series features activities: Topics by WorldWideScience.org

Sample records for series features activities

Effective Feature Preprocessing for Time Series Forecasting

DEFF Research Database (Denmark)

Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

2006-01-01

Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....
Grammar-based feature generation for time-series prediction

CERN Document Server

De Silva, Anthony Mihirana

2015-01-01

This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method ...
A window-based time series feature extraction method.

Science.gov (United States)

Katircioglu-Öztürk, Deniz; Güvenir, H Altay; Ravens, Ursula; Baykal, Nazife

2017-10-01

This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.
Facial Feature Extraction Using Frequency Map Series in PCNN

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Rencan Nie

2016-01-01

Full Text Available Pulse coupled neural network (PCNN has been widely used in image processing. The 3D binary map series (BMS generated by PCNN effectively describes image feature information such as edges and regional distribution, so BMS can be treated as the basis of extracting 1D oscillation time series (OTS for an image. However, the traditional methods using BMS did not consider the correlation of the binary sequence in BMS and the space structure for every map. By further processing for BMS, a novel facial feature extraction method is proposed. Firstly, consider the correlation among maps in BMS; a method is put forward to transform BMS into frequency map series (FMS, and the method lessens the influence of noncontinuous feature regions in binary images on OTS-BMS. Then, by computing the 2D entropy for every map in FMS, the 3D FMS is transformed into 1D OTS (OTS-FMS, which has good geometry invariance for the facial image, and contains the space structure information of the image. Finally, by analyzing the OTS-FMS, the standard Euclidean distance is used to measure the distances for OTS-FMS. Experimental results verify the effectiveness of OTS-FMS in facial recognition, and it shows better recognition performance than other feature extraction methods.
A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.

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Marken, John P; Halleran, Andrew D; Rahman, Atiqur; Odorizzi, Laura; LeFew, Michael C; Golino, Caroline A; Kemper, Peter; Saha, Margaret S

2016-01-01

Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches) which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.
A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.

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John P Marken

Full Text Available Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.
hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction.

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Fulcher, Ben D; Jones, Nick S

2017-11-22

Phenotype measurements frequently take the form of time series, but we currently lack a systematic method for relating these complex data streams to scientifically meaningful outcomes, such as relating the movement dynamics of organisms to their genotype or measurements of brain dynamics of a patient to their disease diagnosis. Previous work addressed this problem by comparing implementations of thousands of diverse scientific time-series analysis methods in an approach termed highly comparative time-series analysis. Here, we introduce hctsa, a software tool for applying this methodological approach to data. hctsa includes an architecture for computing over 7,700 time-series features and a suite of analysis and visualization algorithms to automatically select useful and interpretable time-series features for a given application. Using exemplar applications to high-throughput phenotyping experiments, we show how hctsa allows researchers to leverage decades of time-series research to quantify and understand informative structure in time-series data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Automated Feature Design for Time Series Classification by Genetic Programming

OpenAIRE

Harvey, Dustin Yewell

2014-01-01

Time series classification (TSC) methods discover and exploit patterns in time series and other one-dimensional signals. Although many accurate, robust classifiers exist for multivariate feature sets, general approaches are needed to extend machine learning techniques to make use of signal inputs. Numerous applications of TSC can be found in structural engineering, especially in the areas of structural health monitoring and non-destructive evaluation. Additionally, the fields of process contr...
Training Classifiers with Shadow Features for Sensor-Based Human Activity Recognition.

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Fong, Simon; Song, Wei; Cho, Kyungeun; Wong, Raymond; Wong, Kelvin K L

2017-02-27

In this paper, a novel training/testing process for building/using a classification model based on human activity recognition (HAR) is proposed. Traditionally, HAR has been accomplished by a classifier that learns the activities of a person by training with skeletal data obtained from a motion sensor, such as Microsoft Kinect. These skeletal data are the spatial coordinates (x, y, z) of different parts of the human body. The numeric information forms time series, temporal records of movement sequences that can be used for training a classifier. In addition to the spatial features that describe current positions in the skeletal data, new features called 'shadow features' are used to improve the supervised learning efficacy of the classifier. Shadow features are inferred from the dynamics of body movements, and thereby modelling the underlying momentum of the performed activities. They provide extra dimensions of information for characterising activities in the classification process, and thereby significantly improve the classification accuracy. Two cases of HAR are tested using a classification model trained with shadow features: one is by using wearable sensor and the other is by a Kinect-based remote sensor. Our experiments can demonstrate the advantages of the new method, which will have an impact on human activity detection research.
Training Classifiers with Shadow Features for Sensor-Based Human Activity Recognition

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Simon Fong

2017-02-01

Full Text Available In this paper, a novel training/testing process for building/using a classification model based on human activity recognition (HAR is proposed. Traditionally, HAR has been accomplished by a classifier that learns the activities of a person by training with skeletal data obtained from a motion sensor, such as Microsoft Kinect. These skeletal data are the spatial coordinates (x, y, z of different parts of the human body. The numeric information forms time series, temporal records of movement sequences that can be used for training a classifier. In addition to the spatial features that describe current positions in the skeletal data, new features called ‘shadow features’ are used to improve the supervised learning efficacy of the classifier. Shadow features are inferred from the dynamics of body movements, and thereby modelling the underlying momentum of the performed activities. They provide extra dimensions of information for characterising activities in the classification process, and thereby significantly improve the classification accuracy. Two cases of HAR are tested using a classification model trained with shadow features: one is by using wearable sensor and the other is by a Kinect-based remote sensor. Our experiments can demonstrate the advantages of the new method, which will have an impact on human activity detection research.
Relating interesting quantitative time series patterns with text events and text features

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Wanner, Franz; Schreck, Tobias; Jentner, Wolfgang; Sharalieva, Lyubka; Keim, Daniel A.

2013-12-01

In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data analysis tools need to support an integrated analysis, which allows studying the relationships between textual news documents and quantitative properties of the stock market price series. In this paper, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which reflect quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a-priori method. First, based on heuristics we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a-priori method supports the discovery of such sequential temporal patterns. Then, various text features like the degree of sentence nesting, noun phrase complexity, the vocabulary richness, etc. are extracted from the news to obtain meta patterns. Meta patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time-, cluster- and sequence visualization and analysis functionality. We provide two case studies, showing the effectiveness of our combined quantitative and textual analysis work flow. The workflow can also be generalized to other
Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition.

Science.gov (United States)

Munoz-Organero, Mario; Ruiz-Blazquez, Ramona

2017-02-08

Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates ( F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware.
Hidden discriminative features extraction for supervised high-order time series modeling.

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Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee

2016-11-01

In this paper, an orthogonal Tucker-decomposition-based extraction of high-order discriminative subspaces from a tensor-based time series data structure is presented, named as Tensor Discriminative Feature Extraction (TDFE). TDFE relies on the employment of category information for the maximization of the between-class scatter and the minimization of the within-class scatter to extract optimal hidden discriminative feature subspaces that are simultaneously spanned by every modality for supervised tensor modeling. In this context, the proposed tensor-decomposition method provides the following benefits: i) reduces dimensionality while robustly mining the underlying discriminative features, ii) results in effective interpretable features that lead to an improved classification and visualization, and iii) reduces the processing time during the training stage and the filtering of the projection by solving the generalized eigenvalue issue at each alternation step. Two real third-order tensor-structures of time series datasets (an epilepsy electroencephalogram (EEG) that is modeled as channel×frequency bin×time frame and a microarray data that is modeled as gene×sample×time) were used for the evaluation of the TDFE. The experiment results corroborate the advantages of the proposed method with averages of 98.26% and 89.63% for the classification accuracies of the epilepsy dataset and the microarray dataset, respectively. These performance averages represent an improvement on those of the matrix-based algorithms and recent tensor-based, discriminant-decomposition approaches; this is especially the case considering the small number of samples that are used in practice. Copyright © 2016 Elsevier Ltd. All rights reserved.
Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition

Directory of Open Access Journals (Sweden)

Mario Munoz-Organero

2017-02-01

Full Text Available Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data. The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users, the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates (F = 0.77 even in the case of using different people executing a different sequence of movements and using different
Current features of primary tuberculosis on medical imaging based on a series of fourteen cases

International Nuclear Information System (INIS)

Ouzidane, L.; Adamsbaum, C.; Cohen, P.A.; Kalifa, G.; Gendrel, D.

1995-01-01

Active pulmonary tuberculosis, a source of contamination, is currently undergoing a recrudescence in developed countries, particularly in clinical contexts of immuno-depression. The authors report a retrospective series of 14 cases of primary tuberculosis in a paediatric population (7 girls and 7 boys) with a mean age of 3.5 years (range: 4 months - 16 years) observed over a 3-year period. After reviewing the current radiological features of patent primary tuberculosis, the authors emphasize the contribution of chest CT scan in latent forms with a normal chest x-ray and a difficult bacteriological diagnosis. Imaging remains an essential tool in early diagnosis, therapeutic management and active surveillance of this form. The authors propose a decisional flow-chart in the case of suspected primary tuberculosis in children. (authors). 20 refs., 8 figs
A Two-Dimensional Solar Tracking Stationary Guidance Method Based on Feature-Based Time Series

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Keke Zhang

2018-01-01

Full Text Available The amount of satellite energy acquired has a direct impact on operational capacities of the satellite. As for practical high functional density microsatellites, solar tracking guidance design of solar panels plays an extremely important role. Targeted at stationary tracking problems incurred in a new system that utilizes panels mounted in the two-dimensional turntable to acquire energies to the greatest extent, a two-dimensional solar tracking stationary guidance method based on feature-based time series was proposed under the constraint of limited satellite attitude coupling control capability. By analyzing solar vector variation characteristics within an orbit period and solar vector changes within the whole life cycle, such a method could be adopted to establish a two-dimensional solar tracking guidance model based on the feature-based time series to realize automatic switching of feature-based time series and stationary guidance under the circumstance of different β angles and the maximum angular velocity control, which was applicable to near-earth orbits of all orbital inclination. It was employed to design a two-dimensional solar tracking stationary guidance system, and a mathematical simulation for guidance performance was carried out in diverse conditions under the background of in-orbit application. The simulation results show that the solar tracking accuracy of two-dimensional stationary guidance reaches 10∘ and below under the integrated constraints, which meet engineering application requirements.
Key structural features of nonsteroidal ligands for binding and activation of the androgen receptor.

Science.gov (United States)

Yin, Donghua; He, Yali; Perera, Minoli A; Hong, Seoung Soo; Marhefka, Craig; Stourman, Nina; Kirkovsky, Leonid; Miller, Duane D; Dalton, James T

2003-01-01

The purposes of the present studies were to examine the androgen receptor (AR) binding ability and in vitro functional activity of multiple series of nonsteroidal compounds derived from known antiandrogen pharmacophores and to investigate the structure-activity relationships (SARs) of these nonsteroidal compounds. The AR binding properties of sixty-five nonsteroidal compounds were assessed by a radioligand competitive binding assay with the use of cytosolic AR prepared from rat prostates. The AR agonist and antagonist activities of high-affinity ligands were determined by the ability of the ligand to regulate AR-mediated transcriptional activation in cultured CV-1 cells, using a cotransfection assay. Nonsteroidal compounds with diverse structural features demonstrated a wide range of binding affinity for the AR. Ten compounds, mainly from the bicalutamide-related series, showed a binding affinity superior to the structural pharmacophore from which they were derived. Several SARs regarding nonsteroidal AR binding were revealed from the binding data, including stereoisomeric conformation, steric effect, and electronic effect. The functional activity of high-affinity ligands ranged from antagonist to full agonist for the AR. Several structural features were found to be determinative of agonist and antagonist activities. The nonsteroidal AR agonists identified from the present studies provided a pool of candidates for further development of selective androgen receptor modulators (SARMs) for androgen therapy. Also, these studies uncovered or confirmed numerous important SARs governing AR binding and functional properties by nonsteroidal molecules, which would be valuable in the future structural optimization of SARMs.
Complex network approach to characterize the statistical features of the sunspot series

International Nuclear Information System (INIS)

Zou, Yong; Liu, Zonghua; Small, Michael; Kurths, Jürgen

2014-01-01

Complex network approaches have been recently developed as an alternative framework to study the statistical features of time-series data. We perform a visibility-graph analysis on both the daily and monthly sunspot series. Based on the data, we propose two ways to construct the network: one is from the original observable measurements and the other is from a negative-inverse-transformed series. The degree distribution of the derived networks for the strong maxima has clear non-Gaussian properties, while the degree distribution for minima is bimodal. The long-term variation of the cycles is reflected by hubs in the network that span relatively large time intervals. Based on standard network structural measures, we propose to characterize the long-term correlations by waiting times between two subsequent events. The persistence range of the solar cycles has been identified over 15–1000 days by a power-law regime with scaling exponent γ = 2.04 of the occurrence time of two subsequent strong minima. In contrast, a persistent trend is not present in the maximal numbers, although maxima do have significant deviations from an exponential form. Our results suggest some new insights for evaluating existing models. (paper)
Dihydropyridazinone cardiotonics: discovery of LY195115 and elucidation of structural features necessary for optimal inotropic activity

International Nuclear Information System (INIS)

Krushinski, J.H.; Hayes, J.S.; Beedle, E.E.; Pollock, G.D.; Wilson, H.; Robertson, D.W.

1986-01-01

A series of 4,5-dihydro-6-aryl-3( 2 H)-pyridazinones has been examined for inotropic activity. The optimal compound of the series, LY195115 (1,3-dihydro-3,3-dimethyl-5-(1,4,5,6-tetrahydro-6-oxo-3-pyridazinyl)- 2 H-indol-2-one), is one of the most potent and long-acting oral inotropes described to date. ED 50 's of LY195115, CI-914 and milrinone after i.v. administration to pentobarbital anesthetized dogs were 6.8, 46 and 37 μg/kg, respectively. ED 50 's after oral administration to conscious dogs were 25, 1000 and 500 μg/kg, respectively. For optimal positive inotropic activity and oral bioavailability in this series, the following structural features are necessary: (1) dihydropyridazinone ring with the nitrogen unsubstituted; (2) a hydrogen-bond acceptor substituent with a σ value of ca 0.0 para to the dihydropyridazinone moiety; and (3) additional sterically undemanding lipophilic substituents adjacent to the hydrogen-bond acceptor site
Human Activity Recognition as Time-Series Analysis

Directory of Open Access Journals (Sweden)

Hyesuk Kim

2015-01-01

Full Text Available We propose a system that can recognize daily human activities with a Kinect-style depth camera. Our system utilizes a set of view-invariant features and the hidden state conditional random field (HCRF model to recognize human activities from the 3D body pose stream provided by MS Kinect API or OpenNI. Many high-level daily activities can be regarded as having a hierarchical structure where multiple subactivities are performed sequentially or iteratively. In order to model effectively these high-level daily activities, we utilized a multiclass HCRF model, which is a kind of probabilistic graphical models. In addition, in order to get view-invariant, but more informative features, we extract joint angles from the subject’s skeleton model and then perform the feature transformation to obtain three different types of features regarding motion, structure, and hand positions. Through various experiments using two different datasets, KAD-30 and CAD-60, the high performance of our system is verified.

Dihydropyridazinone cardiotonics: discovery of LY195115 and elucidation of structural features necessary for optimal inotropic activity

Energy Technology Data Exchange (ETDEWEB)

Krushinski, J.H.; Hayes, J.S.; Beedle, E.E.; Pollock, G.D.; Wilson, H.; Robertson, D.W.

1986-03-05

A series of 4,5-dihydro-6-aryl-3(/sup 2/H)-pyridazinones has been examined for inotropic activity. The optimal compound of the series, LY195115 (1,3-dihydro-3,3-dimethyl-5-(1,4,5,6-tetrahydro-6-oxo-3-pyridazinyl)-/sup 2/H-indol-2-one), is one of the most potent and long-acting oral inotropes described to date. ED/sub 50/'s of LY195115, CI-914 and milrinone after i.v. administration to pentobarbital anesthetized dogs were 6.8, 46 and 37 ..mu..g/kg, respectively. ED/sub 50/'s after oral administration to conscious dogs were 25, 1000 and 500 ..mu..g/kg, respectively. For optimal positive inotropic activity and oral bioavailability in this series, the following structural features are necessary: (1) dihydropyridazinone ring with the nitrogen unsubstituted; (2) a hydrogen-bond acceptor substituent with a sigma value of ca 0.0 para to the dihydropyridazinone moiety; and (3) additional sterically undemanding lipophilic substituents adjacent to the hydrogen-bond acceptor site.
The Features of the Normative-Legal Provision of Socially Responsible Activity

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Pavlykivska Olha I.

2018-01-01

Full Text Available The article is aimed at researching the features of the normative-legal provision of socially responsible activity and providing recommendations for its improvement. As a result of the analysis of the world tendencies of standardization of socially responsible activity the scientific classification of standards has been suggested, which will allow to structure more effectively and use their information in the process of economic activity. The opinion is expressed that for a comprehensive assessment of socially responsible activity it is necessary to use several standards in combination, taking into consideration specifics of the activity of a particular enterprise. The most applied among them are: standards of social reporting series AA 1000, standard of social responsibility SA 8000, standard for reporting in the field of sustainable development GRI; Standard ISO 26000 «Guide to Social Responsibility». The author’s own definition of social responsibility has been formulated as an activity in which enterprise adheres to the principles of the social doing business, takes account first of all of the needs of stakeholders, has a positive impact on society, facilitates growth of reputation capital, reduces non-financial risks, which, as a result, contributes to maximizing profits for shareholders.
Extract the Relational Information of Static Features and Motion Features for Human Activities Recognition in Videos

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Li Yao

2016-01-01

Full Text Available Both static features and motion features have shown promising performance in human activities recognition task. However, the information included in these features is insufficient for complex human activities. In this paper, we propose extracting relational information of static features and motion features for human activities recognition. The videos are represented by a classical Bag-of-Word (BoW model which is useful in many works. To get a compact and discriminative codebook with small dimension, we employ the divisive algorithm based on KL-divergence to reconstruct the codebook. After that, to further capture strong relational information, we construct a bipartite graph to model the relationship between words of different feature set. Then we use a k-way partition to create a new codebook in which similar words are getting together. With this new codebook, videos can be represented by a new BoW vector with strong relational information. Moreover, we propose a method to compute new clusters from the divisive algorithm’s projective function. We test our work on the several datasets and obtain very promising results.
Performance analysis of power swing blocking feature in ABB 670 series impedance relays

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Maciej Łosiński

2012-12-01

Full Text Available This paper presents test results of a distance protection’s PSD power swing detection feature in ABB 670 series relays. A RED670 relay was tested, which is part of the hydroelectric set protection in Żarnowiec Pumped Storage Plant. The power swing blocking feature’s performance was analysed on the basis of the results of object tests made with an Omicron digital tester. Also presented are simulation results that illustrate the PSD feature’s response to power swings caused by a disturbance in the power system. It is also shown how a distance protection may react to the same fault, depending on its settings.
Series active power filter in power conditioning

Energy Technology Data Exchange (ETDEWEB)

Turunen, J.

2009-07-01

Power quality has become an important issue nowadays for several reasons, e.g. modern society's growing dependence on electricity and the fact that poor power quality may generate significant economic losses in few moments. Probable power quality problems are, e.g. harmonics, flicker, voltage dips and supply interruptions. The power quality may be improved by using filters and compensators.The purpose of this thesis is to research the operation of the series active power filter (SAPF) in power conditioning. Therefore, this thesis presents a comparison of three series hybrid active power filters (SHAPFs) in current harmonics filtering. In addition to this, it is shown how the voltage dip compensation performance of the SAPF is improved in a unified power quality conditioner (UPQC) application.The three SHAPFs included in the comparison are series connected topology (SCT), filter connected topology (FCT) and electrically tuned LC shunt circuit (ETLC). The operating principle of these filters is to direct the harmonic currents produced by the load to flow in the LC shunt circuits instead of the supply. In the case of the SCT this phenomenon is boosted by applying so-called active resistance in the supply branch using the SAPF. In the case of the FCT a similar action is achieved by applying the compensation voltage in series with the LC shunt circuits using the SAPF. In the case of the ETLC the performance of the LC shunt circuit is enhanced by applying so-called active inductances in series with the LC shunt circuit using the SAPF. The SHAPFs are compared by searching for their best current filtering performance using various main circuit and control system configurations and loads. The operation of the SHAPFs is first analysed mathematically. After this, the current filtering performance of the SHAPFs is inspected using simulations and experimental tests. The experimental tests are carried out using SHAPF prototypes. As a result, it is shown that the current
Recognizing brain motor imagery activities by identifying chaos properties of oxy-hemoglobin dynamics time series

International Nuclear Information System (INIS)

Khoa, Truong Quang Dang; Yuichi, Nakamura; Masahiro, Nakagawa

2009-01-01

In recent years, functional near-infrared spectroscopy (NIRS) has been introduced as a new neuroimaging modality with which to conduct functional brain-imaging studies. With its advanced features, NIRS signal processing has become a very attractive field in computational science. This work explores nonlinear physical aspects of cerebral hemodynamic changes over the time series of NIRS. Detecting the presence of chaos in a dynamical system is an important problem in studying the irregular or chaotic motion that is generated by nonlinear systems whose dynamical laws uniquely determine the time of evolution of a state of the system. The strategy results directly from the definition of the largest Lyapunov exponent. The Lyapunov exponents quantify the exponential divergence of initially close state-space trajectories and estimate the amount of chaos in a system. The method is an application of the Rosenstein algorithm, an efficient method for calculating the largest Lyapunov exponent from an experimental time series. In the present paper, the authors focus mainly on the detection of chaos characteristics of the time series associated to hemoglobin dynamics. Furthermore, the chaos parameters obtained can be used to identify the active state period of the human brain.
Human Activity Recognition Using Hierarchically-Mined Feature Constellations

NARCIS (Netherlands)

Oikonomopoulos, A.; Pantic, Maja

In this paper we address the problem of human activity modelling and recognition by means of a hierarchical representation of mined dense spatiotemporal features. At each level of the hierarchy, the proposed method selects feature constellations that are increasingly discriminative and
Tribal Science 2017 Webinar Series: Harmful Algal Blooms (HABs): Research, Collaborations, and Other Activities

Science.gov (United States)

The Tribal Science Webinar Series provides a forum for discussion of the complex environmental issues facing many tribal and indigenous communities, and features a wide variety of expert guest speakers from government,.....
Lasers. Technology Learning Activity. Teacher Edition. Technology Education Series.

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Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This document contains the materials required for presenting an 8-day competency-based technology learning activity (TLA) designed to introduce students in grades 6-10 to advances and career opportunities in the field of laser technology. The guide uses a series of hands-on exploratory experiences into which activities to help students develop…
Feature selection in classification of eye movements using electrooculography for activity recognition.

Science.gov (United States)

Mala, S; Latha, K

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition.
Nonlinear features identified by Volterra series for damage detection in a buckled beam

Directory of Open Access Journals (Sweden)

Shiki S. B.

2014-01-01

Full Text Available The present paper proposes a new index for damage detection based on nonlinear features extracted from prediction errors computed by multiple convolutions using the discrete-time Volterra series. A reference Volterra model is identified with data in the healthy condition and used for monitoring the system operating with linear or nonlinear behavior. When the system has some structural change, possibly associated with damage, the index metrics computed could give an alert to separate the linear and nonlinear contributions, besides provide a diagnostic about the structural state. To show the applicability of the method, an experimental test is performed using nonlinear vibration signals measured in a clamped buckled beam subject to different levels of force applied and with simulated damages through discontinuities inserted in the beam surface.
Antiplasmodial activity of a series of 1,3,5-triazine-substituted polyamines

OpenAIRE

Klenke, Burkhard; Barrett, Michael P.; Brun, Reto; Gilbert, Ian H.

2017-01-01

Polyamine biosynthesis and function has been shown to be a good drug target in some parasitic protozoa and it is proposed that the pathway might also represent a target in the malaria parasite Plasmodium falciparum. A series of 1,3,5-triazine-substituted polyamine analogues were tested for activity against Plasmodium falciparum in vitro. The series showed activity against the parasites and were generally more active against the chloroquine-resistant line K1 than the chloroquine-susceptible li...
Control algorithms based on the active and non-active currents for a UPQC without series transformers

OpenAIRE

Correa Monteiro, Luis Fernando; Aredes, Mauricio; Pinto, J. G.; Exposto, Bruno; Afonso, João L.

2016-01-01

This study presents control algorithms for a new unified power quality conditioner (UPQC) without the series transformers that are frequently used to make the insertion of the series converter of the UPQC between the power supply and the load. The behaviour of the proposed UPQC is evaluated in presence of voltage imbalances, as well as under non-sinusoidal voltage-and current conditions. The presented algorithms derive from the concepts involving the active and non-active currents, together w...
Feature-Free Activity Classification of Inertial Sensor Data With Machine Vision Techniques: Method, Development, and Evaluation.

Science.gov (United States)

Dominguez Veiga, Jose Juan; O'Reilly, Martin; Whelan, Darragh; Caulfield, Brian; Ward, Tomas E

2017-08-04

Inertial sensors are one of the most commonly used sources of data for human activity recognition (HAR) and exercise detection (ED) tasks. The time series produced by these sensors are generally analyzed through numerical methods. Machine learning techniques such as random forests or support vector machines are popular in this field for classification efforts, but they need to be supported through the isolation of a potentially large number of additionally crafted features derived from the raw data. This feature preprocessing step can involve nontrivial digital signal processing (DSP) techniques. However, in many cases, the researchers interested in this type of activity recognition problems do not possess the necessary technical background for this feature-set development. The study aimed to present a novel application of established machine vision methods to provide interested researchers with an easier entry path into the HAR and ED fields. This can be achieved by removing the need for deep DSP skills through the use of transfer learning. This can be done by using a pretrained convolutional neural network (CNN) developed for machine vision purposes for exercise classification effort. The new method should simply require researchers to generate plots of the signals that they would like to build classifiers with, store them as images, and then place them in folders according to their training label before retraining the network. We applied a CNN, an established machine vision technique, to the task of ED. Tensorflow, a high-level framework for machine learning, was used to facilitate infrastructure needs. Simple time series plots generated directly from accelerometer and gyroscope signals are used to retrain an openly available neural network (Inception), originally developed for machine vision tasks. Data from 82 healthy volunteers, performing 5 different exercises while wearing a lumbar-worn inertial measurement unit (IMU), was collected. The ability of the
A natural approach to convey numerical digits using hand activity recognition based on hand shape features

Science.gov (United States)

Chidananda, H.; Reddy, T. Hanumantha

2017-06-01

This paper presents a natural representation of numerical digit(s) using hand activity analysis based on number of fingers out stretched for each numerical digit in sequence extracted from a video. The analysis is based on determining a set of six features from a hand image. The most important features used from each frame in a video are the first fingertip from top, palm-line, palm-center, valley points between the fingers exists above the palm-line. Using this work user can convey any number of numerical digits using right or left or both the hands naturally in a video. Each numerical digit ranges from 0 to9. Hands (right/left/both) used to convey digits can be recognized accurately using the valley points and with this recognition whether the user is a right / left handed person in practice can be analyzed. In this work, first the hand(s) and face parts are detected by using YCbCr color space and face part is removed by using ellipse based method. Then, the hand(s) are analyzed to recognize the activity that represents a series of numerical digits in a video. This work uses pixel continuity algorithm using 2D coordinate geometry system and does not use regular use of calculus, contours, convex hull and datasets.
Time series analysis of diverse extreme phenomena: universal features

Science.gov (United States)

Eftaxias, K.; Balasis, G.

2012-04-01

The field of study of complex systems holds that the dynamics of complex systems are founded on universal principles that may used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. We suggest that earthquake, epileptic seizures, solar flares, and magnetic storms dynamics can be analyzed within similar mathematical frameworks. A central property of aforementioned extreme events generation is the occurrence of coherent large-scale collective behavior with very rich structure, resulting from repeated nonlinear interactions among the corresponding constituents. Consequently, we apply the Tsallis nonextensive statistical mechanics as it proves an appropriate framework in order to investigate universal principles of their generation. First, we examine the data in terms of Tsallis entropy aiming to discover common "pathological" symptoms of transition to a significant shock. By monitoring the temporal evolution of the degree of organization in time series we observe similar distinctive features revealing significant reduction of complexity during their emergence. Second, a model for earthquake dynamics coming from a nonextensive Tsallis formalism, starting from first principles, has been recently introduced. This approach leads to an energy distribution function (Gutenberg-Richter type law) for the magnitude distribution of earthquakes, providing an excellent fit to seismicities generated in various large geographic areas usually identified as seismic regions. We show that this function is able to describe the energy distribution (with similar non-extensive q-parameter) of solar flares, magnetic storms, epileptic and earthquake shocks. The above mentioned evidence of a universal statistical behavior suggests the possibility of a common approach for studying space weather, earthquakes and epileptic seizures.
Cyclo-speed reducer 6000 series; Saikuro {reg_sign} gensokuki 6000 series

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-04-20

This series was put on the market as the advanced speed reducer '6000 series' in April, 2000 after further improvement of various previous excellent features by adopting innovative technologies. Various series of this cyclo-speed reducers adopting a unique inscribed epicyclic gear mechanism reach 7 million units in sales success. Main specifications: (1) Input capacity range: 0.1-132kW, (2) Output torque: 24-68,200N(center dot)m, (3) Reduction ratio: 6-1,000,000. Features: (1) High efficiency and long life by adopting the analysis system based on the latest analytical technology, (2) Noise reduction by a maximum of nearly 6dB, and tone improvement by adopting a new tooth profile, (3) Weight reduction by a maximum of nearly 40% by adopting a motor direct-coupled mechanism. (translated by NEDO)
Design strategy for the combined system of shunt passive and series active filters

OpenAIRE

Fujita, Hideki; Akagi, Hirofumi

1991-01-01

A design strategy for the combined power filter for a three-phase twelve-pulse thyristor rectifier is proposed. The shunt passive filter, which can minimize the output voltage of the series active filter, is designed and tested in a prototype model. A specially designed shunt passive filter makes it possible to reduce the required rating of the series active filter to 60% compared with a conventional shunt passive filter
Brain activity patterns uniquely supporting visual feature integration after traumatic brain injury

Directory of Open Access Journals (Sweden)

Anjali eRaja Beharelle

2011-12-01

Full Text Available Traumatic brain injury (TBI patients typically respond more slowly and with more variability than controls during tasks of attention requiring speeded reaction time. These behavioral changes are attributable, at least in part, to diffuse axonal injury (DAI, which affects integrated processing in distributed systems. Here we use a multivariate method sensitive to distributed neural activity to compare brain activity patterns of patients with chronic phase moderate-to-severe TBI to those of controls during performance on a visual feature-integration task assessing complex attentional processes that has previously shown sensitivity to TBI. The TBI patients were carefully screened to be free of large focal lesions that can affect performance and brain activation independently of DAI. The task required subjects to hold either one or three features of a target in mind while suppressing responses to distracting information. In controls, the multi-feature condition activated a distributed network including limbic, prefrontal, and medial temporal structures. TBI patients engaged this same network in the single-feature and baseline conditions. In multi-feature presentations, TBI patients alone activated additional frontal, parietal, and occipital regions. These results are consistent with neuroimaging studies using tasks assessing different cognitive domains, where increased spread of brain activity changes was associated with TBI. Our results also extend previous findings that brain activity for relatively moderate task demands in TBI patients is similar to that associated with of high task demands in controls.
A Novel Approach for Automatic Machining Feature Recognition with Edge Blend Feature

OpenAIRE

Keong Chen Wong; Yusof Yusri

2017-01-01

This paper presents an algorithm for efficiently recognizing and determining the convexity of an edge blend feature. The algorithm first recognizes all of the edge blend features from the Boundary Representation of a part; then a series of convexity test have been run on the recognized edge blend features. The novelty of the presented algorithm lies in, instead of each recognized blend feature is suppressed as most of researchers did, the recognized blend features of this research are gone th...

Load compensation for single phase system using series active filter ...

African Journals Online (AJOL)

Load compensation for single phase system using series active filter. ... KK Mishra, R Gupta ... load varies from time to time, the non linear load ranging from voltage source type harmonic load (VSHL) dominant to current source type harmonic ...
feets: feATURE eXTRACTOR for tIME sERIES

Science.gov (United States)

Cabral, Juan; Sanchez, Bruno; Ramos, Felipe; Gurovich, Sebastián; Granitto, Pablo; VanderPlas, Jake

2018-06-01

feets characterizes and analyzes light-curves from astronomical photometric databases for modelling, classification, data cleaning, outlier detection and data analysis. It uses machine learning algorithms to determine the numerical descriptors that characterize and distinguish the different variability classes of light-curves; these range from basic statistical measures such as the mean or standard deviation to complex time-series characteristics such as the autocorrelation function. The library is not restricted to the astronomical field and could also be applied to any kind of time series. This project is a derivative work of FATS (ascl:1711.017).
Using activity-related behavioural features towards more effective automatic stress detection.

Directory of Open Access Journals (Sweden)

Dimitris Giakoumis

Full Text Available This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing.
Working memory templates are maintained as feature-specific perceptual codes.

Science.gov (United States)

Sreenivasan, Kartik K; Sambhara, Deepak; Jha, Amishi P

2011-07-01

Working memory (WM) representations serve as templates that guide behavior, but the neural basis of these templates remains elusive. We tested the hypothesis that WM templates are maintained by biasing activity in sensoriperceptual neurons that code for features of items being held in memory. Neural activity was recorded using event-related potentials (ERPs) as participants viewed a series of faces and responded when a face matched a target face held in WM. Our prediction was that if activity in neurons coding for the features of the target is preferentially weighted during maintenance of the target, then ERP activity evoked by a nontarget probe face should be commensurate with the visual similarity between target and probe. Visual similarity was operationalized as the degree of overlap in visual features between target and probe. A face-sensitive ERP response was modulated by target-probe similarity. Amplitude was largest for probes that were similar to the target, and decreased monotonically as a function of decreasing target-probe similarity. These results indicate that neural activity is weighted in favor of visual features that comprise an actively held memory representation. As such, our findings support the notion that WM templates rely on neural populations involved in forming percepts of memory items.
Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data.

Science.gov (United States)

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-12-22

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification.
Consistent two-dimensional visualization of protein-ligand complex series

Directory of Open Access Journals (Sweden)

Stierand Katrin

2011-06-01

Full Text Available Abstract Background The comparative two-dimensional graphical representation of protein-ligand complex series featuring different ligands bound to the same active site offers a quick insight in their binding mode differences. In comparison to arbitrary orientations of the residue molecules in the individual complex depictions a consistent placement improves the legibility and comparability within the series. The automatic generation of such consistent layouts offers the possibility to apply it to large data sets originating from computer-aided drug design methods. Results We developed a new approach, which automatically generates a consistent layout of interacting residues for a given series of complexes. Based on the structural three-dimensional input information, a global two-dimensional layout for all residues of the complex ensemble is computed. The algorithm incorporates the three-dimensional adjacencies of the active site residues in order to find an universally valid circular arrangement of the residues around the ligand. Subsequent to a two-dimensional ligand superimposition step, a global placement for each residue is derived from the set of already placed ligands. The method generates high-quality layouts, showing mostly overlap-free solutions with molecules which are displayed as structure diagrams providing interaction information in atomic detail. Application examples document an improved legibility compared to series of diagrams whose layouts are calculated independently from each other. Conclusions The presented method extends the field of complex series visualizations. A series of molecules binding to the same protein active site is drawn in a graphically consistent way. Compared to existing approaches these drawings substantially simplify the visual analysis of large compound series.
Depth-based human activity recognition: A comparative perspective study on feature extraction

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Heba Hamdy Ali

2018-06-01

Full Text Available Depth Maps-based Human Activity Recognition is the process of categorizing depth sequences with a particular activity. In this problem, some applications represent robust solutions in domains such as surveillance system, computer vision applications, and video retrieval systems. The task is challenging due to variations inside one class and distinguishes between activities of various classes and video recording settings. In this study, we introduce a detailed study of current advances in the depth maps-based image representations and feature extraction process. Moreover, we discuss the state of art datasets and subsequent classification procedure. Also, a comparative study of some of the more popular depth-map approaches has provided in greater detail. The proposed methods are evaluated on three depth-based datasets “MSR Action 3D”, “MSR Hand Gesture”, and “MSR Daily Activity 3D”. Experimental results achieved 100%, 95.83%, and 96.55% respectively. While combining depth and color features on “RGBD-HuDaAct” Dataset, achieved 89.1%. Keywords: Activity recognition, Depth, Feature extraction, Video, Human body detection, Hand gesture
Sleep Spindle Detection and Prediction Using a Mixture of Time Series and Chaotic Features

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Amin Hekmatmanesh

2017-01-01

Full Text Available It is well established that sleep spindles (bursts of oscillatory brain electrical activity are significant indicators of learning, memory and some disease states. Therefore, many attempts have been made to detect these hallmark patterns automatically. In this pilot investigation, we paid special attention to nonlinear chaotic features of EEG signals (in combination with linear features to investigate the detection and prediction of sleep spindles. These nonlinear features included: Higuchi's, Katz's and Sevcik's Fractal Dimensions, as well as the Largest Lyapunov Exponent and Kolmogorov's Entropy. It was shown that the intensity map of various nonlinear features derived from the constructive interference of spindle signals could improve the detection of the sleep spindles. It was also observed that the prediction of sleep spindles could be facilitated by means of the analysis of these maps. Two well-known classifiers, namely the Multi-Layer Perceptron (MLP and the K-Nearest Neighbor (KNN were used to distinguish between spindle and non-spindle patterns. The MLP classifier produced a~high discriminative capacity (accuracy = 94.93%, sensitivity = 94.31% and specificity = 95.28% with significant robustness (accuracy ranging from 91.33% to 94.93%, sensitivity varying from 91.20% to 94.31%, and specificity extending from 89.79% to 95.28% in separating spindles from non-spindles. This classifier also generated the best results in predicting sleep spindles based on chaotic features. In addition, the MLP was used to find out the best time window for predicting the sleep spindles, with the experimental results reaching 97.96% accuracy.
Integrated Active and Passive Polymer Optical Components with nm to mm Features

DEFF Research Database (Denmark)

Christiansen, Mads Brøkner; Schøler, Mikkel; Kristensen, Anders

2007-01-01

We present wafer-scale fabrication of integrated active and passive polymer optics with nm to mm features. First order DFB lasers, defined in dye doped SU-8 resist are integrated with SU-8 waveguides.......We present wafer-scale fabrication of integrated active and passive polymer optics with nm to mm features. First order DFB lasers, defined in dye doped SU-8 resist are integrated with SU-8 waveguides....
Characteristics of the co-fluctuation matrix transmission network based on financial multi-time series

OpenAIRE

Huajiao Li; Haizhong An; Xiangyun Gao; Wei Fang

2015-01-01

The co-fluctuation of two time series has often been studied by analysing the correlation coefficient over a selected period. However, in both domestic and global financial markets, there are more than two active time series that fluctuate constantly as a result of various factors, including geographic locations, information communications and so on. In addition to correlation relationships over longer periods, daily co-fluctuation relationships and their transmission features are also import...
Feature activation during word recognition: action, visual, and associative-semantic priming effects

Directory of Open Access Journals (Sweden)

Kevin J.Y. Lam

2015-05-01

Full Text Available Embodied theories of language postulate that language meaning is stored in modality-specific brain areas generally involved in perception and action in the real world. However, the temporal dynamics of the interaction between modality-specific information and lexical-semantic processing remain unclear. We investigated the relative timing at which two types of modality-specific information (action-based and visual-form information contribute to lexical-semantic comprehension. To this end, we applied a behavioral priming paradigm in which prime and target words were related with respect to (1 action features, (2 visual features, or (3 semantically associative information. Using a Go/No-Go lexical decision task, priming effects were measured across four different inter-stimulus intervals (ISI = 100 ms, 250 ms, 400 ms, and 1,000 ms to determine the relative time course of the different features . Notably, action priming effects were found in ISIs of 100 ms, 250 ms, and 1,000 ms whereas a visual priming effect was seen only in the ISI of 1,000 ms. Importantly, our data suggest that features follow different time courses of activation during word recognition. In this regard, feature activation is dynamic, measurable in specific time windows but not in others. Thus the current study (1 demonstrates how multiple ISIs can be used within an experiment to help chart the time course of feature activation and (2 provides new evidence for embodied theories of language.
A Feature Fusion Based Forecasting Model for Financial Time Series

Science.gov (United States)

Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

2014-01-01

Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models. PMID:24971455
A Series Active Damper with Closed-loop Control for Stabilizing Single-phase Power-Electronics-Based Power System

DEFF Research Database (Denmark)

Lu, Dapeng; Wang, Xiongfei; Bai, Haofeng

2016-01-01

resistance through detection and resonant controller, the series active damper can suppress the resonance with its external damping character in closed-loop damping character are carried out. Simulation and experimental results are presented to verify the effectiveness of the proposed series active damper....
Desired features of smartphone applications promoting physical activity.

Science.gov (United States)

Rabin, Carolyn; Bock, Beth

2011-12-01

Approximately one-third of adults in the United States are physically inactive. This is a significant public health concern as physical activity (PA) can influence the risk of cardiovascular disease, diabetes, and certain forms of cancer. To minimize these health risks, effective PA interventions must be developed and disseminated to the vast number of individuals who remain sedentary. Smartphone technology presents an exciting opportunity for delivering PA interventions remotely. Although a number of PA applications are currently available for smartphones, these "apps" are not based on established theories of health behavior change and most do not include evidence-based features (e.g., reinforcement and goal setting). Our aim was to collect formative data to develop a smartphone PA app that is empirically and theoretically-based and incorporates user preferences. We recruited 15 sedentary adults to test three currently available PA smartphone apps and provide qualitative and quantitative feedback. Findings indicate that users have a number of specific preferences with regard to PA app features, including that apps provide automatic tracking of PA (e.g., steps taken and calories burned), track progress toward PA goals, and integrate a music feature. Participants also preferred that PA apps be flexible enough to be used with several types of PA, and have well-documented features and user-friendly interfaces (e.g., a one-click main page). When queried by the researcher, most participants endorsed including goal-setting and problem-solving features. These findings provide a blue print for developing a smartphone PA app that incorporates evidence-based components and user preferences.
Human activity recognition based on feature selection in smart home using back-propagation algorithm.

Science.gov (United States)

Fang, Hongqing; He, Lei; Si, Hao; Liu, Peng; Xie, Xiaolei

2014-09-01

In this paper, Back-propagation(BP) algorithm has been used to train the feed forward neural network for human activity recognition in smart home environments, and inter-class distance method for feature selection of observed motion sensor events is discussed and tested. And then, the human activity recognition performances of neural network using BP algorithm have been evaluated and compared with other probabilistic algorithms: Naïve Bayes(NB) classifier and Hidden Markov Model(HMM). The results show that different feature datasets yield different activity recognition accuracy. The selection of unsuitable feature datasets increases the computational complexity and degrades the activity recognition accuracy. Furthermore, neural network using BP algorithm has relatively better human activity recognition performances than NB classifier and HMM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Middle-aged women's preferred theory-based features in mobile physical activity applications.

Science.gov (United States)

Ehlers, Diane K; Huberty, Jennifer L

2014-09-01

The purpose of this study was to describe which theory-based behavioral and technological features middle-aged women prefer to be included in a mobile application designed to help them adopt and maintain regular physical activity (PA). Women aged 30 to 64 years (N = 120) completed an online survey measuring their demographics and mobile PA application preferences. The survey was developed upon behavioral principles of Social Cognitive Theory, recent mobile app research, and technology adoption principles of the Unified Theory of Acceptance and Use of Technology. Frequencies were calculated and content analyses conducted to identify which features women most preferred. Behavioral features that help women self-regulate their PA (PA tracking, goal-setting, progress monitoring) were most preferred. Technological features that enhance perceived effort expectancy and playfulness were most preferred. Many women reported the desire to interact and compete with others through the application. Theory-based PA self-regulation features and theory-based design features that improve perceived effort expectancy and playfulness may be most beneficial in a mobile PA application for middle-aged women. Opportunities to interact with other people and the employment of social, game-like activities may also be attractive. Interdisciplinary engagement of experts in PA behavior change, technology adoption, and software development is needed.
Effectiveness of Multivariate Time Series Classification Using Shapelets

Directory of Open Access Journals (Sweden)

A. P. Karpenko

2015-01-01

Full Text Available Typically, time series classifiers require signal pre-processing (filtering signals from noise and artifact removal, etc., enhancement of signal features (amplitude, frequency, spectrum, etc., classification of signal features in space using the classical techniques and classification algorithms of multivariate data. We consider a method of classifying time series, which does not require enhancement of the signal features. The method uses the shapelets of time series (time series shapelets i.e. small fragments of this series, which reflect properties of one of its classes most of all.Despite the significant number of publications on the theory and shapelet applications for classification of time series, the task to evaluate the effectiveness of this technique remains relevant. An objective of this publication is to study the effectiveness of a number of modifications of the original shapelet method as applied to the multivariate series classification that is a littlestudied problem. The paper presents the problem statement of multivariate time series classification using the shapelets and describes the shapelet–based basic method of binary classification, as well as various generalizations and proposed modification of the method. It also offers the software that implements a modified method and results of computational experiments confirming the effectiveness of the algorithmic and software solutions.The paper shows that the modified method and the software to use it allow us to reach the classification accuracy of about 85%, at best. The shapelet search time increases in proportion to input data dimension.
Activation barriers for series of exothermic homologous reactions. VI. Reactions of lanthanide and transition metal atoms.

Science.gov (United States)

Blue, Alan S.; Fontijn, Arthur

2001-09-01

Semiempirical configuration interaction (SECI) theory to predict activation barriers, E, as given by k(T)=ATn exp(-E(RT), has been applied to homologous series of lanthanide (LN) and transition metal (TM) atom oxidation reactions. This was achieved by considering as homologous series reactions of elements differing only by the number of electrons in one subshell. Comparison between SECI and experimental results leads to an average deviation for the LN+N2O reactions of 0.66 kJ mol-1, and up to 5.5 kJ mol-1 for other series. Thirty-one activation barriers are reported.
Electron-topological investigation of the structure-antitumor activity relationship of thiosemicarbazone derivatives.

Science.gov (United States)

Dimoglo, A S; Chumakov, Y M; Dobrova, B N; Saracoglu, M

1997-04-01

In the frameworks of the electron-topological method (ETM) the structure-antitumor activity relationship was investigated for a series of thiosemicarbazone derivatives. The series included 70 compounds. Conformational analysis and quantum-chemical calculations were carried out for each compound. The revealed activity feature showed a satisfactory description of the class of active compounds according to two different parameters P and alpha estimating the probabilities of the feature realization in the class of active compounds (they are equal to 0.94 and 0.86, correspondingly). The results of testing demonstrated the high ability of ETM in predicting the activity investigated.
Antimalarial activity of HIV-1 protease inhibitor in chromone series.

Science.gov (United States)

Lerdsirisuk, Pradith; Maicheen, Chirattikan; Ungwitayatorn, Jiraporn

2014-12-01

Increasing parasite resistance to nearly all available antimalarial drugs becomes a serious problem to human health and necessitates the need to continue the search for new effective drugs. Recent studies have shown that clinically utilized HIV-1 protease (HIV-1 PR) inhibitors can inhibit the in vitro and in vivo growth of Plasmodium falciparum. In this study, a series of chromone derivatives possessing HIV-1 PR inhibitory activity has been tested for antimalarial activity against P. falciparum (K1 multi-drug resistant strain). Chromone 15, the potent HIV-1 PR inhibitor (IC50=0.65μM), was found to be the most potent antimalarial compound with IC50=0.95μM while primaquine and tafenoquine showed IC50=2.41 and 1.95μM, respectively. Molecular docking study of chromone compounds against plasmepsin II, an aspartic protease enzyme important in hemoglobin degradation, revealed that chromone 15 exhibited the higher binding affinity (binding energy=-13.24kcal/mol) than the known PM II inhibitors. Thus, HIV-1 PR inhibitor in chromone series has the potential to be a new class of antimalarial agent. Copyright © 2014 Elsevier Inc. All rights reserved.

Storage of feature conjunctions in transient auditory memory.

Science.gov (United States)

Gomes, H; Bernstein, R; Ritter, W; Vaughan, H G; Miller, J

1997-11-01

The purpose of this study was to determine whether feature conjunctions are stored in transient auditory memory. The mismatch negativity (MMN), an event-related potential that is elicited by stimuli that differ from a series of preceding stimuli, was used in this endeavour. A tone that differed from the preceding series of stimuli in the conjunction of two of its features, both present in preceding stimuli but in different combinations, was found to elicit the MMN. The data are interpreted to indicate that information about the conjunction of features is stored in the memory.
Nonlinear techniques for forecasting solar activity directly from its time series

Science.gov (United States)

Ashrafi, S.; Roszman, L.; Cooley, J.

1993-01-01

This paper presents numerical techniques for constructing nonlinear predictive models to forecast solar flux directly from its time series. This approach makes it possible to extract dynamical in variants of our system without reference to any underlying solar physics. We consider the dynamical evolution of solar activity in a reconstructed phase space that captures the attractor (strange), give a procedure for constructing a predictor of future solar activity, and discuss extraction of dynamical invariants such as Lyapunov exponents and attractor dimension.
Self-education activities features of primary school teachers in the period between training courses.

Directory of Open Access Journals (Sweden)

Nalyvaiko G.V.

2011-08-01

Full Text Available The article describes self-education activities features of primary school teachers in the period between training courses. The basic conditions and areas of self-education activities features of primary school teachers in the period between training courses is singled out. The interpretations of the self-education definition are considered. The primary school teachers' self-education activities components are carried out. The period between training courses in training primary school teachers is defined.
Feature-space-based FMRI analysis using the optimal linear transformation.

Science.gov (United States)

Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.
Drunk driving detection based on classification of multivariate time series.

Science.gov (United States)

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.
Wearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang Transform.

Science.gov (United States)

Xu, Huile; Liu, Jinyi; Hu, Haibo; Zhang, Yi

2016-12-02

Wearable sensors-based human activity recognition introduces many useful applications and services in health care, rehabilitation training, elderly monitoring and many other areas of human interaction. Existing works in this field mainly focus on recognizing activities by using traditional features extracted from Fourier transform (FT) or wavelet transform (WT). However, these signal processing approaches are suitable for a linear signal but not for a nonlinear signal. In this paper, we investigate the characteristics of the Hilbert-Huang transform (HHT) for dealing with activity data with properties such as nonlinearity and non-stationarity. A multi-features extraction method based on HHT is then proposed to improve the effect of activity recognition. The extracted multi-features include instantaneous amplitude (IA) and instantaneous frequency (IF) by means of empirical mode decomposition (EMD), as well as instantaneous energy density (IE) and marginal spectrum (MS) derived from Hilbert spectral analysis. Experimental studies are performed to verify the proposed approach by using the PAMAP2 dataset from the University of California, Irvine for wearable sensors-based activity recognition. Moreover, the effect of combining multi-features vs. a single-feature are investigated and discussed in the scenario of a dependent subject. The experimental results show that multi-features combination can further improve the performance measures. Finally, we test the effect of multi-features combination in the scenario of an independent subject. Our experimental results show that we achieve four performance indexes: recall, precision, F-measure, and accuracy to 0.9337, 0.9417, 0.9353, and 0.9377 respectively, which are all better than the achievements of related works.
Comparison of CT enterography and MR enterography imaging features of active Crohn disease in children and adolescents

Energy Technology Data Exchange (ETDEWEB)

Gale, Heather I. [The Warren Alpert Medical School of Brown University, Department of Diagnostic Imaging, Rhode Island Hospital/Hasbro Children' s Children' s Hospital/Women and Infants Hospital, Providence, RI (United States); Sharatz, Steven M.; Nimkin, Katherine; Gee, Michael S. [MassGeneral Hospital for Children, Division of Pediatric Imaging, Department of Radiology, Harvard Medical School, Boston, MA (United States); Taphey, Mayureewan [Bumrungrad International Hospital, Bangkok (Thailand); Bradley, William F. [Cambridge Mobile Telematics, Cambridge, MA (United States)

2017-09-15

Assessment for active Crohn disease by CT enterography and MR enterography relies on identifying mural and perienteric imaging features. To evaluate the performance of established imaging features of active Crohn disease in children and adolescents on CT and MR enterography compared with histological reference. We included patients ages 18 years and younger who underwent either CT or MR enterography from 2007 to 2014 and had endoscopic biopsy within 28 days of imaging. Two pediatric radiologists blinded to the histological results reviewed imaging studies and scored the bowel for the presence or absence of mural features (wall thickening >3 mm, mural hyperenhancement) and perienteric features (mesenteric hypervascularity, edema, fibrofatty proliferation and lymphadenopathy) of active disease. We performed univariate analysis and multivariate logistic regression to compare imaging features with histological reference. We evaluated 452 bowel segments (135 from CT enterography, 317 from MR enterography) from 84 patients. Mural imaging features had the highest association with active inflammation both for MR enterography (wall thickening had 80% accuracy, 69% sensitivity and 91% specificity; mural hyperenhancement had 78%, 53% and 96%, respectively) and CT enterography (wall thickening had 84% accuracy, 72% sensitivity and 91% specificity; mural hyperenhancement had 76%, 51% and 91%, respectively), with perienteric imaging features performing significantly worse on MR enterography relative to CT enterography (P < 0.001). Mural features are predictors of active inflammation for both CT and MR enterography, while perienteric features can be distinguished better on CT enterography compared with MR enterography. This likely reflects the increased conspicuity of the mesentery on CT enterography and suggests that mural features are the most reliable imaging features of active Crohn disease in children and adolescents. (orig.)
Conductance and activation energy for electron transport in series and parallel intramolecular circuits.

Science.gov (United States)

Hsu, Liang-Yan; Wu, Ning; Rabitz, Herschel

2016-11-30

We investigate electron transport through series and parallel intramolecular circuits in the framework of the multi-level Redfield theory. Based on the assumption of weak monomer-bath couplings, the simulations depict the length and temperature dependence in six types of intramolecular circuits. In the tunneling regime, we find that the intramolecular circuit rule is only valid in the weak monomer coupling limit. In the thermally activated hopping regime, for circuits based on two different molecular units M a and M b with distinct activation energies E act,a > E act,b , the activation energies of M a and M b in series are nearly the same as E act,a while those in parallel are nearly the same as E act,b . This study gives a comprehensive description of electron transport through intramolecular circuits from tunneling to thermally activated hopping. We hope that this work can motivate additional studies to design intramolecular circuits based on different types of building blocks, and to explore the corresponding circuit laws and the length and temperature dependence of conductance.
The motor and cognitive features of Parkinson's disease in patients with concurrent Gaucher disease over 2 years: a case series.

Science.gov (United States)

Collins, Lucy M; Williams-Gray, Caroline H; Morris, Elizabeth; Deegan, Patrick; Cox, Timothy M; Barker, Roger A

2018-05-29

We report the cognitive features and progression of Parkinson's disease (PD) in five patients with concurrent Gaucher disease. The patients presented at an earlier age than patients with sporadic PD, as previously noted by others; but in contrast to many previous reports, our patients followed a variable clinical course. While two patients developed early cognitive deficits and dementia, three others remained cognitively intact over the follow-up period. Thus, in this small case series, PD in the context of GD more closely resembles idiopathic PD in terms of its clinical heterogeneity in contrast to PD associated with GBA heterozygote mutations.
Robust Sensor-Orientation-Independent Feature Selection for Animal Activity Recognition on Collar Tags

NARCIS (Netherlands)

Kamminga, Jacob Wilhelm; Le Viet Duc, Duc Viet; Meijers, Jan Pieter; Bisby, Helena C.; Meratnia, Nirvana; Havinga, Paul J.M.

2018-01-01

Fundamental challenges faced by real-time animal activity recognition include variation in motion data due to changing sensor orientations, numerous features, and energy and processing constraints of animal tags. This paper aims at finding small optimal feature sets that are lightweight and robust
Correlation optics in progress: introduction to the feature issue

DEFF Research Database (Denmark)

Angelsky, Oleg V.; Desyatnikov, Anton S.; Gbur, Gregory J.

2014-01-01

This feature issue of Applied Optics contains a series of selected papers reflecting recent progress of correlation optics and showing, in part, the trend from micro-optics to nano-optics.......This feature issue of Applied Optics contains a series of selected papers reflecting recent progress of correlation optics and showing, in part, the trend from micro-optics to nano-optics....
Wearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang Transform

Directory of Open Access Journals (Sweden)

Huile Xu

2016-12-01

Full Text Available Wearable sensors-based human activity recognition introduces many useful applications and services in health care, rehabilitation training, elderly monitoring and many other areas of human interaction. Existing works in this field mainly focus on recognizing activities by using traditional features extracted from Fourier transform (FT or wavelet transform (WT. However, these signal processing approaches are suitable for a linear signal but not for a nonlinear signal. In this paper, we investigate the characteristics of the Hilbert-Huang transform (HHT for dealing with activity data with properties such as nonlinearity and non-stationarity. A multi-features extraction method based on HHT is then proposed to improve the effect of activity recognition. The extracted multi-features include instantaneous amplitude (IA and instantaneous frequency (IF by means of empirical mode decomposition (EMD, as well as instantaneous energy density (IE and marginal spectrum (MS derived from Hilbert spectral analysis. Experimental studies are performed to verify the proposed approach by using the PAMAP2 dataset from the University of California, Irvine for wearable sensors-based activity recognition. Moreover, the effect of combining multi-features vs. a single-feature are investigated and discussed in the scenario of a dependent subject. The experimental results show that multi-features combination can further improve the performance measures. Finally, we test the effect of multi-features combination in the scenario of an independent subject. Our experimental results show that we achieve four performance indexes: recall, precision, F-measure, and accuracy to 0.9337, 0.9417, 0.9353, and 0.9377 respectively, which are all better than the achievements of related works.
Cluster analysis of activity-time series in motor learning

DEFF Research Database (Denmark)

Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

2002-01-01

Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...
Methods for summing general Kapteyn series

Energy Technology Data Exchange (ETDEWEB)

Tautz, R C [Zentrum fuer Astronomie und Astrophysik, Technische Universitaet Berlin, Hardenbergstrasse 36, D-10623 Berlin (Germany); Lerche, I [Institut fuer Geowissenschaften, Naturwissenschaftliche Fakultaet III, Martin-Luther-Universitaet Halle, D-06099 Halle (Germany); Dominici, D, E-mail: rct@gmx.eu, E-mail: lercheian@yahoo.com, E-mail: dominicd@newpaltz.edu [Department of Mathematics, State University of New York at New Paltz, 1 Hawk Dr, New Paltz, NY 12561-2443 (United States)

2011-09-23

The general features and characteristics of Kapteyn series, which are a special type of series involving the Bessel function, are investigated. For many applications in physics, astrophysics and mathematics, it is crucial to have closed-form expressions in order to determine their functional structure and parametric behavior. The closed-form expressions of Kapteyn series have mostly been limited to special cases, even though there are often similarities in the approaches used to reduce the series to analytically tractable forms. The goal of this paper is to review the previous work in the area and to show that Kapteyn series can be expressed as trigonometric or gamma function series, which can be evaluated in a closed form for specific parameters. Two examples with a similar structure are given, showing the complexity of Kapteyn series. (paper)
Modelling and Simulation of Single-Phase Series Active Compensator for Power Quality Improvement

Science.gov (United States)

Verma, Arun Kumar; Mathuria, Kirti; Singh, Bhim; Bhuvaneshwari, G.

2017-10-01

A single-phase active series compensator is proposed in this work to reduce harmonic currents at the ac mains and to regulate the dc link voltage of a diode bridge rectifier (DBR) that acts as the front end converter for a voltage source inverter feeding an ac motor. This ac motor drive is used in any of the domestic, commercial or industrial appliances. Under fluctuating ac mains voltages, the dc link voltage of the DBR depicts wide variations and hence the ac motor is used at reduced rating as compared to its name-plate rating. The active series compensator proposed here provides dual functions of improving the power quality at the ac mains and regulating the dc link voltage thus averting the need for derating of the ac motor.
Perspective on Secure Development Activities and Features of Safety I and C Systems

International Nuclear Information System (INIS)

Kang, Youngdoo; Yu, Yeong Jin; Kim, Hyungtae; Kwon, Yong il; Park, Yeunsoo; Choo, Jaeyul; Son, Jun Young; Jeong, Choong Heui

2015-01-01

The Enforcement Decree of the Act on Physical Protection and Radiological Emergency (ED-APPRE) was revised December 2013 to include security requirements on computer systems at nuclear facilities to protect those systems against malicious cyber-attacks. It means Cyber-Security-related measures, controls and activities of safety I and C systems against cyber-attacks shall meet the requirements of ED-APPRE. Still regulation upon inadvertent access or non-malicious modifications to the safety I and C systems is covered under the Nuclear Safety Act. The objective of this paper is to propose KINS' regulatory perspective on secure development and features against non-malicious access or modification of safety I and C systems. Secure development activities and features aim to prevent inadvertent and non-malicious access, and to prevent unwanted action from personnel or connected systems for ensuring reliable operation of safety I and C systems. Secure development activities of safety I and C systems are life cycle activities to ensure unwanted, unneeded and undocumented code is not incorporated into the systems. Secure features shall be developed, verified and qualified throughout the development life cycle
Perspective on Secure Development Activities and Features of Safety I and C Systems

Energy Technology Data Exchange (ETDEWEB)

Kang, Youngdoo; Yu, Yeong Jin; Kim, Hyungtae; Kwon, Yong il; Park, Yeunsoo; Choo, Jaeyul; Son, Jun Young; Jeong, Choong Heui [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

2015-05-15

The Enforcement Decree of the Act on Physical Protection and Radiological Emergency (ED-APPRE) was revised December 2013 to include security requirements on computer systems at nuclear facilities to protect those systems against malicious cyber-attacks. It means Cyber-Security-related measures, controls and activities of safety I and C systems against cyber-attacks shall meet the requirements of ED-APPRE. Still regulation upon inadvertent access or non-malicious modifications to the safety I and C systems is covered under the Nuclear Safety Act. The objective of this paper is to propose KINS' regulatory perspective on secure development and features against non-malicious access or modification of safety I and C systems. Secure development activities and features aim to prevent inadvertent and non-malicious access, and to prevent unwanted action from personnel or connected systems for ensuring reliable operation of safety I and C systems. Secure development activities of safety I and C systems are life cycle activities to ensure unwanted, unneeded and undocumented code is not incorporated into the systems. Secure features shall be developed, verified and qualified throughout the development life cycle.
Time series clustering in large data sets

Directory of Open Access Journals (Sweden)

Jiří Fejfar

2011-01-01

Full Text Available The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM with the unsupervised learning algorithm for clustering of time series. After the first experiment (Fejfar, Weinlichová, Šťastný, 2009 it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to find the correlation between configured parameters and results more precisely. The second requirement arose in a need for a well-defined evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs detection and many others applications.The objective of the presented paper is to compare clustering results made with different parameters of feature vectors and the SOM itself. We are describing time series in a simplistic way evaluating standard deviations for separated parts of recordings. The resulting feature vectors are clustered with the SOM in batch training mode with different topologies varying from few neurons to large maps.There are other algorithms discussed, usable for finding similarities between time series and finally conclusions for further research are presented. We also present an overview of the related actual literature and projects.
Modeling activity patterns of wildlife using time-series analysis.

Science.gov (United States)

Zhang, Jindong; Hull, Vanessa; Ouyang, Zhiyun; He, Liang; Connor, Thomas; Yang, Hongbo; Huang, Jinyan; Zhou, Shiqiang; Zhang, Zejun; Zhou, Caiquan; Zhang, Hemin; Liu, Jianguo

2017-04-01

The study of wildlife activity patterns is an effective approach to understanding fundamental ecological and evolutionary processes. However, traditional statistical approaches used to conduct quantitative analysis have thus far had limited success in revealing underlying mechanisms driving activity patterns. Here, we combine wavelet analysis, a type of frequency-based time-series analysis, with high-resolution activity data from accelerometers embedded in GPS collars to explore the effects of internal states (e.g., pregnancy) and external factors (e.g., seasonal dynamics of resources and weather) on activity patterns of the endangered giant panda ( Ailuropoda melanoleuca ). Giant pandas exhibited higher frequency cycles during the winter when resources (e.g., water and forage) were relatively poor, as well as during spring, which includes the giant panda's mating season. During the summer and autumn when resources were abundant, pandas exhibited a regular activity pattern with activity peaks every 24 hr. A pregnant individual showed distinct differences in her activity pattern from other giant pandas for several months following parturition. These results indicate that animals adjust activity cycles to adapt to seasonal variation of the resources and unique physiological periods. Wavelet coherency analysis also verified the synchronization of giant panda activity level with air temperature and solar radiation at the 24-hr band. Our study also shows that wavelet analysis is an effective tool for analyzing high-resolution activity pattern data and its relationship to internal and external states, an approach that has the potential to inform wildlife conservation and management across species.
Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons.

Directory of Open Access Journals (Sweden)

Kyriaki Sidiropoulou

Full Text Available Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC, which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS and an intrinsic bursting (IB model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given

Depression and anxiety in a case series of amyotrophic lateral sclerosis: frequency and association with clinical features.

Science.gov (United States)

Prado, Laura de Godoy Rousseff; Bicalho, Isabella Carolina Santos; Vidigal-Lopes, Mauro; Prado, Vitor de Godoy Rousseff; Gomez, Rodrigo Santiago; de Souza, Leonardo Cruz; Teixeira, Antônio Lúcio

2017-01-01

To investigate the frequency of anxiety and depression and their association with clinical features of amyotrophic lateral sclerosis. This is a cross-sectional and descriptive study including a consecutive series of patients with sporadic amyotrophic lateral sclerosis according to Awaji's criteria. Patients underwent clinical and psychiatric assessment (anxiety and depression symptoms). We included 76 patients. The men/women ratio was 1.6:1. Participants' mean age at disease onset was 55 years (SD±12.1). Sixty-six patients (86.8%) were able to complete psychiatric evaluation. Clinically significant anxiety was found in 23 patients (34.8%) while clinically significant depression was found in 24 patients (36.4%). When we compared patients with and without depression a significant difference was seen only in the frequency of anxiety symptoms (pescala funcional. Foi encontrada correlação positiva entre os sintomas de ansiedade e depressão (pescala funcional.
Passivity enhancement by series LC filtered active damper with zero current reference

DEFF Research Database (Denmark)

Bai, Haofeng; Wang, Xiongfei; Blaabjerg, Frede

2016-01-01

can be improved by enhancing the passivity of the total admittance seen by the grid, which allows for a zero current reference and a much simpler current controller for the active damper. To show the performance of the active damper with zero reference, this paper first carries out the impedance based...... stability analysis of grid converters in the weak grid. Based on the impedance model of the series LC filtered active damper, the real part of its output admittance is investigated and shown to be able to enhance the passivity of the admittance of the converters seen by the grid. Finally, simulation...
Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)

Science.gov (United States)

Iqtait, M.; Mohamad, F. S.; Mamat, M.

2018-03-01

Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.
Structural features of nitroaromatics that determine mutagenic activity in Salmonella typhimurium

International Nuclear Information System (INIS)

Vance, W.A.; Levin, D.E.

1984-01-01

Seventeen structurally homologous nitroaromatics were tested for direct-acting mutagenic potency in nine strains of Salmonella typhimurium. The following four structural features were determined to have a strong influence on mutagenic activity: physical dimensions of the aromatic rings, isomeric position of the nitro group, conformation of the nitro group with respect to the plane of the aromatic rings, and ability to resonance-stabilize the utimate electrophile. Progressive addition of five- and six-membered rings to a nitrobenzene nucleus demonstrated that mutagenic activity was a direct function of size. Nitroaromatics with a nitro group oriented along the long axis of symmetry of the molecule were more potent mutagens that those with the nitro group oriented along the short axis. These results are discussed in light of the insertion-denaturation model for intercalation of certain DNA adducts. Finally, structural features that contribute to resonance stabilization of the reactive nitrenium ion enhance mutagenic potency. The predictive value of these structure-activity relationships should permit a first approximation in the assessment of mutagenic potency of nitroaromatics
A voltage control method for an active capacitive DC-link module with series-connected circuit

DEFF Research Database (Denmark)

Wang, Haoran; Wang, Huai; Blaabjerg, Frede

2017-01-01

Many efforts have been made to improve the performance of power electronic systems with active capacitive DC-link module in terms of power density as well as reliability. One of the attractive solution is an active capacitive DC-link with the series-connected circuit because of handling small......-rated power. However, in the existing control method of this circuit, the DC-link current of the backward-stage or forward-stage need to be sensed for extracting the ripple components, which limits the flexibility of the active DC-link module. Thus, in this paper, a voltage control method of an active...... capacitive DC-link module is proposed. Current sensor at the DC-link will be cancel from the circuit. The controller of the series-connected circuit requires internal voltage signals of the DC-link module only, making it possible to be fully independent without any additional connection to the main circuit...
Orofacial clinical features in Arnold Chiari type I malformation: A case series.

Science.gov (United States)

de Arruda, José-Alcides; Figueiredo, Eugênia; Monteiro, João-Luiz; Barbosa, Livia-Mirelle; Rodrigues, Cleomar; Vasconcelos, Belmiro

2018-04-01

Arnold Chiari malformation (ACM) is characterized by an anatomical defect at the base of the skull where the cerebellum and the spinal cord herniate through the foramen magnum into the cervical spinal canal. Among the subtypes of the condition, ACM type I (ACM-I) is particularly outstanding because of the severity of symptoms. This study aimed to analyze the orofacial clinical manifestations of patients with ACM-I, and discuss their demographic distribution and clinical features in light of the literature. A case series with patients with ACM-I treated between 2012 and 2015 was described. The sample consisted of patients who were referred by the Department of Neurosurgery to the Oral and Maxillofacial Surgery Service of Hospital da Restauração in Brazil for the assessment of facial symptomatology. A questionnaire was applied to evaluate the presence of painful orofacial findings. Data are reported using descriptive statistical methods. Mean patient age was 39.3 years and the sample consisted mostly of male patients. A high prevalence of headache (50%) and pain in the neck (66.7%) and masticatory muscles (50%) was found. Only one patient reported difficulty in performing mandibular movements and two reported jaw clicking sounds. Mean mouth opening was 40.83 mm. ACM-I patients may exhibit orofacial symptoms which may mimic temporomandibular joint disorders. This study brings interesting information that could help clinicians and oral and maxillofacial surgeons to understand this uncommon condition and also help with the diagnosis of patients with similar physical characteristics by referring them to a neurosurgeon. Key words: Arnold-Chiari malformation, facial pain, diagnosis, orofacial.
In Vitro Antifungal Activities of a Series of Dication-Substituted Carbazoles, Furans, and Benzimidazoles

Science.gov (United States)

Del Poeta, Maurizio; Schell, Wiley A.; Dykstra, Christine C.; Jones, Susan K.; Tidwell, Richard R.; Kumar, Arvind; Boykin, David W.; Perfect, John R.

1998-01-01

Aromatic dicationic compounds possess antimicrobial activity against a wide range of eucaryotic pathogens, and in the present study an examination of the structures-functions of a series of compounds against fungi was performed. Sixty-seven dicationic molecules were screened for their inhibitory and fungicidal activities against Candida albicans and Cryptococcus neoformans. The MICs of a large number of compounds were comparable to those of the standard antifungal drugs amphotericin B and fluconazole. Unlike fluconazole, potent inhibitory compounds in this series were found to have excellent fungicidal activities. The MIC of one of the most potent compounds against C. albicans was 0.39 μg/ml, and it was the most potent compound against C. neoformans (MIC, ≤0.09 μg/ml). Selected compounds were also found to be active against Aspergillus fumigatus, Fusarium solani, Candida species other than C. albicans, and fluconazole-resistant strains of C. albicans and C. neoformans. Since some of these compounds have been safely given to animals, these classes of molecules have the potential to be developed as antifungal agents. PMID:9756748
Citizen Science and Crowdsourcing as effective STEM Education and Engagement activities for Diverse Audiences: case studies featured in THE CROWD & THE CLOUD public TV series.

Science.gov (United States)

Haines-Stiles, G.; Abdalati, W.; Akuginow, E.

2017-12-01

Citizen science and crowdsourcing are relatively unfamiliar terms to the general public, including parents, children and teachers, as seen in focus groups convened by the NSF-funded THE CROWD & THE CLOUD public television series. Once aware, however, of the potential of today's citizen science—often relying on smartphones, apps and innovative sensors—both citizens and professional scientists become excited and seek to learn more. CROWD & CLOUD, premiering on PBS stations in April 2017, hosted by former NASA Chief Scientist Waleed Abdalati, and streaming at CrowdAndCloud.org, features a wide range of projects supported by NASA, NOAA, USGS, EPA and other Federal agencies. Some, such as EyesOnALZ, a startup which aims to accelerate research on Alzheimer's disease, adapt a crowdsourcing model first developed to help analyze data returned by NASA's Stardust spacecraft. Early results from its "StallCatchers" puzzle-game show both high quality data and have been shown to cut one year's worth of academic labor down to one month of effort by "the crowd." While longstanding citizen science projects such as Audubon's Christmas Bird Count (starting in 1900) have proven their worth, Smartfin—embedding sensors in surfboard fins—is taking advantage of recent technical innovations to track sea surface temperatures and ocean acidification, with their accuracy validated by the Scripps Institution of Oceanography. The NASA-supported GLOBE Observer mosquito habitat mapper project uses a $6 microscope attached to a smartphone to aid in species identification. Some projects tap adult volunteers, but many, such as USGS's Nature's Notebook, also appeal to youngsters. In Albuquerque local teens track invasive species and help refuge managers, usefully supplementing the sole salaried ranger. In the Rockaways, New York, high school students plant pollinator gardens and promote ecosystem resilience following Superstorm Sandy. This presentation will feature short videos demonstrating
Optics in computing: introduction to the feature issue.

Science.gov (United States)

Drabik, T; Thienpont, H; Ishikawa, M

2000-02-10

This issue of Applied Optics features 21 papers that describe the implementation of optics in computer systems and applications. This feature is the eighth in a series on the application of optics in the field of computing.
Design of an Active Bumper with a Series Elastic Actuator for Pedestrian Protection of Small Unmanned Vehicles

Science.gov (United States)

Terumasa, Narukawa; Tomoki, Tsuge; Hiroshi, Yamamoto; Takahiro, Suzuki

2016-09-01

When autonomous unmanned vehicles are operated on sidewalks, the vehicles must have high safety standards such as avoiding injury when they come in contact with pedestrians. In this study, we established a design for preventing serious injury when such collisions occur. We designed an active bumper with a series elastic actuator, with the goal of avoiding serious injury to a pedestrian in a collision with a small unmanned vehicle. The series elastic actuator comprised an elastic element in series with a table driven by a ball screw and servo motor. The active bumper was used to control the contact force between a vehicle and a pedestrian. The optimal force for minimizing the deflection of the object of the collision was derived, and the actuator controlled to apply this optimal force. Numerical simulations showed that the active bumper was successful in improving the collision safety of small unmanned vehicles.
Magnetic Resonance Imaging Features as Surrogate Markers of X-Linked Hypophosphatemic Rickets Activity.

Science.gov (United States)

Lempicki, Marta; Rothenbuhler, Anya; Merzoug, Valérie; Franchi-Abella, Stéphanie; Chaussain, Catherine; Adamsbaum, Catherine; Linglart, Agnès

2017-01-01

X-linked hypophosphatemic rickets (XLH) is the most common form of inheritable rickets. Rickets treatment is monitored by assessing alkaline phosphatase (ALP) levels, clinical features, and radiographs. Our objectives were to describe the magnetic resonance imaging (MRI) features of XLH and to assess correlations with disease activity. Twenty-seven XLH patients (median age 9.2 years) were included in this prospective single-center observational study. XLH activity was assessed using height, leg bowing, dental abscess history, and serum ALP levels. We looked for correlations between MRI features and markers of disease activity. On MRI, the median maximum width of the physis was 5.6 mm (range 4.8-7.8; normal 1.5 mm in all of the patients. The appearance of the zone of provisional calcification was abnormal on 21 MRI images (78%), Harris lines were present on 24 (89%), and bone marrow signal abnormalities were present on 16 (59%). ALP levels correlated with the maximum physeal widening and with the transverse extent of the widening. MRI of the knee provides precise rickets patterns that are correlated with ALP, an established biochemical marker of the disease, avoiding X-ray exposure and providing surrogate quantitative markers of disease activity. © 2017 S. Karger AG, Basel.
A DESCRIPTIVE SURVEY ON SMARTPHONES FEATURES FOR SUPPORTING THE ACADEMIC ACTIVITIES AT UNIVERSITAS PENDIDIKAN GANESHA

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Nyoman Putri Rustrini

2016-09-01

Full Text Available The objectives of the study are to analyse the use of smartphones for lecturers and students in Universitas Pendidikan Ganesha which are measured based on the supporting factors of the smartphoness application and to analyse its features in academic activities. The data were collected by using questionnaires and analyzed by using a descriptive analysis method. This study showed that the level of smartphones use to support academic activities is categorized as very high with the motivation factor of 90. 51%. There are 3 groups of features that dominate the use of smartphones namely calculation, storage and documentation. The calculation feature was represented by calculator with the percentage of 99%. The storage feature was represented by contact, gallery, and dropbox with the precentages of 99%, 97%, and 71% respectively. The documentation feature was represented by camera, video and recorder with the percentages of 97%, 81%, and 51% respectively.
Feature diagnosticity and task context shape activity in human scene-selective cortex.

Science.gov (United States)

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.
Study of the relationship between chemical structure and antimicrobial activity in a series of hydrazine-based coordination compounds.

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Dobrova, B N; Dimoglo, A S; Chumakov, Y M

2000-08-01

The dependence of antimicrobial activity on the structure of compounds is studied in a series of compounds based on hydrazine coordinated with ions of Cu(II), Ni(II) and Pd(II). The study has been carried out by means of the original electron-topological method developed earlier. A molecular fragment has been found that is only characteristic of biologically active compounds. Its spatial and electron parameters have been used for the quantitative assessment of the activity in view. The results obtained can be used for the antimicrobial activity prediction in a series of compounds with similar structures.
Features and prospects of juridical predicting of entrepreneurial activity

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Natalya V. Rubtsova

2017-03-01

Full Text Available Objective to identify characteristics and prospects of predicting the business activity. Methods historical sociological logical systematicstructural formallegal comparativelegal legal modeling method. Results in article suggests the legal definition of prediction of business activity as a scientific and practical study aimed at the determination of the future state and prospects of development of business activity consisting of the evaluation of legal regulation and analysis of the prospectsof further socioeconomic development which aims to select the optimal solution for the further development of entrepreneurship through legal regulators. The work proves the necessity of achieving a balanced legal regulation of social relations by changing the legislation in the field of business agreements investment and innovation. Scientific novelty the article for the first time formulates the concept characteristics and features of legal prediction of business activity substantiates the impact of predicting on the development of legal regulation of social relations. Practical significance the main provisions and conclusions of the article can be used in research and teaching while considering the issues of predicting both the socioeconomic processes in general and business activity in particular.
Feature selection for wearable smartphone-based human activity recognition with able bodied, elderly, and stroke patients.

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Nicole A Capela

Full Text Available Human activity recognition (HAR, using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter. The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree. Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations.
Feature selection for wearable smartphone-based human activity recognition with able bodied, elderly, and stroke patients.

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Capela, Nicole A; Lemaire, Edward D; Baddour, Natalie

2015-01-01

Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations.
Automated detection of qualitative spatio-temporal features in electrocardiac activation maps.

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Ironi, Liliana; Tentoni, Stefania

2007-02-01

This paper describes a piece of work aiming at the realization of a tool for the automated interpretation of electrocardiac maps. Such maps can capture a number of electrical conduction pathologies, such as arrhytmia, that can be missed by the analysis of traditional electrocardiograms. But, their introduction into the clinical practice is still far away as their interpretation requires skills that belongs to very few experts. Then, an automated interpretation tool would bridge the gap between the established research outcome and clinical practice with a consequent great impact on health care. Qualitative spatial reasoning can play a crucial role in the identification of spatio-temporal patterns and salient features that characterize the heart electrical activity. We adopted the spatial aggregation (SA) conceptual framework and an interplay of numerical and qualitative information to extract features from epicardial maps, and to make them available for reasoning tasks. Our focus is on epicardial activation isochrone maps as they are a synthetic representation of spatio-temporal aspects of the propagation of the electrical excitation. We provide a computational SA-based methodology to extract, from 3D epicardial data gathered over time, (1) the excitation wavefront structure, and (2) the salient features that characterize wavefront propagation and visually correspond to specific geometric objects. The proposed methodology provides a robust and efficient way to identify salient pieces of information in activation time maps. The hierarchical structure of the abstracted geometric objects, crucial in capturing the prominent information, facilitates the definition of general rules necessary to infer the correlation between pathophysiological patterns and wavefront structure and propagation.
A new approach for measuring power spectra and reconstructing time series in active galactic nuclei

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Li, Yan-Rong; Wang, Jian-Min

2018-05-01

We provide a new approach to measure power spectra and reconstruct time series in active galactic nuclei (AGNs) based on the fact that the Fourier transform of AGN stochastic variations is a series of complex Gaussian random variables. The approach parametrizes a stochastic series in frequency domain and transforms it back to time domain to fit the observed data. The parameters and their uncertainties are derived in a Bayesian framework, which also allows us to compare the relative merits of different power spectral density models. The well-developed fast Fourier transform algorithm together with parallel computation enables an acceptable time complexity for the approach.
Comparison of Feature Learning Methods for Human Activity Recognition Using Wearable Sensors.

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Li, Frédéric; Shirahama, Kimiaki; Nisar, Muhammad Adeel; Köping, Lukas; Grzegorzek, Marcin

2018-02-24

Getting a good feature representation of data is paramount for Human Activity Recognition (HAR) using wearable sensors. An increasing number of feature learning approaches-in particular deep-learning based-have been proposed to extract an effective feature representation by analyzing large amounts of data. However, getting an objective interpretation of their performances faces two problems: the lack of a baseline evaluation setup, which makes a strict comparison between them impossible, and the insufficiency of implementation details, which can hinder their use. In this paper, we attempt to address both issues: we firstly propose an evaluation framework allowing a rigorous comparison of features extracted by different methods, and use it to carry out extensive experiments with state-of-the-art feature learning approaches. We then provide all the codes and implementation details to make both the reproduction of the results reported in this paper and the re-use of our framework easier for other researchers. Our studies carried out on the OPPORTUNITY and UniMiB-SHAR datasets highlight the effectiveness of hybrid deep-learning architectures involving convolutional and Long-Short-Term-Memory (LSTM) to obtain features characterising both short- and long-term time dependencies in the data.

Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

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Peek Andrew S

2007-06-01

Full Text Available Abstract Background RNA interference (RNAi is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM approach was used to quantitatively model RNA interference activities. Results Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative. Conclusion The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid
A new method based on fractal variance function for analysis and quantification of sympathetic and vagal activity in variability of R-R time series in ECG signals

Energy Technology Data Exchange (ETDEWEB)

Conte, Elio [Department of Pharmacology and Human Physiology and Tires, Center for Innovative Technologies for Signal Detection and Processing, University of Bari, Bari (Italy); School of Advanced International Studies on Nuclear, Theoretical and Nonlinear Methodologies-Bari (Italy)], E-mail: fisio2@fisiol.uniba.it; Federici, Antonio [Department of Pharmacology and Human Physiology and Tires, Center for Innovative Technologies for Signal Detection and Processing, University of Bari, Bari (Italy); Zbilut, Joseph P. [Department of Molecular Biophysics and Physiology, Rush University Medical Center, 1653W Congress, Chicago, IL 60612 (United States)

2009-08-15

It is known that R-R time series calculated from a recorded ECG, are strongly correlated to sympathetic and vagal regulation of the sinus pacemaker activity. In human physiology it is a crucial question to estimate such components with accuracy. Fourier analysis dominates still to day the data analysis efforts of such data ignoring that FFT is valid under some crucial restrictions that results largely violated in R-R time series data as linearity and stationarity. In order to go over such approach, we introduce a new method, called CZF. It is based on variogram analysis. It is aimed from a profound link with Recurrence Quantification Analysis that is a basic tool for investigation of non linear and non stationary time series. Therefore, a relevant feature of the method is that it finally may be applied also in cases of non linear and non stationary time series analysis. In addition, the method enables also to analyze the fractal variance function, the Generalized Fractal Dimension and, finally, the relative probability density function of the data. The CZF gives very satisfactory results. In the present paper it has been applied to direct experimental cases of normal subjects, patients with hypertension before and after therapy and in children under some different conditions of experimentation.
A new method based on fractal variance function for analysis and quantification of sympathetic and vagal activity in variability of R-R time series in ECG signals

International Nuclear Information System (INIS)

Conte, Elio; Federici, Antonio; Zbilut, Joseph P.

2009-01-01

It is known that R-R time series calculated from a recorded ECG, are strongly correlated to sympathetic and vagal regulation of the sinus pacemaker activity. In human physiology it is a crucial question to estimate such components with accuracy. Fourier analysis dominates still to day the data analysis efforts of such data ignoring that FFT is valid under some crucial restrictions that results largely violated in R-R time series data as linearity and stationarity. In order to go over such approach, we introduce a new method, called CZF. It is based on variogram analysis. It is aimed from a profound link with Recurrence Quantification Analysis that is a basic tool for investigation of non linear and non stationary time series. Therefore, a relevant feature of the method is that it finally may be applied also in cases of non linear and non stationary time series analysis. In addition, the method enables also to analyze the fractal variance function, the Generalized Fractal Dimension and, finally, the relative probability density function of the data. The CZF gives very satisfactory results. In the present paper it has been applied to direct experimental cases of normal subjects, patients with hypertension before and after therapy and in children under some different conditions of experimentation.
Clinicopathologic and prognostic features of breast cancer in young women: a series from North of Morocco.

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Bakkach, Joaira; Mansouri, Mohamed; Derkaoui, Touria; Loudiyi, Ali; Fihri, Mohamed; Hassani, Samia; Barakat, Amina; Ghailani Nourouti, Naima; Bennani Mechita, Mohcine

2017-11-09

Literature data reported a higher frequency of breast cancer in young women (BCYW) in developing countries. BCYW is associated with delayed diagnosis, aggressive biology and poor prognosis. However, our knowledge of biological profile, treatment received and outcome of young patients is still limited in Morocco. We propose to analyze clinicopathologic, therapeutic and prognostic features of BCYW among a series of patients native and/or inhabitant of North of Morocco. We carried out a retro-prospective study of 331 infiltrating breast cancer cases registered between January 2010 and December 2015. Details of tumor pathology, treatment and outcome were collected. Disease-Free Survival (DFS) and Overall Survival (OS) were assessed by Kaplan-Meier analysis. A total of 82 patients were diagnosed with breast cancer at the age of 40 or younger (24.8%). Median age was 36 years. More than one quarter (26%) of patients had family history of breast or ovarian cancer. Advanced stages accounted for 34.2% of cases. Median tumor diameter was 2.8 cm. Intermediate and high-grade tumors represented 47.6% and 40.2%, respectively. Nodal involvement was present in 58.5% and lymphovascular invasion was found in 47.7% of the patients. About two thirds (66.2%) of tumors were hormone receptor positive, 29.2% over-expressed HER2 receptor and 23% were triple negative. Patients underwent breast conserving surgery in 38.2% of cases, 61.7% were offered adjuvant chemotherapy and 84.6% received hormone therapy. Five-year DFS and OS were respectively 88.9% and 75.6%. Locoregional recurrence occurred in 2.8% of cases and 8.3% of patients developed distant metastases. Our findings are in accordance with previous studies that have shown a higher frequency of breast cancer among Moroccan young women. In line with literature data, clinicopathologic profile seems to be aggressive and prognosis is pejorative in our series.
Chemical features of Ganoderma polysaccharides with antioxidant, antitumor and antimicrobial activities.

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Ferreira, Isabel C F R; Heleno, Sandrina A; Reis, Filipa S; Stojkovic, Dejan; Queiroz, Maria João R P; Vasconcelos, M Helena; Sokovic, Marina

2015-06-01

Ganoderma genus comprises one of the most commonly studied species worldwide, Ganoderma lucidum. However, other Ganoderma species have been also reported as important sources of bioactive compounds. Polysaccharides are important contributors to the medicinal properties reported for Ganoderma species, as demonstrated by the numerous publications, including reviews, on this matter. Yet, what are the chemical features of Ganoderma polysaccharides that have bioactivity? In the present manuscript, the chemical features of Ganoderma polysaccharides with reported antioxidant, antitumor and antimicrobial activities (the most studied worldwide) are analyzed in detail. The composition of sugars (homo- versus hetero-glucans and other polysaccharides), type of glycosidic linkages, branching patterns, and linkage to proteins are discussed. Methods for extraction, isolation and identification are evaluated and, finally, the bioactivity of polysaccharidic extracts and purified compounds are discussed. The integration of data allows deduction of structure-activity relationships and gives clues to the chemical aspects involved in Ganoderma bioactivity. Copyright © 2014 Elsevier Ltd. All rights reserved.
DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

OpenAIRE

Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

2017-01-01

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...
Self-potential time series analysis in a seismic area of the Southern Apennines: preliminary results

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V. Tramutoli

1994-06-01

Full Text Available The self-potential time series recorded during the period May 1991 - August 1992 by an automatic station, located in a seismic area of Southern Apennines, is analyzed. We deal with the spectral and the statistical features of the electrotellurie precursors: they can play a major role in the approach to seismic prediction. The time-dynamics of the experimental time series is investigated, the cyclic components and the time trends are removed. In particular we consider the influence of external noise, related to anthropic activities and meteoclimatic parameters, and pick out the anomalies from the residual series. Finally we show the preliminary results of the correlation between the anomalies in the time patterns of self-potential data and the earthquakes which occurred in the area.
Koopman Operator Framework for Time Series Modeling and Analysis

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Surana, Amit

2018-01-01

We propose an interdisciplinary framework for time series classification, forecasting, and anomaly detection by combining concepts from Koopman operator theory, machine learning, and linear systems and control theory. At the core of this framework is nonlinear dynamic generative modeling of time series using the Koopman operator which is an infinite-dimensional but linear operator. Rather than working with the underlying nonlinear model, we propose two simpler linear representations or model forms based on Koopman spectral properties. We show that these model forms are invariants of the generative model and can be readily identified directly from data using techniques for computing Koopman spectral properties without requiring the explicit knowledge of the generative model. We also introduce different notions of distances on the space of such model forms which is essential for model comparison/clustering. We employ the space of Koopman model forms equipped with distance in conjunction with classical machine learning techniques to develop a framework for automatic feature generation for time series classification. The forecasting/anomaly detection framework is based on using Koopman model forms along with classical linear systems and control approaches. We demonstrate the proposed framework for human activity classification, and for time series forecasting/anomaly detection in power grid application.
Comparison of Feature Learning Methods for Human Activity Recognition Using Wearable Sensors

Directory of Open Access Journals (Sweden)

Frédéric Li

2018-02-01

Full Text Available Getting a good feature representation of data is paramount for Human Activity Recognition (HAR using wearable sensors. An increasing number of feature learning approaches—in particular deep-learning based—have been proposed to extract an effective feature representation by analyzing large amounts of data. However, getting an objective interpretation of their performances faces two problems: the lack of a baseline evaluation setup, which makes a strict comparison between them impossible, and the insufficiency of implementation details, which can hinder their use. In this paper, we attempt to address both issues: we firstly propose an evaluation framework allowing a rigorous comparison of features extracted by different methods, and use it to carry out extensive experiments with state-of-the-art feature learning approaches. We then provide all the codes and implementation details to make both the reproduction of the results reported in this paper and the re-use of our framework easier for other researchers. Our studies carried out on the OPPORTUNITY and UniMiB-SHAR datasets highlight the effectiveness of hybrid deep-learning architectures involving convolutional and Long-Short-Term-Memory (LSTM to obtain features characterising both short- and long-term time dependencies in the data.
Images of Germany, Past and Present: A Film Collection. Series I, Instructional Activities.

Science.gov (United States)

Goethe House, New York, NY.

This set of lessons accompanies a series of 30-minute films for teaching about Germany. Available to educators throughout the United States upon request, the 17 films and accompanying instructional activities focus on culture, politics, economics, society, and sports and are appropriate for middle and high school students. Permission is granted to…
Observation of surface features on an active landslide, and implications for understanding its history of movement

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M. Parise

2003-01-01

Full Text Available Surface features are produced as a result of internal deformation of active landslides, and are continuously created and destroyed by the movement. Observation of their presence and distribution, and surveying of their evolution may provide insights for the zonation of the mass movement in sectors characterized by different behaviour. The present study analyses and describes some example of surface features observed on an active mass movement, the Slumgullion earthflow, in the San Juan Mountains of southwestern Colorado. The Slumgullion earthflow is one of the most famous and spectacular landslides in the world; it consists of a younger, active part which moves on and over an older, much larger, inactive part. Total length of the earthflow is 6.8 km, with an estimated volume of 170 × 10 6 m 3 . Its nearly constant rate of movement (ranging from about 2 m per year at the head, to a maximum of 6–7 m per year at its narrow and central part, to values between 1.3 and 2 m per year at the active toe, and the geological properties of moving material, are well suited for the observation of the development and evolution of surface features. In the last 11 years, repeated surveying at the Slumgullion site has been performed through recognition of surface features, measurements of their main characteristics, and detailed mapping. In this study, two sectors of the Slumgullion earthflow are analysed through comparison of the features observed in this time span, and evaluation of the changes occurred: they are the active toe and an area located at the left flank of the landslide. Choice of the sectors was dictated in the first case, by particular activity of movement and the nearby presence of elements at risk (highway located only 250 m downhill from the toe; and in the second case, by the presence of many surface features, mostly consisting of several generations of flank ridges. The active toe of the landslide is characterized by continuous movement
Time averaging, ageing and delay analysis of financial time series

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Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf

2017-06-01

We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.
Polyalkoxybenzenes from plants. 5. Parsley seed extract in synthesis of azapodophyllotoxins featuring strong tubulin destabilizing activity in the sea urchin embryo and cell culture assays.

Science.gov (United States)

Semenova, Marina N; Kiselyov, Alex S; Tsyganov, Dmitry V; Konyushkin, Leonid D; Firgang, Sergei I; Semenov, Roman V; Malyshev, Oleg R; Raihstat, Mikhail M; Fuchs, Fabian; Stielow, Anne; Lantow, Margareta; Philchenkov, Alex A; Zavelevich, Michael P; Zefirov, Nikolay S; Kuznetsov, Sergei A; Semenov, Victor V

2011-10-27

A series of 4-azapodophyllotoxin derivatives with modified rings B and E have been synthesized using allylpolyalkoxybenzenes from parsley seed oil. The targeted molecules were evaluated in vivo in a phenotypic sea urchin embryo assay for antimitotic and tubulin destabilizing activity. The most active compounds identified by the in vivo sea urchin embryo assay featured myristicin-derived ring E. These molecules were determined to be more potent than podophyllotoxin. Cytotoxic effects of selected molecules were further confirmed and evaluated by conventional assays with A549 and Jurkat human leukemic T-cell lines including cell growth inhibition, cell cycle arrest, cellular microtubule disruption, and induction of apoptosis. The ring B modification yielded 6-OMe substituted molecule as the most active compound. Finally, in Jurkat cells, compound induced caspase-dependent apoptosis mediated by the apical caspases-2 and -9 and not caspase-8, implying the involvement of the intrinsic caspase-9-dependent apoptotic pathway.
Solar activity associated with an unusual series of microwave flux decreases

International Nuclear Information System (INIS)

Sawyer, C.

1976-01-01

East-limb passage of an activity complex in the spring of 1974 was accompanied by a remarkable series of microwave flux decreases. Within an interval of four days, two post-burst decreases and five 'absorption' events occurred, along with two oscillations. Hα patrol films and a spectrogram show a surge and flare sprays with an unusually large velocity of approach at the time of the first post-burst decrease. Two other 'absorption' events were loosely associated with prominence activations, but no outstanding Hα activity was seen at the time of the oscillations. These observations, along with published data, show that the flux decreases followed only flares that lay westward of the major microwave source; ejections from this location would likely have overlain the source while the region was near the east limb. Absorption by flare-ejected material is a plausible, though not exclusive, explanation of these events. (author)
Limits in feature-based attention to multiple colors.

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Liu, Taosheng; Jigo, Michael

2017-11-01

Attention to a feature enhances the sensory representation of that feature. Although much has been learned about the properties of attentional modulation when attending to a single feature, the effectiveness of attending to multiple features is not well understood. We investigated this question in a series of experiments using a color-detection task while varying the number of attended colors in a cueing paradigm. Observers were shown either a single cue, two cues, or no cue (baseline) before detecting a coherent color target. We measured detection threshold by varying the coherence level of the target. Compared to the baseline condition, we found consistent facilitation of detection performance in the one-cue and two-cue conditions, but performance in the two-cue condition was lower than that in the one-cue condition. In the final experiment, we presented a 50% valid cue to emulate the situation in which observers were only able to attend a single color in the two-cue condition, and found equivalent detection thresholds with the standard two-cue condition. These results indicate a limit in attending to two colors and further imply that observers could effectively attend a single color at a time. Such a limit is likely due to an inability to maintain multiple active attentional templates for colors.
Images of Germany: Past and Present. A Film Collection, Series II Instructional Activities.

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Blankenship, Glen; Hutcheson, Gwen

This booklet offers classroom activities for use with 15 social studies-related films for teaching about Germany. The series of 25-minute films are made available by Deutsche Welle Television and Goethe House New York. Lessons in the booklet include: (1) "Germany Since 1945: A Focus on Berlin"; (2) "'I'll Get You All Out of Here!' A…
Measurement of radionuclide activities of uranium-238 series in soil samples by gamma spectrometry: case of Vinaninkarena

International Nuclear Information System (INIS)

Randrianantenaina, F.R.

2017-01-01

The aim of this work is to determine the activity level of radionuclides of uranium-238 series. Eight soil samples are collected at Rural Commune of Vinaninkarena. After obtaining secular equilibrium, these samples have been measured using gamma spectrometry system in the Nuclear Analyses and Techniques Department of INSTN-Madagascar, with HPGe detector (30 % relative efficiency) and a Genie 2000 software. Activities obtained vary from (78±2)Bq.kg -1 to (49 231 ± 415)Bq.kg -1 . Among these eight samples, three activity levels are shown. Low activity is an activity which has value lower or equal to (89±3)Bq.kg -1 . Average activity is an activity which has value between (186± 1)Bq.kg -1 and (1049 ±7)Bq.kg -1 . And high activity is an activity which has value higher or equal to (14501±209)Bq.kg -1 . According to UNSCEAR 2000, these value are all higher than the world average value which is 35 Bq.kg -1 .It is due to the localities of sampling points. The variation of the activity level depends on radionuclide concentration of uranium-238 series in the soil. [fr
Normed algebras and the geometric series test

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Robert Kantrowitz

2017-11-01

Full Text Available The purpose of this article is to survey a class of normed algebras that share many central features of Banach algebras, save for completeness. The likeness of these algebras to Banach algebras derives from the fact that the geometric series test is valid, whereas the lack of completeness points to the failure of the absolute convergence test for series in the algebra. Our main result is a compendium of conditions that are all equivalent to the validity of the geometric series test for commutative unital normed algebras. Several examples in the final section showcase some incomplete normed algebras for which the geometric series test is valid, and still others for which it is not.
Clustering of financial time series

Science.gov (United States)

D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

2013-05-01

This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.
Identification of low variability textural features for heterogeneity quantification of 18F-FDG PET/CT imaging.

Science.gov (United States)

Cortes-Rodicio, J; Sanchez-Merino, G; Garcia-Fidalgo, M A; Tobalina-Larrea, I

To identify those textural features that are insensitive to both technical and biological factors in order to standardise heterogeneity studies on 18 F-FDG PET imaging. Two different studies were performed. First, nineteen series from a cylindrical phantom filled with different 18 F-FDG activity concentration were acquired and reconstructed using three different protocols. Seventy-two texture features were calculated inside a circular region of interest. The variability of each feature was obtained. Second, the data for 15 patients showing non-pathological liver were acquired. Anatomical and physiological features such as patient's weight, height, body mass index, metabolic active volume, blood glucose level, SUV and SUV standard deviation were also recorded. A liver covering region of interest was delineated and low variability textural features calculated in each patient. Finally, a multivariate Spearman's correlation analysis between biological factors and texture features was performed. Only eight texture features analysed show small variability (feature is, indeed, correlated (Ptextural features that are correlated with neither technical nor biological factors are run percentage, short-zone emphasis and intensity, making them suitable for quantifying functional changes or classifying patients. Other textural features are correlated with technical and biological factors and are, therefore, a source of errors if used for this purpose. Copyright © 2016 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

An efficient heuristic method for active feature acquisition and its application to protein-protein interaction prediction

Directory of Open Access Journals (Sweden)

Thahir Mohamed

2012-11-01

Full Text Available Abstract Background Machine learning approaches for classification learn the pattern of the feature space of different classes, or learn a boundary that separates the feature space into different classes. The features of the data instances are usually available, and it is only the class-labels of the instances that are unavailable. For example, to classify text documents into different topic categories, the words in the documents are features and they are readily available, whereas the topic is what is predicted. However, in some domains obtaining features may be resource-intensive because of which not all features may be available. An example is that of protein-protein interaction prediction, where not only are the labels ('interacting' or 'non-interacting' unavailable, but so are some of the features. It may be possible to obtain at least some of the missing features by carrying out a few experiments as permitted by the available resources. If only a few experiments can be carried out to acquire missing features, which proteins should be studied and which features of those proteins should be determined? From the perspective of machine learning for PPI prediction, it would be desirable that those features be acquired which when used in training the classifier, the accuracy of the classifier is improved the most. That is, the utility of the feature-acquisition is measured in terms of how much acquired features contribute to improving the accuracy of the classifier. Active feature acquisition (AFA is a strategy to preselect such instance-feature combinations (i.e. protein and experiment combinations for maximum utility. The goal of AFA is the creation of optimal training set that would result in the best classifier, and not in determining the best classification model itself. Results We present a heuristic method for active feature acquisition to calculate the utility of acquiring a missing feature. This heuristic takes into account the change in
Persistent topological features of dynamical systems

Energy Technology Data Exchange (ETDEWEB)

Maletić, Slobodan, E-mail: slobodan@hitsz.edu.cn [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen (China); Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade (Serbia); Zhao, Yi, E-mail: zhao.yi@hitsz.edu.cn [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen (China); Rajković, Milan, E-mail: milanr@vinca.rs [Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade (Serbia)

2016-05-15

Inspired by an early work of Muldoon et al., Physica D 65, 1–16 (1993), we present a general method for constructing simplicial complex from observed time series of dynamical systems based on the delay coordinate reconstruction procedure. The obtained simplicial complex preserves all pertinent topological features of the reconstructed phase space, and it may be analyzed from topological, combinatorial, and algebraic aspects. In focus of this study is the computation of homology of the invariant set of some well known dynamical systems that display chaotic behavior. Persistent homology of simplicial complex and its relationship with the embedding dimensions are examined by studying the lifetime of topological features and topological noise. The consistency of topological properties for different dynamic regimes and embedding dimensions is examined. The obtained results shed new light on the topological properties of the reconstructed phase space and open up new possibilities for application of advanced topological methods. The method presented here may be used as a generic method for constructing simplicial complex from a scalar time series that has a number of advantages compared to the mapping of the same time series to a complex network.
RNA-Seq of Bacillus licheniformis: active regulatory RNA features expressed within a productive fermentation

Science.gov (United States)

2013-01-01

Background The production of enzymes by an industrial strain requires a complex adaption of the bacterial metabolism to the conditions within the fermenter. Regulatory events within the process result in a dynamic change of the transcriptional activity of the genome. This complex network of genes is orchestrated by proteins as well as regulatory RNA elements. Here we present an RNA-Seq based study considering selected phases of an industry-oriented fermentation of Bacillus licheniformis. Results A detailed analysis of 20 strand-specific RNA-Seq datasets revealed a multitude of transcriptionally active genomic regions. 3314 RNA features encoded by such active loci have been identified and sorted into ten functional classes. The identified sequences include the expected RNA features like housekeeping sRNAs, metabolic riboswitches and RNA switches well known from studies on Bacillus subtilis as well as a multitude of completely new candidates for regulatory RNAs. An unexpectedly high number of 855 RNA features are encoded antisense to annotated protein and RNA genes, in addition to 461 independently transcribed small RNAs. These antisense transcripts contain molecules with a remarkable size range variation from 38 to 6348 base pairs in length. The genome of the type strain B. licheniformis DSM13 was completely reannotated using data obtained from RNA-Seq analyses and from public databases. Conclusion The hereby generated data-sets represent a solid amount of knowledge on the dynamic transcriptional activities during the investigated fermentation stages. The identified regulatory elements enable research on the understanding and the optimization of crucial metabolic activities during a productive fermentation of Bacillus licheniformis strains. PMID:24079885
RNA-Seq of Bacillus licheniformis: active regulatory RNA features expressed within a productive fermentation.

Science.gov (United States)

Wiegand, Sandra; Dietrich, Sascha; Hertel, Robert; Bongaerts, Johannes; Evers, Stefan; Volland, Sonja; Daniel, Rolf; Liesegang, Heiko

2013-10-01

The production of enzymes by an industrial strain requires a complex adaption of the bacterial metabolism to the conditions within the fermenter. Regulatory events within the process result in a dynamic change of the transcriptional activity of the genome. This complex network of genes is orchestrated by proteins as well as regulatory RNA elements. Here we present an RNA-Seq based study considering selected phases of an industry-oriented fermentation of Bacillus licheniformis. A detailed analysis of 20 strand-specific RNA-Seq datasets revealed a multitude of transcriptionally active genomic regions. 3314 RNA features encoded by such active loci have been identified and sorted into ten functional classes. The identified sequences include the expected RNA features like housekeeping sRNAs, metabolic riboswitches and RNA switches well known from studies on Bacillus subtilis as well as a multitude of completely new candidates for regulatory RNAs. An unexpectedly high number of 855 RNA features are encoded antisense to annotated protein and RNA genes, in addition to 461 independently transcribed small RNAs. These antisense transcripts contain molecules with a remarkable size range variation from 38 to 6348 base pairs in length. The genome of the type strain B. licheniformis DSM13 was completely reannotated using data obtained from RNA-Seq analyses and from public databases. The hereby generated data-sets represent a solid amount of knowledge on the dynamic transcriptional activities during the investigated fermentation stages. The identified regulatory elements enable research on the understanding and the optimization of crucial metabolic activities during a productive fermentation of Bacillus licheniformis strains.
Classification of time-series images using deep convolutional neural networks

Science.gov (United States)

Hatami, Nima; Gavet, Yann; Debayle, Johan

2018-04-01

Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images and then take advantage of the deep CNN classifier. Image representation of time-series introduces different feature types that are not available for 1D signals, and therefore TSC can be treated as texture image recognition task. CNN model also allows learning different levels of representations together with a classifier, jointly and automatically. Therefore, using RP and CNN in a unified framework is expected to boost the recognition rate of TSC. Experimental results on the UCR time-series classification archive demonstrate competitive accuracy of the proposed approach, compared not only to the existing deep architectures, but also to the state-of-the art TSC algorithms.
Features of public open spaces and physical activity among children: findings from the CLAN study.

Science.gov (United States)

Timperio, Anna; Giles-Corti, Billie; Crawford, David; Andrianopoulos, Nick; Ball, Kylie; Salmon, Jo; Hume, Clare

2008-11-01

To examine associations between features of public open spaces, and children's physical activity. 163 children aged 8-9 years and 334 adolescents aged 13-15 years from Melbourne, Australia participated in 2004. A Geographic Information System was used to identify all public open spaces (POS) within 800 m of participants' homes and their closest POS. The features of all POS identified were audited in 2004/5. Accelerometers measured moderate-to-vigorous physical activity (MVPA) after school and on weekends. Linear regression analyses examined associations between features of the closest POS and participants' MVPA. Most participants had a POS within 800 m of their home. The presence of playgrounds was positively associated with younger boys' weekend MVPA (B=24.9 min/day; pPOS were associated with participants' MVPA, although mixed associations were evident. Further research is required to clarify these complex relationships.
Passivity Enhancement of Grid-Tied Converter by Series LC-Filtered Active Damper

DEFF Research Database (Denmark)

Bai, Haofeng; Wang, Xiongfei; Loh, Poh Chiang

2015-01-01

attention. Also, parasitic capacitance of the grid transmission line brings new challenge for the application of an active damper, which has not been discussed before. In order to fill these gaps, this paper first analyzes the stability of a grid-tied converter with the help of passivity. Based......Series LC-filtered active damper can be used to stabilize the grid-tied voltage source converter in a non-ideal grid. The operation principle of the active damper is to mimic a damping resistance at the resonance frequencies. However, the selection of the damping resistance has not received much...... on the passivity-based-stability analysis, a damping resistance selection method is proposed. Then, an admittance shaping method is developed to ensure the system stability in the presence of parasitic capacitance of the transmission line. Finally, experimental results are provided to show the validity...
ON THE 10 μm SILICATE FEATURE IN ACTIVE GALACTIC NUCLEI

International Nuclear Information System (INIS)

Nikutta, Robert; Elitzur, Moshe; Lacy, Mark

2009-01-01

The 10 μm silicate feature observed with Spitzer in active galactic nuclei (AGNs) reveals some puzzling behavior. It (1) has been detected in emission in type 2 sources, (2) shows broad, flat-topped emission peaks shifted toward long wavelengths in several type 1 sources, and (3) is not seen in deep absorption in any source observed so far. We solve all three puzzles with our clumpy dust radiative transfer formalism. Addressing (1), we present the spectral energy distribution (SED) of SST1721+6012, the first type 2 quasar observed to show a clear 10 μm silicate feature in emission. Such emission arises in models of the AGN torus easily when its clumpy nature is taken into account. We constructed a large database of clumpy torus models and performed extensive fitting of the observed SED. We find that the cloud radial distribution varies as r -1.5 and the torus contains 2-4 clouds along radial equatorial rays, each with optical depth at visual ∼60-80. The source bolometric luminosity is ∼3 x 10 12 L sun . Our modeling suggests that ∼<35% of objects with tori sharing these characteristics and geometry would have their central engines obscured. This relatively low obscuration probability can explain the clear appearance of the 10 μm emission feature in SST1721+6012 together with its rarity among other QSO2. Investigating (2), we also fitted the SED of PG1211+143, one of the first type 1 QSOs with a 10 μm silicate feature detected in emission. Together with other similar sources, this QSO appears to display an unusually broadened feature whose peak is shifted toward longer wavelengths. Although this led to suggestions of non-standard dust chemistry in these sources, our analysis fits such SEDs with standard galactic dust; the apparent peak shifts arise from simple radiative transfer effects. Regarding (3), we find additionally that the distribution of silicate feature strengths among clumpy torus models closely resembles the observed distribution, and the
On the 10 μm Silicate Feature in Active Galactic Nuclei

Science.gov (United States)

Nikutta, Robert; Elitzur, Moshe; Lacy, Mark

2009-12-01

The 10 μm silicate feature observed with Spitzer in active galactic nuclei (AGNs) reveals some puzzling behavior. It (1) has been detected in emission in type 2 sources, (2) shows broad, flat-topped emission peaks shifted toward long wavelengths in several type 1 sources, and (3) is not seen in deep absorption in any source observed so far. We solve all three puzzles with our clumpy dust radiative transfer formalism. Addressing (1), we present the spectral energy distribution (SED) of SST1721+6012, the first type 2 quasar observed to show a clear 10 μm silicate feature in emission. Such emission arises in models of the AGN torus easily when its clumpy nature is taken into account. We constructed a large database of clumpy torus models and performed extensive fitting of the observed SED. We find that the cloud radial distribution varies as r -1.5 and the torus contains 2-4 clouds along radial equatorial rays, each with optical depth at visual ~60-80. The source bolometric luminosity is ~3 × 1012 Lsun. Our modeling suggests that lsim35% of objects with tori sharing these characteristics and geometry would have their central engines obscured. This relatively low obscuration probability can explain the clear appearance of the 10 μm emission feature in SST1721+6012 together with its rarity among other QSO2. Investigating (2), we also fitted the SED of PG1211+143, one of the first type 1 QSOs with a 10 μm silicate feature detected in emission. Together with other similar sources, this QSO appears to display an unusually broadened feature whose peak is shifted toward longer wavelengths. Although this led to suggestions of non-standard dust chemistry in these sources, our analysis fits such SEDs with standard galactic dust; the apparent peak shifts arise from simple radiative transfer effects. Regarding (3), we find additionally that the distribution of silicate feature strengths among clumpy torus models closely resembles the observed distribution, and the feature
The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

Science.gov (United States)

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep
Harry Potter book series - trivial or not?

Directory of Open Access Journals (Sweden)

Brigita Pavšič

2006-12-01

Full Text Available The article explores the extcnt to which the features of trivial literature appear in the Harry Potter series by J. K. Rowling.This is done in comparison with another popular children's series, The Famous Five by Enid Blyton, which was analysed by Igor Saksida. The main focus of the analysis is on the schematic representation of plot, characters and the exotic nature of the setting and time of the stories.
Time series analysis time series analysis methods and applications

CERN Document Server

Rao, Tata Subba; Rao, C R

2012-01-01

The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...
Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

OpenAIRE

Francisco Javier Ordóñez; Daniel Roggen

2016-01-01

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we pro...
EEG feature selection method based on decision tree.

Science.gov (United States)

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.
Recognizing stationary and locomotion activities using combinational of spectral analysis with statistical descriptors features

Science.gov (United States)

Zainudin, M. N. Shah; Sulaiman, Md Nasir; Mustapha, Norwati; Perumal, Thinagaran

2017-10-01

Prior knowledge in pervasive computing recently garnered a lot of attention due to its high demand in various application domains. Human activity recognition (HAR) considered as the applications that are widely explored by the expertise that provides valuable information to the human. Accelerometer sensor-based approach is utilized as devices to undergo the research in HAR since their small in size and this sensor already build-in in the various type of smartphones. However, the existence of high inter-class similarities among the class tends to degrade the recognition performance. Hence, this work presents the method for activity recognition using our proposed features from combinational of spectral analysis with statistical descriptors that able to tackle the issue of differentiating stationary and locomotion activities. The noise signal is filtered using Fourier Transform before it will be extracted using two different groups of features, spectral frequency analysis, and statistical descriptors. Extracted signal later will be classified using random forest ensemble classifier models. The recognition results show the good accuracy performance for stationary and locomotion activities based on USC HAD datasets.
Features Related to Faunal Activity

NARCIS (Netherlands)

Kooistra, M.J.; Pulleman, M.M.

2010-01-01

Soil fauna plays an important role in transporting and altering various soil components, in particular the decomposition of organic matter and the development of soil structure. Fauna-induced features are found in all types of soils and can be so abundant that they determine the nature and intensity
Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification.

Science.gov (United States)

Chung, Jungman; Oh, Wonjoon; Baek, Dongyoub; Ryu, Sunwoong; Lee, Won Gu; Bang, Hyunwoo

2018-02-14

This study presents a series of protocols of designing and manufacturing a glasses-type wearable device that detects the patterns of temporalis muscle activities during food intake and other physical activities. We fabricated a 3D-printed frame of the glasses and a load cell-integrated printed circuit board (PCB) module inserted in both hinges of the frame. The module was used to acquire the force signals, and transmit them wirelessly. These procedures provide the system with higher mobility, which can be evaluated in practical wearing conditions such as walking and waggling. A performance of the classification is also evaluated by distinguishing the patterns of food intake from those physical activities. A series of algorithms were used to preprocess the signals, generate feature vectors, and recognize the patterns of several featured activities (chewing and winking), and other physical activities (sedentary rest, talking, and walking). The results showed that the average F1 score of the classification among the featured activities was 91.4%. We believe this approach can be potentially useful for automatic and objective monitoring of ingestive behaviors with higher accuracy as practical means to treat ingestive problems.
Coding of visual object features and feature conjunctions in the human brain.

Science.gov (United States)

Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

2008-01-01

Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.
Time Series Modelling using Proc Varmax

DEFF Research Database (Denmark)

Milhøj, Anders

2007-01-01

In this paper it will be demonstrated how various time series problems could be met using Proc Varmax. The procedure is rather new and hence new features like cointegration, testing for Granger causality are included, but it also means that more traditional ARIMA modelling as outlined by Box...
Physical Activity Advertisements That Feature Daily Well-Being Improve Autonomy and Body Image in Overweight Women but Not Men

OpenAIRE

Michelle L. Segar; John A. Updegraff; Brian J. Zikmund-Fisher; Caroline R. Richardson

2012-01-01

The reasons for exercising that are featured in health communications brand exercise and socialize individuals about why they should be physically active. Discovering which reasons for exercising are associated with high-quality motivation and behavioral regulation is essential to promoting physical activity and weight control that can be sustained over time. This study investigates whether framing physical activity in advertisements featuring distinct types of goals differentially influences...

Optimizing methods for linking cinematic features to fMRI data.

Science.gov (United States)

Kauttonen, Janne; Hlushchuk, Yevhen; Tikka, Pia

2015-04-15

One of the challenges of naturalistic neurosciences using movie-viewing experiments is how to interpret observed brain activations in relation to the multiplicity of time-locked stimulus features. As previous studies have shown less inter-subject synchronization across viewers of random video footage than story-driven films, new methods need to be developed for analysis of less story-driven contents. To optimize the linkage between our fMRI data collected during viewing of a deliberately non-narrative silent film 'At Land' by Maya Deren (1944) and its annotated content, we combined the method of elastic-net regularization with the model-driven linear regression and the well-established data-driven independent component analysis (ICA) and inter-subject correlation (ISC) methods. In the linear regression analysis, both IC and region-of-interest (ROI) time-series were fitted with time-series of a total of 36 binary-valued and one real-valued tactile annotation of film features. The elastic-net regularization and cross-validation were applied in the ordinary least-squares linear regression in order to avoid over-fitting due to the multicollinearity of regressors, the results were compared against both the partial least-squares (PLS) regression and the un-regularized full-model regression. Non-parametric permutation testing scheme was applied to evaluate the statistical significance of regression. We found statistically significant correlation between the annotation model and 9 ICs out of 40 ICs. Regression analysis was also repeated for a large set of cubic ROIs covering the grey matter. Both IC- and ROI-based regression analyses revealed activations in parietal and occipital regions, with additional smaller clusters in the frontal lobe. Furthermore, we found elastic-net based regression more sensitive than PLS and un-regularized regression since it detected a larger number of significant ICs and ROIs. Along with the ISC ranking methods, our regression analysis proved
Stochastic modeling of neurobiological time series: Power, coherence, Granger causality, and separation of evoked responses from ongoing activity

Science.gov (United States)

Chen, Yonghong; Bressler, Steven L.; Knuth, Kevin H.; Truccolo, Wilson A.; Ding, Mingzhou

2006-06-01

In this article we consider the stochastic modeling of neurobiological time series from cognitive experiments. Our starting point is the variable-signal-plus-ongoing-activity model. From this model a differentially variable component analysis strategy is developed from a Bayesian perspective to estimate event-related signals on a single trial basis. After subtracting out the event-related signal from recorded single trial time series, the residual ongoing activity is treated as a piecewise stationary stochastic process and analyzed by an adaptive multivariate autoregressive modeling strategy which yields power, coherence, and Granger causality spectra. Results from applying these methods to local field potential recordings from monkeys performing cognitive tasks are presented.
A Cross-Sectional Investigation of the Importance of Park Features for Promoting Regular Physical Activity in Parks.

Science.gov (United States)

Costigan, Sarah A; Veitch, Jenny; Crawford, David; Carver, Alison; Timperio, Anna

2017-11-02

Parks in the US and Australia are generally underutilised, and park visitors typically engage in low levels of physical activity (PA). Better understanding park features that may encourage visitors to be active is important. This study examined the perceived importance of park features for encouraging park-based PA and examined differences by sex, age, parental-status and participation in PA. Cross-sectional surveys were completed by local residents ( n = 2775) living near two parks (2013/2015). Demographic variables, park visitation and leisure-time PA were self-reported, respondents rated the importance of 20 park features for encouraging park-based PA in the next fortnight. Chi-square tests of independence examined differences in importance of park features for PA among sub-groups of local residents (sex, age, parental-status, PA). Park features ranked most important for park-based PA were: well maintained (96.2%), feel safe (95.4%), relaxing atmosphere (91.2%), easy to get to (91.7%), and shady trees (90.3%). All subgroups ranked 'well maintained' as most important. Natural and built environment features of parks are important for promoting adults' park-based PA, and should be considered in park (re)design.
Potential of Ranunculus acris L. for biomonitoring trace element contamination of riverbank soils: photosystem II activity and phenotypic responses for two soil series.

Science.gov (United States)

Marchand, Lilian; Lamy, Pierre; Bert, Valerie; Quintela-Sabaris, Celestino; Mench, Michel

2016-02-01

Foliar ionome, photosystem II activity, and leaf growth parameters of Ranunculus acris L., a potential biomonitor of trace element (TE) contamination and phytoavailability, were assessed using two riverbank soil series. R. acris was cultivated on two potted soil series obtained by mixing a TE (Cd, Cu, Pb, and Zn)-contaminated technosol with either an uncontaminated sandy riverbank soil (A) or a silty clay one slightly contaminated by TE (B). Trace elements concentrations in the soil-pore water and the leaves, leaf dry weight (DW) yield, total leaf area (TLA), specific leaf area (SLA), and photosystem II activity were measured for both soil series after a 50-day growth period. As soil contamination increased, changes in soluble TE concentrations depended on soil texture. Increase in total soil TE did not affect the leaf DW yield, the TLA, the SLA, and the photosystem II activity of R. acris over the 50-day exposure. The foliar ionome did not reflect the total and soluble TE concentrations in both soil series. Foliar ionome of R. acris was only effective to biomonitor total and soluble soil Na concentrations in both soil series and total and soluble soil Mo concentrations in the soil series B.
Monoaminergic tone supports conductance correlations and stabilizes activity features in pattern generating neurons of the lobster, Panulirus interruptus

Directory of Open Access Journals (Sweden)

Wulf-Dieter C. Krenz

2015-10-01

Full Text Available Experimental and computational studies demonstrate that different sets of intrinsic and synaptic conductances can give rise to equivalent activity patterns. This is because the balance of conductances, not their absolute values, defines a given activity feature. Activity-dependent feedback mechanisms maintain neuronal conductance correlations and their corresponding activity features. This study demonstrates that tonic nM concentrations of monoamines enable slow, activity-dependent processes that can maintain a correlation between the transient potassium current (IA and the hyperpolarization activated current (Ih over the long-term (i.e., regulatory change persists for hours after removal of modulator. Tonic 5nM DA acted through an RNA interference silencing complex (RISC- and RNA polymerase II-dependent mechanism to maintain a long-term positive correlation between IA and Ih in the lateral pyloric neuron (LP but not in the pyloric dilator neuron (PD. In contrast, tonic 5nM 5HT maintained a RISC-dependent positive correlation between IA and Ih in PD but not LP over the long-term. Tonic 5nM OCT maintained a long-term negative correlation between IA and Ih in PD but not LP; however, it was only revealed when RISC was inhibited. This study also demonstrated that monoaminergic tone can also preserve activity features over the long-term: The timing of LP activity, LP duty cycle and LP spike number per burst were maintained by tonic 5nM DA. The data suggest that low-level monoaminergic tone acts through multiple slow processes to permit cell-specific, activity-dependent regulation of ionic conductances to maintain conductance correlations and their corresponding activity features over the long-term.
A Depth Video-based Human Detection and Activity Recognition using Multi-features and Embedded Hidden Markov Models for Health Care Monitoring Systems

Directory of Open Access Journals (Sweden)

Ahmad Jalal

2017-08-01

Full Text Available Increase in number of elderly people who are living independently needs especial care in the form of healthcare monitoring systems. Recent advancements in depth video technologies have made human activity recognition (HAR realizable for elderly healthcare applications. In this paper, a depth video-based novel method for HAR is presented using robust multi-features and embedded Hidden Markov Models (HMMs to recognize daily life activities of elderly people living alone in indoor environment such as smart homes. In the proposed HAR framework, initially, depth maps are analyzed by temporal motion identification method to segment human silhouettes from noisy background and compute depth silhouette area for each activity to track human movements in a scene. Several representative features, including invariant, multi-view differentiation and spatiotemporal body joints features were fused together to explore gradient orientation change, intensity differentiation, temporal variation and local motion of specific body parts. Then, these features are processed by the dynamics of their respective class and learned, modeled, trained and recognized with specific embedded HMM having active feature values. Furthermore, we construct a new online human activity dataset by a depth sensor to evaluate the proposed features. Our experiments on three depth datasets demonstrated that the proposed multi-features are efficient and robust over the state of the art features for human action and activity recognition.
Advanced nonlinear control of three phase series active power filter

Directory of Open Access Journals (Sweden)

Abouelmahjoub Y.

2014-01-01

Full Text Available The problem of controlling three-phase series active power filter (TPSAPF is addressed in this paper in presence of the perturbations in the voltages of the electrical supply network. The control objective of the TPSAPF is twofold: (i compensation of all voltage perturbations (voltage harmonics, voltage unbalance and voltage sags, (ii regulation of the DC bus voltage of the inverter. A controller formed by two nonlinear regulators is designed, using the Backstepping technique, to provide the above compensation. The regulation of the DC bus voltage of the inverter is ensured by the use of a diode bridge rectifier which its output is in parallel with the DC bus capacitor. The Analysis of controller performances is illustrated by numerical simulation in Matlab/Simulink environment.
Quantifying memory in complex physiological time-series.

Science.gov (United States)

Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.
EEG Eye State Identification Using Incremental Attribute Learning with Time-Series Classification

Directory of Open Access Journals (Sweden)

Ting Wang

2014-01-01

Full Text Available Eye state identification is a kind of common time-series classification problem which is also a hot spot in recent research. Electroencephalography (EEG is widely used in eye state classification to detect human's cognition state. Previous research has validated the feasibility of machine learning and statistical approaches for EEG eye state classification. This paper aims to propose a novel approach for EEG eye state identification using incremental attribute learning (IAL based on neural networks. IAL is a novel machine learning strategy which gradually imports and trains features one by one. Previous studies have verified that such an approach is applicable for solving a number of pattern recognition problems. However, in these previous works, little research on IAL focused on its application to time-series problems. Therefore, it is still unknown whether IAL can be employed to cope with time-series problems like EEG eye state classification. Experimental results in this study demonstrates that, with proper feature extraction and feature ordering, IAL can not only efficiently cope with time-series classification problems, but also exhibit better classification performance in terms of classification error rates in comparison with conventional and some other approaches.
A practical approach to harmonic compensation in power systems-series connection of passive and active filters

OpenAIRE

Fujita, Hideaki; Akagi, Hirofumi

1991-01-01

The authors present a combined system with a passive filter and a small-rated active filter, both connected in series with each other. The passive filter removes load produced harmonics just as a conventional filter does. The active filter plays a role in improving the filtering characteristics of the passive filter. This results in a great reduction of the required rating of the active filter and in eliminating all the limitations faced by using only the passive filter, leading to a practica...
New features of the Helioviewer Project

Science.gov (United States)

Ireland, J.; Zahniy, S.; Nicula, B.; Mueller, D.; Felix, S.; Verstringe, F.; Bourgoignie, B.

2016-12-01

This year saw the release of major new upgrades to the capabilities of helioviewer.org and JHelioviewer. The helioviewer.org interface was completely re-designed, and now provides image and feature/event time-lines and data download capabilities. JHelioviewer introduced interactive time-series, the ability to query different servers for different data, and image reprojection. We introduce the new features of these software releases and give use cases. We will summarize our latest usage statistics, and discuss what's coming up next for the Helioviewer Project. We will also be soliciting bug reports, requests for new features and comments on the effectiveness of helioviewer.org and JHelioviewer. What would you like to see next from the Helioviewer Project?
Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

Science.gov (United States)

Swartz, R. Andrew

2013-01-01

This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136
Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

Directory of Open Access Journals (Sweden)

Wenjia Liu

2013-01-01

Full Text Available This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate.
Measurements of spatial population synchrony: influence of time series transformations.

Science.gov (United States)

Chevalier, Mathieu; Laffaille, Pascal; Ferdy, Jean-Baptiste; Grenouillet, Gaël

2015-09-01

Two mechanisms have been proposed to explain spatial population synchrony: dispersal among populations, and the spatial correlation of density-independent factors (the "Moran effect"). To identify which of these two mechanisms is driving spatial population synchrony, time series transformations (TSTs) of abundance data have been used to remove the signature of one mechanism, and highlight the effect of the other. However, several issues with TSTs remain, and to date no consensus has emerged about how population time series should be handled in synchrony studies. Here, by using 3131 time series involving 34 fish species found in French rivers, we computed several metrics commonly used in synchrony studies to determine whether a large-scale climatic factor (temperature) influenced fish population dynamics at the regional scale, and to test the effect of three commonly used TSTs (detrending, prewhitening and a combination of both) on these metrics. We also tested whether the influence of TSTs on time series and population synchrony levels was related to the features of the time series using both empirical and simulated time series. For several species, and regardless of the TST used, we evidenced a Moran effect on freshwater fish populations. However, these results were globally biased downward by TSTs which reduced our ability to detect significant signals. Depending on the species and the features of the time series, we found that TSTs could lead to contradictory results, regardless of the metric considered. Finally, we suggest guidelines on how population time series should be processed in synchrony studies.
Visual Search for Feature and Conjunction Targets with an Attention Deficit

OpenAIRE

Arguin, Martin; Joanette, Yves; Cavanagh, Patrick

1993-01-01

Brain-damaged subjects who had previously been identified as suffering from a visual attention deficit for contralesional stimulation were tested on a series of visual search tasks. The experiments examined the hypothesis that the processing of single features is preattentive but that feature integration, necessary for the correct perception of conjunctions of features, requires attention (Treisman & Gelade, 1980 Treisman & Sato, 1990). Subjects searched for a feature target (orientation or c...
A grid-voltage-sensorless resistive active power filter with series LC-filter

DEFF Research Database (Denmark)

Bai, Haofeng; Wang, Xiongfei; Blaabjerg, Frede

2017-01-01

Voltage-sensorless control has been investigated for Voltage Source Inverters (VSIs) for many years due to the reduced system cost and potentially improved system reliability. The VSI based Resistive Active Power Filters (R-APFs) are now widely used to prevent the harmonic resonance in power...... distribution network, for which the voltage sensors are needed in order to obtain the current reference. In this paper a grid-voltage-sensorless control strategy is proposed for the R-APF with series LC-filter. Unlike the traditional resistance emulation method, this proposed control method re...
A Grid-Voltage-Sensorless Resistive Active Power Filter with Series LC-Filter

DEFF Research Database (Denmark)

Bai, Haofeng; Wang, Xiongfei; Blaabjerg, Frede

2018-01-01

Voltage-sensorless control has been investigated for Voltage Source Inverters (VSIs) for many years due to the reduced system cost and potentially improved system reliability. The VSI based Resistive Active Power Filters (R-APFs) are now widely used to prevent the harmonic resonance in power...... distribution network, for which the voltage sensors are needed in order to obtain the current reference. In this paper a grid-voltage-sensorless control strategy is proposed for the R-APF with series LC-filter. Unlike the traditional resistance emulation method, this proposed control method re...
The Economics of the Duration of the Baseball World Series

Science.gov (United States)

Cassuto, Alexander E.; Lowenthal, Franklin

2007-01-01

This note examines some statistical features of the major league baseball World Series. We show that, based upon actual historical data, we cannot reject the hypothesis that the two World Series teams are evenly matched. Yet, we can also calculate the relative strengths of the teams that would best match the actual outcomes, and we find that those…
On-off intermittency in time series of spontaneous paroxysmal activity in rats with genetic absence epilepsy

International Nuclear Information System (INIS)

Hramov, Alexander; Koronovskii, Alexey A.; Midzyanovskaya, I.S.; Sitnikova, E.; Rijn, C.M. van

2006-01-01

In the present paper we consider the on-off intermittency phenomena observed in time series of spontaneous paroxysmal activity in rats with genetic absence epilepsy. The method to register and analyze the electroencephalogram with the help of continuous wavelet transform is also suggested
Synthesis, Leishmanicidal Activity and Theoretical Evaluations of a Series of Substituted bis-2-Hydroxy-1,4-Naphthoquinones

Directory of Open Access Journals (Sweden)

Morgana V. de Araújo

2014-09-01

Full Text Available A series of eight substituted bis-2-hydroxy-1,4-naphthoquinone derivatives was synthesized through lawsone condensation with various aromatic and aliphatic aldehydes under mild acidic conditions. The title compounds were evaluated for antileishmanial activity in vitro against Leishmania amazonensis and Leishmania braziliensis promastigotes; six compounds showed good activity without significant toxic effects. The compound with the highest activity was used for an in vivo assay with Leishmania amazonensis.

Investment Company Series and Class Information

Data.gov (United States)

Securities and Exchange Commission — The Series and Class Report provides basic identification information for all active registered investment company series and classes that have been issued IDs by...
Deciphering structure-activity relationships in a series of Tat/TAR inhibitors.

Science.gov (United States)

Pascale, Lise; González, Alejandro López; Di Giorgio, Audrey; Gaysinski, Marc; Teixido Closa, Jordi; Tejedor, Roger Estrada; Azoulay, Stéphane; Patino, Nadia

2016-11-01

A series of pentameric "Polyamide Amino Acids" (PAAs) compounds derived from the same trimeric precursor have been synthesized and investigated as HIV TAR RNA ligands, in the absence and in the presence of a Tat fragment. All PAAs bind TAR with similar sub-micromolar affinities but their ability to compete efficiently with the Tat fragment strongly differs, IC50 ranging from 35 nM to >2 μM. While NMR and CD studies reveal that all PAA interact with TAR at the same site and induce globally the same RNA conformational change upon binding, a comparative thermodynamic study of PAA/TAR equilibria highlights distinct TAR binding modes for Tat competitor and non-competitor PAAs. This led us to suggest two distinct interaction modes that have been further validated by molecular modeling studies. While the binding of Tat competitor PAAs induces a contraction at the TAR bulge region, the binding of non-competitor ones widens it. This could account for the distinct PAA ability to compete with Tat fragment. Our work illustrates how comparative thermodynamic studies of a series of RNA ligands of same chemical family are of value for understanding their binding modes and for rationalizing structure-activity relationships.
The morphing of geographical features by Fourier transformation.

Science.gov (United States)

Li, Jingzhong; Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.
Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2015-01-01

Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both
Feature-specific encoding flexibility in visual working memory.

Directory of Open Access Journals (Sweden)

Aki Kondo

Full Text Available The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location, and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape can be flexibly added to object representations.
Feature-specific encoding flexibility in visual working memory.

Science.gov (United States)

Kondo, Aki; Saiki, Jun

2012-01-01

The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location), and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape) can be flexibly added to object representations.
New series active power filter for computers loads and small non-linear loads

Energy Technology Data Exchange (ETDEWEB)

Tarnini, M.Y. [Hariri Canadian Univ., Meshref (Lebanon)

2009-07-01

This paper proposed the use of a single-phase series active power filter to reduce voltage total harmonic distortion and provide improved power quality. Control schemes were developed using simple control algorithms and a reduced number of current transducers. The circuit was comprised of a power supply and zero crossing detector; a hall-effect current sensor and signal conditioning circuit; a microcontroller circuit; a driving circuit; and an inverter bridge. The filter corrected fundamental and sinusoidal voltage amplitudes. The amplitude of the fundamental current in the series filter was controlled using a microcontroller placed between the load voltage and a pre-established reference point. Experiments were conducted to test the source voltage and source current after compensation using a prototype of the filter. The control system provided effective correction of the power factor and harmonic distortion, and reached steady state in approximately 2 cycles. It was concluded that the compensator can also be adapted for use in 3-phase systems. 13 refs., 1 tab., 14 figs.
INTERACTION LEVEL OF SPEAKING ACTIVITIES IN A COURSEBOOK SERIES OF TEACHING TURKISH AS A FOREIGN LANGUAGE

OpenAIRE

YAVUZ KIRIK, Muazzez

2015-01-01

Informed by the principles of communicative foreign language teaching, this study focuses on the interaction level of speaking activities in the coursebook series of ‘İstanbul- Yabancılar İçin Türkçe Ders Kitabı’. To this end, the study analyzed firstly the rate of two-way speech to one-way speech among speaking activities and then the characteristics of two-way activities were explored with a focus on their compatibility with the nature of real interaction as described in the relevant litera...
Corporate governance and audit features: SMEs evidence

OpenAIRE

Al-Najjar, Basil

2018-01-01

Purpose\\ud The purpose of this paper is to investigate the effect of corporate governance factors on audit features, namely, audit fees and the selection of Big 4 audit firms within the UK SMEs context.\\ud \\ud Design/methodology/approach\\ud The author uses different regression models to investigate the impact of corporate governance characteristics on audit features, and employs cross-sectional time series models as well as two-stage least squares technique. In addition, the author has used l...
A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

Science.gov (United States)

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

2018-02-01

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

Science.gov (United States)

: Smart Grid and Beyond John McDonald, Director, Technical Strategy and Policy Development, General Control Technologies Workshop Series In July 2015, NREL's energy systems integration team hosted workshops the Energy Systems Integration Facility (ESIF) and included a technology showcase featuring projects
FINE MAGNETIC FEATURES AND CHIRALITY IN SOLAR ACTIVE REGION NOAA 10930

International Nuclear Information System (INIS)

Zhang Hongqi

2010-01-01

In this paper, we present fine magnetic features near the magnetic inversion line in the solar active region NOAA 10930. The high-resolution vector magnetograms obtained by Hinode allow detailed analyses around magnetic fibrils in the active region. The analyses are based on the fact that the electric current density can be divided into two components: the shear component caused by the magnetic inhomogeneity and the twist component caused by the magnetic field twist. The relationships between magnetic field, electric current density, and its two components are examined. It is found that the individual magnetic fibrils are dominated by the current density component caused by the magnetic inhomogeneity, while the large-scale magnetic region is generally dominated by the electric current component associated with the magnetic twist. The microstructure of the magnetic field in the solar atmosphere is far from the force-free field. The current mainly flows around the magnetic flux fibrils in the active regions.
Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

Science.gov (United States)

Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M

2014-01-01

Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].
An Improved Rotation Forest for Multi-Feature Remote-Sensing Imagery Classification

Directory of Open Access Journals (Sweden)

Yingchang Xiu

2017-11-01

Full Text Available Multi-feature, especially multi-temporal, remote-sensing data have the potential to improve land cover classification accuracy. However, sometimes it is difficult to utilize all the features efficiently. To enhance classification performance based on multi-feature imagery, an improved rotation forest, combining Principal Component Analysis (PCA and a boosting naïve Bayesian tree (NBTree, is proposed. First, feature extraction was carried out with PCA. The feature set was randomly split into several disjoint subsets; then, PCA was applied to each subset, and new training data for linear extracted features based on original training data were obtained. These steps were repeated several times. Second, based on the new training data, a boosting naïve Bayesian tree was constructed as the base classifier, which aims to achieve lower prediction error than a decision tree in the original rotation forest. At the classification phase, the improved rotation forest has two-layer voting. It first obtains several predictions through weighted voting in a boosting naïve Bayesian tree; then, the first-layer vote predicts by majority to obtain the final result. To examine the classification performance, the improved rotation forest was applied to multi-feature remote-sensing images, including MODIS Enhanced Vegetation Index (EVI imagery time series, MODIS Surface Reflectance products and ancillary data in Shandong Province for 2013. The EVI imagery time series was preprocessed using harmonic analysis of time series (HANTS to reduce the noise effects. The overall accuracy of the final classification result was 89.17%, and the Kappa coefficient was 0.71, which outperforms the original rotation forest and other classifier ensemble results, as well as the NASA land cover product. However, this new algorithm requires more computational time, meaning the efficiency needs to be further improved. Generally, the improved rotation forest has a potential advantage in
Picture archiving and communications system EFPACS series

International Nuclear Information System (INIS)

Hirasawa, Teiji; Mukasa, Minoru; Hiramatsu, Jun-ichi

1989-01-01

Fuji EFPACS (Effective Fuji PACS) is a picture archiving and communications system which efficiently executes centralized management of quantities of image data produced in a hospital. Main features of this system are high-speed retrieval and display function resulting from high-grade imaging technology. This system also strongly supports picture management for multi-modalities, picture storage, and education. EFPACS-500 and EFPACS-1000 series are available according to a system scale. An optimal system configuration can be obtained in a building-up style. This paper describes the features and performance of the EFPACS. (author)
Activation barriers for series of exothermic homologous reactions. V. Boron group diatomic species reactions

Science.gov (United States)

Blue, Alan S.; Belyung, David P.; Fontijn, Arthur

1997-09-01

Semiempirical configuration interaction (SECI) theory is used to predict activation barriers E, as defined by k(T)=ATn exp(-E/RT). Previously SECI has been applied to homologous series of oxidation reactions of s1, s2, and s2p1 metal atoms. Here it is extended to oxidation reactions of diatomic molecules containing one s2p1 atom. E values are calculated for the reactions of BH, BF, BCl, AlF, AlCl, AlBr, GaF, GaI, InCl, InBr, InI, TlF, TlCl, TlBr, and TlI with O2, CO2, SO2, or N2O. These values correlate with the sums of the ionization potentials and Σ-Π promotion energies of the former minus the electron affinities of the latter. In the earlier work n was chosen somewhat arbitrarily, which affected the absolute values of E. Here it is shown that examination of available experimental and theoretical results allows determination of the best values of n. Using this approach yields n=1.9 for the present series. For the seven reactions which have been studied experimentally, the average deviation of the SECI activation barrier prediction from experiment is 4.0 kJ mol-1. Energy barriers are calculated for another 52 reactions.
Long Range Dependence Prognostics for Bearing Vibration Intensity Chaotic Time Series

Directory of Open Access Journals (Sweden)

Qing Li

2016-01-01

Full Text Available According to the chaotic features and typical fractional order characteristics of the bearing vibration intensity time series, a forecasting approach based on long range dependence (LRD is proposed. In order to reveal the internal chaotic properties, vibration intensity time series are reconstructed based on chaos theory in phase-space, the delay time is computed with C-C method and the optimal embedding dimension and saturated correlation dimension are calculated via the Grassberger–Procaccia (G-P method, respectively, so that the chaotic characteristics of vibration intensity time series can be jointly determined by the largest Lyapunov exponent and phase plane trajectory of vibration intensity time series, meanwhile, the largest Lyapunov exponent is calculated by the Wolf method and phase plane trajectory is illustrated using Duffing-Holmes Oscillator (DHO. The Hurst exponent and long range dependence prediction method are proposed to verify the typical fractional order features and improve the prediction accuracy of bearing vibration intensity time series, respectively. Experience shows that the vibration intensity time series have chaotic properties and the LRD prediction method is better than the other prediction methods (largest Lyapunov, auto regressive moving average (ARMA and BP neural network (BPNN model in prediction accuracy and prediction performance, which provides a new approach for running tendency predictions for rotating machinery and provide some guidance value to the engineering practice.
Geomorphological features of active tectonics and ongoing ...

Indian Academy of Sciences (India)

earthquakes (magnitude 1.0–3.0) frequently occur in the region and hypocenters of these earthquakes are ... movement of Indian landmass and its collision with ... within the Eurasian Plate (Avouac and Tapponnier .... Description of ... (a) Terrace deposition in Dharchula (India) and Darchula (Nepal) side; (b) series of three ...
Time Series Momentum

DEFF Research Database (Denmark)

Moskowitz, Tobias J.; Ooi, Yao Hua; Heje Pedersen, Lasse

2012-01-01

We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial...... under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities...
[Features of adaptive responses in right-handers and left-handers, and their relationship to the functional activity of the brain].

Science.gov (United States)

Barkar, A A; Markina, L D

2014-01-01

In the article there is considered the relationship between adaptation state of the organism and features of bioelectric activity of the brain in right-handers and left-handers. Practically healthy persons of both genders, 23-45 years of age, with the chronic stress disorder were examined. Adaptation status was evaluated with a computer software "Anti-stress", features of bioelectric brain activity were detected by means of spectral and coherent EEG analysis, also the character of motor and sensory asymmetries was determined. The obtained data showed that the response of the organism to excitators of varying strength is a system one and manifested at different levels; adaptation status and bioelectrical activity in right-handers and left-handers have features.

Oscillatory neuronal activity reflects lexical-semantic feature integration within and across sensory modalities in distributed cortical networks.

Science.gov (United States)

van Ackeren, Markus J; Schneider, Till R; Müsch, Kathrin; Rueschemeyer, Shirley-Ann

2014-10-22

Research from the previous decade suggests that word meaning is partially stored in distributed modality-specific cortical networks. However, little is known about the mechanisms by which semantic content from multiple modalities is integrated into a coherent multisensory representation. Therefore we aimed to characterize differences between integration of lexical-semantic information from a single modality compared with two sensory modalities. We used magnetoencephalography in humans to investigate changes in oscillatory neuronal activity while participants verified two features for a given target word (e.g., "bus"). Feature pairs consisted of either two features from the same modality (visual: "red," "big") or different modalities (auditory and visual: "red," "loud"). The results suggest that integrating modality-specific features of the target word is associated with enhanced high-frequency power (80-120 Hz), while integrating features from different modalities is associated with a sustained increase in low-frequency power (2-8 Hz). Source reconstruction revealed a peak in the anterior temporal lobe for low-frequency and high-frequency effects. These results suggest that integrating lexical-semantic knowledge at different cortical scales is reflected in frequency-specific oscillatory neuronal activity in unisensory and multisensory association networks. Copyright © 2014 the authors 0270-6474/14/3314318-06$15.00/0.
Antidiabetic Activity Test of Ethanolic Seri Leave’s (Muntingia Calabura L.) Extract in Male Rats Induced by Alloxan

OpenAIRE

Herlina Herlina; Annisa Amriani; Indah Solihah; Rizky Sintya

2018-01-01

Antidiabetic activity test of ethanol extract of seri leave (Muntingia calabura L.) rats induced by alloxan has been done. Male wistar albino rats are used as animal models which divided into 6 groups, normal group (aquadest), negative control group (Na CMC 0,5%), positive control group (glibenclamide 0,43 mg/200 gBB), and 1, 2, and 3 treatment groups (ethanol extract of seri leave 65, 130, dan 260 mg/kgBB). Rats blood glucose level after induced intraperitoneally by alloxan 130 mg/kgBB can b...
Assessing ionospheric activity by long time series of GNSS signals: the search of possible connection with seismicity

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Galeandro, Angelo; Mancini, Francesco; De Giglio, Michaela; Barbarella, Maurizio

2014-05-01

The modifications of some atmospheric physical properties prior to a high magnitude earthquake were recently debated in the frame of the Lithosphere-Atmosphere-Ionosphere (LAI) Coupling model. Among this variety of phenomena, the ionization of air at the ionospheric levels due to leaking of gases from earth crust through the analysis of long time series of GNSS (Global Navigation Satellite System) signals was investigated in this work. Several authors used the dispersive properties of the ionospheric strata towards the GNSS signals to detect possible ionospheric anomalies over areas affected by earthquakes and some evidences were encountered. However, the spatial scale and temporal domains over which such disturbances come into evidence is still a controversial item. Furthermore, the correspondence by chance between ionospheric disturbances and relevant seismic activity is even more difficult to model whenever the reference time period and spatial extent of investigation are confined. Problems could also arise from phenomena due to solar activity (now at culmination within the 11 years-long solar cycle) because such global effects could reduce the ability to detect disturbances at regional or local spatial scale. In this work, two case studies were investigated. The first one focuses on the M = 6.3 earthquake occurred on April 6, 2009, close to the city of L'Aquila (Abruzzo, Italy). The second concerns the M = 5.9 earthquake occurred on May 20, 2012, between the cities of Ferrara and Modena (Emilia Romagna, Italy). To investigate possible connections between the ionospheric activity and seismicity for such events, a five-year (2008-2012) long series of high resolution ionospheric maps was used. These maps were produced by authors from GNSS data collected by permanent stations uniformly distributed around the epicenters and allowed to assess the ionospheric activity through the analysis of the TEC (Total Electron Content). To avoid the influence of solar activity
Investigation of Equivalent Unsprung Mass and Nonlinear Features of Electromagnetic Actuated Active Suspension

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Jun Yin

2015-01-01

Full Text Available Electromagnetic actuated active suspension benefits active control and energy harvesting from vibration at the same time. However, the rotary type electromagnetic actuated active suspension introduces a significant extra mass on the unsprung mass due to the inertia of the rotating components of the actuator. The magnitude of the introduced unsprung mass is studied based on a gearbox type actuator and a ball screw type actuator. The geometry of the suspension and the actuator also influence the equivalent unsprung mass significantly. The suspension performance simulation or control logic derived should take this equivalent unsprung mass into account. Besides, an extra force should be compensated due to the nonlinear features of the suspension structure and it is studied. The active force of the actuator should compensate this extra force. The discovery of this paper provides a fundamental for evaluating the rotary type electromagnetic actuated active suspension performance and control strategy derived as well as controlling the electromagnetic actuated active suspension more precisely.
Features of influence of sports activities on the identity of students

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Sutula Vasilij

2017-02-01

Full Text Available Purpose: the definition of features of influence of sports activities on the identity of sportsmen. Material & Methods: the special surveys of students and teachers of KhSAPC, and also students, who train in sports club "Politekhnik", and the students who are engaged in sports sections NLA were conducted for the solution of purposes. Results: the most important qualities of the personality which sports activities influence are: formation of "confidence", "emotional stability", and "orientation to achievement" at sportsmen. According to most of the interviewed sportsmen and experts, the authority of the coach is not significant factor which influences the identity of sportsmen. Conclusions: it is established as a result of the conducted researches that sports activities most of all influence the formation of confidence, emotional stability and orientation to achievement at sportsmen. Results of the research demonstrate also that the identity of the sportsman is most influenced by the competitive relationship which develops in the course of competitive activity. Results of the research also indicate disturbing tendency which is shown that most of sportsmen connect the end of their sports career with injuries.
Iniencephaly: Radiological and pathological features of a series of three cases

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Panduranga Chikkannaiah

2014-01-01

Full Text Available Iniencephaly is a rare form of neural tube defect with an incidence of 0.1-10 in 10,000 pregnancies. It is characterized by the presence of occipital bone defects at foramen magnum, fixed retroflexion of head, spinal dysmorphism, and lordosis of cervicothoracic vertebrae. It is usually associated with central nervous system, gastrointestinal, and cardiovascular anomalies. We present radiological and autopsy findings in a series of 3 cases of iniencephaly (gestational ages 29.3, 23, and 24 weeks first fetus in addition showed omphalocele, pulmonary hypoplasia, two lobes in right lung, accessory spleen, atrial septal defect, bilateral clubfoot, ambiguous genitalia, and single umbilical artery. Second fetus was a classical case of iniencephaly apertus with spina bifida. Third fetus had colpocephaly and bifid spine.
The use of synthetic input sequences in time series modeling

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Oliveira, Dair Jose de; Letellier, Christophe; Gomes, Murilo E.D.; Aguirre, Luis A.

2008-01-01

In many situations time series models obtained from noise-like data settle to trivial solutions under iteration. This Letter proposes a way of producing a synthetic (dummy) input, that is included to prevent the model from settling down to a trivial solution, while maintaining features of the original signal. Simulated benchmark models and a real time series of RR intervals from an ECG are used to illustrate the procedure
Antidiabetic Activity Test of Ethanolic Seri Leave’s (Muntingia Calabura L. Extract in Male Rats Induced by Alloxan

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Herlina Herlina

2018-01-01

Full Text Available Antidiabetic activity test of ethanol extract of seri leave (Muntingia calabura L. rats induced by alloxan has been done. Male wistar albino rats are used as animal models which divided into 6 groups, normal group (aquadest, negative control group (Na CMC 0,5%, positive control group (glibenclamide 0,43 mg/200 gBB, and 1, 2, and 3 treatment groups (ethanol extract of seri leave 65, 130, dan 260 mg/kgBB. Rats blood glucose level after induced intraperitoneally by alloxan 130 mg/kgBB can be stated as diabetes when >200 mg/dL. Preprandial blood glucose levels are measured using DTN-410-K photometer, on day 0, 5, 10, and 15. The average result of AUC0-15 and percentage of decreasing blood glucose level for positive control group are 2732,5 and 37,43%, and 3 treatment groups (65 mg/kgBB, 130 mg/kgBB, and 260 mg/kgBB 3105 and 28,90%; 2962,5 and 32,16%; 2810 and 35,66%. This point indicated that the ethanol extract of seri leave has an antidiabetic activity and there is no significant difference compared with glibenclamide (p<0,05. Percentage of blood glucose decrease level the third treatment group there is no significant difference compare with positive control group. According to the relation between percentage of blood glucose decrease level with dose, value of ED50 of ethanol extract of seri leave is 692,424 mg/kgBB.
Land Cover Classification Using Integrated Spectral, Temporal, and Spatial Features Derived from Remotely Sensed Images

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Yongguang Zhai

2018-03-01

Full Text Available Obtaining accurate and timely land cover information is an important topic in many remote sensing applications. Using satellite image time series data should achieve high-accuracy land cover classification. However, most satellite image time-series classification methods do not fully exploit the available data for mining the effective features to identify different land cover types. Therefore, a classification method that can take full advantage of the rich information provided by time-series data to improve the accuracy of land cover classification is needed. In this paper, a novel method for time-series land cover classification using spectral, temporal, and spatial information at an annual scale was introduced. Based on all the available data from time-series remote sensing images, a refined nonlinear dimensionality reduction method was used to extract the spectral and temporal features, and a modified graph segmentation method was used to extract the spatial features. The proposed classification method was applied in three study areas with land cover complexity, including Illinois, South Dakota, and Texas. All the Landsat time series data in 2014 were used, and different study areas have different amounts of invalid data. A series of comparative experiments were conducted on the annual time-series images using training data generated from Cropland Data Layer. The results demonstrated higher overall and per-class classification accuracies and kappa index values using the proposed spectral-temporal-spatial method compared to spectral-temporal classification methods. We also discuss the implications of this study and possibilities for future applications and developments of the method.
Feature Selection Methods for Zero-Shot Learning of Neural Activity

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Carlos A. Caceres

2017-06-01

Full Text Available Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.
Music-induced emotions can be predicted from a combination of brain activity and acoustic features.

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Daly, Ian; Williams, Duncan; Hallowell, James; Hwang, Faustina; Kirke, Alexis; Malik, Asad; Weaver, James; Miranda, Eduardo; Nasuto, Slawomir J

2015-12-01

It is widely acknowledged that music can communicate and induce a wide range of emotions in the listener. However, music is a highly-complex audio signal composed of a wide range of complex time- and frequency-varying components. Additionally, music-induced emotions are known to differ greatly between listeners. Therefore, it is not immediately clear what emotions will be induced in a given individual by a piece of music. We attempt to predict the music-induced emotional response in a listener by measuring the activity in the listeners electroencephalogram (EEG). We combine these measures with acoustic descriptors of the music, an approach that allows us to consider music as a complex set of time-varying acoustic features, independently of any specific music theory. Regression models are found which allow us to predict the music-induced emotions of our participants with a correlation between the actual and predicted responses of up to r=0.234,pmusic induced emotions can be predicted by their neural activity and the properties of the music. Given the large amount of noise, non-stationarity, and non-linearity in both EEG and music, this is an encouraging result. Additionally, the combination of measures of brain activity and acoustic features describing the music played to our participants allows us to predict music-induced emotions with significantly higher accuracies than either feature type alone (p<0.01). Copyright © 2015 Elsevier Inc. All rights reserved.
Predicting delayed cerebral ischemia after subarachnoid hemorrhage using physiological time series data.

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Park, Soojin; Megjhani, Murad; Frey, Hans-Peter; Grave, Edouard; Wiggins, Chris; Terilli, Kalijah L; Roh, David J; Velazquez, Angela; Agarwal, Sachin; Connolly, E Sander; Schmidt, J Michael; Claassen, Jan; Elhadad, Noemie

2018-03-20

To develop and validate a prediction model for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH) using a temporal unsupervised feature engineering approach, demonstrating improved precision over standard features. 488 consecutive SAH admissions from 2006 to 2014 to a tertiary care hospital were included. Models were trained on 80%, while 20% were set aside for validation testing. Baseline information and standard grading scales were evaluated: age, sex, Hunt Hess grade, modified Fisher Scale (mFS), and Glasgow Coma Scale (GCS). An unsupervised approach applying random kernels was used to extract features from physiological time series (systolic and diastolic blood pressure, heart rate, respiratory rate, and oxygen saturation). Classifiers (Partial Least Squares, linear and kernel Support Vector Machines) were trained on feature subsets of the derivation dataset. Models were applied to the validation dataset. The performances of the best classifiers on the validation dataset are reported by feature subset. Standard grading scale (mFS): AUC 0.58. Combined demographics and grading scales: AUC 0.60. Random kernel derived physiologic features: AUC 0.74. Combined baseline and physiologic features with redundant feature reduction: AUC 0.77. Current DCI prediction tools rely on admission imaging and are advantageously simple to employ. However, using an agnostic and computationally inexpensive learning approach for high-frequency physiologic time series data, we demonstrated that our models achieve higher classification accuracy.
Acute ischaemic stroke prediction from physiological time series patterns

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Qing Zhang,

2013-05-01

Full Text Available BackgroundStroke is one of the major diseases with human mortality. Recent clinical research has indicated that early changes in common physiological variables represent a potential therapeutic target, thus the manipulation of these variables may eventually yield an effective way to optimise stroke recovery.AimsWe examined correlations between physiological parameters of patients during the first 48 hours after a stroke, and their stroke outcomes after 3 months. We wanted to discover physiological determinants that could be used to improve health outcomes by supporting the medical decisions that need to be made early on a patient’s stroke experience.Method We applied regression-based machine learning techniques to build a prediction algorithm that can forecast 3-month outcomes from initial physiological time series data during the first 48 hours after stroke. In our method, not only did we use statistical characteristics as traditional prediction features, but also we adopted trend patterns of time series data as new key features.ResultsWe tested our prediction method on a real physiological data set of stroke patients. The experiment results revealed an average high precision rate: 90%. We also tested prediction methods only considering statistical characteristics of physiological data, and concluded an average precision rate: 71%.ConclusionWe demonstrated that using trend pattern features in prediction methods improved the accuracy of stroke outcome prediction. Therefore, trend patterns of physiological time series data have an important role in the early treatment of patients with acute ischaemic stroke.
Is the Binding of Visual Features in Working Memory Resource-Demanding?

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Allen, Richard J.; Baddeley, Alan D.; Hitch, Graham J.

2006-01-01

The episodic buffer component of working memory is assumed to play a role in the binding of features into chunks. A series of experiments compared memory for arrays of colors or shapes with memory for bound combinations of these features. Demanding concurrent verbal tasks were used to investigate the role of general attentional processes,…
COG11.1 description, new features, and development activities

International Nuclear Information System (INIS)

Buck, R.M.; Heinrichs, D.P.; Lee, C.K.; Lent, E.M.

2013-01-01

COG is a modern, full-featured, Monte Carlo radiation transport code, developed by Lawrence Livermore National Laboratory (LLNL), which provides accurate answers to complex shielding, criticality, and activation problems. COG uses Monte Carlo methods to solve the Boltzmann transport equation for particles traveling through arbitrary 3-dimensional problems. Neutrons, photons, electrons, and protons can be transported. Electron transport uses the EGS transport kernel. The article indicates all the data libraries that are used by COG for the transport of neutrons, photons and protons. COG is written for LINUX PC/Workstations and Windows 7 and Windows XP PC/Workstations. The programming languages used are Fortran77 (99%) and C (1%). The latest COG code version is COG11.1BETA2. This version is available from the Radiation Shielding Information Computer Center and the Nuclear Energy Agency Data Bank
Disruption of visual feature binding in working memory.

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Ueno, Taiji; Allen, Richard J; Baddeley, Alan D; Hitch, Graham J; Saito, Satoru

2011-01-01

In a series of five experiments, we studied the effect of a visual suffix on the retention in short-term visual memory of both individual visual features and objects involving the binding of two features. Experiments 1A, 1B, and 2 involved suffixes consisting of features external to the to-be-remembered set and revealed a modest but equivalent disruption on individual and bound feature conditions. Experiments 3A and 3B involved suffixes comprising features that could potentially have formed part of the to-be-remembered set (but did not on that trial). Both experiments showed greater disruption of retention for objects comprising bound features than for their individual features. The results are interpreted as differentiating two components of suffix interference, one affecting memory for features and bindings equally, the other affecting memory for bindings. The general component is tentatively identified with the attentional cost of operating a filter to prevent the suffix from entering visual working memory, whereas the specific component is attributed to the particular fragility of bound representations when the filter fails.
Sending and Receiving Text Messages with Sexual Content: Relations with Early Sexual Activity and Borderline Personality Features in Late Adolescence.

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Brinkley, Dawn Y; Ackerman, Robert A; Ehrenreich, Samuel E; Underwood, Marion K

2017-05-01

This research examined adolescents' written text messages with sexual content to investigate how sexting relates to sexual activity and borderline personality features. Participants (N = 181, 85 girls) completed a measure of borderline personality features prior to 10 th grade and were subsequently given smartphones configured to capture the content of their text messages. Four days of text messaging were micro-coded for content related to sex. Following 12 th grade, participants reported on their sexual activity and again completed a measure of borderline personality features. Results showed that engaging in sexting at age 16 was associated with reporting an early sexual debut, having sexual intercourse experience, having multiple sex partners, and engaging in drug use in combination with sexual activity two years later. Girls engaging in sex talk were more likely to have had sexual intercourse by age 18. Text messaging about hypothetical sex in grade 10 also predicted borderline personality features at age 18. These findings suggest that sending text messages with sexual content poses risks for adolescents. Programs to prevent risky sexual activity and to promote psychological health could be enhanced by teaching adolescents to use digital communication responsibly.
Sending and Receiving Text Messages with Sexual Content: Relations with Early Sexual Activity and Borderline Personality Features in Late Adolescence

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Brinkley, Dawn Y.; Ackerman, Robert A.; Ehrenreich, Samuel E.; Underwood, Marion K.

2017-01-01

This research examined adolescents’ written text messages with sexual content to investigate how sexting relates to sexual activity and borderline personality features. Participants (N = 181, 85 girls) completed a measure of borderline personality features prior to 10th grade and were subsequently given smartphones configured to capture the content of their text messages. Four days of text messaging were micro-coded for content related to sex. Following 12th grade, participants reported on their sexual activity and again completed a measure of borderline personality features. Results showed that engaging in sexting at age 16 was associated with reporting an early sexual debut, having sexual intercourse experience, having multiple sex partners, and engaging in drug use in combination with sexual activity two years later. Girls engaging in sex talk were more likely to have had sexual intercourse by age 18. Text messaging about hypothetical sex in grade 10 also predicted borderline personality features at age 18. These findings suggest that sending text messages with sexual content poses risks for adolescents. Programs to prevent risky sexual activity and to promote psychological health could be enhanced by teaching adolescents to use digital communication responsibly. PMID:28824224
Activities for Studying Ponds (Limnology), Grade Level 5-6. Environmental Education Series, Bulletin No. 247-D.

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Montgomery County Public Schools, Rockville, MD.

This bulletin is one in a series of environmental education activity guides for grades K-12, developed and field-tested by teachers in the Montgomery County (Maryland) Public Schools. Primarily for use in the middle grades four through six, the guides are not intended to constitute complete units in themselves. They are, rather, a compilation of…
Feature Selection and Blind Source Separation in an EEG-Based Brain-Computer Interface

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Michael H. Thaut

2005-11-01

Full Text Available Most EEG-based BCI systems make use of well-studied patterns of brain activity. However, those systems involve tasks that indirectly map to simple binary commands such as Ã¢Â€ÂœyesÃ¢Â€Â or Ã¢Â€ÂœnoÃ¢Â€Â or require many weeks of biofeedback training. We hypothesized that signal processing and machine learning methods can be used to discriminate EEG in a direct Ã¢Â€ÂœyesÃ¢Â€Â/Ã¢Â€ÂœnoÃ¢Â€Â BCI from a single session. Blind source separation (BSS and spectral transformations of the EEG produced a 180-dimensional feature space. We used a modified genetic algorithm (GA wrapped around a support vector machine (SVM classifier to search the space of feature subsets. The GA-based search found feature subsets that outperform full feature sets and random feature subsets. Also, BSS transformations of the EEG outperformed the original time series, particularly in conjunction with a subset search of both spaces. The results suggest that BSS and feature selection can be used to improve the performance of even a Ã¢Â€Âœdirect,Ã¢Â€Â single-session BCI.

Case series of probable sporadic Creutzfeldt-Jakob disease from Eastern India

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Atanu Biswas

2013-01-01

Full Text Available Background: Creutzfeldt-Jakob disease is a rapidly progressive, fatal, transmissible neurodegenerative disorder caused by prion protein. It is still considered rare in countries like India. This is probably due to nonavailability of autopsy studies in majority of the center. The recent European diagnostic criterion for sporadic CJD (sCJD is useful for making an early diagnosis. Objective: To report a series of patients of probable sCJD from a neurology institute of eastern India. Materials and Methods: Patients of rapidly developing dementia fulfilling the diagnostic criteria for sCJD were included. All were investigated in detail to find out any possible treatable cause including electroencephalography (EEG, magnetic resonance imaging (MRI of brain, and cerebrospinal fluid analysis. Results: A total 10 patients of probable sCJD diagnosed using the European diagnostic criterion between December 2011 and January 2013. The clinical features are consistent with other reported series. While 60% of patients had the classical EEG findings, 100% had typical MRI features. Eight patients died within a mean duration of 4.56 months from the disease onset. Conclusions: The clinical features are similar to other reported series. Our observation raises question about the prevalence of this disease in India which needs more elaborate studies.
Square summable power series

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de Branges, Louis

2015-01-01

This text for advanced undergraduate and graduate students introduces Hilbert space and analytic function theory, which is centered around the invariant subspace concept. The book's principal feature is the extensive use of formal power series methods to obtain and sometimes reformulate results of analytic function theory. The presentation is elementary in that it requires little previous knowledge of analysis, but it is designed to lead students to an advanced level of performance. This is achieved chiefly through the use of problems, many of which were proposed by former students. The book's
Radial artery pulse waveform analysis based on curve fitting using discrete Fourier series.

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Jiang, Zhixing; Zhang, David; Lu, Guangming

2018-04-19

Radial artery pulse diagnosis has been playing an important role in traditional Chinese medicine (TCM). For its non-invasion and convenience, the pulse diagnosis has great significance in diseases analysis of modern medicine. The practitioners sense the pulse waveforms in patients' wrist to make diagnoses based on their non-objective personal experience. With the researches of pulse acquisition platforms and computerized analysis methods, the objective study on pulse diagnosis can help the TCM to keep up with the development of modern medicine. In this paper, we propose a new method to extract feature from pulse waveform based on discrete Fourier series (DFS). It regards the waveform as one kind of signal that consists of a series of sub-components represented by sine and cosine (SC) signals with different frequencies and amplitudes. After the pulse signals are collected and preprocessed, we fit the average waveform for each sample using discrete Fourier series by least squares. The feature vector is comprised by the coefficients of discrete Fourier series function. Compared with the fitting method using Gaussian mixture function, the fitting errors of proposed method are smaller, which indicate that our method can represent the original signal better. The classification performance of proposed feature is superior to the other features extracted from waveform, liking auto-regression model and Gaussian mixture model. The coefficients of optimized DFS function, who is used to fit the arterial pressure waveforms, can obtain better performance in modeling the waveforms and holds more potential information for distinguishing different psychological states. Copyright © 2018 Elsevier B.V. All rights reserved.
Recurrent Neural Network Applications for Astronomical Time Series

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Protopapas, Pavlos

2017-06-01

The benefits of good predictive models in astronomy lie in early event prediction systems and effective resource allocation. Current time series methods applicable to regular time series have not evolved to generalize for irregular time series. In this talk, I will describe two Recurrent Neural Network methods, Long Short-Term Memory (LSTM) and Echo State Networks (ESNs) for predicting irregular time series. Feature engineering along with a non-linear modeling proved to be an effective predictor. For noisy time series, the prediction is improved by training the network on error realizations using the error estimates from astronomical light curves. In addition to this, we propose a new neural network architecture to remove correlation from the residuals in order to improve prediction and compensate for the noisy data. Finally, I show how to set hyperparameters for a stable and performant solution correctly. In this work, we circumvent this obstacle by optimizing ESN hyperparameters using Bayesian optimization with Gaussian Process priors. This automates the tuning procedure, enabling users to employ the power of RNN without needing an in-depth understanding of the tuning procedure.
Active Structures as Deduced from Geomorphic Features: A case in Hsinchu Area, northwestern Taiwan

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Chen, Y.; Shyu, J.; Ota, Y.; Chen, W.; Hu, J.; Tsai, B.; Wang, Y.

2002-12-01

Hsinchu area is located in the northwestern Taiwan, the fold-and thrust belt created by arc-continent collision between Eurasian and Philippine. Since the collision event is still ongoing, the island is tectonically active and full of active faults. According to the historical records, some of the faults are seismically acting. In Hsinchuarea two active faults, the Hsinchu and Hsincheng, have been previously mapped. To evaluate the recent activities, we studied the related geomorphic features by using newly developed Digital Elevation Model (DEM), the aerial photos and field investigation. Geologically, both of the faults are coupled with a hanging wall anticline. The anticlines are recently active due to the deformation of the geomorphic surfaces. The Hsinchu fault system shows complicate corresponding scarps, distributed sub-parallel to the fault trace previously suggested by projection of subsurface geology. This is probably caused by its strike-slip component tearing the surrounding area along the main trace. The scarps associated with the Hsincheng fault system are rather simple and unique. It offsets a flight of terraces all the way down to recent flood plain, indicating its long lasting activity. One to two kilometers to east of main trace a back-thrust is found, showing coupled vertical surface offsets with the main fault. The striking discovery in this study is that the surface deformation is only distributed in the southern bank of Touchien river, also suddenly decreasing when crossing another tear fault system, which is originated from Hsincheng fault in the west and extending southeastward parallel to the Touchien river. The strike-slip fault system mentioned above not only bisects the Hsinchu fault, but also divides the Hsincheng fault into segments. The supporting evidence found in this study includes pressure ridges and depressions. As a whole, the study area is tectonically dominated by three active fault systems and two actively growing anticlines
Study of the dependence of resolution temporal activity for a Philips gemini TF PET/CT scanner by applying a statistical analysis of time series

International Nuclear Information System (INIS)

Sanchez Merino, G.; Cortes Rpdicio, J.; Lope Lope, R.; Martin Gonzalez, T.; Garcia Fidalgo, M. A.

2013-01-01

The aim of the present work is to study the dependence of temporal resolution with the activity using statistical techniques applied to the series of values time series measurements of temporal resolution during daily equipment checks. (Author)
High Accuracy Human Activity Recognition Based on Sparse Locality Preserving Projections.

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Zhu, Xiangbin; Qiu, Huiling

2016-01-01

Human activity recognition(HAR) from the temporal streams of sensory data has been applied to many fields, such as healthcare services, intelligent environments and cyber security. However, the classification accuracy of most existed methods is not enough in some applications, especially for healthcare services. In order to improving accuracy, it is necessary to develop a novel method which will take full account of the intrinsic sequential characteristics for time-series sensory data. Moreover, each human activity may has correlated feature relationship at different levels. Therefore, in this paper, we propose a three-stage continuous hidden Markov model (TSCHMM) approach to recognize human activities. The proposed method contains coarse, fine and accurate classification. The feature reduction is an important step in classification processing. In this paper, sparse locality preserving projections (SpLPP) is exploited to determine the optimal feature subsets for accurate classification of the stationary-activity data. It can extract more discriminative activities features from the sensor data compared with locality preserving projections. Furthermore, all of the gyro-based features are used for accurate classification of the moving data. Compared with other methods, our method uses significantly less number of features, and the over-all accuracy has been obviously improved.
High Accuracy Human Activity Recognition Based on Sparse Locality Preserving Projections.

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Xiangbin Zhu

Full Text Available Human activity recognition(HAR from the temporal streams of sensory data has been applied to many fields, such as healthcare services, intelligent environments and cyber security. However, the classification accuracy of most existed methods is not enough in some applications, especially for healthcare services. In order to improving accuracy, it is necessary to develop a novel method which will take full account of the intrinsic sequential characteristics for time-series sensory data. Moreover, each human activity may has correlated feature relationship at different levels. Therefore, in this paper, we propose a three-stage continuous hidden Markov model (TSCHMM approach to recognize human activities. The proposed method contains coarse, fine and accurate classification. The feature reduction is an important step in classification processing. In this paper, sparse locality preserving projections (SpLPP is exploited to determine the optimal feature subsets for accurate classification of the stationary-activity data. It can extract more discriminative activities features from the sensor data compared with locality preserving projections. Furthermore, all of the gyro-based features are used for accurate classification of the moving data. Compared with other methods, our method uses significantly less number of features, and the over-all accuracy has been obviously improved.
Using tactile features to help functionally blind individuals denominate banknotes.

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Lederman, Susan J; Hamilton, Cheryl

2002-01-01

This study, which was conducted for the Bank of Canada, assessed the feasibility of presenting a raised texture feature together with a tactile denomination code on the next Canadian banknote series ($5, $10, $20, $50, and $100). Adding information accessible by hand would permit functionally blind individuals to independently denominate banknotes. In Experiment 1, 20 blindfolded, sighted university students denominated a set of 8 alternate tactile feature designs. Across the 8 design series, the proportion of correct responses never fell below .97; the mean response time per banknote ranged from 11.4 to 13.1 s. In Experiment 2, 27 functionally blind participants denominated 4 of the previous 8 candidate sets of banknotes. The proportion of correct responses never fell below .92; the corresponding mean response time per banknote ranged from 11.7 to 13.0 s. The Bank of Canada selected one of the four raised-texture designs for inclusion on its new banknote series. Other potential applications include designing haptic displays for teleoperation and virtual environment systems.
A statistical method linking geological and historical eruption time series for volcanic hazard estimations: Applications to active polygenetic volcanoes

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Mendoza-Rosas, Ana Teresa; De la Cruz-Reyna, Servando

2008-09-01

The probabilistic analysis of volcanic eruption time series is an essential step for the assessment of volcanic hazard and risk. Such series describe complex processes involving different types of eruptions over different time scales. A statistical method linking geological and historical eruption time series is proposed for calculating the probabilities of future eruptions. The first step of the analysis is to characterize the eruptions by their magnitudes. As is the case in most natural phenomena, lower magnitude events are more frequent, and the behavior of the eruption series may be biased by such events. On the other hand, eruptive series are commonly studied using conventional statistics and treated as homogeneous Poisson processes. However, time-dependent series, or sequences including rare or extreme events, represented by very few data of large eruptions require special methods of analysis, such as the extreme-value theory applied to non-homogeneous Poisson processes. Here we propose a general methodology for analyzing such processes attempting to obtain better estimates of the volcanic hazard. This is done in three steps: Firstly, the historical eruptive series is complemented with the available geological eruption data. The linking of these series is done assuming an inverse relationship between the eruption magnitudes and the occurrence rate of each magnitude class. Secondly, we perform a Weibull analysis of the distribution of repose time between successive eruptions. Thirdly, the linked eruption series are analyzed as a non-homogeneous Poisson process with a generalized Pareto distribution as intensity function. As an application, the method is tested on the eruption series of five active polygenetic Mexican volcanoes: Colima, Citlaltépetl, Nevado de Toluca, Popocatépetl and El Chichón, to obtain hazard estimates.
Using the MCNP Taylor series perturbation feature (efficiently) for shielding problems

Science.gov (United States)

Favorite, Jeffrey

2017-09-01

The Taylor series or differential operator perturbation method, implemented in MCNP and invoked using the PERT card, can be used for efficient parameter studies in shielding problems. This paper shows how only two PERT cards are needed to generate an entire parameter study, including statistical uncertainty estimates (an additional three PERT cards can be used to give exact statistical uncertainties). One realistic example problem involves a detailed helium-3 neutron detector model and its efficiency as a function of the density of its high-density polyethylene moderator. The MCNP differential operator perturbation capability is extremely accurate for this problem. A second problem involves the density of the polyethylene reflector of the BeRP ball and is an example of first-order sensitivity analysis using the PERT capability. A third problem is an analytic verification of the PERT capability.
Clinical features, proximate causes, and consequences of active convulsive epilepsy in Africa

Science.gov (United States)

Kariuki, Symon M; Matuja, William; Akpalu, Albert; Kakooza-Mwesige, Angelina; Chabi, Martin; Wagner, Ryan G; Connor, Myles; Chengo, Eddie; Ngugi, Anthony K; Odhiambo, Rachael; Bottomley, Christian; White, Steven; Sander, Josemir W; Neville, Brian G R; Newton, Charles R J C

2014-01-01

Purpose Epilepsy is common in sub-Saharan Africa (SSA), but the clinical features and consequences are poorly characterized. Most studies are hospital-based, and few studies have compared different ecological sites in SSA. We described active convulsive epilepsy (ACE) identified in cross-sectional community-based surveys in SSA, to understand the proximate causes, features, and consequences. Methods We performed a detailed clinical and neurophysiologic description of ACE cases identified from a community survey of 584,586 people using medical history, neurologic examination, and electroencephalography (EEG) data from five sites in Africa: South Africa; Tanzania; Uganda; Kenya; and Ghana. The cases were examined by clinicians to discover risk factors, clinical features, and consequences of epilepsy. We used logistic regression to determine the epilepsy factors associated with medical comorbidities. Key Findings Half (51%) of the 2,170 people with ACE were children and 69% of seizures began in childhood. Focal features (EEG, seizure types, and neurologic deficits) were present in 58% of ACE cases, and these varied significantly with site. Status epilepticus occurred in 25% of people with ACE. Only 36% received antiepileptic drugs (phenobarbital was the most common drug [95%]), and the proportion varied significantly with the site. Proximate causes of ACE were adverse perinatal events (11%) for onset of seizures before 18 years; and acute encephalopathy (10%) and head injury prior to seizure onset (3%). Important comorbidities were malnutrition (15%), cognitive impairment (23%), and neurologic deficits (15%). The consequences of ACE were burns (16%), head injuries (postseizure) (1%), lack of education (43%), and being unmarried (67%) or unemployed (57%) in adults, all significantly more common than in those without epilepsy. Significance There were significant differences in the comorbidities across sites. Focal features are common in ACE, suggesting identifiable and
Case series in cognitive neuropsychology: promise, perils, and proper perspective.

Science.gov (United States)

Rapp, Brenda

2011-10-01

Schwartz and Dell (2010) advocated for a major role for case series investigations in cognitive neuropsychology. They defined the key features of this approach and presented a number of arguments and examples illustrating the benefits of case series studies and their contribution to computational cognitive neuropsychology. In the Special Issue on "Case Series in Cognitive Neuropsychology" there are six commentaries on Schwartz and Dell as well as a response to the six commentaries by Dell and Schwartz (2011 this issue). In this paper, I provide a brief summary of the key points made in Schwartz and Dell, and I review the promise and perils of case series design as revealed by the six commentaries. I conclude by placing the set of papers within a broader perspective, providing some clarification of the historical record on case series and single-case approaches, raising some cautionary notes for case series studies and situating both case series and single-case approaches within the larger context of theory development in the cognitive sciences.
Case Series in Cognitive Neuropsychology: Promise, Perils and Proper Perspective

Science.gov (United States)

Rapp, Brenda

2012-01-01

Schwartz & Dell (2010) advocated for a major role for case series investigations in cognitive neuropsychology. They defined the key features of this approach and presented a number of arguments and examples illustrating the benefits of case series studies and their contribution to computational cognitive neuropsychology. In the Special Issue on “Case Series in Cognitive Neuropsychology” there are six commentaries on Schwartz and Dell (2010) as well as a response to the six commentaries by Dell and Schwartz. In this paper, I provide a brief summary of the key points made in Schwartz and Dell (2010) and I review the promise and perils of case series design as revealed by the six commentaries. I conclude by placing the set of papers within a broader perspective, providing some clarification of the historical record on case series and single case approaches, raising some cautionary notes for case series studies and situating both case series and single case approaches within the larger context of theory development in the cognitive sciences. PMID:22746685
A Pilot Study of the Attractive Features of Active Videogames Among Chinese Primary School Children.

Science.gov (United States)

Lau, Patrick W C; Lau, Erica Y; Wang, Jing Jing; Choi, Cheong-Rak; Kim, Chang Gyun

2017-04-01

The present study (1) explored the attractive features that affect Chinese primary school children's preferences of active videogames (AVGs) and (2) contrasted these findings with those in the Western literature. A total of 22 Chinese primary school children were recruited and interviewed. Four AVGs (Wii "Boxing," "Wii Fit™ Plus Obstacle Run"; "EyeToy Knockout", "EyeToy Keep ups") from two commercial consoles (Nintendo® Wii™ and Sony PlayStation ® 2 "EyeToy ® ") were employed. Participants used four selected AVGs for 3 minutes each. After each play period, children (1) described the strengths and weaknesses of each game as well as rated the attractive features of each game based on a 16-item questionnaire and (2) rated up to 5 items that were most influential regarding their AVG preferences. Participants indicated that control was the most significant feature, followed by feedback, goal, and graphics. The top five rated features imply that the perception of competence was the most appealing aspect and expected outcome of Chinese children who play AVGs. Compared with the Western findings regarding attractive AVG features, the present study found certain similarities as well as significant differences among Chinese AVG players. Based on the present study, control, feedback, goal, and graphics are the most significant features that attract Chinese children to play AVGs. Physical exertion, social interaction, competition, and learning outcomes, which are valued according to Western studies, were not mentioned as significant features by Chinese children. These findings demonstrate a need to investigate the effect of cultural background in AVG study design.
Principal Feature Analysis: A Multivariate Feature Selection Method for fMRI Data

Directory of Open Access Journals (Sweden)

Lijun Wang

2013-01-01

Full Text Available Brain decoding with functional magnetic resonance imaging (fMRI requires analysis of complex, multivariate data. Multivoxel pattern analysis (MVPA has been widely used in recent years. MVPA treats the activation of multiple voxels from fMRI data as a pattern and decodes brain states using pattern classification methods. Feature selection is a critical procedure of MVPA because it decides which features will be included in the classification analysis of fMRI data, thereby improving the performance of the classifier. Features can be selected by limiting the analysis to specific anatomical regions or by computing univariate (voxel-wise or multivariate statistics. However, these methods either discard some informative features or select features with redundant information. This paper introduces the principal feature analysis as a novel multivariate feature selection method for fMRI data processing. This multivariate approach aims to remove features with redundant information, thereby selecting fewer features, while retaining the most information.
Single and Combined Diagnostic Value of Clinical Features and Laboratory Tests in Acute Appendicitis

NARCIS (Netherlands)

Laméris, Wytze; van Randen, Adrienne; Go, Peter M. N. Y. H.; Bouma, Wim H.; Donkervoort, Sandra C.; Bossuyt, Patrick M. M.; Stoker, Jaap; Boermeester, Marja A.

2009-01-01

Objectives: The objective was to evaluate the diagnostic accuracy of clinical features and laboratory test results in detecting acute appendicitis. Methods: Clinical features and laboratory test results were prospectively recorded in a consecutive series of 1,101 patients presenting with abdominal
Use of sEMG in identification of low level muscle activities: features based on ICA and fractal dimension.

Science.gov (United States)

Naik, Ganesh R; Kumar, Dinesh K; Arjunan, Sridhar

2009-01-01

This paper has experimentally verified and compared features of sEMG (Surface Electromyogram) such as ICA (Independent Component Analysis) and Fractal Dimension (FD) for identification of low level forearm muscle activities. The fractal dimension was used as a feature as reported in the literature. The normalized feature values were used as training and testing vectors for an Artificial neural network (ANN), in order to reduce inter-experimental variations. The identification accuracy using FD of four channels sEMG was 58%, and increased to 96% when the signals are separated to their independent components using ICA.
Analysis of Heavy-Tailed Time Series

DEFF Research Database (Denmark)

Xie, Xiaolei

This thesis is about analysis of heavy-tailed time series. We discuss tail properties of real-world equity return series and investigate the possibility that a single tail index is shared by all return series of actively traded equities in a market. Conditions for this hypothesis to be true...... are identified. We study the eigenvalues and eigenvectors of sample covariance and sample auto-covariance matrices of multivariate heavy-tailed time series, and particularly for time series with very high dimensions. Asymptotic approximations of the eigenvalues and eigenvectors of such matrices are found...... and expressed in terms of the parameters of the dependence structure, among others. Furthermore, we study an importance sampling method for estimating rare-event probabilities of multivariate heavy-tailed time series generated by matrix recursion. We show that the proposed algorithm is efficient in the sense...
The Westinghouse Series 1000 Mobile Phone: Technology and applications

Science.gov (United States)

Connelly, Brian

1993-01-01

Mobile satellite communications will be popularized by the North American Mobile Satellite (MSAT) system. The success of the overall system is dependent upon the quality of the mobile units. Westinghouse is designing our unit, the Series 1000 Mobile Phone, with the user in mind. The architecture and technology aim at providing optimum performance at a low per unit cost. The features and functions of the Series 1000 Mobile Phone have been defined by potential MSAT users. The latter portion of this paper deals with who those users may be.

Conversion (dissociative) symptoms as a presenting feature in early onset bipolar disorder: a case series

OpenAIRE

Ghosal, Malay Kumar; Guha, Prathama; Sinha, Mausumi; Majumdar, Debabrata; Sengupta, Payel

2009-01-01

We present three cases of early onset bipolar disorder where dissociative (conversion) symptoms preceded the onset of mania. This case series underscores the significance of dissociative/conversion symptoms as an early atypical presentation in juvenile bipolar disorder.
RECONSTRUCTION OF PRECIPITATION SERIES AND ANALYSIS OF CLIMATE CHANGE OVER PAST 500 YEARS IN NORTHERN CHINA

Institute of Scientific and Technical Information of China (English)

RONG Yan-shu; TU Qi-pu

2005-01-01

It is important and necessary to get a much longer precipitation series in order to research features of drought/flood and climate change.Based on dryness and wetness grades series of 18 stations in Northern China of 533 years from 1470 to 2002, the Moving Cumulative Frequency Method (MCFM) was developed, moving average precipitation series from 1499 to 2002 were reconstructed by testing three kinds of average precipitation, and the features of climate change and dry and wet periods were researched by using reconstructed precipitation series in the present paper.The results showed that there were good relationship between the reconstructed precipitation series and the observation precipitation series since 1954 and their relative root-mean-square error were below 1.89%, that the relation between reconstructed series and the dryness and wetness grades series were nonlinear and this nonlinear relation implied that reconstructed series were reliable and could became foundation data for researching evolution of the drought and flood.Analysis of climate change upon reconstructed precipitation series revealed that although drought intensity of recent dry period from middle 1970s of 20th century until early 21st century was not the strongest in historical climate of Northern China, intensity and duration of wet period was a great deal decreasing and shortening respectively, climate evolve to aridification situation in Northern China.
FEATURE EXTRACTION FOR EMG BASED PROSTHESES CONTROL

Directory of Open Access Journals (Sweden)

R. Aishwarya

2013-01-01

Full Text Available The control of prosthetic limb would be more effective if it is based on Surface Electromyogram (SEMG signals from remnant muscles. The analysis of SEMG signals depend on a number of factors, such as amplitude as well as time- and frequency-domain properties. Time series analysis using Auto Regressive (AR model and Mean frequency which is tolerant to white Gaussian noise are used as feature extraction techniques. EMG Histogram is used as another feature vector that was seen to give more distinct classification. The work was done with SEMG dataset obtained from the NINAPRO DATABASE, a resource for bio robotics community. Eight classes of hand movements hand open, hand close, Wrist extension, Wrist flexion, Pointing index, Ulnar deviation, Thumbs up, Thumb opposite to little finger are taken into consideration and feature vectors are extracted. The feature vectors can be given to an artificial neural network for further classification in controlling the prosthetic arm which is not dealt in this paper.
Palmprint Verification Using Time Series Method

Directory of Open Access Journals (Sweden)

A. A. Ketut Agung Cahyawan Wiranatha

2013-11-01

Full Text Available The use of biometrics as an automatic recognition system is growing rapidly in solving security problems, palmprint is one of biometric system which often used. This paper used two steps in center of mass moment method for region of interest (ROI segmentation and apply the time series method combined with block window method as feature representation. Normalized Euclidean Distance is used to measure the similarity degrees of two feature vectors of palmprint. System testing is done using 500 samples palms, with 4 samples as the reference image and the 6 samples as test images. Experiment results show that this system can achieve a high performance with success rate about 97.33% (FNMR=1.67%, FMR=1.00 %, T=0.036.
Iak bulo kolys': uchnivs'skyi zoshyt (In Days Gone By: Student Activity Book). Collage 1: A Ukrainian Language Development Series.

Science.gov (United States)

Boruszczak, Bohdan, Comp.; Jaremko, Helen, Comp.

One of four intermediate-level student activity books in a series, this book offers a selection of exercises, word-games, puzzles, cartoons, sentence-completion and vocabulary-building activities in modern Ukrainian. It is intended for both heritage language and second language learners. There is a brief word list in the back of each book. "In…
Common and divergent structural features of a series of corticotropin releasing factor-related peptides.

Science.gov (United States)

Grace, Christy Rani R; Perrin, Marilyn H; Cantle, Jeffrey P; Vale, Wylie W; Rivier, Jean E; Riek, Roland

2007-12-26

Members of the corticoliberin family include the corticotropin releasing factors (CRFs), sauvagine, the urotensins, and urocortin 1 (Ucn1), which bind to both the CRF receptors CRF-R1 and CRF-R2, and the urocortins 2 (Ucn2) and 3 (Ucn3), which are selective agonists of CRF-R2. Structure activity relationship studies led to several potent and long-acting analogues with selective binding to either one of the receptors. NMR structures of six ligands of this family (the antagonists astressin B and astressin2-B, the agonists stressin1, and the natural ligands human Ucn1, Ucn2, and Ucn3) were determined in DMSO. These six peptides show differences in binding affinities, receptor-selectivity, and NMR structure. Overall, their backbones are alpha-helical, with a small kink or a turn around residues 25-27, resulting in a helix-loop-helix motif. The C-terminal helices are of amphipathic nature, whereas the N-terminal helices vary in their amphipathicity. The C-terminal helices thereby assume a conformation very similar to that of astressin bound to the ECD1 of CRF-R2 recently reported by our group.1 On the basis of an analysis of the observed 3D structures and relative potencies of [Ala]-substituted analogues, it is proposed that both helices could play a crucial role in receptor binding and selectivity. In conclusion, the C-terminal helices may interact along their hydrophobic faces with the ECD1, whereas the entire N-terminal helical surface may be involved in receptor activation. On the basis of the common and divergent features observed in the 3D structures of these ligands, multiple binding models are proposed that may explain their plurality of actions.
Arts and Crafts Classes in Years I–III, Based on Methods Featuring Pupils’ Practical Activities

OpenAIRE

Piwowarska, Ewa

2016-01-01

The issue to be analysed here concerns teachers’ planning of arts and crafts classes in Years I–III, with specific reference to methods featuring pupils’ practical activities. A theoretical part briefly presents the concepts involved in teaching a subject that was initially defined as drawing, then as arts and crafts education, and finally as arts and crafts classes. It points out the factors that influence the process of stimulating pupils’ artistic activities. The technique used in the cour...
Synthesis, biological evaluation and molecular modeling of a novel series of 7-azaindole based tri-heterocyclic compounds as potent CDK2/Cyclin E inhibitors.

Science.gov (United States)

Baltus, Christine B; Jorda, Radek; Marot, Christophe; Berka, Karel; Bazgier, Václav; Kryštof, Vladimír; Prié, Gildas; Viaud-Massuard, Marie-Claude

2016-01-27

From four molecules, inspired by the structural features of fascaplysin, with an interesting potential to inhibit cyclin-dependent kinases (CDKs), we designed a new series of tri-heterocyclic derivatives based on 1H-pyrrolo[2,3-b]pyridine (7-azaindole) and triazole heterocycles. Using a Huisgen type [3 + 2] cycloaddition as the convergent key step, 24 derivatives were synthesized and their biological activities were evaluated. Comparative molecular field analysis (CoMFA), based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies, was conducted on a series of 30 compounds from the literature with high to low known inhibitory activity towards CDK2/cyclin E and was validated by a test set of 5 compounds giving satisfactory predictive r(2) value of 0.92. Remarkably, it also gave a good prediction of pIC50 for our tri-heterocyclic series which reinforce the validation of this model for the pIC50 prediction of external set compounds. The most promising compound, 43, showed a micro-molar range inhibitory activity against CDK2/cyclin E and also an antiproliferative and proapoptotic activity against a panel of cancer cell lines. Copyright © 2015 Elsevier Masson SAS. All rights reserved.
Stochastic nature of series of waiting times

Science.gov (United States)

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2series has a short-range correlation, and then we study its stochastic nature using the Markovian method and determine the corresponding Kramers-Moyal coefficients. As an example, we analyze the velocity fluctuations in high Reynolds number turbulence and determine the level dependence of Markov time scales, as well as the drift and diffusion coefficients. We show that the waiting time distributions exhibit power law tails, and we were able to model the distribution with a continuous time random walk.
An Analysis of Audio Features to Develop a Human Activity Recognition Model Using Genetic Algorithms, Random Forests, and Neural Networks

Directory of Open Access Journals (Sweden)

Carlos E. Galván-Tejada

2016-01-01

Full Text Available This work presents a human activity recognition (HAR model based on audio features. The use of sound as an information source for HAR models represents a challenge because sound wave analyses generate very large amounts of data. However, feature selection techniques may reduce the amount of data required to represent an audio signal sample. Some of the audio features that were analyzed include Mel-frequency cepstral coefficients (MFCC. Although MFCC are commonly used in voice and instrument recognition, their utility within HAR models is yet to be confirmed, and this work validates their usefulness. Additionally, statistical features were extracted from the audio samples to generate the proposed HAR model. The size of the information is necessary to conform a HAR model impact directly on the accuracy of the model. This problem also was tackled in the present work; our results indicate that we are capable of recognizing a human activity with an accuracy of 85% using the HAR model proposed. This means that minimum computational costs are needed, thus allowing portable devices to identify human activities using audio as an information source.
Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section

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Chaolong Jia

2014-01-01

Full Text Available Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described.
Special feature on imaging systems and techniques

Science.gov (United States)

Yang, Wuqiang; Giakos, George

2013-07-01

The IEEE International Conference on Imaging Systems and Techniques (IST'2012) was held in Manchester, UK, on 16-17 July 2012. The participants came from 26 countries or regions: Austria, Brazil, Canada, China, Denmark, France, Germany, Greece, India, Iran, Iraq, Italy, Japan, Korea, Latvia, Malaysia, Norway, Poland, Portugal, Sweden, Switzerland, Taiwan, Tunisia, UAE, UK and USA. The technical program of the conference consisted of a series of scientific and technical sessions, exploring physical principles, engineering and applications of new imaging systems and techniques, as reflected by the diversity of the submitted papers. Following a rigorous review process, a total of 123 papers were accepted, and they were organized into 30 oral presentation sessions and a poster session. In addition, six invited keynotes were arranged. The conference not only provided the participants with a unique opportunity to exchange ideas and disseminate research outcomes but also paved a way to establish global collaboration. Following the IST'2012, a total of 55 papers, which were technically extended substantially from their versions in the conference proceeding, were submitted as regular papers to this special feature of Measurement Science and Technology . Following a rigorous reviewing process, 25 papers have been finally accepted for publication in this special feature and they are organized into three categories: (1) industrial tomography, (2) imaging systems and techniques and (3) image processing. These papers not only present the latest developments in the field of imaging systems and techniques but also offer potential solutions to existing problems. We hope that this special feature provides a good reference for researchers who are active in the field and will serve as a catalyst to trigger further research. It has been our great pleasure to be the guest editors of this special feature. We would like to thank the authors for their contributions, without which it would
Computation of solar perturbations with Poisson series

Science.gov (United States)

Broucke, R.

1974-01-01

Description of a project for computing first-order perturbations of natural or artificial satellites by integrating the equations of motion on a computer with automatic Poisson series expansions. A basic feature of the method of solution is that the classical variation-of-parameters formulation is used rather than rectangular coordinates. However, the variation-of-parameters formulation uses the three rectangular components of the disturbing force rather than the classical disturbing function, so that there is no problem in expanding the disturbing function in series. Another characteristic of the variation-of-parameters formulation employed is that six rather unusual variables are used in order to avoid singularities at the zero eccentricity and zero (or 90 deg) inclination. The integration process starts by assuming that all the orbit elements present on the right-hand sides of the equations of motion are constants. These right-hand sides are then simple Poisson series which can be obtained with the use of the Bessel expansions of the two-body problem in conjunction with certain interation methods. These Poisson series can then be integrated term by term, and a first-order solution is obtained.
Fault-tolerant feature-based estimation of space debris rotational motion during active removal missions

Science.gov (United States)

Biondi, Gabriele; Mauro, Stefano; Pastorelli, Stefano; Sorli, Massimo

2018-05-01

One of the key functionalities required by an Active Debris Removal mission is the assessment of the target kinematics and inertial properties. Passive sensors, such as stereo cameras, are often included in the onboard instrumentation of a chaser spacecraft for capturing sequential photographs and for tracking features of the target surface. A plenty of methods, based on Kalman filtering, are available for the estimation of the target's state from feature positions; however, to guarantee the filter convergence, they typically require continuity of measurements and the capability of tracking a fixed set of pre-defined features of the object. These requirements clash with the actual tracking conditions: failures in feature detection often occur and the assumption of having some a-priori knowledge about the shape of the target could be restrictive in certain cases. The aim of the presented work is to propose a fault-tolerant alternative method for estimating the angular velocity and the relative magnitudes of the principal moments of inertia of the target. Raw data regarding the positions of the tracked features are processed to evaluate corrupted values of a 3-dimentional parameter which entirely describes the finite screw motion of the debris and which primarily is invariant on the particular set of considered features of the object. Missing values of the parameter are completely restored exploiting the typical periodicity of the rotational motion of an uncontrolled satellite: compressed sensing techniques, typically adopted for recovering images or for prognostic applications, are herein used in a completely original fashion for retrieving a kinematic signal that appears sparse in the frequency domain. Due to its invariance about the features, no assumptions are needed about the target's shape and continuity of the tracking. The obtained signal is useful for the indirect evaluation of an attitude signal that feeds an unscented Kalman filter for the estimation of
Empirical mode decomposition and long-range correlation analysis of sunspot time series

International Nuclear Information System (INIS)

Zhou, Yu; Leung, Yee

2010-01-01

Sunspots, which are the best known and most variable features of the solar surface, affect our planet in many ways. The number of sunspots during a period of time is highly variable and arouses strong research interest. When multifractal detrended fluctuation analysis (MF-DFA) is employed to study the fractal properties and long-range correlation of the sunspot series, some spurious crossover points might appear because of the periodic and quasi-periodic trends in the series. However many cycles of solar activities can be reflected by the sunspot time series. The 11-year cycle is perhaps the most famous cycle of the sunspot activity. These cycles pose problems for the investigation of the scaling behavior of sunspot time series. Using different methods to handle the 11-year cycle generally creates totally different results. Using MF-DFA, Movahed and co-workers employed Fourier truncation to deal with the 11-year cycle and found that the series is long-range anti-correlated with a Hurst exponent, H, of about 0.12. However, Hu and co-workers proposed an adaptive detrending method for the MF-DFA and discovered long-range correlation characterized by H≈0.74. In an attempt to get to the bottom of the problem in the present paper, empirical mode decomposition (EMD), a data-driven adaptive method, is applied to first extract the components with different dominant frequencies. MF-DFA is then employed to study the long-range correlation of the sunspot time series under the influence of these components. On removing the effects of these periods, the natural long-range correlation of the sunspot time series can be revealed. With the removal of the 11-year cycle, a crossover point located at around 60 months is discovered to be a reasonable point separating two different time scale ranges, H≈0.72 and H≈1.49. And on removing all cycles longer than 11 years, we have H≈0.69 and H≈0.28. The three cycle-removing methods—Fourier truncation, adaptive detrending and the
Exploring spatial-temporal dynamics of fire regime features in mainland Spain

Science.gov (United States)

Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan

2017-10-01

This paper explores spatial-temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial - regional and provincial/NUTS3 - levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974-2013. Temporal shifts in fire features are investigated by means of change point detection procedures - Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) - at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann-Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs - mainly Sen's slope values - to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann-Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).
A procedure to derive intra-and inter-annual changes on vegetation from NDVI time series. A case study in Spain

International Nuclear Information System (INIS)

Gilabert, M. A; Martinez, B.; Melia, J.

2009-01-01

The objective of this work is to study the spatial patterns of vegetation activity over spain and its temporal variability throughout the period 1989-2002. A multi-resolution analysis (MRA) bases on the wavelet transform has been implemented on NDVI time series from the MEDOKADS database. The MRA decomposes the original signal as a sum of series associated with temporal scales. Specifically, the intra-annual series is processed to define several key features in relation with the vegetation penology. In contras, the inter-annual components of the signal is used to detect trends by means of a Mann-Kendall test and map the magnitude of the land-cover change. Finally, a comprehensive identification of the areas presenting a negative value of the magnitude of change is carried out to select those linked to land degradation processes. Results show a major presence of these areas the Southeast of Spain. (Author) 5 refs.
A procedure to derive intra-and inter-annual changes on vegetation from NDVI time series. A case study in Spain

Energy Technology Data Exchange (ETDEWEB)

Gilabert, M. A; Martinez, B.; Melia, J.

2009-07-01

The objective of this work is to study the spatial patterns of vegetation activity over spain and its temporal variability throughout the period 1989-2002. A multi-resolution analysis (MRA) bases on the wavelet transform has been implemented on NDVI time series from the MEDOKADS database. The MRA decomposes the original signal as a sum of series associated with temporal scales. Specifically, the intra-annual series is processed to define several key features in relation with the vegetation penology. In contras, the inter-annual components of the signal is used to detect trends by means of a Mann-Kendall test and map the magnitude of the land-cover change. Finally, a comprehensive identification of the areas presenting a negative value of the magnitude of change is carried out to select those linked to land degradation processes. Results show a major presence of these areas the Southeast of Spain. (Author) 5 refs.
Volcanic features of Io

International Nuclear Information System (INIS)

Carr, M.H.; Masursky, H.; Strom, R.G.; Terrile, R.J.

1979-01-01

The volcanic features of Io as detected during the Voyager mission are discussed. The volcanic activity is apparently higher than on any other body in the Solar System. Its volcanic landforms are compared with features on Earth to indicate the type of volcanism present on Io. (U.K.)
Microprocessor Card for Cuban Series polarimeters Laserpol

International Nuclear Information System (INIS)

Arista Romeu, E.; Mora Mazorra, W.

2012-01-01

We present the design consists of a card based on a micro-processor 8-bit adds new software components and their basic living, which allow to deliver new services and expand the possibilities for use in other applications of the polarimeter LASERPOL series, as the polarimetric detection. Given the limitations of the original card it was necessary to introduce a series of changes that would allow to address new user requirements, and expand the possible applications of the instruments. This was done the expansion of the capacity of the EPROM and RAM memory, the decoder circuit was implemented memory map using a programmable integrated circuit, and introduced a real time clock with nonvolatile RAM, these features are exploited to the introduction of new features such as the realization of the polarimeter calibration by the user from a sample pattern or a calibration pattern used as a reference, and the incorporation of the time and date to the reports of measurements required industry for quality control processes. Card that is achieved along with the rest of the components is compatible with polarimeters LASERPOL 101M Series, 3M and LP4, pin to pin, which facilitates their incorporation into the polarimeters in operation in the industry 'in situ' replacement cards from previous models, allowing to extend the possibilities of statistical processing, precision and accuracy of the instruments. Improved measurements in the industry, resulting in significant savings by elimination of losses in production and raw materials. The improved response speed of reading the polarimeters LASERPOL Use and polarimetric detectors. (Author)

Bayesian near-boundary analysis in basic macroeconomic time series models

NARCIS (Netherlands)

M.D. de Pooter (Michiel); F. Ravazzolo (Francesco); R. Segers (René); H.K. van Dijk (Herman)

2008-01-01

textabstractSeveral lessons learnt from a Bayesian analysis of basic macroeconomic time series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic
Stars in Nutrition and Cancer Lecture Series | Division of Cancer Prevention

Science.gov (United States)

This lecture series features extraordinary contributors or "stars" in the field of cancer and nutrition research. Speakers highlight the important role that nutrition plays in modifying cancer development. Past lectures are videotaped and available for viewing. |
Clinical features, proximate causes, and consequences of active convulsive epilepsy in Africa.

Science.gov (United States)

Kariuki, Symon M; Matuja, William; Akpalu, Albert; Kakooza-Mwesige, Angelina; Chabi, Martin; Wagner, Ryan G; Connor, Myles; Chengo, Eddie; Ngugi, Anthony K; Odhiambo, Rachael; Bottomley, Christian; White, Steven; Sander, Josemir W; Neville, Brian G R; Newton, Charles R J C; Twine, Rhian; Gómez Olivé, F Xavier; Collinson, Mark; Kahn, Kathleen; Tollman, Stephen; Masanja, Honratio; Mathew, Alexander; Pariyo, George; Peterson, Stefan; Ndyomughenyi, Donald; Bauni, Evasius; Kamuyu, Gathoni; Odera, Victor Mung'ala; Mageto, James O; Ae-Ngibise, Ken; Akpalu, Bright; Agbokey, Francis; Adjei, Patrick; Owusu-Agyei, Seth; Kleinschmidt, Immo; Doku, Victor C K; Odermatt, Peter; Nutman, Thomas; Wilkins, Patricia; Noh, John

2014-01-01

Epilepsy is common in sub-Saharan Africa (SSA), but the clinical features and consequences are poorly characterized. Most studies are hospital-based, and few studies have compared different ecological sites in SSA. We described active convulsive epilepsy (ACE) identified in cross-sectional community-based surveys in SSA, to understand the proximate causes, features, and consequences. We performed a detailed clinical and neurophysiologic description of ACE cases identified from a community survey of 584,586 people using medical history, neurologic examination, and electroencephalography (EEG) data from five sites in Africa: South Africa; Tanzania; Uganda; Kenya; and Ghana. The cases were examined by clinicians to discover risk factors, clinical features, and consequences of epilepsy. We used logistic regression to determine the epilepsy factors associated with medical comorbidities. Half (51%) of the 2,170 people with ACE were children and 69% of seizures began in childhood. Focal features (EEG, seizure types, and neurologic deficits) were present in 58% of ACE cases, and these varied significantly with site. Status epilepticus occurred in 25% of people with ACE. Only 36% received antiepileptic drugs (phenobarbital was the most common drug [95%]), and the proportion varied significantly with the site. Proximate causes of ACE were adverse perinatal events (11%) for onset of seizures before 18 years; and acute encephalopathy (10%) and head injury prior to seizure onset (3%). Important comorbidities were malnutrition (15%), cognitive impairment (23%), and neurologic deficits (15%). The consequences of ACE were burns (16%), head injuries (postseizure) (1%), lack of education (43%), and being unmarried (67%) or unemployed (57%) in adults, all significantly more common than in those without epilepsy. There were significant differences in the comorbidities across sites. Focal features are common in ACE, suggesting identifiable and preventable causes. Malnutrition and
Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

Science.gov (United States)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.
Is hearing loss a feature of Joubert syndrome, a ciliopathy?

NARCIS (Netherlands)

Kroes, H.Y.; Van Zanten, B.G.A.; De Ru, S.A.; Boon, M.; Mancini, G.M.S.; van der Knaap, M.S.; Poll-The, B.; Lindhout, D.

2010-01-01

Objective: To assess if hearing loss is a feature of Joubert syndrome (JBS), one of the ciliopathies and therefore possibly associated with hearing loss. Design: Retrospective case series. Setting: University Children's Hospital. Patients: Dutch patients with JBS. Main outcome measures: Audiological
Extraction of Coal and Gangue Geometric Features with Multifractal Detrending Fluctuation Analysis

Directory of Open Access Journals (Sweden)

Kai Liu

2018-03-01

Full Text Available The separation of coal and gangue is an important process of the coal preparation technology. The conventional way of manual selection and separation of gangue from the raw coal can be replaced by computer vision technology. In the literature, research on image recognition and classification of coal and gangue is mainly based on the grayscale and texture features of the coal and gangue. However, there are few studies on characteristics of coal and gangue from the perspective of their outline differences. Therefore, the multifractal detrended fluctuation analysis (MFDFA method is introduced in this paper to extract the geometric features of coal and gangue. Firstly, the outline curves of coal and gangue in polar coordinates are detected and achieved along the centroid, thereby the multifractal characteristics of the series are analyzed and compared. Subsequently, the modified local singular spectrum widths Δ h of the outline curve series are extracted as the characteristic variables of the coal and gangue for pattern recognition. Finally, the extracted geometric features by MFDFA combined with the grayscale and texture features of the images are compared with other methods, indicating that the recognition rate of coal gangue images can be increased by introducing the geometric features.
Comparison of Cytotoxic Activity in Leukemic Lineages Reveals Important Features of β-Hairpin Antimicrobial Peptides.

Science.gov (United States)

Buri, Marcus V; Torquato, Heron F Vieira; Barros, Carlos Castilho; Ide, Jaime S; Miranda, Antonio; Paredes-Gamero, Edgar J

2017-07-01

Several reports described different modes of cell death triggered by antimicrobial peptides (AMPs) due to direct effects on membrane disruption, and more recently by apoptosis and necrosis-like patterns. Cytotoxic curves of four β-hairpin AMPs (gomesin, protegrin, tachyplesin, and polyphemusin) were obtained from several human leukemic lineages and normal monocytes and Two cell lines were then selected based on their cytotoxic sensitivity. One was sensitive to AMPs (K562) and the other resistant (KG-1) and their effect compared between these lineages. Thus, these lineages were chosen to further investigate biological features related with their cytotoxicities to AMPs. Stimulation with AMPs produced cell death, with activation of caspase-3, in K562 lineage. Increase on the fluidity of plasmatic membrane by reducing cholesterol potentiated cytotoxicity of AMPs in both lineages. Quantification of internal and external gomesin binding to the cellular membrane of both K562 and KG-1 cells showed that more peptide is accumulated inside of K562 cells. Additionally, evaluation of multi-drug resistant pumps activity showed that KG-1 has more activity than K562 lineage. A comparison of intrinsic gene patterns showed great differences between K562 and KG-1, but stimulation with gomesin promoted few changes in gene expression patterns. Differences in internalization process through the plasma membrane, multidrug resistance pumps activity, and gene expression pattern are important features to AMPs regulated cell death. J. Cell. Biochem. 118: 1764-1773, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Series: Practical guidance to qualitative research. Part 1: Introduction.

Science.gov (United States)

Moser, Albine; Korstjens, Irene

2017-12-01

In the course of our supervisory work over the years, we have noticed that qualitative research tends to evoke a lot of questions and worries, so-called Frequently Asked Questions. This journal series of four articles intends to provide novice researchers with practical guidance for conducting high-quality qualitative research in primary care. By 'novice' we mean Master's students and junior researchers, as well as experienced quantitative researchers who are engaging in qualitative research for the first time. This series addresses their questions and provides researchers, readers, reviewers and editors with references to criteria and tools for judging the quality of papers reporting on qualitative research. This first article describes the key features of qualitative research, provides publications for further learning and reading, and gives an outline of the series.
Comparative study on the performance of textural image features for active contour segmentation.

Science.gov (United States)

Moraru, Luminita; Moldovanu, Simona

2012-07-01

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard deviation textural feature and a 5×5 kernel, our curve evolution was able to produce results close to the minimal area error rate (namely 8.88% for breast images and 10.82% for liver images). The image resolution was evaluated using the contrast-to-gradient method. The experiments showed promising segmentation results.
LMD Based Features for the Automatic Seizure Detection of EEG Signals Using SVM.

Science.gov (United States)

Zhang, Tao; Chen, Wanzhong

2017-08-01

Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical algorithm, namely local mean decomposition (LMD), is employed in the presented study. LMD is able to decompose an arbitrary signal into a series of product functions (PFs). Primarily, the raw EEG signal is decomposed into several PFs, and then the temporal statistical and non-linear features of the first five PFs are calculated. The features of each PF are fed into five classifiers, including back propagation neural network (BPNN), K-nearest neighbor (KNN), linear discriminant analysis (LDA), un-optimized support vector machine (SVM) and SVM optimized by genetic algorithm (GA-SVM), for five classification cases, respectively. Confluent features of all PFs and raw EEG are further passed into the high-performance GA-SVM for the same classification tasks. Experimental results on the international public Bonn epilepsy EEG dataset show that the average classification accuracy of the presented approach are equal to or higher than 98.10% in all the five cases, and this indicates the effectiveness of the proposed approach for automated seizure detection.
Chemical composition measurements of the low activity waste (LAW) EPA-Series glasses

Energy Technology Data Exchange (ETDEWEB)

Fox, K. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Edwards, T. B. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2016-03-01

In this report, the Savannah River National Laboratory provides chemical analysis results for a series of simulated low activity waste glasses provided by Pacific Northwest National Laboratory as part of an ongoing development task. The measured chemical composition data are reported and compared with the targeted values for each component for each glass. A detailed review showed no indications of errors in the preparation or measurement of the study glasses. All of the measured sums of oxides for the study glasses fell within the interval of 100.2 to 100.8 wt %, indicating recovery of all components. Comparisons of the targeted and measured chemical compositions showed that the measured values for the glasses met the targeted concentrations within 10% for those components present at more than 5 wt %.
FEATURES BASED ON NEIGHBORHOOD PIXELS DENSITY - A STUDY AND COMPARISON

Directory of Open Access Journals (Sweden)

Satish Kumar

2016-02-01

Full Text Available In optical character recognition applications, the feature extraction method(s used to recognize document images play an important role. The features are the properties of the pattern that can be statistical, structural and/or transforms or series expansion. The structural features are difficult to compute particularly from hand-printed images. The structure of the strokes present inside the hand-printed images can be estimated using statistical means. In this paper three features have been purposed, those are based on the distribution of B/W pixels on the neighborhood of a pixel in an image. We name these features as Spiral Neighbor Density, Layer Pixel Density and Ray Density. The recognition performance of these features has been compared with two more features Neighborhood Pixels Weight and Total Distances in Four Directions already studied in our work. We have used more than 20000 Devanagari handwritten character images for conducting experiments. The experiments are conducted with two classifiers i.e. PNN and k-NN.
Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

Science.gov (United States)

Wang, Na; Li, Dong; Wang, Qiwen

2012-12-01

The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government
Time series analysis of temporal networks

Science.gov (United States)

Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh

2016-01-01

A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue
Classification of biosensor time series using dynamic time warping: applications in screening cancer cells with characteristic biomarkers.

Science.gov (United States)

Rai, Shesh N; Trainor, Patrick J; Khosravi, Farhad; Kloecker, Goetz; Panchapakesan, Balaji

2016-01-01

The development of biosensors that produce time series data will facilitate improvements in biomedical diagnostics and in personalized medicine. The time series produced by these devices often contains characteristic features arising from biochemical interactions between the sample and the sensor. To use such characteristic features for determining sample class, similarity-based classifiers can be utilized. However, the construction of such classifiers is complicated by the variability in the time domains of such series that renders the traditional distance metrics such as Euclidean distance ineffective in distinguishing between biological variance and time domain variance. The dynamic time warping (DTW) algorithm is a sequence alignment algorithm that can be used to align two or more series to facilitate quantifying similarity. In this article, we evaluated the performance of DTW distance-based similarity classifiers for classifying time series that mimics electrical signals produced by nanotube biosensors. Simulation studies demonstrated the positive performance of such classifiers in discriminating between time series containing characteristic features that are obscured by noise in the intensity and time domains. We then applied a DTW distance-based k -nearest neighbors classifier to distinguish the presence/absence of mesenchymal biomarker in cancer cells in buffy coats in a blinded test. Using a train-test approach, we find that the classifier had high sensitivity (90.9%) and specificity (81.8%) in differentiating between EpCAM-positive MCF7 cells spiked in buffy coats and those in plain buffy coats.
TIGER/Line Shapefile, 2015, Series Information for the Address Range-Feature County-based Shapefile

Data.gov (United States)

US Census Bureau, Department of Commerce — The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county...
Historicizing video game series through fan art discourses

Directory of Open Access Journals (Sweden)

Jan Švelch

2016-09-01

Full Text Available In this article, we argue that fannish histories should not be dismissed as mere nostalgia over past experiences of one's own media fandom. Instead they should be understood as complex narratives which combine various historical layers (personal, productional, fictional and influence the future reception of and anticipation for sequels. They also shed light on the personal histories of fans, which are often juxtaposed with extratextual and fictional histories of a video game series. The subjective nature of these historical discourses is not to be seen as a constraint but as a feature of everyday history which points to the prominence of historicizing in fan cultures of video game series. These topics are examined in the selected multimodal material from the site DeviantArt consisting of fan art pieces, authorial captions, and respective comments inspired by two single-player video game series: Tomb Raider and Mass Effect.
Is the binding of visual features in working memory resource-demanding?

Science.gov (United States)

Allen, Richard J; Baddeley, Alan D; Hitch, Graham J

2006-05-01

The episodic buffer component of working memory is assumed to play a role in the binding of features into chunks. A series of experiments compared memory for arrays of colors or shapes with memory for bound combinations of these features. Demanding concurrent verbal tasks were used to investigate the role of general attentional processes, producing load effects that were no greater on memory for feature combinations than for the features themselves. However, the binding condition was significantly less accurate with sequential rather than simultaneous presentation, especially for items earlier in the sequence. The findings are interpreted as evidence of a relatively automatic but fragile visual feature binding mechanism in working memory. Implications for the concept of an episodic buffer are discussed. 2006 APA, all rights reserved
Is hearing loss a feature of Joubert syndrome, a ciliopathy?

NARCIS (Netherlands)

Kroes, Hester Y.; Van Zanten, Bert G. A.; De Ru, Sander A.; Boon, Maartje; Mancini, Grazia M. S.; Van der Knaap, Marjo S.; Poll-The, Bwee Tien; Lindhout, Dick

Objective To assess if hearing loss is a feature of Joubert syndrome (JBS). one of the ciliopathies and therefore possibly associated with hearing loss Design: Retrospective case series. Setting University Children's Hospital Patients Dutch patients with JBS. Main outcome measures Audiological data.
Is hearing loss a feature of Joubert syndrome, a ciliopathy?

NARCIS (Netherlands)

Kroes, Hester Y.; van Zanten, Bert G. A.; de Ru, Sander A.; Boon, Maartje; Mancini, Grazia M. S.; van der Knaap, Marjo S.; Poll-The, Bwee Tien; Lindhout, Dick

2010-01-01

Objective To assess if hearing loss is a feature of Joubert syndrome (JBS). one of the ciliopathies and therefore possibly associated with hearing loss Design: Retrospective case series. Setting University Children's Hospital Patients Dutch patients with JBS. Main outcome measures Audiological data.

Design of Passive Power Filter for Hybrid Series Active Power Filter using Estimation, Detection and Classification Method

Science.gov (United States)

Swain, Sushree Diptimayee; Ray, Pravat Kumar; Mohanty, K. B.

2016-06-01

This research paper discover the design of a shunt Passive Power Filter (PPF) in Hybrid Series Active Power Filter (HSAPF) that employs a novel analytic methodology which is superior than FFT analysis. This novel approach consists of the estimation, detection and classification of the signals. The proposed method is applied to estimate, detect and classify the power quality (PQ) disturbance such as harmonics. This proposed work deals with three methods: the harmonic detection through wavelet transform method, the harmonic estimation by Kalman Filter algorithm and harmonic classification by decision tree method. From different type of mother wavelets in wavelet transform method, the db8 is selected as suitable mother wavelet because of its potency on transient response and crouched oscillation at frequency domain. In harmonic compensation process, the detected harmonic is compensated through Hybrid Series Active Power Filter (HSAPF) based on Instantaneous Reactive Power Theory (IRPT). The efficacy of the proposed method is verified in MATLAB/SIMULINK domain and as well as with an experimental set up. The obtained results confirm the superiority of the proposed methodology than FFT analysis. This newly proposed PPF is used to make the conventional HSAPF more robust and stable.
Eccrine Porocarcinoma: Patient Characteristics, Clinical and Histopathologic Features, and Treatment in 7 Cases.

Science.gov (United States)

Gómez-Zubiaur, A; Medina-Montalvo, S; Vélez-Velázquez, M D; Polo-Rodríguez, I

2017-05-01

Eccrine porocarcinoma is a rare, malignant cutaneous adnexal tumor that arises from the ducts of sweat glands. Found mainly in patients of advanced age, this tumor has diverse clinical presentations. Histology confirms the diagnosis, detects features relevant to prognosis, and guides treatment. Growth is slow, but the prognosis is poor if the tumor metastasizes to lymph nodes or visceral organs. We report 7 cases of eccrine porocarcinoma, describing patient characteristics, the clinical and histopathologic features of the tumors, and treatments used. Our observations were similar to those of other published case series. Given the lack of therapeutic algorithms or protocols for this carcinoma, we propose a decision-making schema based on our review of the literature and our experience with this case series. The algorithm centers on sentinel lymph node biopsy and histologic features. Copyright © 2016 AEDV. Publicado por Elsevier España, S.L.U. All rights reserved.
Common dental features and craniofacial development of three siblings with Ter Haar syndrome.

Science.gov (United States)

Parker, K; Pabla, R; Hay, N; Ayliffe, P

2014-02-01

Ter Haar syndrome is a rare genetic syndrome with <30 cases reported worldwide. There is nothing within the published literature regarding the dental development and dental features of these patients. This case series examines three patients with Ter Haar syndrome and tracks their dental development and identifies common dental and skeletal features. All three patients received dental treatment and regular follow-up at Great Ormond Street Hospital Dental Department. These patients have many common dental and craniofacial features which poses the question as to whether these features are due to Ter Haar syndrome.
Neuronal Population Activity in Spinal Motor Circuits

DEFF Research Database (Denmark)

Berg, Rune W.

2017-01-01

The core elements of stereotypical movements such as locomotion, scratching and breathing are generated by networks in the lower brainstem and the spinal cord. Ensemble activities in spinal motor networks had until recently been merely a black box, but with the emergence of ultra-thin Silicon multi......-electrode technology it was possible to reveal the spiking activity of larger parts of the network. A series of experiments revealed unexpected features of spinal networks, such as multiple spiking regimes and lognormal firing rate distributions. The lognormality renders the widespread idea of a typical firing rate...
Las series televisivas juveniles: tramas y conflictos en una «teen series» Television Fiction Series Targeted at Young Audience: Plots and Conflicts Portrayed in a Teen Series

Directory of Open Access Journals (Sweden)

Núria García Muñoz

2011-10-01

Full Text Available Se presentan los principales hallazgos de un estudio sobre las «teen series», es decir las series de ficción televisiva protagonizadas por personajes adolescentes y dirigidas expresamente a una audiencia juvenil. El análisis del retrato de los jóvenes representados en productos específicamente dirigidos a un público juvenil tiene un valor muy significativo tanto por la producción de ficción como por la recepción, ya que los consumidores potenciales se encuentran en un momento clave del proceso de construcción de sus identidades. Después de repasar los principales antecedentes en el estudio de la representación de los jóvenes en la ficción televisiva, se describe el marco conceptual relativo a las «teen series» y se discute su relación con el consumo juvenil. Sucesivamente se presenta un estudio de caso que consiste en un análisis de contenido de la serie norteamericana «Dawson’s creek», realizado sobre una muestra representativa de tres temporadas de la serie, para analizar dos grupos de variables: variables relativas a los personajes y variables relativas a las tramas y a los conflictos. Se discuten los resultados relativos al segundo grupo de variables, con particular atención a las características de las tramas y al papel de los personajes en el desarrollo y en la resolución de las mismas. La aceptación de la identidad personal, el amor y la amistad han resultado ser las temáticas más recurrentes. Además, las relaciones sociales entre los personajes han resultado ejercer un papel fundamental en el desarrollo de las tramas y de los conflictos.This paper presents the main findings of a research project on teen series, which are television fiction series featuring teenagers and specifically targeted at a young audience. The analysis of the portrayal of young people in television fictional series specifically targeted at a young audience has a meaningful value both for television production and for audience reception
Divergent modes of enzyme inhibition in a homologous structure-activity series.

Science.gov (United States)

Ferreira, Rafaela S; Bryant, Clifford; Ang, Kenny K H; McKerrow, James H; Shoichet, Brian K; Renslo, Adam R

2009-08-27

A docking screen identified reversible, noncovalent inhibitors (e.g., 1) of the parasite cysteine protease cruzain. Chemical optimization of 1 led to a series of oxadiazoles possessing interpretable SAR and potencies as much as 500-fold greater than 1. Detailed investigation of the SAR series subsequently revealed that many members of the oxadiazole class (and surprisingly also 1) act via divergent modes of inhibition (competitive or via colloidal aggregation) depending on the assay conditions employed.
The association between built environment features and physical activity in the Australian context: a synthesis of the literature

Directory of Open Access Journals (Sweden)

Belen Zapata-Diomedi

2016-06-01

Full Text Available Abstract Background There is growing evidence indicating that the built environment is a determinant of physical activity. However, despite the well-established health benefits of physical activity this is rarely considered in urban planning. We summarised recent Australian evidence for the association built environment-physical activity among adults. This summary aims to inform policy makers who advocate for the consideration of health in urban planning. Methods A combination of built environment and physical activity terms were used to systematically identify relevant peer reviewed and grey literature. Results A total of 23 studies were included, providing 139 tests of associations between specific built environment features and physical activity. Of the total, 84 relationships using objective measures of built environment attributes were evaluated, whereas 55 relationships using self-reported measures were evaluated. Our results indicate that walkable neighbourhoods with a wide range of local destinations to go to, as well as a diverse use of land, encourage physical activity among their residents. Conclusions This research provides a summary of recent Australian evidence on built environments that are most favourable for physical activity. Features of walkability and availability of destinations within walking distance should be accounted for in the development or redevelopment of urban areas. Our findings emphasise the importance of urban planning for health via its impact on population levels of physical activity.
Unique features in the ARIES glovebox line

International Nuclear Information System (INIS)

Martinez, H.E.; Brown, W.G.; Flamm, B.; James, C.A.; Laskie, R.; Nelson, T.O.; Wedman, D.E.

1998-01-01

A series of unique features have been incorporated into the Advanced Recovery and Integrated Extraction System (ARIES) at the Los Alamos National Laboratory, TA-55 Plutonium Facility. The features enhance the material handling in the process of the dismantlement of nuclear weapon primaries in the glovebox line. Incorporated into these features are the various plutonium process module's different ventilation zone requirements that the material handling systems must meet. These features include a conveyor system that consists of a remotely controlled cart that transverses the length of the conveyor glovebox, can be operated from a remote location and can deliver process components to the entrance of any selected module glovebox. Within the modules there exists linear motion material handling systems with lifting hoist, which are controlled via an Allen Bradley control panel or local control panels. To remove the packaged products from the hot process line, the package is processed through an air lock/electrolytic decontamination process that removes the radioactive contamination from the outside of the package container and allows the package to be removed from the process line
Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

Science.gov (United States)

Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

2015-02-01

We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.
The Risk Return Relationship: Evidence from Index Return and Realised Variance Series

OpenAIRE

Minxian Yang

2014-01-01

The risk return relationship is analysed in bivariate models for return and realised variance(RV) series. Based on daily time series from 21 international market indices for more than 13 years (January 2000 to February 2013), the empirical findings support the arguments of risk return tradeoff, volatility feedback and statistical balance. It is reasoned that the empirical risk return relationship is primarily shaped by two important data features: the negative contemporaneous correlation betw...
Conjunctive Coding of Complex Object Features

Science.gov (United States)

Erez, Jonathan; Cusack, Rhodri; Kendall, William; Barense, Morgan D.

2016-01-01

Critical to perceiving an object is the ability to bind its constituent features into a cohesive representation, yet the manner by which the visual system integrates object features to yield a unified percept remains unknown. Here, we present a novel application of multivoxel pattern analysis of neuroimaging data that allows a direct investigation of whether neural representations integrate object features into a whole that is different from the sum of its parts. We found that patterns of activity throughout the ventral visual stream (VVS), extending anteriorly into the perirhinal cortex (PRC), discriminated between the same features combined into different objects. Despite this sensitivity to the unique conjunctions of features comprising objects, activity in regions of the VVS, again extending into the PRC, was invariant to the viewpoints from which the conjunctions were presented. These results suggest that the manner in which our visual system processes complex objects depends on the explicit coding of the conjunctions of features comprising them. PMID:25921583
ACER Mathematics Profile Series: Number Test. (Test Booklet, Answer and Record Sheet, Score Key, and Teachers Handbook).

Science.gov (United States)

Cornish, Greg; Wines, Robin

The Number Test of the ACER Mathematics Profile Series, contains 30 items, for each of three suggested grade levels: 7-8, 8-9, and 9-10. Raw scores on all tests in the ACER Mathematics Profile Series (Number, Operations, Space and Measurement) are converted to a common scale called MAPS, a major feature of the Series. Based on the Rasch Model,…
Time series analysis of the developed financial markets' integration using visibility graphs

Science.gov (United States)

Zhuang, Enyu; Small, Michael; Feng, Gang

2014-09-01

A time series representing the developed financial markets' segmentation from 1973 to 2012 is studied. The time series reveals an obvious market integration trend. To further uncover the features of this time series, we divide it into seven windows and generate seven visibility graphs. The measuring capabilities of the visibility graphs provide means to quantitatively analyze the original time series. It is found that the important historical incidents that influenced market integration coincide with variations in the measured graphical node degree. Through the measure of neighborhood span, the frequencies of the historical incidents are disclosed. Moreover, it is also found that large "cycles" and significant noise in the time series are linked to large and small communities in the generated visibility graphs. For large cycles, how historical incidents significantly affected market integration is distinguished by density and compactness of the corresponding communities.
Joint Markov Blankets in Feature Sets Extracted from Wavelet Packet Decompositions

Directory of Open Access Journals (Sweden)

Gert Van Dijck

2011-07-01

Full Text Available Since two decades, wavelet packet decompositions have been shown effective as a generic approach to feature extraction from time series and images for the prediction of a target variable. Redundancies exist between the wavelet coefficients and between the energy features that are derived from the wavelet coefficients. We assess these redundancies in wavelet packet decompositions by means of the Markov blanket filtering theory. We introduce the concept of joint Markov blankets. It is shown that joint Markov blankets are a natural extension of Markov blankets, which are defined for single features, to a set of features. We show that these joint Markov blankets exist in feature sets consisting of the wavelet coefficients. Furthermore, we prove that wavelet energy features from the highest frequency resolution level form a joint Markov blanket for all other wavelet energy features. The joint Markov blanket theory indicates that one can expect an increase of classification accuracy with the increase of the frequency resolution level of the energy features.
Evaluation of coexistence of cancer and active tuberculosis; 16 case series

Directory of Open Access Journals (Sweden)

Beyhan Çakar

Full Text Available Introduction: Tuberculosis is an important risk factor for cancer. Pulmonary TB and lung cancer(LC may mimic each other especially in the aspect of the clinical and radiological features. The aim of the study was to evaluate the features and risk factors of cases with coexistence cancer and active TB. Methodology: We retrospectively reviewed the medical records of patients with coexisting TB and cancer a period from 2009 to 2014. We evaluated demographic data, the ways diagnosis of TB cases, the location of TB and cancer, TB treatment results of the cases. Results: We recorded 374 TB cases in our dyspensary at this study period. In 16 (4% of these cases, a coexistence of cancer and TB was detected. The male/female ratio was 12/4. The mean age was 62,12 ± 15,13 years. There were TST results except three cases. There were ten pulmonary TB and six extra-pulmonary TB (four peripheral lymphadenopathy TB, one abdominal TB lymphadenopathy and one salivary gland TB. Cancer types were as follows; eight lung cancer, two breast cancer, one base of tongue, one endometrium cancer, one hypopharyngeal cancer, one stomach cancer, one bladder cancer and one maxillary cancer. Diagnosis of all cases was confirmed by bacteriologic and/or histopathological examination. Squamous cell carcinoma was the most common type of cancers. This rate was 9/16. All TB cases were new. There were risk factors out of two case in the cases. Five cases were died during TB treatment. Others completed TB treatment without any complication. Conclusions: In our study, the coexistence of LC and pulmonary TB was more common. The local immunity is deteriorated in cancer cases. If there is pulmonary infiltrates in lung or peripheral lymphadenopathy, we must search tuberculosis too out of metastatic lesion and other infectious diseases. We should not make delay in the diagnosis of active TB in cancer cases. Keywords: Coexistent, Cancer, Tuberculosis, Tuberculosis treatment
PAH features within few hundred parsecs of active galactic nuclei

Science.gov (United States)

Jensen, J. J.; Hönig, S. F.; Rakshit, S.; Alonso-Herrero, A.; Asmus, D.; Gandhi, P.; Kishimoto, M.; Smette, A.; Tristram, K. R. W.

2017-09-01

Spectral features from polycyclic aromatic hydrocarbon (PAH) molecules observed in the mid-infrared (mid-IR) range are typically used to infer the amount of recent and ongoing star formation on kiloparsec scales around active galactic nuclei (AGN) where more traditional methods fail. This method assumes that the observed PAH features are excited predominantly by star formation. With current ground-based telescopes and the upcoming James Webb Space Telescope, much smaller spatial scales can be probed and we aim at testing if this assumption still holds in the range of few tens to few hundreds of parsecs. For that, we spatially map the emitted 11.3 μm PAH surface flux as a function of distance from 0.4-4 arcsec from the centre in 28 nearby AGN using ground-based high-angular-resolution mid-IR spectroscopy. We detect and extract the 11.3 μm PAH feature in 13 AGN. The fluxes within each aperture are scaled to a luminosity-normalized distance from the nucleus to be able to compare intrinsic spatial scales of AGN radiation spanning about two orders of magnitude in luminosity. For this, we establish an empirical relation between the absorption-corrected X-ray luminosity and the sublimation radius in these sources. Once normalized, the radial profiles of the emitted PAH surface flux show similar radial slopes, with a power-law index of approximately -1.1, and similar absolute values, consistent within a factor of a few of each other as expected from the uncertainty in the intrinsic scale estimate. We interpret this as evidence that the profiles are caused by a common compact central physical process, either the AGN itself or circumnuclear star formation linked in strength to the AGN power. A photoionization-based model of an AGN exciting dense clouds in its environment can reproduce the observed radial slope and confirms that the AGN radiation field is strong enough to explain the observed PAH surface fluxes within ∼10-500 pc of the nucleus. Our results advice caution
Optical computing: introduction by the feature editors.

Science.gov (United States)

Li, Y; Tanida, J; Tooley, F; Wagner, K

1996-03-10

This feature issue of Applied Optics: Information Processing contains 19 papers on Optical Computing. Many of these papers are expanded versions of presentations given at the Optical Society of America's Sixth Topical Meeting on Optical Computing held in Salt Lake City, Utah, in March 1995. This introduction provides a brief historical account of the series of optical computing meetings and a brief review of the papers contained in this special issue.
Exploring spatial–temporal dynamics of fire regime features in mainland Spain

Directory of Open Access Journals (Sweden)

A. Jiménez-Ruano

2017-10-01

Full Text Available This paper explores spatial–temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial – regional and provincial/NUTS3 – levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974–2013. Temporal shifts in fire features are investigated by means of change point detection procedures – Pettitt test, AMOC (at most one change, PELT (pruned exact linear time and BinSeg (binary segmentation – at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann–Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA and varimax rotation to trend outputs – mainly Sen's slope values – to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann–Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1, summer burnt area (PC2, large fires (PC3 and natural fires (PC4.
Designing healthy communities: creating evidence on metrics for built environment features associated with walkable neighbourhood activity centres.

Science.gov (United States)

Gunn, Lucy Dubrelle; Mavoa, Suzanne; Boulangé, Claire; Hooper, Paula; Kavanagh, Anne; Giles-Corti, Billie

2017-12-04

Evidence-based metrics are needed to inform urban policy to create healthy walkable communities. Most active living research has developed metrics of the environment around residential addresses, ignoring other important walking locations. Therefore, this study examined: metrics for built environment features surrounding local shopping centres, (known in Melbourne, Australia as neighbourhood activity centres (NACs) which are typically anchored by a supermarket); the association between NACs and transport walking; and, policy compliance for supermarket provision. In this observational study, cluster analysis was used to categorize 534 NACs in Melbourne, Australia by their built environment features. The NACS were linked to eligible Victorian Integrated Survey of Travel Activity 2009-2010 (VISTA) survey participants (n=19,984). Adjusted multilevel logistic regressions estimated associations between each cluster typology and two outcomes of daily walking: any transport walking; and, any 'neighbourhood' transport walking. Distance between residential dwellings and closest NAC was assessed to evaluate compliance with local planning policy on supermarket locations. Metrics for 19 built environment features were estimated and three NAC clusters associated with walkability were identified. NACs with significantly higher street connectivity (mean:161, SD:20), destination diversity (mean:16, SD:0.4); and net residential density (mean:77, SD:65) were interpreted as being 'highly walkable' when compared with 'low walkable' NACs, which had lower street connectivity (mean:57, SD:15); destination diversity (mean:11, SD:3); and net residential density (mean:10, SD:3). The odds of any daily transport walking was 5.85 times higher (95% CI: 4.22, 8.11), and for any 'neighborhood' transport walking 8.66 (95% CI: 5.89, 12.72) times higher, for residents whose closest NAC was highly walkable compared with those living near low walkable NACs. Only highly walkable NACs met the policy
On clustering fMRI time series

DEFF Research Database (Denmark)

Goutte, Cyril; Toft, Peter Aundal; Rostrup, E.

1999-01-01

Analysis of fMRI time series is often performed by extracting one or more parameters for the individual voxels. Methods based, e.g., on various statistical tests are then used to yield parameters corresponding to probability of activation or activation strength. However, these methods do...

Outlier Detection in Structural Time Series Models

DEFF Research Database (Denmark)

Marczak, Martyna; Proietti, Tommaso

investigate via Monte Carlo simulations how this approach performs for detecting additive outliers and level shifts in the analysis of nonstationary seasonal time series. The reference model is the basic structural model, featuring a local linear trend, possibly integrated of order two, stochastic seasonality......Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has attracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The general......–to–specific approach to the detection of structural change, currently implemented in Autometrics via indicator saturation, has proven to be both practical and effective in the context of stationary dynamic regression models and unit–root autoregressions. By focusing on impulse– and step–indicator saturation, we...
Nonlinear time series analysis with R

CERN Document Server

Huffaker, Ray; Rosa, Rodolfo

2017-01-01

In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behavior, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis, along with scientific principles and other expert information, guide the specification of mechanistic models that serve to explain real-world behavior rather than merely reproducing it. Often there is a misconception regarding the complexity of the level of mathematics needed to understand and utilize the tools of NLTS (for instance Chaos theory). However, mathematics used in NLTS is much simpler than many other subjec...
Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.

Science.gov (United States)

Yuan, Yuan; Chen, Yi-Ping Phoebe; Ni, Shengyu; Xu, Augix Guohua; Tang, Lin; Vingron, Martin; Somel, Mehmet; Khaitovich, Philipp

2011-08-18

Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.
PyEEG: an open source Python module for EEG/MEG feature extraction.

Science.gov (United States)

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.
Supporting the material control and accountancy system with physical protection system features

International Nuclear Information System (INIS)

Miyoshi, D.S.; Olson, C.E.; Caskey, D.L.

1984-01-01

Most physical security functions can be accomplished by a range of alternative features. Careful design can provide comparable levels of security regardless of which option is chosen, albeit with possible differences in cost and efficiency. However, the effectiveness and especially the cost and efficiency of the material control and accounting system may be strongly influenced by the selection of a particular design approach to physical security. In this paper, a series of examples are cited to illustrate the effects that particular physical protection design choices may have. The examples have been chosen from several systems engineering projects at facilities within the DOE nuclear community. These examples are generalized, and a series of design principles are proposed for integrating physical security with material control and accounting by appropriate selection of alternative features. 2 references, 6 figures
Supporting the material control and accountancy system with physical protection system features

International Nuclear Information System (INIS)

Miyoshi, D.S.; Caskey, D.L.; Olson, C.E.

1984-01-01

Most physical security functions can be accomplished by a range of alternative features. Careful design can provide comparable levels of security regardless of which option is chosen, albeit with possible differences in cost and efficiency. However, the effectiveness and especially the cost and efficiency of the material control and accounting system may be strongly influenced by the selection of a particular design approach to physical security. In this paper, a series of examples are cited to illustrate the effects that particular physical protection design choices may have. The examples have been chosen from several systems engineering projects at facilities within the DOE nuclear community. These examples are generalized, and a series of design principles are proposed for integrating physical security with MC and A by appropriate selection of alternative features
Stacked Heterogeneous Neural Networks for Time Series Forecasting

Directory of Open Access Journals (Sweden)

Florin Leon

2010-01-01

Full Text Available A hybrid model for time series forecasting is proposed. It is a stacked neural network, containing one normal multilayer perceptron with bipolar sigmoid activation functions, and the other with an exponential activation function in the output layer. As shown by the case studies, the proposed stacked hybrid neural model performs well on a variety of benchmark time series. The combination of weights of the two stack components that leads to optimal performance is also studied.
Head, Heart, & Hooves: Horse Raising Activities. Level 2. 4-H Skills for Life Animal Series. National 4-H Curriculum. BU-08054

Science.gov (United States)

Neiberger-Miller, Ami

2004-01-01

This is the second in a series of five horse project activity guides for youth. Levels 1-3 focus on "horse-less" activities, while Levels 4 and 5 zero in on riding and horsemanship. Each guide has an achievement program to encourage youth to learn and develop life skills. The assistance of a horse project helper in completing the achievement…
Non-linear time series extreme events and integer value problems

CERN Document Server

Turkman, Kamil Feridun; Zea Bermudez, Patrícia

2014-01-01

This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time ...
Optimizing the coefficients of the leading terms of the Born Series: FWI+MVA+more

KAUST Repository

Alkhalifah, Tariq Ali

2017-05-26

The scattering series theoretically utilizes a model perturbation framework to explain the difference between the seismic modeled data corresponding to a background model and those measured in the field corresponding to the real Earth. These perturbations include short wavelength features like those predicted by full waveform inversion (FWI) gradients, and long wavelength features often constrained by migration velocity analysis (MVA) objectives. The Born series, however, is not a convergent series. If the perturbations are large, we probably will not be able to explain the data difference. Thus, using the leading terms of the Born in an iterative process, in which they are scaled properly, allows us to avoid such limitations and update the short and long wavelength components of the velocity model. In fact, the FWI update is manifested in the first term of the Born series, and the MVA update is represented by the transmission (first Fresnel zone) part of the second term. In this case, FWI and MVA are code names for dividing the optimized update to reflectivity based portions and those adequate for the background, respectively. Examples on synthetic and real data demonstrate this logic.
Biological time series analysis using a context free language: applicability to pulsatile hormone data.

Directory of Open Access Journals (Sweden)

Dennis A Dean

Full Text Available We present a novel approach for analyzing biological time-series data using a context-free language (CFL representation that allows the extraction and quantification of important features from the time-series. This representation results in Hierarchically AdaPtive (HAP analysis, a suite of multiple complementary techniques that enable rapid analysis of data and does not require the user to set parameters. HAP analysis generates hierarchically organized parameter distributions that allow multi-scale components of the time-series to be quantified and includes a data analysis pipeline that applies recursive analyses to generate hierarchically organized results that extend traditional outcome measures such as pharmacokinetics and inter-pulse interval. Pulsicons, a novel text-based time-series representation also derived from the CFL approach, are introduced as an objective qualitative comparison nomenclature. We apply HAP to the analysis of 24 hours of frequently sampled pulsatile cortisol hormone data, which has known analysis challenges, from 14 healthy women. HAP analysis generated results in seconds and produced dozens of figures for each participant. The results quantify the observed qualitative features of cortisol data as a series of pulse clusters, each consisting of one or more embedded pulses, and identify two ultradian phenotypes in this dataset. HAP analysis is designed to be robust to individual differences and to missing data and may be applied to other pulsatile hormones. Future work can extend HAP analysis to other time-series data types, including oscillatory and other periodic physiological signals.
Kearns–Sayre syndrome: a case series of 35 adults and children

Directory of Open Access Journals (Sweden)

Khambatta S

2014-07-01

Full Text Available Sherezade Khambatta, Douglas L Nguyen, Thomas J Beckman, Christopher M Wittich Division of General Internal Medicine, Mayo Clinic, Rochester, MN, USA Background: Kearns–Sayre syndrome (KSS is a rare mitochondrial cytopathy, first described at Mayo Clinic in 1958. Aims: We aimed to define patient and disease characteristics in a large group of adult and pediatric patients with KSS. Methods: We retrospectively searched the Mayo Clinic medical index patient database for the records of patients with KSS between 1976 and 2009. The 35 patients identified with KSS were analyzed in terms of demographic characteristics, presenting signs and symptoms, diagnostic features, clinical evolution, and associations between disease features and the development of disability. Results: The mean (standard [SD] age at KSS presentation was 17 (10 years, but the mean age at diagnosis was 26 (15 years. Ophthalmologic symptoms developed in all patients, and neurologic and cardiac involvement was common. Only four patients (11% in the series died, but all deaths were from sudden cardiac events. The development of physical disability was significantly associated with cognitive decline (P=0.004 but not with other clinical features, such as sex or sudden cardiac death. Conclusion: We report the largest case series to date of patients with KSS from a single institution. In addition to the conduction system abnormalities identified in previous series, our cohort included patients with syncope and sudden cardiac death. This underscores the need to consider formal electrophysiologic studies and prophylactic defibrillators in patients with KSS. Keywords: heart block, mitochondrial diseases, ophthalmoplegia, retinitis pigmentosa
Fourier series

CERN Document Server

Tolstov, Georgi P

1962-01-01

Richard A. Silverman's series of translations of outstanding Russian textbooks and monographs is well-known to people in the fields of mathematics, physics, and engineering. The present book is another excellent text from this series, a valuable addition to the English-language literature on Fourier series.This edition is organized into nine well-defined chapters: Trigonometric Fourier Series, Orthogonal Systems, Convergence of Trigonometric Fourier Series, Trigonometric Series with Decreasing Coefficients, Operations on Fourier Series, Summation of Trigonometric Fourier Series, Double Fourie
MOBBED: a computational data infrastructure for handling large collections of event-rich time series datasets in MATLAB.

Science.gov (United States)

Cockfield, Jeremy; Su, Kyungmin; Robbins, Kay A

2013-01-01

Experiments to monitor human brain activity during active behavior record a variety of modalities (e.g., EEG, eye tracking, motion capture, respiration monitoring) and capture a complex environmental context leading to large, event-rich time series datasets. The considerable variability of responses within and among subjects in more realistic behavioral scenarios requires experiments to assess many more subjects over longer periods of time. This explosion of data requires better computational infrastructure to more systematically explore and process these collections. MOBBED is a lightweight, easy-to-use, extensible toolkit that allows users to incorporate a computational database into their normal MATLAB workflow. Although capable of storing quite general types of annotated data, MOBBED is particularly oriented to multichannel time series such as EEG that have event streams overlaid with sensor data. MOBBED directly supports access to individual events, data frames, and time-stamped feature vectors, allowing users to ask questions such as what types of events or features co-occur under various experimental conditions. A database provides several advantages not available to users who process one dataset at a time from the local file system. In addition to archiving primary data in a central place to save space and avoid inconsistencies, such a database allows users to manage, search, and retrieve events across multiple datasets without reading the entire dataset. The database also provides infrastructure for handling more complex event patterns that include environmental and contextual conditions. The database can also be used as a cache for expensive intermediate results that are reused in such activities as cross-validation of machine learning algorithms. MOBBED is implemented over PostgreSQL, a widely used open source database, and is freely available under the GNU general public license at http://visual.cs.utsa.edu/mobbed. Source and issue reports for MOBBED
Realistic Free-Spins Features Increase Preference for Slot Machines.

Science.gov (United States)

Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.
Identifying Key Features of Effective Active Learning: The Effects of Writing and Peer Discussion

Science.gov (United States)

Pangle, Wiline M.; Wyatt, Kevin H.; Powell, Karli N.; Sherwood, Rachel E.

2014-01-01

We investigated some of the key features of effective active learning by comparing the outcomes of three different methods of implementing active-learning exercises in a majors introductory biology course. Students completed activities in one of three treatments: discussion, writing, and discussion + writing. Treatments were rotated weekly between three sections taught by three different instructors in a full factorial design. The data set was analyzed by generalized linear mixed-effect models with three independent variables: student aptitude, treatment, and instructor, and three dependent (assessment) variables: change in score on pre- and postactivity clicker questions, and coding scores on in-class writing and exam essays. All independent variables had significant effects on student performance for at least one of the dependent variables. Students with higher aptitude scored higher on all assessments. Student scores were higher on exam essay questions when the activity was implemented with a writing component compared with peer discussion only. There was a significant effect of instructor, with instructors showing different degrees of effectiveness with active-learning techniques. We suggest that individual writing should be implemented as part of active learning whenever possible and that instructors may need training and practice to become effective with active learning. PMID:25185230
Problems of Software Detection of Periodic Features in a Time ...

African Journals Online (AJOL)

Problems arise when attempts are made to extract automatically, visually obvious periodic features indicative of defects in a vibration time series for diagnosis using computers. Such problems may be interpretational in nature arising either from insufficient knowledge of the mechanism, or the convolution of the source signal ...
[Importance of the hyperuricaemia, gout and gender nosological features in the activity of general practitioner - family doctor].

Science.gov (United States)

Rudichenko, V M

2012-01-01

In this article there were analyzed gender data about features of hyperuricaemia and gout: women are much older at the onset of gout arthritis (one of main reasons, probably, makes menopause by itself), have more associated comorbid deseases as hypertension and kidney failure and drinks less alcoholic beverages. It was noticed, that typical localisation of the lesion on the first toe is less often in women, and women are more inclined to use diuretics among medical drugs. Abovementioned clinical features are of some importance for the broad activity of general practitioners - family doctors. Gender features of polyarthicular gout are not uniformed. Scientific researches confirmed possibility of the genetic basis of the uric acid metabolism, which influences some fenotypical features of the organism. Several genes are known for their influence on serum uric acid: PDZK1, GCKR, SLC2A9, ABCG2, LRRC16A, SLC17A3, SLC16A9 and SLC22A12. However, conclusions of the research works confirm the necessity of scientific clarification of the importance of different factors of gender differences.
Imaging features of rosette-forming glioneuronal tumours (RGNTs): A series of seven cases

Energy Technology Data Exchange (ETDEWEB)

Medhi, Gorky; Prasad, Chandrajit; Saini, Jitender; Pendharkar, Hima; Bhat, Maya Dattatraya [National Institute of Mental Health and Neurosciences, Department of Neuroimaging and Interventional Radiology, Bangalore (India); Pandey, Paritosh [National Institute of Mental Health and Neurosciences, Department of Neurosurgery, Bangalore (India); Muthane, Yasha [National Institute of Mental Health and Neurosciences, Department of Neuropathology, Bangalore (India)

2016-01-15

Rosette-forming glioneuronal tumours (RGNTs) are a recently described, rare, distinct nosological entity of the glioneuronal family. We describe imaging findings (CT and MRI) in seven patients with RGNTs. This retrospective study includes seven RGNT patients (4 male, 3 female; age range: 7-42 years; mean age: 25 years) diagnosed and treated at our institute. MR studies were performed on 3 T and 1.5-T clinical MR systems. All patients were reviewed by two experienced neuroradiologists and imaging findings were tabulated. Five tumours were located in the posterior fossa, and two were in the pineal region. One of the tumours demonstrated multiple satellite lesions, which involved the midbrain, pons, medulla as well as the cervical cord. Tumours located in the pineal region compressed the 3rd ventricle/aqueduct and extended below the tentorium cerebelli. All the tumours demonstrated enhancement, and susceptibility was evident in six of the seven patients. CSF dissemination was present in two patients. RGNTs are usually solid-cystic tumours and frequently demonstrate peripheral/heterogeneous enhancement upon post-contrast study. Haemorrhage is a common feature which may not be evident on CT. Cerebrospinal fluid (CSF) dissemination is a feature and appropriate imaging should be performed whenever an RGNT is suspected. (orig.)
Imaging features of rosette-forming glioneuronal tumours (RGNTs): A series of seven cases

International Nuclear Information System (INIS)

Medhi, Gorky; Prasad, Chandrajit; Saini, Jitender; Pendharkar, Hima; Bhat, Maya Dattatraya; Pandey, Paritosh; Muthane, Yasha

2016-01-01

Rosette-forming glioneuronal tumours (RGNTs) are a recently described, rare, distinct nosological entity of the glioneuronal family. We describe imaging findings (CT and MRI) in seven patients with RGNTs. This retrospective study includes seven RGNT patients (4 male, 3 female; age range: 7-42 years; mean age: 25 years) diagnosed and treated at our institute. MR studies were performed on 3 T and 1.5-T clinical MR systems. All patients were reviewed by two experienced neuroradiologists and imaging findings were tabulated. Five tumours were located in the posterior fossa, and two were in the pineal region. One of the tumours demonstrated multiple satellite lesions, which involved the midbrain, pons, medulla as well as the cervical cord. Tumours located in the pineal region compressed the 3rd ventricle/aqueduct and extended below the tentorium cerebelli. All the tumours demonstrated enhancement, and susceptibility was evident in six of the seven patients. CSF dissemination was present in two patients. RGNTs are usually solid-cystic tumours and frequently demonstrate peripheral/heterogeneous enhancement upon post-contrast study. Haemorrhage is a common feature which may not be evident on CT. Cerebrospinal fluid (CSF) dissemination is a feature and appropriate imaging should be performed whenever an RGNT is suspected. (orig.)

Brief Report: Major Depressive Disorder with Psychotic Features in Williams Syndrome--A Case Series

Science.gov (United States)

Valdes, Francisca; Keary, Christopher J.; Mullett, Jennifer E.; Palumbo, Michelle L.; Waxler, Jessica L.; Pober, Barbara R.; McDougle, Christopher J.

2018-01-01

Descriptions of individuals with Williams syndrome (WS) and co-morbid major depressive disorder (MDD) with psychotic features have not appeared in the literature. In addition to reviewing previous reports of psychotic symptoms in persons with WS, this paper introduces clinical histories and therapeutic management strategies for three previously…
Historical aspects of arising and features of activity of startup companies: accounting and economic aspects

Directory of Open Access Journals (Sweden)

S.F. Legenchuk

2016-07-01

Full Text Available The history of arising and development of the concept of «startup company» have been studied and the importance of their activities have been determined. Using the largest startups (Amazon, Google, Salesforce, VMware, Facebook, Twitter, Groupon, Zynga and Аpple the main components of their activity have been determined. Because of the lack of the scientific literature that directly investigated this topic the approaches of different authors from electronic sources have been systematized and the most used of them have been analyzed. The own vision of the definition of «startup company» and its key features have been formulated as a result of the research. The place of a startup company in the system of economic categories such as an economic activity, results of company activities, accounting, analysis and risks have been determined. The impact of the consequences of risks (positive and negative of economic activity on the future of companies have been considered. The value of accounting and analysis for the economic activity of startup companies have been evaluated.
New significance test methods for Fourier analysis of geophysical time series

Directory of Open Access Journals (Sweden)

Z. Zhang

2011-09-01

Full Text Available When one applies the discrete Fourier transform to analyze finite-length time series, discontinuities at the data boundaries will distort its Fourier power spectrum. In this paper, based on a rigid statistics framework, we present a new significance test method which can extract the intrinsic feature of a geophysical time series very well. We show the difference in significance level compared with traditional Fourier tests by analyzing the Arctic Oscillation (AO and the Nino3.4 time series. In the AO, we find significant peaks at about 2.8, 4.3, and 5.7 yr periods and in Nino3.4 at about 12 yr period in tests against red noise. These peaks are not significant in traditional tests.
Production design and location in the Danish television drama series Arvingerne

DEFF Research Database (Denmark)

Ion Wille, Jakob; Waade, Anne Marit

2016-01-01

Television fiction is most often referred to as the writer’s medium, whereas feature film is generally perceived as the vision and work of the director. In this article we turn our focus to the role and function of the production design and locations in developing and conceptualising a television...... drama series. We use the drama series Arvingerne (The Legacy, DR, 2014-2015) to illustrate how design ideas can be developed at an early stage, in pre-pre-production, as part of a collective, creative process that includes the scriptwriter, the production designer and the producer. Our empirical study...... of the series draws on an analysis of in-house design/concept documents [1], interviews with the production designer Mia Stensgaard [2], and promotional material made for the series [3]. The paper also draws on visual analysis of the finished production. Our overall argument is that the importance of location...
Synthesis and Structure-Activity Relationships of a Series of Aporphine Derivatives with Antiarrhythmic Activities and Acute Toxicity

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Hui Wang

2016-11-01

Full Text Available Some aporphine alkaloids, such as crebanine, were found to present arrhythmic activity and also higher toxicity. A series of derivatives were synthesized by using three kinds of aporphine alkaloids (crebanine, isocorydine, and stephanine as lead compounds. Chemical methods, including ring-opening reaction, bromination, methylation, acetylation, quaternization, and dehydrogenation, were adopted. Nineteen target derivatives were evaluated for their antiarrhythmic potential in the mouse model of ventricular fibrillation (VF, induced by CHCl3, and five of the derivatives were investigated further in the rat model of arrhythmia, induced by BaCl2. Meanwhile, preliminary structure-activity/toxicity relationship analyses were carried out. Significantly, N-acetamidesecocrebanine (1d, three bromo-substituted products of crebanine (2a, 2b, 2c, N-methylcrebanine (2d, and dehydrostephanine (4a displayed antiarrhythmic effects in the CHCl3-induced model. Among them, 7.5 mg/kg of 2b was able to significantly reduce the incidence of VF induced by CHCl3 (p < 0.05, increase the number of rats that resumed sinus rhythm from arrhythmia, induced by BaCl2 (p < 0.01, and the number of rats that maintained sinus rhythm for more than 20 min (p < 0.01. Therefore, 2b showed remarkably higher antiarrhythmic activity and a lower toxicity (LD50 = 59.62 mg/kg, mice, simultaneously, indicating that 2b could be considered as a promising candidate in the treatment of arrhythmia. Structural-activity analysis suggested that variationsin antiarrhythmic efficacy and toxicity of aporphines were related to the C-1,C-2-methylenedioxy group on ring A, restricted ring B structural conformation, N-quaternization of ring B, levoduction of 6a in ring C, and the 8-, 9-, 10-methoxy groups on ring D on the skeleton.
MEL-N16: A Series of Novel Endomorphin Analogs with Good Analgesic Activity and a Favorable Side Effect Profile.

Science.gov (United States)

Liu, Xin; Zhao, Long; Wang, Yuan; Zhou, Jingjing; Wang, Dan; Zhang, Yixin; Zhang, Xianghui; Wang, Zhaojuan; Yang, Dongxu; Mou, Lingyun; Wang, Rui

2017-10-18

Opioid peptides are neuromodulators that bind to opioid receptors and reduce pain sensitivity. Endomorphins are among the most active endogenous opioid peptides, and they have good affinity and selectivity toward the μ opioid receptor. However, their clinical usage is hindered by their inability to cross the blood-brain barrier and their poor in vivo activity after peripheral injection. In order to overcome these defects, we have designed and synthesized a series of novel endomorphin analogs with multiple site modifications. Radioligand binding, cAMP accumulation, and β-arrestin-2 recruitment assays were employed to determine the activity of synthesized endomorphin analogs toward opioid receptors. The blood-brain barrier permeability and antinociceptive effect of these analogs were determined in several rodent models of acute and persistent pain. In addition, the side effects of the analogs were examined. The radioligand binding assay and functional activity examination indicated that the MEL-N16 series of compounds were more active agonists against μ opioid receptor than were the parent peptides. Notably, the analogs displayed biased downstream signaling toward G-protein pathways over β-arrestin-2 recruitment. The analogs showed highly potent antinociceptive effects in the tested nociceptive models. In comparison with endomorphins, the synthesized analogs were better able to penetrate the blood-brain barrier and exerted their pain regulatory activity in the central nervous system after peripheral injection. These analogs also have lower tendency to cause side effects than morphine does at similar or equal antinociceptive doses. The MEL-N16 compounds have highly potent and efficacious analgesic effects in various pain models with a favorable side effect profile.
Activism as a feature of mental health and wellbeing for racialized immigrant women in a Canadian context.

Science.gov (United States)

MacDonnell, Judith A; Dastjerdi, Mahdieh; Khanlou, Nazilla; Bokore, Nimo; Tharao, Wangari

2017-02-01

Although immigrant women bear a disproportionate burden of chronic disease and mental health issues, limited research addresses how to promote their mental wellbeing. The authors first describe grounded theory findings from community-based focus group research with 57 racialized immigrant women in Toronto, Canada that used a critical gender and intersectional lens to explore the links among settlement, wellbeing, and activism. Secondly, a community mobilization strategy is described whereby racialized immigrant women discuss activism as a feature of wellbeing in various language communities while creating meaningful health promotion resources. Implications for creating activism-based initiatives to promote women's wellbeing are discussed.
Time domain series system definition and gear set reliability modeling

International Nuclear Information System (INIS)

Xie, Liyang; Wu, Ningxiang; Qian, Wenxue

2016-01-01

Time-dependent multi-configuration is a typical feature for mechanical systems such as gear trains and chain drives. As a series system, a gear train is distinct from a traditional series system, such as a chain, in load transmission path, system-component relationship, system functioning manner, as well as time-dependent system configuration. Firstly, the present paper defines time-domain series system to which the traditional series system reliability model is not adequate. Then, system specific reliability modeling technique is proposed for gear sets, including component (tooth) and subsystem (tooth-pair) load history description, material priori/posterior strength expression, time-dependent and system specific load-strength interference analysis, as well as statistically dependent failure events treatment. Consequently, several system reliability models are developed for gear sets with different tooth numbers in the scenario of tooth root material ultimate tensile strength failure. The application of the models is discussed in the last part, and the differences between the system specific reliability model and the traditional series system reliability model are illustrated by virtue of several numerical examples. - Highlights: • A new type of series system, i.e. time-domain multi-configuration series system is defined, that is of great significance to reliability modeling. • Multi-level statistical analysis based reliability modeling method is presented for gear transmission system. • Several system specific reliability models are established for gear set reliability estimation. • The differences between the traditional series system reliability model and the new model are illustrated.
`Indoor` series vending machines; `Indoor` series jido hanbaiki

Energy Technology Data Exchange (ETDEWEB)

Gensui, T.; Kida, A. [Fuji Electric Co. Ltd., Tokyo (Japan); Okumura, H. [Fuji Denki Reiki Co. Ltd., Tokyo (Japan)

1996-07-10

This paper introduces three series of vending machines that were designed to match the interior of an office building. The three series are vending machines for cups, paper packs, cans, and tobacco. Among the three series, `Interior` series has a symmetric design that was coated in a grain pattern. The inside of the `Interior` series is coated by laser satin to ensure a sense of superior quality and a refined style. The push-button used for product selection is hot-stamped on the plastic surface to ensure the hair-line luster. `Interior Phase II` series has a bay window design with a sense of superior quality and lightness. The inside of the `Interior Phase II` series is coated by laser satin. `Interior 21` series is integrated with the wall except the sales operation panel. The upper and lower dress panels can be detached and attached. The door lock is a wire-type structure with high operativity. The operation block is coated by titanium color. The dimensions of three series are standardized. 6 figs., 1 tab.
Case series: toxicity from 25B-NBOMe--a cluster of N-bomb cases.

Science.gov (United States)

Gee, Paul; Schep, Leo J; Jensen, Berit P; Moore, Grant; Barrington, Stuart

2016-01-01

Background A new class of hallucinogens called NBOMes has emerged. This class includes analogues 25I-NBOMe, 25C-NBOMe and 25B-NBOMe. Case reports and judicial seizures indicate that 25I-NBOMe and 25C-NBOMe are more prevalently abused. There have been a few confirmed reports of 25B-NBOMe use or toxicity. Report Observational case series. This report describes a series of 10 patients who suffered adverse effects from 25B-NBOMe. Hallucinations and violent agitation predominate along with serotonergic/stimulant signs such as mydriasis, tachycardia, hypertension and hyperthermia. The majority (7/10) required sedation with benzodiazepines. Analytical method 25B-NBOMe concentrations in plasma and urine were quantified in all patients using a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. Peak plasma levels were measured between 0.7-10.1 ng/ml. Discussion The NBOMes are desired by users because of their hallucinogenic and stimulant effects. They are often sold as LSD or synthetic LSD. Reported cases of 25B- NBOMe toxicity are reviewed and compared to our series. Seizures and one pharmacological death have been described but neither were observed in our series. Based on our experience with cases of mild to moderate toxicity, we suggest that management should be supportive and focused on preventing further (self) harm. High doses of benzodiazepines may be required to control agitation. Patients who develop significant hyperthermia need to be actively managed. Conclusions Effects from 25B-NBOMe in our series were similar to previous individual case reports. The clinical features were also similar to effects from other analogues in the class (25I-NBOMe, 25C-NBOMe). Violent agitation frequently present along with signs of serotonergic stimulation. Hyperthermia, rhabdomyolysis and kidney injury were also observed.
A Reception Analysis on the Youth Audiences of TV Series in Marivan

Directory of Open Access Journals (Sweden)

Omid Karimi

2014-03-01

Full Text Available The aim of this article is to describe the role of foreign media as the agitators of popular culture. For that with reception analysis it’s pay to describe decoding of youth audiences about this series. Globalization theory and Reception in Communication theory are formed the theoretical system of current article. The methodology in this research is qualitative one, and two techniques as in-depth interview and observation are used for data collection. The results show different people based on individual features, social and cultural backgrounds have inclination toward special characters and identify with them. This inclination so far the audience fallow the series because of his/her favorite character. Also there is a great compatibility between audience backgrounds and their receptions. A number of audience have criticized the series and point out the negative consequences on its society. However, seeing the series continue; really they prefer watching series enjoying to risks of it.
Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

Directory of Open Access Journals (Sweden)

Francisco Javier Ordóñez

2016-01-01

Full Text Available Human activity recognition (HAR tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i is suitable for multimodal wearable sensors; (ii can perform sensor fusion naturally; (iii does not require expert knowledge in designing features; and (iv explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation.
Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition.

Science.gov (United States)

Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-18

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters' influence on performance to provide insights about their optimisation.
Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

Science.gov (United States)

Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-01

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation. PMID:26797612
Time series analysis methods and applications for flight data

CERN Document Server

Zhang, Jianye

2017-01-01

This book focuses on different facets of flight data analysis, including the basic goals, methods, and implementation techniques. As mass flight data possesses the typical characteristics of time series, the time series analysis methods and their application for flight data have been illustrated from several aspects, such as data filtering, data extension, feature optimization, similarity search, trend monitoring, fault diagnosis, and parameter prediction, etc. An intelligent information-processing platform for flight data has been established to assist in aircraft condition monitoring, training evaluation and scientific maintenance. The book will serve as a reference resource for people working in aviation management and maintenance, as well as researchers and engineers in the fields of data analysis and data mining.
Complexation of amidocarbamoyl phosphine oxides with Ln+3 (Ln = La, Nd, Pm, Sm and Eu) cation series: structural and thermodynamical features

International Nuclear Information System (INIS)

Hosseinnejad, Tayebeh; Kazemi, Tayebeh

2016-01-01

In the present study, we have mainly investigated the nature of interactions in Ln 3+ (Ln = La, Nd, Pm, Sm, Eu) complexes with amidocarbamoyl methyl phosphine oxide (CMPO) and amidocarbamoyl propyl phosphine oxide (CPPO) ligands based on density functional theory (DFT) approaches. In the first step, thermodynamical properties for complexation of CMPO and CPPO ligands with Ln 3+ cation series have been determined in the gas phase and with the presence of three solvents: n-hexane, chloroform and toluene, via polarized continuum model (PCM) computations. The trend of metal-ligand interaction strength has been analyzed and compared with the trend of ionic hardness within the series of lanthanide cations and different size of alkyl chain of amidocarbamoyl phosphine oxide ligand. The calculated thermochemical results in the gas and solution phases reveals that there is a consistency between increasing trend in the hardness of Ln 3+ cation series and also electron-donating property of alkyl chain with increasing in thermodynamical stability of [Ln-CMPO] 3+ and [Ln-CPPO] 3+ complex series. We have also demonstrated that in the complexation reaction of all complex series, using n-hexane as solvent is more favorable thermodynamically than chloroform and toluene. It should be stated that this issue has been observed in many experiments. Finally, analysis of calculated deformation energies and also the variation in bond order of some selected key bonds in CMPO and CPPO ligands and their corresponded Ln 3+ complexes series show a similar trend with increasing in the hardness of Ln 3+ cation series and electron-donating of alkyl chain of amidocarbamoyl phosphine oxide ligand.
Prediction of consensus binding mode geometries for related chemical series of positive allosteric modulators of adenosine and muscarinic acetylcholine receptors.

Science.gov (United States)

Sakkal, Leon A; Rajkowski, Kyle Z; Armen, Roger S

2017-06-05

Following insights from recent crystal structures of the muscarinic acetylcholine receptor, binding modes of Positive Allosteric Modulators (PAMs) were predicted under the assumption that PAMs should bind to the extracellular surface of the active state. A series of well-characterized PAMs for adenosine (A 1 R, A 2A R, A 3 R) and muscarinic acetylcholine (M 1 R, M 5 R) receptors were modeled using both rigid and flexible receptor CHARMM-based molecular docking. Studies of adenosine receptors investigated the molecular basis of the probe-dependence of PAM activity by modeling in complex with specific agonist radioligands. Consensus binding modes map common pharmacophore features of several chemical series to specific binding interactions. These models provide a rationalization of how PAM binding slows agonist radioligand dissociation kinetics. M 1 R PAMs were predicted to bind in the analogous M 2 R PAM LY2119620 binding site. The M 5 R NAM (ML-375) was predicted to bind in the PAM (ML-380) binding site with a unique induced-fit receptor conformation. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Imaging features of intracerebral hemorrhage with cerebral amyloid angiopathy: Systematic review and meta-analysis.

Directory of Open Access Journals (Sweden)

Neshika Samarasekera

Full Text Available We sought to summarize Computed Tomography (CT/Magnetic Resonance Imaging (MRI features of intracerebral hemorrhage (ICH associated with cerebral amyloid angiopathy (CAA in published observational radio-pathological studies.In November 2016, two authors searched OVID Medline (1946-, Embase (1974- and relevant bibliographies for studies of imaging features of lobar or cerebellar ICH with pathologically proven CAA ("CAA-associated ICH". Two authors assessed studies' diagnostic test accuracy methodology and independently extracted data.We identified 22 studies (21 cases series and one cross-sectional study with controls of CT features in 297 adults, two cross-sectional studies of MRI features in 81 adults and one study which reported both CT and MRI features in 22 adults. Methods of CAA assessment varied, and rating of imaging features was not masked to pathology. The most frequently reported CT features of CAA-associated ICH in 21 case series were: subarachnoid extension (pooled proportion 82%, 95% CI 69-93%, I2 = 51%, 12 studies and an irregular ICH border (64%, 95% CI 32-91%, I2 = 85%, five studies. CAA-associated ICH was more likely to be multiple on CT than non-CAA ICH in one cross-sectional study (CAA-associated ICH 7/41 vs. non-CAA ICH 0/42; χ2 = 7.8, p = 0.005. Superficial siderosis on MRI was present in 52% of CAA-associated ICH (95% CI 39-65%, I2 = 35%, 3 studies.Subarachnoid extension and an irregular ICH border are common imaging features of CAA-associated ICH, but methodologically rigorous diagnostic test accuracy studies are required to determine the sensitivity and specificity of these features.
Fast region-based object detection and tracking using correlation of features

CSIR Research Space (South Africa)

Senekal, F

2010-11-01

Full Text Available and track a target object (or objects) over a series of digital images. Visual target tracking can be accomplished by feature-based or region-based approaches. In feature-based approaches, interest points are calculated in a digital image, and a local...-time performance based on the computational power that is available on a specific platform. To further reduce the computational requirements, process- ing is restricted to the region of interest (ROI). The region of interest is provided as an input parameter...
Dynamical analysis and visualization of tornadoes time series.

Directory of Open Access Journals (Sweden)

António M Lopes

Full Text Available In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Dynamical analysis and visualization of tornadoes time series.

Science.gov (United States)

Lopes, António M; Tenreiro Machado, J A

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.
"Observation Obscurer" - Time Series Viewer, Editor and Processor

Science.gov (United States)

Andronov, I. L.

The program is described, which contains a set of subroutines suitable for East viewing and interactive filtering and processing of regularly and irregularly spaced time series. Being a 32-bit DOS application, it may be used as a default fast viewer/editor of time series in any compute shell ("commander") or in Windows. It allows to view the data in the "time" or "phase" mode, to remove ("obscure") or filter outstanding bad points; to make scale transformations and smoothing using few methods (e.g. mean with phase binning, determination of the statistically opti- mal number of phase bins; "running parabola" (Andronov, 1997, As. Ap. Suppl, 125, 207) fit and to make time series analysis using some methods, e.g. correlation, autocorrelation and histogram analysis: determination of extrema etc. Some features have been developed specially for variable star observers, e.g. the barycentric correction, the creation and fast analysis of "OC" diagrams etc. The manual for "hot keys" is presented. The computer code was compiled with a 32-bit Free Pascal (www.freepascal.org).
A Data-Driven Modeling Strategy for Smart Grid Power Quality Coupling Assessment Based on Time Series Pattern Matching

Directory of Open Access Journals (Sweden)

Hao Yu

2018-01-01

Full Text Available This study introduces a data-driven modeling strategy for smart grid power quality (PQ coupling assessment based on time series pattern matching to quantify the influence of single and integrated disturbance among nodes in different pollution patterns. Periodic and random PQ patterns are constructed by using multidimensional frequency-domain decomposition for all disturbances. A multidimensional piecewise linear representation based on local extreme points is proposed to extract the patterns features of single and integrated disturbance in consideration of disturbance variation trend and severity. A feature distance of pattern (FDP is developed to implement pattern matching on univariate PQ time series (UPQTS and multivariate PQ time series (MPQTS to quantify the influence of single and integrated disturbance among nodes in the pollution patterns. Case studies on a 14-bus distribution system are performed and analyzed; the accuracy and applicability of the FDP in the smart grid PQ coupling assessment are verified by comparing with other time series pattern matching methods.
Specific features of domestic banks activity in the factoring services market

Directory of Open Access Journals (Sweden)

Trygub Olena V.

2014-01-01

Full Text Available The article analyses specific features of formation and development of the domestic factoring market. In the result of the study the article establishes that development of factoring in Ukraine took place due to active participation of banking institutions in this process and nowadays they are leaders in the domestic factoring services market due to possessing significant competitive advantages if compared with non-banking companies that specialise in factoring. The article detects that nowadays the banks are not only offerers of factoring services and finance factoring operations of other market participants, but also take an active part in establishment of factoring branches and are consumers of factoring services. In order to accelerate development of international factoring in Ukraine, the article offers such forms of state support of banks, which render factoring services to domestic exporters. The article recommends to focus banks’ attention, under modern conditions that are characterised with volatility of financial markets, on factoring servicing of those clients, whom they have long business relations with, without jeopardising themselves through provision of factoring services to a big number of small debtors. The article provides schemes of banks’ co-operation in the sphere of “non-classic” factoring with accredited factoring companies.
Development and application of a modified dynamic time warping algorithm (DTW-S to analyses of primate brain expression time series

Directory of Open Access Journals (Sweden)

Vingron Martin

2011-08-01

Full Text Available Abstract Background Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Results Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. Conclusions The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.
Depth estimation of features in video frames with improved feature matching technique using Kinect sensor

Science.gov (United States)

Sharma, Kajal; Moon, Inkyu; Kim, Sung Gaun

2012-10-01

Estimating depth has long been a major issue in the field of computer vision and robotics. The Kinect sensor's active sensing strategy provides high-frame-rate depth maps and can recognize user gestures and human pose. This paper presents a technique to estimate the depth of features extracted from video frames, along with an improved feature-matching method. In this paper, we used the Kinect camera developed by Microsoft, which captured color and depth images for further processing. Feature detection and selection is an important task for robot navigation. Many feature-matching techniques have been proposed earlier, and this paper proposes an improved feature matching between successive video frames with the use of neural network methodology in order to reduce the computation time of feature matching. The features extracted are invariant to image scale and rotation, and different experiments were conducted to evaluate the performance of feature matching between successive video frames. The extracted features are assigned distance based on the Kinect technology that can be used by the robot in order to determine the path of navigation, along with obstacle detection applications.
Relationship between the latest activity of mare volcanism and topographic features of the Moon

Science.gov (United States)

Kato, Shinsuke; Morota, Tomokatsu; Yamaguchi, Yasushi; Watanabe, Sei-ichiro; Otake, Hisashi; Ohtake, Makiko

2016-04-01

Lunar mare basalts provide insights into compositions and thermal history of lunar mantle. According to crater counting analysis with remote sensing data, the model ages of mare basalt units indicate a second peak of magma activity at the end of mare volcanism (~2 Ga), and the latest eruptions were limited in the Procellarum KREEP Terrane (PKT), which has high abundances of heat-producing elements. In order to understand the mechanism for causing the second peak and its magma source, we examined the correlation between the titanium contents and eruption ages of mare basalt units using compositional and chronological data updated by SELENE/Kaguya. Although no systematic relationship is observed globally, a rapid increase in mean titanium (Ti) content occurred at 2.3 Ga in the PKT, suggesting that the magma source of mare basalts changed at that time. The high-Ti basaltic eruption, which occurred at the late stage of mare volcanism, can be correlated with the second peak of volcanic activity at ~2 Ga. The latest volcanic activity can be explained by a high-Ti hot plume originated from the core-mantle boundary. If the hot plume was occurred, the topographic features formed by the hot plume may be remained. We calculated the difference between topography and selenoid and found the circular feature like a plateau in the center of the PKT, which scale is ~1000 km horizontal and ~500 m vertical. We investigated the timing of ridge formation in the PKT by using stratigraphic relationship between mare basalts and ridges. The ridges were formed before and after the high-Ti basaltic eruptions and seem to be along with the plateau. These results suggest that the plateau formation is connected with the high-Ti basaltic eruptions.
Time irreversibility and intrinsics revealing of series with complex network approach

Science.gov (United States)

Xiong, Hui; Shang, Pengjian; Xia, Jianan; Wang, Jing

2018-06-01

In this work, we analyze time series on the basis of the visibility graph algorithm that maps the original series into a graph. By taking into account the all-round information carried by the signals, the time irreversibility and fractal behavior of series are evaluated from a complex network perspective, and considered signals are further classified from different aspects. The reliability of the proposed analysis is supported by numerical simulations on synthesized uncorrelated random noise, short-term correlated chaotic systems and long-term correlated fractal processes, and by the empirical analysis on daily closing prices of eleven worldwide stock indices. Obtained results suggest that finite size has a significant effect on the evaluation, and that there might be no direct relation between the time irreversibility and long-range correlation of series. Similarity and dissimilarity between stock indices are also indicated from respective regional and global perspectives, showing the existence of multiple features of underlying systems.
Extending GIS Technology to Study Karst Features of Southeastern Minnesota

Science.gov (United States)

Gao, Y.; Tipping, R. G.; Alexander, E. C.; Alexander, S. C.

2001-12-01

This paper summarizes ongoing research on karst feature distribution of southeastern Minnesota. The main goals of this interdisciplinary research are: 1) to look for large-scale patterns in the rate and distribution of sinkhole development; 2) to conduct statistical tests of hypotheses about the formation of sinkholes; 3) to create management tools for land-use managers and planners; and 4) to deliver geomorphic and hydrogeologic criteria for making scientifically valid land-use policies and ethical decisions in karst areas of southeastern Minnesota. Existing county and sub-county karst feature datasets of southeastern Minnesota have been assembled into a large GIS-based database capable of analyzing the entire data set. The central database management system (DBMS) is a relational GIS-based system interacting with three modules: GIS, statistical and hydrogeologic modules. ArcInfo and ArcView were used to generate a series of 2D and 3D maps depicting karst feature distributions in southeastern Minnesota. IRIS ExplorerTM was used to produce satisfying 3D maps and animations using data exported from GIS-based database. Nearest-neighbor analysis has been used to test sinkhole distributions in different topographic and geologic settings. All current nearest-neighbor analyses testify that sinkholes in southeastern Minnesota are not evenly distributed in this area (i.e., they tend to be clustered). More detailed statistical methods such as cluster analysis, histograms, probability estimation, correlation and regression have been used to study the spatial distributions of some mapped karst features of southeastern Minnesota. A sinkhole probability map for Goodhue County has been constructed based on sinkhole distribution, bedrock geology, depth to bedrock, GIS buffer analysis and nearest-neighbor analysis. A series of karst features for Winona County including sinkholes, springs, seeps, stream sinks and outcrop has been mapped and entered into the Karst Feature Database
An Incremental Classification Algorithm for Mining Data with Feature Space Heterogeneity

Directory of Open Access Journals (Sweden)

Yu Wang

2014-01-01

Full Text Available Feature space heterogeneity often exists in many real world data sets so that some features are of different importance for classification over different subsets. Moreover, the pattern of feature space heterogeneity might dynamically change over time as more and more data are accumulated. In this paper, we develop an incremental classification algorithm, Supervised Clustering for Classification with Feature Space Heterogeneity (SCCFSH, to address this problem. In our approach, supervised clustering is implemented to obtain a number of clusters such that samples in each cluster are from the same class. After the removal of outliers, relevance of features in each cluster is calculated based on their variations in this cluster. The feature relevance is incorporated into distance calculation for classification. The main advantage of SCCFSH lies in the fact that it is capable of solving a classification problem with feature space heterogeneity in an incremental way, which is favorable for online classification tasks with continuously changing data. Experimental results on a series of data sets and application to a database marketing problem show the efficiency and effectiveness of the proposed approach.
Development of in-series piezoelectric bimorph bending beam actuators for active flow control applications

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Chan, Wilfred K.; Clingman, Dan J.; Amitay, Michael

2016-04-01

Piezoelectric materials have long been used for active flow control purposes in aerospace applications to increase the effectiveness of aerodynamic surfaces on aircraft, wind turbines, and more. Piezoelectric actuators are an appropriate choice due to their low mass, small dimensions, simplistic design, and frequency response. This investigation involves the development of piezoceramic-based actuators with two bimorphs placed in series. Here, the main desired characteristic was the achievable displacement amplitude at specific driving voltages and frequencies. A parametric study was performed, in which actuators with varying dimensions were fabricated and tested. These devices were actuated with a sinusoidal waveform, resulting in an oscillating platform on which to mount active flow control devices, such as dynamic vortex generators. The main quantification method consisted of driving these devices with different voltages and frequencies to determine their free displacement, blocking force, and frequency response. It was found that resonance frequency increased with shorter and thicker actuators, while free displacement increased with longer and thinner actuators. Integration of the devices into active flow control test modules is noted. In addition to physical testing, a quasi-static analytical model was developed and compared with experimental data, which showed close correlation for both free displacement and blocking force.
Choices and Consequences: The Role of Players in The Walking Dead: A Telltale Game Series

Directory of Open Access Journals (Sweden)

Genovesi Matteo

2017-12-01

Full Text Available One of the most important features in a transmedia structure, as Max Giovagnoli argues in his book Transmedia: Storytelling e Comunicazione [Transmedia: Storytelling and Communication], is the development of the user’s decision-making power, defined by the author as “choice excitement.” In this, every choice of the user should have a consequence in the fictional universe of a specific franchise. Consequently, a narrative universe that wants to emphasize choice excitement and the active role of people can focus on video games, where the interactive approach is prominent. This essay will discuss a specific video game, based on the famous franchise of The Walking Dead. This brand, which appears in comic books, novels, TV series, Web episodes and video games, is analysable not only as an exemplary case of transmedia storytelling, where every ramification of the franchise published in different media is both autonomous and synergistic with the others, but also by focusing on the choice excitement of users in the first season of the video game The Walking Dead: A Telltale Game Series.
Time Series Analysis Using Geometric Template Matching.

Science.gov (United States)

Frank, Jordan; Mannor, Shie; Pineau, Joelle; Precup, Doina

2013-03-01

We present a novel framework for analyzing univariate time series data. At the heart of the approach is a versatile algorithm for measuring the similarity of two segments of time series called geometric template matching (GeTeM). First, we use GeTeM to compute a similarity measure for clustering and nearest-neighbor classification. Next, we present a semi-supervised learning algorithm that uses the similarity measure with hierarchical clustering in order to improve classification performance when unlabeled training data are available. Finally, we present a boosting framework called TDEBOOST, which uses an ensemble of GeTeM classifiers. TDEBOOST augments the traditional boosting approach with an additional step in which the features used as inputs to the classifier are adapted at each step to improve the training error. We empirically evaluate the proposed approaches on several datasets, such as accelerometer data collected from wearable sensors and ECG data.
A Series-LC-Filtered Active Trap Filter for High Power Voltage Source Inverter

DEFF Research Database (Denmark)

Bai, Haofeng; Wang, Xiongfei; Loh, Poh Chiang

2016-01-01

Passive trap filters are widely used in high power Voltage Source Inverters (VSI) for the switching harmonic attenuation. The usage of the passive trap filters requires clustered and fixed switching harmonic spectrum, which is not the case for low pulse-ratio or Variable Switching Frequency (VSF...... current control of the auxiliary converter, which can be challenging considering that the switching harmonics have very high orders. In this paper, an Active Trap Filter (ATF) based on output impedance shaping is proposed. It is able to bypass the switching harmonics by providing nearly zero output...... impedance. A series-LC-filter is used to reduce the power rating and synthesize the desired output impedance of the ATF. Compared with the existing approaches, the compensated frequency range is greatly enlarged. Also, the current reference is simply set to zero, which reduces the complexity of the control...
Exploratory data analysis of acceleration signals to select light-weight and accurate features for real-time activity recognition on smartphones.

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Khan, Adil Mehmood; Siddiqi, Muhammad Hameed; Lee, Seok-Won

2013-09-27

Smartphone-based activity recognition (SP-AR) recognizes users' activities using the embedded accelerometer sensor. Only a small number of previous works can be classified as online systems, i.e., the whole process (pre-processing, feature extraction, and classification) is performed on the device. Most of these online systems use either a high sampling rate (SR) or long data-window (DW) to achieve high accuracy, resulting in short battery life or delayed system response, respectively. This paper introduces a real-time/online SP-AR system that solves this problem. Exploratory data analysis was performed on acceleration signals of 6 activities, collected from 30 subjects, to show that these signals are generated by an autoregressive (AR) process, and an accurate AR-model in this case can be built using a low SR (20 Hz) and a small DW (3 s). The high within class variance resulting from placing the phone at different positions was reduced using kernel discriminant analysis to achieve position-independent recognition. Neural networks were used as classifiers. Unlike previous works, true subject-independent evaluation was performed, where 10 new subjects evaluated the system at their homes for 1 week. The results show that our features outperformed three commonly used features by 40% in terms of accuracy for the given SR and DW.
Cerebral oligodendroglioma: MR features indicating anaplastic changes

Energy Technology Data Exchange (ETDEWEB)

Choi, Choong Gon; Chang, Kee Hyun; Han, Moon Hee; Chi, Je Geun [Seoul National Univ., Seoul (Korea, Republic of); Yoon, Hyun Ki [Ulsan Univ., Seoul (Korea, Republic of)

1995-10-15

The purpose of this study is to find helpful MR findings for predicting anaplastic oligodendrogliomas. Retrospective analysis of 46 MR images and 37 CT scans was performed for 46 patients with pathologically-proven cerebral oligodendrogliomas. A neuropathologist graded the tumors as one of low-grade (n = 16), intermediate-grade (n = 12), or anaplastic oligodendroglioma (n 18). MR imaging features were retrospectively analysed with respect to histologic grading of the tumors. Contrast enhancement was observed always in anaplastic group (17/17), in a portion of intermediate-grade group (4/10) but not in low-grade group (0/4). Peritumoral edema was observed infrequently in anaplastic group (4/18) or intermediate-grade group (1/12). Cystic changes (25/46) or calcifications on CT Scans (14/37) were not related with histologic grading. Grossly identifiable hemorrhage was rare in this series (2/46). Among the various imaging features, only tumor enhancement and peritumoral edema were statistically significant for trend test ({rho} < 0.05). When considering the diagnosis of oligodendrogliomas, the presence of contrast enhancement or peritumoral edema is a helpful features suggesting anaplastic oligodendrogliomas.
Entropic Analysis of Electromyography Time Series

Science.gov (United States)

Kaufman, Miron; Sung, Paul

2005-03-01

We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) time series. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.
Physical activity advertisements that feature daily well-being improve autonomy and body image in overweight women but not men.

Science.gov (United States)

Segar, Michelle L; Updegraff, John A; Zikmund-Fisher, Brian J; Richardson, Caroline R

2012-01-01

The reasons for exercising that are featured in health communications brand exercise and socialize individuals about why they should be physically active. Discovering which reasons for exercising are associated with high-quality motivation and behavioral regulation is essential to promoting physical activity and weight control that can be sustained over time. This study investigates whether framing physical activity in advertisements featuring distinct types of goals differentially influences body image and behavioral regulations based on self-determination theory among overweight and obese individuals. Using a three-arm randomized trial, overweight and obese women and men (aged 40-60 yr, n = 1690) read one of three ads framing physical activity as a way to achieve (1) better health, (2) weight loss, or (3) daily well-being. Framing effects were estimated in an ANOVA model with pairwise comparisons using the Bonferroni correction. This study showed that there are immediate framing effects on physical activity behavioral regulations and body image from reading a one-page advertisement about physical activity and that gender and BMI moderate these effects. Framing physical activity as a way to enhance daily well-being positively influenced participants' perceptions about the experience of being physically active and enhanced body image among overweight women, but not men. The experiment had less impact among the obese study participants compared to those who were overweight. These findings support a growing body of research suggesting that, compared to weight loss, framing physical activity for daily well-being is a better gain-frame message for overweight women in midlife.
Feature issue of digital holography and 3D imaging (DH) introduction.

Science.gov (United States)

Hayasaki, Yoshio; Zhou, Changhe; Popescu, Gabriel; Onural, Levent

2014-11-17

The OSA Topical Meeting "Digital Holography and 3D Imaging (DH)," was held in Seattle, Washington, July 13-17, 2014. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year Optics Express (OE) and AO jointly decided to have one such feature issue in each journal. The DH meeting will continue in the future, as expected, and the next meeting is scheduled to be held on 24 - 28 May 2015, in Shanghai Institute of Optics and Fine Mechanics, Shanghai, China.
Feature Statistics Modulate the Activation of Meaning during Spoken Word Processing

Science.gov (United States)

Devereux, Barry J.; Taylor, Kirsten I.; Randall, Billi; Geertzen, Jeroen; Tyler, Lorraine K.

2016-01-01

Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts' features--the number of concepts they occur in ("distinctiveness/sharedness") and likelihood of co-occurrence ("correlational…

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

OpenAIRE

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting ...
What goes through the gate? Exploring interference with visual feature binding.

Science.gov (United States)

Ueno, Taiji; Mate, Judit; Allen, Richard J; Hitch, Graham J; Baddeley, Alan D

2011-05-01

A series of experiments explored the mechanisms determining the encoding and storage of features and objects in visual working memory. We contrasted the effects of three types of visual suffix on cued recall of a display of colored shapes. The suffix was presented after the display and before the recall cue. The latter was either the color or shape of one of the objects and signaled recall of the object's other feature. In Experiments 1 and 2, we found a larger effect of 'plausible' suffixes comprising features (color and shape) drawn from the experimental set, relative to the effect of 'implausible' suffixes comprising features outside the experimental set. Experiment 3 extended this pattern by showing that 'semi-plausible' suffixes containing only one feature (either color or shape) from the experimental set had an equivalent effect to those with both features from the set. Reduction in accuracy was mainly due to an increase in recall of suffix features, rather than within-display confusions. The findings suggest a feature-based filtering process in visual working memory, with any stimuli that pass through this filter serving to directly overwrite existing object representations. Copyright © 2011 Elsevier Ltd. All rights reserved.
Chest x-ray in Q-fever pneumonia: a series of 71 cases; La radiografia de torax en la neumonia por fiebre-Q. Serie de 71 casos

Energy Technology Data Exchange (ETDEWEB)

Encinas, B; Cerezal, L F; Fidalgo, I; Bustamente, M; Lopez Calderon, M [Hospital Universitario Marques de valdecilla, Santander (Spain)

1995-11-01

Chest X ray features of 71 cases of Q-fever serologically confirmed and with clinical manifestations of acute respiratory disease were retrospectively assessed in order to evaluate the radiographic features. In 68 cases (96%) The X-ray films were abnormal. Segmental consolidation, sometimes multiple and bilateral were tue most usual findings. Nodular opacities were found in 6 cases (9%) and can mimic a tumor. Cavitacion , a very unusual findings, was found in two nodular consolidations(two patients). Laminar atelectasis was less common than proviously reported. As in other series, total resolution or with minimal scars occurs within 3 months 15 refs.
Rheumatoid Arthritis Educational Video Series

Medline Plus

Full Text Available ... Patients from Johns Hopkins Stategies to Increase your Level of Physical Activity Role of Body Weight in Osteoarthritis Educational Videos for Patients Rheumatoid Arthritis Educational Video Series Psoriatic Arthritis 101 2010 E.S.C.A.P.E. Study Patient Update Transitioning the JRA ...
A technique for filling gaps in time series with complicated power spectra

International Nuclear Information System (INIS)

Brown, T.M.

1984-01-01

Fahlman and Ulrych (1982) describe a method for estimating the power and phase spectra of gapped time series, using a maximum-entropy reconstruction of the data in the gaps. It has proved difficult to apply this technique to solar oscillations data, because of the great complexity of the solar oscillations spectrum. We describe a means for avoiding this difficulty, and report the results of a series of blind tests of the modified technique. The main results of these tests are: 1. Gap-filling gives good results, provided that the signal-to-noise ration in the original data is large enough, and provided the gaps are short enough. For low-noise data, the duty cycle of the observations should not be less than about 50%. 2. The frequencies and widths of narrow spectrum features are well reproduced by the technique. 3. The technique systematically reduces the apparent amplitudes of small features in the spectrum relative to large ones. (orig.)
Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

Science.gov (United States)

Lahnakoski, Juha M; Salmi, Juha; Jääskeläinen, Iiro P; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

2012-01-01

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.
Forecasting air quality time series using deep learning.

Science.gov (United States)

Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

2018-04-13

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution
Synthesis and Activity of a New Series of(Z-3-Phenyl-2-benzoylpropenoic Acid Derivatives as Aldose Reductase Inhibitors

Directory of Open Access Journals (Sweden)

Shao-Jie Wang

2007-04-01

Full Text Available During the course of studies directed towards the discovery of novel aldose reductase inhibitors for the treatment of diabetic complications, we synthesized a series of new (Z-3-phenyl-2-benzoylpropenoic acid derivatives and tested their in vitro inhibitory activities on rat lens aldose reductase. Of these compounds, (Z-3-(3,4-dihydroxyphenyl-2-(4-methylbenzoylpropenoicacid(3k was identified as the most potent inhibitor, with an IC50 of 0.49μM. The theoretical binding mode of 3k was obtained by simulation of its docking into the active site of the human aldose reductase crystal structure.
Distribution of U and Th decay series and rare earth elements in sediments of Santos Basin. Correlation with industrial activities

International Nuclear Information System (INIS)

Silva, P.S.C.; Mazzilli, B.P.; Favaro, D.I.T.

2005-01-01

Santos Basin, located in Southwest Brazil, is considered the most important industrial region of the country. Among the industrial activities present, phosphate fertilizer plants are responsible for the production of 69 million tons of phosphogypsum waste, which is stockpiled in the surrounding environment. This waste concentrates radionuclides of the natural series as well as rare earth elements originally present in the phosphate rock used as raw material. Environmental impact of such activities in the sediments of the estuarine system by measuring the concentration of U, Th and rare earth elements and activity concentration of radionuclides 226 Ra, 228 Ra, 228 Th and 210 Pb. (author)
Application of spectral decomposition of 222Rn activity concentration signal series measured in Niedźwiedzia Cave to identification of mechanisms responsible for different time-period variations

International Nuclear Information System (INIS)

Przylibski, Tadeusz Andrzej; Wyłomańska, Agnieszka; Zimroz, Radosław; Fijałkowska-Lichwa, Lidia

2015-01-01

The authors present an application of spectral decomposition of 222 Rn activity concentration signal series as a mathematical tool used for distinguishing processes determining temporal changes of radon concentration in cave air. The authors demonstrate that decomposition of monitored signal such as 222 Rn activity concentration in cave air facilitates characterizing the processes affecting changes in the measured concentration of this gas. Thanks to this, one can better correlate and characterize the influence of various processes on radon behaviour in cave air. Distinguishing and characterising these processes enables the understanding of radon behaviour in cave environment and it may also enable and facilitate using radon as a precursor of geodynamic phenomena in the lithosphere. Thanks to the conducted analyses, the authors confirmed the unquestionable influence of convective air exchange between the cave and the atmosphere on seasonal and short-term (diurnal) changes in 222 Rn activity concentration in cave air. Thanks to the applied methodology of signal analysis and decomposition, the authors also identified a third process affecting 222 Rn activity concentration changes in cave air. This is a deterministic process causing changes in radon concentration, with a distribution different from the Gaussian one. The authors consider these changes to be the effect of turbulent air movements caused by the movement of visitors in caves. This movement is heterogeneous in terms of the number of visitors per group and the number of groups visiting a cave per day and per year. Such a process perfectly elucidates the observed character of the registered changes in 222 Rn activity concentration in one of the decomposed components of the analysed signal. The obtained results encourage further research into precise relationships between the registered 222 Rn activity concentration changes and factors causing them, as well as into using radon as a precursor of geodynamic
Homogenising time series: beliefs, dogmas and facts

Science.gov (United States)

Domonkos, P.

2011-06-01

In the recent decades various homogenisation methods have been developed, but the real effects of their application on time series are still not known sufficiently. The ongoing COST action HOME (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As a part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever before to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. Empirical results show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities often have similar statistical characteristics than natural changes caused by climatic variability, thus the pure application of the classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality than in raw time series. Some problems around detecting multiple structures of inhomogeneities, as well as that of time series comparisons within homogenisation procedures are discussed briefly in the study.
Iris-based medical analysis by geometric deformation features.

Science.gov (United States)

Ma, Lin; Zhang, D; Li, Naimin; Cai, Yan; Zuo, Wangmeng; Wang, Kuanguan

2013-01-01

Iris analysis studies the relationship between human health and changes in the anatomy of the iris. Apart from the fact that iris recognition focuses on modeling the overall structure of the iris, iris diagnosis emphasizes the detecting and analyzing of local variations in the characteristics of irises. This paper focuses on studying the geometrical structure changes in irises that are caused by gastrointestinal diseases, and on measuring the observable deformations in the geometrical structures of irises that are related to roundness, diameter and other geometric forms of the pupil and the collarette. Pupil and collarette based features are defined and extracted. A series of experiments are implemented on our experimental pathological iris database, including manual clustering of both normal and pathological iris images, manual classification by non-specialists, manual classification by individuals with a medical background, classification ability verification for the proposed features, and disease recognition by applying the proposed features. The results prove the effectiveness and clinical diagnostic significance of the proposed features and a reliable recognition performance for automatic disease diagnosis. Our research results offer a novel systematic perspective for iridology studies and promote the progress of both theoretical and practical work in iris diagnosis.
Analysis of JET ELMy time series

International Nuclear Information System (INIS)

Zvejnieks, G.; Kuzovkov, V.N.

2005-01-01

Full text: Achievement of the planned operational regime in the next generation tokamaks (such as ITER) still faces principal problems. One of the main challenges is obtaining the control of edge localized modes (ELMs), which should lead to both long plasma pulse times and reasonable divertor life time. In order to control ELMs the hypothesis was proposed by Degeling [1] that ELMs exhibit features of chaotic dynamics and thus a standard chaos control methods might be applicable. However, our findings which are based on the nonlinear autoregressive (NAR) model contradict this hypothesis for JET ELMy time-series. In turn, it means that ELM behavior is of a relaxation or random type. These conclusions coincide with our previous results obtained for ASDEX Upgrade time series [2]. [1] A.W. Degeling, Y.R. Martin, P.E. Bak, J. B.Lister, and X. Llobet, Plasma Phys. Control. Fusion 43, 1671 (2001). [2] G. Zvejnieks, V.N. Kuzovkov, O. Dumbrajs, A.W. Degeling, W. Suttrop, H. Urano, and H. Zohm, Physics of Plasmas 11, 5658 (2004)
On Sums of Numerical Series and Fourier Series

Science.gov (United States)

Pavao, H. Germano; de Oliveira, E. Capelas

2008-01-01

We discuss a class of trigonometric functions whose corresponding Fourier series, on a conveniently chosen interval, can be used to calculate several numerical series. Particular cases are presented and two recent results involving numerical series are recovered. (Contains 1 note.)
Mobility as a feature: Evidence from Zulu

Directory of Open Access Journals (Sweden)

Jochen Zeller

2016-01-01

Full Text Available This paper provides evidence for the view that syntactic movement of an element Y to a position X is not driven by features of the target X, but by features of the moving element Y. The data that constitute evidence for this type of analysis come from A-bar movement constructions (object left and right dislocation; object relativisation in the Bantu language Zulu. As I show, only object-DPs that move out of the VP in Zulu are active Goals for Agree-relations and can trigger object agreement with the verb. The fact that the functional head responsible for object agreement must be able to identify a DP in its c-command domain as an active Goal entails that the “mobility” of this DP must be encoded as a property of the DP. Based on this conclusion, I also discuss two proposals about the nature of the feature that activates a DP for movement in Zulu and examine the conditions that determine how this feature is checked and deleted through movement.
Binding of intrinsic and extrinsic features in working memory.

Science.gov (United States)

Ecker, Ullrich K H; Maybery, Murray; Zimmer, Hubert D

2013-02-01

There is ongoing debate concerning the mechanisms of feature binding in working memory. In particular, there is controversy regarding the extent to which these binding processes are automatic. The present article demonstrates that binding mechanisms differ depending on whether the to-be-integrated features are perceived as forming a coherent object. We presented a series of experiments that investigated the binding of color and shape, whereby color was either an intrinsic feature of the shape or an extrinsic feature of the shape's background. Results show that intrinsic color affected shape recognition, even when it was incidentally studied and irrelevant for the recognition task. In contrast, extrinsic color did not affect shape recognition, even when the association of color and shape was encoded and retrievable on demand. This strongly suggests that binding of intrinsic intra-item information but not extrinsic contextual information is obligatory in visual working memory. We highlight links to perception as well as implicit and explicit long-term memory, which suggest that the intrinsic-extrinsic dimension is a principle relevant to multiple domains of human cognition. 2013 APA, all rights reserved
Mobile and Wearable Device Features that Matter in Promoting Physical Activity.

Science.gov (United States)

Wang, Julie B; Cataldo, Janine K; Ayala, Guadalupe X; Natarajan, Loki; Cadmus-Bertram, Lisa A; White, Martha M; Madanat, Hala; Nichols, Jeanne F; Pierce, John P

2016-07-01

As wearable sensors/devices become increasingly popular to promote physical activity (PA), research is needed to examine how and which components of these devices people use to increase their PA levels. (1) To assess usability and level of engagement with the Fitbit One and daily SMS-based prompts in a 6-week PA intervention, and (2) to examine whether use/ level of engagement with specific intervention components were associated with PA change. Data were analyzed from a randomized controlled trial that compared (1) a wearable sensor/ device (Fitbit One) plus SMS-based PA prompts, and (2) Fitbit One only, among overweight/ obese adults (N = 67). We calculated average scores from Likert-type response items that assessed usability and level of engagement with device features (e.g., tracker, website, mobile app, and SMS-based prompts), and assessed whether such factors were associated with change in steps/day (using Actigraph GT3X+). Participants reported the Fitbit One was easy to use and the tracker helped to be more active. Those who used the Fitbit mobile app (36%) vs. those who did not (64%) had an increase in steps at 6-week follow-up, even after adjusting for previous web/app use: +545 steps/ day ( SE = 265) vs. -28 steps/ day ( SE = 242) ( p = .04). Level of engagement with the Fitbit One, particularly the mobile app, was associated with increased steps. Mobile apps can instantly display summaries of PA performance and could optimize self-regulation to activate change. More research is needed to determine whether such modalities might be cost-effective in future intervention research and practice.
Online feature selection with streaming features.

Science.gov (United States)

Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

2013-05-01

We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.
Infinite series

CERN Document Server

Hirschman, Isidore Isaac

2014-01-01

This text for advanced undergraduate and graduate students presents a rigorous approach that also emphasizes applications. Encompassing more than the usual amount of material on the problems of computation with series, the treatment offers many applications, including those related to the theory of special functions. Numerous problems appear throughout the book.The first chapter introduces the elementary theory of infinite series, followed by a relatively complete exposition of the basic properties of Taylor series and Fourier series. Additional subjects include series of functions and the app
Exploratory Data Analysis of Acceleration Signals to Select Light-Weight and Accurate Features for Real-Time Activity Recognition on Smartphones

Directory of Open Access Journals (Sweden)

Seok-Won Lee

2013-09-01

Full Text Available Smartphone-based activity recognition (SP-AR recognizes users’ activities using the embedded accelerometer sensor. Only a small number of previous works can be classified as online systems, i.e., the whole process (pre-processing, feature extraction, and classification is performed on the device. Most of these online systems use either a high sampling rate (SR or long data-window (DW to achieve high accuracy, resulting in short battery life or delayed system response, respectively. This paper introduces a real-time/online SP-AR system that solves this problem. Exploratory data analysis was performed on acceleration signals of 6 activities, collected from 30 subjects, to show that these signals are generated by an autoregressive (AR process, and an accurate AR-model in this case can be built using a low SR (20 Hz and a small DW (3 s. The high within class variance resulting from placing the phone at different positions was reduced using kernel discriminant analysis to achieve position-independent recognition. Neural networks were used as classifiers. Unlike previous works, true subject-independent evaluation was performed, where 10 new subjects evaluated the system at their homes for 1 week. The results show that our features outperformed three commonly used features by 40% in terms of accuracy for the given SR and DW.

Knowledge fusion: Time series modeling followed by pattern recognition applied to unusual sections of background data

International Nuclear Information System (INIS)

Burr, T.; Doak, J.; Howell, J.A.; Martinez, D.; Strittmatter, R.

1996-03-01

This report describes work performed during FY 95 for the Knowledge Fusion Project, which by the Department of Energy, Office of Nonproliferation and National Security. The project team selected satellite sensor data as the one main example to which its analysis algorithms would be applied. The specific sensor-fusion problem has many generic features that make it a worthwhile problem to attempt to solve in a general way. The generic problem is to recognize events of interest from multiple time series in a possibly noisy background. By implementing a suite of time series modeling and forecasting methods and using well-chosen alarm criteria, we reduce the number of false alarms. We then further reduce the number of false alarms by analyzing all suspicious sections of data, as judged by the alarm criteria, with pattern recognition methods. This report describes the implementation and application of this two-step process for separating events from unusual background. As a fortunate by-product of this activity, it is possible to gain a better understanding of the natural background
Knowledge fusion: Time series modeling followed by pattern recognition applied to unusual sections of background data

Energy Technology Data Exchange (ETDEWEB)

Burr, T.; Doak, J.; Howell, J.A.; Martinez, D.; Strittmatter, R.

1996-03-01

This report describes work performed during FY 95 for the Knowledge Fusion Project, which by the Department of Energy, Office of Nonproliferation and National Security. The project team selected satellite sensor data as the one main example to which its analysis algorithms would be applied. The specific sensor-fusion problem has many generic features that make it a worthwhile problem to attempt to solve in a general way. The generic problem is to recognize events of interest from multiple time series in a possibly noisy background. By implementing a suite of time series modeling and forecasting methods and using well-chosen alarm criteria, we reduce the number of false alarms. We then further reduce the number of false alarms by analyzing all suspicious sections of data, as judged by the alarm criteria, with pattern recognition methods. This report describes the implementation and application of this two-step process for separating events from unusual background. As a fortunate by-product of this activity, it is possible to gain a better understanding of the natural background.
Evolution of the Sunspot Number and Solar Wind B Time Series

Science.gov (United States)

Cliver, Edward W.; Herbst, Konstantin

2018-03-01

The past two decades have witnessed significant changes in our knowledge of long-term solar and solar wind activity. The sunspot number time series (1700-present) developed by Rudolf Wolf during the second half of the 19th century was revised and extended by the group sunspot number series (1610-1995) of Hoyt and Schatten during the 1990s. The group sunspot number is significantly lower than the Wolf series before ˜1885. An effort from 2011-2015 to understand and remove differences between these two series via a series of workshops had the unintended consequence of prompting several alternative constructions of the sunspot number. Thus it has been necessary to expand and extend the sunspot number reconciliation process. On the solar wind side, after a decade of controversy, an ISSI International Team used geomagnetic and sunspot data to obtain a high-confidence time series of the solar wind magnetic field strength (B) from 1750-present that can be compared with two independent long-term (> ˜600 year) series of annual B-values based on cosmogenic nuclides. In this paper, we trace the twists and turns leading to our current understanding of long-term solar and solar wind activity.
Understanding Legacy Features with Featureous

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2011-01-01

Java programs called Featureous that addresses this issue. Featureous allows a programmer to easily establish feature-code traceability links and to analyze their characteristics using a number of visualizations. Featureous is an extension to the NetBeans IDE, and can itself be extended by third...
Complexation of amidocarbamoyl phosphine oxides with Ln{sup +3} (Ln = La, Nd, Pm, Sm and Eu) cation series: structural and thermodynamical features

Energy Technology Data Exchange (ETDEWEB)

Hosseinnejad, Tayebeh; Kazemi, Tayebeh [Alzahra Univ., Tehran (Iran, Islamic Republic of). Dept. of Chemistry

2016-05-01

In the present study, we have mainly investigated the nature of interactions in Ln{sup 3+} (Ln = La, Nd, Pm, Sm, Eu) complexes with amidocarbamoyl methyl phosphine oxide (CMPO) and amidocarbamoyl propyl phosphine oxide (CPPO) ligands based on density functional theory (DFT) approaches. In the first step, thermodynamical properties for complexation of CMPO and CPPO ligands with Ln{sup 3+} cation series have been determined in the gas phase and with the presence of three solvents: n-hexane, chloroform and toluene, via polarized continuum model (PCM) computations. The trend of metal-ligand interaction strength has been analyzed and compared with the trend of ionic hardness within the series of lanthanide cations and different size of alkyl chain of amidocarbamoyl phosphine oxide ligand. The calculated thermochemical results in the gas and solution phases reveals that there is a consistency between increasing trend in the hardness of Ln{sup 3+} cation series and also electron-donating property of alkyl chain with increasing in thermodynamical stability of [Ln-CMPO]{sup 3+} and [Ln-CPPO]{sup 3+} complex series. We have also demonstrated that in the complexation reaction of all complex series, using n-hexane as solvent is more favorable thermodynamically than chloroform and toluene. It should be stated that this issue has been observed in many experiments. Finally, analysis of calculated deformation energies and also the variation in bond order of some selected key bonds in CMPO and CPPO ligands and their corresponded Ln{sup 3+} complexes series show a similar trend with increasing in the hardness of Ln{sup 3+} cation series and electron-donating of alkyl chain of amidocarbamoyl phosphine oxide ligand.
Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition

Directory of Open Access Journals (Sweden)

Kun-Ching Wang

2015-01-01

Full Text Available The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI. In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII. The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.
Building Model NASA Satellites: Elementary Students Studying Science Using a NASA-Themed Transmedia Book Featuring Digital Fabrication Activities

Science.gov (United States)

Tillman, Daniel; An, Song; Boren, Rachel; Slykhuis, David

2014-01-01

This study assessed the impact of nine lessons incorporating a NASA-themed transmedia book featuring digital fabrication activities on 5th-grade students (n = 29) recognized as advanced in mathematics based on their academic record. Data collected included a pretest and posttest of science content questions taken from released Virginia Standards…
Time series analysis as input for clinical predictive modeling: modeling cardiac arrest in a pediatric ICU.

Science.gov (United States)

Kennedy, Curtis E; Turley, James P

2011-10-24

Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1) selecting candidate variables; 2) specifying measurement parameters; 3) defining data format; 4) defining time window duration and resolution; 5) calculating latent variables for candidate variables not directly measured; 6) calculating time series features as latent variables; 7) creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8) reducing the number of candidate features; 9
FARIMA MODELING OF SOLAR FLARE ACTIVITY FROM EMPIRICAL TIME SERIES OF SOFT X-RAY SOLAR EMISSION

International Nuclear Information System (INIS)

Stanislavsky, A. A.; Burnecki, K.; Magdziarz, M.; Weron, A.; Weron, K.

2009-01-01

A time series of soft X-ray emission observed by the Geostationary Operational Environment Satellites from 1974 to 2007 is analyzed. We show that in the solar-maximum periods the energy distribution of soft X-ray solar flares for C, M, and X classes is well described by a fractional autoregressive integrated moving average model with Pareto noise. The model incorporates two effects detected in our empirical studies. One effect is a long-term dependence (long-term memory), and another corresponds to heavy-tailed distributions. The parameters of the model: self-similarity exponent H, tail index α, and memory parameter d are statistically stable enough during the periods 1977-1981, 1988-1992, 1999-2003. However, when the solar activity tends to minimum, the parameters vary. We discuss the possible causes of this evolution and suggest a statistically justified model for predicting the solar flare activity.
Structural health monitoring feature design by genetic programming

International Nuclear Information System (INIS)

Harvey, Dustin Y; Todd, Michael D

2014-01-01

Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems. (paper)
Series-parallel method of direct solar array regulation

Science.gov (United States)

Gooder, S. T.

1976-01-01

A 40 watt experimental solar array was directly regulated by shorting out appropriate combinations of series and parallel segments of a solar array. Regulation switches were employed to control the array at various set-point voltages between 25 and 40 volts. Regulation to within + or - 0.5 volt was obtained over a range of solar array temperatures and illumination levels as an active load was varied from open circuit to maximum available power. A fourfold reduction in regulation switch power dissipation was achieved with series-parallel regulation as compared to the usual series-only switching for direct solar array regulation.
Identifying key features of effective active learning: the effects of writing and peer discussion.

Science.gov (United States)

Linton, Debra L; Pangle, Wiline M; Wyatt, Kevin H; Powell, Karli N; Sherwood, Rachel E

2014-01-01

We investigated some of the key features of effective active learning by comparing the outcomes of three different methods of implementing active-learning exercises in a majors introductory biology course. Students completed activities in one of three treatments: discussion, writing, and discussion + writing. Treatments were rotated weekly between three sections taught by three different instructors in a full factorial design. The data set was analyzed by generalized linear mixed-effect models with three independent variables: student aptitude, treatment, and instructor, and three dependent (assessment) variables: change in score on pre- and postactivity clicker questions, and coding scores on in-class writing and exam essays. All independent variables had significant effects on student performance for at least one of the dependent variables. Students with higher aptitude scored higher on all assessments. Student scores were higher on exam essay questions when the activity was implemented with a writing component compared with peer discussion only. There was a significant effect of instructor, with instructors showing different degrees of effectiveness with active-learning techniques. We suggest that individual writing should be implemented as part of active learning whenever possible and that instructors may need training and practice to become effective with active learning. © 2014 D. L. Linton et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Study of the dependence of resolution temporal activity for a Philips gemini TF PET/CT scanner by applying a statistical analysis of time series; Estudio de la dependencia de la resolucion temporal con la actividad para un escaner PET-TAC philips gemini TF aplicando un analisis estadistico de series temporales

Energy Technology Data Exchange (ETDEWEB)

Sanchez Merino, G.; Cortes Rpdicio, J.; Lope Lope, R.; Martin Gonzalez, T.; Garcia Fidalgo, M. A.

2013-07-01

The aim of the present work is to study the dependence of temporal resolution with the activity using statistical techniques applied to the series of values time series measurements of temporal resolution during daily equipment checks. (Author)
SPITZER IRAC PHOTOMETRY FOR TIME SERIES IN CROWDED FIELDS

Energy Technology Data Exchange (ETDEWEB)

Novati, S. Calchi; Beichman, C. [NASA Exoplanet Science Institute, MS 100-22, California Institute of Technology, Pasadena, CA 91125 (United States); Gould, A.; Fausnaugh, M.; Gaudi, B. S.; Pogge, R. W.; Wibking, B.; Zhu, W.; Poleski, R. [Department of Astronomy, Ohio State University, 140 W. 18th Ave., Columbus, OH 43210 (United States); Yee, J. C. [Harvard-Smithsonian Center for Astrophysics, 60 Garden St., Cambridge, MA 02138 (United States); Bryden, G.; Henderson, C. B.; Shvartzvald, Y. [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States); Carey, S. [Spitzer, Science Center, MS 220-6, California Institute of Technology, Pasadena, CA (United States); Udalski, A.; Pawlak, M.; Szymański, M. K.; Skowron, J.; Mróz, P.; Kozłowski, S. [Warsaw University Observatory, Al. Ujazdowskie 4, 00-478 Warszawa (Poland); Collaboration: Spitzer team; OGLE group; and others

2015-12-01

We develop a new photometry algorithm that is optimized for the Infrared Array Camera (IRAC) Spitzer time series in crowded fields and that is particularly adapted to faint or heavily blended targets. We apply this to the 170 targets from the 2015 Spitzer microlensing campaign and present the results of three variants of this algorithm in an online catalog. We present detailed accounts of the application of this algorithm to two difficult cases, one very faint and the other very crowded. Several of Spitzer's instrumental characteristics that drive the specific features of this algorithm are shared by Kepler and WFIRST, implying that these features may prove to be a useful starting point for algorithms designed for microlensing campaigns by these other missions.
Frequencies, Laboratory Features, and Granulocyte Activation in Chinese Patients with CALR-Mutated Myeloproliferative Neoplasms.

Directory of Open Access Journals (Sweden)

Haixiu Guo

Full Text Available Somatic mutations in the CALR gene have been recently identified as acquired alterations in myeloproliferative neoplasms (MPNs. In this study, we evaluated mutation frequencies, laboratory features, and granulocyte activation in Chinese patients with MPNs. A combination of qualitative allele-specific polymerase chain reaction and Sanger sequencing was used to detect three driver mutations (i.e., CALR, JAK2V617F, and MPL. CALR mutations were identified in 8.4% of cases with essential thrombocythemia (ET and 5.3% of cases with primary myelofibrosis (PMF. Moreover, 25% of polycythemia vera, 29.5% of ET, and 48.1% of PMF were negative for all three mutations (JAK2V617F, MPL, and CALR. Compared with those patients with JAK2V617F mutation, CALR-mutated ET patients displayed unique hematological phenotypes, including higher platelet counts, and lower leukocyte counts and hemoglobin levels. Significant differences were not found between Chinese PMF patients with mutants CALR and JAK2V617F in terms of laboratory features. Interestingly, patients with CALR mutations showed markedly decreased levels of leukocyte alkaline phosphatase (LAP expression, whereas those with JAK2V617F mutation presented with elevated levels. Overall, a lower mutant rate of CALR gene and a higher triple-negative rate were identified in the cohort of Chinese patients with MPNs. This result indicates that an undiscovered mutant gene may have a significant role in these patients. Moreover, these pathological features further imply that the disease biology varies considerably between mutants CALR and JAK2V617F.
Compounding approach for univariate time series with nonstationary variances

Science.gov (United States)

Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich

2015-12-01

A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.
"May the journey continue": Earth 2 fan fiction, or Filling in gaps to revive a canceled series

Directory of Open Access Journals (Sweden)

Francesca Musiani

2010-09-01

Full Text Available This essay explores writing practices in a fan community having to give life to a story deprived of an "official" version: the television series Earth 2. I argue that fan fiction writing for this prematurely canceled series exhibits peculiar features in comparison to fan writing for established series: for example, temporality, choice of protagonists, character pairings, and challenges to the original conception(s of the series. Writing fan fiction for a canceled series is not about creating alternatives to an existing story, but about filling in gaps; it brings to light the ways in which fan fiction deals with closure. I take as a case study Earth 2, a series aired by NBC in the United States in 1994–95, whose first and only season ended in a cliffhanger episode hinting that a mysterious ailment had struck the main and most popular character. Shortly afterward, a significant number of Earth 2 Web sites, online conventions, and especially fan stories started developing; they explored what could have happened next and bore nostalgic but combative mottoes and titles such as "May the Journey Continue." I explore the specific features of Earth 2 fan fiction production and sharing by analyzing the main Earth 2 fan fiction archives on the Web and the responses to my email interviews of fan writers. Exemplars of the Earth 2 case are compared to those of other science fiction TV series, both prematurely canceled (Firefly, Space: Above and Beyond and long-lived (Babylon 5, Star Trek: Deep Space 9.
Case series and descriptive cohort studies in neurosurgery: the confusion and solution.

Science.gov (United States)

Esene, Ignatius N; Ngu, Julius; El Zoghby, Mohamed; Solaroglu, Ihsan; Sikod, Anna M; Kotb, Ali; Dechambenoit, Gilbert; El Husseiny, Hossam

2014-08-01

Case series (CS) are well-known designs in contemporary use in neurosurgery but are sometimes used in contexts that are incompatible with their true meaning as defined by epidemiologists. This inconsistent, inappropriate and incorrect use, and mislabeling impairs the appropriate indexing and sorting of evidence. Using PubMed, we systematically identified published articles that had "case series" in the "title" in 15 top-ranked neurosurgical journals from January 2008 to December 2012. The abstracts and/or full articles were scanned to identify those with descriptions of the principal method as being "case series" and then classified as "true case series" or "non-case series" by two independent investigators with 100 % inter-rater agreement. Sixty-four articles had the label "case series" in their "titles." Based on the definition of "case series" and our appraisal of the articles using Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, 18 articles (28.13 %) were true case series, while 46 (71.87 %) were mislabeled. Thirty-five articles (54.69 %) mistook retrospective (descriptive) cohorts for CS. CS are descriptive with an outcome-based sampling, while "descriptive cohorts" have an exposure-based sampling of patients, followed over time to assess outcome(s). A comparison group is not a defining feature of a cohort study and distinguishes descriptive from analytic cohorts. A distinction between a case report, case series, and descriptive cohorts is absolutely necessary to enable the appropriate indexing, sorting, and application of evidence. Researchers need better training in methods and terminology, and editors and reviewers should scrutinize more carefully manuscripts claiming to be "case series" studies.
Stimulus-Related Independent Component and Voxel-Wise Analysis of Human Brain Activity during Free Viewing of a Feature Film

Science.gov (United States)

Lahnakoski, Juha M.; Salmi, Juha; Jääskeläinen, Iiro P.; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

2012-01-01

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments. PMID:22496909
Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

Directory of Open Access Journals (Sweden)

Juha M Lahnakoski

Full Text Available Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA. Auditory annotations correlated with two independent components (IC disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

Digital database of mining-related features at selected historic and active phosphate mines, Bannock, Bear Lake, Bingham, and Caribou counties, Idaho

Science.gov (United States)

Causey, J. Douglas; Moyle, Phillip R.

2001-01-01

This report provides a description of data and processes used to produce a spatial database that delineates mining-related features in areas of historic and active phosphate mining in the core of the southeastern Idaho phosphate resource area. The data have varying degrees of accuracy and attribution detail. Classification of areas by type of mining-related activity at active mines is generally detailed; however, the spatial coverage does not differentiate mining-related surface disturbance features at many of the closed or inactive mines. Nineteen phosphate mine sites are included in the study. A total of 5,728 hc (14,154 ac), or more than 57 km2 (22 mi2), of phosphate mining-related surface disturbance are documented in the spatial coverage of the core of the southeast Idaho phosphate resource area. The study includes 4 active phosphate mines—Dry Valley, Enoch Valley, Rasmussen Ridge, and Smoky Canyon—and 15 historic phosphate mines—Ballard, Champ, Conda, Diamond Gulch, Gay, Georgetown Canyon, Henry, Home Canyon, Lanes Creek, Maybe Canyon, Mountain Fuel, Trail Canyon, Rattlesnake Canyon, Waterloo, and Wooley Valley. Spatial data on the inactive historic mines is relatively up-to-date; however, spatially described areas for active mines are based on digital maps prepared in early 1999. The inactive Gay mine has the largest total area of disturbance: 1,917 hc (4,736 ac) or about 19 km2 (7.4 mi2). It encompasses over three times the disturbance area of the next largest mine, the Conda mine with 607 hc (1,504 ac), and it is nearly four times the area of the Smoky Canyon mine, the largest of the active mines with 497 hc (1,228 ac). The wide range of phosphate mining-related surface disturbance features (approximately 80) were reduced to 13 types or features used in this study—adit and pit, backfilled mine pit, facilities, mine pit, ore stockpile, railroad, road, sediment catchment, tailings or tailings pond, topsoil stockpile, water reservoir, and disturbed
Remote Sensing Image Registration Using Multiple Image Features

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Kun Yang

2017-06-01

Full Text Available Remote sensing image registration plays an important role in military and civilian fields, such as natural disaster damage assessment, military damage assessment and ground targets identification, etc. However, due to the ground relief variations and imaging viewpoint changes, non-rigid geometric distortion occurs between remote sensing images with different viewpoint, which further increases the difficulty of remote sensing image registration. To address the problem, we propose a multi-viewpoint remote sensing image registration method which contains the following contributions. (i A multiple features based finite mixture model is constructed for dealing with different types of image features. (ii Three features are combined and substituted into the mixture model to form a feature complementation, i.e., the Euclidean distance and shape context are used to measure the similarity of geometric structure, and the SIFT (scale-invariant feature transform distance which is endowed with the intensity information is used to measure the scale space extrema. (iii To prevent the ill-posed problem, a geometric constraint term is introduced into the L2E-based energy function for better behaving the non-rigid transformation. We evaluated the performances of the proposed method by three series of remote sensing images obtained from the unmanned aerial vehicle (UAV and Google Earth, and compared with five state-of-the-art methods where our method shows the best alignments in most cases.
FEATURES OF PROVIDING STEADY INFRASTRUCTURE OF ENTREPRENEURSHIP ACTIVITY

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Vitalii A. Vernikov

2015-01-01

Full Text Available The subject / topic. This article discusses the features of sustainable infrastructure of business activity. The theme of the article is very relevant at the time of transformation and the onset of a new transitional phase in the global economy. Conclusions / significance. The overall crisis in almost every sector of Russia, demanded the application of the new ideology of the organization and business management. In Russia, a new stage in the development of business management establishment of a domestic methodology, comprehensive resources and training for the professional management on the basis of domestic achievements, global experience and creativity of its processing with the actual conditions of our country. The need to use an effective methodology for enterprise management inRussiais determined by two factors: the increasing complexity of the organization, and the fact that modern management methods widely used in countries with market economies. Imperative of our time – to find a scientific management methods in order to create effective management systems. In this paper, a study of modern methods of development and management of business structures. An important condition for achieving these objectives is to ensure the sustainability of development and functioning of the business, as well as strengthening its position and role in the development of socio-economic processes, both at the national and regional levels.Methodology. Theoretical base articles were works of domestic and foreign scholars on various aspects of the theory of the world economy. As a methodological basis used methods: analysis, synthesis, analogy, comparison, induction and deduction, mathematical and statistical (cluster, factor and the method of statistical surface.
Prostatic adenocarcinoma with glomeruloid features.

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Pacelli, A; Lopez-Beltran, A; Egan, A J; Bostwick, D G

1998-05-01

A wide variety of architectural patterns of adenocarcinoma may be seen in the prostate. We have recently encountered a hitherto-undescribed pattern of growth characterized by intraluminal ball-like clusters of cancer cells reminiscent of renal glomeruli, which we refer to as prostatic adenocarcinoma with glomeruloid features. To define the architectural features, frequency, and distribution of prostatic adenocarcinoma with glomeruloid features, we reviewed 202 totally embedded radical prostatectomy specimens obtained between October 1992 and April 1994 from the files of the Mayo Clinic. This series was supplemented by 100 consecutive needle biopsies with prostatic cancer from January to February 1996. Prostatic adenocarcinoma with glomeruloid features was characterized by round to oval epithelial tufts growing within malignant acini, often supported by a fibrovascular core. The epithelial cells were sometimes arranged in semicircular concentric rows separated by clefted spaces. In the radical prostatectomy specimens, nine cases (4.5%) had glomeruloid features. The glomeruloid pattern constituted 5% to 20% of each cancer (mean, 8.33%) and was usually located at the apex or in the peripheral zone of the prostate. Seven cases were associated with a high Gleason score (7 or 8), one with a score of 6, and one with a score of 5. All cases were associated with high-grade prostatic intraepithelial neoplasia and extensive perineural invasion. Pathological stages included T2c (three cases), T3b (four cases), and T3c (two cases); one of the T3b cases had lymph node metastases (N1). Three (3%) of 100 consecutive routine needle biopsy specimens with cancer showed glomeruloid features, and this pattern constituted 5% to 10% of each cancer (mean, 6.7%). The Gleason score was 6 for two cases and 8 for one case. Two cases were associated with high-grade prostatic intraepithelial neoplasia, and one case had perineural invasion. Glomeruloid features were not observed in any benign or
Characterization of the LAWB99-series and ORLEC-series Glasses

Energy Technology Data Exchange (ETDEWEB)

Fox, K. M. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Edwards, T. B. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Riley, W. T. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2017-12-01

In this report, the Savannah River National Laboratory provides chemical analysis results for a series of simulated low activity waste (LAW) glass compositions. These data will be used in the development of improved sulfur solubility models for LAW glass. A procedure developed at the Pacific Northwest National Laboratory for producing sulfur saturated melts (SSMs) was used to fabricate the glasses characterized in this report. This method includes triplicate melting steps with excess sodium sulfate, followed by grinding and washing to remove unincorporated sulfur salts. The wash solutions were also analyzed as part of this study.
Some Characteristics Of the Financial Data Series

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Gheorghe Săvoiu

2013-05-01

Full Text Available This paper attempts to delineate from a theoretical of view the financial data series relative to other statistical data, starting from the financial econometrics’ models and from the resulting features of the specific descriptive statistics’ analysis of these characteristic series. From the analysis of these financial data during either very short and short or medium periods of time or from the information provided by the website of the Bucharest Stock Exchange (BVB, the trend of great values of kurtosis or eccentricity and skewness or asymmetry of series appears as a characteristic tendency. During a long period of time, between 1920 and 2008, this tendency seems to be more relevant, being confirmed by an excerpt from the author’s earlier paper written in 2009, concerning the statistical Dow Jones Industrial Average Index (DJIA Index. The skewness, kurtosis and normality of data distribution analysis, using Jarque Bera test, along with the identification of residual autocorrelation or serial correlation in the presence of significant residual values and heteroskedasticity are the major evaluated aspects. Finally, the author investigates the optimal way to ensure statistical comparability inflationary and deflationary method for financial series of data, and offers a solution to the selection of the appropriate indicator from the categories of the absolute values, absolute variation of the absolute values and the relative variation of the absolute values, expressed by percentages, with the finding of the latter alternative as the best alternative in the world of financial modelling of the economic and financial processes and phenomena.
An Active Power Sharing Method among Distributed Energy Sources in an Islanded Series Micro-Grid

Directory of Open Access Journals (Sweden)

Wei-Man Yang

2014-11-01

Full Text Available Active power-sharing among distributed energy sources (DESs is not only an important way to realize optimal operation of micro-grids, but also the key to maintaining stability for islanded operation. Due to the unique configuration of series micro-grids (SMGs, the power-sharing method adopted in an ordinary AC, DC, and hybrid AC/DC system cannot be directly applied into SMGs. Power-sharing in one SMG with multiple DESs involves two aspects. On the one hand, capacitor voltage stability based on an energy storage system (ESS in the DC link must be complemented. Actually, this is a problem of power allocation between the generating unit and the ESS in the DES; an extensively researched, similar problem has been grid-off distributed power generation, for which there are good solutions. On the other hand, power-sharing among DESs should be considered to optimize the operation of a series micro-grid. In this paper, a novel method combining master control with auxiliary control is proposed. Master action of a quasi-proportional resonant controller is responsible for stability of the islanded SMG; auxiliary action based on state of charge (SOC realizes coordinated allocation of load power among the source. At the same time, it is important to ensure that the auxiliary control does not influence the master action.
Innovative techniques to analyze time series of geomagnetic activity indices

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Balasis, Georgios; Papadimitriou, Constantinos; Daglis, Ioannis A.; Potirakis, Stelios M.; Eftaxias, Konstantinos

2016-04-01

Magnetic storms are undoubtedly among the most important phenomena in space physics and also a central subject of space weather. The non-extensive Tsallis entropy has been recently introduced, as an effective complexity measure for the analysis of the geomagnetic activity Dst index. The Tsallis entropy sensitively shows the complexity dissimilarity among different "physiological" (normal) and "pathological" states (intense magnetic storms). More precisely, the Tsallis entropy implies the emergence of two distinct patterns: (i) a pattern associated with the intense magnetic storms, which is characterized by a higher degree of organization, and (ii) a pattern associated with normal periods, which is characterized by a lower degree of organization. Other entropy measures such as Block Entropy, T-Complexity, Approximate Entropy, Sample Entropy and Fuzzy Entropy verify the above mentioned result. Importantly, the wavelet spectral analysis in terms of Hurst exponent, H, also shows the existence of two different patterns: (i) a pattern associated with the intense magnetic storms, which is characterized by a fractional Brownian persistent behavior (ii) a pattern associated with normal periods, which is characterized by a fractional Brownian anti-persistent behavior. Finally, we observe universality in the magnetic storm and earthquake dynamics, on a basis of a modified form of the Gutenberg-Richter law for the Tsallis statistics. This finding suggests a common approach to the interpretation of both phenomena in terms of the same driving physical mechanism. Signatures of discrete scale invariance in Dst time series further supports the aforementioned proposal.
Síndrome de Gorlin-Goltz: Serie de 7 casos Gorlin-Goltz Syndrome: A 7 cases serie

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S. Rosón-Gómez

2009-10-01

Full Text Available El Síndrome Névico Basocelular (SNBC o Síndrome de Gorlin- Goltz es un trastorno autosómico dominante, caracterizado principalmente por carcinomas basocelulares, múltiples queratoquistes y anomalías esqueléticas. El presente trabajo revisa a este desconocido síndrome dada la importancia que tiene para nosotros como especialistas. Presentamos un total de siete casos recogidos por el Servicio Cirugía Oral y Maxilofacial desde 1992 al 2008, con seguimiento medio de 10 años, determinamos la frecuencia de las características clínicas en nuestra serie de SNBC y el manejo terapéutico de las mismas.Nevoid Basal Cell Carcinoma Syndrome (NBCSS or Gorlin-Goltz Syndrome is an autosomal dominant disorder principally characterized by cutaneous basal cell carcinomas, multiple keratocysts and skeletal anomalies. This report reviews current knowledge of this disorder that is important to us as specialists. The authors reviewed seven case files from the Department of Oral and Maxillofacial Surgery of H. U. La Princesa from 1992-2008. The average follow up was 10 years; we determine the frequency of the clinical features and treatment in our series of NBCCS.
Modeling sports highlights using a time-series clustering framework and model interpretation

Science.gov (United States)

Radhakrishnan, Regunathan; Otsuka, Isao; Xiong, Ziyou; Divakaran, Ajay

2005-01-01

In our past work on sports highlights extraction, we have shown the utility of detecting audience reaction using an audio classification framework. The audio classes in the framework were chosen based on intuition. In this paper, we present a systematic way of identifying the key audio classes for sports highlights extraction using a time series clustering framework. We treat the low-level audio features as a time series and model the highlight segments as "unusual" events in a background of an "usual" process. The set of audio classes to characterize the sports domain is then identified by analyzing the consistent patterns in each of the clusters output from the time series clustering framework. The distribution of features from the training data so obtained for each of the key audio classes, is parameterized by a Minimum Description Length Gaussian Mixture Model (MDL-GMM). We also interpret the meaning of each of the mixture components of the MDL-GMM for the key audio class (the "highlight" class) that is correlated with highlight moments. Our results show that the "highlight" class is a mixture of audience cheering and commentator's excited speech. Furthermore, we show that the precision-recall performance for highlights extraction based on this "highlight" class is better than that of our previous approach which uses only audience cheering as the key highlight class.
Self-potential time series analysis in a seismic area of the Southern Apennines: preliminary results

OpenAIRE

Di Bello, G.; Lapenna, V.; Satriano, C.; Tramutoli, V.

1994-01-01

The self-potential time series recorded during the period May 1991 - August 1992 by an automatic station, located in a seismic area of Southern Apennines, is analyzed. We deal with the spectral and the statistical features of the electrotellurie precursors: they can play a major role in the approach to seismic prediction. The time-dynamics of the experimental time series is investigated, the cyclic components and the time trends are removed. In particular we consider the influence of external...
An Improved Semisupervised Outlier Detection Algorithm Based on Adaptive Feature Weighted Clustering

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Tingquan Deng

2016-01-01

Full Text Available There exist already various approaches to outlier detection, in which semisupervised methods achieve encouraging superiority due to the introduction of prior knowledge. In this paper, an adaptive feature weighted clustering-based semisupervised outlier detection strategy is proposed. This method maximizes the membership degree of a labeled normal object to the cluster it belongs to and minimizes the membership degrees of a labeled outlier to all clusters. In consideration of distinct significance of features or components in a dataset in determining an object being an inlier or outlier, each feature is adaptively assigned different weights according to the deviation degrees between this feature of all objects and that of a certain cluster prototype. A series of experiments on a synthetic dataset and several real-world datasets are implemented to verify the effectiveness and efficiency of the proposal.
a Performance Comparison of Feature Detectors for Planetary Rover Mapping and Localization

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Wan, W.; Peng, M.; Xing, Y.; Wang, Y.; Liu, Z.; Di, K.; Teng, B.; Mao, X.; Zhao, Q.; Xin, X.; Jia, M.

2017-07-01

Feature detection and matching are key techniques in computer vision and robotics, and have been successfully implemented in many fields. So far there is no performance comparison of feature detectors and matching methods for planetary mapping and rover localization using rover stereo images. In this research, we present a comprehensive evaluation and comparison of six feature detectors, including Moravec, Förstner, Harris, FAST, SIFT and SURF, aiming for optimal implementation of feature-based matching in planetary surface environment. To facilitate quantitative analysis, a series of evaluation criteria, including distribution evenness of matched points, coverage of detected points, and feature matching accuracy, are developed in the research. In order to perform exhaustive evaluation, stereo images, simulated under different baseline, pitch angle, and interval of adjacent rover locations, are taken as experimental data source. The comparison results show that SIFT offers the best overall performance, especially it is less sensitive to changes of image taken at adjacent locations.
A PERFORMANCE COMPARISON OF FEATURE DETECTORS FOR PLANETARY ROVER MAPPING AND LOCALIZATION

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W. Wan

2017-07-01

Full Text Available Feature detection and matching are key techniques in computer vision and robotics, and have been successfully implemented in many fields. So far there is no performance comparison of feature detectors and matching methods for planetary mapping and rover localization using rover stereo images. In this research, we present a comprehensive evaluation and comparison of six feature detectors, including Moravec, Förstner, Harris, FAST, SIFT and SURF, aiming for optimal implementation of feature-based matching in planetary surface environment. To facilitate quantitative analysis, a series of evaluation criteria, including distribution evenness of matched points, coverage of detected points, and feature matching accuracy, are developed in the research. In order to perform exhaustive evaluation, stereo images, simulated under different baseline, pitch angle, and interval of adjacent rover locations, are taken as experimental data source. The comparison results show that SIFT offers the best overall performance, especially it is less sensitive to changes of image taken at adjacent locations.
Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

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Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

2016-04-01

Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the
An assessment of schoolyard features and behavior patterns in children's utilization and physical activity.

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Anthamatten, Peter; Brink, Lois; Kingston, Beverly; Kutchman, Eve; Lampe, Sarah; Nigg, Claudio

2014-03-01

Careful research that elucidates how behavior relates to design in the context of elementary school grounds can serve to guide cost-efficient design with the goal of encouraging physical activity (PA). This work explores patterns in children's PA behavior within playground spaces with the specific goal of guiding healthy playground design. Data on children's utilization and PA behavior in 6 playgrounds divided into 106 observation zones were collected in 2005 and 2006 at Denver elementary school playgrounds using the System for Observing Play and Leisure Activity in Youth. Analyses of variance and t tests determined whether there were differences in utilization and behavior patterns across observations zones and between genders. This study provides evidence that children prefer to use certain types of playground zones and that they are more likely to practice moderate-to-vigorous physical activity (MVPA) in some zones. The authors observed statistically significant differences between genders. Boys were more likely to engage in MVPA in zones without equipment, girls were more likely to use zones with equipment. This work suggests that the inclusion or omission of specific playground features may have an impact on the way that children use the spaces.
Properties of Asymmetric Detrended Fluctuation Analysis in the time series of RR intervals

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Piskorski, J.; Kosmider, M.; Mieszkowski, D.; Krauze, T.; Wykretowicz, A.; Guzik, P.

2018-02-01

Heart rate asymmetry is a phenomenon by which the accelerations and decelerations of heart rate behave differently, and this difference is consistent and unidirectional, i.e. in most of the analyzed recordings the inequalities have the same directions. So far, it has been established for variance and runs based types of descriptors of RR intervals time series. In this paper we apply the newly developed method of Asymmetric Detrended Fluctuation Analysis, which so far has mainly been used with economic time series, to the set of 420 stationary 30 min time series of RR intervals from young, healthy individuals aged between 20 and 40. This asymmetric approach introduces separate scaling exponents for rising and falling trends. We systematically study the presence of asymmetry in both global and local versions of this method. In this study global means "applying to the whole time series" and local means "applying to windows jumping along the recording". It is found that the correlation structure of the fluctuations left over after detrending in physiological time series shows strong asymmetric features in both magnitude, with α+ physiological data after shuffling or with a group of symmetric synthetic time series.
Spent coffee-based activated carbon: specific surface features and their importance for H2S separation process.

Science.gov (United States)

Kante, Karifala; Nieto-Delgado, Cesar; Rangel-Mendez, J Rene; Bandosz, Teresa J

2012-01-30

Activated carbons were prepared from spent ground coffee. Zinc chloride was used as an activation agent. The obtained materials were used as a media for separation of hydrogen sulfide from air at ambient conditions. The materials were characterized using adsorption of nitrogen, elemental analysis, SEM, FTIR, and thermal analysis. Surface features of the carbons depend on the amount of an activation agent used. Even though the residual inorganic matter takes part in the H(2)S retention via salt formation, the porous surface of carbons governs the separation process. The chemical activation method chosen resulted in formation of large volume of pores with sizes between 10 and 30Å, optimal for water and hydrogen sulfide adsorption. Even though the activation process can be optimized/changed, the presence of nitrogen in the precursor (caffeine) is a significant asset of that specific organic waste. Nitrogen functional groups play a catalytic role in hydrogen sulfide oxidation. Copyright © 2011 Elsevier B.V. All rights reserved.
Imidazoquinoxaline Src-family kinase p56Lck inhibitors: SAR, QSAR, and the discovery of (S)-N-(2-chloro-6-methylphenyl)-2-(3-methyl-1-piperazinyl)imidazo- [1,5-a]pyrido[3,2-e]pyrazin-6-amine (BMS-279700) as a potent and orally active inhibitor with excellent in vivo antiinflammatory activity.

Science.gov (United States)

Chen, Ping; Doweyko, Arthur M; Norris, Derek; Gu, Henry H; Spergel, Steven H; Das, Jagabundhu; Moquin, Robert V; Lin, James; Wityak, John; Iwanowicz, Edwin J; McIntyre, Kim W; Shuster, David J; Behnia, Kamelia; Chong, Saeho; de Fex, Henry; Pang, Suhong; Pitt, Sydney; Shen, Ding Ren; Thrall, Sara; Stanley, Paul; Kocy, Octavian R; Witmer, Mark R; Kanner, Steven B; Schieven, Gary L; Barrish, Joel C

2004-08-26

A series of novel anilino 5-azaimidazoquinoxaline analogues possessing potent in vitro activity against p56Lck and T cell proliferation have been discovered. Subsequent SAR studies led to the identification of compound 4 (BMS-279700) as an orally active lead candidate that blocks the production of proinflammatory cytokines (IL-2 and TNFalpha) in vivo. In addition, an expanded set of imidazoquinoxalines provided several descriptive QSAR models highlighting the influence of significant steric and electronic features. The H-bonding (Met319) contribution to observed binding affinities within a tightly congeneric series was found to be significant.
Nonlinear dynamical modeling and prediction of the terrestrial magnetospheric activity

International Nuclear Information System (INIS)

Vassiliadis, D.

1992-01-01

The irregular activity of the magnetosphere results from its complex internal dynamics as well as the external influence of the solar wind. The dominating self-organization of the magnetospheric plasma gives rise to repetitive, large-scale coherent behavior manifested in phenomena such as the magnetic substorm. Based on the nonlinearity of the global dynamics this dissertation examines the magnetosphere as a nonlinear dynamical system using time series analysis techniques. Initially the magnetospheric activity is modeled in terms of an autonomous system. A dimension study shows that its observed time series is self-similar, but the correlation dimension is high. The implication of a large number of degrees of freedom is confirmed by other state space techniques such as Poincare sections and search for unstable periodic orbits. At the same time a stability study of the time series in terms of Lyapunov exponents suggests that the series is not chaotic. The absence of deterministic chaos is supported by the low predictive capability of the autonomous model. Rather than chaos, it is an external input which is largely responsible for the irregularity of the magnetospheric activity. In fact, the external driving is so strong that the above state space techniques give results for magnetospheric and solar wind time series that are at least qualitatively similar. Therefore the solar wind input has to be included in a low-dimensional nonautonomous model. Indeed it is shown that such a model can reproduce the observed magnetospheric behavior up to 80-90 percent. The characteristic coefficients of the model show little variation depending on the external disturbance. The impulse response is consistent with earlier results of linear prediction filters. The model can be easily extended to contain nonlinear features of the magnetospheric activity and in particular the loading-unloading behavior of substorms

Invitations to Life's Diversity. Teacher-Friendly Science Activities with Reproducible Handouts in English and Spanish. Grades 3-5. Living Things Science Series.

Science.gov (United States)

Camp, Carole Ann, Ed.

This booklet, one of six in the Living Things Science series, presents activities about diversity and classification of living things which address basic "Benchmarks" suggested by the American Association for the Advancement of Science for the Living Environment for grades 3-5. Contents include background information, vocabulary (in…
Effectiveness of Runoff Control Legislation and Active, Beautiful, Clean (ABC Waters Design Features in Singapore

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Xue Ping Goh

2017-08-01

Full Text Available Storm water management in Singapore has always been a challenge due to intense rainfall in a flat, low-lying and urbanised catchment. PUB’s (Singapore’s National Water Agency recent runoff control regulation limits the runoff coefficient to 0.55 for developments larger than or equal to 0.2 ha. The use of Active, Beautiful, Clean (ABC Waters design features are encouraged to attain peak runoff reduction. Hence the paper focuses on (i determining the actual hydrological response regime of Singapore using the relationship between runoff coefficient (C, land use and slope; and (ii investigating the effectiveness of ABC Waters design features in delaying and reducing peak runoff using a modelling approach. Based on a Storm Water Management Model (SWMM model and using elevation, land use and soil data as inputs, the peak C-values were obtained for 50 m × 50 m grid cells. The results show that for the same land use, the one with steeper slope resulted in a higher runoff coefficient. Simulations were carried out in two study areas, Green Walk District and Tengah Subcatchment, where ABC Waters design features (such as porous pavements, green roofs, rain gardens and detention tanks were incorporated to reduce C-values. Results showed that peak C-values can be reduced to less than 0.55 after increasing the green areas and constructing detention facilities. Reduction in peak discharge (22% to 63% and a delay in peak discharge by up to 30 min were also observed. Hence, it is recommended to consider the relationship between slope and land use while determining runoff coefficients; and to incorporate ABC Waters design features in urban design to reduce the peak flow and runoff coefficient (C.
ENTREPRENEURIAL ACTIVITY IN ROMANIA – A TIME SERIES CLUSTERING ANALYSIS AT THE NUTS3 LEVEL

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Sipos-Gug Sebastian

2013-07-01

Full Text Available Entrepreneurship is an active field of research, having known a major increase in interest and publication levels in the last years (Landström et al., 2012. Within this field recently there has been an increasing interest in understanding why some regions seem to have a significantly higher entrepreneurship activity compared to others. In line with this research field, we would like to investigate the differences in entrepreneurial activity among the Romanian counties (NUTS 3 regions. While the classical research paradigm in this field is to conduct a temporally stationary analysis, we choose to use a time series clustering analysis to better understanding the dynamics of entrepreneurial activity between counties. Our analysis showed that if we use the total number of new privately owned companies that are founded each year in the last decade (2002-2012 we can distinguish between 5 clusters, one with high total entrepreneurial activity (18 counties, one with above average activity (8 counties, two clusters with average and slightly below average activity (total of 18 counties and one cluster with low and declining activity (2 counties. If we are interested in the entrepreneurial activity rate, that is the number of new privately owned companies founded each year adjusted by the population of the respective county, we obtain 4 clusters, one with a very high entrepreneurial rate (1 county, one with average rate (10 counties, and two clusters with below average entrepreneurial rate (total of 31 counties. In conclusion, our research shows that Romania is far from being a homogeneous geographical area in respect to entrepreneurial activity. Depending on what we are interested in, it can be divided in 5 or 4 clusters of counties, which behave differently as a function of time. Further research should be focused on explaining these regional differences, on studying the high performance clusters and trying to improve the low performing ones.
The Impact of Magnesium Oxide on the Hydratation and Features of Mechanicaly Activated Phosphogypsum

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Andrejus Jefimovas

2011-04-01

Full Text Available Extractive hemihydrate phosphogypsum (E-PG is the most popular mineral waste in Lithuania. The dumps of that are rapidly growing and the question of possible use still remains open. Phosphogypsum is obtained during the process of extracting phosphoric acid from apatite using sulphuric acid. Due to low activity and contamination with acidic mineral admixtures (phosphorus and fluorine compounds, this technogenic product cannot be used for producing construction materials. Instead of present energy consuming processes used for neutralisation, another method – mechanical activation neutralizing acid admixtures with cement and opoka mix is offered. Whereas cement and opoka are grey, the items made of phosphogypsum (neutralised using these admixtures are dark. Research was made trying to find out the possibility of gaining the white binder from phosphogypsum. In order to achieve that magnesium oxide was chosen to neutralise phosphogypsum and its impact on E-PG, hydratation and features were studied.Article in Lithuanian
FLT3 mutation incidence and timing of origin in a population case series of pediatric leukemia

Directory of Open Access Journals (Sweden)

Chang Jeffrey

2010-09-01

Full Text Available Abstract Background Mutations in FLT3 result in activated tyrosine kinase activity, cell growth stimulation, and a poor prognosis among various subtypes of leukemia. The causes and timing of the mutations are not currently known. We evaluated the prevalence and timing of origin of FLT3 mutations in a population series of childhood leukemia patients from Northern California. Methods We screened and sequenced FLT3 mutations (point mutations and internal tandem duplications, ITDs among 517 childhood leukemia patients, and assessed whether these mutations occurred before or after birth using sensitive "backtracking" methods. Results We determined a mutation prevalence of 9 of 73 acute myeloid leukemias (AMLs, 12% and 9 of 441 acute lymphocytic leukemias (ALLs, 2%. Among AMLs, FLT3 mutations were more common in older patients, and among ALLs, FLT3 mutations were more common in patients with high hyperdiploidy (3.7% than those without this cytogenetic feature (1.4%. Five FLT3 ITDs, one deletion mutation, and 3 point mutations were assessed for their presence in neonatal Guthrie spots using sensitive real-time PCR techniques, and no patients were found to harbor FLT3 mutations at birth. Conclusions FLT3 mutations were not common in our population-based patient series in California, and patients who harbor FLT3 mutations most likely acquire them after they are born.
Description of the Main Features of the Series Production of the LHC Main Dipole Magnets

CERN Document Server

Savary, F; Chevret, P; de Rijk, G; Fessia, P; Liénard, P; Miles, J; Modena, M; Rossi, L; Tommasini, D; Vlogaert, J; Bresson, D; Grunblatt, G; Decoene, JF; Bressani, F; Drago, G; Gagliardi, P; Eysselein, F; Gärtner, W; Lublow, P

2008-01-01

The series production of the LHC main dipole magnets was completed in November 2006. This paper presents the organization implemented at CERN and the milestones fixed to fullfil the technical requirements and to respect the master schedule of the machine installation. The CERN organization for the production follow-up, the quality assurance and the magnet testing, as well as the organization of the three main contractors will be described. A description of the design work and procurement of most of the specific heavy tooling and key components will be given with emphasis on the advantages and drawbacks.
Machine News and Volatility: The Dow Jones Industrial Average and the TRNA Sentiment Series

NARCIS (Netherlands)

D.E. Allen (David); A.K. Singh (Abhay)

2014-01-01

markdownabstract__Abstract__ This paper features an analysis of the relationship between the volatility of the Dow Jones Industrial Average (DJIA) Index and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA) provided by SIRCA (The Securities Industry
Synthesis, biological evaluation and structure-activity correlation study of a series of imidazol-based compounds as Candida albicans inhibitors.

Science.gov (United States)

Moraca, Francesca; De Vita, Daniela; Pandolfi, Fabiana; Di Santo, Roberto; Costi, Roberta; Cirilli, Roberto; D'Auria, Felicia Diodata; Panella, Simona; Palamara, Anna Teresa; Simonetti, Giovanna; Botta, Maurizio; Scipione, Luigi

2014-08-18

A new series of 2-(1H-imidazol-1-yl)-1-phenylethanol derivatives was synthesized. The antifungal activity was evaluated in vitro against different fungal species. The biological results show that the most active compounds possess an antifungal activity comparable or higher than Fluconazole against Candida albicans, non-albicans Candida species, Cryptococcus neoformans and dermathophytes. Because of their racemic nature, the most active compounds 5f and 6c were tested as pure enantiomers. For 6c the (R)-enantiomer resulted more active than the (S)-one, otherwise for 5f the (S)-enantiomer resulted the most active. To rationalize the experimental data, a ligand-based computational study was carried out; the results of the modelling study show that (S)-5f and (R)-6c perfectly align to the ligand-based model, showing the same relative configuration. Preliminary studies on the human lung adenocarcinoma epithelial cells (A549) have shown that 6c, 5e and 5f possess a low cytotoxicity. Copyright © 2014 Elsevier Masson SAS. All rights reserved.
Multistage feature extraction for accurate face alignment

NARCIS (Netherlands)

Zuo, F.; With, de P.H.N.

2004-01-01

We propose a novel multistage facial feature extraction approach using a combination of 'global' and 'local' techniques. At the first stage, we use template matching, based on an Edge-Orientation-Map for fast feature position estimation. Using this result, a statistical framework applying the Active
Feature integration and spatial attention: common processes for endogenous and exogenous orienting.

Science.gov (United States)

Henderickx, David; Maetens, Kathleen; Soetens, Eric

2010-05-01

Briand (J Exp Psychol Hum Percept Perform 24:1243-1256, 1998) and Briand and Klein (J Exp Psychol Hum Percept Perform 13:228-241, 1987) demonstrated that spatial cueing effects are larger for detecting conjunction of features than for detecting simple features when spatial attention is oriented exogenously, and not when attention is oriented endogenously. Their results were interpreted as if only exogenous attention affects the posterior spatial attention system that performs the feature binding function attributed to spatial attention by Treisman's feature integration theory (FIT; 1980). In a series of 6 experiments, we attempted to replicate Briand's findings. Manipulations of distractor string size and symmetry of stimulus presentation left and right from fixation were implemented in Posner's cueing paradigm. The data indicate that both exogenous and endogenous cueing address the same attentional mechanism needed for feature binding. The results also limit the generalisability of Briand's proposal concerning the role of exogenous attention in feature integration. Furthermore, the importance to control the effect of unintended attentional capture in a cueing task is demonstrated.
Could television series be the best way to familiarize people with nuclear activities?

International Nuclear Information System (INIS)

Michel, A.

2010-01-01

If there is a greater acceptance of nuclear plants, nevertheless their development does still create some anxiety. Against that, the nuclear industry can not reassure only with rational technical reports. Doing so, it runs the risk of not being heard, covered by the continuous presence of dramatic fiction stories and imaginative anti-nuclear demonstrations. Based on years of observation, I will try to demonstrate that the nuclear industry needs to become more emotive and make use of the medium of fiction to get its message across to the public Nuclear energy is mainly presented dangerously in fiction such as James Bond films or 'The China Syndrome'. These films, and novels written in the same way, have certainly more influence on the images that people memorize than all the documents we can distribute. Thus they increase anxieties about nuclear and even the smallest incident makes the media headlines. I have described this situation in a number of papers and conferences previously. Now I consider that if we want to improve this situation, real nuclear activities must become more familiar. But how can we reach the lay-persons who do not really want to be informed, have no time to do so or lack the education to understand the facts? We must penetrate their homes, where they sit every evening looking at their favorite TV series. TV series have more influence than films because little by little, week after week, the situations, actors and atmosphere become familiar.Like other organisations (police, justice, hospitals, firemen,..), we should support producers and scriptwriters who are really interested to work on our subjects.. The present question is: shall we provide the 'seed money' for the production? (authors)
Feature extraction with deep neural networks by a generalized discriminant analysis.

Science.gov (United States)

Stuhlsatz, André; Lippel, Jens; Zielke, Thomas

2012-04-01

We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used.
Detecting dynamical changes in time series by using the Jensen Shannon divergence

Science.gov (United States)

Mateos, D. M.; Riveaud, L. E.; Lamberti, P. W.

2017-08-01

Most of the time series in nature are a mixture of signals with deterministic and random dynamics. Thus the distinction between these two characteristics becomes important. Distinguishing between chaotic and aleatory signals is difficult because they have a common wide band power spectrum, a delta like autocorrelation function, and share other features as well. In general, signals are presented as continuous records and require to be discretized for being analyzed. In this work, we introduce different schemes for discretizing and for detecting dynamical changes in time series. One of the main motivations is to detect transitions between the chaotic and random regime. The tools here used here originate from the Information Theory. The schemes proposed are applied to simulated and real life signals, showing in all cases a high proficiency for detecting changes in the dynamics of the associated time series.
Terrain feature recognition for synthetic aperture radar (SAR) imagery employing spatial attributes of targets

Science.gov (United States)

Iisaka, Joji; Sakurai-Amano, Takako

1994-08-01

This paper describes an integrated approach to terrain feature detection and several methods to estimate spatial information from SAR (synthetic aperture radar) imagery. Spatial information of image features as well as spatial association are key elements in terrain feature detection. After applying a small feature preserving despeckling operation, spatial information such as edginess, texture (smoothness), region-likeliness and line-likeness of objects, target sizes, and target shapes were estimated. Then a trapezoid shape fuzzy membership function was assigned to each spatial feature attribute. Fuzzy classification logic was employed to detect terrain features. Terrain features such as urban areas, mountain ridges, lakes and other water bodies as well as vegetated areas were successfully identified from a sub-image of a JERS-1 SAR image. In the course of shape analysis, a quantitative method was developed to classify spatial patterns by expanding a spatial pattern through the use of a series of pattern primitives.
Account Deletion Prediction on RuNet: A Case Study of Suspicious Twitter Accounts Active During the Russian-Ukrainian Crisis

Energy Technology Data Exchange (ETDEWEB)

Volkova, Svitlana; Bell, Eric B.

2016-06-17

Social networks are dynamically changing over time e.g., some accounts are being created and some are being deleted or become private. This ephemerality at both an account level and content level results from a combination of privacy concerns, spam, and deceptive behaviors. In this study we analyze a large dataset of 180,340 accounts active during the Russian-Ukrainian crisis to discover a series of predictive features for the removal or shutdown of a suspicious account. We find that unlike previously reported profile and net- work features, lexical features form the basis for highly accurate prediction of the deletion of an account.
Estimating changes in riparian and channel features along the Trinity River downstream of Lewiston Dam, California, 1980 to 2011

Science.gov (United States)

Curtis, Jennifer A.

2015-01-01

Dam construction, flow diversion, and legacy landuse effects reduced the transport capacity, sediment supply, channel complexity and floodplain-connectivity along the Trinity River, CA below Lewiston Dam. This study documents the geomorphic evolution of the Trinity River Restoration Program’s intensively managed 65-km long restoration reach from 1980 to 2011. The nature and extent of riparian and channel changes were assessed using a series of geomorphic feature maps constructed from ortho-rectified photography acquired at low flow conditions in 1980, 1997, 2001, 2006, 2009, and 2011. Since 1980 there has been a general conversion of riparian to channel features and expansion of the active channel area. The primary mechanism for expansion of the active channel was bank erosion from 1980 to 1997 and channel widening was well distributed longitudinally throughout the study reach. Subsequent net bar accretion from 1997 to 2001, followed by slightly higher net bar scour from 2001 to 2006, occurred primarily in the central and lower reaches of the study area. In comparison, post-2006 bank and bar changes were spatially-limited to reaches with sufficient local transport capacity or sediment supply supported by gravel augmentation, mechanical channel rehabilitation, and tributary contributions to flow and sediment supply. A series of tributary floods in 1997, 1998 and 2006 were the primary factors leading to documented increases in channel complexity and floodplain connectivity. During the post-2006 period managed flow releases, in the absence of large magnitude tributary flooding, combined with gravel augmentation and mechanical restoration caused localized increases in sediment supply and transport capacity leading to smaller but measurable increases in channel complexity and floodplain connectivity primarily in the upper river below Lewiston Dam.
Feature-Based Statistical Analysis of Combustion Simulation Data

Energy Technology Data Exchange (ETDEWEB)

Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T

2011-11-18

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion
Chest x-ray in Q-fever pneumonia: a series of 71 cases

International Nuclear Information System (INIS)

Encinas, B.; Cerezal, L.F.; Fidalgo, I.; Bustamente, M.; Lopez Calderon, M.

1995-01-01

Chest X ray features of 71 cases of Q-fever serologically confirmed and with clinical manifestations of acute respiratory disease were retrospectively assessed in order to evaluate the radiographic features. In 68 cases (96%) The X-ray films were abnormal. Segmental consolidation, sometimes multiple and bilateral were tue most usual findings. Nodular opacities were found in 6 cases (9%) and can mimic a tumor. Cavitacion , a very unusual findings, was found in two nodular consolidations(two patients). Laminar atelectasis was less common than proviously reported. As in other series, total resolution or with minimal scars occurs within 3 months 15 refs
Magnetic Field Emission Comparison for Series-Parallel and Series-Series Wireless Power Transfer to Vehicles – PART 2/2

DEFF Research Database (Denmark)

Batra, Tushar; Schaltz, Erik

2014-01-01

Series-series and series-parallel topologies are the most favored topologies for design of wireless power transfer system for vehicle applications. The series-series topology has the advantage of reflecting only the resistive part on the primary side. On the other hand, the current source output...... characteristics of the series-parallel topology are more suited for the battery of the vehicle. This paper compares the two topologies in terms of magnetic emissions to the surroundings for the same input power, primary current, quality factor and inductors. Theoretical and simulation results show that the series...
Time-series prediction of shellfish farm closure: A comparison of alternatives

Directory of Open Access Journals (Sweden)

Ashfaqur Rahman

2014-08-01

Full Text Available Shellfish farms are closed for harvest when microbial pollutants are present. Such pollutants are typically present in rainfall runoff from various land uses in catchments. Experts currently use a number of observable parameters (river flow, rainfall, salinity as proxies to determine when to close farms. We have proposed using the short term historical rainfall data as a time-series prediction problem where we aim to predict the closure of shellfish farms based only on rainfall. Time-series event prediction consists of two steps: (i feature extraction, and (ii prediction. A number of data mining challenges exist for these scenarios: (i which feature extraction method best captures the rainfall pattern over successive days that leads to opening or closure of the farms?, (ii The farm closure events occur infrequently and this leads to a class imbalance problem; the question is what is the best way to deal with this problem? In this paper we have analysed and compared different combinations of balancing methods (under-sampling and over-sampling, feature extraction methods (cluster profile, curve fitting, Fourier Transform, Piecewise Aggregate Approximation, and Wavelet Transform and learning algorithms (neural network, support vector machine, k-nearest neighbour, decision tree, and Bayesian Network to predict closure events accurately considering the above data mining challenges. We have identified the best combination of techniques to accurately predict shellfish farm closure from rainfall, given the above data mining challenges.

Discrimination of single features and conjunctions by children.

Science.gov (United States)

Taylor, M J; Chevalier, H; Lobaugh, N J

2003-12-01

Stimuli that are discriminated by a conjunction of features can show more rapid early processing in adults. To determine how this facilitation effect develops, the processing of visual features and their conjunction was examined in 7-12-year-old children. The children completed a series of tasks in which they made a target-non-target judgement as a function of shape only, colour only or shape and colour features, while event-related potentials were recorded. To assess early stages of feature processing the posteriorly distributed P1 and N1 were analysed. Attentional effects were seen for both components. P1 had a shorter latency and P1 and N1 had larger amplitudes to targets than non-targets. Task effects were driven by the conjunction task. P1 amplitude was largest, while N1 amplitude was smallest for the conjunction targets. In contrast to larger left-sided N1 in adults, N1 had a symmetrical distribution in the children. N1 latency was shortest for the conjunction targets in the 9-10-year olds and 11-12-year olds, demonstrating facilitation in children, but which continued to develop over the pre-teen years. These data underline the sensitivity of early stages of processing to both top-down modulations and the parallel binding of non-spatial features in young children. Furthermore, facilitation effects, increased speed of processing when features need to be conjoined, mature in mid-childhood, arguing against a hierarchical model of visual processing, and supporting a rapid, integrated facilitative model.
Multiple Time-Instances Features of Degraded Speech for Single Ended Quality Measurement

Directory of Open Access Journals (Sweden)

Rajesh Kumar Dubey

2017-01-01

Full Text Available The use of single time-instance features, where entire speech utterance is used for feature computation, is not accurate and adequate in capturing the time localized information of short-time transient distortions and their distinction from plosive sounds of speech, particularly degraded by impulsive noise. Hence, the importance of estimating features at multiple time-instances is sought. In this, only active speech segments of degraded speech are used for features computation at multiple time-instances on per frame basis. Here, active speech means both voiced and unvoiced frames except silence. The features of different combinations of multiple contiguous active speech segments are computed and called multiple time-instances features. The joint GMM training has been done using these features along with the subjective MOS of the corresponding speech utterance to obtain the parameters of GMM. These parameters of GMM and multiple time-instances features of test speech are used to compute the objective MOS values of different combinations of multiple contiguous active speech segments. The overall objective MOS of the test speech utterance is obtained by assigning equal weight to the objective MOS values of the different combinations of multiple contiguous active speech segments. This algorithm outperforms the Recommendation ITU-T P.563 and recently published algorithms.
Neural network modelling of antifungal activity of a series of oxazole derivatives based on in silico pharmacokinetic parameters

Directory of Open Access Journals (Sweden)

Kovačević Strahinja Z.

2013-01-01

Full Text Available In the present paper, the antifungal activity of a series of benzoxazole and oxazolo[ 4,5-b]pyridine derivatives was evaluated against Candida albicans by using quantitative structure-activity relationships chemometric methodology with artificial neural network (ANN regression approach. In vitro antifungal activity of the tested compounds was presented by minimum inhibitory concentration expressed as log(1/cMIC. In silico pharmacokinetic parameters related to absorption, distribution, metabolism and excretion (ADME were calculated for all studied compounds by using PreADMET software. A feedforward back-propagation ANN with gradient descent learning algorithm was applied for modelling of the relationship between ADME descriptors (blood-brain barrier penetration, plasma protein binding, Madin-Darby cell permeability and Caco-2 cell permeability and experimental log(1/cMIC values. A 4-6-1 ANN was developed with the optimum momentum and learning rates of 0.3 and 0.05, respectively. An excellent correlation between experimental antifungal activity and values predicted by the ANN was obtained with a correlation coefficient of 0.9536. [Projekat Ministarstva nauke Republike Srbije, br. 172012 i br. 172014
Volatility behavior of visibility graph EMD financial time series from Ising interacting system

Science.gov (United States)

Zhang, Bo; Wang, Jun; Fang, Wen

2015-08-01

A financial market dynamics model is developed and investigated by stochastic Ising system, where the Ising model is the most popular ferromagnetic model in statistical physics systems. Applying two graph based analysis and multiscale entropy method, we investigate and compare the statistical volatility behavior of return time series and the corresponding IMF series derived from the empirical mode decomposition (EMD) method. And the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, we find that the degree distribution of visibility graph for the simulation series has the power law tails, and the assortative network exhibits the mixing pattern property. All these features are in agreement with the real market data, the research confirms that the financial model established by the Ising system is reasonable.
Complexity testing techniques for time series data: A comprehensive literature review

International Nuclear Information System (INIS)

Tang, Ling; Lv, Huiling; Yang, Fengmei; Yu, Lean

2015-01-01

Highlights: • A literature review of complexity testing techniques for time series data is provided. • Complexity measurements can generally fall into fractality, methods derived from nonlinear dynamics and entropy. • Different types investigate time series data from different perspectives. • Measures, applications and future studies for each type are presented. - Abstract: Complexity may be one of the most important measurements for analysing time series data; it covers or is at least closely related to different data characteristics within nonlinear system theory. This paper provides a comprehensive literature review examining the complexity testing techniques for time series data. According to different features, the complexity measurements for time series data can be divided into three primary groups, i.e., fractality (mono- or multi-fractality) for self-similarity (or system memorability or long-term persistence), methods derived from nonlinear dynamics (via attractor invariants or diagram descriptions) for attractor properties in phase-space, and entropy (structural or dynamical entropy) for the disorder state of a nonlinear system. These estimations analyse time series dynamics from different perspectives but are closely related to or even dependent on each other at the same time. In particular, a weaker self-similarity, a more complex structure of attractor, and a higher-level disorder state of a system consistently indicate that the observed time series data are at a higher level of complexity. Accordingly, this paper presents a historical tour of the important measures and works for each group, as well as ground-breaking and recent applications and future research directions.
Toward automatic time-series forecasting using neural networks.

Science.gov (United States)

Yan, Weizhong

2012-07-01

Over the past few decades, application of artificial neural networks (ANN) to time-series forecasting (TSF) has been growing rapidly due to several unique features of ANN models. However, to date, a consistent ANN performance over different studies has not been achieved. Many factors contribute to the inconsistency in the performance of neural network models. One such factor is that ANN modeling involves determining a large number of design parameters, and the current design practice is essentially heuristic and ad hoc, this does not exploit the full potential of neural networks. Systematic ANN modeling processes and strategies for TSF are, therefore, greatly needed. Motivated by this need, this paper attempts to develop an automatic ANN modeling scheme. It is based on the generalized regression neural network (GRNN), a special type of neural network. By taking advantage of several GRNN properties (i.e., a single design parameter and fast learning) and by incorporating several design strategies (e.g., fusing multiple GRNNs), we have been able to make the proposed modeling scheme to be effective for modeling large-scale business time series. The initial model was entered into the NN3 time-series competition. It was awarded the best prediction on the reduced dataset among approximately 60 different models submitted by scholars worldwide.
Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

OpenAIRE

Zeng, Yong; Liu, Dacheng; Lei, Zhou

2014-01-01

The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history si...
Application of eigen value expansion to feature extraction from MRI images

International Nuclear Information System (INIS)

Kinosada, Yasutomi; Takeda, Kan; Nakagawa, Tsuyoshi

1991-01-01

The eigen value expansion technique was utilized for feature extraction of magnetic resonance (MR) images. The eigen value expansion is an orthonormal transformation method which decomposes a set of images into some statistically uncorrelated images. The technique was applied to MR images obtained with various imaging parameters at the same anatomical site. It generated one mean image and another set of images called bases for the images. Each basis corresponds to a feature in the images. A basis is, therefore, utilized for the feature extraction from MR images and a weighted sum of bases is also used for the feature enhancement. Furthermore, any MR image with specific feature can be obtained from a linear combination of the mean image and all of the bases. Images of hemorrhaged brain with a spin echo sequence and a series of cinematic cerebro spinal fluid flow images with ECG gated gradient refocused echo sequence were employed to estimate the ability of the feature extraction and the contrast enhancement. Results showed us that proposed application of an eigen value expansion technique to the feature extraction of MR images is good enough to clinical use and superior to other feature extraction methods such as producing a calculated MR image with a given TR and TE or the matched-filter method in processing speed and reproducibility of results. (author)
Pairwise Constraint-Guided Sparse Learning for Feature Selection.

Science.gov (United States)

Liu, Mingxia; Zhang, Daoqiang

2016-01-01

Feature selection aims to identify the most informative features for a compact and accurate data representation. As typical supervised feature selection methods, Lasso and its variants using L1-norm-based regularization terms have received much attention in recent studies, most of which use class labels as supervised information. Besides class labels, there are other types of supervised information, e.g., pairwise constraints that specify whether a pair of data samples belong to the same class (must-link constraint) or different classes (cannot-link constraint). However, most of existing L1-norm-based sparse learning methods do not take advantage of the pairwise constraints that provide us weak and more general supervised information. For addressing that problem, we propose a pairwise constraint-guided sparse (CGS) learning method for feature selection, where the must-link and the cannot-link constraints are used as discriminative regularization terms that directly concentrate on the local discriminative structure of data. Furthermore, we develop two variants of CGS, including: 1) semi-supervised CGS that utilizes labeled data, pairwise constraints, and unlabeled data and 2) ensemble CGS that uses the ensemble of pairwise constraint sets. We conduct a series of experiments on a number of data sets from University of California-Irvine machine learning repository, a gene expression data set, two real-world neuroimaging-based classification tasks, and two large-scale attribute classification tasks. Experimental results demonstrate the efficacy of our proposed methods, compared with several established feature selection methods.
Basaltic lava flows covering active aeolian dunes in the Paraná Basin in southern Brazil: Features and emplacement aspects

Science.gov (United States)

Waichel, Breno L.; Scherer, Claiton M. S.; Frank, Heinrich T.

2008-03-01

Burial of active aeolian dunes by lava flows can preserve the morphology of the dunes and generate diverse features related to interaction between unconsolidated sediments and lavas. In the study area, located in southern Brazil, burial of aeolian deposits by Cretaceous basaltic lava flows completely preserved dunes, and generate sand-deformation features, sand diapirs and peperite-like breccia. The preserved dunes are crescentic and linear at the main contact with basalts, and smaller crescentic where interlayered with lavas. The various feature types formed on sediment surfaces by the advance of the flows reflect the emplacement style of the lavas which are compound pahoehoe type. Four feature types can be recognized: (a) type 1 features are related to the advance of sheet flows in dune-interdune areas with slopes > 5°, (b) type 2 is formed where the lava flows advance in lobes and climb the stoss slope of crescentic dunes (slopes 8-12°), (c) type 3 is generated by toes that descend the face of linear dunes (slopes 17-23°) and (d) type 4 occurs when lava lobes descend the stoss slope of crescentic dunes (slopes 10-15°). The direction of the flows, the disposition and morphology of the dunes and the ground slope are the main factors controlling formation of the features. The injection of unconsolidated sand in lava lobes forms diapirs and peperite-like breccias. Sand diapirs occur at the basal portion of lobes where the lava was more solidified. Peperite-like breccias occur in the inner portion where lava was more plastic, favoring the mingling of the components. The generation of both features is related to a mechanical process: the weight of the lava causes the injection of sand into the lava and the warming of the air in the pores of the sand facilitates this process. The lava-sediment interaction features presented here are consistent with previous reports of basalt lavas with unconsolidated arid sediments, and additional new sand-deformation features
Technical Manual: 2002 Series GED Tests

Science.gov (United States)

Ezzelle, Carol; Setzer, J. Carl

2009-01-01

This manual was written to provide technical information regarding the 2002 Series GED (General Educational Development) Tests. Throughout this manual, documentation is provided regarding the development of the GED Tests, data collection activities, as well as reliability and validity evidence. The purpose of this manual is to provide evidence…
Optimal Subset Selection of Time-Series MODIS Images and Sample Data Transfer with Random Forests for Supervised Classification Modelling.

Science.gov (United States)

Zhou, Fuqun; Zhang, Aining

2016-10-25

Nowadays, various time-series Earth Observation data with multiple bands are freely available, such as Moderate Resolution Imaging Spectroradiometer (MODIS) datasets including 8-day composites from NASA, and 10-day composites from the Canada Centre for Remote Sensing (CCRS). It is challenging to efficiently use these time-series MODIS datasets for long-term environmental monitoring due to their vast volume and information redundancy. This challenge will be greater when Sentinel 2-3 data become available. Another challenge that researchers face is the lack of in-situ data for supervised modelling, especially for time-series data analysis. In this study, we attempt to tackle the two important issues with a case study of land cover mapping using CCRS 10-day MODIS composites with the help of Random Forests' features: variable importance, outlier identification. The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring sample data available from one year to an adjacent year for supervised classification modelling. The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to that generated using the full dataset. The proposed simple but effective solution of sample transferring could make supervised modelling possible for applications lacking sample data.
Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review.

Science.gov (United States)

Malkin, Zinovy

2016-04-01

The Allan variance (AVAR) was introduced 50 years ago as a statistical tool for assessing the frequency standards deviations. For the past decades, AVAR has increasingly been used in geodesy and astrometry to assess the noise characteristics in geodetic and astrometric time series. A specific feature of astrometric and geodetic measurements, as compared with clock measurements, is that they are generally associated with uncertainties; thus, an appropriate weighting should be applied during data analysis. In addition, some physically connected scalar time series naturally form series of multidimensional vectors. For example, three station coordinates time series X, Y, and Z can be combined to analyze 3-D station position variations. The classical AVAR is not intended for processing unevenly weighted and/or multidimensional data. Therefore, AVAR modifications, namely weighted AVAR (WAVAR), multidimensional AVAR (MAVAR), and weighted multidimensional AVAR (WMAVAR), were introduced to overcome these deficiencies. In this paper, a brief review is given of the experience of using AVAR and its modifications in processing astrogeodetic time series.
A novel six-degrees-of-freedom series-parallel manipulator

Energy Technology Data Exchange (ETDEWEB)

Gallardo-Alvarado, J.; Rodriguez-Castro, R.; Aguilar-Najera, C. R.; Perez-Gonzalez, L. [Instituto Tecnologico de Celaya, Celaya (Mexico)

2012-06-15

This paper addresses the description and kinematic analyses of a new non-redundant series-parallel manipulator. The primary feature of the robot is to have a decoupled topology consisting of a lower parallel manipulator, for controlling the orientation of the coupler platform, assembled in series connection with a upper parallel manipulator, for controlling the position of the output platform, capable to provide arbitrary poses to the output platform with respect to the fixed platform. The forward displacement analysis is carried-out in semi-closed form solutions by resorting to simple closure equations. On the other hand; the velocity, acceleration and singularity analyses of the manipulator are approached by means of the theory of screws. Simple and compact expressions are derived here for solving the infinitesimal kinematics by taking advantage of the concept of reciprocal screws. Furthermore, the analysis of the Jacobians of the robot shows that the lower parallel manipulator is practically free of singularities. In order to illustrate the performance of the manipulator, a numerical example which consists of solving the inverse/forward kinematics of the series-parallel manipulator as well as its singular configurations is provided.
Learning-induced Dependence of Neuronal Activity in Primary Motor Cortex on Motor Task Condition.

Science.gov (United States)

Cai, X; Shimansky, Y; He, Jiping

2005-01-01

A brain-computer interface (BCI) system such as a cortically controlled robotic arm must have a capacity of adjusting its function to a specific environmental condition. We studied this capacity in non-human primates based on chronic multi-electrode recording from the primary motor cortex of a monkey during the animal's performance of a center-out 3D reaching task and adaptation to external force perturbations. The main condition-related feature of motor cortical activity observed before the onset of force perturbation was a phasic raise of activity immediately before the perturbation onset. This feature was observed during a series of perturbation trials, but were absent under no perturbations. After adaptation has been completed, it usually was taking the subject only one trial to recognize a change in the condition to switch the neuronal activity accordingly. These condition-dependent features of neuronal activity can be used by a BCI for recognizing a change in the environmental condition and making corresponding adjustments, which requires that the BCI-based control system possess such advanced properties of the neural motor control system as capacity to learn and adapt.
Linking the Negative Binomial and Logarithmic Series Distributions via their Associated Series

OpenAIRE

SADINLE, MAURICIO

2008-01-01

The negative binomial distribution is associated to the series obtained by taking derivatives of the logarithmic series. Conversely, the logarithmic series distribution is associated to the series found by integrating the series associated to the negative binomial distribution. The parameter of the number of failures of the negative binomial distribution is the number of derivatives needed to obtain the negative binomial series from the logarithmic series. The reasoning in this article could ...
Software Engineering Laboratory Series: Collected Software Engineering Papers. Volume 14

Science.gov (United States)

1996-01-01

The Software Engineering Laboratory (SEL) is an organization sponsored by NASA/GSFC and created to investigate the effectiveness of software engineering technologies when applied to the development of application software. The activities, findings, and recommendations of the SEL are recorded in the Software Engineering Laboratory Series, a continuing series of reports that includes this document.
Software Engineering Laboratory Series: Collected Software Engineering Papers. Volume 15

Science.gov (United States)

1997-01-01

The Software Engineering Laboratory (SEL) is an organization sponsored by NASA/GSFC and created to investigate the effectiveness of software engineering technologies when applied to the development of application software. The activities, findings, and recommendations of the SEL are recorded in the Software Engineering Laboratory Series, a continuing series of reports that includes this document.
Software Engineering Laboratory Series: Collected Software Engineering Papers. Volume 13

Science.gov (United States)

1995-01-01

The Software Engineering Laboratory (SEL) is an organization sponsored by NASA/GSFC and created to investigate the effectiveness of software engineering technologies when applied to the development of application software. The activities, findings, and recommendations of the SEL are recorded in the Software Engineering Laboratory Series, a continuing series of reports that includes this document.
Clustering-based Feature Learning on Variable Stars

Science.gov (United States)

Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos

2016-04-01

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.

CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS

International Nuclear Information System (INIS)

Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos

2016-01-01

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline
CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS

Energy Technology Data Exchange (ETDEWEB)

Mackenzie, Cristóbal; Pichara, Karim [Computer Science Department, Pontificia Universidad Católica de Chile, Santiago (Chile); Protopapas, Pavlos [Institute for Applied Computational Science, Harvard University, Cambridge, MA (United States)

2016-04-01

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.
Alkaline and Organosolv Lignins from Furfural Residue: Structural Features and Antioxidant Activity

Directory of Open Access Journals (Sweden)

Xue-Fei Cao

2013-12-01

Full Text Available Furfural residue (FR, composed mainly of cellulose and lignin, is an industrial waste produced during furfural manufacture. In this study, dioxane, alkali, ethanol, alkali-ethanol, and alkaline hydrogen peroxide (AHP were used to extract lignins from FR. The structural features of these lignins obtained were characterized by sugar analysis, GPC, UV, FT-IR, and HSQC spectra. As compared to dioxane lignin (DL, other lignins showed lower molecular weights (Mw owing to the partial cleavage of the linkages between lignin units. Results from HSQC spectra revealed that β-O-4' and β-5' were still the major linkages of the FR lignin. Moreover, p-coumaric and ferulic acids were released and co-precipitated in the lignin preparations extracted with alkali and AHP, whereas part of the esters in DL were preserved during the dioxane extraction. Antioxidant activity investigation indicated that the antioxidant property of the alkali and alkali-ethanol lignins was higher than that of the commercial antioxidant, butylated hydroxytoluene.
Prewhitening of hydroclimatic time series? Implications for inferred change and variability across time scales

Science.gov (United States)

Razavi, Saman; Vogel, Richard

2018-02-01

Prewhitening, the process of eliminating or reducing short-term stochastic persistence to enable detection of deterministic change, has been extensively applied to time series analysis of a range of geophysical variables. Despite the controversy around its utility, methodologies for prewhitening time series continue to be a critical feature of a variety of analyses including: trend detection of hydroclimatic variables and reconstruction of climate and/or hydrology through proxy records such as tree rings. With a focus on the latter, this paper presents a generalized approach to exploring the impact of a wide range of stochastic structures of short- and long-term persistence on the variability of hydroclimatic time series. Through this approach, we examine the impact of prewhitening on the inferred variability of time series across time scales. We document how a focus on prewhitened, residual time series can be misleading, as it can drastically distort (or remove) the structure of variability across time scales. Through examples with actual data, we show how such loss of information in prewhitened time series of tree rings (so-called "residual chronologies") can lead to the underestimation of extreme conditions in climate and hydrology, particularly droughts, reconstructed for centuries preceding the historical period.
Magnetic Field Emission Comparison for Series-Parallel and Series-Series Wireless Power Transfer to Vehicles – PART 1/2

DEFF Research Database (Denmark)

Batra, Tushar; Schaltz, Erik

2014-01-01

Resonant circuits of wireless power transfer system can be designed in four possible ways by placing the primary and secondary capacitor in a series or parallel order with respect to the corresponding inductor. The two topologies series-parallel and series-series under investigation have been...... already compared in terms of their output behavior (current or voltage source) and reflection of the secondary impedance on the primary side. In this paper it is shown that for the same power rating series-parallel topology emits lesser magnetic fields to the surroundings than its series...
Features, Treatment, and Outcomes of Macrophage Activation Syndrome in Childhood-Onset Systemic Lupus Erythematosus.

Science.gov (United States)

Borgia, R Ezequiel; Gerstein, Maya; Levy, Deborah M; Silverman, Earl D; Hiraki, Linda T

2018-04-01

To describe the features and treatment of macrophage activation syndrome (MAS) in a single-center cohort of patients with childhood-onset systemic lupus erythematosus (SLE), and to compare childhood-onset SLE manifestations and outcomes between those with and those without MAS. We included all patients with childhood-onset SLE followed up at The Hospital for Sick Children from 2002 to 2012, and identified those also diagnosed as having MAS. Demographic, clinical, and laboratory features of MAS and SLE, medication use, hospital and pediatric intensive care unit (PICU) admissions, as well as damage indices and mortality data were extracted from the Lupus database. Student's t-tests and Fisher's exact tests were used to compare continuous and categorical variables, respectively. We calculated incidence rate ratios of hospital and PICU admissions comparing patients with and those without MAS, using Poisson models. Kaplan-Meier survival analysis was used to examine the time to disease damage accrual. Of the 403 patients with childhood-onset SLE, 38 (9%) had MAS. The majority (68%) had concomitant MAS and SLE diagnoses. Fever was the most common MAS clinical feature. The frequency of renal and central nervous system disease, hospital admissions, the average daily dose of steroids, and time to disease damage were similar between those with and those without MAS. We observed a higher mortality rate among those with MAS (5%) than those without MAS (0.2%) (P = 0.02). MAS was most likely to develop concomitantly with childhood-onset SLE diagnosis. The majority of the MAS patients were successfully treated with corticosteroids with no MAS relapses. Although the numbers were small, there was a higher risk of death associated with MAS compared to SLE without MAS. © 2018, American College of Rheumatology.
Classroom Management. TESOL Classroom Practice Series

Science.gov (United States)

Farrell, Thomas S. C., Ed.

2008-01-01

This series captures the dynamics of the contemporary ESOL classroom. It showcases state-of-the-art curricula, materials, tasks, and activities reflecting emerging trends in language education and seeks to build localized language teaching and learning theories based on teachers' and students' unique experiences in and beyond the classroom. Each…
Mitochondrial pyruvate carrier function is negatively linked to Warburg phenotype in vitro and malignant features in esophageal squamous cell carcinomas

Science.gov (United States)

Li, Yaqing; Li, Xiaoran; Kan, Quancheng; Zhang, Mingzhi; Li, Xiaoli; Xu, Ruiping; Wang, Junsheng; Yu, Dandan; Goscinski, Mariusz Adam; Wen, Jian-Guo; Nesland, Jahn M.; Suo, Zhenhe

2017-01-01

Aerobic glycolysis is one of the emerging hallmarks of cancer cells. In this study, we investigated the relationship between blocking mitochondrial pyruvate carrier (MPC) with MPC blocker UK5099 and the metabolic alteration as well as aggressive features of esophageal squamous carcinoma. It was found that blocking pyruvate transportation into mitochondria attenuated mitochondrial oxidative phosphorylation (OXPHOS) and triggered aerobic glycolysis, a feature of Warburg effect. In addition, the HIF-1α expression and ROS production were also activated upon UK5099 application. It was further revealed that the UK5099-treated cells became significantly more resistant to chemotherapy and radiotherapy, and the UK5099-treated tumor cells also exhibited stronger invasive capacity compared to the parental cells. In contrast to esophageal squamous epithelium cells, decreased MPC protein expression was observed in a series of 157 human squamous cell carcinomas, and low/negative MPC1 expression predicted an unfavorable clinical outcome. All these results together revealed the potential connection of altered MPC expression/activity with the Warburg metabolic reprogramming and tumor aggressiveness in cell lines and clinical samples. Collectively, our findings highlighted a therapeutic strategy targeting Warburg reprogramming of human esophageal squamous cell carcinomas. PMID:27911865
Summation of series

CERN Document Server

Jolley, LB W

2004-01-01

Over 1,100 common series, all grouped for easy reference. Arranged by category, these series include arithmetical and geometrical progressions, powers and products of natural numbers, figurate and polygonal numbers, inverse natural numbers, exponential and logarithmic series, binomials, simple inverse products, factorials, trigonometrical and hyperbolic expansions, and additional series. 1961 edition.
2D QSAR studies of the inhibitory activity of a series of substituted purine derivatives against c-Src tyrosine kinase

OpenAIRE

Mukesh C. Sharma

2016-01-01

A series of 34 substituted purine analogues derivatives were subjected to quantitative structure-activity relationship analyses as inhibitors of c-Src tyrosine kinase. Partial least squares regression was applied to derive QSAR models, which were further validated for statistical significance by internal and external validation. The best QSAR model developed had a good predictive correlation coefficient (r2) of 0.8319, a significant cross-validated correlation coefficient (q2) of 0.7550, and ...
Evaluating public awareness of new currency design features

Science.gov (United States)

DiNunzio, Lisa; Church, Sara E.

2002-04-01

One of the goals of the 1996 series design was to integrate highly recognizable features that enable the general public to more easily distinguish counterfeit from genuine notes, thereby reducing the chance of counterfeit notes being passed. The purpose of this study is to evaluate how knowledgeable the public is concerning the new currency, to identify the channels through which the public learns about new currency design, and to assess the usefulness of the new currency's authentication features. Also, the study will serve as a baseline measurement for future design studies and in comparative analysis with other countries. The results of the qualitative research will be described in the following sections of this paper. The quantitative research is scheduled to begin in February 2002, at the same time as the Netherlands' opinion poll of the Euro and NLG-notes in an effort to compare results.
Analysis of time domain active sensing data from CX-100 wind turbine blade fatigue tests for damage assessment

Energy Technology Data Exchange (ETDEWEB)

Choi, Mi Jin [Dept. of Aerospace Engineering and LANL-CBNU Engineering Institute, Chunbuk National University, Jeonju (Korea, Republic of); Jung, Hwee Kwon; Park, Gyu Hae [School of Mechanical Engineering, Chonnam National University, Gwangju (Korea, Republic of); Taylor, Stuart G.; Farinholt, Kevin M. [The Engineering Institute, Los Alamos National Laboratory, Los Alamos (United States)

2016-04-15

This paper presents the results obtained using time-series-based methods for structural damage assessment. The methods are applied to a wind turbine blade structure subjected to fatigue loads. A 9 m CX-100 (carbon experimental 100 kW) blade is harmonically excited at its first natural frequency to introduce a failure mode. Consequently, a through-thickness fatigue crack is visually identified at 8.5 million cycles. The time domain data from the piezoelectric active-sensing techniques are measured during the fatigue loadings and used to detect incipient damage. The damage-sensitive features, such as the first four moments and a normality indicator, are extracted from the time domain data. Time series autoregressive models with exogenous inputs are also implemented. These features could efficiently detect a fatigue crack and are less sensitive to operational variations than the other methods.
Scapular bone destruction: A case report of skeletal tuberculosis with a series of dynamic radiologic features

Directory of Open Access Journals (Sweden)

Lan Lan

2015-09-01

Full Text Available Tuberculosis (TB is an extremely common opportunistic infection in human immunodeficiency virus (HIV-positive patients. Pulmonary TB is the most common manifestation while skeletal TB, especially with an involvement of flat bone like scapula, is quite rare. We report the first case scapular TB in an advanced AIDS individual who was initially considered as lymphoma because of the faulty interpretation of the positivity of PET/CT scan. In this article, we present a series of dynamic radiologic data and emphasize the differential diagnostic of skeletal TB.
Iranian Junior High school English Book Series (Right Path to English Weighted against Material Evaluation Checklists

Directory of Open Access Journals (Sweden)

Farhad Golpour

2012-11-01

Full Text Available Choosing a course textbook is an overwhelming task for both teachers and administrators. The aim of this study was to evaluate Iranian junior high school textbook series base on validated criteria. For this purpose a careful analyzing textbook evaluation checklists suggested by Sheldon (1984 skierso (1991 and Tucker (1992 was picked out. Among proposed criteria, eighteen critical features were selected to analyze Iranian junior high school series written by Birjandi in (1991. The Criteria were applied to the series analytically by researcher to examine the materials. The criteria in a form of questionnaire given to 15 experienced teachers who were teaching mentioned series for more than ten years. The gathered data revealed that it lacks appropriate layout and physical characteristics, materials have not be recycled, not all skills have been considered equally, emphasis is on grammatical points which practiced through speaking and listening. Moreover; recordings are artificial, no attention is paid to students needs and topics are out of date and boring .Also audio-visual materials, teachers’ guide and communicative tasks seems to be forgotten by writer. Therefore; all eighteen features except vocabulary lists, availability of glossary and lots of grammatical points have not been considered a lot. That is, students' interests have been ignored totally and little communicative issues have been regarded in these series. In fact, at end of this determined time students would be proficient at structural points with no efficiency at communication. These findings can be helpful for curriculum designers, textbook writers to design some valuable textbooks that are useful for teachers to teach language communicatively.
Active and Passive Remote Sensing Data Time Series for Flood Detection and Surface Water Mapping

Science.gov (United States)

Bioresita, Filsa; Puissant, Anne; Stumpf, André; Malet, Jean-Philippe

2017-04-01

As a consequence of environmental changes surface waters are undergoing changes in time and space. A better knowledge of the spatial and temporal distribution of surface waters resources becomes essential to support sustainable policies and development activities. Especially because surface waters, are not only a vital sweet water resource, but can also pose hazards to human settlements and infrastructures through flooding. Floods are a highly frequent disaster in the world and can caused huge material losses. Detecting and mapping their spatial distribution is fundamental to ascertain damages and for relief efforts. Spaceborne Synthetic Aperture Radar (SAR) is an effective way to monitor surface waters bodies over large areas since it provides excellent temporal coverage and, all-weather day-and-night imaging capabilities. However, emergent vegetation, trees, wind or flow turbulence can increase radar back-scatter returns and pose problems for the delineation of inundated areas. In such areas, passive remote sensing data can be used to identify vegetated areas and support the interpretation of SAR data. The availability of new Earth Observation products, for example Sentinel-1 (active) and Sentinel-2 (passive) imageries, with both high spatial and temporal resolution, have the potential to facilitate flood detection and monitoring of surface waters changes which are very dynamic in space and time. In this context, the research consists of two parts. In the first part, the objective is to propose generic and reproducible methodologies for the analysis of Sentinel-1 time series data for floods detection and surface waters mapping. The processing chain comprises a series of pre-processing steps and the statistical modeling of the pixel value distribution to produce probabilistic maps for the presence of surface waters. Images pre-processing for all Sentinel-1 images comprise the reduction SAR effect like orbit errors, speckle noise, and geometric effects. A modified
Tensor-based Multi-view Feature Selection with Applications to Brain Diseases

Science.gov (United States)

Cao, Bokai; He, Lifang; Kong, Xiangnan; Yu, Philip S.; Hao, Zhifeng; Ragin, Ann B.

2015-01-01

In the era of big data, we can easily access information from multiple views which may be obtained from different sources or feature subsets. Generally, different views provide complementary information for learning tasks. Thus, multi-view learning can facilitate the learning process and is prevalent in a wide range of application domains. For example, in medical science, measurements from a series of medical examinations are documented for each subject, including clinical, imaging, immunologic, serologic and cognitive measures which are obtained from multiple sources. Specifically, for brain diagnosis, we can have different quantitative analysis which can be seen as different feature subsets of a subject. It is desirable to combine all these features in an effective way for disease diagnosis. However, some measurements from less relevant medical examinations can introduce irrelevant information which can even be exaggerated after view combinations. Feature selection should therefore be incorporated in the process of multi-view learning. In this paper, we explore tensor product to bring different views together in a joint space, and present a dual method of tensor-based multi-view feature selection (dual-Tmfs) based on the idea of support vector machine recursive feature elimination. Experiments conducted on datasets derived from neurological disorder demonstrate the features selected by our proposed method yield better classification performance and are relevant to disease diagnosis. PMID:25937823
Markov transition probability-based network from time series for characterizing experimental two-phase flow

International Nuclear Information System (INIS)

Gao Zhong-Ke; Hu Li-Dan; Jin Ning-De

2013-01-01

We generate a directed weighted complex network by a method based on Markov transition probability to represent an experimental two-phase flow. We first systematically carry out gas—liquid two-phase flow experiments for measuring the time series of flow signals. Then we construct directed weighted complex networks from various time series in terms of a network generation method based on Markov transition probability. We find that the generated network inherits the main features of the time series in the network structure. In particular, the networks from time series with different dynamics exhibit distinct topological properties. Finally, we construct two-phase flow directed weighted networks from experimental signals and associate the dynamic behavior of gas-liquid two-phase flow with the topological statistics of the generated networks. The results suggest that the topological statistics of two-phase flow networks allow quantitative characterization of the dynamic flow behavior in the transitions among different gas—liquid flow patterns. (general)
Diarylpyrimidine-dihydrobenzyloxopyrimidine hybrids: new, wide-spectrum anti-HIV-1 agents active at (sub)-nanomolar level.

Science.gov (United States)

Rotili, Dante; Tarantino, Domenico; Artico, Marino; Nawrozkij, Maxim B; Gonzalez-Ortega, Emmanuel; Clotet, Bonaventura; Samuele, Alberta; Esté, José A; Maga, Giovanni; Mai, Antonello

2011-04-28

Here, we describe a novel small series of non-nucleoside reverse transcriptase inhibitors (NNRTIs) that combine peculiar structural features of diarylpyrimidines (DAPYs) and dihydro-alkoxy-benzyl-oxopyrimidines (DABOs). These DAPY-DABO hybrids (1-4) showed a characteristic SAR profile and a nanomolar anti-HIV-1 activity at both enzymatic and cellular level. In particular, the two compounds 4d and 2d, with a (sub)nanomolar activity against wild-type and clinically relevant HIV-1 mutant strains, were selected as lead compounds for next optimization studies.
Visual dictionaries as intermediate features in the human brain

Directory of Open Access Journals (Sweden)

Kandan eRamakrishnan

2015-01-01

Full Text Available The human visual system is assumed to transform low level visual features to object and scene representations via features of intermediate complexity. How the brain computationally represents intermediate features is still unclear. To further elucidate this, we compared the biologically plausible HMAX model and Bag of Words (BoW model from computer vision. Both these computational models use visual dictionaries, candidate features of intermediate complexity, to represent visual scenes, and the models have been proven effective in automatic object and scene recognition. These models however differ in the computation of visual dictionaries and pooling techniques. We investigated where in the brain and to what extent human fMRI responses to short video can be accounted for by multiple hierarchical levels of the HMAX and BoW models. Brain activity of 20 subjects obtained while viewing a short video clip was analyzed voxel-wise using a distance-based variation partitioning method. Results revealed that both HMAX and BoW explain a significant amount of brain activity in early visual regions V1, V2 and V3. However BoW exhibits more consistency across subjects in accounting for brain activity compared to HMAX. Furthermore, visual dictionary representations by HMAX and BoW explain significantly some brain activity in higher areas which are believed to process intermediate features. Overall our results indicate that, although both HMAX and BoW account for activity in the human visual system, the BoW seems to more faithfully represent neural responses in low and intermediate level visual areas of the brain.
Quantitative structure-activity relationships of selective antagonists of glucagon receptor using QuaSAR descriptors.

Science.gov (United States)

Manoj Kumar, Palanivelu; Karthikeyan, Chandrabose; Hari Narayana Moorthy, Narayana Subbiah; Trivedi, Piyush

2006-11-01

In the present paper, quantitative structure activity relationship (QSAR) approach was applied to understand the affinity and selectivity of a novel series of triaryl imidazole derivatives towards glucagon receptor. Statistically significant and highly predictive QSARs were derived for glucagon receptor inhibition by triaryl imidazoles using QuaSAR descriptors of molecular operating environment (MOE) employing computer-assisted multiple regression procedure. The generated QSAR models revealed that factors related to hydrophobicity, molecular shape and geometry predominantly influences glucagon receptor binding affinity of the triaryl imidazoles indicating the relevance of shape specific steric interactions between the molecule and the receptor. Further, QSAR models formulated for selective inhibition of glucagon receptor over p38 mitogen activated protein (MAP) kinase of the compounds in the series highlights that the same structural features, which influence the glucagon receptor affinity, also contribute to their selective inhibition.

Comparing infants' use of featural and spatiotemporal information when individuating objects in an event monitoring design

DEFF Research Database (Denmark)

Krøjgaard, Peter

. The results obtained using this design reveal that infants are more successful using spatiotemporal object information than when using featural information. However, recent studies using the less cognitively demanding event monitoring design have revealed that even younger infants are capable of object...... in the present series of experiments in which infants' use of spatiotemporal and featural information is compared directly using the less demanding event monitoring design. The results are discussed in relation to existing empirical evidence......., to what extent infants rely on spatiotemporal or featural object information when individuating objects is currently under debate. Hitherto, infants' use of spatiotemporal and featural object information has only been compared directly using the rather cognitively demanding event mapping design...
Change of spatial information under rescaling: A case study using multi-resolution image series

Science.gov (United States)

Chen, Weirong; Henebry, Geoffrey M.

Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features
Reidentification of Persons Using Clothing Features in Real-Life Video

Directory of Open Access Journals (Sweden)

Guodong Zhang

2017-01-01

Full Text Available Person reidentification, which aims to track people across nonoverlapping cameras, is a fundamental task in automated video processing. Moving people often appear differently when viewed from different nonoverlapping cameras because of differences in illumination, pose, and camera properties. The color histogram is a global feature of an object that can be used for identification. This histogram describes the distribution of all colors on the object. However, the use of color histograms has two disadvantages. First, colors change differently under different lighting and at different angles. Second, traditional color histograms lack spatial information. We used a perception-based color space to solve the illumination problem of traditional histograms. We also used the spatial pyramid matching (SPM model to improve the image spatial information in color histograms. Finally, we used the Gaussian mixture model (GMM to show features for person reidentification, because the main color feature of GMM is more adaptable for scene changes, and improve the stability of the retrieved results for different color spaces in various scenes. Through a series of experiments, we found the relationships of different features that impact person reidentification.
Blue gum gaming machine: an evaluation of responsible gambling features.

Science.gov (United States)

Blaszczynski, Alexander; Gainsbury, Sally; Karlov, Lisa

2014-09-01

Structural characteristics of gaming machines contribute to persistence in play and excessive losses. The purpose of this study was to evaluate the effectiveness of five proposed responsible gaming features: responsible gaming messages; a bank meter quarantining winnings until termination of play; alarm clock facilitating setting time-reminders; demo mode allowing play without money; and a charity donation feature where residual amounts can be donated rather than played to zero credits. A series of ten modified gaming machines were located in five Australian gambling venues. The sample comprised 300 patrons attending the venue and who played the gaming machines. Participants completed a structured interview eliciting gambling and socio-demographic data and information on their perceptions and experience of play on the index machines. Results showed that one-quarter of participants considered that these features would contribute to preventing recreational gamblers from developing problems. Just under half of the participants rated these effects to be at least moderate or significant. The promising results suggest that further refinements to several of these features could represent a modest but effective approach to minimising excessive gambling on gaming machines.
CERN at Arles: LHC featured in prestigious photography festival

CERN Multimedia

Jordan Juras

2011-01-01

Six photographs of the LHC experiment are being featured in this year’s Rencontres d’Arles photography festival. Simon Norfolk’s series, The LHC: the spirit of enquiry, was chosen as part of an exhibition celebrating 30 years of photography at the New York Times Magazine. Simon Norfolk’s series "The LHC: the spirit of enquiry" on display at the Rencontres d'Arles festival. The photographs were originally taken in October 2006, when Norfolk was sent on an assignment to a ‘little known’ laboratory in Switzerland. “When I came to CERN, nobody I knew had ever heard of the place,” explains Norfolk. “Everybody I spoke to when I came back said, ‘You’ve been where? You’ve done what?’” Kathy Ryan, New York Times Magazine photo editor, sent Norfolk to ‘capture something new’. He describes Ryan’s assignments...
A radiographic comparative study of two series of skeletally mature clubfeet treated by two different protocols

Energy Technology Data Exchange (ETDEWEB)

Ippolito, E.; Caterini, R.; Farsetti, P. [Department of Orthopaedic Surgery, University of Rome ' ' Tor Vergata' ' , Via della Ricerca Scientifica 135, 00173, Rome (Italy); Fraracci, L.; Di Mario, M. [Department of Radiology, IRCCS Santa Lucia Institute, Via Ardeatina 306, 00179, Rome (Italy)

2003-08-01

To compare the radiographic features of two series of congenital clubfeet to determine whether a different treatment protocol may influence the radiographic results at the end of skeletal growth. Two series of patients with congenital clubfeet, treated by two different manipulative techniques and by two different complementary soft tissue release operations, were radiographically studied at skeletal maturity. Twenty-one normal feet of the unilateral cases in both series served as controls. Anteroposterior and lateral radiographs of the feet were taken with the patient standing, and several radiographic parameters were studied. The size of the talus and calcaneus and the height of the talar trochlea were smaller than normal in all cases of clubfeet, were similar in both series and were not influenced by treatment, whereas all the other radiographic parameters studied were more or less different between the two series and seemed to be influenced by treatment. In no treated clubfoot of either series was a normal radiographic foot anatomy restored, not even in those feet that had an excellent clinical result. (orig.)
A radiographic comparative study of two series of skeletally mature clubfeet treated by two different protocols

International Nuclear Information System (INIS)

Ippolito, E.; Caterini, R.; Farsetti, P.; Fraracci, L.; Di Mario, M.

2003-01-01

To compare the radiographic features of two series of congenital clubfeet to determine whether a different treatment protocol may influence the radiographic results at the end of skeletal growth. Two series of patients with congenital clubfeet, treated by two different manipulative techniques and by two different complementary soft tissue release operations, were radiographically studied at skeletal maturity. Twenty-one normal feet of the unilateral cases in both series served as controls. Anteroposterior and lateral radiographs of the feet were taken with the patient standing, and several radiographic parameters were studied. The size of the talus and calcaneus and the height of the talar trochlea were smaller than normal in all cases of clubfeet, were similar in both series and were not influenced by treatment, whereas all the other radiographic parameters studied were more or less different between the two series and seemed to be influenced by treatment. In no treated clubfoot of either series was a normal radiographic foot anatomy restored, not even in those feet that had an excellent clinical result. (orig.)
Radiographic features of Ewing's sarcoma of the bones of the hands and feet

International Nuclear Information System (INIS)

Baraga, J.J.; Amrami, K.K.; Swee, R.G.; Wold, L.; Unni, K.K.

2001-01-01

The radiographic features of Ewing's sarcoma of the bones of the hands and feet are reviewed utilizing cases obtained from the Mayo Clinic patient files and the consultation files of Drs. D.C. Dahlin and K.K. Unni. This series consists of a total of 43 cases of pathologically proven Ewing's sarcoma involving the small bones of the hands and feet. The classic radiographic features of Ewing's sarcoma in the long bones, including lytic, permeative destruction, aggressive periosteal reaction, cortical violation, and a soft tissue mass, are also seen in the bones of the hands and feet, with similar frequency. These classic features are most commonly present in lesions affecting the short tubular bones. Lesions affecting the tarsal bones more often demonstrate atypical radiographic features. These atypical radiographic appearances may play a role in the reported delay in diagnosis of Ewing's sarcoma within the tarsal bones. (orig.)
Electrical imaging of deep crustal features of Kutch, India

Science.gov (United States)

Sastry, R. S.; Nagarajan, Nandini; Sarma, S. V. S.

2008-03-01

A regional Magnetotelluric (MT) study, was carried out with 55 MT soundings, distributed along five traverses, across the Kutch Mainland Unit (KMU), on the west coast of India, a region characterized by a series of successive uplifts and intervening depressions in the form of half graben, bounded by master faults. We obtain the deeper electrical structure of the crust beneath Kutch, from 2-D modelling of MT data along the 5 traverses, in order to evaluate the geo-electrical signatures, if any, of the known primary tectonic structures in this region. The results show that the deeper electrical structure in the Kutch region presents a mosaic of high resistive crustal blocks separated by deep-rooted conductive features. Two such crustal conductive features spatially correlate with the known tectonic features, viz., the Kutch Mainland Fault (KMF), and the Katrol Hill Fault (KHF). An impressive feature of the geo-electrical sections is an additional, well-defined conductive feature, running between Jakhau and Mundra, located at the southern end of each of the five MT traverses and interpreted to be the electrical signature of yet another hidden fault at the southern margin of the KMU. This new feature is named as Jakhau-Mundra Fault (JMF). It is inferred that the presence of JMF together with the Kathiawar Fault (NKF), further south, located at the northern boundary of the Saurashtra Horst, would enhance the possibility of occurrence of a thick sedimentary column in the Gulf of Kutch. The region between the newly delineated fault (JMF) and the Kathiawar fault (NKF) could thus be significant for Hydrocarbon Exploration.
Identification of pests and diseases of Dalbergia hainanensis based on EVI time series and classification of decision tree

Science.gov (United States)

Luo, Qiu; Xin, Wu; Qiming, Xiong

2017-06-01

In the process of vegetation remote sensing information extraction, the problem of phenological features and low performance of remote sensing analysis algorithm is not considered. To solve this problem, the method of remote sensing vegetation information based on EVI time-series and the classification of decision-tree of multi-source branch similarity is promoted. Firstly, to improve the time-series stability of recognition accuracy, the seasonal feature of vegetation is extracted based on the fitting span range of time-series. Secondly, the decision-tree similarity is distinguished by adaptive selection path or probability parameter of component prediction. As an index, it is to evaluate the degree of task association, decide whether to perform migration of multi-source decision tree, and ensure the speed of migration. Finally, the accuracy of classification and recognition of pests and diseases can reach 87%--98% of commercial forest in Dalbergia hainanensis, which is significantly better than that of MODIS coverage accuracy of 80%--96% in this area. Therefore, the validity of the proposed method can be verified.
The broken mirror. Metafiction in anglosaxon tv series / El espejo roto: la metaficción en las series anglosajonas

Directory of Open Access Journals (Sweden)

Alberto Nahum García Martínez

2009-01-01

Full Text Available This article examines how, coming from different aesthetic and generic directions, a representative portion of Anglosaxon television series build up their stories by means of breaking –at different levels– the illusionist mirror that characterizes traditional fiction. In this way, they are –implicitly or explicitly– reflecting on the conventions of Realism. The article begins by exposing some theoretical issues about the concept of metafiction. Featuring examples collected since 2001, there follows cartographic research into all the possibilities that metafictional tv-series can harbor: a manipulative narrator, the juxtaposition of diegetical worlds, television as thematic seed for innovative stories, the hybrid game of self-consciousness and, lastly, the direct appeal to the audience’s attention as the major reflective device used by contemporary anglosaxon television series up to now.El artículo estudia cómo, desde diversas propuestas estéticas y genéricas, una porción significativa de la serialidad televisiva anglosajona construye sus tramas rompiendo –en diversos grados– el espejo ilusionista de la ficción y reflexionando así –implícita o explícitamente– sobre las convenciones del realismo. La investigación comienza sentando las bases teóricas de la metaficción. Después, ayudado por ejemplos extraídos desde el año 2001, se traza un repaso cartográfico a sus diferentes posibilidades: la contraposición de mundos diegéticos, la presencia de un narrador que manipula el relato, la propia televisión como semilla temática para nuevas ficciones, el juego híbrido de la autoconsciencia y, por último, la apelación directa al espectador como el mayor alarde reflexivo que se permiten las series anglosajonas contemporáneas.
Generalised Brown Clustering and Roll-up Feature Generation

DEFF Research Database (Denmark)

Derczynski, Leon; Chester, Sean

2016-01-01

active set size. Moreover, the generalisation permits a novel approach to feature selection from Brown clusters: We show that the standard approach of shearing the Brown clustering output tree at arbitrary bitlengths is lossy and that features should be chosen instead by rolling up Generalised Brown...
Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods.

Science.gov (United States)

Georgiadis, Pantelis; Cavouras, Dionisis; Kalatzis, Ioannis; Glotsos, Dimitris; Athanasiadis, Emmanouil; Kostopoulos, Spiros; Sifaki, Koralia; Malamas, Menelaos; Nikiforidis, George; Solomou, Ekaterini

2009-01-01

Three-dimensional (3D) texture analysis of volumetric brain magnetic resonance (MR) images has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to evaluate the efficiency of 3D textural features using a pattern recognition system in the task of discriminating benign, malignant and metastatic brain tissues on T1 postcontrast MR imaging (MRI) series. The dataset consisted of 67 brain MRI series obtained from patients with verified and untreated intracranial tumors. The pattern recognition system was designed as an ensemble classification scheme employing a support vector machine classifier, specially modified in order to integrate the least squares features transformation logic in its kernel function. The latter, in conjunction with using 3D textural features, enabled boosting up the performance of the system in discriminating metastatic, malignant and benign brain tumors with 77.14%, 89.19% and 93.33% accuracy, respectively. The method was evaluated using an external cross-validation process; thus, results might be considered indicative of the generalization performance of the system to "unseen" cases. The proposed system might be used as an assisting tool for brain tumor characterization on volumetric MRI series.
From Fourier Series to Rapidly Convergent Series for Zeta(3)

DEFF Research Database (Denmark)

Scheufens, Ernst E

2011-01-01

The article presents a mathematical study which investigates the exact values of the Riemann zeta (ζ) function. It states that exact values can be determined from Fourier series for periodic versions of even power functions. It notes that using power series for logarithmic functions on this such ......The article presents a mathematical study which investigates the exact values of the Riemann zeta (ζ) function. It states that exact values can be determined from Fourier series for periodic versions of even power functions. It notes that using power series for logarithmic functions...
Cleveland Clinic television series enhances branding in active market.

Science.gov (United States)

Rees, T

2001-01-01

"Medical Miracles" premiered April 26. It is an information-packed series of programs showcasing The Cleveland Clinic's advanced medical practices. The Cleveland Clinic teamed with local NBC-affiliate, WKYC to develop half-hour shows on topics including neuro-sciences, orthopedics, eye, heart, pediatrics and cancer. As of this writing, three of the half-hour shows already have aired. They will resume in September, October and November, following a summer break. The collaboration is a healthy prospect all the way around. For Cleveland Clinic, it provides highly credible visibility in a competitive marketplace. And, according to WKYC president and general manager, Brooke Spectorsky, " Medical news and information is a high priority among our viewers."
Professional activity of the researcher in the field of education: features of planning,resources for implementation, satisfaction with the results

Directory of Open Access Journals (Sweden)

Vladimir S. Sobkin

2017-12-01

Full Text Available Background. The paper examines the attitude of scientists engaged in research in the field of education to various aspects of professional activity: the features of planning, resources for implementation, and satisfaction with the results. The relevance of the study is due to a number of institutional changes in the national science. Thus, the active reform initiated in 2013 was aimed at optimizing and increasing the efficiency of various research institutes, primarily those within the structure of state academies. In this regard, it seems important to identify the scientists’ attitude to the results of the implemented initiatives within the period of the last four years. Objective. The paper is to analyze the influence of age and social indicators of professional status (academic degree, academic title, position held, publication activity on various aspects of the professional activity of the researches. Design and sample characteristics. A special questionnaire of 72 questions was developed (closed, open and scale, 721 respondents were interviewed. The sample included employees with different levels of scientific qualifications and length of professional scientific activity. Both employees of scientific research institutes and universities from different regions of the Russian Federation were interviewed. Results. The results show the manifestation of negative tendencies concerning the planning of scientific activity related to its authoritarian nature and formal requirements for reporting on the results of scientific activity. The peculiarities of well-being of scientific employees at the stage of completing a professional career are revealed. The features of the manifestation of the professional crisis, which is characteristic for the age cohort of forty-year scientific workers, are considered. The specifics of attracting personal funds and additional financial sources depending on various indicators of the professional status of the
Analysis of a hundred-years series of magnetic activity indices. III. Is the frequency distribution logarithmo-normal

International Nuclear Information System (INIS)

Mayaud, P.N.

1976-01-01

Because of the various components of positive conservation existing in the series of aa indices, their frequency distribution is necessarily distorted with respect to any random distribution. However when one takes these various components into account, the observed distribution can be considered as being a logarithmo-normal distribution. This implies that the geomagnetic activity satisfies the conditions of the central limit theorem, according to which a phenomenon which presents such a distribution is due to independent causes whose effects are multiplicative. Furthermore, the distorsion of the frequency distribution caused by the 11-year and 90-year cycles corresponds to a pure attenuation effect; an interpretation by the solar 'coronal holes' is proposed [fr
Series, Telenovelas and Soaps: Tragedy in the Living Room

Directory of Open Access Journals (Sweden)

Lejla Panjeta

2015-12-01

Full Text Available The focus of this work is to establish the inherent features of the serial genres in television that emerged from literature and discuss their importance and impact on the spectatorship. The rise and development of the serial genres will be discussed along with the growing influence on the society and individuals. How much do the genres of telenovelas and series differ in the context of cultural nuances and what is the genesis of the human urgency in retelling the melodramatic and tragic narratives? Enormous popularity deriving from these stories is reflected in the prime time broadcasting by Croatian, Serbian and Bosnian TV stations since 2002. The essay will explain the ontogenesis of the popularity, reflections and influences on societies and cultures, and features of this hybrid and changing genre of telenovelas and the most recent infatuation with Turkish serials in the TV region of West Balkans.
Chromospheric rotation. II. Dependence on the size of chromospheric features

Energy Technology Data Exchange (ETDEWEB)

Azzarelli, L; Casalini, P; Cerri, S; Denoth, F [Consiglio Nazionale delle Ricerche, Pisa (Italy). Ist. di Elaborazione della Informazione

1979-08-01

The dependence of solar rotation on the size of the chromospheric tracers is considered. On the basis of an analysis of Ca II K/sub 3/ daily filtergrams taken in the period 8 May-14 August, 1972, chromospheric features can be divided into two classes according to their size. Features with size falling into the range 24 000-110 000 km can be identified with network elements, while those falling into the range 120 000-300 000 km with active regions, or brightness features of comparable size present at high latitudes. The rotation rate is determined separately for the two families of chromospheric features by means of a cross-correlation technique directly yields the average daily displacement of tracers due to rotation. Before computing the cross-correlation functions, chromospheric brightness data have been filtered with appropriate bandpass and highpass filters for separating spatial periodicities whose wavelengths fall into the two ranges of size, characteristic of the network pattern and of the activity centers. A difference less than 1% of the rotation rate of the two families of chromospheric features has been found. This is an indication for a substantial corotation at chromospheric levels of different short-lived features, both related to solar activity and controlled by the convective supergranular motions.
HRPT2- (CDC73) RELATED HEREDITARY HYPERPARATHYROIDISM: A CASE SERIES FROM WESTERN INDIA.

Science.gov (United States)

Khadilkar, Kranti S; Budyal, Sweta R; Kasliwal, Rajiv; Lila, Anurag R; Bandgar, Tushar; Shah, Nalini S

2015-09-01

To describe a case series of HRPT2- (CDC73) related hereditary primary hyperparathyroidism (PHPT) from western India. We present a case series of 4 families (7 patients) with PHPT caused by CDC73 gene mutations. The mean age of presentation of the 4 index cases was 27.25 ± 9.8 years. Two family members were identified through biochemical screening (Cases 1b and 2b), while 1 mutation-positive family member did not manifest any features of PHPT or hyperparathyroidism jaw tumor syndrome (HPT-JT) syndrome (Case 2c). Biochemistry showed increased serum calcium (mean: 13.21 ± 1.24 mg/dL), low serum phosphorus (mean: 1.78 ± 0.44 mg/dL), and high parathyroid hormone (PTH, mean: 936 ± 586.9 pg/mL). All patients had a uniglandular presentation and underwent single adenoma excision initially except Cases 2a and 2b, who underwent subtotal parathyroidectomy at baseline. Two cases experienced PHPT recurrence (Cases 3 and 4), while 1 remained uncured due to parathyroid carcinoma (Case 1a). Other associated syndromic features like ossifying jaw fibromas were present in 2 patients, renal cysts in 3 patients, and uterine involvement in 2 patients. Two families had novel germline CDC73 mutations (Families 1 and 3), while the other 2 had reported mutations. Family 2 had familial isolated PHPT without any other features of HPT-JT syndrome. Our findings reaffirm the need for genetic analysis of patients with PHPT, especially those with younger age of disease onset; recurrent disease; and associated features like polycystic kidneys, endometrial involvement, ossifying jaw tumors, or parathyroid carcinoma.

Feature Extraction and Analysis of Breast Cancer Specimen

Science.gov (United States)

Bhattacharyya, Debnath; Robles, Rosslin John; Kim, Tai-Hoon; Bandyopadhyay, Samir Kumar

In this paper, we propose a method to identify abnormal growth of cells in breast tissue and suggest further pathological test, if necessary. We compare normal breast tissue with malignant invasive breast tissue by a series of image processing steps. Normal ductal epithelial cells and ductal / lobular invasive carcinogenic cells also consider for comparison here in this paper. In fact, features of cancerous breast tissue (invasive) are extracted and analyses with normal breast tissue. We also suggest the breast cancer recognition technique through image processing and prevention by controlling p53 gene mutation to some greater extent.
Gastric schwannomas: radiological features with endoscopic and pathological correlation

Energy Technology Data Exchange (ETDEWEB)

Hong, H.S. [Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seodaemoon-gu, Seoul (Korea, Republic of); Ha, H.K. [Department of Radiology, University of Ulsan College of Medicine, Songpa-gu, Seoul (Korea, Republic of)], E-mail: hkha@amc.seoul.kr; Won, H.J.; Byun, J.H.; Shin, Y.M.; Kim, A.Y.; Kim, P.N.; Lee, M.-G. [Department of Radiology, University of Ulsan College of Medicine, Songpa-gu, Seoul (Korea, Republic of); Lee, G.H. [Internal Medicine, University of Ulsan College of Medicine, Songpa-gu, Seoul (Korea, Republic of); Kim, M.J. [Pathology, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul (Korea, Republic of)

2008-05-15

Aim: To describe the radiological, endoscopic, and pathological findings of gastric schwannomas in 16 patients. Materials and methods: The radiological, endoscopic, and pathological findings of 16 surgically proven cases of gastric schwannoma were retrospectively reviewed. All patients underwent computed tomography (CT) and four patients were evaluated with upper gastrointestinal series. Two radiologists reviewed the CT and upper gastrointestinal series images by consensus with regard to tumour size, contour, margin, and growth pattern, the presence or absence of ulcer, cystic change, and the CT enhancement pattern. Endoscopy was performed in eight of these 16 patients. Six patients underwent endoscopic ultrasonography. Pathological specimens were obtained from and reviewed in all 16 patients. Immunohistochemistry was performed for c-kit, CD34, smooth muscle actin, and S-100 protein. Results: On radiographic examination, gastric schwannomas appeared as submucosal tumours with the CT features of well-demarcated, homogeneous, and uncommonly ulcerated masses. Endoscopy with endoscopic ultrasonography demonstrated homogeneous, submucosal masses contiguous with the muscularis propria in all six examined cases. On pathological examination, gastric schwannomas appeared as well-circumscribed and homogeneous tumours in the muscularis propria and consisted microscopically of interlacing bundles of spindle cells. Strong positivity for S-100 protein was demonstrated in all 16 cases on immunohistochemistry. Conclusion: Gastric schwannomas appear as submucosal tumours of the stomach and have well-demarcated and homogeneous features on CT, endoscopic ultrasonography, and gross pathology. Immunohistochemistry consistently reveals positivity for S-100 protein in the tumours.
Gastric schwannomas: radiological features with endoscopic and pathological correlation

International Nuclear Information System (INIS)

Hong, H.S.; Ha, H.K.; Won, H.J.; Byun, J.H.; Shin, Y.M.; Kim, A.Y.; Kim, P.N.; Lee, M.-G.; Lee, G.H.; Kim, M.J.

2008-01-01

Aim: To describe the radiological, endoscopic, and pathological findings of gastric schwannomas in 16 patients. Materials and methods: The radiological, endoscopic, and pathological findings of 16 surgically proven cases of gastric schwannoma were retrospectively reviewed. All patients underwent computed tomography (CT) and four patients were evaluated with upper gastrointestinal series. Two radiologists reviewed the CT and upper gastrointestinal series images by consensus with regard to tumour size, contour, margin, and growth pattern, the presence or absence of ulcer, cystic change, and the CT enhancement pattern. Endoscopy was performed in eight of these 16 patients. Six patients underwent endoscopic ultrasonography. Pathological specimens were obtained from and reviewed in all 16 patients. Immunohistochemistry was performed for c-kit, CD34, smooth muscle actin, and S-100 protein. Results: On radiographic examination, gastric schwannomas appeared as submucosal tumours with the CT features of well-demarcated, homogeneous, and uncommonly ulcerated masses. Endoscopy with endoscopic ultrasonography demonstrated homogeneous, submucosal masses contiguous with the muscularis propria in all six examined cases. On pathological examination, gastric schwannomas appeared as well-circumscribed and homogeneous tumours in the muscularis propria and consisted microscopically of interlacing bundles of spindle cells. Strong positivity for S-100 protein was demonstrated in all 16 cases on immunohistochemistry. Conclusion: Gastric schwannomas appear as submucosal tumours of the stomach and have well-demarcated and homogeneous features on CT, endoscopic ultrasonography, and gross pathology. Immunohistochemistry consistently reveals positivity for S-100 protein in the tumours
Synthesis and Structure-Activity Relationships of Novel Amino/Nitro Substituted 3-Arylcoumarins as Antibacterial Agents

Directory of Open Access Journals (Sweden)

Ysabel Santos

2013-01-01

Full Text Available A new series of amino/nitro-substituted 3-arylcoumarins were synthesized and their antibacterial activity against clinical isolates of Staphylococcus aureus (Gram-positive and Escherichia coli (Gram-negative was evaluated. Some of these molecules exhibited antibacterial activity against S. aureus comparable to the standards used (oxolinic acid and ampicillin. The preliminary structure-activity relationship (SAR study showed that the antibacterial activity against S. aureus depends on the position of the 3-arylcoumarin substitution pattern. With the aim of finding the structural features for the antibacterial activity and selectivity, in the present manuscript different positions of nitro, methyl, methoxy, amino and bromo substituents on the 3-arylcoumarin scaffold were reported.
A study of radiological features of healing in long bone fractures among infants less than a year

Energy Technology Data Exchange (ETDEWEB)

Warner, Christopher; Miller, Angie; Weinman, Jason; Fadell, Michael [Children' s Hospital Colorado, Department of Radiology, Aurora, CO (United States); Maguire, Sabine; Trefan, Laszlo [Cardiff University, Institute of Primary Care and Child Health, Cardiff (United Kingdom)

2017-03-15

To create a timetable for dating long bone fractures in infants aged less than 1 year using previously defined radiographic signs of fracture healing. A retrospective cross-sectional time series of long bone fractures in infants aged less than 1 year was conducted from 2006 to 2013. After exclusion criteria were applied 59 digital image series were available for review from 40 infants. Utilizing published criteria for dating fractures, the presence or absence of four pre-defined features of healing was scored: periosteal reaction, callus, bridging, and remodeling. Three radiologists independently scored radiographs with a 3-point scale, marking each feature as present, absent, or equivocal. The times in days when features were first seen, peaked (feature agreed present in >40% of images), and last seen were noted. Statistical analysis using free marginal kappa was conducted. The level of agreement among the three radiologists was high (0.64-0.85). The sequence in which the features were seen was: periosteal reaction range 7-130 (present in the majority of cases between 9 and 49 days); callus range 9-130 (present in the majority of cases between days 9-26); bridging range 15-130 (seen in the majority of cases between 15 and 67 days); remodeling range 51-247 days. This study provides a timetable of radiological features of long bone healing among young infants for the first time. Dating of incomplete long bone fractures is challenging, beyond the presence of periosteal reaction, but a consistent sequence of changes is present in complete fractures. (orig.)
Incorporating Satellite Time-Series Data into Modeling

Science.gov (United States)

Gregg, Watson

2008-01-01

In situ time series observations have provided a multi-decadal view of long-term changes in ocean biology. These observations are sufficiently reliable to enable discernment of even relatively small changes, and provide continuous information on a host of variables. Their key drawback is their limited domain. Satellite observations from ocean color sensors do not suffer the drawback of domain, and simultaneously view the global oceans. This attribute lends credence to their use in global and regional model validation and data assimilation. We focus on these applications using the NASA Ocean Biogeochemical Model. The enhancement of the satellite data using data assimilation is featured and the limitation of tongterm satellite data sets is also discussed.
Discovery of a Series of Imidazo[4,5-b]pyridines with Dual Activity at Angiotensin II Type 1 Receptor and Peroxisome Proliferator-Activated Receptor-[gamma

Energy Technology Data Exchange (ETDEWEB)

Casimiro-Garcia, Agustin; Filzen, Gary F.; Flynn, Declan; Bigge, Christopher F.; Chen, Jing; Davis, Jo Ann; Dudley, Danette A.; Edmunds, Jeremy J.; Esmaeil, Nadia; Geyer, Andrew; Heemstra, Ronald J.; Jalaie, Mehran; Ohren, Jeffrey F.; Ostroski, Robert; Ellis, Teresa; Schaum, Robert P.; Stoner, Chad (Pfizer)

2013-03-07

Mining of an in-house collection of angiotensin II type 1 receptor antagonists to identify compounds with activity at the peroxisome proliferator-activated receptor-{gamma} (PPAR{gamma}) revealed a new series of imidazo[4,5-b]pyridines 2 possessing activity at these two receptors. Early availability of the crystal structure of the lead compound 2a bound to the ligand binding domain of human PPAR{gamma} confirmed the mode of interaction of this scaffold to the nuclear receptor and assisted in the optimization of PPAR{gamma} activity. Among the new compounds, (S)-3-(5-(2-(1H-tetrazol-5-yl)phenyl)-2,3-dihydro-1H-inden-1-yl)-2-ethyl-5-isobutyl-7-methyl-3H-imidazo[4,5-b]pyridine (2l) was identified as a potent angiotensin II type I receptor blocker (IC{sub 50} = 1.6 nM) with partial PPAR{gamma} agonism (EC{sub 50} = 212 nM, 31% max) and oral bioavailability in rat. The dual pharmacology of 2l was demonstrated in animal models of hypertension (SHR) and insulin resistance (ZDF rat). In the SHR, 2l was highly efficacious in lowering blood pressure, while robust lowering of glucose and triglycerides was observed in the male ZDF rat.
Overview of centaur and graspin enviroment generators part 1 syntx related features

OpenAIRE

Zuppa, Elisabetta

1989-01-01

A short presentation of two generic interactive environments- GRASPIN and CENTAUR- is given. When provided with the description of a particular language-including its syntax and semantics- GRASPIN and CENTAUR produce an environment specific for that language. This is the first of a series of notes regarding the above systems which will cover the semantic specification and user-interface features of both of them.
An Investigation Into the Culture and Social Actors Representation in Summit Series ELT Textbooks Within van Leeuwen’s 1996 Framework

Directory of Open Access Journals (Sweden)

Nasser Rashidi

2015-03-01

Full Text Available The current study aims at identifying particular ways through which social actors are represented in Summit Series ELT textbooks. It examines cultural load in the textbooks within critical discourse analysis framework, in this case van Leeuwen’s framework. Particularly, the study attempts to explore if values, norms, and roles are culture/context-bound. Results of the analyses showed that among discursive features, Inclusion, Genericization, and Indetermination were used more than Exclusion, Specification, and Determination. Activation was more observed than Passivation, and Categorization had an important function in the representation of some of the social actors along with Assimilation and Impersonalization. The analysis also indicated the impartiality toward the representation of social actors. Moral, social, and personal values were the most disseminated values, while social morality and traditions had the highest occurrence. However, a few discriminative cases were found regarding gender roles. The researchers proposed that Summit Series were less grounded in cultural assumptions/biases. This impartiality eases language learning by keeping learners away from misunderstanding and incomprehensibility.
OceanXtremes: Scalable Anomaly Detection in Oceanographic Time-Series

Science.gov (United States)

Wilson, B. D.; Armstrong, E. M.; Chin, T. M.; Gill, K. M.; Greguska, F. R., III; Huang, T.; Jacob, J. C.; Quach, N.

2016-12-01

The oceanographic community must meet the challenge to rapidly identify features and anomalies in complex and voluminous observations to further science and improve decision support. Given this data-intensive reality, we are developing an anomaly detection system, called OceanXtremes, powered by an intelligent, elastic Cloud-based analytic service backend that enables execution of domain-specific, multi-scale anomaly and feature detection algorithms across the entire archive of 15 to 30-year ocean science datasets.Our parallel analytics engine is extending the NEXUS system and exploits multiple open-source technologies: Apache Cassandra as a distributed spatial "tile" cache, Apache Spark for in-memory parallel computation, and Apache Solr for spatial search and storing pre-computed tile statistics and other metadata. OceanXtremes provides these key capabilities: Parallel generation (Spark on a compute cluster) of 15 to 30-year Ocean Climatologies (e.g. sea surface temperature or SST) in hours or overnight, using simple pixel averages or customizable Gaussian-weighted "smoothing" over latitude, longitude, and time; Parallel pre-computation, tiling, and caching of anomaly fields (daily variables minus a chosen climatology) with pre-computed tile statistics; Parallel detection (over the time-series of tiles) of anomalies or phenomena by regional area-averages exceeding a specified threshold (e.g. high SST in El Nino or SST "blob" regions), or more complex, custom data mining algorithms; Shared discovery and exploration of ocean phenomena and anomalies (facet search using Solr), along with unexpected correlations between key measured variables; Scalable execution for all capabilities on a hybrid Cloud, using our on-premise OpenStack Cloud cluster or at Amazon. The key idea is that the parallel data-mining operations will be run "near" the ocean data archives (a local "network" hop) so that we can efficiently access the thousands of files making up a three decade time-series
Chronic actinic dermatitis - A study of clinical features

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Somani Vijay

2005-01-01

Full Text Available Background: Chronic actinic dermatitis (CAD, one of the immune mediated photo-dermatoses, comprises a spectrum of conditions including persistent light reactivity, photosensitive eczema and actinic reticuloid. Diagnostic criteria were laid down about 20 years back, but clinical features are the mainstay in diagnosis. In addition to extreme sensitivity to UVB, UVA and/or visible light, about three quarters of patients exhibit contact sensitivity to several allergens, which may contribute to the etiopathogenesis of CAD. This study was undertaken to examine the clinical features of CAD in India and to evaluate the relevance of patch testing and photo-aggravation testing in the diagnosis of CAD. Methods: The clinical data of nine patients with CAD were analyzed. Histopathology, patch testing and photo-aggravation testing were also performed. Results: All the patients were males. The average age of onset was 57 years. The first episode was usually noticed in the beginning of summer. Later the disease gradually tended to be perennial, without any seasonal variations. The areas affected were mainly the photo-exposed areas in all patients, and the back in three patients. Erythroderma was the presenting feature in two patients. The palms and soles were involved in five patients. Patch testing was positive in seven of nine patients. Conclusions: The diagnosis of CAD mainly depended upon the history and clinical features. The incidence of erythroderma and palmoplantar eczema was high in our series. Occupation seems to play a role in the etiopathogenesis of CAD.
On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

Science.gov (United States)

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.
Clinical, biochemical and ultrasonographic features of infertile women with polycystic ovarian syndrome

International Nuclear Information System (INIS)

Haq, F.; Rizvi, J.

2007-01-01

To evaluate and compare the clinical, biochemical and ultrasonic features of infertile women with PCOS from the two infertility centers of Karachi, The Aga Khan University Hospital and Concept Fertility Centre. Patients attending the Infertility Clinics of Aga Khan University Hospital, Karachi and Concept Fertility Centre, Karachi, were evaluated for their clinical features. Complete biochemical evaluation was performed by day 2 FSH, LH, serum prolactin, serum testosterone and fasting serum insulin determination. These results were recorded on the data collection form. Ultrasonic evaluation was performed with transvaginal ultrasound to check the morphological appearance of ovaries. A total of 508 patients were evaluated for epidemiological features of PCOS. Frequency of PCOS in the infertility clinic was 17.6% with high rate of obesity (68.5%) and hyperinsulinemia (59%). The highest rate of abnormal clinical, biochemical features were seen above BMI of 30. High rates of obesity, hyperinsulinemia and impaired glycemic control were seen in this series. It was demonstrated that high BMI had an association and correlation with abnormal clinical and biochemical features. Obese women with PCOS need more attention for their appropriate management. (author)
A review of feature detection and match algorithms for localization and mapping

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Li, Shimiao

2017-09-01

Localization and mapping is an essential ability of a robot to keep track of its own location in an unknown environment. Among existing methods for this purpose, vision-based methods are more effective solutions for being accurate, inexpensive and versatile. Vision-based methods can generally be categorized as feature-based approaches and appearance-based approaches. The feature-based approaches prove higher performance in textured scenarios. However, their performance depend highly on the applied feature-detection algorithms. In this paper, we surveyed algorithms for feature detection, which is an essential step in achieving vision-based localization and mapping. In this pater, we present mathematical models of the algorithms one after another. To compare the performances of the algorithms, we conducted a series of experiments on their accuracy, speed, scale invariance and rotation invariance. The results of the experiments showed that ORB is the fastest algorithm in detecting and matching features, the speed of which is more than 10 times that of SURF and approximately 40 times that of SIFT. And SIFT, although with no advantage in terms of speed, shows the most correct matching pairs and proves its accuracy.
The Generalized Hill Model: A Kinematic Approach Towards Active Muscle Contraction

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Menzel, Andreas; Kuhl, Ellen

2014-01-01

Excitation-contraction coupling is the physiological process of converting an electrical stimulus into a mechanical response. In muscle, the electrical stimulus is an action potential and the mechanical response is active contraction. The classical Hill model characterizes muscle contraction though one contractile element, activated by electrical excitation, and two non-linear springs, one in series and one in parallel. This rheology translates into an additive decomposition of the total stress into a passive and an active part. Here we supplement this additive decomposition of the stress by a multiplicative decomposition of the deformation gradient into a passive and an active part. We generalize the one-dimensional Hill model to the three-dimensional setting and constitutively define the passive stress as a function of the total deformation gradient and the active stress as a function of both the total deformation gradient and its active part. We show that this novel approach combines the features of both the classical stress-based Hill model and the recent active-strain models. While the notion of active stress is rather phenomenological in nature, active strain is micro-structurally motivated, physically measurable, and straightforward to calibrate. We demonstrate that our model is capable of simulating excitation-contraction coupling in cardiac muscle with its characteristic features of wall thickening, apical lift, and ventricular torsion. PMID:25221354
Transition Icons for Time-Series Visualization and Exploratory Analysis.

Science.gov (United States)

Nickerson, Paul V; Baharloo, Raheleh; Wanigatunga, Amal A; Manini, Todd M; Tighe, Patrick J; Rashidi, Parisa

2018-03-01

The modern healthcare landscape has seen the rapid emergence of techniques and devices that temporally monitor and record physiological signals. The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our framework, which we call transition icons, renders common patterns in a visual format useful for understanding the shared behavior within groups of time series. Transition icons are adept at detecting and displaying subtle differences and similarities, e.g., between measurements taken from patients receiving different treatment strategies or stratified by demographics. We introduce various methods that collectively allow for exploratory analysis of groups of time series, while being free of distribution assumptions and including simple heuristics for parameter determination. Our technique extracts discrete transition patterns from symbolic aggregate approXimation representations, and compiles transition frequencies into a bag of patterns constructed for each group. These transition frequencies are normalized and aligned in icon form to intuitively display the underlying patterns. We demonstrate the transition icon technique for two time-series datasets-postoperative pain scores, and hip-worn accelerometer activity counts. We believe transition icons can be an important tool for researchers approaching time-series data, as they give rich and intuitive information about collective time-series behaviors.
Linear feature detection algorithm for astronomical surveys - I. Algorithm description

Science.gov (United States)

Bektešević, Dino; Vinković, Dejan

2017-11-01

Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars and galaxies, ignoring completely the detection of existing linear features. With the emergence of wide-field sky surveys, linear features attract scientific interest as possible trails of fast flybys of near-Earth asteroids and meteors. In this work, we describe a new linear feature detection algorithm designed specifically for implementation in big data astronomy. The algorithm combines a series of algorithmic steps that first remove other objects (stars and galaxies) from the image and then enhance the line to enable more efficient line detection with the Hough algorithm. The rate of false positives is greatly reduced thanks to a step that replaces possible line segments with rectangles and then compares lines fitted to the rectangles with the lines obtained directly from the image. The speed of the algorithm and its applicability in astronomical surveys are also discussed.
Features of Investment Activity in Agriculture in the South of Russia and Ways of its Activation

Directory of Open Access Journals (Sweden)

Vladimir Ivanovich Trukhachev

2018-03-01

Full Text Available The relevance of this article on the topic: “Features of Investment Activity in Agriculture in the South of Russia and Ways of its Activation” is that at the present time, as a result of the systemic crisis of the Russian economy, a set of objective prerequisites for improving the financial and credit mechanisms in the agro industrial complex has been formed. The fall in the rouble exchange rate to foreign currencies made foreign agricultural products and food too expensive on the Russian market and sales fell sharply in Russia. This led to the emergence of free niches in the domestic agrarian market and increased the competitiveness of domestic agricultural products and food. In these conditions, an important task for Russian agricultural producers is to increase the volume of production and sales of agricultural products, and this requires an increase in production capacity, modernization of the material and technical base. To solve these problems, it is necessary to increase investment in the agricul-tural sector of the economy, which without improving the existing credit and financial system in the Russian agribusiness sector cannot be done. Based on the goal set by the authors, the subject of the study are factors and patterns that affect investment in agriculture. To write the article, dialectical methods of cognition of socioeconomic, natural-biological processes and phenomena were used as well as the systemic approach: analytical, economic-statistical, monographic, calculating and constructive and expert evaluations. This allowed working out effective measures to intensify investment activity by improving the lending process as the main source of external investment, and solving the problems of financing agricultural organizations, using non-traditional external sources of investment for agriculture in Stavropol Krai.
Two-parameter double-oscillator model of Mathews-Lakshmanan type: Series solutions and supersymmetric partners

International Nuclear Information System (INIS)

Schulze-Halberg, Axel; Wang, Jie

2015-01-01

We obtain series solutions, the discrete spectrum, and supersymmetric partners for a quantum double-oscillator system. Its potential features a superposition of the one-parameter Mathews-Lakshmanan interaction and a one-parameter harmonic or inverse harmonic oscillator contribution. Furthermore, our results are transferred to a generalized Pöschl-Teller model that is isospectral to the double-oscillator system
Two-parameter double-oscillator model of Mathews-Lakshmanan type: Series solutions and supersymmetric partners

Energy Technology Data Exchange (ETDEWEB)

Schulze-Halberg, Axel, E-mail: axgeschu@iun.edu, E-mail: xbataxel@gmail.com [Department of Mathematics and Actuarial Science and Department of Physics, Indiana University Northwest, 3400 Broadway, Gary, Indiana 46408 (United States); Wang, Jie, E-mail: wangjie@iun.edu [Department of Computer Information Systems, Indiana University Northwest, 3400 Broadway, Gary, Indiana 46408 (United States)

2015-07-15

We obtain series solutions, the discrete spectrum, and supersymmetric partners for a quantum double-oscillator system. Its potential features a superposition of the one-parameter Mathews-Lakshmanan interaction and a one-parameter harmonic or inverse harmonic oscillator contribution. Furthermore, our results are transferred to a generalized Pöschl-Teller model that is isospectral to the double-oscillator system.

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