved by complicated post processing. Here, we propose using a physical broadband white chaos generated by optical heterodyning of two ECLs as entropy source to construct high-speed random bit generation (RBG) with minimal post processing. The optical heterodyne chaos not only has a white spectrum without signature of relaxation oscillation and external-cavity resonance but also has a symmetric amplitude distribution. Thus, after quantization with a multi-bit analog-digital-convertor (ADC), random bits can be obtained by extracting several least significant bits (LSBs) without any other processing. In experiments, a white chaos with a 3-dB bandwidth of 16.7 GHz is generated. Its entropy rate is estimated as 16 Gbps by single-bit quantization which means a spectrum efficiency of 96%. With quantization using an 8-bit ADC, 320-Gbps physical RBG is achieved by directly extracting 4 LSBs at 80-GHz sampling rate.

Chaos and complexity by design

DOE PAGES

Roberts, Daniel A.; Yoshida, Beni

2017-04-20

We study the relationship between quantum chaos and pseudorandomness by developing probes of unitary design. A natural probe of randomness is the “frame poten-tial,” which is minimized by unitary k-designs and measures the 2-norm distance between the Haar random unitary ensemble and another ensemble. A natural probe of quantum chaos is out-of-time-order (OTO) four-point correlation functions. We also show that the norm squared of a generalization of out-of-time-order 2k-point correlators is proportional to the kth frame potential, providing a quantitative connection between chaos and pseudorandomness. In addition, we prove that these 2k-point correlators for Pauli operators completely determine the k-foldmore » channel of an ensemble of unitary operators. Finally, we use a counting argument to obtain a lower bound on the quantum circuit complexity in terms of the frame potential. This provides a direct link between chaos, complexity, and randomness.« less

Outcrops In Aram Chaos

NASA Technical Reports Server (NTRS)

2004-01-01

16 October 2004 Aram Chaos is the name of an approximately 275 km (171 mi) diameter impact crater near Ares Vallis, roughly half way between the Mars Exploration Rover, Opportunity, site in Meridiani Planum and the easternmost troughs of the Valles Marineris. The Aram Chaos crater is partially filled with a thick accumulation of layered rock. Erosion has exposed light- and dark-toned rock materials in the basin. This Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) image shows a small area exhibiting some of the rock outcrops in Aram Chaos. The light-toned rocks may be sedimentary in origin. This image is located near 4.0oN, 20.6oW, and covers an area about 3 km (1.9 mi) wide. Sunlight illuminates the scene from the upper left.

Meaning Finds a Way: Chaos (Theory) and Composition

ERIC Educational Resources Information Center

Kyburz, Bonnie Lenore

2004-01-01

The explanatory power provided by the chaos theory is explored. A dynamic and reciprocal relationship between culture and chaos theory indicates that the progressive cultural work may be formed by the cross-disciplinary resonance of chaos theory.

Chaos in World Politics: A Reflection

NASA Astrophysics Data System (ADS)

Ferreira, Manuel Alberto Martins; Filipe, José António Candeias Bonito; Coelho, Manuel F. P.; Pedro, Isabel C.

Chaos theory results from natural scientists' findings in the area of non-linear dynamics. The importance of related models has increased in the last decades, by studying the temporal evolution of non-linear systems. In consequence, chaos is one of the concepts that most rapidly have been expanded in what research topics respects. Considering that relationships in non-linear systems are unstable, chaos theory aims to understand and to explain this kind of unpredictable aspects of nature, social life, the uncertainties, the nonlinearities, the disorders and confusion, scientifically it represents a disarray connection, but basically it involves much more than that. The existing close relationship between change and time seems essential to understand what happens in the basics of chaos theory. In fact, this theory got a crucial role in the explanation of many phenomena. The relevance of this kind of theories has been well recognized to explain social phenomena and has permitted new advances in the study of social systems. Chaos theory has also been applied, particularly in the context of politics, in this area. The goal of this chapter is to make a reflection on chaos theory - and dynamical systems such as the theories of complexity - in terms of the interpretation of political issues, considering some kind of events in the political context and also considering the macro-strategic ideas of states positioning in the international stage.

Controllable chaos in hybrid electro-optomechanical systems

PubMed Central

Wang, Mei; Lü, Xin-You; Ma, Jin-Yong; Xiong, Hao; Si, Liu-Gang; Wu, Ying

2016-01-01

We investigate the nonlinear dynamics of a hybrid electro-optomechanical system (EOMS) that allows us to realize the controllable opto-mechanical nonlinearity by driving the microwave LC resonator with a tunable electric field. A controllable optical chaos is realized even without changing the optical pumping. The threshold and lifetime of the chaos could be optimized by adjusting the strength, frequency, or phase of the electric field. This study provides a method of manipulating optical chaos with an electric field. It may offer the prospect of exploring the controllable chaos in on-chip optoelectronic devices and its applications in secret communication. PMID:26948505

Controllable chaos in hybrid electro-optomechanical systems.

PubMed

Wang, Mei; Lü, Xin-You; Ma, Jin-Yong; Xiong, Hao; Si, Liu-Gang; Wu, Ying

2016-03-07

We investigate the nonlinear dynamics of a hybrid electro-optomechanical system (EOMS) that allows us to realize the controllable opto-mechanical nonlinearity by driving the microwave LC resonator with a tunable electric field. A controllable optical chaos is realized even without changing the optical pumping. The threshold and lifetime of the chaos could be optimized by adjusting the strength, frequency, or phase of the electric field. This study provides a method of manipulating optical chaos with an electric field. It may offer the prospect of exploring the controllable chaos in on-chip optoelectronic devices and its applications in secret communication.

Relativistic quantum chaos-An emergent interdisciplinary field.

PubMed

Lai, Ying-Cheng; Xu, Hong-Ya; Huang, Liang; Grebogi, Celso

2018-05-01

Quantum chaos is referred to as the study of quantum manifestations or fingerprints of classical chaos. A vast majority of the studies were for nonrelativistic quantum systems described by the Schrödinger equation. Recent years have witnessed a rapid development of Dirac materials such as graphene and topological insulators, which are described by the Dirac equation in relativistic quantum mechanics. A new field has thus emerged: relativistic quantum chaos. This Tutorial aims to introduce this field to the scientific community. Topics covered include scarring, chaotic scattering and transport, chaos regularized resonant tunneling, superpersistent currents, and energy level statistics-all in the relativistic quantum regime. As Dirac materials have the potential to revolutionize solid-state electronic and spintronic devices, a good understanding of the interplay between chaos and relativistic quantum mechanics may lead to novel design principles and methodologies to enhance device performance.

Household chaos and family sleep during infants' first year.

PubMed

Whitesell, Corey J; Crosby, Brian; Anders, Thomas F; Teti, Douglas M

2018-05-21

Household chaos has been linked with dysregulated family and individual processes. The present study investigated linkages between household chaos and infant and parent sleep, a self-regulated process impacted by individual, social, and environmental factors. Studies of relations between household chaos and child sleep have focused on older children and teenagers, with little attention given to infants or parent sleep. This study examines these relationships using objective measures of household chaos and sleep while controlling for, respectively, maternal emotional availability at bedtime and martial adjustment, in infant and parent sleep. Multilevel modeling examined mean and variability of sleep duration and fragmentation for infants, mothers, and fathers when infants were 1, 3, 6, 9, and 12 months (N = 167). Results indicated infants in higher chaos homes experienced delays in sleep consolidation patterns, with longer and more variable sleep duration, and greater fragmentation. Parent sleep was also associated with household chaos such that in higher chaos homes, mothers and fathers experienced greater variability in sleep duration, which paralleled infant findings. In lower chaos homes, parents' sleep fragmentation mirrored infants' decreasingly fragmented sleep across the first year and remained lower at all timepoints compared to parents and infants in high chaos homes. Collectively, these findings indicate that after controlling for maternal emotional availability and marital adjustment (respectively) household chaos has a dysregulatory impact on infant and parent sleep. Results are discussed in terms of the potential for chaos-induced poor sleep to dysregulate daytime functioning and, in turn, place parent-infant relationships at risk. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Counseling Chaos: Techniques for Practitioners

ERIC Educational Resources Information Center

Pryor, Robert G. L.; Bright, Jim E. H.

2006-01-01

The chaos theory of careers draws together a number of themes in current theory and research. This article applies some of these themes to career counseling. The chaos theory of careers is outlined, and a conceptual framework for understanding assessment and counseling issues that focuses on convergent and emergent qualities is presented. Three…

Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.

PubMed

Zhao, Yu; Ge, Fangfei; Liu, Tianming

2018-07-01

fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional Autoencoder (DCAE). However, interpretations of those decomposed networks are still open questions due to the lack of functional brain atlases, no correspondence across decomposed or reconstructed networks across different subjects, and significant individual variabilities. Recent studies showed that deep learning, especially deep convolutional neural networks (CNN), has extraordinary ability of accommodating spatial object patterns, e.g., our recent works using 3D CNN for fMRI-derived network classifications achieved high accuracy with a remarkable tolerance for mistakenly labelled training brain networks. However, the training data preparation is one of the biggest obstacles in these supervised deep learning models for functional brain network map recognitions, since manual labelling requires tedious and time-consuming labours which will sometimes even introduce label mistakes. Especially for mapping functional networks in large scale datasets such as hundreds of thousands of brain networks used in this paper, the manual labelling method will become almost infeasible. In response, in this work, we tackled both the network recognition and training data labelling tasks by proposing a new iteratively optimized deep learning CNN (IO-CNN) framework with an automatic weak label initialization, which enables the functional brain networks recognition task to a fully automatic large-scale classification procedure. Our extensive experiments based on ABIDE-II 1099 brains' fMRI data showed the great promise of our IO-CNN framework. Copyright © 2018 Elsevier B.V. All rights reserved.

Shape and size distribution of chaos areas on Europa

NASA Astrophysics Data System (ADS)

Mikell, T.; Cox, R.

2008-12-01

Chaos terrain is ubiquitous on Europa's surface, but not randomly distributed. The global distribution of chaos areas shows a significant concentration between 30° N and S latitude, decreasing dramatically at higher latitudes. The low-latitude clustering is not an artifact of recognizability, as there is a greater proportion of images with high solar incidence angle (low light) at higher latitudes. Clustering is especially marked in context of the few but vast regional chaos tracts (>15,000 km2) that occupy a substantial proportion of the equatorial region: i.e. the low latitudes have not only greater numbers but much greater areal chaos coverage. Apex-antapex asymmetry is difficult to evaluate because the Galileo longitudinal coverage is so poor; but comparison of the image swaths that follow great circles across the leading and trailing hemispheres respectively shows greater numbers of chaos areas on the leading side. In spite of the equatorial location of a few vast chaos tracts, there is no apparent relationship between chaos area size and latitude. Chaos area outlines vary from smoothly circular to extremely jagged: the irregularity index ranges from 2- 270% (based on the ratio between measured chaos area perimeter and the circumference of a circle of equal area). There is a range of shapes in all size brackets, but smaller chaos areas on average have simpler, more equidimensional shapes, and edge complexity increases for larger chaos areas. Chaos areas of ~10 km equivalent circle diameter (ECD) have outlines that are 4-90% irregular, ones ~50 km ECD are 15-180% and those >100 km ECD are 35-270% irregular. In general, chaos areas with higher irregularity indices also have a higher raft:matrix ratio. These results, while preliminary, are consistent with experimental evidence suggesting an impact origin for some chaos terrain on Europa. In particular, the relationship between shape and size parallels the results of impact experiments into ice over water, in

The information geometry of chaos

NASA Astrophysics Data System (ADS)

Cafaro, Carlo

2008-10-01

In this Thesis, we propose a new theoretical information-geometric framework (IGAC, Information Geometrodynamical Approach to Chaos) suitable to characterize chaotic dynamical behavior of arbitrary complex systems. First, the problem being investigated is defined; its motivation and relevance are discussed. The basic tools of information physics and the relevant mathematical tools employed in this work are introduced. The basic aspects of Entropic Dynamics (ED) are reviewed. ED is an information-constrained dynamics developed by Ariel Caticha to investigate the possibility that laws of physics---either classical or quantum---may emerge as macroscopic manifestations of underlying microscopic statistical structures. ED is of primary importance in our IGAC. The notion of chaos in classical and quantum physics is introduced. Special focus is devoted to the conventional Riemannian geometrodynamical approach to chaos (Jacobi geometrodynamics) and to the Zurek-Paz quantum chaos criterion of linear entropy growth. After presenting this background material, we show that the ED formalism is not purely an abstract mathematical framework, but is indeed a general theoretical scheme from which conventional Newtonian dynamics is obtained as a special limiting case. The major elements of our IGAC and the novel notion of information geometrodynamical entropy (IGE) are introduced by studying two "toy models". To illustrate the potential power of our IGAC, one application is presented. An information-geometric analogue of the Zurek-Paz quantum chaos criterion of linear entropy growth is suggested. Finally, concluding remarks emphasizing strengths and weak points of our approach are presented and possible further research directions are addressed. At this stage of its development, IGAC remains an ambitious unifying information-geometric theoretical construct for the study of chaotic dynamics with several unsolved problems. However, based on our recent findings, we believe it already

Chaos Theory and Post Modernism

ERIC Educational Resources Information Center

Snell, Joel

2009-01-01

Chaos theory is often associated with post modernism. However, one may make the point that both terms are misunderstood. The point of this article is to define both terms and indicate their relationship. Description: Chaos theory is associated with a definition of a theory dealing with variables (butterflies) that are not directly related to a…

Pre-trained D-CNN models for detecting complex events in unconstrained videos

NASA Astrophysics Data System (ADS)

Robinson, Joseph P.; Fu, Yun

2016-05-01

Rapid event detection faces an emergent need to process large videos collections; whether surveillance videos or unconstrained web videos, the ability to automatically recognize high-level, complex events is a challenging task. Motivated by pre-existing methods being complex, computationally demanding, and often non-replicable, we designed a simple system that is quick, effective and carries minimal overhead in terms of memory and storage. Our system is clearly described, modular in nature, replicable on any Desktop, and demonstrated with extensive experiments, backed by insightful analysis on different Convolutional Neural Networks (CNNs), as stand-alone and fused with others. With a large corpus of unconstrained, real-world video data, we examine the usefulness of different CNN models as features extractors for modeling high-level events, i.e., pre-trained CNNs that differ in architectures, training data, and number of outputs. For each CNN, we use 1-fps from all training exemplar to train one-vs-rest SVMs for each event. To represent videos, frame-level features were fused using a variety of techniques. The best being to max-pool between predetermined shot boundaries, then average-pool to form the final video-level descriptor. Through extensive analysis, several insights were found on using pre-trained CNNs as off-the-shelf feature extractors for the task of event detection. Fusing SVMs of different CNNs revealed some interesting facts, finding some combinations to be complimentary. It was concluded that no single CNN works best for all events, as some events are more object-driven while others are more scene-based. Our top performance resulted from learning event-dependent weights for different CNNs.

Iani Chaos

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site] Context image for PIA03200 Iani Chaos

This VIS image of Iani Chaos shows the layered deposit that occurs on the floor. It appears that the layers were deposited after the chaos was formed.

Image information: VIS instrument. Latitude 2.3S, Longitude 342.3E. 17 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Iani Chaos

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site] Context image for PIA03046 Iani Chaos

This image shows a small portion of Iani Chaos. The brighter floor material is being covered by sand, probably eroded from the mesas of the Chaos.

Image information: VIS instrument. Latitude 1.7S, Longitude 341.6E. 17 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Analyzing the Appropriateness of Internet-Based School News Programs for Social Studies Classrooms: "CNN Student News" as a Case Study

ERIC Educational Resources Information Center

Journell, Wayne

2014-01-01

This article describes a research study on the appropriateness for social studies classrooms of "CNN Student News," a free online news program specifically aimed at middle and high school students. The author conducted a content analysis of "CNN Student News" during October 2012 and evaluated the program's content for…

Household Chaos--Links with Parenting and Child Behaviour

ERIC Educational Resources Information Center

Coldwell, Joanne; Pike, Alison; Dunn, Judy

2006-01-01

Background: The study aimed to confirm previous findings showing links between household chaos and parenting in addition to examining whether household chaos was predictive of children's behaviour over and above parenting. In addition, we investigated whether household chaos acts as a moderator between parenting and children's behaviour. Method:…

Experimental Chaos - Proceedings of the 3rd Conference

NASA Astrophysics Data System (ADS)

Harrison, Robert G.; Lu, Weiping; Ditto, William; Pecora, Lou; Spano, Mark; Vohra, Sandeep

1996-10-01

The Table of Contents for the full book PDF is as follows: * Preface * Spatiotemporal Chaos and Patterns * Scale Segregation via Formation of Domains in a Nonlinear Optical System * Laser Dynamics as Hydrodynamics * Spatiotemporal Dynamics of Human Epileptic Seizures * Experimental Transition to Chaos in a Quasi 1D Chain of Oscillators * Measuring Coupling in Spatiotemporal Dynamical Systems * Chaos in Vortex Breakdown * Dynamical Analysis * Radial Basis Function Modelling and Prediction of Time Series * Nonlinear Phenomena in Polyrhythmic Hand Movements * Using Models to Diagnose, Test and Control Chaotic Systems * New Real-Time Analysis of Time Series Data with Physical Wavelets * Control and Synchronization * Measuring and Controlling Chaotic Dynamics in a Slugging Fluidized Bed * Control of Chaos in a Laser with Feedback * Synchronization and Chaotic Diode Resonators * Control of Chaos by Continuous-time Feedback with Delay * A Framework for Communication using Chaos Sychronization * Control of Chaos in Switching Circuits * Astrophysics, Meteorology and Oceanography * Solar-Wind-Magnetospheric Dynamics via Satellite Data * Nonlinear Dynamics of the Solar Atmosphere * Fractal Dimension of Scalar and Vector Variables from Turbulence Measurements in the Atmospheric Surface Layer * Mechanics * Escape and Overturning: Subtle Transient Behavior in Nonlinear Mechanical Models * Organising Centres in the Dynamics of Parametrically Excited Double Pendulums * Intermittent Behaviour in a Heating System Driven by Phase Transitions * Hydrodynamics * Size Segregation in Couette Flow of Granular Material * Routes to Chaos in Rotational Taylor-Couette Flow * Experimental Study of the Laminar-Turbulent Transition in an Open Flow System * Chemistry * Order and Chaos in Excitable Media under External Forcing * A Chemical Wave Propagation with Accelerating Speed Accompanied by Hydrodynamic Flow * Optics * Instabilities in Semiconductor Lasers with Optical Injection * Spatio

Hybrid information privacy system: integration of chaotic neural network and RSA coding

NASA Astrophysics Data System (ADS)

Hsu, Ming-Kai; Willey, Jeff; Lee, Ting N.; Szu, Harold H.

2005-03-01

Electronic mails are adopted worldwide; most are easily hacked by hackers. In this paper, we purposed a free, fast and convenient hybrid privacy system to protect email communication. The privacy system is implemented by combining private security RSA algorithm with specific chaos neural network encryption process. The receiver can decrypt received email as long as it can reproduce the specified chaos neural network series, so called spatial-temporal keys. The chaotic typing and initial seed value of chaos neural network series, encrypted by the RSA algorithm, can reproduce spatial-temporal keys. The encrypted chaotic typing and initial seed value are hidden in watermark mixed nonlinearly with message media, wrapped with convolution error correction codes for wireless 3rd generation cellular phones. The message media can be an arbitrary image. The pattern noise has to be considered during transmission and it could affect/change the spatial-temporal keys. Since any change/modification on chaotic typing or initial seed value of chaos neural network series is not acceptable, the RSA codec system must be robust and fault-tolerant via wireless channel. The robust and fault-tolerant properties of chaos neural networks (CNN) were proved by a field theory of Associative Memory by Szu in 1997. The 1-D chaos generating nodes from the logistic map having arbitrarily negative slope a = p/q generating the N-shaped sigmoid was given first by Szu in 1992. In this paper, we simulated the robust and fault-tolerance properties of CNN under additive noise and pattern noise. We also implement a private version of RSA coding and chaos encryption process on messages.

Decrease of cardiac chaos in congestive heart failure

NASA Astrophysics Data System (ADS)

Poon, Chi-Sang; Merrill, Christopher K.

1997-10-01

The electrical properties of the mammalian heart undergo many complex transitions in normal and diseased states. It has been proposed that the normal heartbeat may display complex nonlinear dynamics, including deterministic chaos,, and that such cardiac chaos may be a useful physiological marker for the diagnosis and management, of certain heart trouble. However, it is not clear whether the heartbeat series of healthy and diseased hearts are chaotic or stochastic, or whether cardiac chaos represents normal or abnormal behaviour. Here we have used a highly sensitive technique, which is robust to random noise, to detect chaos. We analysed the electrocardiograms from a group of healthy subjects and those with severe congestive heart failure (CHF), a clinical condition associated with a high risk of sudden death. The short-term variations of beat-to-beat interval exhibited strongly and consistently chaotic behaviour in all healthy subjects, but were frequently interrupted by periods of seemingly non-chaotic fluctuations in patients with CHF. Chaotic dynamics in the CHF data, even when discernible, exhibited a high degree of random variability over time, suggesting a weaker form of chaos. These findings suggest that cardiac chaos is prevalent in healthy heart, and a decrease in such chaos may be indicative of CHF.

Exploiting chaos for applications.

PubMed

Ditto, William L; Sinha, Sudeshna

2015-09-01

We discuss how understanding the nature of chaotic dynamics allows us to control these systems. A controlled chaotic system can then serve as a versatile pattern generator that can be used for a range of application. Specifically, we will discuss the application of controlled chaos to the design of novel computational paradigms. Thus, we present an illustrative research arc, starting with ideas of control, based on the general understanding of chaos, moving over to applications that influence the course of building better devices.

Role of the NH2 functionality and solvent in terdentate CNN alkoxide ruthenium complexes for the fast transfer hydrogenation of ketones in 2-propanol.

PubMed

Baratta, Walter; Ballico, Maurizio; Esposito, Gennaro; Rigo, Pierluigi

2008-01-01

The reaction of [RuCl(CNN)(dppb)] (1; HCNN=6-(4-methylphenyl)-2-pyridylmethylamine) with NaOiPr in 2-propanol/C6D6 affords the alcohol adduct alkoxide [Ru(OiPr)(CNN)(dppb)].n iPrOH (5), containing the Ru-NH2 linkage. The alkoxide [Ru(OiPr)(CNN)(dppb)] (4) is formed by treatment of the hydride [Ru(H)(CNN)(dppb)] (2) with acetone in C6D6. Complex 5 in 2-propanol/C6D6 equilibrates quickly with hydride 2 and acetone with an exchange rate of (5.4+/-0.2) s(-1) at 25 degrees C, higher than that found between 4 and 2 ((2.9+/-0.4) s(-1)). This fast process, involving a beta-hydrogen elimination versus ketone insertion into the Ru-H bond, occurs within a hydrogen-bonding network favored by the Ru-NH2 motif. The cationic alcohol complex [Ru(CNN)(dppb)(iPrOH)](BAr(f)4) (6; Ar(f)=3,5-C6H3(CF3)2), obtained from 1, Na[BAr(f)4], and 2-propanol, reacts with NaOiPr to afford 5. Complex 5 reacts with either 4,4'-difluorobenzophenone through hydride 2 or with 4,4'-difluorobenzhydrol through protonation, affording the alkoxide [Ru(OCH(4-C6H4F)2)(CNN)(dppb)] (7) in 90 and 85 % yield of the isolated product. The chiral CNN-ruthenium compound [RuCl(CNN)((S,S)-Skewphos)] (8), obtained by the reaction of [RuCl2(PPh3)3] with (S,S)-Skewphos and orthometalation of HCNN in the presence of NEt3, is a highly active catalyst for the enantioselective transfer hydrogenation of methylaryl ketones (turnover frequencies (TOFs) of up to 1.4 x 10(6) h(-1) at reflux were obtained) with up to 89% ee. Also the ketone CF3CO(4-C6H4F), containing the strong electron-withdrawing CF3 group, is reduced to the R alcohol with 64% ee and a TOF of 1.5 x 10(4) h(-1). The chiral alkoxide [Ru(OiPr)(CNN)((S,S)-Skewphos)]n iPrOH (9), obtained from 8 and NaOiPr in the presence of 2-propanol, reacts with CF3CO(4-C6H4F) to afford a mixture of the diastereomer alkoxides [Ru(OCH(CF3)(4-C6H4F))(CNN)((S,S)-Skewphos)] (10/11; 74% yield) with 67% de. This value is very close to the enantiomeric excess of the alcohol (R)-CF3CH

Chaos, Chaos Control and Synchronization of a Gyrostat System

NASA Astrophysics Data System (ADS)

GE, Z.-M.; LIN, T.-N.

2002-03-01

The dynamic behavior of a gyrostat system subjected to external disturbance is studied in this paper. By applying numerical results, phase diagrams, power spectrum, period-T maps, and Lyapunov exponents are presented to observe periodic and choatic motions. The effect of the parameters changed in the system can be found in the bifurcation and parametric diagrams. For global analysis, the basins of attraction of each attractor of the system are located by employing the modified interpolated cell mapping (MICM) method. Several methods, the delayed feedback control, the addition of constant torque, the addition of periodic force, the addition of periodic impulse torque, injection of dither signal control, adaptive control algorithm (ACA) control and bang-bang control are used to control chaos effectively. Finally, synchronization of chaos in the gyrostat system is studied.

Applied Chaos: From Oxymoron to Reality.

NASA Astrophysics Data System (ADS)

Ditto, William

1996-11-01

The rapidly emerging field of chaotic dynamics has presented the applied scientist with intriguing new tools to understand and manipulate systems that behave chaotically. An overview will be presented which will answer the questions: What is Chaos? and What can you do with Chaos? Examples of recent applications of chaos theory to the physical and biological sciences will be presented covering applications that range from encryption in communications to control of chaotically beating human hearts. Part A of program listing

The Capabilities of Chaos and Complexity

PubMed Central

Abel, David L.

2009-01-01

To what degree could chaos and complexity have organized a Peptide or RNA World of crude yet necessarily integrated protometabolism? How far could such protolife evolve in the absence of a heritable linear digital symbol system that could mutate, instruct, regulate, optimize and maintain metabolic homeostasis? To address these questions, chaos, complexity, self-ordered states, and organization must all be carefully defined and distinguished. In addition their cause-and-effect relationships and mechanisms of action must be delineated. Are there any formal (non physical, abstract, conceptual, algorithmic) components to chaos, complexity, self-ordering and organization, or are they entirely physicodynamic (physical, mass/energy interaction alone)? Chaos and complexity can produce some fascinating self-ordered phenomena. But can spontaneous chaos and complexity steer events and processes toward pragmatic benefit, select function over non function, optimize algorithms, integrate circuits, produce computational halting, organize processes into formal systems, control and regulate existing systems toward greater efficiency? The question is pursued of whether there might be some yet-to-be discovered new law of biology that will elucidate the derivation of prescriptive information and control. “System” will be rigorously defined. Can a low-informational rapid succession of Prigogine’s dissipative structures self-order into bona fide organization? PMID:19333445

Brownian motion properties of optoelectronic random bit generators based on laser chaos.

PubMed

Li, Pu; Yi, Xiaogang; Liu, Xianglian; Wang, Yuncai; Wang, Yongge

2016-07-11

The nondeterministic property of the optoelectronic random bit generator (RBG) based on laser chaos are experimentally analyzed from two aspects of the central limit theorem and law of iterated logarithm. The random bits are extracted from an optical feedback chaotic laser diode using a multi-bit extraction technique in the electrical domain. Our experimental results demonstrate that the generated random bits have no statistical distance from the Brownian motion, besides that they can pass the state-of-the-art industry-benchmark statistical test suite (NIST SP800-22). All of them give a mathematically provable evidence that the ultrafast random bit generator based on laser chaos can be used as a nondeterministic random bit source.

Automatic bladder segmentation from CT images using deep CNN and 3D fully connected CRF-RNN.

PubMed

Xu, Xuanang; Zhou, Fugen; Liu, Bo

2018-03-19

Automatic approach for bladder segmentation from computed tomography (CT) images is highly desirable in clinical practice. It is a challenging task since the bladder usually suffers large variations of appearance and low soft-tissue contrast in CT images. In this study, we present a deep learning-based approach which involves a convolutional neural network (CNN) and a 3D fully connected conditional random fields recurrent neural network (CRF-RNN) to perform accurate bladder segmentation. We also propose a novel preprocessing method, called dual-channel preprocessing, to further advance the segmentation performance of our approach. The presented approach works as following: first, we apply our proposed preprocessing method on the input CT image and obtain a dual-channel image which consists of the CT image and an enhanced bladder density map. Second, we exploit a CNN to predict a coarse voxel-wise bladder score map on this dual-channel image. Finally, a 3D fully connected CRF-RNN refines the coarse bladder score map and produce final fine-localized segmentation result. We compare our approach to the state-of-the-art V-net on a clinical dataset. Results show that our approach achieves superior segmentation accuracy, outperforming the V-net by a significant margin. The Dice Similarity Coefficient of our approach (92.24%) is 8.12% higher than that of the V-net. Moreover, the bladder probability maps performed by our approach present sharper boundaries and more accurate localizations compared with that of the V-net. Our approach achieves higher segmentation accuracy than the state-of-the-art method on clinical data. Both the dual-channel processing and the 3D fully connected CRF-RNN contribute to this improvement. The united deep network composed of the CNN and 3D CRF-RNN also outperforms a system where the CRF model acts as a post-processing method disconnected from the CNN.

SAR target recognition and posture estimation using spatial pyramid pooling within CNN

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-01-01

Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.

Harnessing quantum transport by transient chaos.

PubMed

Yang, Rui; Huang, Liang; Lai, Ying-Cheng; Grebogi, Celso; Pecora, Louis M

2013-03-01

Chaos has long been recognized to be generally advantageous from the perspective of control. In particular, the infinite number of unstable periodic orbits embedded in a chaotic set and the intrinsically sensitive dependence on initial conditions imply that a chaotic system can be controlled to a desirable state by using small perturbations. Investigation of chaos control, however, was largely limited to nonlinear dynamical systems in the classical realm. In this paper, we show that chaos may be used to modulate or harness quantum mechanical systems. To be concrete, we focus on quantum transport through nanostructures, a problem of considerable interest in nanoscience, where a key feature is conductance fluctuations. We articulate and demonstrate that chaos, more specifically transient chaos, can be effective in modulating the conductance-fluctuation patterns. Experimentally, this can be achieved by applying an external gate voltage in a device of suitable geometry to generate classically inaccessible potential barriers. Adjusting the gate voltage allows the characteristics of the dynamical invariant set responsible for transient chaos to be varied in a desirable manner which, in turn, can induce continuous changes in the statistical characteristics of the quantum conductance-fluctuation pattern. To understand the physical mechanism of our scheme, we develop a theory based on analyzing the spectrum of the generalized non-Hermitian Hamiltonian that includes the effect of leads, or electronic waveguides, as self-energy terms. As the escape rate of the underlying non-attracting chaotic set is increased, the imaginary part of the complex eigenenergy becomes increasingly large so that pointer states are more difficult to form, making smoother the conductance-fluctuation pattern.

DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

NASA Astrophysics Data System (ADS)

Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.

2017-12-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remotesensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud/shadow mask from geostationary satellite data iscritical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds, which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoder-decoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multi-spectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

Detecting nonlinearity and chaos in epidemic data

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

Ellner, S.; Gallant, A.R.; Theiler, J.

1993-08-01

Historical data on recurrent epidemics have been central to the debate about the prevalence of chaos in biological population dynamics. Schaffer and Kot who first recognized that the abundance and accuracy of disease incidence data opened the door to applying a range of methods for detecting chaos that had been devised in the early 1980`s. Using attractor reconstruction, estimates of dynamical invariants, and comparisons between data and simulation of SEIR models, the ``case for chaos in childhood epidemics`` was made through a series of influential papers beginning in the mid 1980`s. The proposition that the precise timing and magnitude ofmore » epidemic outbreaks are deterministic but chaotic is appealing, since it raises the hope of finding determinism and simplicity beneath the apparently stochastic and complicated surface of the data. The initial enthusiasm for methods of detecting chaos in data has been followed by critical re-evaluations of their limitations. Early hopes of a ``one size fits all`` algorithm to diagnose chaos vs. noise in any data set have given way to a recognition that a variety of methods must be used, and interpretation of results must take into account the limitations of each method and the imperfections of the data. Our goals here are to outline some newer methods for detecting nonlinearity and chaos that have a solid statistical basis and are suited to epidemic data, and to begin a re-evaluation of the claims for nonlinear dynamics and chaos in epidemics using these newer methods. We also identify features of epidemic data that create problems for the older, better known methods of detecting chaos. When we ask ``are epidemics nonlinear?``, we are not questioning the existence of global nonlinearities in epidemic dynamics, such as nonlinear transmission rates. Our question is whether the data`s deviations from an annual cyclic trend (which would reflect global nonlinearities) are described by a linear, noise-driven stochastic process.« less

Counterintuitive Constraints on Chaos Formation Set by Heat Flux through Europa's Ocean

NASA Astrophysics Data System (ADS)

Goodman, J. C.

2013-12-01

Models for the formation of disruptive chaos features on the icy surface of Europa fall into two broad categories: either chaos is formed when basal heating causes localized melting and thinning of the ice shell, or basal heating drives diapiric convection within the ice shell. We argue that in both of these cases, heating of the ice shell from below does not lead to chaos formation at the location of heating. If chaos is formed when a localized oceanic heat source, such as a hydrothermal plume, "melts through" the ice crust, we must consider what happens to the melted liquid. If Europa's ocean is salty, the melt will form a buoyant pool inside the melted cavity, leading to a stable interface between cold fresh meltwater and warm salty seawater. This stable interface acts like an ablative heat shield, protecting the ice from further damage. Some heat can be transferred across the stable layer by double diffusion, but this transfer is very inefficient. We calculate that local ocean heating cannot be balanced by local flux through the stable layer: instead, the warm ocean water must spread laterally until it is delivering heat to the ice base on a regional or global scale (a heating zone hundreds or thousands of km across, for conservative parameters.) If chaos is formed by diapiric solid-state convection within the ice shell, many investigators have assumed that diapirism and chaos should be most prevalent where the basal heat flux is strongest. We argue that this is not the case. In Rayleigh-Benard convection, increasing the heat flux will make convection more vigorous --- if and only if the convecting layer thickness does not change. We argue that increased basal heat flux will thin the ice shell, reducing its Rayleigh number and making convection less likely, not more. This insight allows us to reverse the logic of recent discussions of the relationship between ocean circulation and chaos (for instance, Soderlund et al, 2013 LPSC). We argue that global oceanic

Catastrophic ice lake collapse in Aram Chaos, Mars

NASA Astrophysics Data System (ADS)

Roda, Manuel; Kleinhans, Maarten G.; Zegers, Tanja E.; Oosthoek, Jelmer H. P.

2014-07-01

Hesperian chaotic terrains have been recognized as the source of outflow channels formed by catastrophic outflows. Four main scenarios have been proposed for the formation of chaotic terrains that involve different amounts of water and single or multiple outflow events. Here, we test these scenarios with morphological and structural analyses of imagery and elevation data for Aram Chaos in conjunction with numerical modeling of the morphological evolution of the catastrophic carving of the outflow valley. The morphological and geological analyses of Aram Chaos suggest large-scale collapse and subsidence (1500 m) of the entire area, which is consistent with a massive expulsion of liquid water from the subsurface in one single event. The combined observations suggest a complex process starting with the outflow of water from two small channels, followed by continuous groundwater sapping and headward erosion and ending with a catastrophic lake rim collapse and carving of the Aram Valley, which is synchronous with the 2.5 Ga stage of the Ares Vallis formation. The water volume and formative time scale required to carve the Aram channels indicate that a single, rapid (maximum tens of days) and catastrophic (flood volume of 9.3 × 104 km3) event carved the outflow channel. We conclude that a sub-ice lake collapse model can best explain the features of the Aram Chaos Valley system as well as the time scale required for its formation.

Contractility of glycerinated Amoeba proteus and Chaos-chaos.

PubMed

Rinaldi, R; Opas, M; Hrebenda, B

1975-05-01

Immediate contact with large volumes of cold 50% (v/v) buffered glycerol preserved typical ameboid shape of Chaos chaos and Amoeba proteus with no visible distortions. These technics allowed determination of the contraction sites in these glycerinated models upon applications of ATP-Ca-Mg-solutions. The ectoplasmic tube was the main site of contraction. Preliminary EM investigations revealed thick and thin filaments, associated with the ectoplasmic tube near the plasma-lemma, which appeared to be the basis for the contractility of the ectoplasmic tube. There was no predominant contraction of the pseudopodial tips or the endoplasm in these models. The changes of volume were as much as 50%, and in some cases were not accompanied by any change in the length of the ameba; however, lengthwise contractions of the ectoplasmic tube in some amebae occurred to as much as 25%. The data substantiate a basic requirement of the ectoplasmic tube contraction theory of ameboid locomotion.

Chaos based encryption system for encrypting electroencephalogram signals.

PubMed

Lin, Chin-Feng; Shih, Shun-Han; Zhu, Jin-De

2014-05-01

In the paper, we use the Microsoft Visual Studio Development Kit and C# programming language to implement a chaos-based electroencephalogram (EEG) encryption system involving three encryption levels. A chaos logic map, initial value, and bifurcation parameter for the map were used to generate Level I chaos-based EEG encryption bit streams. Two encryption-level parameters were added to these elements to generate Level II chaos-based EEG encryption bit streams. An additional chaotic map and chaotic address index assignment process was used to implement the Level III chaos-based EEG encryption system. Eight 16-channel EEG Vue signals were tested using the encryption system. The encryption was the most rapid and robust in the Level III system. The test yielded superior encryption results, and when the correct deciphering parameter was applied, the EEG signals were completely recovered. However, an input parameter error (e.g., a 0.00001 % initial point error) causes chaotic encryption bit streams, preventing the recovery of 16-channel EEG Vue signals.

Investigating a link between large and small-scale chaos features on Europa

NASA Astrophysics Data System (ADS)

Tognetti, L.; Rhoden, A.; Nelson, D. M.

2017-12-01

Chaos is one of the most recognizable, and studied, features on Europa's surface. Most models of chaos formation invoke liquid water at shallow depths within the ice shell; the liquid destabilizes the overlying ice layer, breaking it into mobile rafts and destroying pre-existing terrain. This class of model has been applied to both large-scale chaos like Conamara and small-scale features (i.e. microchaos), which are typically <10 km in diameter. Currently unknown, however, is whether both large-scale and small-scale features are produced together, e.g. through a network of smaller sills linked to a larger liquid water pocket. If microchaos features do form as satellites of large-scale chaos features, we would expect a drop off in the number density of microchaos with increasing distance from the large chaos feature; the trend should not be observed in regions without large-scale chaos features. Here, we test the hypothesis that large chaos features create "satellite" systems of smaller chaos features. Either outcome will help us better understand the relationship between large-scale chaos and microchaos. We focus first on regions surrounding the large chaos features Conamara and Murias (e.g. the Mitten). We map all chaos features within 90,000 sq km of the main chaos feature and assign each one a ranking (High Confidence, Probable, or Low Confidence) based on the observed characteristics of each feature. In particular, we look for a distinct boundary, loss of preexisting terrain, the existence of rafts or blocks, and the overall smoothness of the feature. We also note features that are chaos-like but lack sufficient characteristics to be classified as chaos. We then apply the same criteria to map microchaos features in regions of similar area ( 90,000 sq km) that lack large chaos features. By plotting the distribution of microchaos with distance from the center point of the large chaos feature or the mapping region (for the cases without a large feature), we

Heuristic versus Systematic Processing of Specialist versus Generalist Sources in Online Media

ERIC Educational Resources Information Center

Koh, Yoon Jeon; Sundar, S. Shyam

2010-01-01

In exploring why specialist sources (e.g., CNN.com) are more persuasive than generalist sources (e.g., CBS.com), this study examines theoretical mechanisms related to information-processing differences caused by these sources. When we have a chain of sources (Websites and agents) in online media, does specialization of one of them bias the…

Semantic image segmentation with fused CNN features

NASA Astrophysics Data System (ADS)

Geng, Hui-qiang; Zhang, Hua; Xue, Yan-bing; Zhou, Mian; Xu, Guang-ping; Gao, Zan

2017-09-01

Semantic image segmentation is a task to predict a category label for every image pixel. The key challenge of it is to design a strong feature representation. In this paper, we fuse the hierarchical convolutional neural network (CNN) features and the region-based features as the feature representation. The hierarchical features contain more global information, while the region-based features contain more local information. The combination of these two kinds of features significantly enhances the feature representation. Then the fused features are used to train a softmax classifier to produce per-pixel label assignment probability. And a fully connected conditional random field (CRF) is used as a post-processing method to improve the labeling consistency. We conduct experiments on SIFT flow dataset. The pixel accuracy and class accuracy are 84.4% and 34.86%, respectively.

Fabric defect detection based on faster R-CNN

NASA Astrophysics Data System (ADS)

Liu, Zhoufeng; Liu, Xianghui; Li, Chunlei; Li, Bicao; Wang, Baorui

2018-04-01

In order to effectively detect the defects for fabric image with complex texture, this paper proposed a novel detection algorithm based on an end-to-end convolutional neural network. First, the proposal regions are generated by RPN (regional proposal Network). Then, Fast Region-based Convolutional Network method (Fast R-CNN) is adopted to determine whether the proposal regions extracted by RPN is a defect or not. Finally, Soft-NMS (non-maximum suppression) and data augmentation strategies are utilized to improve the detection precision. Experimental results demonstrate that the proposed method can locate the fabric defect region with higher accuracy compared with the state-of- art, and has better adaptability to all kinds of the fabric image.

CNN for breaking text-based CAPTCHA with noise

NASA Astrophysics Data System (ADS)

Liu, Kaixuan; Zhang, Rong; Qing, Ke

2017-07-01

A CAPTCHA ("Completely Automated Public Turing test to tell Computers and Human Apart") system is a program that most humans can pass but current computer programs could hardly pass. As the most common type of CAPTCHAs , text-based CAPTCHA has been widely used in different websites to defense network bots. In order to breaking textbased CAPTCHA, in this paper, two trained CNN models are connected for the segmentation and classification of CAPTCHA images. Then base on these two models, we apply sliding window segmentation and voting classification methods realize an end-to-end CAPTCHA breaking system with high success rate. The experiment results show that our method is robust and effective in breaking text-based CAPTCHA with noise.

Maintenance and suppression of chaos by weak harmonic perturbations: a unified view.

PubMed

Chacón, R

2001-02-26

General results concerning maintenance or enhancement of chaos are presented for dissipative systems subjected to two harmonic perturbations (one chaos inducing and the other chaos enhancing). The connection with previous results on chaos suppression is also discussed in a general setting. It is demonstrated that, in general, a second harmonic perturbation can reliably play an enhancer or inhibitor role by solely adjusting its initial phase. Numerical results indicate that general theoretical findings concerning periodic chaos-inducing perturbations also work for aperiodic chaos-inducing perturbations, and in arrays of identical chaotic coupled oscillators.

Effortful control and school adjustment: The moderating role of classroom chaos.

PubMed

Berger, Rebecca H; Valiente, Carlos; Eisenberg, Nancy; Hernandez, Maciel M; Thompson, Marilyn; Spinrad, Tracy; VanSchyndel, Sarah; Silva, Kassondra; Southworth, Jody

2017-11-01

Guided by the person by environment framework, the primary goal of this study was to determine whether classroom chaos moderated the relation between effortful control and kindergarteners' school adjustment. Classroom observers reported on children's ( N = 301) effortful control in the fall. In the spring, teachers reported on classroom chaos and school adjustment outcomes (teacher-student relationship closeness and conflict, and school liking and avoidance). Cross-level interactions between effortful control and classroom chaos predicting school adjustment outcomes were assessed. A consistent pattern of interactions between effortful control and classroom chaos indicated that the relations between effortful control and the school adjustment outcomes were strongest in high chaos classrooms. Post-hoc analyses indicated that classroom chaos was associated with poor school adjustment when effortful control was low, suggesting that the combination of high chaos and low effortful control was associated with the poorest school outcomes.

Chaos: Choto delat?

NASA Astrophysics Data System (ADS)

Campbell, David

1987-11-01

I provide a brief overview of the current status of the field of deterministic "chaos" stressing its interrelations and applications to other fields and suggesting a number of important open problems for future study.

Origins of Chaos in Autonomous Boolean Networks

NASA Astrophysics Data System (ADS)

Socolar, Joshua; Cavalcante, Hugo; Gauthier, Daniel; Zhang, Rui

2010-03-01

Networks with nodes consisting of ideal Boolean logic gates are known to display either steady states, periodic behavior, or an ultraviolet catastrophe where the number of logic-transition events circulating in the network per unit time grows as a power-law. In an experiment, non-ideal behavior of the logic gates prevents the ultraviolet catastrophe and may lead to deterministic chaos. We identify certain non-ideal features of real logic gates that enable chaos in experimental networks. We find that short-pulse rejection and the asymmetry between the logic states tends to engender periodic behavior. On the other hand, a memory effect termed ``degradation'' can generate chaos. Our results strongly suggest that deterministic chaos can be expected in a large class of experimental Boolean-like networks. Such devices may find application in a variety of technologies requiring fast complex waveforms or flat power spectra. The non-ideal effects identified here also have implications for the statistics of attractors in large complex networks.

Mining key elements for severe convection prediction based on CNN

NASA Astrophysics Data System (ADS)

Liu, Ming; Pan, Ning; Zhang, Changan; Sha, Hongzhou; Zhang, Bolei; Liu, Liang; Zhang, Meng

2017-04-01

Severe convective weather is a kind of weather disasters accompanied by heavy rainfall, gust wind, hail, etc. Along with recent developments on remote sensing and numerical modeling, there are high-volume and long-term observational and modeling data accumulated to capture massive severe convective events over particular areas and time periods. With those high-volume and high-variety weather data, most of the existing studies and methods carry out the dynamical laws, cause analysis, potential rule study, and prediction enhancement by utilizing the governing equations from fluid dynamics and thermodynamics. In this study, a key-element mining method is proposed for severe convection prediction based on convolution neural network (CNN). It aims to identify the key areas and key elements from huge amounts of historical weather data including conventional measurements, weather radar, satellite, so as numerical modeling and/or reanalysis data. Under this manner, the machine-learning based method could help the human forecasters on their decision-making on operational weather forecasts on severe convective weathers by extracting key information from the real-time and historical weather big data. In this paper, it first utilizes computer vision technology to complete the data preprocessing work of the meteorological variables. Then, it utilizes the information such as radar map and expert knowledge to annotate all images automatically. And finally, by using CNN model, it cloud analyze and evaluate each weather elements (e.g., particular variables, patterns, features, etc.), and identify key areas of those critical weather elements, then help forecasters quickly screen out the key elements from huge amounts of observation data by current weather conditions. Based on the rich weather measurement and model data (up to 10 years) over Fujian province in China, where the severe convective weathers are very active during the summer months, experimental tests are conducted with

Philosophical perspectives on quantum chaos: Models and interpretations

NASA Astrophysics Data System (ADS)

Bokulich, Alisa Nicole

2001-09-01

The problem of quantum chaos is a special case of the larger problem of understanding how the classical world emerges from quantum mechanics. While we have learned that chaos is pervasive in classical systems, it appears to be almost entirely absent in quantum systems. The aim of this dissertation is to determine what implications the interpretation of quantum mechanics has for attempts to explain the emergence of classical chaos. There are three interpretations of quantum mechanics that have set out programs for solving the problem of quantum chaos: the standard interpretation, the statistical interpretation, and the deBroglie-Bohm causal interpretation. One of the main conclusions of this dissertation is that an interpretation alone is insufficient for solving the problem of quantum chaos and that the phenomenon of decoherence must be taken into account. Although a completely satisfactory solution of the problem of quantum chaos is still outstanding, I argue that the deBroglie-Bohm interpretation with the help of decoherence outlines the most promising research program to pursue. In addition to making a contribution to the debate in the philosophy of physics concerning the interpretation of quantum mechanics, this dissertation reveals two important methodological lessons for the philosophy of science. First, issues of reductionism and intertheoretic relations cannot be divorced from questions concerning the interpretation of the theories involved. Not only is the exploration of intertheoretic relations a central part of the articulation and interpretation of an individual theory, but the very terms used to discuss intertheoretic relations, such as `state' and `classical limit', are themselves defined by particular interpretations of the theory. The second lesson that emerges is that, when it comes to characterizing the relationship between classical chaos and quantum mechanics, the traditional approaches to intertheoretic relations, namely reductionism and

Inspecting rapidly moving surfaces for small defects using CNN cameras

NASA Astrophysics Data System (ADS)

Blug, Andreas; Carl, Daniel; Höfler, Heinrich

2013-04-01

A continuous increase in production speed and manufacturing precision raises a demand for the automated detection of small image features on rapidly moving surfaces. An example are wire drawing processes where kilometers of cylindrical metal surfaces moving with 10 m/s have to be inspected for defects such as scratches, dents, grooves, or chatter marks with a lateral size of 100 μm in real time. Up to now, complex eddy current systems are used for quality control instead of line cameras, because the ratio between lateral feature size and surface speed is limited by the data transport between camera and computer. This bottleneck is avoided by "cellular neural network" (CNN) cameras which enable image processing directly on the camera chip. This article reports results achieved with a demonstrator based on this novel analogue camera - computer system. The results show that computational speed and accuracy of the analogue computer system are sufficient to detect and discriminate the different types of defects. Area images with 176 x 144 pixels are acquired and evaluated in real time with frame rates of 4 to 10 kHz - depending on the number of defects to be detected. These frame rates correspond to equivalent line rates on line cameras between 360 and 880 kHz, a number far beyond the available features. Using the relation between lateral feature size and surface speed as a figure of merit, the CNN based system outperforms conventional image processing systems by an order of magnitude.

Comparison Between Terrestrial Explosion Crater Morphology in Floating Ice and Europan Chaos

NASA Technical Reports Server (NTRS)

Billings, S. E.; Kattenhorn, S. A.

2003-01-01

Craters created by explosives have been found to serve as valuable analogs to impact craters, within limits. Explosion craters have been created in floating terrestrial ice in experiments related to clearing ice from waterways. Features called chaos occur on the surface of Europa s floating ice shell. Chaos is defined as a region in which the background plains have been disrupted. Common features of chaos include rafted blocks of pre-existing terrain suspended in a matrix of smooth or hummocky material; low surface albedo; and structural control on chaos outline shape by pre-existing lineaments. All published models of chaos formation call on endogenic processes whereby chaos forms through thermal processes. Nonetheless, we note morphological similarities between terrestrial explosion craters and Europan chaos at a range of scales and consider whether some chaos may have formed by impact. We explore these similarities through geologic and morphologic mapping.

Polynomiography and Chaos

NASA Astrophysics Data System (ADS)

Kalantari, Bahman

Polynomiography is the algorithmic visualization of iterative systems for computing roots of a complex polynomial. It is well known that iterations of a rational function in the complex plane result in chaotic behavior near its Julia set. In one scheme of computing polynomiography for a given polynomial p(z), we select an individual member from the Basic Family, an infinite fundamental family of rational iteration functions that in particular include Newton's. Polynomiography is an excellent means for observing, understanding, and comparing chaotic behavior for variety of iterative systems. Other iterative schemes in polynomiography are possible and result in chaotic behavior of different kinds. In another scheme, the Basic Family is collectively applied to p(z) and the iterates for any seed in the Voronoi cell of a root converge to that root. Polynomiography reveals chaotic behavior of another kind near the boundary of the Voronoi diagram of the roots. We also describe a novel Newton-Ellipsoid iterative system with its own chaos and exhibit images demonstrating polynomiographies of chaotic behavior of different kinds. Finally, we consider chaos for the more general case of polynomiography of complex analytic functions. On the one hand polynomiography is a powerful medium capable of demonstrating chaos in different forms, it is educationally instructive to students and researchers, also it gives rise to numerous research problems. On the other hand, it is a medium resulting in images with enormous aesthetic appeal to general audiences.

Collision analysis of one kind of chaos-based hash function

NASA Astrophysics Data System (ADS)

Xiao, Di; Peng, Wenbing; Liao, Xiaofeng; Xiang, Tao

2010-02-01

In the last decade, various chaos-based hash functions have been proposed. Nevertheless, the corresponding analyses of them lag far behind. In this Letter, we firstly take a chaos-based hash function proposed very recently in Amin, Faragallah and Abd El-Latif (2009) [11] as a sample to analyze its computational collision problem, and then generalize the construction method of one kind of chaos-based hash function and summarize some attentions to avoid the collision problem. It is beneficial to the hash function design based on chaos in the future.

Congenital high airway obstruction syndrome (CHAOS) associated with cervical myelomeningocele.

PubMed

Adin, Mehmet Emin

2017-10-01

Congenital high airway obstruction syndrome (CHAOS) is a rare and potentially fatal entity resulting from complete or near complete developmental airway obstruction. Although most reported cases of CHAOS are sporadic, the condition may also be associated with certain syndromes and a variety of cervical masses. Meningocele and myelomeningocele have not yet been reported in association with CHAOS. We describe the typical constellation of sonographic findings in a case of early diagnosis of CHAOS associated with cervical myelomeningocele. © 2016 Wiley Periodicals, Inc. J Clin Ultrasound 45:507-510, 2017. © 2016 Wiley Periodicals, Inc.

Is case-chaos methodology an appropriate alternative to conventional case-control studies for investigating outbreaks?

PubMed

Edelstein, Michael; Wallensten, Anders; Kühlmann-Berenzon, Sharon

2014-08-15

Case-chaos methodology is a proposed alternative to case-control studies that simulates controls by randomly reshuffling the exposures of cases. We evaluated the method using data on outbreaks in Sweden. We identified 5 case-control studies from foodborne illness outbreaks that occurred between 2005 and 2012. Using case-chaos methodology, we calculated odds ratios 1,000 times for each exposure. We used the median as the point estimate and the 2.5th and 97.5th percentiles as the confidence interval. We compared case-chaos matched odds ratios with their respective case-control odds ratios in terms of statistical significance. Using Spearman's correlation, we estimated the correlation between matched odds ratios and the proportion of cases exposed to each exposure and quantified the relationship between the 2 using a normal linear mixed model. Each case-control study identified an outbreak vehicle (odds ratios = 4.9-45). Case-chaos methodology identified the outbreak vehicle 3 out of 5 times. It identified significant associations in 22 of 113 exposures that were not associated with outcome and 5 of 18 exposures that were significantly associated with outcome. Log matched odds ratios correlated with their respective proportion of cases exposed (Spearman ρ = 0.91) and increased significantly with the proportion of cases exposed (b = 0.054). Case-chaos methodology missed the outbreak source 2 of 5 times and identified spurious associations between a number of exposures and outcome. Measures of association correlated with the proportion of cases exposed. We recommended against using case-chaos analysis during outbreak investigations. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Low-dimensional chaos in turbulence

NASA Technical Reports Server (NTRS)

Vastano, John A.

1989-01-01

Direct numerical simulations are being performed on two different fluid flows in an attempt to discover the mechanism underlying the transition to turbulence in each. The first system is Taylor-Couette flow; the second, two-dimensional flow over an airfoil. Both flows exhibit a gradual transition to high-dimensional turbulence through low-dimensional chaos. The hope is that the instabilities leading to chaos will be easier to relate to physical processes in this case, and that the understanding of these mechanisms can then be applied to a wider array of turbulent systems.

Chaos in plasma simulation and experiment

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

Watts, C.; Newman, D.E.; Sprott, J.C.

1993-09-01

We investigate the possibility that chaos and simple determinism are governing the dynamics of reversed field pinch (RFP) plasmas using data from both numerical simulations and experiment. A large repertoire of nonlinear analysis techniques is used to identify low dimensional chaos. These tools include phase portraits and Poincard sections, correlation dimension, the spectrum of Lyapunov exponents and short term predictability. In addition, nonlinear noise reduction techniques are applied to the experimental data in an attempt to extract any underlying deterministic dynamics. Two model systems are used to simulate the plasma dynamics. These are -the DEBS code, which models global RFPmore » dynamics, and the dissipative trapped electron mode (DTEM) model, which models drift wave turbulence. Data from both simulations show strong indications of low,dimensional chaos and simple determinism. Experimental data were obtained from the Madison Symmetric Torus RFP and consist of a wide array of both global and local diagnostic signals. None of the signals shows any indication of low dimensional chaos or other simple determinism. Moreover, most of the analysis tools indicate the experimental system is very high dimensional with properties similar to noise. Nonlinear noise reduction is unsuccessful at extracting an underlying deterministic system.« less

Chaos in nuclei: Theory and experiment

NASA Astrophysics Data System (ADS)

Muñoz, L.; Molina, R. A.; Gómez, J. M. G.

2018-05-01

During the last three decades the quest for chaos in nuclei has been quite intensive, both with theoretical calculations using nuclear models and with detailed analyses of experimental data. In this paper we outline the concept and characteristics of quantum chaos in two different approaches, the random matrix theory fluctuations and the time series fluctuations. Then we discuss the theoretical and experimental evidence of chaos in nuclei. Theoretical calculations, especially shell-model calculations, have shown a strongly chaotic behavior of bound states in regions of high level density. The analysis of experimental data has shown a strongly chaotic behavior of nuclear resonances just above the one-nucleon emission threshold. For bound states, combining experimental data of a large number of nuclei, a tendency towards chaotic motion is observed in spherical nuclei, while deformed nuclei exhibit a more regular behavior associated to the collective motion. On the other hand, it had never been possible to observe chaos in the experimental bound energy levels of any single nucleus. However, the complete experimental spectrum of the first 151 states up to excitation energies of 6.20 MeV in the 208Pb nucleus have been recently identified and the analysis of its spectral fluctuations clearly shows the existence of chaotic motion.

Criticality and Chaos in Systems of Communities

NASA Astrophysics Data System (ADS)

Ostilli, Massimo; Figueiredo, Wagner

2016-01-01

We consider a simple model of communities interacting via bilinear terms. After analyzing the thermal equilibrium case, which can be described by an Hamiltonian, we introduce the dynamics that, for Ising-like variables, reduces to a Glauber-like dynamics. We analyze and compare four different versions of the dynamics: flow (differential equations), map (discretetime dynamics), local-time update flow, and local-time update map. The presence of only bilinear interactions prevent the flow cases to develop any dynamical instability, the system converging always to the thermal equilibrium. The situation is different for the map when unfriendly couplings are involved, where period-two oscillations arise. In the case of the map with local-time updates, oscillations of any period and chaos can arise as a consequence of the reciprocal “tension” accumulated among the communities during their sleeping time interval. The resulting chaos can be of two kinds: true chaos characterized by positive Lyapunov exponent and bifurcation cascades, or marginal chaos characterized by zero Lyapunov exponent and critical continuous regions.

A CNN based neurobiology inspired approach for retinal image quality assessment.

PubMed

Mahapatra, Dwarikanath; Roy, Pallab K; Sedai, Suman; Garnavi, Rahil

2016-08-01

Retinal image quality assessment (IQA) algorithms use different hand crafted features for training classifiers without considering the working of the human visual system (HVS) which plays an important role in IQA. We propose a convolutional neural network (CNN) based approach that determines image quality using the underlying principles behind the working of the HVS. CNNs provide a principled approach to feature learning and hence higher accuracy in decision making. Experimental results demonstrate the superior performance of our proposed algorithm over competing methods.

The Nature (and Nurture) of Children's Perceptions of Family Chaos

ERIC Educational Resources Information Center

Hanscombe, Ken B.; Haworth, Claire M. A.; Davis, Oliver S. P.; Jaffee, Sara R.; Plomin, Robert

2010-01-01

Chaos in the home is a key environment in cognitive and behavioural development. However, we show that children's experience of home chaos is partly genetically mediated. We assessed children's perceptions of household chaos at ages 9 and 12 in 2337 pairs of twins. Using child-specific reports allowed us to use structural equation modelling to…

Chaos Theory as a Model for Managing Issues and Crises.

ERIC Educational Resources Information Center

Murphy, Priscilla

1996-01-01

Uses chaos theory to model public relations situations in which the salient feature is volatility of public perceptions. Discusses the premises of chaos theory and applies them to issues management, the evolution of interest groups, crises, and rumors. Concludes that chaos theory is useful as an analogy to structure image problems and to raise…

Weak nanoscale chaos and anomalous relaxation in DNA

NASA Astrophysics Data System (ADS)

Mazur, Alexey K.

2017-06-01

Anomalous nonexponential relaxation in hydrated biomolecules is commonly attributed to the complexity of the free-energy landscapes, similarly to polymers and glasses. It was found recently that the hydrogen-bond breathing of terminal DNA base pairs exhibits a slow power-law relaxation attributable to weak Hamiltonian chaos, with parameters similar to experimental data. Here, the relationship is studied between this motion and spectroscopic signals measured in DNA with a small molecular photoprobe inserted into the base-pair stack. To this end, the earlier computational approach in combination with an analytical theory is applied to the experimental DNA fragment. It is found that the intensity of breathing dynamics is strongly increased in the internal base pairs that flank the photoprobe, with anomalous relaxation quantitatively close to that in terminal base pairs. A physical mechanism is proposed to explain the coupling between the relaxation of base-pair breathing and the experimental response signal. It is concluded that the algebraic relaxation observed experimentally is very likely a manifestation of weakly chaotic dynamics of hydrogen-bond breathing in the base pairs stacked to the photoprobe and that the weak nanoscale chaos can represent an ubiquitous hidden source of nonexponential relaxation in ultrafast spectroscopy.

Weak nanoscale chaos and anomalous relaxation in DNA.

PubMed

Mazur, Alexey K

2017-06-01

Anomalous nonexponential relaxation in hydrated biomolecules is commonly attributed to the complexity of the free-energy landscapes, similarly to polymers and glasses. It was found recently that the hydrogen-bond breathing of terminal DNA base pairs exhibits a slow power-law relaxation attributable to weak Hamiltonian chaos, with parameters similar to experimental data. Here, the relationship is studied between this motion and spectroscopic signals measured in DNA with a small molecular photoprobe inserted into the base-pair stack. To this end, the earlier computational approach in combination with an analytical theory is applied to the experimental DNA fragment. It is found that the intensity of breathing dynamics is strongly increased in the internal base pairs that flank the photoprobe, with anomalous relaxation quantitatively close to that in terminal base pairs. A physical mechanism is proposed to explain the coupling between the relaxation of base-pair breathing and the experimental response signal. It is concluded that the algebraic relaxation observed experimentally is very likely a manifestation of weakly chaotic dynamics of hydrogen-bond breathing in the base pairs stacked to the photoprobe and that the weak nanoscale chaos can represent an ubiquitous hidden source of nonexponential relaxation in ultrafast spectroscopy.

Remote pedestrians detection at night time in FIR Image using contrast filtering and locally projected region based CNN

NASA Astrophysics Data System (ADS)

Kim, Taehwan; Kim, Sungho

2017-02-01

This paper presents a novel method to detect the remote pedestrians. After producing the human temperature based brightness enhancement image using the temperature data input, we generates the regions of interest (ROIs) by the multiscale contrast filtering based approach including the biased hysteresis threshold and clustering, remote pedestrian's height, pixel area and central position information. Afterwards, we conduct local vertical and horizontal projection based ROI refinement and weak aspect ratio based ROI limitation to solve the problem of region expansion in the contrast filtering stage. Finally, we detect the remote pedestrians by validating the final ROIs using transfer learning with convolutional neural network (CNN) feature, following non-maximal suppression (NMS) with strong aspect ratio limitation to improve the detection performance. In the experimental results, we confirmed that the proposed contrast filtering and locally projected region based CNN (CFLP-CNN) outperforms the baseline method by 8% in term of logaveraged miss rate. Also, the proposed method is more effective than the baseline approach and the proposed method provides the better regions that are suitably adjusted to the shape and appearance of remote pedestrians, which makes it detect the pedestrian that didn't find in the baseline approach and are able to help detect pedestrians by splitting the people group into a person.

Quasiperiodicity route to chaos in cardiac conduction model

NASA Astrophysics Data System (ADS)

Quiroz-Juárez, M. A.; Vázquez-Medina, R.; Ryzhii, E.; Ryzhii, M.; Aragón, J. L.

2017-01-01

It has been suggested that cardiac arrhythmias are instances of chaos. In particular that the ventricular fibrillation is a form of spatio-temporal chaos that arises from normal rhythm through a quasi-periodicity or Ruelle-Takens-Newhouse route to chaos. In this work, we modify the heterogeneous oscillator model of cardiac conduction system proposed in Ref. [Ryzhii E, Ryzhii M. A heterogeneous coupled oscillator model for simulation of ECG signals. Comput Meth Prog Bio 2014;117(1):40-49. doi:10.1016/j.cmpb.2014.04.009.], by including an ectopic pacemaker that stimulates the ventricular muscle to model arrhythmias. With this modification, the transition from normal rhythm to ventricular fibrillation is controlled by a single parameter. We show that this transition follows the so-called torus of quasi-periodic route to chaos, as verified by using numerical tools such as power spectrum and largest Lyapunov exponent.

The Importance of Chaos and Lenticulae on Europa for the JIMO Mission

NASA Technical Reports Server (NTRS)

Spaun, Nicole A.

2003-01-01

The Galileo Solid State Imaging (SSI) experiment provided high-resolution images of Europa's surface allowing identification of surface features barely distinguishable at Voyager's resolution. SSI revealed the visible pitting on Europa's surface to be due to large disrupted features, chaos, and smaller sub-circular patches, lenticulae. Chaos features contain a hummocky matrix material and commonly contain dislocated blocks of ridged plains. Lenticulae are morphologically interrelated and can be divided into three classes: domes, spots, and micro-chaos. Domes are broad, upwarped features that generally do not disrupt the texture of the ridged plains. Spots are areas of low albedo that are generally smooth in texture compared to other units. Micro-chaos are disrupted features with a hummocky matrix material, resembling that observed within chaos regions. Chaos and lenticulae are ubiquitous in the SSI regional map observations, which average approximately 200 meters per pixel (m/pxl) in resolution, and appear in several of the ultra-high resolution, i.e., better than 50 m/pxl, images of Europa as well. SSI also provided a number of multi-spectral observations of chaos and lenticulae. Using this dataset we have undertaken a thorough study of the morphology, size, spacing, stratigraphy, and color of chaos and lenticulae to determine their properties and evaluate models of their formation. Geological mapping indicates that chaos and micro-chaos have a similar internal morphology of in-situ degradation suggesting that a similar process was operating during their formation. The size distribution denotes a dominant size of 4-8 km in diameter for features containing hummocky material (i.e., chaos and micro-chaos). Results indicate a dominant spacing of 15 - 36 km apart. Chaos and lenticulae are generally among the youngest features stratigraphically observed on the surface, suggesting a recent change in resurfacing style. Also, the reddish non-icy materials on Europa

Generic superweak chaos induced by Hall effect

NASA Astrophysics Data System (ADS)

Ben-Harush, Moti; Dana, Itzhack

2016-05-01

We introduce and study the "kicked Hall system" (KHS), i.e., charged particles periodically kicked in the presence of uniform magnetic (B ) and electric (E ) fields that are perpendicular to each other and to the kicking direction. We show that for resonant values of B and E and in the weak-chaos regime of sufficiently small nonintegrability parameter κ (the kicking strength), there exists a generic family of periodic kicking potentials for which the Hall effect from B and E significantly suppresses the weak chaos, replacing it by "superweak" chaos (SWC). This means that the system behaves as if the kicking strength were κ2 rather than κ . For E =0 , SWC is known to be a classical fingerprint of quantum antiresonance, but it occurs under much less generic conditions, in particular only for very special kicking potentials. Manifestations of SWC are a decrease in the instability of periodic orbits and a narrowing of the chaotic layers, relative to the ordinary weak-chaos case. Also, for global SWC, taking place on an infinite "stochastic web" in phase space, the chaotic diffusion on the web is much slower than the weak-chaos one. Thus, the Hall effect can be relatively stabilizing for small κ . In some special cases, the effect is shown to cause ballistic motion for almost all parameter values. The generic global SWC on stochastic webs in the KHS appears to be the two-dimensional closest analog to the Arnol'd web in higher dimensional systems.

Chaos: A Topic for Interdisciplinary Education in Physics

ERIC Educational Resources Information Center

Bae, Saebyok

2009-01-01

Since society and science need interdisciplinary works, the interesting topic of chaos is chosen for interdisciplinary education in physics. The educational programme contains various university-level activities such as computer simulations, chaos experiment and team projects besides ordinary teaching. According to the participants, the programme…

Controlling chaos faster.

PubMed

Bick, Christian; Kolodziejski, Christoph; Timme, Marc

2014-09-01

Predictive feedback control is an easy-to-implement method to stabilize unknown unstable periodic orbits in chaotic dynamical systems. Predictive feedback control is severely limited because asymptotic convergence speed decreases with stronger instabilities which in turn are typical for larger target periods, rendering it harder to effectively stabilize periodic orbits of large period. Here, we study stalled chaos control, where the application of control is stalled to make use of the chaotic, uncontrolled dynamics, and introduce an adaptation paradigm to overcome this limitation and speed up convergence. This modified control scheme is not only capable of stabilizing more periodic orbits than the original predictive feedback control but also speeds up convergence for typical chaotic maps, as illustrated in both theory and application. The proposed adaptation scheme provides a way to tune parameters online, yielding a broadly applicable, fast chaos control that converges reliably, even for periodic orbits of large period.

Chaos and the (un)predictability of evolution in a changing environment

PubMed Central

Rego-Costa, Artur; Débarre, Florence; Chevin, Luis-Miguel

2018-01-01

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution, by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability. PMID:29235104

Household chaos, sociodemographic risk, coparenting, and parent-infant relations during infants' first year.

PubMed

Whitesell, Corey J; Teti, Douglas M; Crosby, Brian; Kim, Bo-Ram

2015-04-01

Household chaos is a construct often overlooked in studies of human development, despite its theoretical links with the integrity of individual well-being, family processes, and child development. The present longitudinal study examined relations between household chaos and well-established correlates of chaos (sociodemographic risk, major life events, and personal distress) and several constructs that, to date, are theoretically linked with chaos but never before assessed as correlates (quality of coparenting and emotional availability with infants at bedtime). In addressing this aim, we introduce a new measure of household chaos (the Descriptive In-home Survey of Chaos--Observer ReporteD, or DISCORD), wholly reliant on independent observer report, which draws from household chaos theory and prior empirical work but extends the measurement of chaos to include information about families' compliance with a home visiting protocol. Household chaos was significantly associated with socioeconomic risk, negative life events, less favorable coparenting, and less emotionally available bedtime parenting, but not with personal distress. These findings emphasize the need to examine household chaos as a direct and indirect influence on child and family outcomes, as a moderator of intervention attempts to improving parenting and child development, and as a target of intervention in its own right. (c) 2015 APA, all rights reserved).

Interplay of Determinism and Randomness: From Irreversibility to Chaos, Fractals, and Stochasticity

NASA Astrophysics Data System (ADS)

Tsonis, A.

2017-12-01

We will start our discussion into randomness by looking exclusively at our formal mathematical system to show that even in this pure and strictly logical system one cannot do away with randomness. By employing simple mathematical models, we will identify the three possible sources of randomness: randomness due to inability to find the rules (irreversibility), randomness due to inability to have infinite power (chaos), and randomness due to stochastic processes. Subsequently we will move from the mathematical system to our physical world to show that randomness, through the quantum mechanical character of small scales, through chaos, and because of the second law of thermodynamics, is an intrinsic property of nature as well. We will subsequently argue that the randomness in the physical world is consistent with the three sources of randomness suggested from the study of simple mathematical systems. Many examples ranging from purely mathematical to natural processes will be presented, which clearly demonstrate how the combination of rules and randomness produces the world we live in. Finally, the principle of least effort or the principle of minimum energy consumption will be suggested as the underlying principle behind this symbiosis between determinism and randomness.

Chaotic operation and chaos control of travelling wave ultrasonic motor.

PubMed

Shi, Jingzhuo; Zhao, Fujie; Shen, Xiaoxi; Wang, Xiaojie

2013-08-01

The travelling wave ultrasonic motor, which is a nonlinear dynamic system, has complex chaotic phenomenon with some certain choices of system parameters and external inputs, and its chaotic characteristics have not been studied until now. In this paper, the preliminary study of the chaos phenomenon in ultrasonic motor driving system has been done. The experiment of speed closed-loop control is designed to obtain several groups of time sampling data sequence of the amplitude of driving voltage, and phase-space reconstruction is used to analyze the chaos characteristics of these time sequences. The largest Lyapunov index is calculated and the result is positive, which shows that the travelling wave ultrasonic motor has chaotic characteristics in a certain working condition Then, the nonlinear characteristics of travelling wave ultrasonic motor are analyzed which includes Lyapunov exponent map, the bifurcation diagram and the locus of voltage relative to speed based on the nonlinear chaos model of a travelling wave ultrasonic motor. After that, two kinds of adaptive delay feedback controllers are designed in this paper to control and suppress chaos in USM speed control system. Simulation results show that the method can control unstable periodic orbits, suppress chaos in USM control system. Proportion-delayed feedback controller was designed following and arithmetic of fuzzy logic was used to adaptively adjust the delay time online. Simulation results show that this method could fast and effectively change the chaos movement into periodic or fixed-point movement and make the system enter into stable state from chaos state. Finally the chaos behavior was controlled. Copyright © 2013 Elsevier B.V. All rights reserved.

Chaos in learning a simple two-person game

PubMed Central

Sato, Yuzuru; Akiyama, Eizo; Farmer, J. Doyne

2002-01-01

We investigate the problem of learning to play the game of rock–paper–scissors. Each player attempts to improve her/his average score by adjusting the frequency of the three possible responses, using reinforcement learning. For the zero sum game the learning process displays Hamiltonian chaos. Thus, the learning trajectory can be simple or complex, depending on initial conditions. We also investigate the non-zero sum case and show that it can give rise to chaotic transients. This is, to our knowledge, the first demonstration of Hamiltonian chaos in learning a basic two-person game, extending earlier findings of chaotic attractors in dissipative systems. As we argue here, chaos provides an important self-consistency condition for determining when players will learn to behave as though they were fully rational. That chaos can occur in learning a simple game indicates one should use caution in assuming real people will learn to play a game according to a Nash equilibrium strategy. PMID:11930020

Does chaos theory have major implications for philosophy of medicine?

PubMed

Holm, S

2002-12-01

In the literature it is sometimes claimed that chaos theory, non-linear dynamics, and the theory of fractals have major implications for philosophy of medicine, especially for our analysis of the concept of disease and the concept of causation. This paper gives a brief introduction to the concepts underlying chaos theory and non-linear dynamics. It is then shown that chaos theory has only very minimal implications for the analysis of the concept of disease and the concept of causation, mainly because the mathematics of chaotic processes entail that these processes are fully deterministic. The practical unpredictability of chaotic processes, caused by their extreme sensitivity to initial conditions, may raise practical problems in diagnosis, prognosis, and treatment, but it raises no major theoretical problems. The relation between chaos theory and the problem of free will is discussed, and it is shown that chaos theory may remove the problem of predictability of decisions, but does not solve the problem of free will. Chaos theory may thus be very important for our understanding of physiological processes, and specific disease entities, without having any major implications for philosophy of medicine.

Biologically inspired rate control of chaos.

PubMed

Olde Scheper, Tjeerd V

2017-10-01

The overall intention of chaotic control is to eliminate chaos and to force the system to become stable in the classical sense. In this paper, I demonstrate a more subtle method that does not eliminate all traces of chaotic behaviour; yet it consistently, and reliably, can provide control as intended. The Rate Control of Chaos (RCC) method is derived from metabolic control processes and has several remarkable properties. RCC can control complex systems continuously, and unsupervised, it can also maintain control across bifurcations, and in the presence of significant systemic noise. Specifically, I show that RCC can control a typical set of chaotic models, including the 3 and 4 dimensional chaotic Lorenz systems, in all modes. Furthermore, it is capable of controlling spatiotemporal chaos without supervision and maintains control of the system across bifurcations. This property of RCC allows a dynamic system to operate in parameter spaces that are difficult to control otherwise. This may be particularly interesting for the control of forced systems or dynamic systems that are chaotically perturbed. These control properties of RCC are applicable to a range of dynamic systems, thereby appearing to have far-reaching effects beyond just controlling chaos. RCC may also point to the existence of a biochemical control function of an enzyme, to stabilise the dynamics of the reaction cascade.

Deterministic chaos in an ytterbium-doped mode-locked fiber laser

NASA Astrophysics Data System (ADS)

Mélo, Lucas B. A.; Palacios, Guillermo F. R.; Carelli, Pedro V.; Acioli, Lúcio H.; Rios Leite, José R.; de Miranda, Marcio H. G.

2018-05-01

We experimentally study the nonlinear dynamics of a femtosecond ytterbium doped mode-locked fiber laser. With the laser operating in the pulsed regime a route to chaos is presented, starting from stable mode-locking, period two, period four, chaos and period three regimes. Return maps and bifurcation diagrams were extracted from time series for each regime. The analysis of the time series with the laser operating in the quasi mode-locked regime presents deterministic chaos described by an unidimensional Rossler map. A positive Lyapunov exponent $\\lambda = 0.14$ confirms the deterministic chaos of the system. We suggest an explanation about the observed map by relating gain saturation and intra-cavity loss.

Chaos in charged AdS black hole extended phase space

NASA Astrophysics Data System (ADS)

Chabab, M.; El Moumni, H.; Iraoui, S.; Masmar, K.; Zhizeh, S.

2018-06-01

We present an analytical study of chaos in a charged black hole in the extended phase space in the context of the Poincare-Melnikov theory. Along with some background on dynamical systems, we compute the relevant Melnikov function and find its zeros. Then we analyse these zeros either to identify the temporal chaos in the spinodal region, or to observe spatial chaos in the small/large black hole equilibrium configuration. As a byproduct, we derive a constraint on the Black hole' charge required to produce chaotic behaviour. To the best of our knowledge, this is the first endeavour to understand the correlation between chaos and phase picture in black holes.

Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series

NASA Astrophysics Data System (ADS)

Sugihara, George; May, Robert M.

1990-04-01

An approach is presented for making short-term predictions about the trajectories of chaotic dynamical systems. The method is applied to data on measles, chickenpox, and marine phytoplankton populations, to show how apparent noise associated with deterministic chaos can be distinguished from sampling error and other sources of externally induced environmental noise.

Chaos and Christianity: A Response to Butz and a Biblical Alternative.

ERIC Educational Resources Information Center

Watts, Richard E.; Trusty, Jerry

1997-01-01

M.R. Butz's position regarding chaos theory and Christianity is reviewed. The compatibility of biblical theology and the sciences is discussed. Parallels between chaos theory and the philosophical perspective of Soren Kierkegaard are explored. A biblical model is offered for counselors in assisting Christian clients in embracing chaos. (Author/EMK)

Convergent chaos

NASA Astrophysics Data System (ADS)

Pradas, Marc; Pumir, Alain; Huber, Greg; Wilkinson, Michael

2017-07-01

Chaos is widely understood as being a consequence of sensitive dependence upon initial conditions. This is the result of an instability in phase space, which separates trajectories exponentially. Here, we demonstrate that this criterion should be refined. Despite their overall intrinsic instability, trajectories may be very strongly convergent in phase space over extremely long periods, as revealed by our investigation of a simple chaotic system (a realistic model for small bodies in a turbulent flow). We establish that this strong convergence is a multi-facetted phenomenon, in which the clustering is intense, widespread and balanced by lacunarity of other regions. Power laws, indicative of scale-free features, characterize the distribution of particles in the system. We use large-deviation and extreme-value statistics to explain the effect. Our results show that the interpretation of the ‘butterfly effect’ needs to be carefully qualified. We argue that the combination of mixing and clustering processes makes our specific model relevant to understanding the evolution of simple organisms. Lastly, this notion of convergent chaos, which implies the existence of conditions for which uncertainties are unexpectedly small, may also be relevant to the valuation of insurance and futures contracts.

Effect of smoothing on robust chaos.

PubMed

Deshpande, Amogh; Chen, Qingfei; Wang, Yan; Lai, Ying-Cheng; Do, Younghae

2010-08-01

In piecewise-smooth dynamical systems, situations can arise where the asymptotic attractors of the system in an open parameter interval are all chaotic (e.g., no periodic windows). This is the phenomenon of robust chaos. Previous works have established that robust chaos can occur through the mechanism of border-collision bifurcation, where border is the phase-space region where discontinuities in the derivatives of the dynamical equations occur. We investigate the effect of smoothing on robust chaos and find that periodic windows can arise when a small amount of smoothness is present. We introduce a parameter of smoothing and find that the measure of the periodic windows in the parameter space scales linearly with the parameter, regardless of the details of the smoothing function. Numerical support and a heuristic theory are provided to establish the scaling relation. Experimental evidence of periodic windows in a supposedly piecewise linear dynamical system, which has been implemented as an electronic circuit, is also provided.

Dynamic Ice-Water Interactions Form Europa's Chaos Terrains

NASA Astrophysics Data System (ADS)

Blankenship, D. D.; Schmidt, B. E.; Patterson, G. W.; Schenk, P.

2011-12-01

Unique to the surface of Europa, chaos terrain is diagnostic of the properties and dynamics of its icy shell. We present a new model that suggests large melt lenses form within the shell and that water-ice interactions above and within these lenses drive the production of chaos. This model is consistent with key observations of chaos, predicts observables for future missions, and indicates that the surface is likely still active today[1]. We apply lessons from ice-water interaction in the terrestrial cryosphere to hypothesize a dynamic lense-collapse model to for Europa's chaos terrain. Chaos terrain morphology, like that of Conamara chaos and Thera Macula, suggests a four-phase formation [1]: 1) Surface deflection occurs as ice melts over ascending thermal plumes, as regularly occurs on Earth as subglacial volcanoes activate. The same process can occur at Europa if thermal plumes cause pressure melt as they cross ice-impurity eutectics. 2) Resulting hydraulic gradients and driving forces produce a sealed, pressurized melt lense, akin to the hydraulic sealing of subglacial caldera lakes. On Europa, the water cannot escape the lense due to the horizontally continuous ice shell. 3) Extension of the brittle ice lid above the lense opens cracks, allowing for the ice to be hydrofractured by pressurized water. Fracture, brine injection and percolation within the ice and possible iceberg toppling produces ice-melange-like granular matrix material. 4) Refreezing of the melt lense and brine-filled pores and cracks within the matrix results in raised chaos. Brine soaking and injection concentrates the ice in brines and adds water volume to the shell. As this englacial water freezes, the now water-filled ice will expand, not unlike the process of forming pingos and other "expansion ice" phenomena on Earth. The refreezing can raise the surface and create the oft-observed matrix "domes" In this presentation, we describe how catastrophic ice-water interactions on Earth have

Chaos Theory: Implications for Nonlinear Dynamics in Counseling.

ERIC Educational Resources Information Center

Stickel, Sue A.

The purpose of this paper is to explore the implications of chaos theory for counseling. The scientific notion of chaos refers to the tendency of dynamical, nonlinear systems toward irregular, sometimes unpredictable, yet deterministic behavior. Therapists, especially those working from a brief approach, have noted the importance of the client's…

Chaos and Forecasting - Proceedings of the Royal Society Discussion Meeting

NASA Astrophysics Data System (ADS)

Tong, Howell

1995-04-01

The Table of Contents for the full book PDF is as follows: * Preface * Orthogonal Projection, Embedding Dimension and Sample Size in Chaotic Time Series from a Statistical Perspective * A Theory of Correlation Dimension for Stationary Time Series * On Prediction and Chaos in Stochastic Systems * Locally Optimized Prediction of Nonlinear Systems: Stochastic and Deterministic * A Poisson Distribution for the BDS Test Statistic for Independence in a Time Series * Chaos and Nonlinear Forecastability in Economics and Finance * Paradigm Change in Prediction * Predicting Nonuniform Chaotic Attractors in an Enzyme Reaction * Chaos in Geophysical Fluids * Chaotic Modulation of the Solar Cycle * Fractal Nature in Earthquake Phenomena and its Simple Models * Singular Vectors and the Predictability of Weather and Climate * Prediction as a Criterion for Classifying Natural Time Series * Measuring and Characterising Spatial Patterns, Dynamics and Chaos in Spatially-Extended Dynamical Systems and Ecologies * Non-Linear Forecasting and Chaos in Ecology and Epidemiology: Measles as a Case Study

Chaos and the (un)predictability of evolution in a changing environment.

PubMed

Rego-Costa, Artur; Débarre, Florence; Chevin, Luis-Miguel

2018-02-01

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Li-Yorke Chaos in Hybrid Systems on a Time Scale

NASA Astrophysics Data System (ADS)

Akhmet, Marat; Fen, Mehmet Onur

2015-12-01

By using the reduction technique to impulsive differential equations [Akhmet & Turan, 2006], we rigorously prove the presence of chaos in dynamic equations on time scales (DETS). The results of the present study are based on the Li-Yorke definition of chaos. This is the first time in the literature that chaos is obtained for DETS. An illustrative example is presented by means of a Duffing equation on a time scale.

Synchronisation of chaos and its applications

NASA Astrophysics Data System (ADS)

Eroglu, Deniz; Lamb, Jeroen S. W.; Pereira, Tiago

2017-07-01

Dynamical networks are important models for the behaviour of complex systems, modelling physical, biological and societal systems, including the brain, food webs, epidemic disease in populations, power grids and many other. Such dynamical networks can exhibit behaviour in which deterministic chaos, exhibiting unpredictability and disorder, coexists with synchronisation, a classical paradigm of order. We survey the main theory behind complete, generalised and phase synchronisation phenomena in simple as well as complex networks and discuss applications to secure communications, parameter estimation and the anticipation of chaos.

The uncertainty principle and quantum chaos

NASA Technical Reports Server (NTRS)

Chirikov, Boris V.

1993-01-01

The conception of quantum chaos is described in some detail. The most striking feature of this novel phenomenon is that all the properties of classical dynamical chaos persist here but, typically, on the finite and different time scales only. The ultimate origin of such a universal quantum stability is in the fundamental uncertainty principle which makes discrete the phase space and, hence, the spectrum of bounded quantum motion. Reformulation of the ergodic theory, as a part of the general theory of dynamical systems, is briefly discussed.

Some new surprises in chaos.

PubMed

Bunimovich, Leonid A; Vela-Arevalo, Luz V

2015-09-01

"Chaos is found in greatest abundance wherever order is being sought.It always defeats order, because it is better organized"Terry PratchettA brief review is presented of some recent findings in the theory of chaotic dynamics. We also prove a statement that could be naturally considered as a dual one to the Poincaré theorem on recurrences. Numerical results demonstrate that some parts of the phase space of chaotic systems are more likely to be visited earlier than other parts. A new class of chaotic focusing billiards is discussed that clearly violates the main condition considered to be necessary for chaos in focusing billiards.

Extension of spatiotemporal chaos in glow discharge-semiconductor systems.

PubMed

Akhmet, Marat; Rafatov, Ismail; Fen, Mehmet Onur

2014-12-01

Generation of chaos in response systems is discovered numerically through specially designed unidirectional coupling of two glow discharge-semiconductor systems. By utilizing the auxiliary system approach, [H. D. I. Abarbanel, N. F. Rulkov, and M. M. Sushchik, Phys. Rev. E 53, 4528-4535 (1996)] it is verified that the phenomenon is not a chaos synchronization. Simulations demonstrate various aspects of the chaos appearance in both drive and response systems. Chaotic control is through the external circuit equation and governs the electrical potential on the boundary. The expandability of the theory to collectives of glow discharge systems is discussed, and this increases the potential of applications of the results. Moreover, the research completes the previous discussion of the chaos appearance in a glow discharge-semiconductor system [D. D. Šijačić U. Ebert, and I. Rafatov, Phys. Rev. E 70, 056220 (2004).].

"I Had Seen Order and Chaos, but Had Thought They Were Different." The Challenges of the Chaos Theory for Career Development

ERIC Educational Resources Information Center

Pryor, Robert; Bright, Jim

2004-01-01

This paper highlights five challenges to the accepted wisdom in career development theory and practice. It presents the chaos theory of careers and argues that the chaos theory provides a more complete and authentic account of human behaviour. The paper argues that positivism, reductionism and assumptions of linearity are inappropriate for…

Applying Chaos Theory to Lesson Planning and Delivery

ERIC Educational Resources Information Center

Cvetek, Slavko

2008-01-01

In this article, some of the ways in which thinking about chaos theory can help teachers and student-teachers to accept uncertainty and randomness as natural conditions in the classroom are considered. Building on some key features of complex systems commonly attributed to chaos theory (e.g. complexity, nonlinearity, sensitivity to initial…

Planning in Higher Education and Chaos Theory: A Model, a Method.

ERIC Educational Resources Information Center

Cutright, Marc

This paper proposes a model, based on chaos theory, that explores strategic planning in higher education. It notes that chaos theory was first developed in the physical sciences to explain how apparently random activity was, in fact, complexity patterned. The paper goes on to describe how chaos theory has subsequently been applied to the social…

Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

PubMed

Guo, Hao; Wu, Danni; An, Jubai

2017-08-09

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.

Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN

PubMed Central

An, Jubai

2017-01-01

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features. PMID:28792477

Conduct problems, IQ, and household chaos: a longitudinal multi-informant study

PubMed Central

Deater-Deckard, Kirby; Mullineaux, Paula Y.; Beekman, Charles; Petrill, Stephen A.; Schatschneider, Chris; Thompson, Lee A.

2010-01-01

Background We tested the hypothesis that household chaos would be associated with lower child IQ and more child conduct problems concurrently and longitudinally over two years while controlling for housing conditions, parent education/IQ, literacy environment, parental warmth/negativity, and stressful events. Methods The sample included 302 families with same-sex twins (58% female) in Kindergarten/1st grade at the first assessment. Parents’ and observers’ ratings were gathered, with some collected over a two-year period. Results Chaos varied widely. There was substantial mother–father agreement and longitudinal stability. Chaos covaried with poorer housing conditions, lower parental education/IQ, poorer home literacy environment, higher stress, higher negativity and lower warmth. Chaos statistically predicted lower IQ and more conduct problems, beyond the effects of other home environment factors. Conclusions Even with other home environment factors controlled, higher levels of chaos were linked concurrently with lower child IQ, and concurrently and longitudinally with more child conduct problems. Parent self-reported chaos represents an important aspect of housing and family functioning, with respect to children’s cognitive and behavioral functioning. PMID:19527431

Early Exposure to Environmental Chaos and Children's Physical and Mental Health.

PubMed

Coley, Rebekah Levine; Lynch, Alicia Doyle; Kull, Melissa

Environmental chaos has been proposed as a central influence impeding children's health and development, with the potential for particularly pernicious effects during the earliest years when children are most susceptible to environmental insults. This study evaluated a high-risk sample, following 495 low-income children living in poor urban neighborhoods from infancy to age 6. Longitudinal multilevel models tested the main tenets of the ecobiodevelopmental theory, finding that: (1) numerous distinct domains of environmental chaos were associated with children's physical and mental health outcomes, including housing disorder, neighborhood disorder, and relationship instability, with no significant results for residential instability; (2) different patterns emerged in relation to the timing of exposure to chaos, with more proximal exposure most strongly associated with children's functioning; and (3) the intensity of chaos also was a robust predictor of child functioning. Contrary to expectations, neither biological vulnerability (proxied through low birth weight status), maternal sensitivity, nor maternal distress moderated the role of chaos. Rather, maternal psychological distress functioned as a pathway through which environmental chaos was associated with children's functioning.

Atypical epigenetic mark in an atypical location: cytosine methylation at asymmetric (CNN) sites within the body of a non-repetitive tomato gene.

PubMed

González, Rodrigo M; Ricardi, Martiniano M; Iusem, Norberto D

2011-05-20

Eukaryotic DNA methylation is one of the most studied epigenetic processes, as it results in a direct and heritable covalent modification triggered by external stimuli. In contrast to mammals, plant DNA methylation, which is stimulated by external cues exemplified by various abiotic types of stress, is often found not only at CG sites but also at CNG (N denoting A, C or T) and CNN (asymmetric) sites. A genome-wide analysis of DNA methylation in Arabidopsis has shown that CNN methylation is preferentially concentrated in transposon genes and non-coding repetitive elements. We are particularly interested in investigating the epigenetics of plant species with larger and more complex genomes than Arabidopsis, particularly with regards to the associated alterations elicited by abiotic stress. We describe the existence of CNN-methylated epialleles that span Asr1, a non-transposon, protein-coding gene from tomato plants that lacks an orthologous counterpart in Arabidopsis. In addition, to test the hypothesis of a link between epigenetics modifications and the adaptation of crop plants to abiotic stress, we exhaustively explored the cytosine methylation status in leaf Asr1 DNA, a model gene in our system, resulting from water-deficit stress conditions imposed on tomato plants. We found that drought conditions brought about removal of methyl marks at approximately 75 of the 110 asymmetric (CNN) sites analysed, concomitantly with a decrease of the repressive H3K27me3 epigenetic mark and a large induction of expression at the RNA level. When pinpointing those sites, we observed that demethylation occurred mostly in the intronic region. These results demonstrate a novel genomic distribution of CNN methylation, namely in the transcribed region of a protein-coding, non-repetitive gene, and the changes in those epigenetic marks that are caused by water stress. These findings may represent a general mechanism for the acquisition of new epialleles in somatic cells, which are

The Chaos Theory of Careers: A User's Guide

ERIC Educational Resources Information Center

Bright, Jim E. H.; Pryor, Robert G. L.

2005-01-01

The purpose of this article is to set out the key elements of the Chaos Theory of Careers. The complexity of influences on career development presents a significant challenge to traditional predictive models of career counseling. Chaos theory can provide a more appropriate description of career behavior, and the theory can be applied with clients…

Electro-optic chaotic system based on the reverse-time chaos theory and a nonlinear hybrid feedback loop.

PubMed

Jiang, Xingxing; Cheng, Mengfan; Luo, Fengguang; Deng, Lei; Fu, Songnian; Ke, Changjian; Zhang, Minming; Tang, Ming; Shum, Ping; Liu, Deming

2016-12-12

A novel electro-optic chaos source is proposed on the basis of the reverse-time chaos theory and an analog-digital hybrid feedback loop. The analog output of the system can be determined by the numeric states of shift registers, which makes the system robust and easy to control. The dynamical properties as well as the complexity dependence on the feedback parameters are investigated in detail. The correlation characteristics of the system are also studied. Two improving strategies which were established in digital field and analog field are proposed to conceal the time-delay signature. The proposed scheme has the potential to be used in radar and optical secure communication systems.

Identifying Corresponding Patches in SAR and Optical Images With a Pseudo-Siamese CNN

NASA Astrophysics Data System (ADS)

Hughes, Lloyd H.; Schmitt, Michael; Mou, Lichao; Wang, Yuanyuan; Zhu, Xiao Xiang

2018-05-01

In this letter, we propose a pseudo-siamese convolutional neural network (CNN) architecture that enables to solve the task of identifying corresponding patches in very-high-resolution (VHR) optical and synthetic aperture radar (SAR) remote sensing imagery. Using eight convolutional layers each in two parallel network streams, a fully connected layer for the fusion of the features learned in each stream, and a loss function based on binary cross-entropy, we achieve a one-hot indication if two patches correspond or not. The network is trained and tested on an automatically generated dataset that is based on a deterministic alignment of SAR and optical imagery via previously reconstructed and subsequently co-registered 3D point clouds. The satellite images, from which the patches comprising our dataset are extracted, show a complex urban scene containing many elevated objects (i.e. buildings), thus providing one of the most difficult experimental environments. The achieved results show that the network is able to predict corresponding patches with high accuracy, thus indicating great potential for further development towards a generalized multi-sensor key-point matching procedure. Index Terms-synthetic aperture radar (SAR), optical imagery, data fusion, deep learning, convolutional neural networks (CNN), image matching, deep matching

5W1H Information Extraction with CNN-Bidirectional LSTM

NASA Astrophysics Data System (ADS)

Nurdin, A.; Maulidevi, N. U.

2018-03-01

In this work, information about who, did what, when, where, why, and how on Indonesian news articles were extracted by combining Convolutional Neural Network and Bidirectional Long Short-Term Memory. Convolutional Neural Network can learn semantically meaningful representations of sentences. Bidirectional LSTM can analyze the relations among words in the sequence. We also use word embedding word2vec for word representation. By combining these algorithms, we obtained F-measure 0.808. Our experiments show that CNN-BLSTM outperforms other shallow methods, namely IBk, C4.5, and Naïve Bayes with the F-measure 0.655, 0.645, and 0.595, respectively.

Fuzzy-C-Means Clustering Based Segmentation and CNN-Classification for Accurate Segmentation of Lung Nodules

PubMed

K, Jalal Deen; R, Ganesan; A, Merline

2017-07-27

Objective: Accurate segmentation of abnormal and healthy lungs is very crucial for a steadfast computer-aided disease diagnostics. Methods: For this purpose a stack of chest CT scans are processed. In this paper, novel methods are proposed for segmentation of the multimodal grayscale lung CT scan. In the conventional methods using Markov–Gibbs Random Field (MGRF) model the required regions of interest (ROI) are identified. Result: The results of proposed FCM and CNN based process are compared with the results obtained from the conventional method using MGRF model. The results illustrate that the proposed method can able to segment the various kinds of complex multimodal medical images precisely. Conclusion: However, in this paper, to obtain an exact boundary of the regions, every empirical dispersion of the image is computed by Fuzzy C-Means Clustering segmentation. A classification process based on the Convolutional Neural Network (CNN) classifier is accomplished to distinguish the normal tissue and the abnormal tissue. The experimental evaluation is done using the Interstitial Lung Disease (ILD) database. Creative Commons Attribution License

Fuzzy-C-Means Clustering Based Segmentation and CNN-Classification for Accurate Segmentation of Lung Nodules

PubMed Central

K, Jalal Deen; R, Ganesan; A, Merline

2017-01-01

Objective: Accurate segmentation of abnormal and healthy lungs is very crucial for a steadfast computer-aided disease diagnostics. Methods: For this purpose a stack of chest CT scans are processed. In this paper, novel methods are proposed for segmentation of the multimodal grayscale lung CT scan. In the conventional methods using Markov–Gibbs Random Field (MGRF) model the required regions of interest (ROI) are identified. Result: The results of proposed FCM and CNN based process are compared with the results obtained from the conventional method using MGRF model. The results illustrate that the proposed method can able to segment the various kinds of complex multimodal medical images precisely. Conclusion: However, in this paper, to obtain an exact boundary of the regions, every empirical dispersion of the image is computed by Fuzzy C-Means Clustering segmentation. A classification process based on the Convolutional Neural Network (CNN) classifier is accomplished to distinguish the normal tissue and the abnormal tissue. The experimental evaluation is done using the Interstitial Lung Disease (ILD) database. PMID:28749127

Extension of spatiotemporal chaos in glow discharge-semiconductor systems

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

Akhmet, Marat, E-mail: marat@metu.edu.tr; Fen, Mehmet Onur; Rafatov, Ismail

2014-12-15

Generation of chaos in response systems is discovered numerically through specially designed unidirectional coupling of two glow discharge-semiconductor systems. By utilizing the auxiliary system approach, [H. D. I. Abarbanel, N. F. Rulkov, and M. M. Sushchik, Phys. Rev. E 53, 4528–4535 (1996)] it is verified that the phenomenon is not a chaos synchronization. Simulations demonstrate various aspects of the chaos appearance in both drive and response systems. Chaotic control is through the external circuit equation and governs the electrical potential on the boundary. The expandability of the theory to collectives of glow discharge systems is discussed, and this increases themore » potential of applications of the results. Moreover, the research completes the previous discussion of the chaos appearance in a glow discharge-semiconductor system [D. D. Šijačić U. Ebert, and I. Rafatov, Phys. Rev. E 70, 056220 (2004).].« less

Home Chaos: Sociodemographic, Parenting, Interactional, and Child Correlates

ERIC Educational Resources Information Center

Dumas, Jean E.; Nissley, Jenelle; Nordstrom, Alicia; Smith, Emilie Phillips; Prinz, Ronald J.; Levine, Douglas W.

2005-01-01

We conducted 2 studies to (a) establish the usefulness of the construct of home chaos, (b) investigate its correlates, and (c) determine the validity of the Confusion, Hubbub, and Order Scale (CHAOS) used to measure the construct in each study. Study 1 relied on a sample of European American preschoolers and their mothers and Study 2 on a sample…

Lane marking detection based on waveform analysis and CNN

NASA Astrophysics Data System (ADS)

Ye, Yang Yang; Chen, Hou Jin; Hao, Xiao Li

2017-06-01

Lane markings detection is a very important part of the ADAS to avoid traffic accidents. In order to obtain accurate lane markings, in this work, a novel and efficient algorithm is proposed, which analyses the waveform generated from the road image after inverse perspective mapping (IPM). The algorithm includes two main stages: the first stage uses an image preprocessing including a CNN to reduce the background and enhance the lane markings. The second stage obtains the waveform of the road image and analyzes the waveform to get lanes. The contribution of this work is that we introduce local and global features of the waveform to detect the lane markings. The results indicate the proposed method is robust in detecting and fitting the lane markings.

Topographic variations in chaos on Europa: Implications for diapiric formation

NASA Technical Reports Server (NTRS)

Schenk, Paul M.; Pappalardo, Robert T.

2004-01-01

Disrupted terrain, or chaos, on Europa, might have formed through melting of a floating ice shell from a subsurface ocean [Cam et al., 1998; Greenberg et al., 19991, or breakup by diapirs rising from the warm lower portion of the ice shell [Head and Pappalardo, 1999; Collins et al., 20001. Each model makes specific and testable predictions for topographic expression within chaos and relative to surrounding terrains on local and regional scales. High-resolution stereo-controlled photoclinometric topography indicates that chaos topography, including the archetypal Conamara Chaos region, is uneven and commonly higher than surrounding plains by up to 250 m. Elevated and undulating topography is more consistent with diapiric uplift of deep material in a relatively thick ice shell, rather than melt-through and refreezing of regionally or globally thin ice by a subsurface ocean. Vertical and horizontal scales of topographic doming in Conamara Chaos are consistent with a total ice shell thickness >15 km. Contact between Europa's ocean and surface may most likely be indirectly via diapirism or convection.

Topographic variations in chaos on Europa: Implications for diapiric formation

NASA Astrophysics Data System (ADS)

Schenk, Paul M.; Pappalardo, Robert T.

2004-08-01

Disrupted terrain, or chaos, on Europa, might have formed through melting of a floating ice shell from a subsurface ocean [Carr et al., 1998; Greenberg et al., 1999], or breakup by diapirs rising from the warm lower portion of the ice shell [Head and Pappalardo, 1999; Collins et al., 2000]. Each model makes specific and testable predictions for topographic expression within chaos and relative to surrounding terrains on local and regional scales. High-resolution stereo-controlled photoclinometric topography indicates that chaos topography, including the archetypal Conamara Chaos region, is uneven and commonly higher than surrounding plains by up to 250 m. Elevated and undulating topography is more consistent with diapiric uplift of deep material in a relatively thick ice shell, rather than melt-through and refreezing of regionally or globally thin ice by a subsurface ocean. Vertical and horizontal scales of topographic doming in Conamara Chaos are consistent with a total ice shell thickness >15 km. Contact between Europa's ocean and surface may most likely be indirectly via diapirism or convection.

Transient chaos - a resolution of breakdown of quantum-classical correspondence in optomechanics.

PubMed

Wang, Guanglei; Lai, Ying-Cheng; Grebogi, Celso

2016-10-17

Recently, the phenomenon of quantum-classical correspondence breakdown was uncovered in optomechanics, where in the classical regime the system exhibits chaos but in the corresponding quantum regime the motion is regular - there appears to be no signature of classical chaos whatsoever in the corresponding quantum system, generating a paradox. We find that transient chaos, besides being a physically meaningful phenomenon by itself, provides a resolution. Using the method of quantum state diffusion to simulate the system dynamics subject to continuous homodyne detection, we uncover transient chaos associated with quantum trajectories. The transient behavior is consistent with chaos in the classical limit, while the long term evolution of the quantum system is regular. Transient chaos thus serves as a bridge for the quantum-classical transition (QCT). Strikingly, as the system transitions from the quantum to the classical regime, the average chaotic transient lifetime increases dramatically (faster than the Ehrenfest time characterizing the QCT for isolated quantum systems). We develop a physical theory to explain the scaling law.

Manifestation of resonance-related chaos in coupled Josephson junctions

NASA Astrophysics Data System (ADS)

Shukrinov, Yu. M.; Hamdipour, M.; Kolahchi, M. R.; Botha, A. E.; Suzuki, M.

2012-11-01

Manifestation of chaos in the temporal dependence of the electric charge is demonstrated through the calculation of the maximal Lyapunov exponent, phase-charge and charge-charge Lissajous diagrams and correlation functions. It is found that the number of junctions in the stack strongly influences the fine structure in the current-voltage characteristics and a strong proximity effect results from the nonperiodic boundary conditions. The observed resonance-related chaos exhibits intermittency. The criteria for a breakpoint region with no chaos are obtained. Such criteria could clarify recent experimental observations of variations in the power output from intrinsic Josephson junctions in high temperature superconductors.

Hydaspis Chaos

NASA Technical Reports Server (NTRS)

2002-01-01

[figure removed for brevity, see original site]

Collapsed terrain in Hydapsis Chaos.

This is the source terrain for several outflow channels. Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

VIS Instrument. Latitude 3.2, Longitude 333.2 East. 19 meter/pixel resolution.

Controlling Mackey-Glass chaos.

PubMed

Kiss, Gábor; Röst, Gergely

2017-11-01

The Mackey-Glass equation is the representative example of delay induced chaotic behavior. Here, we propose various control mechanisms so that otherwise erratic solutions are forced to converge to the positive equilibrium or to a periodic orbit oscillating around that equilibrium. We take advantage of some recent results of the delay differential literature, when a sufficiently large domain of the phase space has been shown to be attractive and invariant, where the system is governed by monotone delayed feedback and chaos is not possible due to some Poincaré-Bendixson type results. We systematically investigate what control mechanisms are suitable to drive the system into such a situation and prove that constant perturbation, proportional feedback control, Pyragas control, and state dependent delay control can all be efficient to control Mackey-Glass chaos with properly chosen control parameters.

Controlling Mackey-Glass chaos

NASA Astrophysics Data System (ADS)

Kiss, Gábor; Röst, Gergely

2017-11-01

The Mackey-Glass equation is the representative example of delay induced chaotic behavior. Here, we propose various control mechanisms so that otherwise erratic solutions are forced to converge to the positive equilibrium or to a periodic orbit oscillating around that equilibrium. We take advantage of some recent results of the delay differential literature, when a sufficiently large domain of the phase space has been shown to be attractive and invariant, where the system is governed by monotone delayed feedback and chaos is not possible due to some Poincaré-Bendixson type results. We systematically investigate what control mechanisms are suitable to drive the system into such a situation and prove that constant perturbation, proportional feedback control, Pyragas control, and state dependent delay control can all be efficient to control Mackey-Glass chaos with properly chosen control parameters.

A Chaos MIMO-OFDM Scheme for Mobile Communication with Physical-Layer Security

NASA Astrophysics Data System (ADS)

Okamoto, Eiji

Chaos communications enable a physical-layer security, which can enhance the transmission security in combining with upper-layer encryption techniques, or can omit the upper-layer secure protocol and enlarges the transmission efficiency. However, the chaos communication usually degrades the error rate performance compared to unencrypted digital modulations. To achieve both physical-layer security and channel coding gain, we have proposed a chaos multiple-input multiple-output (MIMO) scheme in which a rate-one chaos convolution is applied to MIMO multiplexing. However, in the conventional study only flat fading is considered. To apply this scheme to practical mobile environments, i.e., multipath fading channels, we propose a chaos MIMO-orthogonal frequency division multi-plexing (OFDM) scheme and show its effectiveness through computer simulations.

Chaos, Fractals, and Polynomials.

ERIC Educational Resources Information Center

Tylee, J. Louis; Tylee, Thomas B.

1996-01-01

Discusses chaos theory; linear algebraic equations and the numerical solution of polynomials, including the use of the Newton-Raphson technique to find polynomial roots; fractals; search region and coordinate systems; convergence; and generating color fractals on a computer. (LRW)

Atlantis Chaos - False Color

NASA Image and Video Library

2014-12-23

The THEMIS VIS camera contains 5 filters. The data from different filters can be combined in multiple ways to create a false color image. This false color image from NASA 2001 Mars Odyssey spacecraft shows part of Atlantis Chaos.

The "Chaos" Pattern in Piaget's Theory of Cognitive Development.

ERIC Educational Resources Information Center

Lindsay, Jean S.

Piaget's theory of the cognitive development of the child is related to the recently developed non-linear "chaos" model. The term "chaos" refers to the tendency of dynamical, non-linear systems toward irregular, sometimes unpredictable, deterministic behavior. Piaget identified this same pattern in his model of cognitive…

Developing Quality Preschool Movement Programs: CHAOS and KinderPlay

ERIC Educational Resources Information Center

Robert, Darren L.; Yongue, Bill

2004-01-01

This article presents two models for creating new developmentally appropriate preschool movement programs: CHAOS (Children Helping Adults Open Senses) at Eastern Connecticut State University and "KinderPlay" at Florida International University. CHAOS and KinderPlay utilize skill themes and movement concepts as their focus and incorporate…

H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

NASA Technical Reports Server (NTRS)

Kalia, Subodh; Ganguly, Sangram; Li, Shuang; Nemani, Ramakrishna R.

2017-01-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

Specifying the Links Between Household Chaos and Preschool Children’s Development

PubMed Central

Martin, Anne; Razza, Rachel; Brooks-Gunn, Jeanne

2011-01-01

Household chaos has been linked to poorer cognitive, behavioral, and self-regulatory outcomes in young children, but the mechanisms responsible remain largely unknown. Using a diverse sample of families in Chicago, the present study tests for the independent contributions made by five indicators of household chaos: noise, crowding, family instability, lack of routine, and television usually on. Chaos was measured at age 2; outcomes measured at age 5 tap receptive vocabulary, attention and behavior problems, and effortful control. Results show that controlling for all other measures of chaos, children with a lack of routine scored lower on receptive vocabulary and delayed gratification, while children whose television was generally on scored higher on aggression and attention problems. The provision of learning materials mediated a small part of the association between television and receptive vocabulary. Family instability, crowding, and noise did not predict any outcomes once other measures of chaos were controlled. PMID:22919120

How does the Xenopus laevis embryonic cell cycle avoid spatial chaos?

PubMed Central

Gelens, Lendert; Huang, Kerwyn Casey; Ferrell, James E.

2015-01-01

Summary Theoretical studies have shown that a deterministic biochemical oscillator can become chaotic when operating over a sufficiently large volume, and have suggested that the Xenopus laevis cell cycle oscillator operates close to such a chaotic regime. To experimentally test this hypothesis, we decreased the speed of the post-fertilization calcium wave, which had been predicted to generate chaos. However, cell divisions were found to develop normally and eggs developed into normal tadpoles. Motivated by these experiments, we carried out modeling studies to understand the prerequisites for the predicted spatial chaos. We showed that this type of spatial chaos requires oscillatory reaction dynamics with short pulse duration, and postulated that the mitotic exit in Xenopus laevis is likely slow enough to avoid chaos. In systems with shorter pulses, chaos may be an important hazard, as in cardiac arrhythmias, or a useful feature, as in the pigmentation of certain mollusk shells. PMID:26212326

[Chaos theory: a fascinating concept for oncologists].

PubMed

Denis, F; Letellier, C

2012-05-01

The oncologist is confronted daily by questions related to the fact that any patient presents a specific evolution for his cancer: he is challenged by very different, unexpected and often unpredictable outcomes, in some of his patients. The mathematical approach used today to describe this evolution has recourse to statistics and probability laws: such an approach does not ultimately apply to one particular patient, but to a given more or less heterogeneous population. This approach therefore poorly characterizes the dynamics of this disease and does not allow to state whether a patient is cured, to predict if he will relapse and when this could occur, and in what form, nor to predict the response to treatment and, in particular, to radiation therapy. Chaos theory, not well known by oncologists, could allow a better understanding of these issues. Developed to investigate complex systems producing behaviours that cannot be predicted due to a great sensitivity to initial conditions, chaos theory is rich of suitable concepts for a new approach of cancer dynamics. This article is three-fold: to provide a brief introduction to chaos theory, to clarify the main connecting points between chaos and carcinogenesis and to point out few promising research perspectives, especially in radiotherapy. Copyright © 2012 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Fractals and Chaos

DTIC Science & Technology

1991-06-01

22 C. AFFINE TRANSFORMATIONS OF THE PLANE ........................... 25 D. CONTRACTION MAPPINGS OF THE SPACE gi(X...Henri Poincare (1854-1912) knew about chaos in dynamical systems in the late nineteenth century. Additionally, the French mathematicians Pierre Fatou...portion) are presented in the Euclidean plane , with a brief mention of more abstract spaces where applicable. Mathematical proofs that can be

Chaos Theory and Its Application to Education: Mehmet Akif Ersoy University Case

ERIC Educational Resources Information Center

Akmansoy, Vesile; Kartal, Sadik

2014-01-01

Discussions have arisen regarding the application of the new paradigms of chaos theory to social sciences as compared to physical sciences. This study examines what role chaos theory has within the education process and what effect it has by describing the views of university faculty regarding chaos and education. The participants in this study…

Error function attack of chaos synchronization based encryption schemes.

PubMed

Wang, Xingang; Zhan, Meng; Lai, C-H; Gang, Hu

2004-03-01

Different chaos synchronization based encryption schemes are reviewed and compared from the practical point of view. As an efficient cryptanalysis tool for chaos encryption, a proposal based on the error function attack is presented systematically and used to evaluate system security. We define a quantitative measure (quality factor) of the effective applicability of a chaos encryption scheme, which takes into account the security, the encryption speed, and the robustness against channel noise. A comparison is made of several encryption schemes and it is found that a scheme based on one-way coupled chaotic map lattices performs outstandingly well, as judged from quality factor. Copyright 2004 American Institute of Physics.

Early Exposure to Environmental Chaos and Children’s Physical and Mental Health

PubMed Central

Coley, Rebekah Levine; Lynch, Alicia Doyle; Kull, Melissa

2015-01-01

Environmental chaos has been proposed as a central influence impeding children’s health and development, with the potential for particularly pernicious effects during the earliest years when children are most susceptible to environmental insults. This study evaluated a high-risk sample, following 495 low-income children living in poor urban neighborhoods from infancy to age 6. Longitudinal multilevel models tested the main tenets of the ecobiodevelopmental theory, finding that: (1) numerous distinct domains of environmental chaos were associated with children’s physical and mental health outcomes, including housing disorder, neighborhood disorder, and relationship instability, with no significant results for residential instability; (2) different patterns emerged in relation to the timing of exposure to chaos, with more proximal exposure most strongly associated with children’s functioning; and (3) the intensity of chaos also was a robust predictor of child functioning. Contrary to expectations, neither biological vulnerability (proxied through low birth weight status), maternal sensitivity, nor maternal distress moderated the role of chaos. Rather, maternal psychological distress functioned as a pathway through which environmental chaos was associated with children’s functioning. PMID:25844016

Transient chaos - a resolution of breakdown of quantum-classical correspondence in optomechanics

PubMed Central

Wang, Guanglei; Lai, Ying-Cheng; Grebogi, Celso

2016-01-01

Recently, the phenomenon of quantum-classical correspondence breakdown was uncovered in optomechanics, where in the classical regime the system exhibits chaos but in the corresponding quantum regime the motion is regular - there appears to be no signature of classical chaos whatsoever in the corresponding quantum system, generating a paradox. We find that transient chaos, besides being a physically meaningful phenomenon by itself, provides a resolution. Using the method of quantum state diffusion to simulate the system dynamics subject to continuous homodyne detection, we uncover transient chaos associated with quantum trajectories. The transient behavior is consistent with chaos in the classical limit, while the long term evolution of the quantum system is regular. Transient chaos thus serves as a bridge for the quantum-classical transition (QCT). Strikingly, as the system transitions from the quantum to the classical regime, the average chaotic transient lifetime increases dramatically (faster than the Ehrenfest time characterizing the QCT for isolated quantum systems). We develop a physical theory to explain the scaling law. PMID:27748418

Identifikationsverfahren zur Analyse von EEG-Signalen bei Epilepsie mit Reaktions-Diffusions Netzwerken

NASA Astrophysics Data System (ADS)

Gollas, F.; Tetzlaff, R.

2007-06-01

Partielle Differentialgleichungen des Reaktions-Diffusions-Typs beschreiben Phänomene wie Musterbildung, nichtlineare Wellenausbreitung und deterministisches Chaos und werden oft zur Untersuchung komplexer Vorgänge auf den Gebieten der Biologie, Chemie und Physik herangezogen. Zellulare Nichtlineare Netzwerke (CNN) sind eine räumliche Anordnung vergleichsweise einfacher dynamischer Systeme, die eine lokale Kopplung untereinander aufweisen. Durch eine Diskretisierung der Ortsvariablen können Reaktions-Diffusions-Gleichungen häufig auf CNN mit nichtlinearen Gewichtsfunktionen abgebildet werden. Die resultierenden Reaktions-Diffusions-CNN (RD-CNN) weisen dann in ihrer Dynamik näherungsweise gleiches Verhalten wie die zugrunde gelegten Reaktions-Diffusions-Systeme auf. Werden RD-CNN zur Identifikation neuronaler Strukturen anhand von EEG-Signalen herangezogen, so besteht die Möglichkeit festzustellen, ob das gefundene Netzwerk lokale Aktivität aufweist. Die von Chua eingeführte Theorie der lokalen Aktivität Chua (1998); Dogaru und Chua (1998) liefert eine notwendige Bedingung für das Auftreten von emergentem Verhalten in zellularen Netzwerken. Änderungen in den Parametern bestimmter RD-CNN könnten auf bevorstehende epileptische Anfälle hinweisen. In diesem Beitrag steht die Identifikation neuronaler Strukturen anhand von EEG-Signalen durch Reaktions-Diffusions-Netzwerke im Vordergrund der dargestellten Untersuchungen. In der Ergebnisdiskussion wird insbesondere auch die Frage nach einer geeigneten Netzwerkstruktur mit minimaler Komplexität behandelt.

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity.

PubMed

Napoletano, Paolo; Piccoli, Flavio; Schettini, Raimondo

2018-01-12

Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM) imaging are the most effective. In this paper, we propose a region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity. The method evaluates the degree of abnormality of each subregion of an image under consideration by computing a CNN-based visual similarity with respect to a dictionary of anomaly-free subregions belonging to a training set. The proposed method outperforms the state of the art.

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity

PubMed Central

Schettini, Raimondo

2018-01-01

Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM) imaging are the most effective. In this paper, we propose a region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity. The method evaluates the degree of abnormality of each subregion of an image under consideration by computing a CNN-based visual similarity with respect to a dictionary of anomaly-free subregions belonging to a training set. The proposed method outperforms the state of the art. PMID:29329268

The Application of Chaos Theory to the Career-Plateaued Worker.

ERIC Educational Resources Information Center

Duffy, Jean Ann

2000-01-01

Applies some of the principles of chaos theory to career-plateaued workers on the basis of a case study. Concludes that chaos theory provides career practitioners a useful application for working with this type of client. (Author/JDM)

Filtering with Marked Point Process Observations via Poisson Chaos Expansion

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

Sun Wei, E-mail: wsun@mathstat.concordia.ca; Zeng Yong, E-mail: zengy@umkc.edu; Zhang Shu, E-mail: zhangshuisme@hotmail.com

2013-06-15

We study a general filtering problem with marked point process observations. The motivation comes from modeling financial ultra-high frequency data. First, we rigorously derive the unnormalized filtering equation with marked point process observations under mild assumptions, especially relaxing the bounded condition of stochastic intensity. Then, we derive the Poisson chaos expansion for the unnormalized filter. Based on the chaos expansion, we establish the uniqueness of solutions of the unnormalized filtering equation. Moreover, we derive the Poisson chaos expansion for the unnormalized filter density under additional conditions. To explore the computational advantage, we further construct a new consistent recursive numerical schememore » based on the truncation of the chaos density expansion for a simple case. The new algorithm divides the computations into those containing solely system coefficients and those including the observations, and assign the former off-line.« less

Facet Annotation by Extending CNN with a Matching Strategy.

PubMed

Wu, Bei; Wei, Bifan; Liu, Jun; Guo, Zhaotong; Zheng, Yuanhao; Chen, Yihe

2018-06-01

Most community question answering (CQA) websites manage plenty of question-answer pairs (QAPs) through topic-based organizations, which may not satisfy users' fine-grained search demands. Facets of topics serve as a powerful tool to navigate, refine, and group the QAPs. In this work, we propose FACM, a model to annotate QAPs with facets by extending convolution neural networks (CNNs) with a matching strategy. First, phrase information is incorporated into text representation by CNNs with different kernel sizes. Then, through a matching strategy among QAPs and facet label texts (FaLTs) acquired from Wikipedia, we generate similarity matrices to deal with the facet heterogeneity. Finally, a three-channel CNN is trained for facet label assignment of QAPs. Experiments on three real-world data sets show that FACM outperforms the state-of-the-art methods.

Fast object detection algorithm based on HOG and CNN

NASA Astrophysics Data System (ADS)

Lu, Tongwei; Wang, Dandan; Zhang, Yanduo

2018-04-01

In the field of computer vision, object classification and object detection are widely used in many fields. The traditional object detection have two main problems:one is that sliding window of the regional selection strategy is high time complexity and have window redundancy. And the other one is that Robustness of the feature is not well. In order to solve those problems, Regional Proposal Network (RPN) is used to select candidate regions instead of selective search algorithm. Compared with traditional algorithms and selective search algorithms, RPN has higher efficiency and accuracy. We combine HOG feature and convolution neural network (CNN) to extract features. And we use SVM to classify. For TorontoNet, our algorithm's mAP is 1.6 percentage points higher. For OxfordNet, our algorithm's mAP is 1.3 percentage higher.

Controlling transient chaos in deterministic flows with applications to electrical power systems and ecology

NASA Astrophysics Data System (ADS)

Dhamala, Mukeshwar; Lai, Ying-Cheng

1999-02-01

Transient chaos is a common phenomenon in nonlinear dynamics of many physical, biological, and engineering systems. In applications it is often desirable to maintain sustained chaos even in parameter regimes of transient chaos. We address how to sustain transient chaos in deterministic flows. We utilize a simple and practical method, based on extracting the fundamental dynamics from time series, to maintain chaos. The method can result in control of trajectories from almost all initial conditions in the original basin of the chaotic attractor from which transient chaos is created. We apply our method to three problems: (1) voltage collapse in electrical power systems, (2) species preservation in ecology, and (3) elimination of undesirable bursting behavior in a chemical reaction system.

Many-Body Quantum Chaos and Entanglement in a Quantum Ratchet

NASA Astrophysics Data System (ADS)

Valdez, Marc Andrew; Shchedrin, Gavriil; Heimsoth, Martin; Creffield, Charles E.; Sols, Fernando; Carr, Lincoln D.

2018-06-01

We uncover signatures of quantum chaos in the many-body dynamics of a Bose-Einstein condensate-based quantum ratchet in a toroidal trap. We propose measures including entanglement, condensate depletion, and spreading over a fixed basis in many-body Hilbert space, which quantitatively identify the region in which quantum chaotic many-body dynamics occurs, where random matrix theory is limited or inaccessible. With these tools, we show that many-body quantum chaos is neither highly entangled nor delocalized in the Hilbert space, contrary to conventionally expected signatures of quantum chaos.

Many-Body Quantum Chaos and Entanglement in a Quantum Ratchet.

PubMed

Valdez, Marc Andrew; Shchedrin, Gavriil; Heimsoth, Martin; Creffield, Charles E; Sols, Fernando; Carr, Lincoln D

2018-06-08

We uncover signatures of quantum chaos in the many-body dynamics of a Bose-Einstein condensate-based quantum ratchet in a toroidal trap. We propose measures including entanglement, condensate depletion, and spreading over a fixed basis in many-body Hilbert space, which quantitatively identify the region in which quantum chaotic many-body dynamics occurs, where random matrix theory is limited or inaccessible. With these tools, we show that many-body quantum chaos is neither highly entangled nor delocalized in the Hilbert space, contrary to conventionally expected signatures of quantum chaos.

Synthesis, structure and catalytic properties of CNN pincer palladium(II) and ruthenium(II) complexes with N-substituted-2-aminomethyl-6-phenylpyridines.

PubMed

Wang, Tao; Hao, Xin-Qi; Zhang, Xiao-Xue; Gong, Jun-Fang; Song, Mao-Ping

2011-09-21

N-substituted-2-aminomethyl-6-phenylpyridines 2a-c have been easily prepared from commercially available 6-bromo-2-picolinaldehyde in two steps. Reaction of 2a-c with PdCl(2) in toluene in the presence of triethylamine gave the CNN pincer Pd(II) complexes 3a-c in 18-28% yields. The CNN pincer Ru(II) complex 5 containing a Ru-NHR functionality could be obtained in a 71% yield by treatment of 2c with a Ru(II) precursor instead of PdCl(2). Additionally, the related CNN pincer Ru(II) complex 7 containing a Ru-NH(2) functionality has been synthesized by the reaction of 2-aminomethyl-6-phenylpyridine with the same Ru(II) precursor in a 68% yield. All the new compounds were characterized by elemental analysis (MS for ligands), (1)H, (13)C NMR, (31)P{(1)H} NMR (for Ru complexes) and IR spectra. Molecular structures of Pd complex 3c as well as Ru complexes 5 and 7 have been determined by X-ray single-crystal diffraction. The obtained Pd complexes 3a-c were effective catalysts for the allylation of aldehydes as well as for three-component allylation of aldehydes, arylamines and allyltributyltin and their activity was found to be much higher than a related NCN Pd(II) pincer in the allylation of aldehyde. On the other hand, the two new CNN pincer Ru(II) complexes 5 and 7 displayed excellent catalytic activity in the transfer hydrogenation of ketones in refluxing 2-propanol with the latter being much more active. The final TOF values were up to 4510 h(-1) with 0.01 mol% of 5 and 220,800 h(-1) with 0.005 mol% of 7, respectively. This journal is © The Royal Society of Chemistry 2011

Dynamical topology and statistical properties of spatiotemporal chaos.

PubMed

Zhuang, Quntao; Gao, Xun; Ouyang, Qi; Wang, Hongli

2012-12-01

For spatiotemporal chaos described by partial differential equations, there are generally locations where the dynamical variable achieves its local extremum or where the time partial derivative of the variable vanishes instantaneously. To a large extent, the location and movement of these topologically special points determine the qualitative structure of the disordered states. We analyze numerically statistical properties of the topologically special points in one-dimensional spatiotemporal chaos. The probability distribution functions for the number of point, the lifespan, and the distance covered during their lifetime are obtained from numerical simulations. Mathematically, we establish a probabilistic model to describe the dynamics of these topologically special points. In spite of the different definitions in different spatiotemporal chaos, the dynamics of these special points can be described in a uniform approach.

Entanglement as a signature of quantum chaos.

PubMed

Wang, Xiaoguang; Ghose, Shohini; Sanders, Barry C; Hu, Bambi

2004-01-01

We explore the dynamics of entanglement in classically chaotic systems by considering a multiqubit system that behaves collectively as a spin system obeying the dynamics of the quantum kicked top. In the classical limit, the kicked top exhibits both regular and chaotic dynamics depending on the strength of the chaoticity parameter kappa in the Hamiltonian. We show that the entanglement of the multiqubit system, considered for both the bipartite and the pairwise entanglement, yields a signature of quantum chaos. Whereas bipartite entanglement is enhanced in the chaotic region, pairwise entanglement is suppressed. Furthermore, we define a time-averaged entangling power and show that this entangling power changes markedly as kappa moves the system from being predominantly regular to being predominantly chaotic, thus sharply identifying the edge of chaos. When this entangling power is averaged over all states, it yields a signature of global chaos. The qualitative behavior of this global entangling power is similar to that of the classical Lyapunov exponent.

A Multi-modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling.

PubMed

Asif, Umar; Bennamoun, Mohammed; Sohel, Ferdous

2017-08-30

While deep convolutional neural networks have shown a remarkable success in image classification, the problems of inter-class similarities, intra-class variances, the effective combination of multimodal data, and the spatial variability in images of objects remain to be major challenges. To address these problems, this paper proposes a novel framework to learn a discriminative and spatially invariant classification model for object and indoor scene recognition using multimodal RGB-D imagery. This is achieved through three postulates: 1) spatial invariance - this is achieved by combining a spatial transformer network with a deep convolutional neural network to learn features which are invariant to spatial translations, rotations, and scale changes, 2) high discriminative capability - this is achieved by introducing Fisher encoding within the CNN architecture to learn features which have small inter-class similarities and large intra-class compactness, and 3) multimodal hierarchical fusion - this is achieved through the regularization of semantic segmentation to a multi-modal CNN architecture, where class probabilities are estimated at different hierarchical levels (i.e., imageand pixel-levels), and fused into a Conditional Random Field (CRF)- based inference hypothesis, the optimization of which produces consistent class labels in RGB-D images. Extensive experimental evaluations on RGB-D object and scene datasets, and live video streams (acquired from Kinect) show that our framework produces superior object and scene classification results compared to the state-of-the-art methods.

The Nature of Nurture: A Genomewide Association Scan for Family Chaos

PubMed Central

Plomin, Robert

2008-01-01

Widely used measures of the environment, especially the family environment of children, show genetic influence in dozens of twin and adoption studies. This phenomenon is known as gene-environment correlation in which genetically driven influences of individuals affect their environments. We conducted the first genome-wide association (GWA) analysis of an environmental measure. We used a measure called CHAOS which assesses ‘environmental confusion’ in the home, a measure that is more strongly associated with cognitive development in childhood than any other environmental measure. CHAOS was assessed by parental report when the children were 3 years and again when the children were 4 years; a composite CHAOS measure was constructed across the 2 years. We screened 490,041 autosomal single-nucleotide polymorphisms (SNPs) in a two-stage design in which children in low chaos families (N = 469) versus high chaos families (N = 369) from 3,000 families of 4-year-old twins were screened in Stage 1 using pooled DNA. In Stage 2, following SNP quality control procedures, 41 nominated SNPs were tested for association with family chaos by individual genotyping an independent representative sample of 3,529. Despite having 99% power to detect associations that account for more than 0.5% of the variance, none of the 41 nominated SNPs met conservative criteria for replication. Similar to GWA analyses of other complex traits, it is likely that most of the heritable variation in environmental measures such as family chaos is due to many genes of very small effect size. PMID:18360741

The nature of nurture: a genomewide association scan for family chaos.

PubMed

Butcher, Lee M; Plomin, Robert

2008-07-01

Widely used measures of the environment, especially the family environment of children, show genetic influence in dozens of twin and adoption studies. This phenomenon is known as gene-environment correlation in which genetically driven influences of individuals affect their environments. We conducted the first genome-wide association (GWA) analysis of an environmental measure. We used a measure called CHAOS which assesses 'environmental confusion' in the home, a measure that is more strongly associated with cognitive development in childhood than any other environmental measure. CHAOS was assessed by parental report when the children were 3 years and again when the children were 4 years; a composite CHAOS measure was constructed across the 2 years. We screened 490,041 autosomal single-nucleotide polymorphisms (SNPs) in a two-stage design in which children in low chaos families (N = 469) versus high chaos families (N = 369) from 3,000 families of 4-year-old twins were screened in Stage 1 using pooled DNA. In Stage 2, following SNP quality control procedures, 41 nominated SNPs were tested for association with family chaos by individual genotyping an independent representative sample of 3,529. Despite having 99% power to detect associations that account for more than 0.5% of the variance, none of the 41 nominated SNPs met conservative criteria for replication. Similar to GWA analyses of other complex traits, it is likely that most of the heritable variation in environmental measures such as family chaos is due to many genes of very small effect size.

Discretization chaos - Feedback control and transition to chaos

NASA Technical Reports Server (NTRS)

Grantham, Walter J.; Athalye, Amit M.

1990-01-01

Problems in the design of feedback controllers for chaotic dynamical systems are considered theoretically, focusing on two cases where chaos arises only when a nonchaotic continuous-time system is discretized into a simpler discrete-time systems (exponential discretization and pseudo-Euler integration applied to Lotka-Volterra competition and prey-predator systems). Numerical simulation results are presented in extensive graphs and discussed in detail. It is concluded that care must be taken in applying standard dynamical-systems methods to control systems that may be discontinuous or nondifferentiable.

Accessing Creativity: Jungian Night Sea Journeys, Wandering Minds, and Chaos.

PubMed

Rosen, Diane

2016-01-01

NDS theory has been meaningfully applied to the dynamics of creativity and psychology. These complex systems have much in common, including a broad definition of "product" as new order emerging from disorder, a new whole (etymologically, 'health') out of disintegration or destabilization. From a nonlinear dynamical systems perspective, this paper explores the far-from-equilibrium zone of creative incubation: first in the Jungian night sea journey, a primordial myth of psychological and creative transformation; then in the neuroscience of mind wandering, the well-spring of creative ideation within the larger neural matrix. Finally, chaos theory grounds the elusive subject of creativity, modeling chaotic generation of idea elements that tend toward strange attractors, combine unpredictably, and produce change by means of tension between opposites, particularly notes consciousness (light) and the poetic unconscious (darkness). Examples from my own artwork illustrate this dialectical process. Considered together, the unconscious mythic sea journey, the unknowing wandering mind, and the generative paradigm of deterministic chaos suggest conditions that facilitate creativity across disciplines, providing fresh indications that the darkness of the unknown or irrational is, paradoxically, the illuminative source and strength of creativity.

Cnn dynamics drive centrosome size asymmetry to ensure daughter centriole retention in Drosophila neuroblasts.

PubMed

Conduit, Paul T; Raff, Jordan W

2010-12-21

Centrosomes comprise a pair of centrioles surrounded by an amorphous network of pericentriolar material (PCM). In certain stem cells, the two centrosomes differ in size, and this appears to be important for asymmetric cell division [1, 2]. In some cases, centrosome asymmetry is linked to centriole age because the older, mother centriole always organizes more PCM than the daughter centriole, thus ensuring that the mother centriole is always retained in the stem cell after cell division [3]. This has raised the possibility that an "immortal" mother centriole may help maintain stem cell fate [4, 5]. It is unclear, however, how centrosome size asymmetry is generated in stem cells. Here we provide compelling evidence that centrosome size asymmetry in Drosophila neuroblasts is generated by the differential regulation of Cnn incorporation into the PCM at mother and daughter centrioles. Shortly after centriole separation, mother and daughter centrioles organize similar amounts of PCM, but Cnn incorporation is then rapidly downregulated at the mother centriole, while it is maintained at the daughter centriole. This ensures that the daughter centriole maintains its PCM and so its position at the apical cortex. Thus, the daughter centriole, rather than an "immortal" mother centriole, is ultimately retained in these stem cells.

The CHAOS-4 geomagnetic field model

NASA Astrophysics Data System (ADS)

Olsen, Nils; Lühr, Hermann; Finlay, Christopher C.; Sabaka, Terence J.; Michaelis, Ingo; Rauberg, Jan; Tøffner-Clausen, Lars

2014-05-01

We present CHAOS-4, a new version in the CHAOS model series, which aims to describe the Earth's magnetic field with high spatial and temporal resolution. Terms up to spherical degree of at least n = 85 for the lithospheric field, and up to n = 16 for the time-varying core field are robustly determined. More than 14 yr of data from the satellites Ørsted, CHAMP and SAC-C, augmented with magnetic observatory monthly mean values have been used for this model. Maximum spherical harmonic degree of the static (lithospheric) field is n = 100. The core field is expressed by spherical harmonic expansion coefficients up to n = 20; its time-evolution is described by order six splines, with 6-month knot spacing, spanning the time interval 1997.0-2013.5. The third time derivative of the squared radial magnetic field component is regularized at the core-mantle boundary. No spatial regularization is applied to the core field, but the high-degree lithospheric field is regularized for n > 85. CHAOS-4 model is derived by merging two submodels: its low-degree part has been derived using similar model parametrization and data sets as used for previous CHAOS models (but of course including more recent data), while its high-degree lithospheric field part is solely determined from low-altitude CHAMP satellite observations taken during the last 2 yr (2008 September-2010 September) of the mission. We obtain a good agreement with other recent lithospheric field models like MF7 for degrees up to n = 85, confirming that lithospheric field structures down to a horizontal wavelength of 500 km are currently robustly determined.

Stochastic Representation of Chaos using Terminal Attractors

NASA Technical Reports Server (NTRS)

Zak, Michail

2005-01-01

A nonlinear version of the Liouville equation based upon terminal attractors is proposed for describing post-instability motions of dynamical systems with exponential divergence of trajectories such as those leading to chaos and turbulence. As a result, the post-instability motions are represented by expectations, variances, and higher moments of the state variables as functions of time. The proposed approach can be applied to conservative chaos, and in particular, to n-bodies problem, as well as to dissipative systems, and in particular, to chaotic attractors and turbulence.

Strategy and Structure for Online News Production - Case Studies of CNN and NRK

NASA Astrophysics Data System (ADS)

Krumsvik, Arne H.

This cross-national comparative case study of online news production analyzes the strategies of Cable News Network (CNN) and the Norwegian Broadcasting Corporation (NRK), aiming at understanding of the implications of organizational strategy on the role of journalists, explains why traditional media organizations have a tendency to develop a multi-platform approach (distributing content on several platforms, such as television, online, mobile) rather than developing the cross-media (with interplay between media types) or multimedia approach anticipated by both scholars and practitioners.

On chaos synchronization and secure communication.

PubMed

Kinzel, W; Englert, A; Kanter, I

2010-01-28

Chaos synchronization, in particular isochronal synchronization of two chaotic trajectories to each other, may be used to build a means of secure communication over a public channel. In this paper, we give an overview of coupling schemes of Bernoulli units deduced from chaotic laser systems, different ways to transmit information by chaos synchronization and the advantage of bidirectional over unidirectional coupling with respect to secure communication. We present the protocol for using dynamical private commutative filters for tap-proof transmission of information that maps the task of a passive attacker to the class of non-deterministic polynomial time-complete problems. This journal is © 2010 The Royal Society

Quasiperiodicity and chaos in cardiac fibrillation.

PubMed

Garfinkel, A; Chen, P S; Walter, D O; Karagueuzian, H S; Kogan, B; Evans, S J; Karpoukhin, M; Hwang, C; Uchida, T; Gotoh, M; Nwasokwa, O; Sager, P; Weiss, J N

1997-01-15

In cardiac fibrillation, disorganized waves of electrical activity meander through the heart, and coherent contractile function is lost. We studied fibrillation in three stationary forms: in human chronic atrial fibrillation, in a stabilized form of canine ventricular fibrillation, and in fibrillation-like activity in thin sheets of canine and human ventricular tissue in vitro. We also created a computer model of fibrillation. In all four studies, evidence indicated that fibrillation arose through a quasiperiodic stage of period and amplitude modulation, thus exemplifying the "quasiperiodic transition to chaos" first suggested by Ruelle and Takens. This suggests that fibrillation is a form of spatio-temporal chaos, a finding that implies new therapeutic approaches.

Applied Chaos Level Test for Validation of Signal Conditions Underlying Optimal Performance of Voice Classification Methods.

PubMed

Liu, Boquan; Polce, Evan; Sprott, Julien C; Jiang, Jack J

2018-05-17

The purpose of this study is to introduce a chaos level test to evaluate linear and nonlinear voice type classification method performances under varying signal chaos conditions without subjective impression. Voice signals were constructed with differing degrees of noise to model signal chaos. Within each noise power, 100 Monte Carlo experiments were applied to analyze the output of jitter, shimmer, correlation dimension, and spectrum convergence ratio. The computational output of the 4 classifiers was then plotted against signal chaos level to investigate the performance of these acoustic analysis methods under varying degrees of signal chaos. A diffusive behavior detection-based chaos level test was used to investigate the performances of different voice classification methods. Voice signals were constructed by varying the signal-to-noise ratio to establish differing signal chaos conditions. Chaos level increased sigmoidally with increasing noise power. Jitter and shimmer performed optimally when the chaos level was less than or equal to 0.01, whereas correlation dimension was capable of analyzing signals with chaos levels of less than or equal to 0.0179. Spectrum convergence ratio demonstrated proficiency in analyzing voice signals with all chaos levels investigated in this study. The results of this study corroborate the performance relationships observed in previous studies and, therefore, demonstrate the validity of the validation test method. The presented chaos level validation test could be broadly utilized to evaluate acoustic analysis methods and establish the most appropriate methodology for objective voice analysis in clinical practice.

Suppression of chaos at slow variables by rapidly mixing fast dynamics

NASA Astrophysics Data System (ADS)

Abramov, R.

2012-04-01

One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation property promotes the suppression of chaos at the slow variables through the rapid mixing at the fast variables, both theoretically and through numerical simulations. A suitable mathematical framework is developed, connecting the slow dynamics on the tangent subspaces to the infinite-time linear response of the mean state to a constant external forcing at the fast variables. Additionally, it is shown that the uncoupled dynamics for the slow variables may remain chaotic while the complete multiscale system loses chaos and becomes completely predictable at the slow variables through increasing chaos and turbulence at the fast variables. This result contradicts the common sense intuition, where, naturally, one would think that coupling a slow weakly chaotic system with another much faster and much stronger mixing system would result in general increase of chaos at the slow variables.

Chaos in quantum channels

DOE PAGES

Hosur, Pavan; Qi, Xiao-Liang; Roberts, Daniel A.; ...

2016-02-01

For this research, we study chaos and scrambling in unitary channels by considering their entanglement properties as states. Using out-of-time-order correlation functions to diagnose chaos, we characterize the ability of a channel to process quantum information. We show that the generic decay of such correlators implies that any input subsystem must have near vanishing mutual information with almost all partitions of the output. Additionally, we propose the negativity of the tripartite information of the channel as a general diagnostic of scrambling. This measures the delocalization of information and is closely related to the decay of out-of-time-order correlators. We back upmore » our results with numerics in two non-integrable models and analytic results in a perfect tensor network model of chaotic time evolution. In conclusion, these results show that the butterfly effect in quantum systems implies the information-theoretic definition of scrambling.« less

Magnetic field induced dynamical chaos.

PubMed

Ray, Somrita; Baura, Alendu; Bag, Bidhan Chandra

2013-12-01

In this article, we have studied the dynamics of a particle having charge in the presence of a magnetic field. The motion of the particle is confined in the x-y plane under a two dimensional nonlinear potential. We have shown that constant magnetic field induced dynamical chaos is possible even for a force which is derived from a simple potential. For a given strength of the magnetic field, initial position, and velocity of the particle, the dynamics may be regular, but it may become chaotic when the field is time dependent. Chaotic dynamics is very often if the field is time dependent. Origin of chaos has been explored using the Hamiltonian function of the dynamics in terms of action and angle variables. Applicability of the present study has been discussed with a few examples.

A history of chaos theory.

PubMed

Oestreicher, Christian

2007-01-01

Whether every effect can be precisely linked to a given cause or to a list of causes has been a matter of debate for centuries, particularly during the 17th century, when astronomers became capable of predicting the trajectories of planets. Recent mathematical models applied to physics have included the idea that given phenomena cannot be predicted precisely, although they can be predicted to some extent, in line with the chaos theory. Concepts such as deterministic models, sensitivity to initial conditions, strange attractors, and fractal dimensions are inherent to the development of this theory A few situations involving normal or abnormal endogenous rhythms in biology have been analyzed following the principles of chaos theory. This is particularly the case with cardiac arrhythmias, but less so with biological clocks and circadian rhythms.

A history of chaos theory

PubMed Central

Oestreicher, Christian

2007-01-01

Whether every effect can be precisely linked to a given cause or to a list of causes has been a matter of debate for centuries, particularly during the 17th century when astronomers became capable of predicting the trajectories of planets. Recent mathematical models applied to physics have included the idea that given phenomena cannot be predicted precisely although they can be predicted to some extent in line with the chaos theory Concepts such as deterministic models, sensitivity to initial conditions, strange attractors, and fractal dimensions are inherent to the development of this theory, A few situations involving normal or abnormal endogenous rhythms in biology have been analyzed following the principles of chaos theory This is particularly the case with cardiac arrhythmias, but less so with biological clocks and circadian rhythms. PMID:17969865

Chaos control of Hastings-Powell model by combining chaotic motions

NASA Astrophysics Data System (ADS)

Danca, Marius-F.; Chattopadhyay, Joydev

2016-04-01

In this paper, we propose a Parameter Switching (PS) algorithm as a new chaos control method for the Hastings-Powell (HP) system. The PS algorithm is a convergent scheme that switches the control parameter within a set of values while the controlled system is numerically integrated. The attractor obtained with the PS algorithm matches the attractor obtained by integrating the system with the parameter replaced by the averaged value of the switched parameter values. The switching rule can be applied periodically or randomly over a set of given values. In this way, every stable cycle of the HP system can be approximated if its underlying parameter value equalizes the average value of the switching values. Moreover, the PS algorithm can be viewed as a generalization of Parrondo's game, which is applied for the first time to the HP system, by showing that losing strategy can win: "losing + losing = winning." If "loosing" is replaced with "chaos" and, "winning" with "order" (as the opposite to "chaos"), then by switching the parameter value in the HP system within two values, which generate chaotic motions, the PS algorithm can approximate a stable cycle so that symbolically one can write "chaos + chaos = regular." Also, by considering a different parameter control, new complex dynamics of the HP model are revealed.

Chaos in an imperfectly premixed model combustor.

PubMed

Kabiraj, Lipika; Saurabh, Aditya; Karimi, Nader; Sailor, Anna; Mastorakos, Epaminondas; Dowling, Ann P; Paschereit, Christian O

2015-02-01

This article reports nonlinear bifurcations observed in a laboratory scale, turbulent combustor operating under imperfectly premixed mode with global equivalence ratio as the control parameter. The results indicate that the dynamics of thermoacoustic instability correspond to quasi-periodic bifurcation to low-dimensional, deterministic chaos, a route that is common to a variety of dissipative nonlinear systems. The results support the recent identification of bifurcation scenarios in a laminar premixed flame combustor (Kabiraj et al., Chaos: Interdiscip. J. Nonlinear Sci. 22, 023129 (2012)) and extend the observation to a practically relevant combustor configuration.

Quantum chaos on a critical Fermi surface.

PubMed

Patel, Aavishkar A; Sachdev, Subir

2017-02-21

We compute parameters characterizing many-body quantum chaos for a critical Fermi surface without quasiparticle excitations. We examine a theory of [Formula: see text] species of fermions at nonzero density coupled to a [Formula: see text] gauge field in two spatial dimensions and determine the Lyapunov rate and the butterfly velocity in an extended random-phase approximation. The thermal diffusivity is found to be universally related to these chaos parameters; i.e., the relationship is independent of [Formula: see text], the gauge-coupling constant, the Fermi velocity, the Fermi surface curvature, and high-energy details.

Chaos Theory and James Joyce's "ulysses": Leopold Bloom as a Human COMPLEX@SYSTEM^

NASA Astrophysics Data System (ADS)

Mackey, Peter Francis

1995-01-01

These four ideas apply as much to our lives as to the life of Leopold Bloom: (1) A trivial decision can wholly change a life. (2) A chance encounter can dramatically alter life's course. (3) A contingent nexus exists between consciousness and environment. (4) A structure of meaning helps us interpret life's chaos. These ideas also relate to a contemporary science called by some "chaos theory." The connection between Ulysses and chaos theory enhances our understanding of Bloom's day; it also suggests that this novel may be about the real process of life itself. The first chapter explains how Joyce's own essays and comments to friends compel attention to the links between Ulysses and chaos theory. His scientific contemporaries anticipated chaos theory, and their ideas seem to have rubbed off on him. We see this in his sense of trivial things and chance, his modernistic organizational impulses, and the contingent nature of Bloom's experience. The second chapter studies what chaos theory and Joyce's ideas tell us about "Ithaca," the episode which particularly implicates our processes of interpreting this text as well as life itself as we face their chaos. The third chapter examines Bloom's close feel for the aboriginal world, a contingency that clarifies his vulnerability to trivial changes. The fourth chapter studies how Bloom's stream of consciousness unfolds--from his chance encounters with trivial things. Beneath this stream's seeming chaos, Bloom's distinct personality endures, similar to how Joyce's schemas give Ulysses an imbedded, underlying order. The fifth chapter examines how trivial perturbations, such as Lyons' misunderstanding about "Throwaway," produce small crises for Bloom, exacerbating his seeming impotence before his lonely "fate.". The final chapter analyzes Bloom's views that fate and chance dictate his life. His views provide an opportunity to explore the implications chaos theory has for our understanding of free will and determinism. Ultimately

Geometric and dynamic perspectives on phase-coherent and noncoherent chaos.

PubMed

Zou, Yong; Donner, Reik V; Kurths, Jürgen

2012-03-01

Statistically distinguishing between phase-coherent and noncoherent chaotic dynamics from time series is a contemporary problem in nonlinear sciences. In this work, we propose different measures based on recurrence properties of recorded trajectories, which characterize the underlying systems from both geometric and dynamic viewpoints. The potentials of the individual measures for discriminating phase-coherent and noncoherent chaotic oscillations are discussed. A detailed numerical analysis is performed for the chaotic Rössler system, which displays both types of chaos as one control parameter is varied, and the Mackey-Glass system as an example of a time-delay system with noncoherent chaos. Our results demonstrate that especially geometric measures from recurrence network analysis are well suited for tracing transitions between spiral- and screw-type chaos, a common route from phase-coherent to noncoherent chaos also found in other nonlinear oscillators. A detailed explanation of the observed behavior in terms of attractor geometry is given.

Mesoscopic chaos mediated by Drude electron-hole plasma in silicon optomechanical oscillators

PubMed Central

Wu, Jiagui; Huang, Shu-Wei; Huang, Yongjun; Zhou, Hao; Yang, Jinghui; Liu, Jia-Ming; Yu, Mingbin; Lo, Guoqiang; Kwong, Dim-Lee; Duan, Shukai; Wei Wong, Chee

2017-01-01

Chaos has revolutionized the field of nonlinear science and stimulated foundational studies from neural networks, extreme event statistics, to physics of electron transport. Recent studies in cavity optomechanics provide a new platform to uncover quintessential architectures of chaos generation and the underlying physics. Here, we report the generation of dynamical chaos in silicon-based monolithic optomechanical oscillators, enabled by the strong and coupled nonlinearities of two-photon absorption induced Drude electron–hole plasma. Deterministic chaotic oscillation is achieved, and statistical and entropic characterization quantifies the chaos complexity at 60 fJ intracavity energies. The correlation dimension D2 is determined at 1.67 for the chaotic attractor, along with a maximal Lyapunov exponent rate of about 2.94 times the fundamental optomechanical oscillation for fast adjacent trajectory divergence. Nonlinear dynamical maps demonstrate the subharmonics, bifurcations and stable regimes, along with distinct transitional routes into chaos. This provides a CMOS-compatible and scalable architecture for understanding complex dynamics on the mesoscopic scale. PMID:28598426

The onset of chaos in orbital pilot-wave dynamics.

PubMed

Tambasco, Lucas D; Harris, Daniel M; Oza, Anand U; Rosales, Rodolfo R; Bush, John W M

2016-10-01

We present the results of a numerical investigation of the emergence of chaos in the orbital dynamics of droplets walking on a vertically vibrating fluid bath and acted upon by one of the three different external forces, specifically, Coriolis, Coulomb, or linear spring forces. As the vibrational forcing of the bath is increased progressively, circular orbits destabilize into wobbling orbits and eventually chaotic trajectories. We demonstrate that the route to chaos depends on the form of the external force. When acted upon by Coriolis or Coulomb forces, the droplet's orbital motion becomes chaotic through a period-doubling cascade. In the presence of a central harmonic potential, the transition to chaos follows a path reminiscent of the Ruelle-Takens-Newhouse scenario.

Rank one chaos in a class of planar systems with heteroclinic cycle.

PubMed

Chen, Fengjuan; Han, Maoan

2009-12-01

In this paper, we study rank one chaos in a class of planar systems with heteroclinic cycle. We first find a stable limit cycle inside the heteroclinic cycle. We then add an external periodic forcing to create rank one chaos. We follow a step-by-step procedure guided by the theory of rank one chaos to find experimental evidence of strange attractors with Sinai, Ruelle, and Bowen measures.

Specifying the Links between Household Chaos and Preschool Children's Development

ERIC Educational Resources Information Center

Martin, Anne; Razza, Rachel A.; Brooks-Gunn, Jeanne

2012-01-01

Household chaos has been linked to poorer cognitive, behavioural, and self-regulatory outcomes in young children, but the mechanisms responsible remain largely unknown. Using a diverse sample of families in Chicago, the present study tests for the independent contributions made by five indicators of household chaos: noise, crowding, family…

Flavors of Chaos in the Asteroid Belt

NASA Astrophysics Data System (ADS)

Tsiganis, Kleomenis

2016-10-01

The asteroid belt is a natural laboratory for studying chaos, as a large fraction of asteroids actually reside on chaotic orbits. Numerous studies over the past 25 years have unveiled a multitude of dynamical chaos-generating mechanisms, operating on different time-scales and dominating over different regions of the belt. In fact, the distribution of chaotic asteroids in orbital space can be largely understood as the outcome of the combined action of resonant gravitational perturbations and the Yarkovsky effect - two topics on which Paolo Farinella has made an outstanding contribution! - notwithstanding the fact that the different "flavors" of chaos can give rise to a wide range of outcomes, from fast escape (e.g. to NEA space) to slow (~100s My) macroscopic diffusion (e.g. spreading of families) and strange, stable-looking, chaotic orbits (ultra-slow diffusion). In this talk I am going to present an overview of these mechanisms, presenting both analytical and numerical results, and their role in understanding the long-term evolution and stability of individual bodies, asteroid groups and families.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

Quasiperiodicity and chaos in cardiac fibrillation.

PubMed Central

Garfinkel, A; Chen, P S; Walter, D O; Karagueuzian, H S; Kogan, B; Evans, S J; Karpoukhin, M; Hwang, C; Uchida, T; Gotoh, M; Nwasokwa, O; Sager, P; Weiss, J N

1997-01-01

In cardiac fibrillation, disorganized waves of electrical activity meander through the heart, and coherent contractile function is lost. We studied fibrillation in three stationary forms: in human chronic atrial fibrillation, in a stabilized form of canine ventricular fibrillation, and in fibrillation-like activity in thin sheets of canine and human ventricular tissue in vitro. We also created a computer model of fibrillation. In all four studies, evidence indicated that fibrillation arose through a quasiperiodic stage of period and amplitude modulation, thus exemplifying the "quasiperiodic transition to chaos" first suggested by Ruelle and Takens. This suggests that fibrillation is a form of spatio-temporal chaos, a finding that implies new therapeutic approaches. PMID:9005999

Iceberg Ahead: The Effect of Bands and Ridges During Chaos Formation on Europa.

NASA Astrophysics Data System (ADS)

Hedgepeth, J. E.; Schmidt, B. E.

2016-12-01

Europa presents a dynamic and varied surface, but the most enticing component is arguably its chaos structures. With it, the surface and subsurface can interact, but in order to fully understand if this is occurring we have to properly parameterize the surface structural integrity. We consider the Schmidt et al. (2011) method of classifying icebergs by feature type to study what features remained intact in the chaos matrix. In this work we expand on this idea. We hypothesize that the ice that forms ridges and bands exhibit higher structural strengths than plains. Subsequently, this ice is more likely to remain during chaos formation in the form of icebergs. We begin by mapping the surface around Murias chaos and other prominent chaos features. Maps are used to infer what paleo-topographic features existed before chaos formation by using the features surrounding the chaos regions as blueprints for what existed before. We perform a multivariate regression to correlate the amount of icebergs present to the amount of surface that was covered by either bands, plains, or ridges. We find ridges play the biggest role in the production of icebergs with a weighted value of 40%. Bands may play a smaller role (13%), but plains show little to no correlation (5%). Further mapping will better reveal if this trend holds true in other regions. This statistical analysis supports our hypothesis, and further work will better quantify what is occurring. We will address the energy expended in the chaos regions via movement and rotation of icebergs during the formation event and through ice-melt.

Socioeconomic Risk Moderates the Link between Household Chaos and Maternal Executive Function

PubMed Central

Deater-Deckard, Kirby; Chen, Nan; Wang, Zhe; Bell, Martha Ann

2012-01-01

We examined the link between household chaos (i.e., noise, clutter, disarray, lack of routines) and maternal executive function (i.e., effortful regulation of attention and memory), and whether it varied as a function of socioeconomic risk (i.e., single parenthood, lower mother and father educational attainment, housing situation, and father unemployment). We hypothesized that: 1) higher levels of household chaos would be linked with poorer maternal executive function, even when controlling for other measures of cognitive functioning (e.g., verbal ability), and 2) this link would be strongest in the most socioeconomically distressed or lowest-socioeconomic status households. The diverse sample included 153 mothers from urban and rural areas who completed a questionnaire and a battery of cognitive executive function tasks and a verbal ability task in the laboratory. Results were mixed for hypothesis 1, and consistent with hypothesis 2. Two-thirds of the variance overlapped between household chaos and maternal executive function, but only in families with high levels of socioeconomic risk. This pattern was not found for chaos and maternal verbal ability, suggesting that the potentially deleterious effects of household chaos may be specific to maternal executive function. The findings implicate household chaos as a powerful statistical predictor of maternal executive function in socioeconomically distressed contexts. PMID:22563703

Emergence of chaos in a spatially confined reactive system

NASA Astrophysics Data System (ADS)

Voorsluijs, Valérie; De Decker, Yannick

2016-11-01

In spatially restricted media, interactions between particles and local fluctuations of density can lead to important deviations of the dynamics from the unconfined, deterministic picture. In this context, we investigated how molecular crowding can affect the emergence of chaos in small reactive systems. We developed to this end an amended version of the Willamowski-Rössler model, where we account for the impenetrability of the reactive species. We analyzed the deterministic kinetics of this model and studied it with spatially-extended stochastic simulations in which the mobility of particles is included explicitly. We show that homogeneous fluctuations can lead to a destruction of chaos through a fluctuation-induced collision between chaotic trajectories and absorbing states. However, an interplay between the size of the system and the mobility of particles can counterbalance this effect so that chaos can indeed be found when particles diffuse slowly. This unexpected effect can be traced back to the emergence of spatial correlations which strongly affect the dynamics. The mobility of particles effectively acts as a new bifurcation parameter, enabling the system to switch from stationary states to absorbing states, oscillations or chaos.

Differences in Television Sports Reporting of Men's and Women's Athletics: ESPN SportsCenter and CNN Sports Tonight.

ERIC Educational Resources Information Center

Tuggle, C. A.

1997-01-01

Examines the amount of coverage given to women's athletics by ESPN SportsCenter and CNN Sports Tonight. Results indicated: both programs devoted only about 5% of their air time to women's sports; story placement and on-camera comments indicated an emphasis on men's athletics; and stories about women involved individual competition, with almost no…

How to couple identical ring oscillators to get quasiperiodicity, extended chaos, multistability, and the loss of symmetry

NASA Astrophysics Data System (ADS)

Hellen, Edward H.; Volkov, Evgeny

2018-09-01

We study the dynamical regimes demonstrated by a pair of identical 3-element ring oscillators (reduced version of synthetic 3-gene genetic Repressilator) coupled using the design of the 'quorum sensing (QS)' process natural for interbacterial communications. In this work QS is implemented as an additional network incorporating elements of the ring as both the source and the activation target of the fast diffusion QS signal. This version of indirect nonlinear coupling, in cooperation with the reasonable extension of the parameters which control properties of the isolated oscillators, exhibits the formation of a very rich array of attractors. Using a parameter-space defined by the individual oscillator amplitude and the coupling strength, we found the extended area of parameter-space where the identical oscillators demonstrate quasiperiodicity, which evolves to chaos via the period doubling of either resonant limit cycles or complex antiphase symmetric limit cycles with five winding numbers. The symmetric chaos extends over large parameter areas up to its loss of stability, followed by a system transition to an unexpected mode: an asymmetric limit cycle with a winding number of 1:2. In turn, after long evolution across the parameter-space, this cycle demonstrates a period doubling cascade which restores the symmetry of dynamics by formation of symmetric chaos, which nevertheless preserves the memory of the asymmetric limit cycles in the form of stochastic alternating "polarization" of the time series. All stable attractors coexist with some others, forming remarkable and complex multistability including the coexistence of torus and limit cycles, chaos and regular attractors, symmetric and asymmetric regimes. We traced the paths and bifurcations leading to all areas of chaos, and presented a detailed map of all transformations of the dynamics.

Chaos as the hub of systems dynamics. The part I-The attitude control of spacecraft by involving in the heteroclinic chaos

NASA Astrophysics Data System (ADS)

Doroshin, Anton V.

2018-06-01

In this work the chaos in dynamical systems is considered as a positive aspect of dynamical behavior which can be applied to change systems dynamical parameters and, moreover, to change systems qualitative properties. From this point of view, the chaos can be characterized as a hub for the system dynamical regimes, because it allows to interconnect separated zones of the phase space of the system, and to fulfill the jump into the desirable phase space zone. The concretized aim of this part of the research is to focus on developing the attitude control method for magnetized gyrostat-satellites, which uses the passage through the intentionally generated heteroclinic chaos. The attitude dynamics of the satellite/spacecraft in this case represents the series of transitions from the initial dynamical regime into the chaotic heteroclinic regime with the subsequent exit to the final target dynamical regime with desirable parameters of the attitude dynamics.

Chaos: A Mathematical Introduction

NASA Astrophysics Data System (ADS)

Banks, John; Dragan, Valentina; Jones, Arthur

2003-06-01

This text presents concepts on chaos in discrete time dynamics that are accessible to anyone who has taken a first course in undergraduate calculus. Retaining its commitment to mathematical integrity, the book, originating in a popular one-semester middle level undergraduate course, constitutes the first elementary presentation of a traditionally advanced subject.

Analysis of chaos attractors of MCG-recordings.

PubMed

Jiang, Shiqin; Yang, Fan; Yi, Panke; Chen, Bo; Luo, Ming; Wang, Lemin

2006-01-01

By studying the chaos attractor of cardiac magnetic induction strength B(z) generated by the electrical activity of the heart, we found that its projection in the reconstructed phase space has a similar shape with the map of the total current dipole vector. It is worth noting that the map of the total current dipole vector is computed with MCG recordings measured at 36 locations, whereas the chaos attractor of B(z) is generated by only one cardiac magnetic field recordings on the measured plan. We discuss only two subjects of different ages in this paper.

Signatures of chaos in the Brillouin zone.

PubMed

Barr, Aaron; Barr, Ariel; Porter, Max D; Reichl, Linda E

2017-10-01

When the classical dynamics of a particle in a finite two-dimensional billiard undergoes a transition to chaos, the quantum dynamics of the particle also shows manifestations of chaos in the form of scarring of wave functions and changes in energy level spacing distributions. If we "tile" an infinite plane with such billiards, we find that the Bloch states on the lattice undergo avoided crossings, energy level spacing statistics change from Poisson-like to Wigner-like, and energy sheets of the Brillouin zone begin to "mix" as the classical dynamics of the billiard changes from regular to chaotic behavior.

Chaos and random matrices in supersymmetric SYK

NASA Astrophysics Data System (ADS)

Hunter-Jones, Nicholas; Liu, Junyu

2018-05-01

We use random matrix theory to explore late-time chaos in supersymmetric quantum mechanical systems. Motivated by the recent study of supersymmetric SYK models and their random matrix classification, we consider the Wishart-Laguerre unitary ensemble and compute the spectral form factors and frame potentials to quantify chaos and randomness. Compared to the Gaussian ensembles, we observe the absence of a dip regime in the form factor and a slower approach to Haar-random dynamics. We find agreement between our random matrix analysis and predictions from the supersymmetric SYK model, and discuss the implications for supersymmetric chaotic systems.

2,3-Di(2-pyridyl)-5-phenylpyrazine: a NN-CNN-type bridging ligand for dinuclear transition-metal complexes.

PubMed

Wu, Si-Hai; Zhong, Yu-Wu; Yao, Jiannian

2013-07-01

A new bridging ligand, 2,3-di(2-pyridyl)-5-phenylpyrazine (dpppzH), has been synthesized. This ligand was designed so that it could bind two metals through a NN-CNN-type coordination mode. The reaction of dpppzH with cis-[(bpy)2RuCl2] (bpy = 2,2'-bipyridine) affords monoruthenium complex [(bpy)2Ru(dpppzH)](2+) (1(2+)) in 64 % yield, in which dpppzH behaves as a NN bidentate ligand. The asymmetric biruthenium complex [(bpy)2Ru(dpppz)Ru(Mebip)](3+) (2(3+)) was prepared from complex 1(2+) and [(Mebip)RuCl3] (Mebip = bis(N-methylbenzimidazolyl)pyridine), in which one hydrogen atom on the phenyl ring of dpppzH is lost and the bridging ligand binds to the second ruthenium atom in a CNN tridentate fashion. In addition, the RuPt heterobimetallic complex [(bpy)2Ru(dpppz)Pt(C≡CPh)](2+) (4(2+)) has been prepared from complex 1(2+), in which the bridging ligand binds to the platinum atom through a CNN binding mode. The electronic properties of these complexes have been probed by using electrochemical and spectroscopic techniques and studied by theoretical calculations. Complex 1(2+) is emissive at room temperature, with an emission λmax = 695 nm. No emission was detected for complex 2(3+) at room temperature in MeCN, whereas complex 4(2+) displayed an emission at about 750 nm. The emission properties of these complexes are compared to those of previously reported Ru and RuPt bimetallic complexes with a related ligand, 2,3-di(2-pyridyl)-5,6-diphenylpyrazine. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of chaos in high-dimensional wind power system.

PubMed

Wang, Cong; Zhang, Hongli; Fan, Wenhui; Ma, Ping

2018-01-01

A comprehensive analysis on the chaos of a high-dimensional wind power system is performed in this study. A high-dimensional wind power system is more complex than most power systems. An 11-dimensional wind power system proposed by Huang, which has not been analyzed in previous studies, is investigated. When the systems are affected by external disturbances including single parameter and periodic disturbance, or its parameters changed, chaotic dynamics of the wind power system is analyzed and chaotic parameters ranges are obtained. Chaos existence is confirmed by calculation and analysis of all state variables' Lyapunov exponents and the state variable sequence diagram. Theoretical analysis and numerical simulations show that the wind power system chaos will occur when parameter variations and external disturbances change to a certain degree.

Fusing Panchromatic and SWIR Bands Based on Cnn - a Preliminary Study Over WORLDVIEW-3 Datasets

NASA Astrophysics Data System (ADS)

Guo, M.; Ma, H.; Bao, Y.; Wang, L.

2018-04-01

The traditional fusion methods are based on the fact that the spectral ranges of the Panchromatic (PAN) and multispectral bands (MS) are almost overlapping. In this paper, we propose a new pan-sharpening method for the fusion of PAN and SWIR (short-wave infrared) bands, whose spectral coverages are not overlapping. This problem is addressed with a convolutional neural network (CNN), which is trained by WorldView-3 dataset. CNN can learn the complex relationship among bands, and thus alleviate spectral distortion. Consequently, in our network, we use the simple three-layer basic architecture with 16 × 16 kernels to conduct the experiment. Every layer use different receptive field. The first two layers compute 512 feature maps by using the 16 × 16 and 1 × 1 receptive field respectively and the third layer with a 8 × 8 receptive field. The fusion results are optimized by continuous training. As for assessment, four evaluation indexes including Entropy, CC, SAM and UIQI are selected built on subjective visual effect and quantitative evaluation. The preliminary experimental results demonstrate that the fusion algorithms can effectively enhance the spatial information. Unfortunately, the fusion image has spectral distortion, it cannot maintain the spectral information of the SWIR image.

Chaos, Hubbub, and Order Scale and Health Risk Behaviors in Adolescents in Los Angeles.

PubMed

Chatterjee, Avik; Gillman, Matthew W; Wong, Mitchell D

2015-12-01

To determine the relationship between household chaos and substance use, sexual activity, and violence-related risk behaviors in adolescents. We analyzed cross-sectional data among 929 high-school students in Los Angeles who completed a 90-minute interview that assessed health behaviors and household chaos with the 14-question Chaos, Hubbub, and Order Scale (CHAOS). Using the generalized estimating equation and adjusting for personal, parental, and family covariates, we examined associations of CHAOS score with substance use, sexual activity, and violent behavior outcome variables. We also examined the role of depression and school engagement as mediators. Mean (SD) age of the 929 students was 16.4 (1.3) years, 516 (55%) were female, and 780 (84%) were Latino. After adjustment, compared with students with CHAOS score 0, those students with the greatest scores (5-14) had ORs of 3.1 (95% CI 1.1-8.7) for smoking, 2.6 (95% CI 1.6-4.4) for drinking, 6.1 (95% CI 1.8-21) for substance use at school, and 1.9 (95% CI 1.1-3.3) for fighting in the past 12 months. Associations between CHAOS score and sexual risk and other violent behaviors were not significant. Depression and school engagement attenuated the associations. In this group of adolescents, greatest CHAOS score was associated with increased odds of risky health behaviors, with depression and school engagement as potential mediators. In the future, CHAOS score could be measured to assess risk for such behaviors or be a target for intervention to reduce chances of engaging in these behaviors. Copyright © 2015 Elsevier Inc. All rights reserved.

Detection of Gray Crystalline Hematite in the Aureum and Iani Chaos Layered Terrains

NASA Astrophysics Data System (ADS)

Glotch, T. D.; Rogers, D.; Christensen, P. R.

2005-12-01

Using the TES and THEMIS datasets, small hematite-rich deposits have been discovered in Aureum and Iani Chaos. The newly discovered hematite-rich deposits share several similarities with the deposit in Aram Chaos [1], including the occurrence of hematite in a friable layered unit, and the presence of a light-toned caprock. The presence of these units over a distance of several hundred kilometers in the equatorial latitudes of Mars may point to a preferred global mechanism for hematite formation. However, it is unclear how, if at all, these units are related to the hematite- and sulfate-rich unit in Meridiani Planum, which is substantially larger and older (by as much as 1 Ga) than the layered units seen in the equatorial chaotic terrains. Though the caprock units in Aram Chaos and Aureum Chaos are similar, the corresponding unit in Iani Chaos is morphologically different, exhibiting less of a cliff-forming erosional pattern. The hematite-rich units in Aram and Aureum Chaos lie stratigraphically below the light-toned caprock units. In Iani Chaos, the hematite deposit is coincident with the light-toned unit. Data returned from the Mars Express OMEGA instrument have shown the presence of hydrated sulfates in the hematite-rich units associated with Aram and Iani Chaos, although to date, no sulfate detection has been reported in Aureum Chaos [2]. The sequence of caprock and hematite units in Aram, Aureum, and Iani Chaos probably did not form coincidentally as part of an extensive regional layer, but instead formed by similar, but not identical, processes in their respective chaotic terrains. The presence of these units in chaotic terrains, which have been hypothesized to form by subsidence after the release of subsurface water, indicate that these units may have been deposited in an aqueous environment. By analogy to Meridiani Planum, later subsurface aqueous activity in the region of the chaotic terrains may have provided the necessary diagenetic conditions for the

Chaos and insect ecology

Treesearch

Jesse A. Logan; Fred P. Hain

1990-01-01

Recent advances in applied mathematical analysis have uncovered a fascinating and unexpected dynamical richness that underlies behavior of even the simplest non-linear mathematical models. Due to the complexity of solutions to these non-linear equations, a new mathematical term, chaos, has been coined to describe the resulting dynamics. This term captures the notion...

Narrative and Chaos Acknowledging the Novelty of Lives-in-Time

ERIC Educational Resources Information Center

Randall, William L.

2007-01-01

In this paper I propose that interest in "narrative" within the human sciences is comparable to interest in "chaos" within the natural sciences. In their respective ways, theories on narrative and theories on chaos are aimed at appreciating the dynamics of complex, multi-dimensional systems which otherwise resist our attempts to predict, measure,…

"The CNN Effect:" TV & Foreign Policy. Study Guide. Episode #834. America's Defense Monitor, Educational TV for the Classroom.

ERIC Educational Resources Information Center

Edwards, B. T.

This program examines the current acceleration of the decision-making cycle in the conduct of foreign policy due to the instantaneous reporting of events, called "The CNN Effect." The sometimes paradoxical consequences of global media coverage are noted, along with the examination of the medium of television itself, and its shortcomings…

Examining the Relationship Between Children's ADHD Symptomatology and Inadequate Parenting: The Role of Household Chaos.

PubMed

Wirth, Andrea; Reinelt, Tilman; Gawrilow, Caterina; Schwenck, Christina; Freitag, Christine M; Rauch, Wolfgang A

2017-02-01

This study examines the interrelations of parenting practices, emotional climate, and household chaos in families with children with and without ADHD. In particular, indirect pathways from children's ADHD symptomatology to inadequate parenting and negative emotional climate via household chaos were investigated. Parenting, emotional climate, and household chaos were assessed using questionnaires and a speech sample of parents of 31 children with and 53 without ADHD, aged 7 to 13 years. Group differences were found for certain parenting dimensions, the parent-child relationship, critical comments, and household chaos. While we found significant indirect effects between children's ADHD and certain parenting dimensions through household chaos, no effects were found for any aspect of emotional climate. Children's ADHD symptoms translate into inadequate parenting through household chaos, which underlines the need for interventions to improve household organization skills in parents of children with ADHD.

Socioeconomic risk moderates the link between household chaos and maternal executive function.

PubMed

Deater-Deckard, Kirby; Chen, Nan; Wang, Zhe; Bell, Martha Ann

2012-06-01

We examined the link between household chaos (i.e., noise, clutter, disarray, lack of routines) and maternal executive function (i.e., effortful regulation of attention and memory), and whether it varied as a function of socioeconomic risk (i.e., single parenthood, lower mother and father educational attainment, housing situation, and father unemployment). We hypothesized that: 1) higher levels of household chaos would be linked with poorer maternal executive function, even when controlling for other measures of cognitive functioning (e.g., verbal ability), and 2) this link would be strongest in the most socioeconomically distressed or lowest-socioeconomic status households. The diverse sample included 153 mothers from urban and rural areas who completed a questionnaire and a battery of cognitive executive function tasks and a verbal ability task in the laboratory. Results were mixed for Hypothesis 1, and consistent with Hypothesis 2. Two-thirds of the variance overlapped between household chaos and maternal executive function, but only in families with high levels of socioeconomic risk. This pattern was not found for chaos and maternal verbal ability, suggesting that the potentially deleterious effects of household chaos may be specific to maternal executive function. The findings implicate household chaos as a powerful statistical predictor of maternal executive function in socioeconomically distressed contexts. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Quantum chaos: An entropy approach

NASA Astrophysics Data System (ADS)

Sl/omczyński, Wojciech; Życzkowski, Karol

1994-11-01

A new definition of the entropy of a given dynamical system and of an instrument describing the measurement process is proposed within the operational approach to quantum mechanics. It generalizes other definitions of entropy, in both the classical and quantum cases. The Kolmogorov-Sinai (KS) entropy is obtained for a classical system and the sharp measurement instrument. For a quantum system and a coherent states instrument, a new quantity, coherent states entropy, is defined. It may be used to measure chaos in quantum mechanics. The following correspondence principle is proved: the upper limit of the coherent states entropy of a quantum map as ℏ→0 is less than or equal to the KS-entropy of the corresponding classical map. ``Chaos umpire sits, And by decision more imbroils the fray By which he reigns: next him high arbiter Chance governs all.'' John Milton, Paradise Lost, Book II

Master Teachers: Making a Difference on the Edge of Chaos

ERIC Educational Resources Information Center

Chapin, Dexter

2008-01-01

The No Child Left Behind legislation, by legitimizing a stark, one-size-fits-all, industrial model of education, has denied the inherent complexity and richness of what teachers do. Discussing teaching in terms of Chaos Theory, Chapin explains that while excellent teaching may occur at the edge of chaos, it is not chaotic. There are patterns…

Aram Chaos Rocks

NASA Technical Reports Server (NTRS)

2005-01-01

8 September 2005 This Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) image shows outcrops of light-toned, sedimentary rock among darker-toned mesas in Aram Chaos. Dark, windblown megaripples -- large ripples -- are also present at this location.

Location near: 3.0oN, 21.6oW Image width: width: 3 km (1.9 mi) Illumination from: lower left Season: Northern Autumn

Properties of a Martian local dust storm in Atlantis Chaos from OMEGA/MEX data

NASA Astrophysics Data System (ADS)

Oliva, F.; Geminale, A.; D'Aversa, E.; Altieri, F.; Bellucci, G.; Carrozzo, F. G.; Sindoni, G.; Grassi, D.

2018-01-01

In this study we present the analysis of the dust properties of a local storm imaged in the Atlantis Chaos region on Mars by the OMEGA imaging spectrometer on March 2nd, 2005. We use the radiative transfer model MITRA to study the dust properties at solar wavelengths between 0.5 μm and 2.5 μm and infer the connection between the local storm dynamics and the topography. We retrieve maps of effective grain radius (reff), optical depth at 9.3 μm (τ9.3) and top altitude (ta) of the dust layer. Our results show that large particles (reff = 1.6 μm) are gathered in the centre of the storm (lat = 33.5° S; lon = 183.5° W), where the optical depth is maximum (τ9.3 > 7.0) and the top altitude exceeds 18 km. Outside the storm, we obtain τ9.3<0.2, in agreement with the estimates derived from global climate models (GCM). We speculate that a low thermal inertia region at the western border of Atlantis Chaos is a possible source of the dust storm. Moreover, we find evidence that topography plays a role in confining the local storm in Atlantis Chaos. The vertical wind component from the GCM does not provide any hint for the triggering of dust lifting. On the other hand, the combination of the horizontal and vertical wind profiles suggests that the dust, once lifted, is pushed eastward and then downward and gets confined within the north-east ridge of Atlantis Chaos. From our results, the thickness of the dust layer collapsed on the surface ranges from about 1 μm at the storm boundaries up to more than 100 μm at its centre. We verify that a layer of dust thicker than 1 μm, deposited on the surface, can prevent the detection of mafic absorption features. However, such features are still present in OMEGA data of Atlantis Chaos registered after the storm. Hence, we deduce that, once the storm is over, the dust deposited on an area larger than the one where it has been observed.

Chaos, Poverty, and Parenting: Predictors of Early Language Development

PubMed Central

Vernon-Feagans, Lynne; Garrett-Peters, Patricia; Willoughby, Mike; Mills-Koonce, Roger

2011-01-01

Studies have shown that distal family risk factors like poverty and maternal education are strongly related to children's early language development. Yet, few studies have examined these risk factors in combination with more proximal day-to-day experiences of children that might be critical to understanding variation in early language. Young children's exposure to a chronically chaotic household may be one critical experience that is related to poorer language, beyond the contribution of SES and other demographic variables. In addition, it is not clear whether parenting might mediate the relationship between chaos and language. The purpose of this study was to understand how multiple indicators of chaos over children's first three years of life, in a representative sample of children living in low wealth rural communities, were related to child expressive and receptive language at 36 months. Factor analysis of 10 chaos indicators over five time periods suggested two factors that were named household disorganization and instability. Results suggested that after accounting for thirteen covariates like maternal education and poverty, one of two chaos composites (household disorganization) accounted for significant variance in receptive and expressive language. Parenting partially mediated this relationship although household disorganization continued to account for unique variance in predicting early language. PMID:23049162

Direct generation of all-optical random numbers from optical pulse amplitude chaos.

PubMed

Li, Pu; Wang, Yun-Cai; Wang, An-Bang; Yang, Ling-Zhen; Zhang, Ming-Jiang; Zhang, Jian-Zhong

2012-02-13

We propose and theoretically demonstrate an all-optical method for directly generating all-optical random numbers from pulse amplitude chaos produced by a mode-locked fiber ring laser. Under an appropriate pump intensity, the mode-locked laser can experience a quasi-periodic route to chaos. Such a chaos consists of a stream of pulses with a fixed repetition frequency but random intensities. In this method, we do not require sampling procedure and external triggered clocks but directly quantize the chaotic pulses stream into random number sequence via an all-optical flip-flop. Moreover, our simulation results show that the pulse amplitude chaos has no periodicity and possesses a highly symmetric distribution of amplitude. Thus, in theory, the obtained random number sequence without post-processing has a high-quality randomness verified by industry-standard statistical tests.

Towards completing the cyclopropenylidene cycle: rovibrational analysis of cyclic N3+, CNN, HCNN+, and CNC.

PubMed

Fortenberry, Ryan C; Lee, Timothy J; Huang, Xinchuan

2017-08-30

The simple aromatic hydrocarbon, cyclopropenylidene (c-C 3 H 2 ), is a known, naturally-occurring molecule. The question remains as to whether its isoelectronic, cyclic, fellow aromatics of c-N 3 + , c-CNN, HCNN + , and c-CNC - are as well. Each of these are exciting objects for observation of Titan, and the rotational constants and vibrational frequencies produced here will allow for remote sensing of Titan's atmosphere or other astrophysical or terrestrial sources. None of these four aromatic species are vibrationally strong absorbers/emitters, but the two ions, HCNN + and c-CNC - , have dipole moments of greater than 3 D and 1 D, respectively, making them good targets for rotational spectroscopic observation. Each of these molecules is shown here to exhibit its own, unique vibrational properties, but the general trends put the vibrational behavior for corresponding fundamental modes within close ranges of one another, even producing nearly the same heavy atom, symmetric stretching frequencies for HCNN + and c-C 3 H 2 at 1600 cm -1 . The c-N 3 + cation is confirmed to be fairly unstable and has almost no intensity in its ν 2 fundamental. Hence, it will likely remain difficult to characterize experimentally.

Detecting chaos in irregularly sampled time series.

PubMed

Kulp, C W

2013-09-01

Recently, Wiebe and Virgin [Chaos 22, 013136 (2012)] developed an algorithm which detects chaos by analyzing a time series' power spectrum which is computed using the Discrete Fourier Transform (DFT). Their algorithm, like other time series characterization algorithms, requires that the time series be regularly sampled. Real-world data, however, are often irregularly sampled, thus, making the detection of chaotic behavior difficult or impossible with those methods. In this paper, a characterization algorithm is presented, which effectively detects chaos in irregularly sampled time series. The work presented here is a modification of Wiebe and Virgin's algorithm and uses the Lomb-Scargle Periodogram (LSP) to compute a series' power spectrum instead of the DFT. The DFT is not appropriate for irregularly sampled time series. However, the LSP is capable of computing the frequency content of irregularly sampled data. Furthermore, a new method of analyzing the power spectrum is developed, which can be useful for differentiating between chaotic and non-chaotic behavior. The new characterization algorithm is successfully applied to irregularly sampled data generated by a model as well as data consisting of observations of variable stars.

Melnikov's criteria, parametric control of chaos, and stationary chaos occurrence in systems with asymmetric potential subjected to multiscale type excitation.

PubMed

Kwuimy, C A Kitio; Nataraj, C; Litak, G

2011-12-01

We consider the problems of chaos and parametric control in nonlinear systems under an asymmetric potential subjected to a multiscale type excitation. The lower bound line for horseshoes chaos is analyzed using the Melnikov's criterion for a transition to permanent or transient nonperiodic motions, complement by the fractal or regular shape of the basin of attraction. Numerical simulations based on the basins of attraction, bifurcation diagrams, Poincaré sections, Lyapunov exponents, and phase portraits are used to show how stationary dissipative chaos occurs in the system. Our attention is focussed on the effects of the asymmetric potential term and the driven frequency. It is shown that the threshold amplitude ∣γ(c)∣ of the excitation decreases for small values of the driven frequency ω and increases for large values of ω. This threshold value decreases with the asymmetric parameter α and becomes constant for sufficiently large values of α. γ(c) has its maximum value for asymmetric load in comparison with the symmetric load. Finally, we apply the Melnikov theorem to the controlled system to explore the gain control parameter dependencies.

Chaos, Complexity, Learning, and the Learning Organization: Towards a Chaordic Enterprise

ERIC Educational Resources Information Center

van Eijnatten, Frans M.; Putnik, Goran D.

2004-01-01

In order to set the stage for this special issue, the prime concepts are defined: i.e. "chaos," "complexity," "learning" (individual and organizational), "learning organization," and "chaordic enterprise". Also, several chaos-and-complexity-related definitions of learning and learning organizations are provided. Next, the guest editors' main…

An introduction to chaos theory in CFD

NASA Technical Reports Server (NTRS)

Pulliam, Thomas H.

1990-01-01

The popular subject 'chaos theory' has captured the imagination of a wide variety of scientists and engineers. CFD has always been faced with nonlinear systems and it is natural to assume that nonlinear dynamics will play a role at sometime in such work. This paper will attempt to introduce some of the concepts and analysis procedures associated with nonlinear dynamics theory. In particular, results from computations of an airfoil at high angle of attack which exhibits a sequence of bifurcations for single frequency unsteady shedding through period doublings cascading into low dimensional chaos are used to present and demonstrate various aspects of nonlinear dynamics in CFD.

The Chaos Theory of Careers.

ERIC Educational Resources Information Center

Pryor, Robert G. L.; Bright, Jim

2003-01-01

Four theoretical streams--contexualism/ecology, systems theory, realism/constructivism, and chaos theory--contributed to a theory of individuals as complex, unique, nonlinear, adaptive chaotic and open systems. Individuals use purposive action to construct careers but can make maladaptive and inappropriate choices. (Contains 42 references.) (SK)

Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium.

PubMed

Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

2017-09-01

Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium

NASA Astrophysics Data System (ADS)

Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

2017-09-01

Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

Chaos synchronization communication using extremely unsymmetrical bidirectional injections.

PubMed

Zhang, Wei Li; Pan, Wei; Luo, Bin; Zou, Xi Hua; Wang, Meng Yao; Zhou, Zhi

2008-02-01

Chaos synchronization and message transmission between two semiconductor lasers with extremely unsymmetrical bidirectional injections (EUBIs) are discussed. By using EUBIs, synchronization is realized through injection locking. Numerical results show that if the laser subjected to strong injection serves as the receiver, chaos pass filtering (CPF) of the system is similar to that of unidirectional coupled systems. Moreover, if the other laser serves as the receiver, a stronger CPF can be obtained. Finally, we demonstrate that messages can be extracted successfully from either of the two transmission directions of the system.

Arsinoes Chaos

NASA Technical Reports Server (NTRS)

2003-01-01

[figure removed for brevity, see original site]

At the easternmost end of Valles Marineris, a rugged, jumbled terrain known as chaos displays a stratigraphy that could be described as precarious. Perched on top of the jumbled blocks is another layer of sedimentary material that is in the process of being eroded off the top. This material is etched by the wind into yardangs before it ultimately is stripped off to reveal the existing chaos.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Image information: VIS instrument. Latitude -7.8, Longitude 19.1 East (340.9 West). 19 meter/pixel resolution.

The design and research of anti-color-noise chaos M-ary communication system

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

Fu, Yongqing, E-mail: fuyongqing@hrbeu.edu.cn; Li, Xingyuan; Li, Yanan

Previously a novel chaos M-ary digital communication method based on spatiotemporal chaos Hamilton oscillator has been proposed. Without chaos synchronization circumstance, it has performance improvement in bandwidth efficiency, transmission efficiency and anti-white-noise performance compared with traditional communication method. In this paper, the channel noise influence on chaotic modulation signals and the construction problem of anti-color-noise chaotic M-ary communication system are studied. The formula of zone partition demodulator’s boundary in additive white Gaussian noise is derived, besides, the problem about how to determine the boundary of zone partition demodulator in additive color noise is deeply studied; Then an approach on constructingmore » anti-color-noise chaos M-ary communication system is proposed, in which a pre-distortion filter is added after the chaos baseband modulator in the transmitter and whitening filter is added before zone partition demodulator in the receiver. Finally, the chaos M-ary communication system based on Hamilton oscillator is constructed and simulated in different channel noise. The result shows that the proposed method in this paper can improve the anti-color-noise performance of the whole communication system compared with the former system, and it has better anti-fading and resisting disturbance performance than Quadrature Phase Shift Keying system.« less

Understanding the Role of Chaos Theory in Military Decision Making

DTIC Science & Technology

2009-01-01

Because chaos is bounded, planners can create allowances for system noise. The existence of strange and normal chaotic attractors helps explain why... strange and normal chaotic attractors helps explain why system turbulence is uneven or concentrated around specific solution regions. Finally, the...give better understanding of the implications of chaos: sensitivity to initial conditions, strange attractors , and constants of motion. By showing the

Chaos: Understanding and Controlling Laser Instability

NASA Technical Reports Server (NTRS)

Blass, William E.

1997-01-01

In order to characterize the behavior of tunable diode lasers (TDL), the first step in the project involved the redesign of the TDL system here at the University of Tennessee Molecular Systems Laboratory (UTMSL). Having made these changes it was next necessary to optimize the new optical system. This involved the fine adjustments to the optical components, particularly in the monochromator, to minimize the aberrations of coma and astigmatism and to assure that the energy from the beam is focused properly on the detector element. The next step involved the taking of preliminary data. We were then ready for the analysis of the preliminary data. This required the development of computer programs that use mathematical techniques to look for signatures of chaos. Commercial programs were also employed. We discovered some indication of high dimensional chaos, but were hampered by the low sample rate of 200 KSPS (kilosamples/sec) and even more by our sample size of 1024 (1K) data points. These limitations were expected and we added a high speed data acquisition board. We incorporated into the system a computer with a 40 MSPS (million samples/sec) data acquisition board. This board can also capture 64K of data points so that were then able to perform the more accurate tests for chaos. The results were dramatic and compelling, we had demonstrated that the lead salt diode laser had a chaotic frequency output. Having identified the chaotic character in our TDL data, we proceeded to stage two as outlined in our original proposal. This required the use of an Occasional Proportional Feedback (OPF) controller to facilitate the control and stabilization of the TDL system output. The controller was designed and fabricated at GSFC and debugged in our laboratories. After some trial and error efforts, we achieved chaos control of the frequency emissions of the laser. The two publications appended to this introduction detail the entire project and its results.

Arsinoes Chaos Landforms

NASA Technical Reports Server (NTRS)

2004-01-01

23 October 2004 This Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) image shows light-toned rock outcrops, possibly sedimentary rocks, in the Arsinoes Chaos region east of the Valles Marineris trough system. These rocky materials were once below the martian surface. These features are located near 7.2oS, 27.9oW. The image covers an area about 3 km (1.9 mi) wide. Sunlight illuminates the scene from the upper left.

Poincaré chaos and unpredictable functions

NASA Astrophysics Data System (ADS)

Akhmet, Marat; Fen, Mehmet Onur

2017-07-01

The results of this study are continuation of the research of Poincaré chaos initiated in the papers (M. Akhmet and M.O. Fen, Commun Nonlinear Sci Numer Simulat 40 (2016) 1-5; M. Akhmet and M.O. Fen, Turk J Math, doi:10.3906/mat-1603-51, in press). We focus on the construction of an unpredictable function, continuous on the real axis. As auxiliary results, unpredictable orbits for the symbolic dynamics and the logistic map are obtained. By shaping the unpredictable function as well as Poisson function we have performed the first step in the development of the theory of unpredictable solutions for differential and discrete equations. The results are preliminary ones for deep analysis of chaos existence in differential and hybrid systems. Illustrative examples concerning unpredictable solutions of differential equations are provided.

Introduction to the focus issue: fifty years of chaos: applied and theoretical.

PubMed

Hikihara, Takashi; Holmes, Philip; Kambe, Tsutomu; Rega, Giuseppe

2012-12-01

The discovery of deterministic chaos in the late nineteenth century, its subsequent study, and the development of mathematical and computational methods for its analysis have substantially influenced the sciences. Chaos is, however, only one phenomenon in the larger area of dynamical systems theory. This Focus Issue collects 13 papers, from authors and research groups representing the mathematical, physical, and biological sciences, that were presented at a symposium held at Kyoto University from November 28 to December 2, 2011. The symposium, sponsored by the International Union of Theoretical and Applied Mechanics, was called 50 Years of Chaos: Applied and Theoretical. Following some historical remarks to provide a background for the last 50 years, and for chaos, this Introduction surveys the papers and identifies some common themes that appear in them and in the theory of dynamical systems.

Anticontrol of chaos in continuous-time systems via time-delay feedback.

PubMed

Wang, Xiao Fan; Chen, Guanrong; Yu, Xinghuo

2000-12-01

In this paper, a systematic design approach based on time-delay feedback is developed for anticontrol of chaos in a continuous-time system. This anticontrol method can drive a finite-dimensional, continuous-time, autonomous system from nonchaotic to chaotic, and can also enhance the existing chaos of an originally chaotic system. Asymptotic analysis is used to establish an approximate relationship between a time-delay differential equation and a discrete map. Anticontrol of chaos is then accomplished based on this relationship and the differential-geometry control theory. Several examples are given to verify the effectiveness of the methodology and to illustrate the systematic design procedure. (c) 2000 American Institute of Physics.

Opinion mining on book review using CNN-L2-SVM algorithm

NASA Astrophysics Data System (ADS)

Rozi, M. F.; Mukhlash, I.; Soetrisno; Kimura, M.

2018-03-01

Review of a product can represent quality of a product itself. An extraction to that review can be used to know sentiment of that opinion. Process to extract useful information of user review is called Opinion Mining. Review extraction model that is enhancing nowadays is Deep Learning model. This Model has been used by many researchers to obtain excellent performance on Natural Language Processing. In this research, one of deep learning model, Convolutional Neural Network (CNN) is used for feature extraction and L2 Support Vector Machine (SVM) as classifier. These methods are implemented to know the sentiment of book review data. The result of this method shows state-of-the art performance in 83.23% for training phase and 64.6% for testing phase.

Self-organization of chaos in mythology from a scientific point of view

NASA Astrophysics Data System (ADS)

Melker, Alexander I.

2007-04-01

In this contribution ancient Greek myths describing world's creation are analyzed as if they were a scientific paper. The 'paper' divided into the following parts: initial and boundary conditions, self-organization of chaos, world lines of self-organization, conclusion. It is shown that the self-organization of chaos consists of several stages during which two motive forces (attractive and repulsive) are generated, and totally disordered chaos transforms into partially ordered. It is found that there are five world lines of self-organization: water, light, cosmos-weather, water-fire, and State evolution.

Canyons and Mesas of Aureum Chaos

NASA Image and Video Library

2002-06-26

This image from NASA Mars Odyssey shows a portion of Aureum Chaos located just south of the Martian equator. This fractured landscape contains canyons and mesas with two large impact craters in the upper left.

A heuristic method for identifying chaos from frequency content.

PubMed

Wiebe, R; Virgin, L N

2012-03-01

The sign of the largest Lyapunov exponent is the fundamental indicator of chaos in a dynamical system. However, although the extraction of Lyapunov exponents can be accomplished with (necessarily noisy) the experimental data, this is still a relatively data-intensive and sensitive endeavor. This paper presents an alternative pragmatic approach to identifying chaos using response frequency characteristics and extending the concept of the spectrogram. The method is shown to work well on both experimental and simulated time series.

Active formation of 'chaos terrain' over shallow subsurface water on Europa.

PubMed

Schmidt, B E; Blankenship, D D; Patterson, G W; Schenk, P M

2011-11-16

Europa, the innermost icy satellite of Jupiter, has a tortured young surface and sustains a liquid water ocean below an ice shell of highly debated thickness. Quasi-circular areas of ice disruption called chaos terrains are unique to Europa, and both their formation and the ice-shell thickness depend on Europa's thermal state. No model so far has been able to explain why features such as Conamara Chaos stand above surrounding terrain and contain matrix domes. Melt-through of a thin (few-kilometre) shell is thermodynamically improbable and cannot raise the ice. The buoyancy of material rising as either plumes of warm, pure ice called diapirs or convective cells in a thick (>10 kilometres) shell is insufficient to produce the observed chaos heights, and no single plume can create matrix domes. Here we report an analysis of archival data from Europa, guided by processes observed within Earth's subglacial volcanoes and ice shelves. The data suggest that chaos terrains form above liquid water lenses perched within the ice shell as shallow as 3 kilometres. Our results suggest that ice-water interactions and freeze-out give rise to the diverse morphologies and topography of chaos terrains. The sunken topography of Thera Macula indicates that Europa is actively resurfacing over a lens comparable in volume to the Great Lakes in North America. ©2011 Macmillan Publishers Limited. All rights reserved

Active formation of `chaos terrain' over shallow subsurface water on Europa

NASA Astrophysics Data System (ADS)

Schmidt, B. E.; Blankenship, D. D.; Patterson, G. W.; Schenk, P. M.

2011-11-01

Europa, the innermost icy satellite of Jupiter, has a tortured young surface and sustains a liquid water ocean below an ice shell of highly debated thickness. Quasi-circular areas of ice disruption called chaos terrains are unique to Europa, and both their formation and the ice-shell thickness depend on Europa's thermal state. No model so far has been able to explain why features such as Conamara Chaos stand above surrounding terrain and contain matrix domes. Melt-through of a thin (few-kilometre) shell is thermodynamically improbable and cannot raise the ice. The buoyancy of material rising as either plumes of warm, pure ice called diapirs or convective cells in a thick (>10 kilometres) shell is insufficient to produce the observed chaos heights, and no single plume can create matrix domes. Here we report an analysis of archival data from Europa, guided by processes observed within Earth's subglacial volcanoes and ice shelves. The data suggest that chaos terrains form above liquid water lenses perched within the ice shell as shallow as 3kilometres. Our results suggest that ice-water interactions and freeze-out give rise to the diverse morphologies and topography of chaos terrains. The sunken topography of Thera Macula indicates that Europa is actively resurfacing over a lens comparable in volume to the Great Lakes in North America.

Quantum chaos in the Heisenberg spin chain: The effect of Dzyaloshinskii-Moriya interaction.

PubMed

Vahedi, J; Ashouri, A; Mahdavifar, S

2016-10-01

Using one-dimensional spin-1/2 systems as prototypes of quantum many-body systems, we study the emergence of quantum chaos. The main purpose of this work is to answer the following question: how the spin-orbit interaction, as a pure quantum interaction, may lead to the onset of quantum chaos? We consider the three integrable spin-1/2 systems: the Ising, the XX, and the XXZ limits and analyze whether quantum chaos develops or not after the addition of the Dzyaloshinskii-Moriya interaction. We find that depending on the strength of the anisotropy parameter, the answer is positive for the XXZ and Ising models, whereas no such evidence is observed for the XX model. We also discuss the relationship between quantum chaos and thermalization.

The Drosophila Pericentrin-like-protein (PLP) cooperates with Cnn to maintain the integrity of the outer PCM

PubMed Central

Richens, Jennifer H.; Barros, Teresa P.; Lucas, Eliana P.; Peel, Nina; Pinto, David Miguel Susano; Wainman, Alan; Raff, Jordan W.

2015-01-01

ABSTRACT Centrosomes comprise a pair of centrioles surrounded by a matrix of pericentriolar material (PCM). In vertebrate cells, Pericentrin plays an important part in mitotic PCM assembly, but the Drosophila Pericentrin-like protein (PLP) appears to have a more minor role in mitotic fly cells. Here we investigate the function of PLP during the rapid mitotic cycles of the early Drosophila embryo. Unexpectedly, we find that PLP is specifically enriched in the outer-most regions of the PCM, where it largely co-localizes with the PCM scaffold protein Cnn. In the absence of PLP the outer PCM appears to be structurally weakened, and it rapidly disperses along the centrosomal microtubules (MTs). As a result, centrosomal MTs are subtly disorganized in embryos lacking PLP, although mitosis is largely unperturbed and these embryos develop and hatch at near-normal rates. Y2H analysis reveals that PLP can potentially form multiple interactions with itself and with the PCM recruiting proteins Asl, Spd-2 and Cnn. A deletion analysis suggests that PLP participates in a complex network of interactions that ultimately help to strengthen the PCM. PMID:26157019

The Drosophila Pericentrin-like-protein (PLP) cooperates with Cnn to maintain the integrity of the outer PCM.

PubMed

Richens, Jennifer H; Barros, Teresa P; Lucas, Eliana P; Peel, Nina; Pinto, David Miguel Susano; Wainman, Alan; Raff, Jordan W

2015-07-08

Centrosomes comprise a pair of centrioles surrounded by a matrix of pericentriolar material (PCM). In vertebrate cells, Pericentrin plays an important part in mitotic PCM assembly, but the Drosophila Pericentrin-like protein (PLP) appears to have a more minor role in mitotic fly cells. Here we investigate the function of PLP during the rapid mitotic cycles of the early Drosophila embryo. Unexpectedly, we find that PLP is specifically enriched in the outer-most regions of the PCM, where it largely co-localizes with the PCM scaffold protein Cnn. In the absence of PLP the outer PCM appears to be structurally weakened, and it rapidly disperses along the centrosomal microtubules (MTs). As a result, centrosomal MTs are subtly disorganized in embryos lacking PLP, although mitosis is largely unperturbed and these embryos develop and hatch at near-normal rates. Y2H analysis reveals that PLP can potentially form multiple interactions with itself and with the PCM recruiting proteins Asl, Spd-2 and Cnn. A deletion analysis suggests that PLP participates in a complex network of interactions that ultimately help to strengthen the PCM. © 2015. Published by The Company of Biologists Ltd.

Ariadnes Colles Chaos

NASA Technical Reports Server (NTRS)

2002-01-01

(Released 18 June 2002) Among the many varied landscapes on Mars the term chaos is applied to those places that have a jumbled, blocky appearance. Most of the better known chaotic terrain occurs in the northern hemisphere but there are other occurrences in the southern hemisphere, three of which are centered on 180 degrees west longitude. Ariadnes Colles, Atlantis, and Gorgonum Chaos all share similar features: relatively bright, irregularly shaped knobs and mesas that rise above a dark, sand-covered, hummocky floor. Close inspection of this THEMIS image shows that the darker material tends to lap up to the base of the knobs and stops where the slopes are steep. On some of the lowest knobs, the dark material appears to overtop them. The knobs themselves are highly eroded, many having a pitted appearance. Images from the camera on Mars Global Surveyor clearly show that the dark material is sand, based on its mantling appearance and the presence of dunes. It looks as though the material that composes the knobs was probably a continuous layer that was subsequently heavily eroded. While it is likely that the dark sand is responsible for some of the erosion it is also possible that the this landscape was eroded by some other process and the sand was emplaced at a later time.

Free-Energy Fluctuations and Chaos in the Sherrington-Kirkpatrick Model

NASA Astrophysics Data System (ADS)

Aspelmeier, T.

2008-03-01

The sample-to-sample fluctuations ΔFN of the free-energy in the Sherrington-Kirkpatrick model are shown rigorously to be related to bond chaos. Via this connection, the fluctuations become analytically accessible by replica methods. The replica calculation for bond chaos shows that the exponent μ governing the growth of the fluctuations with system size N, ΔFN˜Nμ, is bounded by μ≤(1)/(4).

At the Edge of Chaos: A New Paradigm for Social Work?

ERIC Educational Resources Information Center

Hudson, Christopher G.

2000-01-01

Reviews key concepts and applications of chaos theory and the broader complex systems theory in the context of general systems theory and the search for a unified conceptual framework for social work. Concludes that chaos theory shows promise as a solution to many problems posed by the now dated general systems approach. (DB)

Effect of the centrifugal force on domain chaos in Rayleigh-Bénard convection.

PubMed

Becker, Nathan; Scheel, J D; Cross, M C; Ahlers, Guenter

2006-06-01

Experiments and simulations from a variety of sample sizes indicated that the centrifugal force significantly affects the domain-chaos state observed in rotating Rayleigh-Bénard convection-patterns. In a large-aspect-ratio sample, we observed a hybrid state consisting of domain chaos close to the sample center, surrounded by an annulus of nearly stationary nearly radial rolls populated by occasional defects reminiscent of undulation chaos. Although the Coriolis force is responsible for domain chaos, by comparing experiment and simulation we show that the centrifugal force is responsible for the radial rolls. Furthermore, simulations of the Boussinesq equations for smaller aspect ratios neglecting the centrifugal force yielded a domain precession-frequency f approximately epsilon(mu) with mu approximately equal to 1 as predicted by the amplitude-equation model for domain chaos, but contradicted by previous experiment. Additionally the simulations gave a domain size that was larger than in the experiment. When the centrifugal force was included in the simulation, mu and the domain size were consistent with experiment.

Shear-induced chaos

NASA Astrophysics Data System (ADS)

Lin, Kevin K.; Young, Lai-Sang

2008-05-01

Guided by a geometric understanding developed in earlier works of Wang and Young, we carry out numerical studies of shear-induced chaos in several parallel but different situations. The settings considered include periodic kicking of limit cycles, random kicks at Poisson times and continuous-time driving by white noise. The forcing of a quasi-periodic model describing two coupled oscillators is also investigated. In all cases, positive Lyapunov exponents are found in suitable parameter ranges when the forcing is suitably directed.

Monohydrated Sulfates in Aurorae Chaos

NASA Technical Reports Server (NTRS)

2008-01-01

This image of sulfate-containing deposits in Aurorae Chaos was taken by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) at 0653 UTC (2:53 a.m. EDT) on June 10, 2007, near 7.5 degrees south latitude, 327.25 degrees east longitude. CRISM's image was taken in 544 colors covering 0.36-3.92 micrometers, and shows features as small as 40 meters (132 feet) across. The region covered is roughly 12 kilometers (7.5 miles) wide at its narrowest point.

Aurorae Chaos lies east of the Valles Marineris canyon system. Its western edge extends toward Capri and Eos Chasmata, while its eastern edge connects with Aureum Chaos. Some 750 kilometers (466 miles) wide, Aurorae Chaos is most likely the result of collapsed surface material that settled when subsurface ice or water was released.

The top panel in the montage above shows the location of the CRISM image on a mosaic taken by the Mars Odyssey spacecraft's Thermal Emission Imaging System (THEMIS). The CRISM data covers an area featuring several knobs of erosion-resistant material at one end of what appears to be a large teardrop shaped plateau. Similar plateaus occur throughout the interior of Valles Marineris, and they are formed of younger, typically layered rocks that post-date formation of the canyon system. Many of the deposits contain sulfate-rich layers, hinting at ancient saltwater.

The center left image, an infrared false color image, reveals a swath of light-colored material draped over the knobs. The center right image unveils the mineralogical composition of the area, with yellow representing monohydrated sulfates (sulfates with one water molecule incorporated into each molecule of the mineral).

The lower two images are renderings of data draped over topography with 5 times vertical exaggeration. These images provide a view of the topography and reveal how the monohydrated sulfate-containing deposits drape over the knobs and also an outcrop in lower-elevation parts of the

Equilibriumizing all food chain chaos through reproductive efficiency.

PubMed

Deng, Bo

2006-12-01

The intraspecific interference of a top-predator is incorporated into a classical mathematical model for three-trophic food chains. All chaos types known to the classical model are shown to exist for this comprehensive model. It is further demonstrated that if the top-predator reproduces at high efficiency, then all chaotic dynamics will change to a stable coexisting equilibrium, a novel property not found in the classical model. This finding gives a mechanistic explanation to the question of why food chain chaos is rare in the field. It also suggests that high reproductive efficiency of top-predators tends to stabilize food chains.

Suppression of chaos via control of energy flow

NASA Astrophysics Data System (ADS)

Guo, Shengli; Ma, Jun; Alsaedi, Ahmed

2018-03-01

Continuous energy supply is critical and important to support oscillating behaviour; otherwise, the oscillator will die. For nonlinear and chaotic circuits, enough energy supply is also important to keep electric devices working. In this paper, Hamilton energy is calculated for dimensionless dynamical system (e.g., the chaotic Lorenz system) using Helmholtz's theorem. The Hamilton energy is considered as a new variable and then the dynamical system is controlled by using the scheme of energy feedback. It is found that chaos can be suppressed even when intermittent feedback scheme is applied. This scheme is effective to control chaos and to stabilise other dynamical systems.

The Chaos of Katrina

DTIC Science & Technology

2007-03-01

partners for their mutual benefit. Unfortunately, based on government reports, FEMA did not have adequate control of its supply chain information ...is one attractor . “Edge of chaos” systems have two to eight attractors and in chaotic systems many attractors . Some are called strange attractors ...investigates whether chaos theory, part of complexity science, can extract information from Katrina contracting data to help managers make better logistics

Short-term data forecasting based on wavelet transformation and chaos theory

NASA Astrophysics Data System (ADS)

Wang, Yi; Li, Cunbin; Zhang, Liang

2017-09-01

A sketch of wavelet transformation and its application was given. Concerning the characteristics of time sequence, Haar wavelet was used to do data reduction. After processing, the effect of “data nail” on forecasting was reduced. Chaos theory was also introduced, a new chaos time series forecasting flow based on wavelet transformation was proposed. The largest Lyapunov exponent was larger than zero from small data sets, it verified the data change behavior still met chaotic behavior. Based on this, chaos time series to forecast short-term change behavior could be used. At last, the example analysis of the price from a real electricity market showed that the forecasting method increased the precision of the forecasting more effectively and steadily.

Multiple Scenarios of Transition to Chaos in the Alternative Splicing Model

NASA Astrophysics Data System (ADS)

Kogai, Vladislav V.; Likhoshvai, Vitaly A.; Fadeev, Stanislav I.; Khlebodarova, Tamara M.

We have investigated the scenarios of transition to chaos in the mathematical model of a genetic system constituted by a single transcription factor-encoding gene, the expression of which is self-regulated by a feedback loop that involves protein isoforms. Alternative splicing results in the synthesis of protein isoforms providing opposite regulatory outcomes — activation or repression. The model is represented by a differential equation with two delayed arguments. The possibility of transition to chaos dynamics via all classical scenarios: a cascade of period-doubling bifurcations, quasiperiodicity and type-I, type-II and type-III intermittencies, has been numerically demonstrated. The parametric features of each type of transition to chaos have been described.

A period-doubling cascade precedes chaos for planar maps.

PubMed

Sander, Evelyn; Yorke, James A

2013-09-01

A period-doubling cascade is often seen in numerical studies of those smooth (one-parameter families of) maps for which as the parameter is varied, the map transitions from one without chaos to one with chaos. Our emphasis in this paper is on establishing the existence of such a cascade for many maps with phase space dimension 2. We use continuation methods to show the following: under certain general assumptions, if at one parameter there are only finitely many periodic orbits, and at another parameter value there is chaos, then between those two parameter values there must be a cascade. We investigate only families that are generic in the sense that all periodic orbit bifurcations are generic. Our method of proof in showing there is one cascade is to show there must be infinitely many cascades. We discuss in detail two-dimensional families like those which arise as a time-2π maps for the Duffing equation and the forced damped pendulum equation.

Efficient topological chaos embedded in the blinking vortex system.

PubMed

Kin, Eiko; Sakajo, Takashi

2005-06-01

We consider the particle mixing in the plane by two vortex points appearing one after the other, called the blinking vortex system. Mathematical and numerical studies of the system reveal that the chaotic particle mixing, i.e., the chaotic advection, is observed due to the homoclinic chaos, but the mixing region is restricted locally in the neighborhood of the vortex points. The present article shows that it is possible to realize a global and efficient chaotic advection in the blinking vortex system with the help of the Thurston-Nielsen theory, which classifies periodic orbits for homeomorphisms in the plane into three types: periodic, reducible, and pseudo-Anosov (pA). It is mathematically shown that periodic orbits of pA type generate a complicated dynamics, which is called topological chaos. We show that the combination of the local chaotic mixing due to the topological chaos and the dipole-like return orbits realize an efficient and global particle mixing in the blinking vortex system.

Chaos control and synchronization in Bragg acousto-optic bistable systems driven by a separate chaotic system.

PubMed

Wang, Rong; Gao, Jin-Yue

2005-09-01

In this paper we propose a new scheme to achieve chaos control and synchronization in Bragg acousto-optic bistable systems. In the scheme, we use the output of one system to drive two identical chaotic systems. Using the maximal conditional Lyapunov exponent (MCLE) as the criterion, we analyze the conditions for realizing chaos synchronization. Numerical calculation shows that the two identical systems in chaos with negative MCLEs and driven by a chaotic system can go into chaotic synchronization whether or not they were in chaos initially. The two systems can go into different periodic states from chaos following an inverse period-doubling bifurcation route as well when driven by a periodic system.

Modeling Uncertainty in Steady State Diffusion Problems via Generalized Polynomial Chaos

DTIC Science & Technology

2002-07-25

Some basic hypergeometric polynomials that generalize Jacobi polynomials . Memoirs Amer. Math. Soc., AMS... orthogonal polynomial functionals from the Askey scheme, as a generalization of the original polynomial chaos idea of Wiener (1938). A Galerkin projection...1) by generalized polynomial chaos expansion, where the uncertainties can be introduced through κ, f , or g, or some combinations. It is worth

Anti-control of chaos of single time-scale brushless DC motor.

PubMed

Ge, Zheng-Ming; Chang, Ching-Ming; Chen, Yen-Sheng

2006-09-15

Anti-control of chaos of single time-scale brushless DC motors is studied in this paper. In order to analyse a variety of periodic and chaotic phenomena, we employ several numerical techniques such as phase portraits, bifurcation diagrams and Lyapunov exponents. Anti-control of chaos can be achieved by adding an external constant term or an external periodic term.

[CNN]-pincer nickel(II) complexes of N-heterocyclic carbene (NHC): synthesis and catalysis of the Kumada reaction of unactivated C-Cl bonds.

PubMed

Sun, Yunqiang; Li, Xiaoyan; Sun, Hongjian

2014-07-07

Three novel [CNN]-pincer nickel(ii) complexes with NHC-amine arms were synthesized in three steps. Complex was proven to be an efficient catalyst for the Kumada coupling of aryl chlorides or aryl dichlorides under mild conditions.

Aram Chaos: a Long Lived Subsurface Aqueous Environment with Strong Water Resources Potential for Human Missions on Mars

NASA Technical Reports Server (NTRS)

Sibille, L.; Mueller, R.; Niles, P. B.; Glotch, T.; Archer, P. D.; Bell, M. S.

2015-01-01

Aram Chaos, Mars is a crater 280 kilometers in diameter with elevations circa. minus 2 to minus 3 kilometers below datum that provides a compelling landing site for future human explorers as it features multiple scientific regions of interest (ROI) paired with a rich extensible Resource ROI that features poly-hydrated sulfates [1]. The geologic history of Aram Chaos suggests several past episodes of groundwater recharge and infilling by liquid water, ice, and other materials [1-3]. The creation of the fractured region with no known terrestrial equivalent may have been caused by melting of deep ice reservoirs that triggered the collapse of terrain followed by catastrophic water outflows over the region. Aram Chaos is of particular scientific interest because it is hypothesized that the chaotic terrain may be the source of water that contributed to the creation of nearby valleys such as Ares Vallis flowing toward Chryse Planitia. The liquid water was likely sourced as groundwater and therefore represents water derived from a protected subsurface environment making it a compelling astrobiological site [2]. The past history of water is also represented by high concentrations of hematite, Fe-oxyhydroxides, mono-hydrated and poly-hydrated sulfates [1, 2]. Poly-hydrated sulfates are likely to contain abundant water that evolves at temperatures below 500 degrees Centigrade thus conferring Aram Chaos a potentially high value for early in-situ resource utilization (ISRU) [4]. The geologic history also calls for future prospecting of deep ice deposits and possibly liquid water via deep drilling. The most recent stratigraphic units in the central part of Aram Chaos are not fractured, and are part of a dome-shaped formation that features bright, poorly-consolidated material that contains both hydrated sulfates and ferric oxides according to OMEGA (Observatoire pour la Minéralogie, l'Eau, les Glaces et l'Activité) data [5]. These surface material characteristics are

Transition to Chaos in Random Neuronal Networks

NASA Astrophysics Data System (ADS)

Kadmon, Jonathan; Sompolinsky, Haim

2015-10-01

Firing patterns in the central nervous system often exhibit strong temporal irregularity and considerable heterogeneity in time-averaged response properties. Previous studies suggested that these properties are the outcome of the intrinsic chaotic dynamics of the neural circuits. Indeed, simplified rate-based neuronal networks with synaptic connections drawn from Gaussian distribution and sigmoidal nonlinearity are known to exhibit chaotic dynamics when the synaptic gain (i.e., connection variance) is sufficiently large. In the limit of an infinitely large network, there is a sharp transition from a fixed point to chaos, as the synaptic gain reaches a critical value. Near the onset, chaotic fluctuations are slow, analogous to the ubiquitous, slow irregular fluctuations observed in the firing rates of many cortical circuits. However, the existence of a transition from a fixed point to chaos in neuronal circuit models with more realistic architectures and firing dynamics has not been established. In this work, we investigate rate-based dynamics of neuronal circuits composed of several subpopulations with randomly diluted connections. Nonzero connections are either positive for excitatory neurons or negative for inhibitory ones, while single neuron output is strictly positive with output rates rising as a power law above threshold, in line with known constraints in many biological systems. Using dynamic mean field theory, we find the phase diagram depicting the regimes of stable fixed-point, unstable-dynamic, and chaotic-rate fluctuations. We focus on the latter and characterize the properties of systems near this transition. We show that dilute excitatory-inhibitory architectures exhibit the same onset to chaos as the single population with Gaussian connectivity. In these architectures, the large mean excitatory and inhibitory inputs dynamically balance each other, amplifying the effect of the residual fluctuations. Importantly, the existence of a transition to chaos

Secure communications of CAP-4 and OOK signals over MMF based on electro-optic chaos.

PubMed

Ai, Jianzhou; Wang, Lulu; Wang, Jian

2017-09-15

Chaos-based secure communication can provide a high level of privacy in data transmission. Here, we experimentally demonstrate secure signal transmission over two kinds of multimode fiber (MMF) based on electro-optic intensity chaos. High-quality synchronization is achieved in an electro-optic feedback configuration. Both 5  Gbit/s carrier-less amplitude/phase (CAP-4) modulation and 10  Gbit/s on-off key (OOK) signals are recovered efficiently in electro-optic chaos-based communication systems. Degradations of chaos synchronization and communication system due to mismatch of various hardware keys are also discussed.

The Chaos Theory of Careers

ERIC Educational Resources Information Center

Bright, Jim E. H.; Pryor, Robert G. L.

2011-01-01

The Chaos Theory of Careers (CTC; Pryor & Bright, 2011) construes both individuals and the contexts in which they develop their careers in terms of complex dynamical systems. Such systems perpetually operate under influences of stability and change both internally and in relation to each other. The CTC introduces new concepts to account for…

Turbulence transition and the edge of chaos in pipe flow.

PubMed

Schneider, Tobias M; Eckhardt, Bruno; Yorke, James A

2007-07-20

The linear stability of pipe flow implies that only perturbations of sufficient strength will trigger the transition to turbulence. In order to determine this threshold in perturbation amplitude we study the edge of chaos which separates perturbations that decay towards the laminar profile and perturbations that trigger turbulence. Using the lifetime as an indicator and methods developed in Skufca et al., Phys. Rev. Lett. 96, 174101 (2006), we show that superimposed on an overall 1/Re scaling predicted and studied previously there are small, nonmonotonic variations reflecting folds in the edge of chaos. By tracing the motion in the edge we find that it is formed by the stable manifold of a unique flow field that is dominated by a pair of downstream vortices, asymmetrically placed towards the wall. The flow field that generates the edge of chaos shows intrinsic chaotic dynamics.

Automated assessment of breast tissue density in non-contrast 3D CT images without image segmentation based on a deep CNN

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Kano, Takuya; Koyasu, Hiromi; Li, Shuo; Zhou, Xinxin; Hara, Takeshi; Matsuo, Masayuki; Fujita, Hiroshi

2017-03-01

This paper describes a novel approach for the automatic assessment of breast density in non-contrast three-dimensional computed tomography (3D CT) images. The proposed approach trains and uses a deep convolutional neural network (CNN) from scratch to classify breast tissue density directly from CT images without segmenting the anatomical structures, which creates a bottleneck in conventional approaches. Our scheme determines breast density in a 3D breast region by decomposing the 3D region into several radial 2D-sections from the nipple, and measuring the distribution of breast tissue densities on each 2D section from different orientations. The whole scheme is designed as a compact network without the need for post-processing and provides high robustness and computational efficiency in clinical settings. We applied this scheme to a dataset of 463 non-contrast CT scans obtained from 30- to 45-year-old-women in Japan. The density of breast tissue in each CT scan was assigned to one of four categories (glandular tissue within the breast <25%, 25%-50%, 50%-75%, and >75%) by a radiologist as ground truth. We used 405 CT scans for training a deep CNN and the remaining 58 CT scans for testing the performance. The experimental results demonstrated that the findings of the proposed approach and those of the radiologist were the same in 72% of the CT scans among the training samples and 76% among the testing samples. These results demonstrate the potential use of deep CNN for assessing breast tissue density in non-contrast 3D CT images.

Spreading Chaos: The Role of Popularizations in the Diffusion of Scientific Ideas

ERIC Educational Resources Information Center

Paul, Danette

2004-01-01

Scientific popularizations are generally considered translations (often dubious ones) of scientific research for a lay audience. This study explores the role popularizations play within scientific discourse, specifically in the development of chaos theory. The methods included a review of the popular and the semipopular books on chaos theory from…

Chaos as a psychological construct: historical roots, principal findings, and current growth directions.

PubMed

Guastello, Stephen J

2009-07-01

The landmarks in the use of chaos and related constructs in psychology were entwined with the growing use of other nonlinear dynamical constructs, especially catastrophes and self-organization. The growth in substantive applications of chaos in psychology is partially related to the development of methodologies that work within the constraints of psychological data. The psychological literature includes rigorous theory with testable propositions, lighter-weight metaphorical uses of the construct, and colloquial uses of "chaos" with no particular theoretical intent. The current state of the chaos construct and supporting empirical research in psychological theory is summarized in neuroscience, psychophysics, psychomotor skill and other learning phenomena, clinical and abnormal psychology, and group dynamics and organizational behavior. Trends indicate that human systems do not remain chaotic indefinitely; they eventually self-organize, and the concept of the complex adaptive system has become prominent. Chaotic turbulence is generally higher in healthy systems compared to unhealthy systems, although opposite appears true in mood disorders. Group dynamics research shows trends consistent with the complex adaptive system, whereas organizational behavior lags behind in empirical studies relative to the quantity of its theory. Future directions for research involving the chaos construct and other nonlinear dynamics are outlined.

Hydaspis Chaos in Nighttime Infrared

NASA Technical Reports Server (NTRS)

2002-01-01

This nighttime infrared image, taken by the thermal emission imaging system, captures a massively disrupted region on Mars called Hydaspis Chaos, which is located near the equator at two degrees north, 29 degrees west. The total vertical difference from the lowest to highest points in this region is about five kilometers (three miles.)

The steep slopes leading down into the canyon of Hydaspsis Chaos are strewn with rocks, while the plateaus and mesas above are covered in dust. This pattern indicates that processes are at work to prevent the dust from completely covering the surface of these slopes, even over the very long period since these canyons were formed.

The slopes and floor of these canyons show remarkable variability in the distribution of rocks and fine-grained material. Chaotic terrain may have been formed when subsurface ground water or ice was removed, and the overlying ground collapsed. The release of this water or ice (or both)formed the outflow channel Tiu Valles, which flowed across the Mars Pathfinder landing site.

This image captures a region of chaotic terrain about 106 kilometers (65 miles) long and 32 kilometers (20 miles) wide. The channel that feeds into the chaos at the bottom of the image is about 7 kilometers (4.3 miles)wide and 280 meters (930 feet) deep. The image was acquired on February 19, 2002. North is to the right of the image.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The thermal emission imaging system was provided by Arizona State University, Tempe. Lockheed Martin Astronautics, Denver, is the prime contractor for the project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Chaos minimization in DC-DC boost converter using circuit parameter optimization

NASA Astrophysics Data System (ADS)

Sudhakar, N.; Natarajan, Rajasekar; Gourav, Kumar; Padmavathi, P.

2017-11-01

DC-DC converters are prone to several types of nonlinear phenomena including bifurcation, quasi periodicity, intermittency and chaos. These undesirable effects must be controlled for periodic operation of the converter to ensure the stability. In this paper an effective solution to control of chaos in solar fed DC-DC boost converter is proposed. Controlling of chaos is significantly achieved using optimal circuit parameters obtained through Bacterial Foraging Optimization Algorithm. The optimization renders the suitable parameters in minimum computational time. The obtained results are compared with the operation of traditional boost converter. Further the obtained results with BFA optimized parameter ensures the operations of the converter are within the controllable region. To elaborate the study of bifurcation analysis with optimized and unoptimized parameters are also presented.

Chaos enhancing tunneling in a coupled Bose-Einstein condensate with a double driving.

PubMed

Rong, Shiguang; Hai, Wenhua; Xie, Qiongtao; Zhu, Qianquan

2009-09-01

We study the effects of chaotic dynamics on atomic tunneling between two weakly coupled Bose-Einstein condensates driven by a double-frequency periodic field. Under the Melnikov's chaos criterion, we divide the parameter space into three parts of different types, regular region, low-chaoticity region, and high-chaoticity region, and give the accurate boundaries between the different regions. It is found that the atomic tunneling can be enhanced in the presence of chaos. Particularly, in the high-chaoticity regions, the chaos-induced inversion of the population imbalance is observed numerically.

Routes to spatiotemporal chaos in Kerr optical frequency combs.

PubMed

Coillet, Aurélien; Chembo, Yanne K

2014-03-01

We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato-Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

Time-delay signature of chaos in 1550 nm VCSELs with variable-polarization FBG feedback.

PubMed

Li, Yan; Wu, Zheng-Mao; Zhong, Zhu-Qiang; Yang, Xian-Jie; Mao, Song; Xia, Guang-Qiong

2014-08-11

Based on the framework of spin-flip model (SFM), the output characteristics of a 1550 nm vertical-cavity surface-emitting laser (VCSEL) subject to variable-polarization fiber Bragg grating (FBG) feedback (VPFBGF) have been investigated. With the aid of the self-correlation function (SF) and the permutation entropy (PE) function, the time-delay signature (TDS) of chaos in the VPFBGF-VCSEL is evaluated, and then the influences of the operation parameters on the TDS of chaos are analyzed. The results show that the TDS of chaos can be suppressed efficiently through selecting suitable coupling coefficient and feedback rate of the FBG, and is weaker than that of chaos generated by traditional variable-polarization mirror feedback VCSELs (VPMF-VCSELs) or polarization-preserved FBG feedback VCSELs (PPFBGF-VCSELs).

Applied Chaos Level Test for Validation of Signal Conditions Underlying Optimal Performance of Voice Classification Methods

ERIC Educational Resources Information Center

Liu, Boquan; Polce, Evan; Sprott, Julien C.; Jiang, Jack J.

2018-01-01

Purpose: The purpose of this study is to introduce a chaos level test to evaluate linear and nonlinear voice type classification method performances under varying signal chaos conditions without subjective impression. Study Design: Voice signals were constructed with differing degrees of noise to model signal chaos. Within each noise power, 100…

Learning the Uses of Chaos.

ERIC Educational Resources Information Center

Berthoff, Ann E.

This paper addresses the issue of learning to write and the need for defining a means of teaching the process of composing. Following a description of what kind of process writing is not, the composing process is presented as a continuum of making meaning out of a chaos of images, half-truths, remembrances, and syntactic fragments. The discovery…

Aureum Chaos

NASA Technical Reports Server (NTRS)

2003-01-01

[figure removed for brevity, see original site]

Released 11 November 2003

Aureum Chaos is a large crater that was filled with sediment after its formation. After the infilling of sediment, something occurred that caused the sediment to be broken up into large, slumped blocks and smaller knobs. Currently, it is believed that the blocks and knobs form when material is removed from the subsurface, creating void space. Subsurface ice was probably heated, and the water burst out to the surface, maybe forming a temporary lake. Other areas of chaos terrain have large outflow channels that emanate from them, indicating that a tremendous amount of water was released.

Image information: VIS instrument. Latitude -3.2, Longitude 331 East (29 West). 19 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Family CHAOS is associated with glycaemic control in children and adolescents with type 1 diabetes mellitus.

PubMed

Chae, M; Taylor, B J; Lawrence, J; Healey, D; Reith, D M; Gray, A; Wheeler, B J

2016-02-01

Despite advances in the medical management of type 1 diabetes mellitus (T1DM), for many, glycaemic control remains substandard. Other factors are clearly important in determining success, or lack thereof, with diabetes management. With this in mind, we have investigated whether family CHAOS may provide a novel tool to identify when environmental confusion could impact on diabetes management and subsequent glycaemic control. A case-control study of children and adolescents with established T1DM and age-/sex-matched controls was conducted. Demographic information, both maternal and paternal CHAOS scores, and HbA1c were collected. Statistical analysis was undertaken to explore associations between T1DM and CHAOS and between CHAOS and HbA1c. Data on 65 children with T1DM and 60 age-/sex-matched controls were obtained. There was no evidence of group differences for maternal CHAOS (p = 0.227), but paternal CHAOS scores were higher for the T1DM group (p = 0.041). Greater maternal and paternal CHAOS scores were both associated with higher HbA1c (p ≤ 0.027). The maternal association remained after controlling for diabetes duration, SMBG frequency, and insulin therapy. In children with T1DM, there appears to be a negative association between increased environmental confusion, as rated by CHAOS, and glycaemic control. In addition, when compared to controls, fathers of children and adolescents with T1DM appear to experience CHAOS differently to mothers. These findings contribute to the growing body of literature exploring psychosocial factors in T1DM. Continuing efforts are required to fully understand how the family and psychosocial environment interact with diabetes to impact on long-term health outcomes.

Interactions between neural networks: a mechanism for tuning chaos and oscillations

PubMed Central

2007-01-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability. PMID:19003511

Interactions between neural networks: a mechanism for tuning chaos and oscillations.

PubMed

Wang, Lipo

2007-06-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.

Western Eos Chaos on Mars: A Potential Site for Future Landing and Returning Samples

NASA Astrophysics Data System (ADS)

Asif Iqbal Kakkassery; Rajesh, V. J.

2018-04-01

Introducing Eos Chaos as a potential area for collecting samples. Eos Chaos contains a number of aqueous minerals. We have detected zoisite — a least reported low-grade metamorphic mineral from this area.

Low-temperature physics: Chaos in the cold

NASA Astrophysics Data System (ADS)

Julienne, Paul S.

2014-03-01

A marriage between theory and experiment has shown that ultracold erbium atoms trapped with laser light and subjected to a magnetic field undergo collisions that are characterized by quantum chaos. See Letter p.475

Anisoplanatic image propagation along a slanted path under lower atmosphere phase turbulence in the presence of encrypted chaos

NASA Astrophysics Data System (ADS)

Chatterjee, Monish R.; Mohamed, Ali A.

2017-05-01

In recent research, anisoplanatic electromagnetic (EM) wave propagation along a slanted path in the presence of low atmosphere phase turbulence (modified von Karman spectrum or MVKS) has been investigated assuming a Hufnagel-Valley (HV) type structure parameter. Preliminary results indicate a strong dependence on the slant angle especially for long range transmission and relatively strong turbulence. The investigation was further divided into two regimes, viz. (a) one where the EM source consisted of a plane wave modulated with a digitized image, which is propagated along the turbulent path and recovered via demodulation at the receiver; and (b) transmit the plane wave without modulation along the turbulent path through an image transparency and a thin lens designed to gather the received image in the focal plane. In this paper, we reexamine the same problem (part (a) only) in the presence of a chaotic optical carrier where the chaos is generated in the feedback loop of an acousto-optic Bragg cell. The image information is encrypted within the chaos wave, and subsequently propagated along a similar slant path and identical turbulence conditions. The recovered image extracted via heterodyning from the received chaos is compared quantitatively (through image cross-correlations and mean-squared error measures) for the non-chaotic versus the chaotic approaches. Generally, "packaging" the information in chaos improves performance through turbulent propagation, and results are discussed from this perspective. Concurrently, we will also examine the effect of a non-encrypted plane EM wave propagation through a transparency-lens combination. These results are also presented with appropriate comparisons with the cases involving lensless transmission of imagery through corresponding turbulent and non-turbulent layers.

Gastric precancerous diseases classification using CNN with a concise model.

PubMed

Zhang, Xu; Hu, Weiling; Chen, Fei; Liu, Jiquan; Yang, Yuanhang; Wang, Liangjing; Duan, Huilong; Si, Jianmin

2017-01-01

Gastric precancerous diseases (GPD) may deteriorate into early gastric cancer if misdiagnosed, so it is important to help doctors recognize GPD accurately and quickly. In this paper, we realize the classification of 3-class GPD, namely, polyp, erosion, and ulcer using convolutional neural networks (CNN) with a concise model called the Gastric Precancerous Disease Network (GPDNet). GPDNet introduces fire modules from SqueezeNet to reduce the model size and parameters about 10 times while improving speed for quick classification. To maintain classification accuracy with fewer parameters, we propose an innovative method called iterative reinforced learning (IRL). After training GPDNet from scratch, we apply IRL to fine-tune the parameters whose values are close to 0, and then we take the modified model as a pretrained model for the next training. The result shows that IRL can improve the accuracy about 9% after 6 iterations. The final classification accuracy of our GPDNet was 88.90%, which is promising for clinical GPD recognition.

Non Linear Dynamics and Chaos (La Dynamique Non-Lineaie et le Chaos)

DTIC Science & Technology

1993-06-01

mention some aspects of non-linear dynamics and/or disorder is independence. All other definitions are merely negative chaos which p,.Laps a,, margin- al ...collection of fixed coefficients and input-output corellation is U1, pp. 1037-1044, 1990, Roger Cerf et al . Among ,ie very slightly modified. If Rl is...des param~tres qui ou la deformation 61astique d’une partie du sol d~finissent le syst~me A contr~ler, et donne lieu, soudainement A un saut

Geology and Origin of Europa's Mitten Feature (Murias Chaos)

NASA Technical Reports Server (NTRS)

Figueredo, P. H.; Chuang, F. C.; Rathbun, J.; Kirk, R. L.; Greeley, R.

2002-01-01

The "Mitten" (provisionally named Murias Chaos by the International Astronomical Union) is a region of elevated chaos-like terrain in the leading hemisphere of Europa. Its origin had been explained under the currently debated theories of melting through a thin lithosphere or convection within a thick one. Galileo observations reveal several characteristics that suggest that the Mitten is distinct from typical chaos terrain and point to a different formational process. Photoclinometric elevation estimates suggest that the Mitten is slightly elevated with respect to the surrounding terrain; geologic relations indicate that it must have raised significantly from the plains in its past, resembling disrupted domes on Europa's trailing hemisphere. Moreover, the Mitten material appears to have extruded onto the plains and flowed for tens of kilometers. The area subsequently subsided as a result of isostatic adjustment, viscous relaxation, and/or plains loading. Using plate flexure models, we estimated the elastic lithosphere in the area to be several kilometers thick. We propose that the Mitten originated by the ascent and extrusion of a large thermal diapir. Thermal-mechanical modeling shows that a Mitten-sized plume would remain sufficiently warm and buoyant to pierce through the crust and flow unconfined on the surface. Such a diapir probably had an initial radius between 5 and 8 km and an initial depth of 20-40 km, consistent with a thick-lithosphere model. In this scenario the Mitten appears to represent the surface expression of the rare ascent of a large diapir, in contrast to lenticulae and chaos terrain, which may form by isolated and clustered small diapirs, respectively.

Geology and origin of Europa's "Mitten" feature (Murias Chaos)

USGS Publications Warehouse

Figueredo, P.H.; Chuang, F.C.; Rathbun, J.; Kirk, R.L.; Greeley, R.

2002-01-01

The "Mitten" (provisionally named Murias Chaos by the International Astronomical Union) is a region of elevated chaos-like terrain in the leading hemisphere of Europa. Its origin had been explained under the currently debated theories of melting through a thin lithosphere or convection within a thick one. Galileo observations reveal several characteristics that suggest that the Mitten is distinct from typical chaos terrain and point to a different formational process. Photoclinometric elevation estimates suggest that the Mitten is slightly elevated with respect to the surrounding terrain; geologic relations indicate that it must have raised significantly from the plains in its past, resembling disrupted domes on Europa's trailing hemisphere. Moreover, the Mitten material appears to have extruded onto the plains and flowed for tens of kilometers. The area subsequently subsided as a result of isostatic adjustment, viscous relaxation, and/or plains loading. Using plate flexure models, we estimated the elastic lithosphere in the area to be several kilometers thick. We propose that the Mitten originated by the ascent and extrusion of a large thermal diapir. Thermal-mechanical modeling shows that a Mitten-sized plume would remain sufficiently warm and buoyant to pierce through the crust and flow unconfined on the surface. Such a diapir probably had an initial radius between 5 and 8 km and an initial depth of 20-40 km, consistent with a thick-lithosphere model. In this scenario the Mitten appears to represent the surface expression of the rare ascent of a large diapir, in contrast to lenticulae and chaos terrain, which may form by isolated and clustered small diapirs, respectively.

Tuning quantum measurements to control chaos.

PubMed

Eastman, Jessica K; Hope, Joseph J; Carvalho, André R R

2017-03-20

Environment-induced decoherence has long been recognised as being of crucial importance in the study of chaos in quantum systems. In particular, the exact form and strength of the system-environment interaction play a major role in the quantum-to-classical transition of chaotic systems. In this work we focus on the effect of varying monitoring strategies, i.e. for a given decoherence model and a fixed environmental coupling, there is still freedom on how to monitor a quantum system. We show here that there is a region between the deep quantum regime and the classical limit where the choice of the monitoring parameter allows one to control the complex behaviour of the system, leading to either the emergence or suppression of chaos. Our work shows that this is a result from the interplay between quantum interference effects induced by the nonlinear dynamics and the effectiveness of the decoherence for different measurement schemes.

Chaos synchronization in vertical-cavity surface-emitting laser based on rotated polarization-preserved optical feedback.

PubMed

Nazhan, Salam; Ghassemlooy, Zabih; Busawon, Krishna

2016-01-01

In this paper, the influence of the rotating polarization-preserved optical feedback on the chaos synchronization of a vertical-cavity surface-emitting laser (VCSEL) is investigated experimentally. Two VCSELs' polarization modes (XP) and (YP) are gradually rotated and re-injected back into the VCSEL. The anti-phase dynamics synchronization of the two polarization modes is evaluated using the cross-correlation function. For a fixed optical feedback, a clear relationship is found between the cross-correlation coefficient and the polarization angle θp. It is shown that high-quality anti-phase polarization-resolved chaos synchronization is achieved at higher values of θp. The maximum value of the cross-correlation coefficient achieved is -0.99 with a zero time delay over a wide range of θp beyond 65° with a poor synchronization dynamic at θp less than 65°. Furthermore, it is observed that the antiphase irregular oscillation of the XP and YP modes changes with θp. VCSEL under the rotating polarization optical feedback can be a good candidate as a chaotic synchronization source for a secure communication system.

Chaos M-ary modulation and demodulation method based on Hamilton oscillator and its application in communication.

PubMed

Fu, Yongqing; Li, Xingyuan; Li, Yanan; Yang, Wei; Song, Hailiang

2013-03-01

Chaotic communication has aroused general interests in recent years, but its communication effect is not ideal with the restriction of chaos synchronization. In this paper a new chaos M-ary digital modulation and demodulation method is proposed. By using region controllable characteristics of spatiotemporal chaos Hamilton map in phase plane and chaos unique characteristic, which is sensitive to initial value, zone mapping method is proposed. It establishes the map relationship between M-ary digital information and the region of Hamilton map phase plane, thus the M-ary information chaos modulation is realized. In addition, zone partition demodulation method is proposed based on the structure characteristic of Hamilton modulated information, which separates M-ary information from phase trajectory of chaotic Hamilton map, and the theory analysis of zone partition demodulator's boundary range is given. Finally, the communication system based on the two methods is constructed on the personal computer. The simulation shows that in high speed transmission communications and with no chaos synchronization circumstance, the proposed chaotic M-ary modulation and demodulation method has outperformed some conventional M-ary modulation methods, such as quadrature phase shift keying and M-ary pulse amplitude modulation in bit error rate. Besides, it has performance improvement in bandwidth efficiency, transmission efficiency and anti-noise performance, and the system complexity is low and chaos signal is easy to generate.

Viewing Eye Movements During Reading through the Lens of Chaos Theory: How Reading Is Like the Weather

ERIC Educational Resources Information Center

Paulson, Eric J.

2005-01-01

This theoretical article examines reading processes using chaos theory as an analogy. Three principles of chaos theory are identified and discussed, then related to reading processes as revealed through eye movement research. Used as an analogy, the chaos theory principle of sensitive dependence contributes to understanding the difficulty in…

Stochastic resonance based on modulation instability in spatiotemporal chaos.

PubMed

Han, Jing; Liu, Hongjun; Huang, Nan; Wang, Zhaolu

2017-04-03

A novel dynamic of stochastic resonance in spatiotemporal chaos is presented, which is based on modulation instability of perturbed partially coherent wave. The noise immunity of chaos can be reinforced through this effect and used to restore the coherent signal information buried in chaotic perturbation. A theoretical model with fluctuations term is derived from the complex Ginzburg-Landau equation via Wigner transform. It shows that through weakening the nonlinear threshold and triggering energy redistribution, the coherent component dominates the instability damped by incoherent component. The spatiotemporal output showing the properties of stochastic resonance may provide a potential application of signal encryption and restoration.

Generalized chaos synchronization theorems for bidirectional differential equations and discrete systems with applications

NASA Astrophysics Data System (ADS)

Ji, Ye; Liu, Ting; Min, Lequan

2008-05-01

Two constructive generalized chaos synchronization (GCS) theorems for bidirectional differential equations and discrete systems are introduced. Using the two theorems, one can construct new chaos systems to make the system variables be in GCS. Five examples are presented to illustrate the effectiveness of the theoretical results.

A discrete-time chaos synchronization system for electronic locking devices

NASA Astrophysics Data System (ADS)

Minero-Ramales, G.; López-Mancilla, D.; Castañeda, Carlos E.; Huerta Cuellar, G.; Chiu Z., R.; Hugo García López, J.; Jaimes Reátegui, R.; Villafaña Rauda, E.; Posadas-Castillo, C.

2016-11-01

This paper presents a novel electronic locking key based on discrete-time chaos synchronization. Two Chen chaos generators are synchronized using the Model-Matching Approach, from non-linear control theory, in order to perform the encryption/decryption of the signal to be transmitted. A model/transmitter system is designed, generating a key of chaotic pulses in discrete-time. A plant/receiver system uses the above mentioned key to unlock the mechanism. Two alternative schemes to transmit the private chaotic key are proposed. The first one utilizes two transmission channels. One channel is used to encrypt the chaotic key and the other is used to achieve output synchronization. The second alternative uses only one transmission channel for obtaining synchronization and encryption of the chaotic key. In both cases, the private chaotic key is encrypted again with chaos to solve secure communication-related problems. The results obtained via simulations contribute to enhance the electronic locking devices.

Dermoscopic 'Chaos and Clues' in the diagnosis of melanoma in situ.

PubMed

Ramji, Rajan; Valdes-Gonzalez, Guillermo; Oakley, Amanda; Rademaker, Marius

2017-11-02

To describe the dermoscopic features of melanoma in situ using the Chaos and Clues method. Histologically proven primary melanoma in situ (MIS) diagnosed through a specialist teledermoscopy clinic were reviewed by three dermatologists. By consensus they agreed on the global dermoscopic pattern, colours, presence of chaos (asymmetry of colour and structure and more than one pattern), and each of the nine clues described for malignancy. One hundred MIS in 92 patients of European ethnicity (45 males) were assessed. Mean age was 67.3 years (range 20-95). The mean dimensions of the lesions were 11.1 × 12.0 mm (range 2.5-31.3 × 2.3-32.3 mm). Using pattern analysis, 82% of the lesions had three or more patterns (multicomponent) and the rest had 2 patterns. Colours included light brown (100%), dark brown (98%) and grey (75%). All MIS demonstrated chaos. The most prevalent clues were thick lines (88%), eccentric structureless areas (88%), and grey or blue structures (75%). Dermoscopy can be very helpful in the early diagnosis of melanoma and MIS. The Chaos and Clues method is simple to use. Its unambiguous descriptors can be successfully used to describe MIS. The presence of chaos and clues to malignancy (including thick lines, eccentric structureless areas, and blue/grey structures) should raise a red flag and lead to referral or excision. © 2017 The Australasian College of Dermatologists.

The Simple Map for Single-null Divertor Tokamak : How to Find Chaos

NASA Astrophysics Data System (ADS)

Martinez, Ilissa; Ali, Halima; Punjabi, Alkesh

2000-10-01

The Simple Map^1 represents the magnetic field inside a single-null divertor tokamak. The Simple map is given by the equations X_n+1=X_n-KYn (1-Y_n) and Y_n+1=Y_n+KX_n+1. We fix k at 0.6 and X0 at 0. We choose two different starting values of Y_0. These two values are very close together. These values of Y0 represent two field lines which start out very close together. We calculate the distance between two field lines as n is increased. This distance is given by d_n. For both equations given by the distance formula (d_n=[Y_n,2-Y_n,1)^2+(X_n,2-X_n,1)^2]. If dn increases exponentially as n is increased we find chaos, if dn does not increase exponentially then you have not found chaos. We have found chaos, Y0 must be less than one, but higher than 0.9971 for chaos. For Y0 between 0 and 0.9971, there is no chaos. This work is supported by US DOE OFES. Ms. Ilissa Martinez is a HU CFRT Summer Fusion High School Workshop Scholar from the Blanca Malaret High School in Puerto Rico. She is supported by NASA SHARP Plus Program. 1. Punjabi A, Verma A and Booze A, Phys Rev Lett 69 3322 (1992) and J Plasma Phys 52 91 (1994)

Probability Simulations by Non-Lipschitz Chaos

NASA Technical Reports Server (NTRS)

Zak, Michail

1996-01-01

It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-Lipschitz dynamics, without utilization of any man-made devices. Self-organizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed.