WorldWideScience

Sample records for randomly selected based

  1. Materials selection for oxide-based resistive random access memories

    International Nuclear Information System (INIS)

    Guo, Yuzheng; Robertson, John

    2014-01-01

    The energies of atomic processes in resistive random access memories (RRAMs) are calculated for four typical oxides, HfO 2 , TiO 2 , Ta 2 O 5 , and Al 2 O 3 , to define a materials selection process. O vacancies have the lowest defect formation energy in the O-poor limit and dominate the processes. A band diagram defines the operating Fermi energy and O chemical potential range. It is shown how the scavenger metal can be used to vary the O vacancy formation energy, via controlling the O chemical potential, and the mean Fermi energy. The high endurance of Ta 2 O 5 RRAM is related to its more stable amorphous phase and the adaptive lattice rearrangements of its O vacancy

  2. Materials selection for oxide-based resistive random access memories

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Yuzheng; Robertson, John [Engineering Department, Cambridge University, Cambridge CB2 1PZ (United Kingdom)

    2014-12-01

    The energies of atomic processes in resistive random access memories (RRAMs) are calculated for four typical oxides, HfO{sub 2}, TiO{sub 2}, Ta{sub 2}O{sub 5}, and Al{sub 2}O{sub 3}, to define a materials selection process. O vacancies have the lowest defect formation energy in the O-poor limit and dominate the processes. A band diagram defines the operating Fermi energy and O chemical potential range. It is shown how the scavenger metal can be used to vary the O vacancy formation energy, via controlling the O chemical potential, and the mean Fermi energy. The high endurance of Ta{sub 2}O{sub 5} RRAM is related to its more stable amorphous phase and the adaptive lattice rearrangements of its O vacancy.

  3. TEHRAN AIR POLLUTANTS PREDICTION BASED ON RANDOM FOREST FEATURE SELECTION METHOD

    Directory of Open Access Journals (Sweden)

    A. Shamsoddini

    2017-09-01

    Full Text Available Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

  4. Tehran Air Pollutants Prediction Based on Random Forest Feature Selection Method

    Science.gov (United States)

    Shamsoddini, A.; Aboodi, M. R.; Karami, J.

    2017-09-01

    Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

  5. Blocked Randomization with Randomly Selected Block Sizes

    Directory of Open Access Journals (Sweden)

    Jimmy Efird

    2010-12-01

    Full Text Available When planning a randomized clinical trial, careful consideration must be given to how participants are selected for various arms of a study. Selection and accidental bias may occur when participants are not assigned to study groups with equal probability. A simple random allocation scheme is a process by which each participant has equal likelihood of being assigned to treatment versus referent groups. However, by chance an unequal number of individuals may be assigned to each arm of the study and thus decrease the power to detect statistically significant differences between groups. Block randomization is a commonly used technique in clinical trial design to reduce bias and achieve balance in the allocation of participants to treatment arms, especially when the sample size is small. This method increases the probability that each arm will contain an equal number of individuals by sequencing participant assignments by block. Yet still, the allocation process may be predictable, for example, when the investigator is not blind and the block size is fixed. This paper provides an overview of blocked randomization and illustrates how to avoid selection bias by using random block sizes.

  6. Differential privacy-based evaporative cooling feature selection and classification with relief-F and random forests.

    Science.gov (United States)

    Le, Trang T; Simmons, W Kyle; Misaki, Masaya; Bodurka, Jerzy; White, Bill C; Savitz, Jonathan; McKinney, Brett A

    2017-09-15

    Classification of individuals into disease or clinical categories from high-dimensional biological data with low prediction error is an important challenge of statistical learning in bioinformatics. Feature selection can improve classification accuracy but must be incorporated carefully into cross-validation to avoid overfitting. Recently, feature selection methods based on differential privacy, such as differentially private random forests and reusable holdout sets, have been proposed. However, for domains such as bioinformatics, where the number of features is much larger than the number of observations p≫n , these differential privacy methods are susceptible to overfitting. We introduce private Evaporative Cooling, a stochastic privacy-preserving machine learning algorithm that uses Relief-F for feature selection and random forest for privacy preserving classification that also prevents overfitting. We relate the privacy-preserving threshold mechanism to a thermodynamic Maxwell-Boltzmann distribution, where the temperature represents the privacy threshold. We use the thermal statistical physics concept of Evaporative Cooling of atomic gases to perform backward stepwise privacy-preserving feature selection. On simulated data with main effects and statistical interactions, we compare accuracies on holdout and validation sets for three privacy-preserving methods: the reusable holdout, reusable holdout with random forest, and private Evaporative Cooling, which uses Relief-F feature selection and random forest classification. In simulations where interactions exist between attributes, private Evaporative Cooling provides higher classification accuracy without overfitting based on an independent validation set. In simulations without interactions, thresholdout with random forest and private Evaporative Cooling give comparable accuracies. We also apply these privacy methods to human brain resting-state fMRI data from a study of major depressive disorder. Code

  7. Minimization over randomly selected lines

    Directory of Open Access Journals (Sweden)

    Ismet Sahin

    2013-07-01

    Full Text Available This paper presents a population-based evolutionary optimization method for minimizing a given cost function. The mutation operator of this method selects randomly oriented lines in the cost function domain, constructs quadratic functions interpolating the cost function at three different points over each line, and uses extrema of the quadratics as mutated points. The crossover operator modifies each mutated point based on components of two points in population, instead of one point as is usually performed in other evolutionary algorithms. The stopping criterion of this method depends on the number of almost degenerate quadratics. We demonstrate that the proposed method with these mutation and crossover operations achieves faster and more robust convergence than the well-known Differential Evolution and Particle Swarm algorithms.

  8. Comparison of confirmed inactive and randomly selected compounds as negative training examples in support vector machine-based virtual screening.

    Science.gov (United States)

    Heikamp, Kathrin; Bajorath, Jürgen

    2013-07-22

    The choice of negative training data for machine learning is a little explored issue in chemoinformatics. In this study, the influence of alternative sets of negative training data and different background databases on support vector machine (SVM) modeling and virtual screening has been investigated. Target-directed SVM models have been derived on the basis of differently composed training sets containing confirmed inactive molecules or randomly selected database compounds as negative training instances. These models were then applied to search background databases consisting of biological screening data or randomly assembled compounds for available hits. Negative training data were found to systematically influence compound recall in virtual screening. In addition, different background databases had a strong influence on the search results. Our findings also indicated that typical benchmark settings lead to an overestimation of SVM-based virtual screening performance compared to search conditions that are more relevant for practical applications.

  9. A Permutation Importance-Based Feature Selection Method for Short-Term Electricity Load Forecasting Using Random Forest

    Directory of Open Access Journals (Sweden)

    Nantian Huang

    2016-09-01

    Full Text Available The prediction accuracy of short-term load forecast (STLF depends on prediction model choice and feature selection result. In this paper, a novel random forest (RF-based feature selection method for STLF is proposed. First, 243 related features were extracted from historical load data and the time information of prediction points to form the original feature set. Subsequently, the original feature set was used to train an RF as the original model. After the training process, the prediction error of the original model on the test set was recorded and the permutation importance (PI value of each feature was obtained. Then, an improved sequential backward search method was used to select the optimal forecasting feature subset based on the PI value of each feature. Finally, the optimal forecasting feature subset was used to train a new RF model as the final prediction model. Experiments showed that the prediction accuracy of RF trained by the optimal forecasting feature subset was higher than that of the original model and comparative models based on support vector regression and artificial neural network.

  10. Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

    Science.gov (United States)

    Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark

    2015-01-01

    Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed

  11. Field-based random sampling without a sampling frame: control selection for a case-control study in rural Africa.

    Science.gov (United States)

    Crampin, A C; Mwinuka, V; Malema, S S; Glynn, J R; Fine, P E

    2001-01-01

    Selection bias, particularly of controls, is common in case-control studies and may materially affect the results. Methods of control selection should be tailored both for the risk factors and disease under investigation and for the population being studied. We present here a control selection method devised for a case-control study of tuberculosis in rural Africa (Karonga, northern Malawi) that selects an age/sex frequency-matched random sample of the population, with a geographical distribution in proportion to the population density. We also present an audit of the selection process, and discuss the potential of this method in other settings.

  12. Fast selection of miRNA candidates based on large-scale pre-computed MFE sets of randomized sequences.

    Science.gov (United States)

    Warris, Sven; Boymans, Sander; Muiser, Iwe; Noback, Michiel; Krijnen, Wim; Nap, Jan-Peter

    2014-01-13

    Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings. Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition. The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification.

  13. DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues.

    Science.gov (United States)

    Ma, Xin; Guo, Jing; Sun, Xiao

    2016-01-01

    DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. However, insufficient work has been done on the prediction of DNA-binding proteins from protein sequence information. In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. The hybrid feature contains two types of novel sequence features, which reflect information about the conservation of physicochemical properties of the amino acids, and the binding propensity of DNA-binding residues and non-binding propensities of non-binding residues. The comparisons with each feature demonstrated that these two novel features contributed most to the improvement in predictive ability. Furthermore, to improve the prediction performance of the DNABP model, feature selection using the minimum redundancy maximum relevance (mRMR) method combined with incremental feature selection (IFS) was carried out during the model construction. The results showed that the DNABP model could achieve 86.90% accuracy, 83.76% sensitivity, 90.03% specificity and a Matthews correlation coefficient of 0.727. High prediction accuracy and performance comparisons with previous research suggested that DNABP could be a useful approach to identify DNA-binding proteins from sequence information. The DNABP web server system is freely available at http://www.cbi.seu.edu.cn/DNABP/.

  14. High Entropy Random Selection Protocols

    NARCIS (Netherlands)

    H. Buhrman (Harry); M. Christandl (Matthias); M. Koucky (Michal); Z. Lotker (Zvi); B. Patt-Shamir; M. Charikar; K. Jansen; O. Reingold; J. Rolim

    2007-01-01

    textabstractIn this paper, we construct protocols for two parties that do not trust each other, to generate random variables with high Shannon entropy. We improve known bounds for the trade off between the number of rounds, length of communication and the entropy of the outcome.

  15. Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection

    Directory of Open Access Journals (Sweden)

    Xin Ma

    2015-01-01

    Full Text Available The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR method, followed by incremental feature selection (IFS. We incorporated features of conjoint triad features and three novel features: binding propensity (BP, nonbinding propensity (NBP, and evolutionary information combined with physicochemical properties (EIPP. The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient. High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

  16. Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naïve Bayes.

    Directory of Open Access Journals (Sweden)

    Wangchao Lou

    Full Text Available Developing an efficient method for determination of the DNA-binding proteins, due to their vital roles in gene regulation, is becoming highly desired since it would be invaluable to advance our understanding of protein functions. In this study, we proposed a new method for the prediction of the DNA-binding proteins, by performing the feature rank using random forest and the wrapper-based feature selection using forward best-first search strategy. The features comprise information from primary sequence, predicted secondary structure, predicted relative solvent accessibility, and position specific scoring matrix. The proposed method, called DBPPred, used Gaussian naïve Bayes as the underlying classifier since it outperformed five other classifiers, including decision tree, logistic regression, k-nearest neighbor, support vector machine with polynomial kernel, and support vector machine with radial basis function. As a result, the proposed DBPPred yields the highest average accuracy of 0.791 and average MCC of 0.583 according to the five-fold cross validation with ten runs on the training benchmark dataset PDB594. Subsequently, blind tests on the independent dataset PDB186 by the proposed model trained on the entire PDB594 dataset and by other five existing methods (including iDNA-Prot, DNA-Prot, DNAbinder, DNABIND and DBD-Threader were performed, resulting in that the proposed DBPPred yielded the highest accuracy of 0.769, MCC of 0.538, and AUC of 0.790. The independent tests performed by the proposed DBPPred on completely a large non-DNA binding protein dataset and two RNA binding protein datasets also showed improved or comparable quality when compared with the relevant prediction methods. Moreover, we observed that majority of the selected features by the proposed method are statistically significantly different between the mean feature values of the DNA-binding and the non DNA-binding proteins. All of the experimental results indicate that

  17. Organic Ferroelectric-Based 1T1T Random Access Memory Cell Employing a Common Dielectric Layer Overcoming the Half-Selection Problem.

    Science.gov (United States)

    Zhao, Qiang; Wang, Hanlin; Ni, Zhenjie; Liu, Jie; Zhen, Yonggang; Zhang, Xiaotao; Jiang, Lang; Li, Rongjin; Dong, Huanli; Hu, Wenping

    2017-09-01

    Organic electronics based on poly(vinylidenefluoride/trifluoroethylene) (P(VDF-TrFE)) dielectric is facing great challenges in flexible circuits. As one indispensable part of integrated circuits, there is an urgent demand for low-cost and easy-fabrication nonvolatile memory devices. A breakthrough is made on a novel ferroelectric random access memory cell (1T1T FeRAM cell) consisting of one selection transistor and one ferroelectric memory transistor in order to overcome the half-selection problem. Unlike complicated manufacturing using multiple dielectrics, this system simplifies 1T1T FeRAM cell fabrication using one common dielectric. To achieve this goal, a strategy for semiconductor/insulator (S/I) interface modulation is put forward and applied to nonhysteretic selection transistors with high performances for driving or addressing purposes. As a result, high hole mobility of 3.81 cm 2 V -1 s -1 (average) for 2,6-diphenylanthracene (DPA) and electron mobility of 0.124 cm 2 V -1 s -1 (average) for N,N'-1H,1H-perfluorobutyl dicyanoperylenecarboxydiimide (PDI-FCN 2 ) are obtained in selection transistors. In this work, we demonstrate this technology's potential for organic ferroelectric-based pixelated memory module fabrication. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. EcmPred: Prediction of extracellular matrix proteins based on random forest with maximum relevance minimum redundancy feature selection

    KAUST Repository

    Kandaswamy, Krishna Kumar Umar

    2013-01-01

    The extracellular matrix (ECM) is a major component of tissues of multicellular organisms. It consists of secreted macromolecules, mainly polysaccharides and glycoproteins. Malfunctions of ECM proteins lead to severe disorders such as marfan syndrome, osteogenesis imperfecta, numerous chondrodysplasias, and skin diseases. In this work, we report a random forest approach, EcmPred, for the prediction of ECM proteins from protein sequences. EcmPred was trained on a dataset containing 300 ECM and 300 non-ECM and tested on a dataset containing 145 ECM and 4187 non-ECM proteins. EcmPred achieved 83% accuracy on the training and 77% on the test dataset. EcmPred predicted 15 out of 20 experimentally verified ECM proteins. By scanning the entire human proteome, we predicted novel ECM proteins validated with gene ontology and InterPro. The dataset and standalone version of the EcmPred software is available at http://www.inb.uni-luebeck.de/tools-demos/Extracellular_matrix_proteins/EcmPred. © 2012 Elsevier Ltd.

  19. 47 CFR 1.1603 - Conduct of random selection.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false Conduct of random selection. 1.1603 Section 1.1603 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1603 Conduct of random selection. The...

  20. 47 CFR 1.1602 - Designation for random selection.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false Designation for random selection. 1.1602 Section 1.1602 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1602 Designation for random selection...

  1. Random Decrement Based FRF Estimation

    DEFF Research Database (Denmark)

    Brincker, Rune; Asmussen, J. C.

    to speed and quality. The basis of the new method is the Fourier transformation of the Random Decrement functions which can be used to estimate the frequency response functions. The investigations are based on load and response measurements of a laboratory model of a 3 span bridge. By applying both methods...... that the Random Decrement technique is based on a simple controlled averaging of time segments of the load and response processes. Furthermore, the Random Decrement technique is expected to produce reliable results. The Random Decrement technique will reduce leakage, since the Fourier transformation...

  2. Random Decrement Based FRF Estimation

    DEFF Research Database (Denmark)

    Brincker, Rune; Asmussen, J. C.

    1997-01-01

    to speed and quality. The basis of the new method is the Fourier transformation of the Random Decrement functions which can be used to estimate the frequency response functions. The investigations are based on load and response measurements of a laboratory model of a 3 span bridge. By applying both methods...... that the Random Decrement technique is based on a simple controlled averaging of time segments of the load and response processes. Furthermore, the Random Decrement technique is expected to produce reliable results. The Random Decrement technique will reduce leakage, since the Fourier transformation...

  3. Local randomization in neighbor selection improves PRM roadmap quality

    KAUST Repository

    McMahon, Troy

    2012-10-01

    Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K\\'), that first computes the K\\' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K\\'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.

  4. Local randomization in neighbor selection improves PRM roadmap quality

    KAUST Repository

    McMahon, Troy; Jacobs, Sam; Boyd, Bryan; Tapia, Lydia; Amato, Nancy M.

    2012-01-01

    Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K'), that first computes the K' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.

  5. Testing, Selection, and Implementation of Random Number Generators

    National Research Council Canada - National Science Library

    Collins, Joseph C

    2008-01-01

    An exhaustive evaluation of state-of-the-art random number generators with several well-known suites of tests provides the basis for selection of suitable random number generators for use in stochastic simulations...

  6. Selection for altruism through random drift in variable size populations

    Directory of Open Access Journals (Sweden)

    Houchmandzadeh Bahram

    2012-05-01

    Full Text Available Abstract Background Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel show that altruistic behaviors can have ‘hidden’ advantages if the ‘common good’ produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. Results Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of “selfish” alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. Conclusions The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.

  7. [Intel random number generator-based true random number generator].

    Science.gov (United States)

    Huang, Feng; Shen, Hong

    2004-09-01

    To establish a true random number generator on the basis of certain Intel chips. The random numbers were acquired by programming using Microsoft Visual C++ 6.0 via register reading from the random number generator (RNG) unit of an Intel 815 chipset-based computer with Intel Security Driver (ISD). We tested the generator with 500 random numbers in NIST FIPS 140-1 and X(2) R-Squared test, and the result showed that the random number it generated satisfied the demand of independence and uniform distribution. We also compared the random numbers generated by Intel RNG-based true random number generator and those from the random number table statistically, by using the same amount of 7500 random numbers in the same value domain, which showed that the SD, SE and CV of Intel RNG-based random number generator were less than those of the random number table. The result of u test of two CVs revealed no significant difference between the two methods. Intel RNG-based random number generator can produce high-quality random numbers with good independence and uniform distribution, and solves some problems with random number table in acquisition of the random numbers.

  8. Brain Tumor Segmentation Based on Random Forest

    Directory of Open Access Journals (Sweden)

    László Lefkovits

    2016-09-01

    Full Text Available In this article we present a discriminative model for tumor detection from multimodal MR images. The main part of the model is built around the random forest (RF classifier. We created an optimization algorithm able to select the important features for reducing the dimensionality of data. This method is also used to find out the training parameters used in the learning phase. The algorithm is based on random feature properties for evaluating the importance of the variable, the evolution of learning errors and the proximities between instances. The detection performances obtained have been compared with the most recent systems, offering similar results.

  9. Random effect selection in generalised linear models

    DEFF Research Database (Denmark)

    Denwood, Matt; Houe, Hans; Forkman, Björn

    We analysed abattoir recordings of meat inspection codes with possible relevance to onfarm animal welfare in cattle. Random effects logistic regression models were used to describe individual-level data obtained from 461,406 cattle slaughtered in Denmark. Our results demonstrate that the largest...

  10. Discriminative Projection Selection Based Face Image Hashing

    Science.gov (United States)

    Karabat, Cagatay; Erdogan, Hakan

    Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

  11. A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

    Science.gov (United States)

    Thomas, D.L.; Johnson, D.; Griffith, B.

    2006-01-01

    Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a

  12. Interference-aware random beam selection for spectrum sharing systems

    KAUST Repository

    Abdallah, Mohamed M.; Sayed, Mostafa M.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

    2012-01-01

    . In this paper, we develop interference-aware random beam selection schemes that provide enhanced throughput for the secondary link under the condition that the interference observed at the primary link is within a predetermined acceptable value. For a secondary

  13. On the role of heat and mass transfer into laser processability during selective laser melting AlSi12 alloy based on a randomly packed powder-bed

    Science.gov (United States)

    Wang, Lianfeng; Yan, Biao; Guo, Lijie; Gu, Dongdong

    2018-04-01

    A newly transient mesoscopic model with a randomly packed powder-bed has been proposed to investigate the heat and mass transfer and laser process quality between neighboring tracks during selective laser melting (SLM) AlSi12 alloy by finite volume method (FVM), considering the solid/liquid phase transition, variable temperature-dependent properties and interfacial force. The results apparently revealed that both the operating temperature and resultant cooling rate were obviously elevated by increasing the laser power. Accordingly, the resultant viscosity of liquid significantly reduced under a large laser power and was characterized with a large velocity, which was prone to result in a more intensive convection within pool. In this case, the sufficient heat and mass transfer occurred at the interface between the previously fabricated tracks and currently building track, revealing a strongly sufficient spreading between the neighboring tracks and a resultant high-quality surface without obvious porosity. By contrast, the surface quality of SLM-processed components with a relatively low laser power notably weakened due to the limited and insufficient heat and mass transfer at the interface of neighboring tracks. Furthermore, the experimental surface morphologies of the top surface were correspondingly acquired and were in full accordance to the calculated results via simulation.

  14. Primitive polynomials selection method for pseudo-random number generator

    Science.gov (United States)

    Anikin, I. V.; Alnajjar, Kh

    2018-01-01

    In this paper we suggested the method for primitive polynomials selection of special type. This kind of polynomials can be efficiently used as a characteristic polynomials for linear feedback shift registers in pseudo-random number generators. The proposed method consists of two basic steps: finding minimum-cost irreducible polynomials of the desired degree and applying primitivity tests to get the primitive ones. Finally two primitive polynomials, which was found by the proposed method, used in pseudorandom number generator based on fuzzy logic (FRNG) which had been suggested before by the authors. The sequences generated by new version of FRNG have low correlation magnitude, high linear complexity, less power consumption, is more balanced and have better statistical properties.

  15. Selectivity and sparseness in randomly connected balanced networks.

    Directory of Open Access Journals (Sweden)

    Cengiz Pehlevan

    Full Text Available Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the "paradoxical" effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.

  16. The signature of positive selection at randomly chosen loci.

    OpenAIRE

    Przeworski, Molly

    2002-01-01

    In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequ...

  17. Pseudo-random number generator based on asymptotic deterministic randomness

    Science.gov (United States)

    Wang, Kai; Pei, Wenjiang; Xia, Haishan; Cheung, Yiu-ming

    2008-06-01

    A novel approach to generate the pseudorandom-bit sequence from the asymptotic deterministic randomness system is proposed in this Letter. We study the characteristic of multi-value correspondence of the asymptotic deterministic randomness constructed by the piecewise linear map and the noninvertible nonlinearity transform, and then give the discretized systems in the finite digitized state space. The statistic characteristics of the asymptotic deterministic randomness are investigated numerically, such as stationary probability density function and random-like behavior. Furthermore, we analyze the dynamics of the symbolic sequence. Both theoretical and experimental results show that the symbolic sequence of the asymptotic deterministic randomness possesses very good cryptographic properties, which improve the security of chaos based PRBGs and increase the resistance against entropy attacks and symbolic dynamics attacks.

  18. Pseudo-random number generator based on asymptotic deterministic randomness

    International Nuclear Information System (INIS)

    Wang Kai; Pei Wenjiang; Xia Haishan; Cheung Yiuming

    2008-01-01

    A novel approach to generate the pseudorandom-bit sequence from the asymptotic deterministic randomness system is proposed in this Letter. We study the characteristic of multi-value correspondence of the asymptotic deterministic randomness constructed by the piecewise linear map and the noninvertible nonlinearity transform, and then give the discretized systems in the finite digitized state space. The statistic characteristics of the asymptotic deterministic randomness are investigated numerically, such as stationary probability density function and random-like behavior. Furthermore, we analyze the dynamics of the symbolic sequence. Both theoretical and experimental results show that the symbolic sequence of the asymptotic deterministic randomness possesses very good cryptographic properties, which improve the security of chaos based PRBGs and increase the resistance against entropy attacks and symbolic dynamics attacks

  19. The reliability of randomly selected final year pharmacy students in ...

    African Journals Online (AJOL)

    Employing ANOVA, factorial experimental analysis, and the theory of error, reliability studies were conducted on the assessment of the drug product chloroquine phosphate tablets. The G–Study employed equal numbers of the factors for uniform control, and involved three analysts (randomly selected final year Pharmacy ...

  20. Interference-aware random beam selection for spectrum sharing systems

    KAUST Repository

    Abdallah, Mohamed M.

    2012-09-01

    Spectrum sharing systems have been introduced to alleviate the problem of spectrum scarcity by allowing secondary unlicensed networks to share the spectrum with primary licensed networks under acceptable interference levels to the primary users. In this paper, we develop interference-aware random beam selection schemes that provide enhanced throughput for the secondary link under the condition that the interference observed at the primary link is within a predetermined acceptable value. For a secondary transmitter equipped with multiple antennas, our schemes select a random beam, among a set of power- optimized orthogonal random beams, that maximizes the capacity of the secondary link while satisfying the interference constraint at the primary receiver for different levels of feedback information describing the interference level at the primary receiver. For the proposed schemes, we develop a statistical analysis for the signal-to-noise and interference ratio (SINR) statistics as well as the capacity of the secondary link. Finally, we present numerical results that study the effect of system parameters including number of beams and the maximum transmission power on the capacity of the secondary link attained using the proposed schemes. © 2012 IEEE.

  1. Strategyproof Peer Selection using Randomization, Partitioning, and Apportionment

    OpenAIRE

    Aziz, Haris; Lev, Omer; Mattei, Nicholas; Rosenschein, Jeffrey S.; Walsh, Toby

    2016-01-01

    Peer review, evaluation, and selection is a fundamental aspect of modern science. Funding bodies the world over employ experts to review and select the best proposals of those submitted for funding. The problem of peer selection, however, is much more general: a professional society may want to give a subset of its members awards based on the opinions of all members; an instructor for a MOOC or online course may want to crowdsource grading; or a marketing company may select ideas from group b...

  2. Random selection of items. Selection of n1 samples among N items composing a stratum

    International Nuclear Information System (INIS)

    Jaech, J.L.; Lemaire, R.J.

    1987-02-01

    STR-224 provides generalized procedures to determine required sample sizes, for instance in the course of a Physical Inventory Verification at Bulk Handling Facilities. The present report describes procedures to generate random numbers and select groups of items to be verified in a given stratum through each of the measurement methods involved in the verification. (author). 3 refs

  3. The signature of positive selection at randomly chosen loci.

    Science.gov (United States)

    Przeworski, Molly

    2002-03-01

    In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequency alleles drift to fixation and no longer contribute to polymorphism, while linkage disequilibrium is broken down by recombination. As a result, loci chosen without independent evidence of recent selection are not expected to exhibit either of these features, even if they have been affected by numerous sweeps in their genealogical history. How then can we explain the patterns in the data? One possibility is population structure, with unequal sampling from different subpopulations. Alternatively, positive selection may not operate as is commonly modeled. In particular, the rate of fixation of advantageous mutations may have increased in the recent past.

  4. Blind Measurement Selection: A Random Matrix Theory Approach

    KAUST Repository

    Elkhalil, Khalil

    2016-12-14

    This paper considers the problem of selecting a set of $k$ measurements from $n$ available sensor observations. The selected measurements should minimize a certain error function assessing the error in estimating a certain $m$ dimensional parameter vector. The exhaustive search inspecting each of the $n\\\\choose k$ possible choices would require a very high computational complexity and as such is not practical for large $n$ and $k$. Alternative methods with low complexity have recently been investigated but their main drawbacks are that 1) they require perfect knowledge of the measurement matrix and 2) they need to be applied at the pace of change of the measurement matrix. To overcome these issues, we consider the asymptotic regime in which $k$, $n$ and $m$ grow large at the same pace. Tools from random matrix theory are then used to approximate in closed-form the most important error measures that are commonly used. The asymptotic approximations are then leveraged to select properly $k$ measurements exhibiting low values for the asymptotic error measures. Two heuristic algorithms are proposed: the first one merely consists in applying the convex optimization artifice to the asymptotic error measure. The second algorithm is a low-complexity greedy algorithm that attempts to look for a sufficiently good solution for the original minimization problem. The greedy algorithm can be applied to both the exact and the asymptotic error measures and can be thus implemented in blind and channel-aware fashions. We present two potential applications where the proposed algorithms can be used, namely antenna selection for uplink transmissions in large scale multi-user systems and sensor selection for wireless sensor networks. Numerical results are also presented and sustain the efficiency of the proposed blind methods in reaching the performances of channel-aware algorithms.

  5. Optimizing Event Selection with the Random Grid Search

    Energy Technology Data Exchange (ETDEWEB)

    Bhat, Pushpalatha C. [Fermilab; Prosper, Harrison B. [Florida State U.; Sekmen, Sezen [Kyungpook Natl. U.; Stewart, Chip [Broad Inst., Cambridge

    2017-06-29

    The random grid search (RGS) is a simple, but efficient, stochastic algorithm to find optimal cuts that was developed in the context of the search for the top quark at Fermilab in the mid-1990s. The algorithm, and associated code, have been enhanced recently with the introduction of two new cut types, one of which has been successfully used in searches for supersymmetry at the Large Hadron Collider. The RGS optimization algorithm is described along with the recent developments, which are illustrated with two examples from particle physics. One explores the optimization of the selection of vector boson fusion events in the four-lepton decay mode of the Higgs boson and the other optimizes SUSY searches using boosted objects and the razor variables.

  6. Selective decontamination in pediatric liver transplants. A randomized prospective study.

    Science.gov (United States)

    Smith, S D; Jackson, R J; Hannakan, C J; Wadowsky, R M; Tzakis, A G; Rowe, M I

    1993-06-01

    Although it has been suggested that selective decontamination of the digestive tract (SDD) decreases postoperative aerobic Gram-negative and fungal infections in orthotopic liver transplantation (OLT), no controlled trials exist in pediatric patients. This prospective, randomized controlled study of 36 pediatric OLT patients examines the effect of short-term SDD on postoperative infection and digestive tract flora. Patients were randomized into two groups. The control group received perioperative parenteral antibiotics only. The SDD group received in addition polymyxin E, tobramycin, and amphotericin B enterally and by oropharyngeal swab postoperatively until oral intake was tolerated (6 +/- 4 days). Indications for operation, preoperative status, age, and intensive care unit and hospital length of stay were no different in SDD (n = 18) and control (n = 18) groups. A total of 14 Gram-negative infections (intraabdominal abscess 7, septicemia 5, pneumonia 1, urinary tract 1) developed in the 36 patients studied. Mortality was not significantly different in the two groups. However, there were significantly fewer patients with Gram-negative infections in the SDD group: 3/18 patients (11%) vs. 11/18 patients (50%) in the control group, P < 0.001. There was also significant reduction in aerobic Gram-negative flora in the stool and pharynx in patients receiving SDD. Gram-positive and anaerobic organisms were unaffected. We conclude that short-term postoperative SDD significantly reduces Gram-negative infections in pediatric OLT patients.

  7. Applications of random forest feature selection for fine-scale genetic population assignment.

    Science.gov (United States)

    Sylvester, Emma V A; Bentzen, Paul; Bradbury, Ian R; Clément, Marie; Pearce, Jon; Horne, John; Beiko, Robert G

    2018-02-01

    Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine-learning algorithms (random forest, regularized random forest and guided regularized random forest) compared with F ST ranking for selection of single nucleotide polymorphisms (SNP) for fine-scale population assignment. We applied these methods to an unpublished SNP data set for Atlantic salmon ( Salmo salar ) and a published SNP data set for Alaskan Chinook salmon ( Oncorhynchus tshawytscha ). In each species, we identified the minimum panel size required to obtain a self-assignment accuracy of at least 90% using each method to create panels of 50-700 markers Panels of SNPs identified using random forest-based methods performed up to 7.8 and 11.2 percentage points better than F ST -selected panels of similar size for the Atlantic salmon and Chinook salmon data, respectively. Self-assignment accuracy ≥90% was obtained with panels of 670 and 384 SNPs for each data set, respectively, a level of accuracy never reached for these species using F ST -selected panels. Our results demonstrate a role for machine-learning approaches in marker selection across large genomic data sets to improve assignment for management and conservation of exploited populations.

  8. Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

    International Nuclear Information System (INIS)

    Yu, Zhiyong

    2013-01-01

    This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right

  9. Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)

    2013-12-15

    This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.

  10. Pediatric selective mutism therapy: a randomized controlled trial.

    Science.gov (United States)

    Esposito, Maria; Gimigliano, Francesca; Barillari, Maria R; Precenzano, Francesco; Ruberto, Maria; Sepe, Joseph; Barillari, Umberto; Gimigliano, Raffaele; Militerni, Roberto; Messina, Giovanni; Carotenuto, Marco

    2017-10-01

    Selective mutism (SM) is a rare disease in children coded by DSM-5 as an anxiety disorder. Despite the disabling nature of the disease, there is still no specific treatment. The aims of this study were to verify the efficacy of six-month standard psychomotor treatment and the positive changes in lifestyle, in a population of children affected by SM. Randomized controlled trial registered in the European Clinical Trials Registry (EuDract 2015-001161-36). University third level Centre (Child and Adolescent Neuropsychiatry Clinic). Study population was composed by 67 children in group A (psychomotricity treatment) (35 M, mean age 7.84±1.15) and 71 children in group B (behavioral and educational counseling) (37 M, mean age 7.75±1.36). Psychomotor treatment was administered by trained child therapists in residential settings three times per week. Each child was treated for the whole period by the same therapist and all the therapists shared the same protocol. The standard psychomotor session length is of 45 minutes. At T0 and after 6 months (T1) of treatments, patients underwent a behavioral and SM severity assessment. To verify the effects of the psychomotor management, the Child Behavior Checklist questionnaire (CBCL) and Selective Mutism Questionnaire (SMQ) were administered to the parents. After 6 months of psychomotor treatment SM children showed a significant reduction among CBCL scores such as in social relations, anxious/depressed, social problems and total problems (Pselective mutism, even if further studies are needed. The present study identifies in psychomotricity a safe and efficacy therapy for pediatric selective mutism.

  11. DNA-based random number generation in security circuitry.

    Science.gov (United States)

    Gearheart, Christy M; Arazi, Benjamin; Rouchka, Eric C

    2010-06-01

    DNA-based circuit design is an area of research in which traditional silicon-based technologies are replaced by naturally occurring phenomena taken from biochemistry and molecular biology. This research focuses on further developing DNA-based methodologies to mimic digital data manipulation. While exhibiting fundamental principles, this work was done in conjunction with the vision that DNA-based circuitry, when the technology matures, will form the basis for a tamper-proof security module, revolutionizing the meaning and concept of tamper-proofing and possibly preventing it altogether based on accurate scientific observations. A paramount part of such a solution would be self-generation of random numbers. A novel prototype schema employs solid phase synthesis of oligonucleotides for random construction of DNA sequences; temporary storage and retrieval is achieved through plasmid vectors. A discussion of how to evaluate sequence randomness is included, as well as how these techniques are applied to a simulation of the random number generation circuitry. Simulation results show generated sequences successfully pass three selected NIST random number generation tests specified for security applications.

  12. Performance Evaluation of User Selection Protocols in Random Networks with Energy Harvesting and Hardware Impairments

    Directory of Open Access Journals (Sweden)

    Tan Nhat Nguyen

    2016-01-01

    Full Text Available In this paper, we evaluate performances of various user selection protocols under impact of hardware impairments. In the considered protocols, a Base Station (BS selects one of available Users (US to serve, while the remaining USs harvest the energy from the Radio Frequency (RF transmitted by the BS. We assume that all of the US randomly appear around the BS. In the Random Selection Protocol (RAN, the BS randomly selects a US to transmit the data. In the second proposed protocol, named Minimum Distance Protocol (MIND, the US that is nearest to the BS will be chosen. In the Optimal Selection Protocol (OPT, the US providing the highest channel gain between itself and the BS will be served. For performance evaluation, we derive exact and asymptotic closed-form expressions of average Outage Probability (OP over Rayleigh fading channels. We also consider average harvested energy per a US. Finally, Monte-Carlo simulations are then performed to verify the theoretical results.

  13. Random amplified polymorphic DNA based genetic characterization ...

    African Journals Online (AJOL)

    Random amplified polymorphic DNA based genetic characterization of four important species of Bamboo, found in Raigad district, Maharashtra State, India. ... Bambusoideae are differentiated from other members of the family by the presence of petiolate blades with parallel venation and stamens are three, four, six or more, ...

  14. SDE based regression for random PDEs

    KAUST Repository

    Bayer, Christian

    2016-01-01

    A simulation based method for the numerical solution of PDE with random coefficients is presented. By the Feynman-Kac formula, the solution can be represented as conditional expectation of a functional of a corresponding stochastic differential equation driven by independent noise. A time discretization of the SDE for a set of points in the domain and a subsequent Monte Carlo regression lead to an approximation of the global solution of the random PDE. We provide an initial error and complexity analysis of the proposed method along with numerical examples illustrating its behaviour.

  15. SDE based regression for random PDEs

    KAUST Repository

    Bayer, Christian

    2016-01-06

    A simulation based method for the numerical solution of PDE with random coefficients is presented. By the Feynman-Kac formula, the solution can be represented as conditional expectation of a functional of a corresponding stochastic differential equation driven by independent noise. A time discretization of the SDE for a set of points in the domain and a subsequent Monte Carlo regression lead to an approximation of the global solution of the random PDE. We provide an initial error and complexity analysis of the proposed method along with numerical examples illustrating its behaviour.

  16. From Protocols to Publications: A Study in Selective Reporting of Outcomes in Randomized Trials in Oncology

    Science.gov (United States)

    Raghav, Kanwal Pratap Singh; Mahajan, Sminil; Yao, James C.; Hobbs, Brian P.; Berry, Donald A.; Pentz, Rebecca D.; Tam, Alda; Hong, Waun K.; Ellis, Lee M.; Abbruzzese, James; Overman, Michael J.

    2015-01-01

    Purpose The decision by journals to append protocols to published reports of randomized trials was a landmark event in clinical trial reporting. However, limited information is available on how this initiative effected transparency and selective reporting of clinical trial data. Methods We analyzed 74 oncology-based randomized trials published in Journal of Clinical Oncology, the New England Journal of Medicine, and The Lancet in 2012. To ascertain integrity of reporting, we compared published reports with their respective appended protocols with regard to primary end points, nonprimary end points, unplanned end points, and unplanned analyses. Results A total of 86 primary end points were reported in 74 randomized trials; nine trials had greater than one primary end point. Nine trials (12.2%) had some discrepancy between their planned and published primary end points. A total of 579 nonprimary end points (median, seven per trial) were planned, of which 373 (64.4%; median, five per trial) were reported. A significant positive correlation was found between the number of planned and nonreported nonprimary end points (Spearman r = 0.66; P < .001). Twenty-eight studies (37.8%) reported a total of 65 unplanned end points; 52 (80.0%) of which were not identified as unplanned. Thirty-one (41.9%) and 19 (25.7%) of 74 trials reported a total of 52 unplanned analyses involving primary end points and 33 unplanned analyses involving nonprimary end points, respectively. Studies reported positive unplanned end points and unplanned analyses more frequently than negative outcomes in abstracts (unplanned end points odds ratio, 6.8; P = .002; unplanned analyses odd ratio, 8.4; P = .007). Conclusion Despite public and reviewer access to protocols, selective outcome reporting persists and is a major concern in the reporting of randomized clinical trials. To foster credible evidence-based medicine, additional initiatives are needed to minimize selective reporting. PMID:26304898

  17. Blind Measurement Selection: A Random Matrix Theory Approach

    KAUST Repository

    Elkhalil, Khalil; Kammoun, Abla; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2016-01-01

    -aware fashions. We present two potential applications where the proposed algorithms can be used, namely antenna selection for uplink transmissions in large scale multi-user systems and sensor selection for wireless sensor networks. Numerical results are also

  18. Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models

    Directory of Open Access Journals (Sweden)

    Hui Wang

    2017-10-01

    Full Text Available Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the selection of input variables, which can have significant impacts on forecasting performance. This paper presents an input variable selection method for wind speed forecasting models. The candidate input variables for various leading periods are selected and random forests (RF is employed to evaluate the importance of all variable as features. The feature subset with the best evaluation performance is selected as the optimal feature set. Then, kernel-based extreme learning machine is constructed to evaluate the performance of input variables selection based on RF. The results of the case study show that by removing the uncorrelated and redundant features, RF effectively extracts the most strongly correlated set of features from the candidate input variables. By finding the optimal feature combination to represent the original information, RF simplifies the structure of the wind speed forecasting model, shortens the training time required, and substantially improves the model’s accuracy and generalization ability, demonstrating that the input variables selected by RF are effective.

  19. Optimization of the Dutch Matrix Test by Random Selection of Sentences From a Preselected Subset

    Directory of Open Access Journals (Sweden)

    Rolph Houben

    2015-04-01

    Full Text Available Matrix tests are available for speech recognition testing in many languages. For an accurate measurement, a steep psychometric function of the speech materials is required. For existing tests, it would be beneficial if it were possible to further optimize the available materials by increasing the function’s steepness. The objective is to show if the steepness of the psychometric function of an existing matrix test can be increased by selecting a homogeneous subset of recordings with the steepest sentence-based psychometric functions. We took data from a previous multicenter evaluation of the Dutch matrix test (45 normal-hearing listeners. Based on half of the data set, first the sentences (140 out of 311 with a similar speech reception threshold and with the steepest psychometric function (≥9.7%/dB were selected. Subsequently, the steepness of the psychometric function for this selection was calculated from the remaining (unused second half of the data set. The calculation showed that the slope increased from 10.2%/dB to 13.7%/dB. The resulting subset did not allow the construction of enough balanced test lists. Therefore, the measurement procedure was changed to randomly select the sentences during testing. Random selection may interfere with a representative occurrence of phonemes. However, in our material, the median phonemic occurrence remained close to that of the original test. This finding indicates that phonemic occurrence is not a critical factor. The work highlights the possibility that existing speech tests might be improved by selecting sentences with a steep psychometric function.

  20. From Protocols to Publications: A Study in Selective Reporting of Outcomes in Randomized Trials in Oncology.

    Science.gov (United States)

    Raghav, Kanwal Pratap Singh; Mahajan, Sminil; Yao, James C; Hobbs, Brian P; Berry, Donald A; Pentz, Rebecca D; Tam, Alda; Hong, Waun K; Ellis, Lee M; Abbruzzese, James; Overman, Michael J

    2015-11-01

    The decision by journals to append protocols to published reports of randomized trials was a landmark event in clinical trial reporting. However, limited information is available on how this initiative effected transparency and selective reporting of clinical trial data. We analyzed 74 oncology-based randomized trials published in Journal of Clinical Oncology, the New England Journal of Medicine, and The Lancet in 2012. To ascertain integrity of reporting, we compared published reports with their respective appended protocols with regard to primary end points, nonprimary end points, unplanned end points, and unplanned analyses. A total of 86 primary end points were reported in 74 randomized trials; nine trials had greater than one primary end point. Nine trials (12.2%) had some discrepancy between their planned and published primary end points. A total of 579 nonprimary end points (median, seven per trial) were planned, of which 373 (64.4%; median, five per trial) were reported. A significant positive correlation was found between the number of planned and nonreported nonprimary end points (Spearman r = 0.66; P medicine, additional initiatives are needed to minimize selective reporting. © 2015 by American Society of Clinical Oncology.

  1. Variable Selection in Time Series Forecasting Using Random Forests

    Directory of Open Access Journals (Sweden)

    Hristos Tyralis

    2017-10-01

    Full Text Available Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored. Here we focus on assessing the performance of random forests in one-step forecasting using two large datasets of short time series with the aim to suggest an optimal set of predictor variables. Furthermore, we compare its performance to benchmarking methods. The first dataset is composed by 16,000 simulated time series from a variety of Autoregressive Fractionally Integrated Moving Average (ARFIMA models. The second dataset consists of 135 mean annual temperature time series. The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables. This outcome could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.

  2. Polystyrene Based Silver Selective Electrodes

    Directory of Open Access Journals (Sweden)

    Shiva Agarwal

    2002-06-01

    Full Text Available Silver(I selective sensors have been fabricated from polystyrene matrix membranes containing macrocycle, Me6(14 diene.2HClO4 as ionophore. Best performance was exhibited by the membrane having a composition macrocycle : Polystyrene in the ratio 15:1. This membrane worked well over a wide concentration range 5.0×10-6–1.0×10-1M of Ag+ with a near-Nernstian slope of 53.0 ± 1.0 mV per decade of Ag+ activity. The response time of the sensor is <15 s and the membrane can be used over a period of four months with good reproducibility. The proposed electrode works well in a wide pH range 2.5-9.0 and demonstrates good discriminating power over a number of mono-, di-, and trivalent cations. The sensor has also been used as an indicator electrode in the potentiometric titration of silver(II ions against NaCl solution. The sensor can also be used in non-aqueous medium with no significant change in the value of slope or working concentration range for the estimation of Ag+ in solution having up to 25% (v/v nonaqueous fraction.

  3. On theoretical models of gene expression evolution with random genetic drift and natural selection.

    Directory of Open Access Journals (Sweden)

    Osamu Ogasawara

    2009-11-01

    Full Text Available The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference.In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1 our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2 cytological constraints can be explicitly formulated to describe long-term evolution; (3 the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances.The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.

  4. Random-walk simulation of selected aspects of dissipative collisions

    International Nuclear Information System (INIS)

    Toeke, J.; Gobbi, A.; Matulewicz, T.

    1984-11-01

    Internuclear thermal equilibrium effects and shell structure effects in dissipative collisions are studied numerically within the framework of the model of stochastic exchanges by applying the random-walk technique. Effective blocking of the drift through the mass flux induced by the temperature difference, while leaving the variances of the mass distributions unaltered is found possible, provided an internuclear potential barrier is present. Presence of the shell structure is found to lead to characteristic correlations between the consecutive exchanges. Experimental evidence for the predicted effects is discussed. (orig.)

  5. Application of random effects to the study of resource selection by animals.

    Science.gov (United States)

    Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L

    2006-07-01

    1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions

  6. Interference-aware random beam selection schemes for spectrum sharing systems

    KAUST Repository

    Abdallah, Mohamed; Qaraqe, Khalid; Alouini, Mohamed-Slim

    2012-01-01

    users. In this work, we develop interference-aware random beam selection schemes that provide enhanced performance for the secondary network under the condition that the interference observed by the receivers of the primary network is below a

  7. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

    Science.gov (United States)

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...

  8. Analysis and applications of a frequency selective surface via a random distribution method

    International Nuclear Information System (INIS)

    Xie Shao-Yi; Huang Jing-Jian; Yuan Nai-Chang; Liu Li-Guo

    2014-01-01

    A novel frequency selective surface (FSS) for reducing radar cross section (RCS) is proposed in this paper. This FSS is based on the random distribution method, so it can be called random surface. In this paper, the stacked patches serving as periodic elements are employed for RCS reduction. Previous work has demonstrated the efficiency by utilizing the microstrip patches, especially for the reflectarray. First, the relevant theory of the method is described. Then a sample of a three-layer variable-sized stacked patch random surface with a dimension of 260 mm×260 mm is simulated, fabricated, and measured in order to demonstrate the validity of the proposed design. For the normal incidence, the 8-dB RCS reduction can be achieved both by the simulation and the measurement in 8 GHz–13 GHz. The oblique incidence of 30° is also investigated, in which the 7-dB RCS reduction can be obtained in a frequency range of 8 GHz–14 GHz. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

  9. The mathematics of random mutation and natural selection for multiple simultaneous selection pressures and the evolution of antimicrobial drug resistance.

    Science.gov (United States)

    Kleinman, Alan

    2016-12-20

    The random mutation and natural selection phenomenon act in a mathematically predictable behavior, which when understood leads to approaches to reduce and prevent the failure of the use of these selection pressures when treating infections and cancers. The underlying principle to impair the random mutation and natural selection phenomenon is to use combination therapy, which forces the population to evolve to multiple selection pressures simultaneously that invoke the multiplication rule of probabilities simultaneously as well. Recently, it has been seen that combination therapy for the treatment of malaria has failed to prevent the emergence of drug-resistant variants. Using this empirical example and the principles of probability theory, the derivation of the equations describing this treatment failure is carried out. These equations give guidance as to how to use combination therapy for the treatment of cancers and infectious diseases and prevent the emergence of drug resistance. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  10. Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa

    Directory of Open Access Journals (Sweden)

    Thandi Kapwata

    2016-11-01

    Full Text Available Malaria is an environmentally driven disease. In order to quantify the spatial variability of malaria transmission, it is imperative to understand the interactions between environmental variables and malaria epidemiology at a micro-geographic level using a novel statistical approach. The random forest (RF statistical learning method, a relatively new variable-importance ranking method, measures the variable importance of potentially influential parameters through the percent increase of the mean squared error. As this value increases, so does the relative importance of the associated variable. The principal aim of this study was to create predictive malaria maps generated using the selected variables based on the RF algorithm in the Ehlanzeni District of Mpumalanga Province, South Africa. From the seven environmental variables used [temperature, lag temperature, rainfall, lag rainfall, humidity, altitude, and the normalized difference vegetation index (NDVI], altitude was identified as the most influential predictor variable due its high selection frequency. It was selected as the top predictor for 4 out of 12 months of the year, followed by NDVI, temperature and lag rainfall, which were each selected twice. The combination of climatic variables that produced the highest prediction accuracy was altitude, NDVI, and temperature. This suggests that these three variables have high predictive capabilities in relation to malaria transmission. Furthermore, it is anticipated that the predictive maps generated from predictions made by the RF algorithm could be used to monitor the progression of malaria and assist in intervention and prevention efforts with respect to malaria.

  11. Distribution of orientation selectivity in recurrent networks of spiking neurons with different random topologies.

    Science.gov (United States)

    Sadeh, Sadra; Rotter, Stefan

    2014-01-01

    Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity.

  12. Acceptance sampling using judgmental and randomly selected samples

    Energy Technology Data Exchange (ETDEWEB)

    Sego, Landon H.; Shulman, Stanley A.; Anderson, Kevin K.; Wilson, John E.; Pulsipher, Brent A.; Sieber, W. Karl

    2010-09-01

    We present a Bayesian model for acceptance sampling where the population consists of two groups, each with different levels of risk of containing unacceptable items. Expert opinion, or judgment, may be required to distinguish between the high and low-risk groups. Hence, high-risk items are likely to be identifed (and sampled) using expert judgment, while the remaining low-risk items are sampled randomly. We focus on the situation where all observed samples must be acceptable. Consequently, the objective of the statistical inference is to quantify the probability that a large percentage of the unsampled items in the population are also acceptable. We demonstrate that traditional (frequentist) acceptance sampling and simpler Bayesian formulations of the problem are essentially special cases of the proposed model. We explore the properties of the model in detail, and discuss the conditions necessary to ensure that required samples sizes are non-decreasing function of the population size. The method is applicable to a variety of acceptance sampling problems, and, in particular, to environmental sampling where the objective is to demonstrate the safety of reoccupying a remediated facility that has been contaminated with a lethal agent.

  13. Treatment selection in a randomized clinical trial via covariate-specific treatment effect curves.

    Science.gov (United States)

    Ma, Yunbei; Zhou, Xiao-Hua

    2017-02-01

    For time-to-event data in a randomized clinical trial, we proposed two new methods for selecting an optimal treatment for a patient based on the covariate-specific treatment effect curve, which is used to represent the clinical utility of a predictive biomarker. To select an optimal treatment for a patient with a specific biomarker value, we proposed pointwise confidence intervals for each covariate-specific treatment effect curve and the difference between covariate-specific treatment effect curves of two treatments. Furthermore, to select an optimal treatment for a future biomarker-defined subpopulation of patients, we proposed confidence bands for each covariate-specific treatment effect curve and the difference between each pair of covariate-specific treatment effect curve over a fixed interval of biomarker values. We constructed the confidence bands based on a resampling technique. We also conducted simulation studies to evaluate finite-sample properties of the proposed estimation methods. Finally, we illustrated the application of the proposed method in a real-world data set.

  14. 40 CFR 761.308 - Sample selection by random number generation on any two-dimensional square grid.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sample selection by random number... § 761.79(b)(3) § 761.308 Sample selection by random number generation on any two-dimensional square... area created in accordance with paragraph (a) of this section, select two random numbers: one each for...

  15. A Rewritable, Random-Access DNA-Based Storage System.

    Science.gov (United States)

    Yazdi, S M Hossein Tabatabaei; Yuan, Yongbo; Ma, Jian; Zhao, Huimin; Milenkovic, Olgica

    2015-09-18

    We describe the first DNA-based storage architecture that enables random access to data blocks and rewriting of information stored at arbitrary locations within the blocks. The newly developed architecture overcomes drawbacks of existing read-only methods that require decoding the whole file in order to read one data fragment. Our system is based on new constrained coding techniques and accompanying DNA editing methods that ensure data reliability, specificity and sensitivity of access, and at the same time provide exceptionally high data storage capacity. As a proof of concept, we encoded parts of the Wikipedia pages of six universities in the USA, and selected and edited parts of the text written in DNA corresponding to three of these schools. The results suggest that DNA is a versatile media suitable for both ultrahigh density archival and rewritable storage applications.

  16. An explicit semantic relatedness measure based on random walk

    Directory of Open Access Journals (Sweden)

    HU Sihui

    2016-10-01

    Full Text Available The semantic relatedness calculation of open domain knowledge network is a significant issue.In this paper,pheromone strategy is drawn from the thought of ant colony algorithm and is integrated into the random walk which is taken as the basic framework of calculating the semantic relatedness degree.The pheromone distribution is taken as a criterion of determining the tightness degree of semantic relatedness.A method of calculating semantic relatedness degree based on random walk is proposed and the exploration process of calculating the semantic relatedness degree is presented in a dominant way.The method mainly contains Path Select Model(PSM and Semantic Relatedness Computing Model(SRCM.PSM is used to simulate the path selection of ants and pheromone release.SRCM is used to calculate the semantic relatedness by utilizing the information returned by ants.The result indicates that the method could complete semantic relatedness calculation in linear complexity and extend the feasible strategy of semantic relatedness calculation.

  17. Supplier selection an MCDA-based approach

    CERN Document Server

    Mukherjee, Krishnendu

    2017-01-01

    The purpose of this book is to present a comprehensive review of the latest research and development trends at the international level for modeling and optimization of the supplier selection process for different industrial sectors. It is targeted to serve two audiences: the MBA and PhD student interested in procurement, and the practitioner who wishes to gain a deeper understanding of procurement analysis with multi-criteria based decision tools to avoid upstream risks to get better supply chain visibility. The book is expected to serve as a ready reference for supplier selection criteria and various multi-criteria based supplier’s evaluation methods for forward, reverse and mass customized supply chain. This book encompasses several criteria, methods for supplier selection in a systematic way based on extensive literature review from 1998 to 2012. It provides several case studies and some useful links which can serve as a starting point for interested researchers. In the appendix several computer code wri...

  18. Norm based Threshold Selection for Fault Detectors

    DEFF Research Database (Denmark)

    Rank, Mike Lind; Niemann, Henrik

    1998-01-01

    The design of fault detectors for fault detection and isolation (FDI) in dynamic systems is considered from a norm based point of view. An analysis of norm based threshold selection is given based on different formulations of FDI problems. Both the nominal FDI problem as well as the uncertain FDI...... problem are considered. Based on this analysis, a performance index based on norms of the involved transfer functions is given. The performance index allows us also to optimize the structure of the fault detection filter directly...

  19. Personnel Selection Based on Fuzzy Methods

    Directory of Open Access Journals (Sweden)

    Lourdes Cañós

    2011-03-01

    Full Text Available The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate. Our method is based on the Hamming distance and a Matching Level Index. The algorithms, implemented in the software StaffDesigner, allow us to rank the candidates, even when the competences of the ideal candidate have been evaluated only in part. Our approach is applied in a numerical example.

  20. Day-ahead load forecast using random forest and expert input selection

    International Nuclear Information System (INIS)

    Lahouar, A.; Ben Hadj Slama, J.

    2015-01-01

    Highlights: • A model based on random forests for short term load forecast is proposed. • An expert feature selection is added to refine inputs. • Special attention is paid to customers behavior, load profile and special holidays. • The model is flexible and able to handle complex load signal. • A technical comparison is performed to assess the forecast accuracy. - Abstract: The electrical load forecast is getting more and more important in recent years due to the electricity market deregulation and integration of renewable resources. To overcome the incoming challenges and ensure accurate power prediction for different time horizons, sophisticated intelligent methods are elaborated. Utilization of intelligent forecast algorithms is among main characteristics of smart grids, and is an efficient tool to face uncertainty. Several crucial tasks of power operators such as load dispatch rely on the short term forecast, thus it should be as accurate as possible. To this end, this paper proposes a short term load predictor, able to forecast the next 24 h of load. Using random forest, characterized by immunity to parameter variations and internal cross validation, the model is constructed following an online learning process. The inputs are refined by expert feature selection using a set of if–then rules, in order to include the own user specifications about the country weather or market, and to generalize the forecast ability. The proposed approach is tested through a real historical set from the Tunisian Power Company, and the simulation shows accurate and satisfactory results for one day in advance, with an average error exceeding rarely 2.3%. The model is validated for regular working days and weekends, and special attention is paid to moving holidays, following non Gregorian calendar

  1. Automatic learning-based beam angle selection for thoracic IMRT

    International Nuclear Information System (INIS)

    Amit, Guy; Marshall, Andrea; Purdie, Thomas G.; Jaffray, David A.; Levinshtein, Alex; Hope, Andrew J.; Lindsay, Patricia; Pekar, Vladimir

    2015-01-01

    Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationally efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume

  2. Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti.

    Science.gov (United States)

    Wampler, Peter J; Rediske, Richard R; Molla, Azizur R

    2013-01-18

    A remote sensing technique was developed which combines a Geographic Information System (GIS); Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner. The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. The development and use of a remote sensing method was essential to the selection and location of random households. A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. 16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. A total of 55 households were located using this method during the 10 days of fieldwork in May and June of 2012. The method used to generate and field locate random homes for surveys and water sampling was an effective means of selecting random households in a rural environment lacking geolocation infrastructure. The success rate for locating households using a handheld GPS was excellent and only rarely was local knowledge required to identify and locate households. This

  3. Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti

    Directory of Open Access Journals (Sweden)

    Wampler Peter J

    2013-01-01

    Full Text Available Abstract Background A remote sensing technique was developed which combines a Geographic Information System (GIS; Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner. Methods The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. The development and use of a remote sensing method was essential to the selection and location of random households. Results A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. 16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. A total of 55 households were located using this method during the 10 days of fieldwork in May and June of 2012. Conclusions The method used to generate and field locate random homes for surveys and water sampling was an effective means of selecting random households in a rural environment lacking geolocation infrastructure. The success rate for locating households using a handheld GPS was excellent and only

  4. A cluster-based randomized controlled trial promoting community participation in arsenic mitigation efforts in Bangladesh

    OpenAIRE

    George, Christine Marie; van Geen, Alexander; Slavkovich, Vesna; Singha, Ashit; Levy, Diane; Islam, Tariqul; Ahmed, Kazi Matin; Moon-Howard, Joyce; Tarozzi, Alessandro; Liu, Xinhua; Factor-Litvak, Pam; Graziano, Joseph

    2012-01-01

    Abstract Objective To reduce arsenic (As) exposure, we evaluated the effectiveness of training community members to perform water arsenic (WAs) testing and provide As education compared to sending representatives from outside communities to conduct these tasks. Methods We conducted a cluster based randomized controlled trial of 20 villages in Singair, Bangladesh. Fifty eligible respondents were randomly selected in each village. In 10 villages, a community member provided As education and WAs...

  5. Feature Selection Based on Mutual Correlation

    Czech Academy of Sciences Publication Activity Database

    Haindl, Michal; Somol, Petr; Ververidis, D.; Kotropoulos, C.

    2006-01-01

    Roč. 19, č. 4225 (2006), s. 569-577 ISSN 0302-9743. [Iberoamerican Congress on Pattern Recognition. CIARP 2006 /11./. Cancun, 14.11.2006-17.11.2006] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : feature selection Subject RIV: BD - Theory of Information Impact factor: 0.402, year: 2005 http://library.utia.cas.cz/separaty/historie/haindl-feature selection based on mutual correlation.pdf

  6. Non-random mating for selection with restricted rates of inbreeding and overlapping generations

    NARCIS (Netherlands)

    Sonesson, A.K.; Meuwissen, T.H.E.

    2002-01-01

    Minimum coancestry mating with a maximum of one offspring per mating pair (MC1) is compared with random mating schemes for populations with overlapping generations. Optimum contribution selection is used, whereby $\\\\\\\\Delta F$ is restricted. For schemes with $\\\\\\\\Delta F$ restricted to 0.25% per

  7. 40 CFR 761.306 - Sampling 1 meter square surfaces by random selection of halves.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sampling 1 meter square surfaces by...(b)(3) § 761.306 Sampling 1 meter square surfaces by random selection of halves. (a) Divide each 1 meter square portion where it is necessary to collect a surface wipe test sample into two equal (or as...

  8. Modified random hinge transport mechanics and multiple scattering step-size selection in EGS5

    International Nuclear Information System (INIS)

    Wilderman, S.J.; Bielajew, A.F.

    2005-01-01

    The new transport mechanics in EGS5 allows for significantly longer electron transport step sizes and hence shorter computation times than required for identical problems in EGS4. But as with all Monte Carlo electron transport algorithms, certain classes of problems exhibit step-size dependencies even when operating within recommended ranges, sometimes making selection of step-sizes a daunting task for novice users. Further contributing to this problem, because of the decoupling of multiple scattering and continuous energy loss in the dual random hinge transport mechanics of EGS5, there are two independent step sizes in EGS5, one for multiple scattering and one for continuous energy loss, each of which influences speed and accuracy in a different manner. Further, whereas EGS4 used a single value of fractional energy loss (ESTEPE) to determine step sizes at all energies, to increase performance by decreasing the amount of effort expended simulating lower energy particles, EGS5 permits the fractional energy loss values which are used to determine both the multiple scattering and continuous energy loss step sizes to vary with energy. This results in requiring the user to specify four fractional energy loss values when optimizing computations for speed. Thus, in order to simplify step-size selection and to mitigate step-size dependencies, a method has been devised to automatically optimize step-size selection based on a single material dependent input related to the size of problem tally region. In this paper we discuss the new transport mechanics in EGS5 and describe the automatic step-size optimization algorithm. (author)

  9. Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

    Science.gov (United States)

    Lindsay, Grace W.

    2017-01-01

    Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (

  10. Pseudo-random bit generator based on Chebyshev map

    Science.gov (United States)

    Stoyanov, B. P.

    2013-10-01

    In this paper, we study a pseudo-random bit generator based on two Chebyshev polynomial maps. The novel derivative algorithm shows perfect statistical properties established by number of statistical tests.

  11. Random number generation based on digital differential chaos

    KAUST Repository

    Zidan, Mohammed A.; Radwan, Ahmed G.; Salama, Khaled N.

    2012-01-01

    In this paper, we present a fully digital differential chaos based random number generator. The output of the digital circuit is proved to be chaotic by calculating the output time series maximum Lyapunov exponent. We introduce a new post processing

  12. Simulated Performance Evaluation of a Selective Tracker Through Random Scenario Generation

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar

    2006-01-01

    performance assessment. Therefore, a random target motion scenario is adopted. Its implementation in particular for testing the proposed selective track splitting algorithm using Kalman filters is investigated through a number of performance parameters which gives the activity profile of the tracking scenario......  The paper presents a simulation study on the performance of a target tracker using selective track splitting filter algorithm through a random scenario implemented on a digital signal processor.  In a typical track splitting filter all the observation which fall inside a likelihood ellipse...... are used for update, however, in our proposed selective track splitting filter less number of observations are used for track update.  Much of the previous performance work [1] has been done on specific (deterministic) scenarios. One of the reasons for considering the specific scenarios, which were...

  13. Rule-based versus probabilistic selection for active surveillance using three definitions of insignificant prostate cancer

    NARCIS (Netherlands)

    L.D.F. Venderbos (Lionne); M.J. Roobol-Bouts (Monique); C.H. Bangma (Chris); R.C.N. van den Bergh (Roderick); L.P. Bokhorst (Leonard); D. Nieboer (Daan); Godtman, R; J. Hugosson (Jonas); van der Kwast, T; E.W. Steyerberg (Ewout)

    2016-01-01

    textabstractTo study whether probabilistic selection by the use of a nomogram could improve patient selection for active surveillance (AS) compared to the various sets of rule-based AS inclusion criteria currently used. We studied Dutch and Swedish patients participating in the European Randomized

  14. Automatic Recognition of Chinese Personal Name Using Conditional Random Fields and Knowledge Base

    Directory of Open Access Journals (Sweden)

    Chuan Gu

    2015-01-01

    Full Text Available According to the features of Chinese personal name, we present an approach for Chinese personal name recognition based on conditional random fields (CRF and knowledge base in this paper. The method builds multiple features of CRF model by adopting Chinese character as processing unit, selects useful features based on selection algorithm of knowledge base and incremental feature template, and finally implements the automatic recognition of Chinese personal name from Chinese document. The experimental results on open real corpus demonstrated the effectiveness of our method and obtained high accuracy rate and high recall rate of recognition.

  15. Ultrafast quantum random number generation based on quantum phase fluctuations.

    Science.gov (United States)

    Xu, Feihu; Qi, Bing; Ma, Xiongfeng; Xu, He; Zheng, Haoxuan; Lo, Hoi-Kwong

    2012-05-21

    A quantum random number generator (QRNG) can generate true randomness by exploiting the fundamental indeterminism of quantum mechanics. Most approaches to QRNG employ single-photon detection technologies and are limited in speed. Here, we experimentally demonstrate an ultrafast QRNG at a rate over 6 Gbits/s based on the quantum phase fluctuations of a laser operating near threshold. Moreover, we consider a potential adversary who has partial knowledge on the raw data and discuss how one can rigorously remove such partial knowledge with postprocessing. We quantify the quantum randomness through min-entropy by modeling our system and employ two randomness extractors--Trevisan's extractor and Toeplitz-hashing--to distill the randomness, which is information-theoretically provable. The simplicity and high-speed of our experimental setup show the feasibility of a robust, low-cost, high-speed QRNG.

  16. Experimental nonlocality-based randomness generation with nonprojective measurements

    Science.gov (United States)

    Gómez, S.; Mattar, A.; Gómez, E. S.; Cavalcanti, D.; Farías, O. Jiménez; Acín, A.; Lima, G.

    2018-04-01

    We report on an optical setup generating more than one bit of randomness from one entangled bit (i.e., a maximally entangled state of two qubits). The amount of randomness is certified through the observation of Bell nonlocal correlations. To attain this result we implemented a high-purity entanglement source and a nonprojective three-outcome measurement. Our implementation achieves a gain of 27% of randomness as compared with the standard methods using projective measurements. Additionally, we estimate the amount of randomness certified in a one-sided device-independent scenario, through the observation of Einstein-Podolsky-Rosen steering. Our results prove that nonprojective quantum measurements allow extending the limits for nonlocality-based certified randomness generation using current technology.

  17. Characterization of Pharmacologic and Pharmacokinetic Properties of CCX168, a Potent and Selective Orally Administered Complement 5a Receptor Inhibitor, Based on Preclinical Evaluation and Randomized Phase 1 Clinical Study.

    Science.gov (United States)

    Bekker, Pirow; Dairaghi, Daniel; Seitz, Lisa; Leleti, Manmohan; Wang, Yu; Ertl, Linda; Baumgart, Trageen; Shugarts, Sarah; Lohr, Lisa; Dang, Ton; Miao, Shichang; Zeng, Yibin; Fan, Pingchen; Zhang, Penglie; Johnson, Daniel; Powers, Jay; Jaen, Juan; Charo, Israel; Schall, Thomas J

    2016-01-01

    The complement 5a receptor has been an attractive therapeutic target for many autoimmune and inflammatory disorders. However, development of a selective and potent C5aR antagonist has been challenging. Here we describe the characterization of CCX168 (avacopan), an orally administered selective and potent C5aR inhibitor. CCX168 blocked the C5a binding, C5a-mediated migration, calcium mobilization, and CD11b upregulation in U937 cells as well as in freshly isolated human neutrophils. CCX168 retains high potency when present in human blood. A transgenic human C5aR knock-in mouse model allowed comparison of the in vitro and in vivo efficacy of the molecule. CCX168 effectively blocked migration in in vitro and ex vivo chemotaxis assays, and it blocked the C5a-mediated neutrophil vascular endothelial margination. CCX168 was effective in migration and neutrophil margination assays in cynomolgus monkeys. This thorough in vitro and preclinical characterization enabled progression of CCX168 into the clinic and testing of its safety, tolerability, pharmacokinetic, and pharmacodynamic profiles in a Phase 1 clinical trial in 48 healthy volunteers. CCX168 was shown to be well tolerated across a broad dose range (1 to 100 mg) and it showed dose-dependent pharmacokinetics. An oral dose of 30 mg CCX168 given twice daily blocked the C5a-induced upregulation of CD11b in circulating neutrophils by 94% or greater throughout the entire day, demonstrating essentially complete target coverage. This dose regimen is being tested in clinical trials in patients with anti-neutrophil cytoplasmic antibody-associated vasculitis. Trial Registration ISRCTN registry with trial ID ISRCTN13564773.

  18. Characterization of Pharmacologic and Pharmacokinetic Properties of CCX168, a Potent and Selective Orally Administered Complement 5a Receptor Inhibitor, Based on Preclinical Evaluation and Randomized Phase 1 Clinical Study.

    Directory of Open Access Journals (Sweden)

    Pirow Bekker

    Full Text Available The complement 5a receptor has been an attractive therapeutic target for many autoimmune and inflammatory disorders. However, development of a selective and potent C5aR antagonist has been challenging. Here we describe the characterization of CCX168 (avacopan, an orally administered selective and potent C5aR inhibitor. CCX168 blocked the C5a binding, C5a-mediated migration, calcium mobilization, and CD11b upregulation in U937 cells as well as in freshly isolated human neutrophils. CCX168 retains high potency when present in human blood. A transgenic human C5aR knock-in mouse model allowed comparison of the in vitro and in vivo efficacy of the molecule. CCX168 effectively blocked migration in in vitro and ex vivo chemotaxis assays, and it blocked the C5a-mediated neutrophil vascular endothelial margination. CCX168 was effective in migration and neutrophil margination assays in cynomolgus monkeys. This thorough in vitro and preclinical characterization enabled progression of CCX168 into the clinic and testing of its safety, tolerability, pharmacokinetic, and pharmacodynamic profiles in a Phase 1 clinical trial in 48 healthy volunteers. CCX168 was shown to be well tolerated across a broad dose range (1 to 100 mg and it showed dose-dependent pharmacokinetics. An oral dose of 30 mg CCX168 given twice daily blocked the C5a-induced upregulation of CD11b in circulating neutrophils by 94% or greater throughout the entire day, demonstrating essentially complete target coverage. This dose regimen is being tested in clinical trials in patients with anti-neutrophil cytoplasmic antibody-associated vasculitis. Trial Registration ISRCTN registry with trial ID ISRCTN13564773.

  19. Emergence of multilevel selection in the prisoner's dilemma game on coevolving random networks

    International Nuclear Information System (INIS)

    Szolnoki, Attila; Perc, Matjaz

    2009-01-01

    We study the evolution of cooperation in the prisoner's dilemma game, whereby a coevolutionary rule is introduced that molds the random topology of the interaction network in two ways. First, existing links are deleted whenever a player adopts a new strategy or its degree exceeds a threshold value; second, new links are added randomly after a given number of game iterations. These coevolutionary processes correspond to the generic formation of new links and deletion of existing links that, especially in human societies, appear frequently as a consequence of ongoing socialization, change of lifestyle or death. Due to the counteraction of deletions and additions of links the initial heterogeneity of the interaction network is qualitatively preserved, and thus cannot be held responsible for the observed promotion of cooperation. Indeed, the coevolutionary rule evokes the spontaneous emergence of a powerful multilevel selection mechanism, which despite the sustained random topology of the evolving network, maintains cooperation across the whole span of defection temptation values.

  20. Pseudo-random bit generator based on lag time series

    Science.gov (United States)

    García-Martínez, M.; Campos-Cantón, E.

    2014-12-01

    In this paper, we present a pseudo-random bit generator (PRBG) based on two lag time series of the logistic map using positive and negative values in the bifurcation parameter. In order to hidden the map used to build the pseudo-random series we have used a delay in the generation of time series. These new series when they are mapped xn against xn+1 present a cloud of points unrelated to the logistic map. Finally, the pseudo-random sequences have been tested with the suite of NIST giving satisfactory results for use in stream ciphers.

  1. Topology-selective jamming of fully-connected, code-division random-access networks

    Science.gov (United States)

    Polydoros, Andreas; Cheng, Unjeng

    1990-01-01

    The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.

  2. Random drift versus selection in academic vocabulary: an evolutionary analysis of published keywords.

    Directory of Open Access Journals (Sweden)

    R Alexander Bentley

    Full Text Available The evolution of vocabulary in academic publishing is characterized via keyword frequencies recorded in the ISI Web of Science citations database. In four distinct case-studies, evolutionary analysis of keyword frequency change through time is compared to a model of random copying used as the null hypothesis, such that selection may be identified against it. The case studies from the physical sciences indicate greater selection in keyword choice than in the social sciences. Similar evolutionary analyses can be applied to a wide range of phenomena; wherever the popularity of multiple items through time has been recorded, as with web searches, or sales of popular music and books, for example.

  3. Random drift versus selection in academic vocabulary: an evolutionary analysis of published keywords.

    Science.gov (United States)

    Bentley, R Alexander

    2008-08-27

    The evolution of vocabulary in academic publishing is characterized via keyword frequencies recorded in the ISI Web of Science citations database. In four distinct case-studies, evolutionary analysis of keyword frequency change through time is compared to a model of random copying used as the null hypothesis, such that selection may be identified against it. The case studies from the physical sciences indicate greater selection in keyword choice than in the social sciences. Similar evolutionary analyses can be applied to a wide range of phenomena; wherever the popularity of multiple items through time has been recorded, as with web searches, or sales of popular music and books, for example.

  4. The Reliability of Randomly Generated Math Curriculum-Based Measurements

    Science.gov (United States)

    Strait, Gerald G.; Smith, Bradley H.; Pender, Carolyn; Malone, Patrick S.; Roberts, Jarod; Hall, John D.

    2015-01-01

    "Curriculum-Based Measurement" (CBM) is a direct method of academic assessment used to screen and evaluate students' skills and monitor their responses to academic instruction and intervention. Interventioncentral.org offers a math worksheet generator at no cost that creates randomly generated "math curriculum-based measures"…

  5. High-Tg Polynorbornene-Based Block and Random Copolymers for Butanol Pervaporation Membranes

    Science.gov (United States)

    Register, Richard A.; Kim, Dong-Gyun; Takigawa, Tamami; Kashino, Tomomasa; Burtovyy, Oleksandr; Bell, Andrew

    Vinyl addition polymers of substituted norbornene (NB) monomers possess desirably high glass transition temperatures (Tg); however, until very recently, the lack of an applicable living polymerization chemistry has precluded the synthesis of such polymers with controlled architecture, or copolymers with controlled sequence distribution. We have recently synthesized block and random copolymers of NB monomers bearing hydroxyhexafluoroisopropyl and n-butyl substituents (HFANB and BuNB) via living vinyl addition polymerization with Pd-based catalysts. Both series of polymers were cast into the selective skin layers of thin film composite (TFC) membranes, and these organophilic membranes investigated for the isolation of n-butanol from dilute aqueous solution (model fermentation broth) via pervaporation. The block copolymers show well-defined microphase-separated morphologies, both in bulk and as the selective skin layers on TFC membranes, while the random copolymers are homogeneous. Both block and random vinyl addition copolymers are effective as n-butanol pervaporation membranes, with the block copolymers showing a better flux-selectivity balance. While polyHFANB has much higher permeability and n-butanol selectivity than polyBuNB, incorporating BuNB units into the polymer (in either a block or random sequence) limits the swelling of the polyHFANB and thereby improves the n-butanol pervaporation selectivity.

  6. Risk-based audit selection of dairy farms.

    Science.gov (United States)

    van Asseldonk, M A P M; Velthuis, A G J

    2014-02-01

    Dairy farms are audited in the Netherlands on numerous process standards. Each farm is audited once every 2 years. Increasing demands for cost-effectiveness in farm audits can be met by introducing risk-based principles. This implies targeting subpopulations with a higher risk of poor process standards. To select farms for an audit that present higher risks, a statistical analysis was conducted to test the relationship between the outcome of farm audits and bulk milk laboratory results before the audit. The analysis comprised 28,358 farm audits and all conducted laboratory tests of bulk milk samples 12 mo before the audit. The overall outcome of each farm audit was classified as approved or rejected. Laboratory results included somatic cell count (SCC), total bacterial count (TBC), antimicrobial drug residues (ADR), level of butyric acid spores (BAB), freezing point depression (FPD), level of free fatty acids (FFA), and cleanliness of the milk (CLN). The bulk milk laboratory results were significantly related to audit outcomes. Rejected audits are likely to occur on dairy farms with higher mean levels of SCC, TBC, ADR, and BAB. Moreover, in a multivariable model, maxima for TBC, SCC, and FPD as well as standard deviations for TBC and FPD are risk factors for negative audit outcomes. The efficiency curve of a risk-based selection approach, on the basis of the derived regression results, dominated the current random selection approach. To capture 25, 50, or 75% of the population with poor process standards (i.e., audit outcome of rejected), respectively, only 8, 20, or 47% of the population had to be sampled based on a risk-based selection approach. Milk quality information can thus be used to preselect high-risk farms to be audited more frequently. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  7. Comparative Evaluations of Randomly Selected Four Point-of-Care Glucometer Devices in Addis Ababa, Ethiopia.

    Science.gov (United States)

    Wolde, Mistire; Tarekegn, Getahun; Kebede, Tedla

    2018-05-01

    Point-of-care glucometer (PoCG) devices play a significant role in self-monitoring of the blood sugar level, particularly in the follow-up of high blood sugar therapeutic response. The aim of this study was to evaluate blood glucose test results performed with four randomly selected glucometers on diabetes and control subjects versus standard wet chemistry (hexokinase) methods in Addis Ababa, Ethiopia. A prospective cross-sectional study was conducted on randomly selected 200 study participants (100 participants with diabetes and 100 healthy controls). Four randomly selected PoCG devices (CareSens N, DIAVUE Prudential, On Call Extra, i-QARE DS-W) were evaluated against hexokinase method and ISO 15197:2003 and ISO 15197:2013 standards. The minimum and maximum blood sugar values were recorded by CareSens N (21 mg/dl) and hexokinase method (498.8 mg/dl), respectively. The mean sugar values of all PoCG devices except On Call Extra showed significant differences compared with the reference hexokinase method. Meanwhile, all four PoCG devices had strong positive relationship (>80%) with the reference method (hexokinase). On the other hand, none of the four PoCG devices fulfilled the minimum accuracy measurement set by ISO 15197:2003 and ISO 15197:2013 standards. In addition, the linear regression analysis revealed that all four selected PoCG overestimated the glucose concentrations. The overall evaluation of the selected four PoCG measurements were poorly correlated with standard reference method. Therefore, before introducing PoCG devices to the market, there should be a standardized evaluation platform for validation. Further similar large-scale studies on other PoCG devices also need to be undertaken.

  8. Selection bias and subject refusal in a cluster-randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Rochelle Yang

    2017-07-01

    Full Text Available Abstract Background Selection bias and non-participation bias are major methodological concerns which impact external validity. Cluster-randomized controlled trials are especially prone to selection bias as it is impractical to blind clusters to their allocation into intervention or control. This study assessed the impact of selection bias in a large cluster-randomized controlled trial. Methods The Improved Cardiovascular Risk Reduction to Enhance Rural Primary Care (ICARE study examined the impact of a remote pharmacist-led intervention in twelve medical offices. To assess eligibility, a standardized form containing patient demographics and medical information was completed for each screened patient. Eligible patients were approached by the study coordinator for recruitment. Both the study coordinator and the patient were aware of the site’s allocation prior to consent. Patients who consented or declined to participate were compared across control and intervention arms for differing characteristics. Statistical significance was determined using a two-tailed, equal variance t-test and a chi-square test with adjusted Bonferroni p-values. Results were adjusted for random cluster variation. Results There were 2749 completed screening forms returned to research staff with 461 subjects who had either consented or declined participation. Patients with poorly controlled diabetes were found to be significantly more likely to decline participation in intervention sites compared to those in control sites. A higher mean diastolic blood pressure was seen in patients with uncontrolled hypertension who declined in the control sites compared to those who declined in the intervention sites. However, these findings were no longer significant after adjustment for random variation among the sites. After this adjustment, females were now found to be significantly more likely to consent than males (odds ratio = 1.41; 95% confidence interval = 1.03, 1

  9. Implementing traceability using particle randomness-based textile printed tags

    Science.gov (United States)

    Agrawal, T. K.; Koehl, L.; Campagne, C.

    2017-10-01

    This article introduces a random particle-based traceability tag for textiles. The proposed tag not only act as a unique signature for the corresponding textile product but also possess the features such as easy to manufacture and hard to copy. It seeks applications in brand authentication and traceability in textile and clothing (T&C) supply chain. A prototype has been developed by screen printing process, in which micron-scale particles were mixed with the printing paste and printed on cotton fabrics to attain required randomness. To encode the randomness, the image of the developed tag was taken and analyzed using image processing. The randomness of the particles acts as a product key or unique signature which is required to decode the tag. Finally, washing and abrasion resistance tests were conducted to check the durability of the printed tag.

  10. N-state random switching based on quantum tunnelling

    Science.gov (United States)

    Bernardo Gavito, Ramón; Jiménez Urbanos, Fernando; Roberts, Jonathan; Sexton, James; Astbury, Benjamin; Shokeir, Hamzah; McGrath, Thomas; Noori, Yasir J.; Woodhead, Christopher S.; Missous, Mohamed; Roedig, Utz; Young, Robert J.

    2017-08-01

    In this work, we show how the hysteretic behaviour of resonant tunnelling diodes (RTDs) can be exploited for new functionalities. In particular, the RTDs exhibit a stochastic 2-state switching mechanism that could be useful for random number generation and cryptographic applications. This behaviour can be scaled to N-bit switching, by connecting various RTDs in series. The InGaAs/AlAs RTDs used in our experiments display very sharp negative differential resistance (NDR) peaks at room temperature which show hysteresis cycles that, rather than having a fixed switching threshold, show a probability distribution about a central value. We propose to use this intrinsic uncertainty emerging from the quantum nature of the RTDs as a source of randomness. We show that a combination of two RTDs in series results in devices with three-state outputs and discuss the possibility of scaling to N-state devices by subsequent series connections of RTDs, which we demonstrate for the up to the 4-state case. In this work, we suggest using that the intrinsic uncertainty in the conduction paths of resonant tunnelling diodes can behave as a source of randomness that can be integrated into current electronics to produce on-chip true random number generators. The N-shaped I-V characteristic of RTDs results in a two-level random voltage output when driven with current pulse trains. Electrical characterisation and randomness testing of the devices was conducted in order to determine the validity of the true randomness assumption. Based on the results obtained for the single RTD case, we suggest the possibility of using multi-well devices to generate N-state random switching devices for their use in random number generation or multi-valued logic devices.

  11. Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach

    Science.gov (United States)

    Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mitra, Swapan Kumar

    2010-10-01

    To reach the investment goal, one has to select a combination of securities among different portfolios containing large number of securities. Only the past records of each security do not guarantee the future return. As there are many uncertain factors which directly or indirectly influence the stock market and there are also some newer stock markets which do not have enough historical data, experts' expectation and experience must be combined with the past records to generate an effective portfolio selection model. In this paper the return of security is assumed to be Fuzzy Random Variable Set (FRVS), where returns are set of random numbers which are in turn fuzzy numbers. A new λ-Mean Semi Absolute Deviation (λ-MSAD) portfolio selection model is developed. The subjective opinions of the investors to the rate of returns of each security are taken into consideration by introducing a pessimistic-optimistic parameter vector λ. λ-Mean Semi Absolute Deviation (λ-MSAD) model is preferred as it follows absolute deviation of the rate of returns of a portfolio instead of the variance as the measure of the risk. As this model can be reduced to Linear Programming Problem (LPP) it can be solved much faster than quadratic programming problems. Ant Colony Optimization (ACO) is used for solving the portfolio selection problem. ACO is a paradigm for designing meta-heuristic algorithms for combinatorial optimization problem. Data from BSE is used for illustration.

  12. Age replacement policy based on imperfect repair with random probability

    International Nuclear Information System (INIS)

    Lim, J.H.; Qu, Jian; Zuo, Ming J.

    2016-01-01

    In most of literatures of age replacement policy, failures before planned replacement age can be either minimally repaired or perfectly repaired based on the types of failures, cost for repairs and so on. In this paper, we propose age replacement policy based on imperfect repair with random probability. The proposed policy incorporates the case that such intermittent failure can be either minimally repaired or perfectly repaired with random probabilities. The mathematical formulas of the expected cost rate per unit time are derived for both the infinite-horizon case and the one-replacement-cycle case. For each case, we show that the optimal replacement age exists and is finite. - Highlights: • We propose a new age replacement policy with random probability of perfect repair. • We develop the expected cost per unit time. • We discuss the optimal age for replacement minimizing the expected cost rate.

  13. MIS-based sensors with hydrogen selectivity

    Energy Technology Data Exchange (ETDEWEB)

    Li,; Dongmei, [Boulder, CO; Medlin, J William [Boulder, CO; McDaniel, Anthony H [Livermore, CA; Bastasz, Robert J [Livermore, CA

    2008-03-11

    The invention provides hydrogen selective metal-insulator-semiconductor sensors which include a layer of hydrogen selective material. The hydrogen selective material can be polyimide layer having a thickness between 200 and 800 nm. Suitable polyimide materials include reaction products of benzophenone tetracarboxylic dianhydride 4,4-oxydianiline m-phenylene diamine and other structurally similar materials.

  14. ANALYTIC WORD RECOGNITION WITHOUT SEGMENTATION BASED ON MARKOV RANDOM FIELDS

    NARCIS (Netherlands)

    Coisy, C.; Belaid, A.

    2004-01-01

    In this paper, a method for analytic handwritten word recognition based on causal Markov random fields is described. The words models are HMMs where each state corresponds to a letter; each letter is modelled by a NSHP­HMM (Markov field). Global models are build dynamically, and used for recognition

  15. Novel pseudo-random number generator based on quantum random walks

    Science.gov (United States)

    Yang, Yu-Guang; Zhao, Qian-Qian

    2016-02-01

    In this paper, we investigate the potential application of quantum computation for constructing pseudo-random number generators (PRNGs) and further construct a novel PRNG based on quantum random walks (QRWs), a famous quantum computation model. The PRNG merely relies on the equations used in the QRWs, and thus the generation algorithm is simple and the computation speed is fast. The proposed PRNG is subjected to statistical tests such as NIST and successfully passed the test. Compared with the representative PRNG based on quantum chaotic maps (QCM), the present QRWs-based PRNG has some advantages such as better statistical complexity and recurrence. For example, the normalized Shannon entropy and the statistical complexity of the QRWs-based PRNG are 0.999699456771172 and 1.799961178212329e-04 respectively given the number of 8 bits-words, say, 16Mbits. By contrast, the corresponding values of the QCM-based PRNG are 0.999448131481064 and 3.701210794388818e-04 respectively. Thus the statistical complexity and the normalized entropy of the QRWs-based PRNG are closer to 0 and 1 respectively than those of the QCM-based PRNG when the number of words of the analyzed sequence increases. It provides a new clue to construct PRNGs and also extends the applications of quantum computation.

  16. Novel pseudo-random number generator based on quantum random walks.

    Science.gov (United States)

    Yang, Yu-Guang; Zhao, Qian-Qian

    2016-02-04

    In this paper, we investigate the potential application of quantum computation for constructing pseudo-random number generators (PRNGs) and further construct a novel PRNG based on quantum random walks (QRWs), a famous quantum computation model. The PRNG merely relies on the equations used in the QRWs, and thus the generation algorithm is simple and the computation speed is fast. The proposed PRNG is subjected to statistical tests such as NIST and successfully passed the test. Compared with the representative PRNG based on quantum chaotic maps (QCM), the present QRWs-based PRNG has some advantages such as better statistical complexity and recurrence. For example, the normalized Shannon entropy and the statistical complexity of the QRWs-based PRNG are 0.999699456771172 and 1.799961178212329e-04 respectively given the number of 8 bits-words, say, 16Mbits. By contrast, the corresponding values of the QCM-based PRNG are 0.999448131481064 and 3.701210794388818e-04 respectively. Thus the statistical complexity and the normalized entropy of the QRWs-based PRNG are closer to 0 and 1 respectively than those of the QCM-based PRNG when the number of words of the analyzed sequence increases. It provides a new clue to construct PRNGs and also extends the applications of quantum computation.

  17. Text Clustering Algorithm Based on Random Cluster Core

    Directory of Open Access Journals (Sweden)

    Huang Long-Jun

    2016-01-01

    Full Text Available Nowadays clustering has become a popular text mining algorithm, but the huge data can put forward higher requirements for the accuracy and performance of text mining. In view of the performance bottleneck of traditional text clustering algorithm, this paper proposes a text clustering algorithm with random features. This is a kind of clustering algorithm based on text density, at the same time using the neighboring heuristic rules, the concept of random cluster is introduced, which effectively reduces the complexity of the distance calculation.

  18. Optical image encryption based on interference under convergent random illumination

    International Nuclear Information System (INIS)

    Kumar, Pramod; Joseph, Joby; Singh, Kehar

    2010-01-01

    In an optical image encryption system based on the interference principle, two pure phase masks are designed analytically to hide an image. These two masks are illuminated with a plane wavefront to retrieve the original image in the form of an interference pattern at the decryption plane. Replacement of the plane wavefront with convergent random illumination in the proposed scheme leads to an improvement in the security of interference based encryption. The proposed encryption scheme retains the simplicity of an interference based method, as the two pure masks are generated with an analytical method without any iterative algorithm. In addition to the free-space propagation distance and the two pure phase masks, the convergence distance and the randomized lens phase function are two new encryption parameters to enhance the system security. The robustness of this scheme against occlusion of the random phase mask of the randomized lens phase function is investigated. The feasibility of the proposed scheme is demonstrated with numerical simulation results

  19. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

    Science.gov (United States)

    Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

    2017-07-01

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

  20. A random spatial network model based on elementary postulates

    Science.gov (United States)

    Karlinger, Michael R.; Troutman, Brent M.

    1989-01-01

    A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.

  1. RandomSpot: A web-based tool for systematic random sampling of virtual slides.

    Science.gov (United States)

    Wright, Alexander I; Grabsch, Heike I; Treanor, Darren E

    2015-01-01

    This paper describes work presented at the Nordic Symposium on Digital Pathology 2014, Linköping, Sweden. Systematic random sampling (SRS) is a stereological tool, which provides a framework to quickly build an accurate estimation of the distribution of objects or classes within an image, whilst minimizing the number of observations required. RandomSpot is a web-based tool for SRS in stereology, which systematically places equidistant points within a given region of interest on a virtual slide. Each point can then be visually inspected by a pathologist in order to generate an unbiased sample of the distribution of classes within the tissue. Further measurements can then be derived from the distribution, such as the ratio of tumor to stroma. RandomSpot replicates the fundamental principle of traditional light microscope grid-shaped graticules, with the added benefits associated with virtual slides, such as facilitated collaboration and automated navigation between points. Once the sample points have been added to the region(s) of interest, users can download the annotations and view them locally using their virtual slide viewing software. Since its introduction, RandomSpot has been used extensively for international collaborative projects, clinical trials and independent research projects. So far, the system has been used to generate over 21,000 sample sets, and has been used to generate data for use in multiple publications, identifying significant new prognostic markers in colorectal, upper gastro-intestinal and breast cancer. Data generated using RandomSpot also has significant value for training image analysis algorithms using sample point coordinates and pathologist classifications.

  2. Selective oropharyngeal decontamination versus selective digestive decontamination in critically ill patients: a meta-analysis of randomized controlled trials

    Directory of Open Access Journals (Sweden)

    Zhao D

    2015-07-01

    Full Text Available Di Zhao,1,* Jian Song,2,* Xuan Gao,3 Fei Gao,4 Yupeng Wu,2 Yingying Lu,5 Kai Hou1 1Department of Neurosurgery, The First Hospital of Hebei Medical University, 2Department of Neurosurgery, 3Department of Neurology, The Second Hospital of Hebei Medical University, 4Hebei Provincial Procurement Centers for Medical Drugs and Devices, 5Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang People’s Republic of China *These authors contributed equally to this work Background: Selective digestive decontamination (SDD and selective oropharyngeal decontamination (SOD are associated with reduced mortality and infection rates among patients in intensive care units (ICUs; however, whether SOD has a superior effect than SDD remains uncertain. Hence, we conducted a meta-analysis of randomized controlled trials (RCTs to compare SOD with SDD in terms of clinical outcomes and antimicrobial resistance rates in patients who were critically ill. Methods: RCTs published in PubMed, Embase, and Web of Science were systematically reviewed to compare the effects of SOD and SDD in patients who were critically ill. Outcomes included day-28 mortality, length of ICU stay, length of hospital stay, duration of mechanical ventilation, ICU-acquired bacteremia, and prevalence of antibiotic-resistant Gram-negative bacteria. Results were expressed as risk ratio (RR with 95% confidence intervals (CIs, and weighted mean differences (WMDs with 95% CIs. Pooled estimates were performed using a fixed-effects model or random-effects model, depending on the heterogeneity among studies. Results: A total of four RCTs involving 23,822 patients met the inclusion criteria and were included in this meta-analysis. Among patients whose admitting specialty was surgery, cardiothoracic surgery (57.3% and neurosurgery (29.7% were the two main types of surgery being performed. Pooled results showed that SOD had similar effects as SDD in day-28 mortality (RR =1

  3. Geography and genography: prediction of continental origin using randomly selected single nucleotide polymorphisms

    Directory of Open Access Journals (Sweden)

    Ramoni Marco F

    2007-03-01

    Full Text Available Abstract Background Recent studies have shown that when individuals are grouped on the basis of genetic similarity, group membership corresponds closely to continental origin. There has been considerable debate about the implications of these findings in the context of larger debates about race and the extent of genetic variation between groups. Some have argued that clustering according to continental origin demonstrates the existence of significant genetic differences between groups and that these differences may have important implications for differences in health and disease. Others argue that clustering according to continental origin requires the use of large amounts of genetic data or specifically chosen markers and is indicative only of very subtle genetic differences that are unlikely to have biomedical significance. Results We used small numbers of randomly selected single nucleotide polymorphisms (SNPs from the International HapMap Project to train naïve Bayes classifiers for prediction of ancestral continent of origin. Predictive accuracy was tested on two independent data sets. Genetically similar groups should be difficult to distinguish, especially if only a small number of genetic markers are used. The genetic differences between continentally defined groups are sufficiently large that one can accurately predict ancestral continent of origin using only a minute, randomly selected fraction of the genetic variation present in the human genome. Genotype data from only 50 random SNPs was sufficient to predict ancestral continent of origin in our primary test data set with an average accuracy of 95%. Genetic variations informative about ancestry were common and widely distributed throughout the genome. Conclusion Accurate characterization of ancestry is possible using small numbers of randomly selected SNPs. The results presented here show how investigators conducting genetic association studies can use small numbers of arbitrarily

  4. Interference-aware random beam selection schemes for spectrum sharing systems

    KAUST Repository

    Abdallah, Mohamed

    2012-10-19

    Spectrum sharing systems have been recently introduced to alleviate the problem of spectrum scarcity by allowing secondary unlicensed networks to share the spectrum with primary licensed networks under acceptable interference levels to the primary users. In this work, we develop interference-aware random beam selection schemes that provide enhanced performance for the secondary network under the condition that the interference observed by the receivers of the primary network is below a predetermined/acceptable value. We consider a secondary link composed of a transmitter equipped with multiple antennas and a single-antenna receiver sharing the same spectrum with a primary link composed of a single-antenna transmitter and a single-antenna receiver. The proposed schemes select a beam, among a set of power-optimized random beams, that maximizes the signal-to-interference-plus-noise ratio (SINR) of the secondary link while satisfying the primary interference constraint for different levels of feedback information describing the interference level at the primary receiver. For the proposed schemes, we develop a statistical analysis for the SINR statistics as well as the capacity and bit error rate (BER) of the secondary link.

  5. Joint random beam and spectrum selection for spectrum sharing systems with partial channel state information

    KAUST Repository

    Abdallah, Mohamed M.

    2013-11-01

    In this work, we develop joint interference-aware random beam and spectrum selection scheme that provide enhanced performance for the secondary network under the condition that the interference observed at the primary receiver is below a predetermined acceptable value. We consider a secondary link composed of a transmitter equipped with multiple antennas and a single-antenna receiver sharing the same spectrum with a set of primary links composed of a single-antenna transmitter and a single-antenna receiver. The proposed schemes jointly select a beam, among a set of power-optimized random beams, as well as the primary spectrum that maximizes the signal-to-interference-plus-noise ratio (SINR) of the secondary link while satisfying the primary interference constraint. In particular, we consider the case where the interference level is described by a q-bit description of its magnitude, whereby we propose a technique to find the optimal quantizer thresholds in a mean square error (MSE) sense. © 2013 IEEE.

  6. Joint random beam and spectrum selection for spectrum sharing systems with partial channel state information

    KAUST Repository

    Abdallah, Mohamed M.; Sayed, Mostafa M.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

    2013-01-01

    In this work, we develop joint interference-aware random beam and spectrum selection scheme that provide enhanced performance for the secondary network under the condition that the interference observed at the primary receiver is below a predetermined acceptable value. We consider a secondary link composed of a transmitter equipped with multiple antennas and a single-antenna receiver sharing the same spectrum with a set of primary links composed of a single-antenna transmitter and a single-antenna receiver. The proposed schemes jointly select a beam, among a set of power-optimized random beams, as well as the primary spectrum that maximizes the signal-to-interference-plus-noise ratio (SINR) of the secondary link while satisfying the primary interference constraint. In particular, we consider the case where the interference level is described by a q-bit description of its magnitude, whereby we propose a technique to find the optimal quantizer thresholds in a mean square error (MSE) sense. © 2013 IEEE.

  7. Feature selection and classification of mechanical fault of an induction motor using random forest classifier

    OpenAIRE

    Patel, Raj Kumar; Giri, V.K.

    2016-01-01

    Fault detection and diagnosis is the most important technology in condition-based maintenance (CBM) system for rotating machinery. This paper experimentally explores the development of a random forest (RF) classifier, a recently emerged machine learning technique, for multi-class mechanical fault diagnosis in bearing of an induction motor. Firstly, the vibration signals are collected from the bearing using accelerometer sensor. Parameters from the vibration signal are extracted in the form of...

  8. Random Valued Impulse Noise Removal Using Region Based Detection Approach

    Directory of Open Access Journals (Sweden)

    S. Banerjee

    2017-12-01

    Full Text Available Removal of random valued noisy pixel is extremely challenging when the noise density is above 50%. The existing filters are generally not capable of eliminating such noise when density is above 70%. In this paper a region wise density based detection algorithm for random valued impulse noise has been proposed. On the basis of the intensity values, the pixels of a particular window are sorted and then stored into four regions. The higher density based region is considered for stepwise detection of noisy pixels. As a result of this detection scheme a maximum of 75% of noisy pixels can be detected. For this purpose this paper proposes a unique noise removal algorithm. It was experimentally proved that the proposed algorithm not only performs exceptionally when it comes to visual qualitative judgment of standard images but also this filter combination outsmarts the existing algorithm in terms of MSE, PSNR and SSIM comparison even up to 70% noise density level.

  9. Fine mapping quantitative trait loci under selective phenotyping strategies based on linkage and linkage disequilibrium criteria

    DEFF Research Database (Denmark)

    Ansari-Mahyari, S; Berg, P; Lund, M S

    2009-01-01

    disequilibrium-based sampling criteria (LDC) for selecting individuals to phenotype are compared to random phenotyping in a quantitative trait loci (QTL) verification experiment using stochastic simulation. Several strategies based on LAC and LDC for selecting the most informative 30%, 40% or 50% of individuals...... for phenotyping to extract maximum power and precision in a QTL fine mapping experiment were developed and assessed. Linkage analyses for the mapping was performed for individuals sampled on LAC within families and combined linkage disequilibrium and linkage analyses was performed for individuals sampled across...... the whole population based on LDC. The results showed that selecting individuals with similar haplotypes to the paternal haplotypes (minimum recombination criterion) using LAC compared to random phenotyping gave at least the same power to detect a QTL but decreased the accuracy of the QTL position. However...

  10. Factors Associated with High Use of a Workplace Web-Based Stress Management Program in a Randomized Controlled Intervention Study

    Science.gov (United States)

    Hasson, H.; Brown, C.; Hasson, D.

    2010-01-01

    In web-based health promotion programs, large variations in participant engagement are common. The aim was to investigate determinants of high use of a worksite self-help web-based program for stress management. Two versions of the program were offered to randomly selected departments in IT and media companies. A static version of the program…

  11. Integrated Behavior Therapy for Selective Mutism: a randomized controlled pilot study.

    Science.gov (United States)

    Bergman, R Lindsey; Gonzalez, Araceli; Piacentini, John; Keller, Melody L

    2013-10-01

    To evaluate the feasibility, acceptability, and preliminary efficacy of a novel behavioral intervention for reducing symptoms of selective mutism and increasing functional speech. A total of 21 children ages 4 to 8 with primary selective mutism were randomized to 24 weeks of Integrated Behavior Therapy for Selective Mutism (IBTSM) or a 12-week Waitlist control. Clinical outcomes were assessed using blind independent evaluators, parent-, and teacher-report, and an objective behavioral measure. Treatment recipients completed a three-month follow-up to assess durability of treatment gains. Data indicated increased functional speaking behavior post-treatment as rated by parents and teachers, with a high rate of treatment responders as rated by blind independent evaluators (75%). Conversely, children in the Waitlist comparison group did not experience significant improvements in speaking behaviors. Children who received IBTSM also demonstrated significant improvements in number of words spoken at school compared to baseline, however, significant group differences did not emerge. Treatment recipients also experienced significant reductions in social anxiety per parent, but not teacher, report. Clinical gains were maintained over 3 month follow-up. IBTSM appears to be a promising new intervention that is efficacious in increasing functional speaking behaviors, feasible, and acceptable to parents and teachers. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Two-year Randomized Clinical Trial of Self-etching Adhesives and Selective Enamel Etching.

    Science.gov (United States)

    Pena, C E; Rodrigues, J A; Ely, C; Giannini, M; Reis, A F

    2016-01-01

    The aim of this randomized, controlled prospective clinical trial was to evaluate the clinical effectiveness of restoring noncarious cervical lesions with two self-etching adhesive systems applied with or without selective enamel etching. A one-step self-etching adhesive (Xeno V(+)) and a two-step self-etching system (Clearfil SE Bond) were used. The effectiveness of phosphoric acid selective etching of enamel margins was also evaluated. Fifty-six cavities were restored with each adhesive system and divided into two subgroups (n=28; etch and non-etch). All 112 cavities were restored with the nanohybrid composite Esthet.X HD. The clinical effectiveness of restorations was recorded in terms of retention, marginal integrity, marginal staining, caries recurrence, and postoperative sensitivity after 3, 6, 12, 18, and 24 months (modified United States Public Health Service). The Friedman test detected significant differences only after 18 months for marginal staining in the groups Clearfil SE non-etch (p=0.009) and Xeno V(+) etch (p=0.004). One restoration was lost during the trial (Xeno V(+) etch; p>0.05). Although an increase in marginal staining was recorded for groups Clearfil SE non-etch and Xeno V(+) etch, the clinical effectiveness of restorations was considered acceptable for the single-step and two-step self-etching systems with or without selective enamel etching in this 24-month clinical trial.

  13. SADA: Ecological Risk Based Decision Support System for Selective Remediation

    Science.gov (United States)

    Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

  14. Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

    Science.gov (United States)

    Li, Jin; Tran, Maggie; Siwabessy, Justy

    2016-01-01

    Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and

  15. Prediction of plant promoters based on hexamers and random triplet pair analysis

    Directory of Open Access Journals (Sweden)

    Noman Nasimul

    2011-06-01

    Full Text Available Abstract Background With an increasing number of plant genome sequences, it has become important to develop a robust computational method for detecting plant promoters. Although a wide variety of programs are currently available, prediction accuracy of these still requires further improvement. The limitations of these methods can be addressed by selecting appropriate features for distinguishing promoters and non-promoters. Methods In this study, we proposed two feature selection approaches based on hexamer sequences: the Frequency Distribution Analyzed Feature Selection Algorithm (FDAFSA and the Random Triplet Pair Feature Selecting Genetic Algorithm (RTPFSGA. In FDAFSA, adjacent triplet-pairs (hexamer sequences were selected based on the difference in the frequency of hexamers between promoters and non-promoters. In RTPFSGA, random triplet-pairs (RTPs were selected by exploiting a genetic algorithm that distinguishes frequencies of non-adjacent triplet pairs between promoters and non-promoters. Then, a support vector machine (SVM, a nonlinear machine-learning algorithm, was used to classify promoters and non-promoters by combining these two feature selection approaches. We referred to this novel algorithm as PromoBot. Results Promoter sequences were collected from the PlantProm database. Non-promoter sequences were collected from plant mRNA, rRNA, and tRNA of PlantGDB and plant miRNA of miRBase. Then, in order to validate the proposed algorithm, we applied a 5-fold cross validation test. Training data sets were used to select features based on FDAFSA and RTPFSGA, and these features were used to train the SVM. We achieved 89% sensitivity and 86% specificity. Conclusions We compared our PromoBot algorithm to five other algorithms. It was found that the sensitivity and specificity of PromoBot performed well (or even better with the algorithms tested. These results show that the two proposed feature selection methods based on hexamer frequencies

  16. Structuring AHP-based maintenance policy selection

    NARCIS (Netherlands)

    Goossens, Adriaan; Basten, Robertus Johannes Ida; Hummel, J. Marjan; van der Wegen, Leonardus L.M.

    2015-01-01

    We aim to structure the maintenance policy selection process for ships, using the Analytic Hierarchy Process (AHP). Maintenance is an important contributor to reach the intended life-time of capital technical assets, and it is gaining increasing interest and relevance. A maintenance policy is a

  17. Cellular Automata-Based Parallel Random Number Generators Using FPGAs

    Directory of Open Access Journals (Sweden)

    David H. K. Hoe

    2012-01-01

    Full Text Available Cellular computing represents a new paradigm for implementing high-speed massively parallel machines. Cellular automata (CA, which consist of an array of locally connected processing elements, are a basic form of a cellular-based architecture. The use of field programmable gate arrays (FPGAs for implementing CA accelerators has shown promising results. This paper investigates the design of CA-based pseudo-random number generators (PRNGs using an FPGA platform. To improve the quality of the random numbers that are generated, the basic CA structure is enhanced in two ways. First, the addition of a superrule to each CA cell is considered. The resulting self-programmable CA (SPCA uses the superrule to determine when to make a dynamic rule change in each CA cell. The superrule takes its inputs from neighboring cells and can be considered itself a second CA working in parallel with the main CA. When implemented on an FPGA, the use of lookup tables in each logic cell removes any restrictions on how the super-rules should be defined. Second, a hybrid configuration is formed by combining a CA with a linear feedback shift register (LFSR. This is advantageous for FPGA designs due to the compactness of the LFSR implementations. A standard software package for statistically evaluating the quality of random number sequences known as Diehard is used to validate the results. Both the SPCA and the hybrid CA/LFSR were found to pass all the Diehard tests.

  18. Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Heide, J; Zhang, Qi; Fitzek, F H P

    2013-01-01

    This work studies how to select optimal code parameters of Random Linear Network Coding (RLNC) in Wireless Sensor Networks (WSNs). With Rateless Deluge [1] the authors proposed to apply Network Coding (NC) for Over-the-Air Programming (OAP) in WSNs, and demonstrated that with NC a significant...... reduction in the number of transmitted packets can be achieved. However, NC introduces additional computations and potentially a non-negligible transmission overhead, both of which depend on the chosen coding parameters. Therefore it is necessary to consider the trade-off that these coding parameters...... present in order to obtain the lowest energy consumption per transmitted bit. This problem is analyzed and suitable coding parameters are determined for the popular Tmote Sky platform. Compared to the use of traditional RLNC, these parameters enable a reduction in the energy spent per bit which grows...

  19. Implications of structural genomics target selection strategies: Pfam5000, whole genome, and random approaches

    Energy Technology Data Exchange (ETDEWEB)

    Chandonia, John-Marc; Brenner, Steven E.

    2004-07-14

    The structural genomics project is an international effort to determine the three-dimensional shapes of all important biological macromolecules, with a primary focus on proteins. Target proteins should be selected according to a strategy which is medically and biologically relevant, of good value, and tractable. As an option to consider, we present the Pfam5000 strategy, which involves selecting the 5000 most important families from the Pfam database as sources for targets. We compare the Pfam5000 strategy to several other proposed strategies that would require similar numbers of targets. These include including complete solution of several small to moderately sized bacterial proteomes, partial coverage of the human proteome, and random selection of approximately 5000 targets from sequenced genomes. We measure the impact that successful implementation of these strategies would have upon structural interpretation of the proteins in Swiss-Prot, TrEMBL, and 131 complete proteomes (including 10 of eukaryotes) from the Proteome Analysis database at EBI. Solving the structures of proteins from the 5000 largest Pfam families would allow accurate fold assignment for approximately 68 percent of all prokaryotic proteins (covering 59 percent of residues) and 61 percent of eukaryotic proteins (40 percent of residues). More fine-grained coverage which would allow accurate modeling of these proteins would require an order of magnitude more targets. The Pfam5000 strategy may be modified in several ways, for example to focus on larger families, bacterial sequences, or eukaryotic sequences; as long as secondary consideration is given to large families within Pfam, coverage results vary only slightly. In contrast, focusing structural genomics on a single tractable genome would have only a limited impact in structural knowledge of other proteomes: a significant fraction (about 30-40 percent of the proteins, and 40-60 percent of the residues) of each proteome is classified in small

  20. Research on machine learning framework based on random forest algorithm

    Science.gov (United States)

    Ren, Qiong; Cheng, Hui; Han, Hai

    2017-03-01

    With the continuous development of machine learning, industry and academia have released a lot of machine learning frameworks based on distributed computing platform, and have been widely used. However, the existing framework of machine learning is limited by the limitations of machine learning algorithm itself, such as the choice of parameters and the interference of noises, the high using threshold and so on. This paper introduces the research background of machine learning framework, and combined with the commonly used random forest algorithm in machine learning classification algorithm, puts forward the research objectives and content, proposes an improved adaptive random forest algorithm (referred to as ARF), and on the basis of ARF, designs and implements the machine learning framework.

  1. Chaos-based Pseudo-random Number Generation

    KAUST Repository

    Barakat, Mohamed L.

    2014-04-10

    Various methods and systems related to chaos-based pseudo-random number generation are presented. In one example, among others, a system includes a pseudo-random number generator (PRNG) to generate a series of digital outputs and a nonlinear post processing circuit to perform an exclusive OR (XOR) operation on a first portion of a current digital output of the PRNG and a permutated version of a corresponding first portion of a previous post processed output to generate a corresponding first portion of a current post processed output. In another example, a method includes receiving at least a first portion of a current output from a PRNG and performing an XOR operation on the first portion of the current PRNG output with a permutated version of a corresponding first portion of a previous post processed output to generate a corresponding first portion of a current post processed output.

  2. Chaos-based Pseudo-random Number Generation

    KAUST Repository

    Barakat, Mohamed L.; Mansingka, Abhinav S.; Radwan, Ahmed Gomaa Ahmed; Salama, Khaled N.

    2014-01-01

    Various methods and systems related to chaos-based pseudo-random number generation are presented. In one example, among others, a system includes a pseudo-random number generator (PRNG) to generate a series of digital outputs and a nonlinear post processing circuit to perform an exclusive OR (XOR) operation on a first portion of a current digital output of the PRNG and a permutated version of a corresponding first portion of a previous post processed output to generate a corresponding first portion of a current post processed output. In another example, a method includes receiving at least a first portion of a current output from a PRNG and performing an XOR operation on the first portion of the current PRNG output with a permutated version of a corresponding first portion of a previous post processed output to generate a corresponding first portion of a current post processed output.

  3. Computational intelligence-based polymerase chain reaction primer selection based on a novel teaching-learning-based optimisation.

    Science.gov (United States)

    Cheng, Yu-Huei

    2014-12-01

    Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.

  4. DNA based random key generation and management for OTP encryption.

    Science.gov (United States)

    Zhang, Yunpeng; Liu, Xin; Sun, Manhui

    2017-09-01

    One-time pad (OTP) is a principle of key generation applied to the stream ciphering method which offers total privacy. The OTP encryption scheme has proved to be unbreakable in theory, but difficult to realize in practical applications. Because OTP encryption specially requires the absolute randomness of the key, its development has suffered from dense constraints. DNA cryptography is a new and promising technology in the field of information security. DNA chromosomes storing capabilities can be used as one-time pad structures with pseudo-random number generation and indexing in order to encrypt the plaintext messages. In this paper, we present a feasible solution to the OTP symmetric key generation and transmission problem with DNA at the molecular level. Through recombinant DNA technology, by using only sender-receiver known restriction enzymes to combine the secure key represented by DNA sequence and the T vector, we generate the DNA bio-hiding secure key and then place the recombinant plasmid in implanted bacteria for secure key transmission. The designed bio experiments and simulation results show that the security of the transmission of the key is further improved and the environmental requirements of key transmission are reduced. Analysis has demonstrated that the proposed DNA-based random key generation and management solutions are marked by high security and usability. Published by Elsevier B.V.

  5. Random fiber lasers based on artificially controlled backscattering fibers

    Science.gov (United States)

    Chen, Daru; Wang, Xiaoliang; She, Lijuan; Qiang, Zexuan; Yu, Zhangwei

    2017-10-01

    The random fiber laser (RFL) which is a milestone in laser physics and nonlinear optics, has attracted considerable attention recently. Most previous RFLs are based on distributed feedback of Rayleigh scattering amplified through stimulated Raman/Brillouin scattering effect in single mode fibers, which required long-distance (tens of kilometers) single mode fibers and high threshold up to watt-level due to the extremely small Rayleigh scattering coefficient of the fiber. We proposed and demonstrated a half-open cavity RFL based on a segment of a artificially controlled backscattering SMF(ACB-SMF) with a length of 210m, 310m or 390m. A fiber Bragg grating with the central wavelength of 1530nm and a segment of ACB-SMF forms the half-open cavity. The proposed RFL achieves the threshold of 25mW, 30mW and 30mW, respectively. Random lasing at the wavelength of 1530nm and the extinction ratio of 50dB is achieved when a segment of 5m EDF is pumped by a 980nm LD in the RFL. Another half-open cavity RFL based on a segment of a artificially controlled backscattering EDF(ACBS-EDF) is also demonstrated without an ACB-SMF. The 3m ACB-EDF is fabricated by using the femtosecond laser with pulse energy of 0.34mJ which introduces about 50 reflectors in the EDF. Random lasing at the wavelength of 1530nm is achieved with the output power of 7.5mW and the efficiency of 1.88%. Two novel RFLs with much short cavities have been achieved with low threshold and high efficiency.

  6. A random network based, node attraction facilitated network evolution method

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2016-03-01

    Full Text Available In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999 of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor Lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor Lamda can reflect various effects of the node degree on connection mechanism. Even the changes of Lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.

  7. Random number generation based on digital differential chaos

    KAUST Repository

    Zidan, Mohammed A.

    2012-07-29

    In this paper, we present a fully digital differential chaos based random number generator. The output of the digital circuit is proved to be chaotic by calculating the output time series maximum Lyapunov exponent. We introduce a new post processing technique to improve the distribution and statistical properties of the generated data. The post-processed output passes the NIST Sp. 800-22 statistical tests. The system is written in Verilog VHDL and realized on Xilinx Virtex® FPGA. The generator can fit into a very small area and have a maximum throughput of 2.1 Gb/s.

  8. Random-Profiles-Based 3D Face Recognition System

    Directory of Open Access Journals (Sweden)

    Joongrock Kim

    2014-03-01

    Full Text Available In this paper, a noble nonintrusive three-dimensional (3D face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the performance of 3D face recognition highly depends on the precision of acquired 3D face data, while also requiring more computational power and storage capacity than 2D face recognition systems. In this paper, we present a developed nonintrusive 3D face modeling system composed of a stereo vision system and an invisible near-infrared line laser, which can be directly applied to profile-based 3D face recognition. We further propose a novel random-profile-based 3D face recognition method that is memory-efficient and pose-invariant. The experimental results demonstrate that the reconstructed 3D face data consists of more than 50 k 3D point clouds and a reliable recognition rate against pose variation.

  9. The Random Walk Model Based on Bipartite Network

    Directory of Open Access Journals (Sweden)

    Zhang Man-Dun

    2016-01-01

    Full Text Available With the continuing development of the electronic commerce and growth of network information, there is a growing possibility for citizens to be confused by the information. Though the traditional technology of information retrieval have the ability to relieve the overload of information in some extent, it can not offer a targeted personality service based on user’s interests and activities. In this context, the recommendation algorithm arose. In this paper, on the basis of conventional recommendation, we studied the scheme of random walk based on bipartite network and the application of it. We put forward a similarity measurement based on implicit feedback. In this method, a uneven character vector is imported(the weight of item in the system. We put forward a improved random walk pattern which make use of partial or incomplete neighbor information to create recommendation information. In the end, there is an experiment in the real data set, the recommendation accuracy and practicality are improved. We promise the reality of the result of the experiment

  10. Randomized clinical trial of Appendicitis Inflammatory Response score-based management of patients with suspected appendicitis.

    Science.gov (United States)

    Andersson, M; Kolodziej, B; Andersson, R E

    2017-10-01

    The role of imaging in the diagnosis of appendicitis is controversial. This prospective interventional study and nested randomized trial analysed the impact of implementing a risk stratification algorithm based on the Appendicitis Inflammatory Response (AIR) score, and compared routine imaging with selective imaging after clinical reassessment. Patients presenting with suspicion of appendicitis between September 2009 and January 2012 from age 10 years were included at 21 emergency surgical centres and from age 5 years at three university paediatric centres. Registration of clinical characteristics, treatments and outcomes started during the baseline period. The AIR score-based algorithm was implemented during the intervention period. Intermediate-risk patients were randomized to routine imaging or selective imaging after clinical reassessment. The baseline period included 1152 patients, and the intervention period 2639, of whom 1068 intermediate-risk patients were randomized. In low-risk patients, use of the AIR score-based algorithm resulted in less imaging (19·2 versus 34·5 per cent; P appendicitis (6·8 versus 9·7 per cent; P = 0·034). Intermediate-risk patients randomized to the imaging and observation groups had the same proportion of negative appendicectomies (6·4 versus 6·7 per cent respectively; P = 0·884), number of admissions, number of perforations and length of hospital stay, but routine imaging was associated with an increased proportion of patients treated for appendicitis (53·4 versus 46·3 per cent; P = 0·020). AIR score-based risk classification can safely reduce the use of diagnostic imaging and hospital admissions in patients with suspicion of appendicitis. Registration number: NCT00971438 ( http://www.clinicaltrials.gov). © 2017 BJS Society Ltd Published by John Wiley & Sons Ltd.

  11. A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity Prediction.

    Science.gov (United States)

    Haider, Saad; Rahman, Raziur; Ghosh, Souparno; Pal, Ranadip

    2015-01-01

    Modeling sensitivity to drugs based on genetic characterizations is a significant challenge in the area of systems medicine. Ensemble based approaches such as Random Forests have been shown to perform well in both individual sensitivity prediction studies and team science based prediction challenges. However, Random Forests generate a deterministic predictive model for each drug based on the genetic characterization of the cell lines and ignores the relationship between different drug sensitivities during model generation. This application motivates the need for generation of multivariate ensemble learning techniques that can increase prediction accuracy and improve variable importance ranking by incorporating the relationships between different output responses. In this article, we propose a novel cost criterion that captures the dissimilarity in the output response structure between the training data and node samples as the difference in the two empirical copulas. We illustrate that copulas are suitable for capturing the multivariate structure of output responses independent of the marginal distributions and the copula based multivariate random forest framework can provide higher accuracy prediction and improved variable selection. The proposed framework has been validated on genomics of drug sensitivity for cancer and cancer cell line encyclopedia database.

  12. 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.

  13. The adverse effect of selective cyclooxygenase-2 inhibitor on random skin flap survival in rats.

    Directory of Open Access Journals (Sweden)

    Haiyong Ren

    Full Text Available BACKGROUND: Cyclooxygenase-2(COX-2 inhibitors provide desired analgesic effects after injury or surgery, but evidences suggested they also attenuate wound healing. The study is to investigate the effect of COX-2 inhibitor on random skin flap survival. METHODS: The McFarlane flap model was established in 40 rats and evaluated within two groups, each group gave the same volume of Parecoxib and saline injection for 7 days. The necrotic area of the flap was measured, the specimens of the flap were stained with haematoxylin-eosin(HE for histologic analysis. Immunohistochemical staining was performed to analyse the level of VEGF and COX-2 . RESULTS: 7 days after operation, the flap necrotic area ratio in study group (66.65 ± 2.81% was significantly enlarged than that of the control group(48.81 ± 2.33%(P <0.01. Histological analysis demonstrated angiogenesis with mean vessel density per mm(2 being lower in study group (15.4 ± 4.4 than in control group (27.2 ± 4.1 (P <0.05. To evaluate the expression of COX-2 and VEGF protein in the intermediate area II in the two groups by immunohistochemistry test .The expression of COX-2 in study group was (1022.45 ± 153.1, and in control group was (2638.05 ± 132.2 (P <0.01. The expression of VEGF in the study and control groups were (2779.45 ± 472.0 vs (4938.05 ± 123.6(P <0.01.In the COX-2 inhibitor group, the expressions of COX-2 and VEGF protein were remarkably down-regulated as compared with the control group. CONCLUSION: Selective COX-2 inhibitor had adverse effect on random skin flap survival. Suppression of neovascularization induced by low level of VEGF was supposed to be the biological mechanism.

  14. An improved label propagation algorithm based on node importance and random walk for community detection

    Science.gov (United States)

    Ma, Tianren; Xia, Zhengyou

    2017-05-01

    Currently, with the rapid development of information technology, the electronic media for social communication is becoming more and more popular. Discovery of communities is a very effective way to understand the properties of complex networks. However, traditional community detection algorithms consider the structural characteristics of a social organization only, with more information about nodes and edges wasted. In the meanwhile, these algorithms do not consider each node on its merits. Label propagation algorithm (LPA) is a near linear time algorithm which aims to find the community in the network. It attracts many scholars owing to its high efficiency. In recent years, there are more improved algorithms that were put forward based on LPA. In this paper, an improved LPA based on random walk and node importance (NILPA) is proposed. Firstly, a list of node importance is obtained through calculation. The nodes in the network are sorted in descending order of importance. On the basis of random walk, a matrix is constructed to measure the similarity of nodes and it avoids the random choice in the LPA. Secondly, a new metric IAS (importance and similarity) is calculated by node importance and similarity matrix, which we can use to avoid the random selection in the original LPA and improve the algorithm stability. Finally, a test in real-world and synthetic networks is given. The result shows that this algorithm has better performance than existing methods in finding community structure.

  15. Application of random coherence order selection in gradient-enhanced multidimensional NMR

    International Nuclear Information System (INIS)

    Bostock, Mark J.; Nietlispach, Daniel

    2016-01-01

    Development of multidimensional NMR is essential to many applications, for example in high resolution structural studies of biomolecules. Multidimensional techniques enable separation of NMR signals over several dimensions, improving signal resolution, whilst also allowing identification of new connectivities. However, these advantages come at a significant cost. The Fourier transform theorem requires acquisition of a grid of regularly spaced points to satisfy the Nyquist criterion, while frequency discrimination and acquisition of a pure phase spectrum require acquisition of both quadrature components for each time point in every indirect (non-acquisition) dimension, adding a factor of 2 N -1 to the number of free- induction decays which must be acquired, where N is the number of dimensions. Compressed sensing (CS) ℓ 1 -norm minimisation in combination with non-uniform sampling (NUS) has been shown to be extremely successful in overcoming the Nyquist criterion. Previously, maximum entropy reconstruction has also been used to overcome the limitation of frequency discrimination, processing data acquired with only one quadrature component at a given time interval, known as random phase detection (RPD), allowing a factor of two reduction in the number of points for each indirect dimension (Maciejewski et al. 2011 PNAS 108 16640). However, whilst this approach can be easily applied in situations where the quadrature components are acquired as amplitude modulated data, the same principle is not easily extended to phase modulated (P-/N-type) experiments where data is acquired in the form exp (iωt) or exp (-iωt), and which make up many of the multidimensional experiments used in modern NMR. Here we demonstrate a modification of the CS ℓ 1 -norm approach to allow random coherence order selection (RCS) for phase modulated experiments; we generalise the nomenclature for RCS and RPD as random quadrature detection (RQD). With this method, the power of RQD can be extended

  16. Content-based image retrieval: Color-selection exploited

    NARCIS (Netherlands)

    Broek, E.L. van den; Vuurpijl, L.G.; Kisters, P. M. F.; Schmid, J.C.M. von; Moens, M.F.; Busser, R. de; Hiemstra, D.; Kraaij, W.

    2002-01-01

    This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

  17. Content-Based Image Retrieval: Color-selection exploited

    NARCIS (Netherlands)

    Moens, Marie-Francine; van den Broek, Egon; Vuurpijl, L.G.; de Brusser, Rik; Kisters, P.M.F.; Hiemstra, Djoerd; Kraaij, Wessel; von Schmid, J.C.M.

    2002-01-01

    This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

  18. Order-based representation in random networks of cortical neurons.

    Directory of Open Access Journals (Sweden)

    Goded Shahaf

    2008-11-01

    Full Text Available The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen.

  19. A Table-Based Random Sampling Simulation for Bioluminescence Tomography

    Directory of Open Access Journals (Sweden)

    Xiaomeng Zhang

    2006-01-01

    Full Text Available As a popular simulation of photon propagation in turbid media, the main problem of Monte Carlo (MC method is its cumbersome computation. In this work a table-based random sampling simulation (TBRS is proposed. The key idea of TBRS is to simplify multisteps of scattering to a single-step process, through randomly table querying, thus greatly reducing the computing complexity of the conventional MC algorithm and expediting the computation. The TBRS simulation is a fast algorithm of the conventional MC simulation of photon propagation. It retained the merits of flexibility and accuracy of conventional MC method and adapted well to complex geometric media and various source shapes. Both MC simulations were conducted in a homogeneous medium in our work. Also, we present a reconstructing approach to estimate the position of the fluorescent source based on the trial-and-error theory as a validation of the TBRS algorithm. Good agreement is found between the conventional MC simulation and the TBRS simulation.

  20. Random fiber laser based on artificially controlled backscattering fibers.

    Science.gov (United States)

    Wang, Xiaoliang; Chen, Daru; Li, Haitao; She, Lijuan; Wu, Qiong

    2018-01-10

    The random fiber laser (RFL), which is a milestone in laser physics and nonlinear optics, has attracted considerable attention recently. Most previously reported RFLs are based on distributed feedback of Rayleigh scattering amplified through the stimulated Raman-Brillouin scattering effect in single-mode fibers, which require long-distance (tens of kilometers) single-mode fibers and high threshold, up to watt level, due to the extremely small Rayleigh scattering coefficient of the fiber. We proposed and demonstrated a half-open-cavity RFL based on a segment of an artificially controlled backscattering single-mode fiber with a length of 210 m, 310 m, or 390 m. A fiber Bragg grating with a central wavelength of 1530 nm and a segment of artificially controlled backscattering single-mode fiber fabricated by using a femtosecond laser form the half-open cavity. The proposed RFL achieves thresholds of 25 mW, 30 mW, and 30 mW, respectively. Random lasing at a wavelength of 1530 nm and extinction ratio of 50 dB is achieved when a segment of 5 m erbium-doped fiber is pumped by a 980 nm laser diode in the RFL. A novel RFL with many short cavities has been achieved with low threshold.

  1. Tungsten based catalysts for selective deoxygenation

    NARCIS (Netherlands)

    Gosselink, R.W.|info:eu-repo/dai/nl/326164081; Stellwagen, D.R.; Bitter, J.H.|info:eu-repo/dai/nl/160581435

    2013-01-01

    Over the past decades, impending oil shortages combined with petroleum market instability have prompted a search for a new source of both transportation fuels and bulk chemicals. Renewable bio-based feedstocks such as sugars, grains, and seeds are assumed to be capable of contributing to a

  2. The use of odd random phase electrochemical impedance spectroscopy to study lithium-based corrosion inhibition by active protective coatings

    NARCIS (Netherlands)

    Meeusen, M.; Visser, P.; Fernández Macía, L.; Hubin, A.; Terryn, H.A.; Mol, J.M.C.

    2018-01-01

    In this work, the study of the time-dependent behaviour of lithium carbonate based inhibitor technology for the active corrosion protection of aluminium alloy 2024-T3 is presented. Odd random phase electrochemical impedance spectroscopy (ORP-EIS) is selected as the electrochemical tool to study

  3. Random genetic drift, natural selection, and noise in human cranial evolution.

    Science.gov (United States)

    Roseman, Charles C

    2016-08-01

    This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology. Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality. Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  4. A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data

    Directory of Open Access Journals (Sweden)

    Himmelreich Uwe

    2009-07-01

    Full Text Available Abstract Background Regularized regression methods such as principal component or partial least squares regression perform well in learning tasks on high dimensional spectral data, but cannot explicitly eliminate irrelevant features. The random forest classifier with its associated Gini feature importance, on the other hand, allows for an explicit feature elimination, but may not be optimally adapted to spectral data due to the topology of its constituent classification trees which are based on orthogonal splits in feature space. Results We propose to combine the best of both approaches, and evaluated the joint use of a feature selection based on a recursive feature elimination using the Gini importance of random forests' together with regularized classification methods on spectral data sets from medical diagnostics, chemotaxonomy, biomedical analytics, food science, and synthetically modified spectral data. Here, a feature selection using the Gini feature importance with a regularized classification by discriminant partial least squares regression performed as well as or better than a filtering according to different univariate statistical tests, or using regression coefficients in a backward feature elimination. It outperformed the direct application of the random forest classifier, or the direct application of the regularized classifiers on the full set of features. Conclusion The Gini importance of the random forest provided superior means for measuring feature relevance on spectral data, but – on an optimal subset of features – the regularized classifiers might be preferable over the random forest classifier, in spite of their limitation to model linear dependencies only. A feature selection based on Gini importance, however, may precede a regularized linear classification to identify this optimal subset of features, and to earn a double benefit of both dimensionality reduction and the elimination of noise from the classification task.

  5. Cermet based solar selective absorbers : further selectivity improvement and developing new fabrication technique

    OpenAIRE

    Nejati, Mohammadreza

    2008-01-01

    Spectral selectivity of cermet based selective absorbers were increased by inducing surface roughness on the surface of the cermet layer using a roughening technique (deposition on hot substrates) or by micro-structuring the metallic substrates before deposition of the absorber coating using laser and imprint structuring techniques. Cu-Al2O3 cermet absorbers with very rough surfaces and excellent selectivity were obtained by employing a roughness template layer under the infrared reflective l...

  6. Predictive Validity of an Empirical Approach for Selecting Promising Message Topics: A Randomized-Controlled Study

    Science.gov (United States)

    Lee, Stella Juhyun; Brennan, Emily; Gibson, Laura Anne; Tan, Andy S. L.; Kybert-Momjian, Ani; Liu, Jiaying; Hornik, Robert

    2016-01-01

    Several message topic selection approaches propose that messages based on beliefs pretested and found to be more strongly associated with intentions will be more effective in changing population intentions and behaviors when used in a campaign. This study aimed to validate the underlying causal assumption of these approaches which rely on cross-sectional belief–intention associations. We experimentally tested whether messages addressing promising themes as identified by the above criterion were more persuasive than messages addressing less promising themes. Contrary to expectations, all messages increased intentions. Interestingly, mediation analyses showed that while messages deemed promising affected intentions through changes in targeted promising beliefs, messages deemed less promising also achieved persuasion by influencing nontargeted promising beliefs. Implications for message topic selection are discussed. PMID:27867218

  7. ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

    Institute of Scientific and Technical Information of China (English)

    X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

    2003-01-01

    An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

  8. Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.

    Science.gov (United States)

    Wang, Xiao; Li, Guo-Zheng

    2013-03-12

    Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multi-location proteins to multiple proteins with single location, which doesn't take correlations among different subcellular locations into account. In this paper, a novel method named RALS (multi-label learning via RAndom Label Selection), is proposed to learn from multi-location proteins in an effective and efficient way. Through five-fold cross validation test on a benchmark dataset, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark datasets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multi-locations of proteins. The prediction web server is available at http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.

  9. Pseudo random number generator based on quantum chaotic map

    Science.gov (United States)

    Akhshani, A.; Akhavan, A.; Mobaraki, A.; Lim, S.-C.; Hassan, Z.

    2014-01-01

    For many years dissipative quantum maps were widely used as informative models of quantum chaos. In this paper, a new scheme for generating good pseudo-random numbers (PRNG), based on quantum logistic map is proposed. Note that the PRNG merely relies on the equations used in the quantum chaotic map. The algorithm is not complex, which does not impose high requirement on computer hardware and thus computation speed is fast. In order to face the challenge of using the proposed PRNG in quantum cryptography and other practical applications, the proposed PRNG is subjected to statistical tests using well-known test suites such as NIST, DIEHARD, ENT and TestU01. The results of the statistical tests were promising, as the proposed PRNG successfully passed all these tests. Moreover, the degree of non-periodicity of the chaotic sequences of the quantum map is investigated through the Scale index technique. The obtained result shows that, the sequence is more non-periodic. From these results it can be concluded that, the new scheme can generate a high percentage of usable pseudo-random numbers for simulation and other applications in scientific computing.

  10. Motifs in triadic random graphs based on Steiner triple systems

    Science.gov (United States)

    Winkler, Marco; Reichardt, Jörg

    2013-08-01

    Conventionally, pairwise relationships between nodes are considered to be the fundamental building blocks of complex networks. However, over the last decade, the overabundance of certain subnetwork patterns, i.e., the so-called motifs, has attracted much attention. It has been hypothesized that these motifs, instead of links, serve as the building blocks of network structures. Although the relation between a network's topology and the general properties of the system, such as its function, its robustness against perturbations, or its efficiency in spreading information, is the central theme of network science, there is still a lack of sound generative models needed for testing the functional role of subgraph motifs. Our work aims to overcome this limitation. We employ the framework of exponential random graph models (ERGMs) to define models based on triadic substructures. The fact that only a small portion of triads can actually be set independently poses a challenge for the formulation of such models. To overcome this obstacle, we use Steiner triple systems (STSs). These are partitions of sets of nodes into pair-disjoint triads, which thus can be specified independently. Combining the concepts of ERGMs and STSs, we suggest generative models capable of generating ensembles of networks with nontrivial triadic Z-score profiles. Further, we discover inevitable correlations between the abundance of triad patterns, which occur solely for statistical reasons and need to be taken into account when discussing the functional implications of motif statistics. Moreover, we calculate the degree distributions of our triadic random graphs analytically.

  11. Selection of components based on their importance

    International Nuclear Information System (INIS)

    Stvan, F.

    2004-12-01

    A proposal is presented for sorting components of the Dukovany nuclear power plant with respect to their importance. The classification scheme includes property priority, property criticality and property structure. Each area has its criteria with weight coefficients to calculate the importance of each component by the Risk Priority Number method. The aim of the process is to generate a list of components in order of operating and safety importance, which will help spend funds to ensure operation and safety in an optimal manner. This proposal is linked to a proposal for a simple database which should serve to enter information and perform assessments. The present stage focused on a safety assessment of components categorized in safety classes BT1, BT2 and BT3 pursuant to Decree No. 76. Assessment was performed based ona PSE study for Level 1. The database includes inputs for entering financial data, which are represented by a potential damage resulting from the given failure and by the loss of MWh in financial terms. In a next input, the failure incidence intensity and time of correction can be entered. Information regarding the property structure, represented by the degree of backup and reparability of the component, is the last input available

  12. Maximum relevance, minimum redundancy band selection based on neighborhood rough set for hyperspectral data classification

    International Nuclear Information System (INIS)

    Liu, Yao; Chen, Yuehua; Tan, Kezhu; Xie, Hong; Wang, Liguo; Xie, Wu; Yan, Xiaozhen; Xu, Zhen

    2016-01-01

    Band selection is considered to be an important processing step in handling hyperspectral data. In this work, we selected informative bands according to the maximal relevance minimal redundancy (MRMR) criterion based on neighborhood mutual information. Two measures MRMR difference and MRMR quotient were defined and a forward greedy search for band selection was constructed. The performance of the proposed algorithm, along with a comparison with other methods (neighborhood dependency measure based algorithm, genetic algorithm and uninformative variable elimination algorithm), was studied using the classification accuracy of extreme learning machine (ELM) and random forests (RF) classifiers on soybeans’ hyperspectral datasets. The results show that the proposed MRMR algorithm leads to promising improvement in band selection and classification accuracy. (paper)

  13. Generative Learning Objects Instantiated with Random Numbers Based Expressions

    Directory of Open Access Journals (Sweden)

    Ciprian Bogdan Chirila

    2015-12-01

    Full Text Available The development of interactive e-learning content requires special skills like programming techniques, web integration, graphic design etc. Generally, online educators do not possess such skills and their e-learning products tend to be static like presentation slides and textbooks. In this paper we propose a new interactive model of generative learning objects as a compromise betweenstatic, dull materials and dynamic, complex software e-learning materials developed by specialized teams. We find that random numbers based automatic initialization learning objects increases content diversity, interactivity thus enabling learners’ engagement. The resulted learning object model is at a limited level of complexity related to special e-learning software, intuitive and capable of increasing learners’ interactivity, engagement and motivation through dynamic content. The approach was applied successfully on several computer programing disciplines.

  14. Information Gain Based Dimensionality Selection for Classifying Text Documents

    Energy Technology Data Exchange (ETDEWEB)

    Dumidu Wijayasekara; Milos Manic; Miles McQueen

    2013-06-01

    Selecting the optimal dimensions for various knowledge extraction applications is an essential component of data mining. Dimensionality selection techniques are utilized in classification applications to increase the classification accuracy and reduce the computational complexity. In text classification, where the dimensionality of the dataset is extremely high, dimensionality selection is even more important. This paper presents a novel, genetic algorithm based methodology, for dimensionality selection in text mining applications that utilizes information gain. The presented methodology uses information gain of each dimension to change the mutation probability of chromosomes dynamically. Since the information gain is calculated a priori, the computational complexity is not affected. The presented method was tested on a specific text classification problem and compared with conventional genetic algorithm based dimensionality selection. The results show an improvement of 3% in the true positives and 1.6% in the true negatives over conventional dimensionality selection methods.

  15. Fault diagnosis in spur gears based on genetic algorithm and random forest

    Science.gov (United States)

    Cerrada, Mariela; Zurita, Grover; Cabrera, Diego; Sánchez, René-Vinicio; Artés, Mariano; Li, Chuan

    2016-03-01

    There are growing demands for condition-based monitoring of gearboxes, and therefore new methods to improve the reliability, effectiveness, accuracy of the gear fault detection ought to be evaluated. Feature selection is still an important aspect in machine learning-based diagnosis in order to reach good performance of the diagnostic models. On the other hand, random forest classifiers are suitable models in industrial environments where large data-samples are not usually available for training such diagnostic models. The main aim of this research is to build up a robust system for the multi-class fault diagnosis in spur gears, by selecting the best set of condition parameters on time, frequency and time-frequency domains, which are extracted from vibration signals. The diagnostic system is performed by using genetic algorithms and a classifier based on random forest, in a supervised environment. The original set of condition parameters is reduced around 66% regarding the initial size by using genetic algorithms, and still get an acceptable classification precision over 97%. The approach is tested on real vibration signals by considering several fault classes, one of them being an incipient fault, under different running conditions of load and velocity.

  16. Multispectral iris recognition based on group selection and game theory

    Science.gov (United States)

    Ahmad, Foysal; Roy, Kaushik

    2017-05-01

    A commercially available iris recognition system uses only a narrow band of the near infrared spectrum (700-900 nm) while iris images captured in the wide range of 405 nm to 1550 nm offer potential benefits to enhance recognition performance of an iris biometric system. The novelty of this research is that a group selection algorithm based on coalition game theory is explored to select the best patch subsets. In this algorithm, patches are divided into several groups based on their maximum contribution in different groups. Shapley values are used to evaluate the contribution of patches in different groups. Results show that this group selection based iris recognition

  17. Pseudo-Random Number Generator Based on Coupled Map Lattices

    Science.gov (United States)

    Lü, Huaping; Wang, Shihong; Hu, Gang

    A one-way coupled chaotic map lattice is used for generating pseudo-random numbers. It is shown that with suitable cooperative applications of both chaotic and conventional approaches, the output of the spatiotemporally chaotic system can easily meet the practical requirements of random numbers, i.e., excellent random statistical properties, long periodicity of computer realizations, and fast speed of random number generations. This pseudo-random number generator system can be used as ideal synchronous and self-synchronizing stream cipher systems for secure communications.

  18. The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation

    International Nuclear Information System (INIS)

    Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom

    2015-01-01

    The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy

  19. Bayesian dose selection design for a binary outcome using restricted response adaptive randomization.

    Science.gov (United States)

    Meinzer, Caitlyn; Martin, Renee; Suarez, Jose I

    2017-09-08

    In phase II trials, the most efficacious dose is usually not known. Moreover, given limited resources, it is difficult to robustly identify a dose while also testing for a signal of efficacy that would support a phase III trial. Recent designs have sought to be more efficient by exploring multiple doses through the use of adaptive strategies. However, the added flexibility may potentially increase the risk of making incorrect assumptions and reduce the total amount of information available across the dose range as a function of imbalanced sample size. To balance these challenges, a novel placebo-controlled design is presented in which a restricted Bayesian response adaptive randomization (RAR) is used to allocate a majority of subjects to the optimal dose of active drug, defined as the dose with the lowest probability of poor outcome. However, the allocation between subjects who receive active drug or placebo is held constant to retain the maximum possible power for a hypothesis test of overall efficacy comparing the optimal dose to placebo. The design properties and optimization of the design are presented in the context of a phase II trial for subarachnoid hemorrhage. For a fixed total sample size, a trade-off exists between the ability to select the optimal dose and the probability of rejecting the null hypothesis. This relationship is modified by the allocation ratio between active and control subjects, the choice of RAR algorithm, and the number of subjects allocated to an initial fixed allocation period. While a responsive RAR algorithm improves the ability to select the correct dose, there is an increased risk of assigning more subjects to a worse arm as a function of ephemeral trends in the data. A subarachnoid treatment trial is used to illustrate how this design can be customized for specific objectives and available data. Bayesian adaptive designs are a flexible approach to addressing multiple questions surrounding the optimal dose for treatment efficacy

  20. 44 CFR 321.2 - Selection of the mobilization base.

    Science.gov (United States)

    2010-10-01

    ... base. 321.2 Section 321.2 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY PREPAREDNESS MAINTENANCE OF THE MOBILIZATION BASE (DEPARTMENT OF DEFENSE, DEPARTMENT OF ENERGY, MARITIME ADMINISTRATION) § 321.2 Selection of the mobilization base. (a) The Department...

  1. Rich: Region-based Intelligent Cluster-Head Selection and Node Deployment Strategy in Concentric-based WSNs

    Directory of Open Access Journals (Sweden)

    FAN, C.-S.

    2013-11-01

    Full Text Available In a random deployment, sensor nodes are scattered randomly in the sensing field. Hence, the coverage can not be guaranteed. In contrast, the coverage of uniformly deployment is in general larger than the random deployment. However, uniformly deployment strategy may cause unbalanced traffic pattern in wireless sensor networks (WSNs. In this situation, larger load may be imposed to CHs (cluster heads around the sink. Therefore, CHs close to the sink use up their energy earlier than those farther away from the sink. To overcome this problem, we propose a novel node deployment strategy in the concentric model, namely, Region-based Intelligent Cluster-Head selection and node deployment strategy (called Rich. The coverage, energy consumption and data routing issues are well investigated and taken into consideration in the proposed Rich scheme. The simulation results show that the proposed Rich alleviates the unbalanced traffic pattern significantly, prolongs network lifetime and achieves satisfactory coverage ratio.

  2. Peculiarities of the statistics of spectrally selected fluorescence radiation in laser-pumped dye-doped random media

    Science.gov (United States)

    Yuvchenko, S. A.; Ushakova, E. V.; Pavlova, M. V.; Alonova, M. V.; Zimnyakov, D. A.

    2018-04-01

    We consider the practical realization of a new optical probe method of the random media which is defined as the reference-free path length interferometry with the intensity moments analysis. A peculiarity in the statistics of the spectrally selected fluorescence radiation in laser-pumped dye-doped random medium is discussed. Previously established correlations between the second- and the third-order moments of the intensity fluctuations in the random interference patterns, the coherence function of the probe radiation, and the path difference probability density for the interfering partial waves in the medium are confirmed. The correlations were verified using the statistical analysis of the spectrally selected fluorescence radiation emitted by a laser-pumped dye-doped random medium. Water solution of Rhodamine 6G was applied as the doping fluorescent agent for the ensembles of the densely packed silica grains, which were pumped by the 532 nm radiation of a solid state laser. The spectrum of the mean path length for a random medium was reconstructed.

  3. IMAGE SEGMENTATION BASED ON MARKOV RANDOM FIELD AND WATERSHED TECHNIQUES

    Institute of Scientific and Technical Information of China (English)

    纳瑟; 刘重庆

    2002-01-01

    This paper presented a method that incorporates Markov Random Field(MRF), watershed segmentation and merging techniques for performing image segmentation and edge detection tasks. MRF is used to obtain an initial estimate of x regions in the image under process where in MRF model, gray level x, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The process needs an initial segmented result. An initial segmentation is got based on K-means clustering technique and the minimum distance, then the region process in modeled by MRF to obtain an image contains different intensity regions. Starting from this we calculate the gradient values of that image and then employ a watershed technique. When using MRF method it obtains an image that has different intensity regions and has all the edge and region information, then it improves the segmentation result by superimpose closed and an accurate boundary of each region using watershed algorithm. After all pixels of the segmented regions have been processed, a map of primitive region with edges is generated. Finally, a merge process based on averaged mean values is employed. The final segmentation and edge detection result is one closed boundary per actual region in the image.

  4. Capturing the Flatness of a peer-to-peer lending network through random and selected perturbations

    Science.gov (United States)

    Karampourniotis, Panagiotis D.; Singh, Pramesh; Uparna, Jayaram; Horvat, Emoke-Agnes; Szymanski, Boleslaw K.; Korniss, Gyorgy; Bakdash, Jonathan Z.; Uzzi, Brian

    Null models are established tools that have been used in network analysis to uncover various structural patterns. They quantify the deviance of an observed network measure to that given by the null model. We construct a null model for weighted, directed networks to identify biased links (carrying significantly different weights than expected according to the null model) and thus quantify the flatness of the system. Using this model, we study the flatness of Kiva, a large international crownfinancing network of borrowers and lenders, aggregated to the country level. The dataset spans the years from 2006 to 2013. Our longitudinal analysis shows that flatness of the system is reducing over time, meaning the proportion of biased inter-country links is growing. We extend our analysis by testing the robustness of the flatness of the network in perturbations on the links' weights or the nodes themselves. Examples of such perturbations are event shocks (e.g. erecting walls) or regulatory shocks (e.g. Brexit). We find that flatness is unaffected by random shocks, but changes after shocks target links with a large weight or bias. The methods we use to capture the flatness are based on analytics, simulations, and numerical computations using Shannon's maximum entropy. Supported by ARL NS-CTA.

  5. Selection of examples in case-based computer-aided decision systems

    International Nuclear Information System (INIS)

    Mazurowski, Maciej A; Zurada, Jacek M; Tourassi, Georgia D

    2008-01-01

    Case-based computer-aided decision (CB-CAD) systems rely on a database of previously stored, known examples when classifying new, incoming queries. Such systems can be particularly useful since they do not need retraining every time a new example is deposited in the case base. The adaptive nature of case-based systems is well suited to the current trend of continuously expanding digital databases in the medical domain. To maintain efficiency, however, such systems need sophisticated strategies to effectively manage the available evidence database. In this paper, we discuss the general problem of building an evidence database by selecting the most useful examples to store while satisfying existing storage requirements. We evaluate three intelligent techniques for this purpose: genetic algorithm-based selection, greedy selection and random mutation hill climbing. These techniques are compared to a random selection strategy used as the baseline. The study is performed with a previously presented CB-CAD system applied for false positive reduction in screening mammograms. The experimental evaluation shows that when the development goal is to maximize the system's diagnostic performance, the intelligent techniques are able to reduce the size of the evidence database to 37% of the original database by eliminating superfluous and/or detrimental examples while at the same time significantly improving the CAD system's performance. Furthermore, if the case-base size is a main concern, the total number of examples stored in the system can be reduced to only 2-4% of the original database without a decrease in the diagnostic performance. Comparison of the techniques shows that random mutation hill climbing provides the best balance between the diagnostic performance and computational efficiency when building the evidence database of the CB-CAD system.

  6. Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection

    Directory of Open Access Journals (Sweden)

    Jaesung Lee

    2016-11-01

    Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

  7. Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF

    Directory of Open Access Journals (Sweden)

    Yu Ding

    2018-01-01

    Full Text Available Playing an important role in electromechanical systems, hydraulic servo system is crucial to mechanical systems like engineering machinery, metallurgical machinery, ships, and other equipment. Fault diagnosis based on monitoring and sensory signals plays an important role in avoiding catastrophic accidents and enormous economic losses. This study presents a fault diagnosis scheme for hydraulic servo system using compressed random subspace based ReliefF (CRSR method. From the point of view of feature selection, the scheme utilizes CRSR method to determine the most stable feature combination that contains the most adequate information simultaneously. Based on the feature selection structure of ReliefF, CRSR employs feature integration rules in the compressed domain. Meanwhile, CRSR substitutes information entropy and fuzzy membership for traditional distance measurement index. The proposed CRSR method is able to enhance the robustness of the feature information against interference while selecting the feature combination with balanced information expressing ability. To demonstrate the effectiveness of the proposed CRSR method, a hydraulic servo system joint simulation model is constructed by HyPneu and Simulink, and three fault modes are injected to generate the validation data.

  8. Selective serotonin reuptake inhibitors (SSRIs) for post-partum depression (PPD): a systematic review of randomized clinical trials.

    Science.gov (United States)

    De Crescenzo, Franco; Perelli, Federica; Armando, Marco; Vicari, Stefano

    2014-01-01

    The treatment of postpartum depression with selective serotonin reuptake inhibitors (SSRIs) has been claimed to be both efficacious and well tolerated, but no recent systematic reviews have been conducted. A qualitative systematic review of randomized clinical trials on women with postpartum depression comparing SSRIs to placebo and/or other treatments was performed. A comprehensive literature search of online databases, the bibliographies of published articles and grey literature were conducted. Data on efficacy, acceptability and tolerability were extracted and the quality of the trials was assessed. Six randomised clinical trials, comprising 595 patients, met quality criteria for inclusion in the analysis. Cognitive-behavioural intervention, psychosocial community-based intervention, psychodynamic therapy, cognitive behavioural therapy, a second-generation tricyclic antidepressant and placebo were used as comparisons. All studies demonstrated higher response and remission rates among those treated with SSRIs and greater mean changes on depression scales, although findings were not always statistically significant. Dropout rates were high in three of the trials but similar among treatment and comparison groups. In general, SSRIs were well tolerated and trial quality was good. There are few trials, patients included in the trials were not representative of all patients with postpartum depression, dropout rates in three trials were high, and long-term efficacy and tolerability were assessed in only two trials. SSRIs appear to be efficacious and well tolerated in the treatment of postpartum depression, but the available evidence fails to demonstrate a clear superiority over other treatments. © 2013 Elsevier B.V. All rights reserved.

  9. Microbiota-based Signature of Gingivitis Treatments: A Randomized Study.

    Science.gov (United States)

    Huang, Shi; Li, Zhen; He, Tao; Bo, Cunpei; Chang, Jinlan; Li, Lin; He, Yanyan; Liu, Jiquan; Charbonneau, Duane; Li, Rui; Xu, Jian

    2016-04-20

    Plaque-induced gingivitis can be alleviated by various treatment regimens. To probe the impacts of various anti-gingivitis treatments on plaque microflora, here a double blinded, randomized controlled trial of 91 adults with moderate gingivitis was designed with two anti-gingivitis regimens: the brush-alone treatment and the brush-plus-rinse treatment. In the later group, more reduction in both Plaque Index (TMQHI) and Gingival Index (mean MGI) at Day 3, Day 11 and Day 27 was evident, and more dramatic changes were found between baseline and other time points for both supragingival plaque microbiota structure and salivary metabonomic profiles. A comparison of plaque microbiota changes was also performed between these two treatments and a third dataset where 50 subjects received regimen of dental scaling. Only Actinobaculum, TM7 and Leptotrichia were consistently reduced by all the three treatments, whereas the different microbial signatures of the three treatments during gingivitis relieve indicate distinct mechanisms of action. Our study suggests that microbiota based signatures can serve as a valuable approach for understanding and potentially comparing the modes of action for clinical treatments and oral-care products in the future.

  10. Greater fruit selection following an appearance-based compared with a health-based health promotion poster

    Science.gov (United States)

    2016-01-01

    Abstract Background This study investigated the impact of an appearance-based compared with a traditional health-based public health message for healthy eating. Methods A total of 166 British University students (41 males; aged 20.6 ± 1.9 years) were randomized to view either an appearance-based (n = 82) or a health-based (n = 84) fruit promotion poster. Intentions to consume fruit and immediate fruit selection (laboratory observation) were assessed immediately after poster viewing, and subsequent self-report fruit consumption was assessed 3 days later. Results Intentions to consume fruit were not predicted by poster type (largest β = 0.03, P = 0.68) but were associated with fruit-based liking, past consumption, attitudes and social norms (smallest β = 0.16, P = 0.04). Immediate fruit selection was greater following the appearance-based compared with the health-based poster (β = −0.24, P poster (β = −0.22, P = 0.03), but this effect became non-significant on consideration of participant characteristics (β = −0.15, P = 0.13), and was instead associated with fruit-based liking and past consumption (smallest β = 0.24, P = 0.03). Conclusions These findings demonstrate the clear value of an appearance-based compared with a health-based health promotion poster for increasing fruit selection. A distinction between outcome measures and the value of a behavioural measure is also demonstrated. PMID:28158693

  11. Development of Base Transceiver Station Selection Algorithm for ...

    African Journals Online (AJOL)

    TEMS) equipment was carried out on the existing BTSs, and a linear algorithm optimization program based on the spectral link efficiency of each BTS was developed, the output of this site optimization gives the selected number of base station sites ...

  12. Enhancing Security of Double Random Phase Encoding Based on Random S-Box

    Science.gov (United States)

    Girija, R.; Singh, Hukum

    2018-06-01

    In this paper, we propose a novel asymmetric cryptosystem for double random phase encoding (DRPE) using random S-Box. While utilising S-Box separately is not reliable and DRPE does not support non-linearity, so, our system unites the effectiveness of S-Box with an asymmetric system of DRPE (through Fourier transform). The uniqueness of proposed cryptosystem lies on employing high sensitivity dynamic S-Box for our DRPE system. The randomness and scalability achieved due to applied technique is an additional feature of the proposed solution. The firmness of random S-Box is investigated in terms of performance parameters such as non-linearity, strict avalanche criterion, bit independence criterion, linear and differential approximation probabilities etc. S-Boxes convey nonlinearity to cryptosystems which is a significant parameter and very essential for DRPE. The strength of proposed cryptosystem has been analysed using various parameters such as MSE, PSNR, correlation coefficient analysis, noise analysis, SVD analysis, etc. Experimental results are conferred in detail to exhibit proposed cryptosystem is highly secure.

  13. The basic science and mathematics of random mutation and natural selection.

    Science.gov (United States)

    Kleinman, Alan

    2014-12-20

    The mutation and natural selection phenomenon can and often does cause the failure of antimicrobial, herbicidal, pesticide and cancer treatments selection pressures. This phenomenon operates in a mathematically predictable behavior, which when understood leads to approaches to reduce and prevent the failure of the use of these selection pressures. The mathematical behavior of mutation and selection is derived using the principles given by probability theory. The derivation of the equations describing the mutation and selection phenomenon is carried out in the context of an empirical example. Copyright © 2014 John Wiley & Sons, Ltd.

  14. Supplier selection based on multi-criterial AHP method

    Directory of Open Access Journals (Sweden)

    Jana Pócsová

    2010-03-01

    Full Text Available This paper describes a case-study of supplier selection based on multi-criterial Analytic Hierarchy Process (AHP method.It is demonstrated that using adequate mathematical method can bring us “unprejudiced” conclusion, even if the alternatives (suppliercompanies are very similar in given selection-criteria. The result is the best possible supplier company from the viewpoint of chosen criteriaand the price of the product.

  15. Personnel Selection Method Based on Personnel-Job Matching

    OpenAIRE

    Li Wang; Xilin Hou; Lili Zhang

    2013-01-01

    The existing personnel selection decisions in practice are based on the evaluation of job seeker's human capital, and it may be difficult to make personnel-job matching and make each party satisfy. Therefore, this paper puts forward a new personnel selection method by consideration of bilateral matching. Starting from the employment thoughts of ¡°satisfy¡±, the satisfaction evaluation indicator system of each party are constructed. The multi-objective optimization model is given according to ...

  16. Construction Tender Subcontract Selection using Case-based Reasoning

    Directory of Open Access Journals (Sweden)

    Due Luu

    2012-11-01

    Full Text Available Obtaining competitive quotations from suitably qualified subcontractors at tender tim n significantly increase the chance of w1nmng a construction project. Amidst an increasingly growing trend to subcontracting in Australia, selecting appropriate subcontractors for a construction project can be a daunting task requiring the analysis of complex and dynamic criteria such as past performance, suitable experience, track record of competitive pricing, financial stability and so on. Subcontractor selection is plagued with uncertainty and vagueness and these conditions are difficul_t o represent in generalised sets of rules. DeciSIOns pertaining to the selection of subcontr:act?s tender time are usually based on the mtu1t1onand past experience of construction estimators. Case-based reasoning (CBR may be an appropriate method of addressing the chal_lenges of selecting subcontractors because CBR 1s able to harness the experiential knowledge of practitioners. This paper reviews the practicality and suitability of a CBR approach for subcontractor tender selection through the development of a prototype CBR procurement advisory system. In this system, subcontractor selection cases are represented by a set of attributes elicited from experienced construction estimators. The results indicate that CBR can enhance the appropriateness of the selection of subcontractors for construction projects.

  17. Cooperative Technique Based on Sensor Selection in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    ISLAM, M. R.

    2009-02-01

    Full Text Available An energy efficient cooperative technique is proposed for the IEEE 1451 based Wireless Sensor Networks. Selected numbers of Wireless Transducer Interface Modules (WTIMs are used to form a Multiple Input Single Output (MISO structure wirelessly connected with a Network Capable Application Processor (NCAP. Energy efficiency and delay of the proposed architecture are derived for different combination of cluster size and selected number of WTIMs. Optimized constellation parameters are used for evaluating derived parameters. The results show that the selected MISO structure outperforms the unselected MISO structure and it shows energy efficient performance than SISO structure after a certain distance.

  18. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

    Science.gov (United States)

    Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

    2017-01-01

    Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  19. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    Directory of Open Access Journals (Sweden)

    Jun-He Yang

    2017-01-01

    Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  20. Knowledge based expert system approach to instrumentation selection (INSEL

    Directory of Open Access Journals (Sweden)

    S. Barai

    2004-08-01

    Full Text Available The selection of appropriate instrumentation for any structural measurement of civil engineering structure is a complex task. Recent developments in Artificial Intelligence (AI can help in an organized use of experiential knowledge available on instrumentation for laboratory and in-situ measurement. Usually, the instrumentation decision is based on the experience and judgment of experimentalists. The heuristic knowledge available for different types of measurement is domain dependent and the information is scattered in varied knowledge sources. The knowledge engineering techniques can help in capturing the experiential knowledge. This paper demonstrates a prototype knowledge based system for INstrument SELection (INSEL assistant where the experiential knowledge for various structural domains can be captured and utilized for making instrumentation decision. In particular, this Knowledge Based Expert System (KBES encodes the heuristics on measurement and demonstrates the instrument selection process with reference to steel bridges. INSEL runs on a microcomputer and uses an INSIGHT 2+ environment.

  1. Diversified models for portfolio selection based on uncertain semivariance

    Science.gov (United States)

    Chen, Lin; Peng, Jin; Zhang, Bo; Rosyida, Isnaini

    2017-02-01

    Since the financial markets are complex, sometimes the future security returns are represented mainly based on experts' estimations due to lack of historical data. This paper proposes a semivariance method for diversified portfolio selection, in which the security returns are given subjective to experts' estimations and depicted as uncertain variables. In the paper, three properties of the semivariance of uncertain variables are verified. Based on the concept of semivariance of uncertain variables, two types of mean-semivariance diversified models for uncertain portfolio selection are proposed. Since the models are complex, a hybrid intelligent algorithm which is based on 99-method and genetic algorithm is designed to solve the models. In this hybrid intelligent algorithm, 99-method is applied to compute the expected value and semivariance of uncertain variables, and genetic algorithm is employed to seek the best allocation plan for portfolio selection. At last, several numerical examples are presented to illustrate the modelling idea and the effectiveness of the algorithm.

  2. Comparative analysis of instance selection algorithms for instance-based classifiers in the context of medical decision support

    International Nuclear Information System (INIS)

    Mazurowski, Maciej A; Tourassi, Georgia D; Malof, Jordan M

    2011-01-01

    When constructing a pattern classifier, it is important to make best use of the instances (a.k.a. cases, examples, patterns or prototypes) available for its development. In this paper we present an extensive comparative analysis of algorithms that, given a pool of previously acquired instances, attempt to select those that will be the most effective to construct an instance-based classifier in terms of classification performance, time efficiency and storage requirements. We evaluate seven previously proposed instance selection algorithms and compare their performance to simple random selection of instances. We perform the evaluation using k-nearest neighbor classifier and three classification problems: one with simulated Gaussian data and two based on clinical databases for breast cancer detection and diagnosis, respectively. Finally, we evaluate the impact of the number of instances available for selection on the performance of the selection algorithms and conduct initial analysis of the selected instances. The experiments show that for all investigated classification problems, it was possible to reduce the size of the original development dataset to less than 3% of its initial size while maintaining or improving the classification performance. Random mutation hill climbing emerges as the superior selection algorithm. Furthermore, we show that some previously proposed algorithms perform worse than random selection. Regarding the impact of the number of instances available for the classifier development on the performance of the selection algorithms, we confirm that the selection algorithms are generally more effective as the pool of available instances increases. In conclusion, instance selection is generally beneficial for instance-based classifiers as it can improve their performance, reduce their storage requirements and improve their response time. However, choosing the right selection algorithm is crucial.

  3. An optical authentication system based on imaging of excitation-selected lanthanide luminescence.

    Science.gov (United States)

    Carro-Temboury, Miguel R; Arppe, Riikka; Vosch, Tom; Sørensen, Thomas Just

    2018-01-01

    Secure data encryption relies heavily on one-way functions, and copy protection relies on features that are difficult to reproduce. We present an optical authentication system based on lanthanide luminescence from physical one-way functions or physical unclonable functions (PUFs). They cannot be reproduced and thus enable unbreakable encryption. Further, PUFs will prevent counterfeiting if tags with unique PUFs are grafted onto products. We have developed an authentication system that comprises a hardware reader, image analysis, and authentication software and physical keys that we demonstrate as an anticounterfeiting system. The physical keys are PUFs made from random patterns of taggants in polymer films on glass that can be imaged following selected excitation of particular lanthanide(III) ions doped into the individual taggants. This form of excitation-selected imaging ensures that by using at least two lanthanide(III) ion dopants, the random patterns cannot be copied, because the excitation selection will fail when using any other emitter. With the developed reader and software, the random patterns are read and digitized, which allows a digital pattern to be stored. This digital pattern or digital key can be used to authenticate the physical key in anticounterfeiting or to encrypt any message. The PUF key was produced with a staggering nominal encoding capacity of 7 3600 . Although the encoding capacity of the realized authentication system reduces to 6 × 10 104 , it is more than sufficient to completely preclude counterfeiting of products.

  4. Bearing Fault Classification Based on Conditional Random Field

    Directory of Open Access Journals (Sweden)

    Guofeng Wang

    2013-01-01

    Full Text Available Condition monitoring of rolling element bearing is paramount for predicting the lifetime and performing effective maintenance of the mechanical equipment. To overcome the drawbacks of the hidden Markov model (HMM and improve the diagnosis accuracy, conditional random field (CRF model based classifier is proposed. In this model, the feature vectors sequences and the fault categories are linked by an undirected graphical model in which their relationship is represented by a global conditional probability distribution. In comparison with the HMM, the main advantage of the CRF model is that it can depict the temporal dynamic information between the observation sequences and state sequences without assuming the independence of the input feature vectors. Therefore, the interrelationship between the adjacent observation vectors can also be depicted and integrated into the model, which makes the classifier more robust and accurate than the HMM. To evaluate the effectiveness of the proposed method, four kinds of bearing vibration signals which correspond to normal, inner race pit, outer race pit and roller pit respectively are collected from the test rig. And the CRF and HMM models are built respectively to perform fault classification by taking the sub band energy features of wavelet packet decomposition (WPD as the observation sequences. Moreover, K-fold cross validation method is adopted to improve the evaluation accuracy of the classifier. The analysis and comparison under different fold times show that the accuracy rate of classification using the CRF model is higher than the HMM. This method brings some new lights on the accurate classification of the bearing faults.

  5. Non-Random Inversion Landscapes in Prokaryotic Genomes Are Shaped by Heterogeneous Selection Pressures.

    Science.gov (United States)

    Repar, Jelena; Warnecke, Tobias

    2017-08-01

    Inversions are a major contributor to structural genome evolution in prokaryotes. Here, using a novel alignment-based method, we systematically compare 1,651 bacterial and 98 archaeal genomes to show that inversion landscapes are frequently biased toward (symmetric) inversions around the origin-terminus axis. However, symmetric inversion bias is not a universal feature of prokaryotic genome evolution but varies considerably across clades. At the extremes, inversion landscapes in Bacillus-Clostridium and Actinobacteria are dominated by symmetric inversions, while there is little or no systematic bias favoring symmetric rearrangements in archaea with a single origin of replication. Within clades, we find strong but clade-specific relationships between symmetric inversion bias and different features of adaptive genome architecture, including the distance of essential genes to the origin of replication and the preferential localization of genes on the leading strand. We suggest that heterogeneous selection pressures have converged to produce similar patterns of structural genome evolution across prokaryotes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  6. Performance-Based Technology Selection Filter description report

    International Nuclear Information System (INIS)

    O'Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

    1992-05-01

    A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL)

  7. Performance-Based Technology Selection Filter description report

    Energy Technology Data Exchange (ETDEWEB)

    O' Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

    1992-05-01

    A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL).

  8. Selecting for Fast Protein-Protein Association As Demonstrated on a Random TEM1 Yeast Library Binding BLIP.

    Science.gov (United States)

    Cohen-Khait, Ruth; Schreiber, Gideon

    2018-04-27

    Protein-protein interactions mediate the vast majority of cellular processes. Though protein interactions obey basic chemical principles also within the cell, the in vivo physiological environment may not allow for equilibrium to be reached. Thus, in vitro measured thermodynamic affinity may not provide a complete picture of protein interactions in the biological context. Binding kinetics composed of the association and dissociation rate constants are relevant and important in the cell. Therefore, changes in protein-protein interaction kinetics have a significant impact on the in vivo activity of the proteins. The common protocol for the selection of tighter binders from a mutant library selects for protein complexes with slower dissociation rate constants. Here we describe a method to specifically select for variants with faster association rate constants by using pre-equilibrium selection, starting from a large random library. Toward this end, we refine the selection conditions of a TEM1-β-lactamase library against its natural nanomolar affinity binder β-lactamase inhibitor protein (BLIP). The optimal selection conditions depend on the ligand concentration and on the incubation time. In addition, we show that a second sort of the library helps to separate signal from noise, resulting in a higher percent of faster binders in the selected library. Fast associating protein variants are of particular interest for drug development and other biotechnological applications.

  9. Dynamic approach to space and habitat use based on biased random bridges.

    Directory of Open Access Journals (Sweden)

    Simon Benhamou

    Full Text Available BACKGROUND: Although habitat use reflects a dynamic process, most studies assess habitat use statically as if an animal's successively recorded locations reflected a point rather than a movement process. By relying on the activity time between successive locations instead of the local density of individual locations, movement-based methods can substantially improve the biological relevance of utilization distribution (UD estimates (i.e. the relative frequencies with which an animal uses the various areas of its home range, HR. One such method rests on Brownian bridges (BBs. Its theoretical foundation (purely and constantly diffusive movements is paradoxically inconsistent with both HR settlement and habitat selection. An alternative involves movement-based kernel density estimation (MKDE through location interpolation, which may be applied to various movement behaviours but lacks a sound theoretical basis. METHODOLOGY/PRINCIPAL FINDINGS: I introduce the concept of a biased random (advective-diffusive bridge (BRB and show that the MKDE method is a practical means to estimate UDs based on simplified (isotropically diffusive BRBs. The equation governing BRBs is constrained by the maximum delay between successive relocations warranting constant within-bridge advection (allowed to vary between bridges but remains otherwise similar to the BB equation. Despite its theoretical inconsistencies, the BB method can therefore be applied to animals that regularly reorientate within their HRs and adapt their movements to the habitats crossed, provided that they were relocated with a high enough frequency. CONCLUSIONS/SIGNIFICANCE: Biased random walks can approximate various movement types at short times from a given relocation. Their simplified form constitutes an effective trade-off between too simple, unrealistic movement models, such as Brownian motion, and more sophisticated and realistic ones, such as biased correlated random walks (BCRWs, which are too

  10. The sequence relay selection strategy based on stochastic dynamic programming

    Science.gov (United States)

    Zhu, Rui; Chen, Xihao; Huang, Yangchao

    2017-07-01

    Relay-assisted (RA) network with relay node selection is a kind of effective method to improve the channel capacity and convergence performance. However, most of the existing researches about the relay selection did not consider the statically channel state information and the selection cost. This shortage limited the performance and application of RA network in practical scenarios. In order to overcome this drawback, a sequence relay selection strategy (SRSS) was proposed. And the performance upper bound of SRSS was also analyzed in this paper. Furthermore, in order to make SRSS more practical, a novel threshold determination algorithm based on the stochastic dynamic program (SDP) was given to work with SRSS. Numerical results are also presented to exhibit the performance of SRSS with SDP.

  11. Multi-parameter sensor based on random fiber lasers

    Directory of Open Access Journals (Sweden)

    Yanping Xu

    2016-09-01

    Full Text Available We demonstrate a concept of utilizing random fiber lasers to achieve multi-parameter sensing. The proposed random fiber ring laser consists of an erbium-doped fiber as the gain medium and a random fiber grating as the feedback. The random feedback is effectively realized by a large number of reflections from around 50000 femtosecond laser induced refractive index modulation regions over a 10cm standard single mode fiber. Numerous polarization-dependent spectral filters are formed and superimposed to provide multiple lasing lines with high signal-to-noise ratio up to 40dB, which gives an access for a high-fidelity multi-parameter sensing scheme. The number of sensing parameters can be controlled by the number of the lasing lines via input polarizations and wavelength shifts of each peak can be explored for the simultaneous multi-parameter sensing with one sensing probe. In addition, the random grating induced coupling between core and cladding modes can be potentially used for liquid medical sample sensing in medical diagnostics, biology and remote sensing in hostile environments.

  12. A school-based randomized controlled trial to improve physical activity among Iranian high school girls

    Directory of Open Access Journals (Sweden)

    Ghofranipour Fazloalha

    2008-04-01

    Full Text Available Abstract Background Physical activity (PA rates decline precipitously during the high school years and are consistently lower among adolescent girls than adolescent boys. Due to cultural barriers, this problem might be exacerbated in female Iranian adolescents. However, little intervention research has been conducted to try to increase PA participation rates with this population. Because PA interventions in schools have the potential to reach many children and adolescents, this study reports on PA intervention research conducted in all-female Iranian high schools. Methods A randomized controlled trial was conducted to examine the effects of two six-month tailored interventions on potential determinants of PA and PA behavior. Students (N = 161 were randomly allocated to one of three conditions: an intervention based on Pender's Health Promotion model (HP, an intervention based on an integration of the health promotion model and selected constructs from the Transtheoretical model (THP, and a control group (CON. Measures were administered prior to the intervention, at post-intervention and at a six-month follow-up. Results Repeated measure ANOVAs showed a significant interaction between group and time for perceived benefits, self efficacy, interpersonal norms, social support, behavioral processes, and PA behavior, indicating that both intervention groups significantly improved across the 24-week intervention, whereas the control group did not. Participants in the THP group showed greater use of counter conditioning and stimulus control at post-intervention and at follow-up. While there were no significant differences in PA between the HP and CON groups at follow-up, a significant difference was still found between the THP and the CON group. Conclusion This study provides the first evidence of the effectiveness of a PA intervention based on Pender's HP model combined with selected aspects of the TTM on potential determinants to increase PA among

  13. Rank-based model selection for multiple ions quantum tomography

    International Nuclear Information System (INIS)

    Guţă, Mădălin; Kypraios, Theodore; Dryden, Ian

    2012-01-01

    The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the ‘sparsity’ properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods—the Akaike information criterion (AIC) and the Bayesian information criterion (BIC)—two models consisting of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of four ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a four ions experiment aimed at creating a Smolin state of rank 4. By applying the two methods together with the Pearson χ 2 test we conclude that the data can be suitably described with a model whose rank is between 7 and 9. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements. (paper)

  14. Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

    Science.gov (United States)

    Zeng, Xueqiang; Luo, Gang

    2017-12-01

    Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

  15. Sensitivity analysis for missing dichotomous outcome data in multi-visit randomized clinical trial with randomization-based covariance adjustment.

    Science.gov (United States)

    Li, Siying; Koch, Gary G; Preisser, John S; Lam, Diana; Sanchez-Kam, Matilde

    2017-01-01

    Dichotomous endpoints in clinical trials have only two possible outcomes, either directly or via categorization of an ordinal or continuous observation. It is common to have missing data for one or more visits during a multi-visit study. This paper presents a closed form method for sensitivity analysis of a randomized multi-visit clinical trial that possibly has missing not at random (MNAR) dichotomous data. Counts of missing data are redistributed to the favorable and unfavorable outcomes mathematically to address possibly informative missing data. Adjusted proportion estimates and their closed form covariance matrix estimates are provided. Treatment comparisons over time are addressed with Mantel-Haenszel adjustment for a stratification factor and/or randomization-based adjustment for baseline covariables. The application of such sensitivity analyses is illustrated with an example. An appendix outlines an extension of the methodology to ordinal endpoints.

  16. Modal Analysis Based on the Random Decrement Transform

    DEFF Research Database (Denmark)

    Asmussen, J. C.; Brincker, Rune; Ibrahim, S. R.

    of this paper is to present a state-of-the-art description of the Random Decrement technique where the statistical theory is outlined and examples are given. But also new results such as estimation of frequency response functions and quality assessment are introduced. Special attention is given......During the last years several papers utilizing the Random Decrement transform as a basis for extraction of modal parameters from the response of linear systems subjected to unknown ambient loads have been presented. Although the Random Decrement technique was developed in a decade starting from...... the introduktion in 1968 the technique seems still to be attractive. This is probably due to the simplicity and the speed of the algorithm and the fact that the theory of the technique has been extended by introducing statistical measures such as correlation functions or spectral densities. The purpose...

  17. Attribute based selection of thermoplastic resin for vacuum infusion process

    DEFF Research Database (Denmark)

    Prabhakaran, R.T. Durai; Lystrup, Aage; Løgstrup Andersen, Tom

    2011-01-01

    The composite industry looks toward a new material system (resins) based on thermoplastic polymers for the vacuum infusion process, similar to the infusion process using thermosetting polymers. A large number of thermoplastics are available in the market with a variety of properties suitable...... for different engineering applications, and few of those are available in a not yet polymerised form suitable for resin infusion. The proper selection of a new resin system among these thermoplastic polymers is a concern for manufactures in the current scenario and a special mathematical tool would...... be beneficial. In this paper, the authors introduce a new decision making tool for resin selection based on significant attributes. This article provides a broad overview of suitable thermoplastic material systems for vacuum infusion process available in today’s market. An illustrative example—resin selection...

  18. [Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

    Science.gov (United States)

    Zhou, Jinzhi; Tang, Xiaofang

    2015-08-01

    In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

  19. Intelligent Fault Diagnosis of HVCB with Feature Space Optimization-Based Random Forest.

    Science.gov (United States)

    Ma, Suliang; Chen, Mingxuan; Wu, Jianwen; Wang, Yuhao; Jia, Bowen; Jiang, Yuan

    2018-04-16

    Mechanical faults of high-voltage circuit breakers (HVCBs) always happen over long-term operation, so extracting the fault features and identifying the fault type have become a key issue for ensuring the security and reliability of power supply. Based on wavelet packet decomposition technology and random forest algorithm, an effective identification system was developed in this paper. First, compared with the incomplete description of Shannon entropy, the wavelet packet time-frequency energy rate (WTFER) was adopted as the input vector for the classifier model in the feature selection procedure. Then, a random forest classifier was used to diagnose the HVCB fault, assess the importance of the feature variable and optimize the feature space. Finally, the approach was verified based on actual HVCB vibration signals by considering six typical fault classes. The comparative experiment results show that the classification accuracy of the proposed method with the origin feature space reached 93.33% and reached up to 95.56% with optimized input feature vector of classifier. This indicates that feature optimization procedure is successful, and the proposed diagnosis algorithm has higher efficiency and robustness than traditional methods.

  20. An opinion formation based binary optimization approach for feature selection

    Science.gov (United States)

    Hamedmoghadam, Homayoun; Jalili, Mahdi; Yu, Xinghuo

    2018-02-01

    This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.

  1. Quantum random number generator based on quantum tunneling effect

    OpenAIRE

    Zhou, Haihan; Li, Junlin; Pan, Dong; Zhang, Weixing; Long, Guilu

    2017-01-01

    In this paper, we proposed an experimental implementation of quantum random number generator(QRNG) with inherent randomness of quantum tunneling effect of electrons. We exploited InGaAs/InP diodes, whose valance band and conduction band shared a quasi-constant energy barrier. We applied a bias voltage on the InGaAs/InP avalanche diode, which made the diode works under Geiger mode, and triggered the tunneling events with a periodic pulse. Finally, after data collection and post-processing, our...

  2. Utility based maintenance analysis using a Random Sign censoring model

    International Nuclear Information System (INIS)

    Andres Christen, J.; Ruggeri, Fabrizio; Villa, Enrique

    2011-01-01

    Industrial systems subject to failures are usually inspected when there are evident signs of an imminent failure. Maintenance is therefore performed at a random time, somehow dependent on the failure mechanism. A competing risk model, namely a Random Sign model, is considered to relate failure and maintenance times. We propose a novel Bayesian analysis of the model and apply it to actual data from a water pump in an oil refinery. The design of an optimal maintenance policy is then discussed under a formal decision theoretic approach, analyzing the goodness of the current maintenance policy and making decisions about the optimal maintenance time.

  3. Dose selection based on physiologically based pharmacokinetic (PBPK) approaches.

    Science.gov (United States)

    Jones, Hannah M; Mayawala, Kapil; Poulin, Patrick

    2013-04-01

    Physiologically based pharmacokinetic (PBPK) models are built using differential equations to describe the physiology/anatomy of different biological systems. Readily available in vitro and in vivo preclinical data can be incorporated into these models to not only estimate pharmacokinetic (PK) parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. They provide a mechanistic framework to understand and extrapolate PK and dose across in vitro and in vivo systems and across different species, populations and disease states. Using small molecule and large molecule examples from the literature and our own company, we have shown how PBPK techniques can be utilised for human PK and dose prediction. Such approaches have the potential to increase efficiency, reduce the need for animal studies, replace clinical trials and increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however some limitations need to be addressed to realise its application and utility more broadly.

  4. Automatic Peak Selection by a Benjamini-Hochberg-Based Algorithm

    KAUST Repository

    Abbas, Ahmed; Kong, Xin-Bing; Liu, Zhi; Jing, Bing-Yi; Gao, Xin

    2013-01-01

    A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into p-values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak [1] and PICKY [2]. Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx. © 2013

  5. Automatic Peak Selection by a Benjamini-Hochberg-Based Algorithm

    KAUST Repository

    Abbas, Ahmed

    2013-01-07

    A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into p-values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak [1] and PICKY [2]. Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx. © 2013

  6. ANALYSIS OF FUZZY QUEUES: PARAMETRIC PROGRAMMING APPROACH BASED ON RANDOMNESS - FUZZINESS CONSISTENCY PRINCIPLE

    OpenAIRE

    Dhruba Das; Hemanta K. Baruah

    2015-01-01

    In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM...

  7. Discrete Biogeography Based Optimization for Feature Selection in Molecular Signatures.

    Science.gov (United States)

    Liu, Bo; Tian, Meihong; Zhang, Chunhua; Li, Xiangtao

    2015-04-01

    Biomarker discovery from high-dimensional data is a complex task in the development of efficient cancer diagnoses and classification. However, these data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a discrete biogeography based optimization is proposed to select the good subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the fisher-markov selector is used to choose fixed number of gene data. Secondly, to make biogeography based optimization suitable for the feature selection problem; discrete migration model and discrete mutation model are proposed to balance the exploration and exploitation ability. Then, discrete biogeography based optimization, as we called DBBO, is proposed by integrating discrete migration model and discrete mutation model. Finally, the DBBO method is used for feature selection, and three classifiers are used as the classifier with the 10 fold cross-validation method. In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on four breast cancer dataset benchmarks. Comparison with genetic algorithm, particle swarm optimization, differential evolution algorithm and hybrid biogeography based optimization, experimental results demonstrate that the proposed method is better or at least comparable with previous method from literature when considering the quality of the solutions obtained. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Classification and Target Group Selection Based Upon Frequent Patterns

    NARCIS (Netherlands)

    W.H.L.M. Pijls (Wim); R. Potharst (Rob)

    2000-01-01

    textabstractIn this technical report , two new algorithms based upon frequent patterns are proposed. One algorithm is a classification method. The other one is an algorithm for target group selection. In both algorithms, first of all, the collection of frequent patterns in the training set is

  9. Robot soccer action selection based on Q learning

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper researches robot soccer action selection based on Q learning . The robot learn to activate particular behavior given their current situation and reward signal. We adopt neural network to implementations of Q learning for their generalization properties and limited computer memory requirements

  10. Evaporation rate-based selection of supramolecular chirality.

    Science.gov (United States)

    Hattori, Shingo; Vandendriessche, Stefaan; Koeckelberghs, Guy; Verbiest, Thierry; Ishii, Kazuyuki

    2017-03-09

    We demonstrate the evaporation rate-based selection of supramolecular chirality for the first time. P-type aggregates prepared by fast evaporation, and M-type aggregates prepared by slow evaporation are kinetic and thermodynamic products under dynamic reaction conditions, respectively. These findings provide a novel solution reaction chemistry under the dynamic reaction conditions.

  11. Validity of selected cardiovascular field-based test among Malaysian ...

    African Journals Online (AJOL)

    Based on emerge obese problem among Malaysian, this research is formulated to validate published tests among healthy female adult. Selected test namely; 20 meter multi-stage shuttle run, 2.4km run test, 1 mile walk test and Harvard Step test were correlated with laboratory test (Bruce protocol) to find the criterion validity ...

  12. Solar Thermal AIR Collector Based on New Type Selective Coating

    Directory of Open Access Journals (Sweden)

    Musiy, R.Y.

    2014-01-01

    Full Text Available Based on the best for optical performance and selective coating solar thermal air collector, which operates by solar power on the principle of simultaneous ventilation and heating facilities, is designed. It can be used for vacation homes, museums, wooden churches, warehouses, garages, houses, greenhouses etc.

  13. Exposure level from selected base station tower around Kuala Nerus

    African Journals Online (AJOL)

    Health risk due to RF radiation exposure from base station tower (BST) has been debated for years leading to public concerns. Thus, this preliminary study aims to measure, evaluate and analyze the exposure level on three selected BST around Kuala Nerus. The measurement of exposure level in terms of voltage ...

  14. r2VIM: A new variable selection method for random forests in genome-wide association studies.

    Science.gov (United States)

    Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E

    2016-01-01

    Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.

  15. Annotation-Based Whole Genomic Prediction and Selection

    DEFF Research Database (Denmark)

    Kadarmideen, Haja; Do, Duy Ngoc; Janss, Luc

    Genomic selection is widely used in both animal and plant species, however, it is performed with no input from known genomic or biological role of genetic variants and therefore is a black box approach in a genomic era. This study investigated the role of different genomic regions and detected QTLs...... in their contribution to estimated genomic variances and in prediction of genomic breeding values by applying SNP annotation approaches to feed efficiency. Ensembl Variant Predictor (EVP) and Pig QTL database were used as the source of genomic annotation for 60K chip. Genomic prediction was performed using the Bayes...... classes. Predictive accuracy was 0.531, 0.532, 0.302, and 0.344 for DFI, RFI, ADG and BF, respectively. The contribution per SNP to total genomic variance was similar among annotated classes across different traits. Predictive performance of SNP classes did not significantly differ from randomized SNP...

  16. Evaluation of Randomly Selected Completed Medical Records Sheets in Teaching Hospitals of Jahrom University of Medical Sciences, 2009

    Directory of Open Access Journals (Sweden)

    Mohammad Parsa Mahjob

    2011-06-01

    Full Text Available Background and objective: Medical record documentation, often use to protect the patients legal rights, also providing information for medical researchers, general studies, education of health care staff and qualitative surveys is used. There is a need to control the amount of data entered in the medical record sheets of patients, considering the completion of these sheets is often carried out after completion of service delivery to the patients. Therefore, in this study the prevalence of completeness of medical history, operation reports, and physician order sheets by different documentaries in Jahrom teaching hospitals during year 2009 was analyzed. Methods and Materials: In this descriptive / retrospective study, the 400 medical record sheets of the patients from two teaching hospitals affiliated to Jahrom medical university was randomly selected. The tool of data collection was a checklist based on the content of medical history sheet, operation report and physician order sheets. The data were analyzed by SPSS (Version10 software and Microsoft Office Excel 2003. Results: Average of personal (Demography data entered in medical history, physician order and operation report sheets which is done by department's secretaries were 32.9, 35.8 and 40.18 percent. Average of clinical data entered by physician in medical history sheet is 38 percent. Surgical data entered by the surgeon in operation report sheet was 94.77 percent. Average of data entered by operation room's nurse in operation report sheet was 36.78 percent; Average of physician order data in physician order sheet entered by physician was 99.3 percent. Conclusion: According to this study, the rate of completed record papers reviewed by documentary in Jahrom teaching hospitals were not desirable and in some cases were very weak and incomplete. This deficiency was due to different reason such as medical record documentaries negligence, lack of adequate education for documentaries, High work

  17. Water chemistry in 179 randomly selected Swedish headwater streams related to forest production, clear-felling and climate.

    Science.gov (United States)

    Löfgren, Stefan; Fröberg, Mats; Yu, Jun; Nisell, Jakob; Ranneby, Bo

    2014-12-01

    From a policy perspective, it is important to understand forestry effects on surface waters from a landscape perspective. The EU Water Framework Directive demands remedial actions if not achieving good ecological status. In Sweden, 44 % of the surface water bodies have moderate ecological status or worse. Many of these drain catchments with a mosaic of managed forests. It is important for the forestry sector and water authorities to be able to identify where, in the forested landscape, special precautions are necessary. The aim of this study was to quantify the relations between forestry parameters and headwater stream concentrations of nutrients, organic matter and acid-base chemistry. The results are put into the context of regional climate, sulphur and nitrogen deposition, as well as marine influences. Water chemistry was measured in 179 randomly selected headwater streams from two regions in southwest and central Sweden, corresponding to 10 % of the Swedish land area. Forest status was determined from satellite images and Swedish National Forest Inventory data using the probabilistic classifier method, which was used to model stream water chemistry with Bayesian model averaging. The results indicate that concentrations of e.g. nitrogen, phosphorus and organic matter are related to factors associated with forest production but that it is not forestry per se that causes the excess losses. Instead, factors simultaneously affecting forest production and stream water chemistry, such as climate, extensive soil pools and nitrogen deposition, are the most likely candidates The relationships with clear-felled and wetland areas are likely to be direct effects.

  18. Genetic diversity of Kenyan Prosopis populations based on random ...

    African Journals Online (AJOL)

    To determine whether naturally established stands consist of a single or mixture of species, six populations from Bamburi, Bura, Isiolo, Marigat, Taveta and Turkwel were compared for relatedness with reference to Prosopis chilensis, Prosopis juliflora and Prosopis pallida using random amplified polymorphic DNA markers.

  19. Genetic relationships among Rosa species based on random ...

    African Journals Online (AJOL)

    To investigate the genetic diversity of Rosa accessions, random amplified polymorphism DNA (RAPD) approach was employed. Nine of ten primers amplified 138 scorable RAPD loci with 111 polymorphic bands (80%). Percentages of polymorphic bands ranged from 75 to 100%. Sizes of amplified DNA fragments ranged ...

  20. Introducing two Random Forest based methods for cloud detection in remote sensing images

    Science.gov (United States)

    Ghasemian, Nafiseh; Akhoondzadeh, Mehdi

    2018-07-01

    Cloud detection is a necessary phase in satellite images processing to retrieve the atmospheric and lithospheric parameters. Currently, some cloud detection methods based on Random Forest (RF) model have been proposed but they do not consider both spectral and textural characteristics of the image. Furthermore, they have not been tested in the presence of snow/ice. In this paper, we introduce two RF based algorithms, Feature Level Fusion Random Forest (FLFRF) and Decision Level Fusion Random Forest (DLFRF) to incorporate visible, infrared (IR) and thermal spectral and textural features (FLFRF) including Gray Level Co-occurrence Matrix (GLCM) and Robust Extended Local Binary Pattern (RELBP_CI) or visible, IR and thermal classifiers (DLFRF) for highly accurate cloud detection on remote sensing images. FLFRF first fuses visible, IR and thermal features. Thereafter, it uses the RF model to classify pixels to cloud, snow/ice and background or thick cloud, thin cloud and background. DLFRF considers visible, IR and thermal features (both spectral and textural) separately and inserts each set of features to RF model. Then, it holds vote matrix of each run of the model. Finally, it fuses the classifiers using the majority vote method. To demonstrate the effectiveness of the proposed algorithms, 10 Terra MODIS and 15 Landsat 8 OLI/TIRS images with different spatial resolutions are used in this paper. Quantitative analyses are based on manually selected ground truth data. Results show that after adding RELBP_CI to input feature set cloud detection accuracy improves. Also, the average cloud kappa values of FLFRF and DLFRF on MODIS images (1 and 0.99) are higher than other machine learning methods, Linear Discriminate Analysis (LDA), Classification And Regression Tree (CART), K Nearest Neighbor (KNN) and Support Vector Machine (SVM) (0.96). The average snow/ice kappa values of FLFRF and DLFRF on MODIS images (1 and 0.85) are higher than other traditional methods. The

  1. Retention of Statistical Concepts in a Preliminary Randomization-Based Introductory Statistics Curriculum

    Science.gov (United States)

    Tintle, Nathan; Topliff, Kylie; VanderStoep, Jill; Holmes, Vicki-Lynn; Swanson, Todd

    2012-01-01

    Previous research suggests that a randomization-based introductory statistics course may improve student learning compared to the consensus curriculum. However, it is unclear whether these gains are retained by students post-course. We compared the conceptual understanding of a cohort of students who took a randomization-based curriculum (n = 76)…

  2. Randomized controlled trials of simulation-based interventions in Emergency Medicine: a methodological review.

    Science.gov (United States)

    Chauvin, Anthony; Truchot, Jennifer; Bafeta, Aida; Pateron, Dominique; Plaisance, Patrick; Yordanov, Youri

    2018-04-01

    The number of trials assessing Simulation-Based Medical Education (SBME) interventions has rapidly expanded. Many studies show that potential flaws in design, conduct and reporting of randomized controlled trials (RCTs) can bias their results. We conducted a methodological review of RCTs assessing a SBME in Emergency Medicine (EM) and examined their methodological characteristics. We searched MEDLINE via PubMed for RCT that assessed a simulation intervention in EM, published in 6 general and internal medicine and in the top 10 EM journals. The Cochrane Collaboration risk of Bias tool was used to assess risk of bias, intervention reporting was evaluated based on the "template for intervention description and replication" checklist, and methodological quality was evaluated by the Medical Education Research Study Quality Instrument. Reports selection and data extraction was done by 2 independents researchers. From 1394 RCTs screened, 68 trials assessed a SBME intervention. They represent one quarter of our sample. Cardiopulmonary resuscitation (CPR) is the most frequent topic (81%). Random sequence generation and allocation concealment were performed correctly in 66 and 49% of trials. Blinding of participants and assessors was performed correctly in 19 and 68%. Risk of attrition bias was low in three-quarters of the studies (n = 51). Risk of selective reporting bias was unclear in nearly all studies. The mean MERQSI score was of 13.4/18.4% of the reports provided a description allowing the intervention replication. Trials assessing simulation represent one quarter of RCTs in EM. Their quality remains unclear, and reproducing the interventions appears challenging due to reporting issues.

  3. Transmit antenna selection based on shadowing side information

    KAUST Repository

    Yilmaz, Ferkan

    2011-05-01

    In this paper, we propose a new transmit antenna selection scheme based on shadowing side information. In the proposed scheme, single transmit antenna which has the highest shadowing coefficient is selected. By the proposed technique, usage of the feedback channel and channel estimation complexity at the receiver can be reduced. We consider independent but not identically distributed Generalized-K composite fading model, which is a general composite fading & shadowing channel model for wireless environments. Exact closed-form outage probability, moment generating function and symbol error probability expressions are derived. In addition, theoretical performance results are validated by Monte Carlo simulations. © 2011 IEEE.

  4. Transmit antenna selection based on shadowing side information

    KAUST Repository

    Yilmaz, Ferkan; Yilmaz, Ahmet Oǧuz; Alouini, Mohamed-Slim; Kucur, Oǧuz

    2011-01-01

    In this paper, we propose a new transmit antenna selection scheme based on shadowing side information. In the proposed scheme, single transmit antenna which has the highest shadowing coefficient is selected. By the proposed technique, usage of the feedback channel and channel estimation complexity at the receiver can be reduced. We consider independent but not identically distributed Generalized-K composite fading model, which is a general composite fading & shadowing channel model for wireless environments. Exact closed-form outage probability, moment generating function and symbol error probability expressions are derived. In addition, theoretical performance results are validated by Monte Carlo simulations. © 2011 IEEE.

  5. Expectation-based approach for one-dimensional randomly disordered phononic crystals

    International Nuclear Information System (INIS)

    Wu, Feng; Gao, Qiang; Xu, Xiaoming; Zhong, Wanxie

    2014-01-01

    An expectation-based approach to the statistical theorem is proposed for the one-dimensional randomly disordered phononic crystal. In the proposed approach, the expectations of the random eigenstates of randomly disordered phononic crystals are investigated. In terms of the expectations of the random eigenstates, the wave propagation and localization phenomenon in the random phononic crystal could be understood in a statistical perspective. Using the proposed approach, it is proved that for a randomly disordered phononic crystal, the Bloch theorem holds in the perspective of expectation. A one-dimensional randomly disordered binary phononic crystal consisting of two materials with the random geometry size or random physical parameter is addressed by using the proposed approach. From the result, it can be observed that with the increase of the disorder degree, the localization of the expectations of the eigenstates is strengthened. The effect of the random disorder on the eigenstates at higher frequencies is more significant than that at lower frequencies. Furthermore, after introducing the random disorder into phononic crystals, some random divergent eigenstates are changed to localized eigenstates in expectation sense.

  6. A novel EMD selecting thresholding method based on multiple iteration for denoising LIDAR signal

    Science.gov (United States)

    Li, Meng; Jiang, Li-hui; Xiong, Xing-long

    2015-06-01

    Empirical mode decomposition (EMD) approach has been believed to be potentially useful for processing the nonlinear and non-stationary LIDAR signals. To shed further light on its performance, we proposed the EMD selecting thresholding method based on multiple iteration, which essentially acts as a development of EMD interval thresholding (EMD-IT), and randomly alters the samples of noisy parts of all the corrupted intrinsic mode functions to generate a better effect of iteration. Simulations on both synthetic signals and LIDAR signals from real world support this method.

  7. Prediction of Geological Subsurfaces Based on Gaussian Random Field Models

    Energy Technology Data Exchange (ETDEWEB)

    Abrahamsen, Petter

    1997-12-31

    During the sixties, random functions became practical tools for predicting ore reserves with associated precision measures in the mining industry. This was the start of the geostatistical methods called kriging. These methods are used, for example, in petroleum exploration. This thesis reviews the possibilities for using Gaussian random functions in modelling of geological subsurfaces. It develops methods for including many sources of information and observations for precise prediction of the depth of geological subsurfaces. The simple properties of Gaussian distributions make it possible to calculate optimal predictors in the mean square sense. This is done in a discussion of kriging predictors. These predictors are then extended to deal with several subsurfaces simultaneously. It is shown how additional velocity observations can be used to improve predictions. The use of gradient data and even higher order derivatives are also considered and gradient data are used in an example. 130 refs., 44 figs., 12 tabs.

  8. Numerical Model based Reliability Estimation of Selective Laser Melting Process

    DEFF Research Database (Denmark)

    Mohanty, Sankhya; Hattel, Jesper Henri

    2014-01-01

    Selective laser melting is developing into a standard manufacturing technology with applications in various sectors. However, the process is still far from being at par with conventional processes such as welding and casting, the primary reason of which is the unreliability of the process. While...... of the selective laser melting process. A validated 3D finite-volume alternating-direction-implicit numerical technique is used to model the selective laser melting process, and is calibrated against results from single track formation experiments. Correlation coefficients are determined for process input...... parameters such as laser power, speed, beam profile, etc. Subsequently, uncertainties in the processing parameters are utilized to predict a range for the various outputs, using a Monte Carlo method based uncertainty analysis methodology, and the reliability of the process is established....

  9. Implementation of IMAGE STEGANOGRAPHY Based on Random LSB

    OpenAIRE

    Ashish kumari; Shyama Sharma; Navdeep Bohra

    2012-01-01

    Steganography is the technique of hiding a private message within a file in such a manner that third party cannot know the existence of matter or the hidden information. The purpose of Steganography is to create secrete communication between the sender and the receiver byreplacing the least significant bits (LSB)of the cover image with the data bits. And in this paper we have shown that how image steganography (random and sequential LSB) works and practical understanding of what image Stegano...

  10. Deep Random based Key Exchange protocol resisting unlimited MITM

    OpenAIRE

    de Valroger, Thibault

    2018-01-01

    We present a protocol enabling two legitimate partners sharing an initial secret to mutually authenticate and to exchange an encryption session key. The opponent is an active Man In The Middle (MITM) with unlimited computation and storage capacities. The resistance to unlimited MITM is obtained through the combined use of Deep Random secrecy, formerly introduced and proved as unconditionally secure against passive opponent for key exchange, and universal hashing techniques. We prove the resis...

  11. Hyperspectral band selection based on consistency-measure of neighborhood rough set theory

    International Nuclear Information System (INIS)

    Liu, Yao; Xie, Hong; Wang, Liguo; Tan, Kezhu; Chen, Yuehua; Xu, Zhen

    2016-01-01

    Band selection is a well-known approach for reducing dimensionality in hyperspectral imaging. In this paper, a band selection method based on consistency-measure of neighborhood rough set theory (CMNRS) was proposed to select informative bands from hyperspectral images. A decision-making information system was established by the reflection spectrum of soybeans’ hyperspectral data between 400 nm and 1000 nm wavelengths. The neighborhood consistency-measure, which reflects not only the size of the decision positive region, but also the sample distribution in the boundary region, was used as the evaluation function of band significance. The optimal band subset was selected by a forward greedy search algorithm. A post-pruning strategy was employed to overcome the over-fitting problem and find the minimum subset. To assess the effectiveness of the proposed band selection technique, two classification models (extreme learning machine (ELM) and random forests (RF)) were built. The experimental results showed that the proposed algorithm can effectively select key bands and obtain satisfactory classification accuracy. (paper)

  12. Novel Zn2+-chelating peptides selected from a fimbria-displayed random peptide library

    DEFF Research Database (Denmark)

    Kjærgaard, Kristian; Schembri, Mark; Klemm, Per

    2001-01-01

    The display of peptide sequences on the surface of bacteria is a technology that offers exciting applications in biotechnology and medical research. Type 1 fimbriae are surface organelles of Escherichia coli which mediate D-mannose-sensitive binding to different host surfaces by virtue of the Fim......H adhesin. FimH is a component of the fimbrial organelle that can accommodate and display a diverse range of peptide sequences on the E. coli cell surface. In this study we have constructed a random peptide library in FimH. The library, consisting of similar to 40 million individual clones, was screened...

  13. Improved targeted immunization strategies based on two rounds of selection

    Science.gov (United States)

    Xia, Ling-Ling; Song, Yu-Rong; Li, Chan-Chan; Jiang, Guo-Ping

    2018-04-01

    In the case of high degree targeted immunization where the number of vaccine is limited, when more than one node associated with the same degree meets the requirement of high degree centrality, how can we choose a certain number of nodes from those nodes, so that the number of immunized nodes will not exceed the limit? In this paper, we introduce a new idea derived from the selection process of second-round exam to solve this problem and then propose three improved targeted immunization strategies. In these proposed strategies, the immunized nodes are selected through two rounds of selection, where we increase the quotas of first-round selection according the evaluation criterion of degree centrality and then consider another characteristic parameter of node, such as node's clustering coefficient, betweenness and closeness, to help choose targeted nodes in the second-round selection. To validate the effectiveness of the proposed strategies, we compare them with the degree immunizations including the high degree targeted and the high degree adaptive immunizations using two metrics: the size of the largest connected component of immunized network and the number of infected nodes. Simulation results demonstrate that the proposed strategies based on two rounds of sorting are effective for heterogeneous networks and their immunization effects are better than that of the degree immunizations.

  14. Hybrid Feature Selection Approach Based on GRASP for Cancer Microarray Data

    Directory of Open Access Journals (Sweden)

    Arpita Nagpal

    2017-01-01

    Full Text Available Microarray data usually contain a large number of genes, but a small number of samples. Feature subset selection for microarray data aims at reducing the number of genes so that useful information can be extracted from the samples. Reducing the dimension of data sets further helps in improving the computational efficiency of the learning model. In this paper, we propose a modified algorithm based on the tabu search as local search procedures to a Greedy Randomized Adaptive Search Procedure (GRASP for high dimensional microarray data sets. The proposed Tabu based Greedy Randomized Adaptive Search Procedure algorithm is named as TGRASP. In TGRASP, a new parameter has been introduced named as Tabu Tenure and the existing parameters, NumIter and size have been modified. We observed that different parameter settings affect the quality of the optimum. The second proposed algorithm known as FFGRASP (Firefly Greedy Randomized Adaptive Search Procedure uses a firefly optimization algorithm in the local search optimzation phase of the greedy randomized adaptive search procedure (GRASP. Firefly algorithm is one of the powerful algorithms for optimization of multimodal applications. Experimental results show that the proposed TGRASP and FFGRASP algorithms are much better than existing algorithm with respect to three performance parameters viz. accuracy, run time, number of a selected subset of features. We have also compared both the approaches with a unified metric (Extended Adjusted Ratio of Ratios which has shown that TGRASP approach outperforms existing approach for six out of nine cancer microarray datasets and FFGRASP performs better on seven out of nine datasets.

  15. A generator for unique quantum random numbers based on vacuum states

    DEFF Research Database (Denmark)

    Gabriel, C.; Wittmann, C.; Sych, D.

    2010-01-01

    the purity of a continuous-variable quantum vacuum state to generate unique random numbers. We use the intrinsic randomness in measuring the quadratures of a mode in the lowest energy vacuum state, which cannot be correlated to any other state. The simplicity of our source, combined with its verifiably......Random numbers are a valuable component in diverse applications that range from simulations(1) over gambling to cryptography(2,3). The quest for true randomness in these applications has engendered a large variety of different proposals for producing random numbers based on the foundational...... unpredictability of quantum mechanics(4-11). However, most approaches do not consider that a potential adversary could have knowledge about the generated numbers, so the numbers are not verifiably random and unique(12-15). Here we present a simple experimental setup based on homodyne measurements that uses...

  16. A new simple technique for improving the random properties of chaos-based cryptosystems

    Science.gov (United States)

    Garcia-Bosque, M.; Pérez-Resa, A.; Sánchez-Azqueta, C.; Celma, S.

    2018-03-01

    A new technique for improving the security of chaos-based stream ciphers has been proposed and tested experimentally. This technique manages to improve the randomness properties of the generated keystream by preventing the system to fall into short period cycles due to digitation. In order to test this technique, a stream cipher based on a Skew Tent Map algorithm has been implemented on a Virtex 7 FPGA. The randomness of the keystream generated by this system has been compared to the randomness of the keystream generated by the same system with the proposed randomness-enhancement technique. By subjecting both keystreams to the National Institute of Standards and Technology (NIST) tests, we have proved that our method can considerably improve the randomness of the generated keystreams. In order to incorporate our randomness-enhancement technique, only 41 extra slices have been needed, proving that, apart from effective, this method is also efficient in terms of area and hardware resources.

  17. Uniform design based SVM model selection for face recognition

    Science.gov (United States)

    Li, Weihong; Liu, Lijuan; Gong, Weiguo

    2010-02-01

    Support vector machine (SVM) has been proved to be a powerful tool for face recognition. The generalization capacity of SVM depends on the model with optimal hyperparameters. The computational cost of SVM model selection results in application difficulty in face recognition. In order to overcome the shortcoming, we utilize the advantage of uniform design--space filling designs and uniformly scattering theory to seek for optimal SVM hyperparameters. Then we propose a face recognition scheme based on SVM with optimal model which obtained by replacing the grid and gradient-based method with uniform design. The experimental results on Yale and PIE face databases show that the proposed method significantly improves the efficiency of SVM model selection.

  18. NetProt: Complex-based Feature Selection.

    Science.gov (United States)

    Goh, Wilson Wen Bin; Wong, Limsoon

    2017-08-04

    Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .

  19. Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

    International Nuclear Information System (INIS)

    Ohdaira, Tetsushi

    2014-01-01

    Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision. (paper)

  20. Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

    Science.gov (United States)

    Ohdaira, Tetsushi

    2014-07-01

    Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision.

  1. Attention-based Memory Selection Recurrent Network for Language Modeling

    OpenAIRE

    Liu, Da-Rong; Chuang, Shun-Po; Lee, Hung-yi

    2016-01-01

    Recurrent neural networks (RNNs) have achieved great success in language modeling. However, since the RNNs have fixed size of memory, their memory cannot store all the information about the words it have seen before in the sentence, and thus the useful long-term information may be ignored when predicting the next words. In this paper, we propose Attention-based Memory Selection Recurrent Network (AMSRN), in which the model can review the information stored in the memory at each previous time ...

  2. Development of a thermodynamic data base for selected heavy metals

    International Nuclear Information System (INIS)

    Hageman, Sven; Scharge, Tina; Willms, Thomas

    2015-07-01

    The report on the development of a thermodynamic data base for selected heavy metals covers the description of experimental methods, the thermodynamic model for chromate, the thermodynamic model for dichromate, the thermodynamic model for manganese (II), the thermodynamic model for cobalt, the thermodynamic model for nickel, the thermodynamic model for copper (I), the thermodynamic model for copper(II), the thermodynamic model for mercury (0) and mercury (I), the thermodynamic model for mercury (III), the thermodynamic model for arsenate.

  3. Modeling and optimizing of the random atomic spin gyroscope drift based on the atomic spin gyroscope

    Energy Technology Data Exchange (ETDEWEB)

    Quan, Wei; Lv, Lin, E-mail: lvlinlch1990@163.com; Liu, Baiqi [School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing 100191 (China)

    2014-11-15

    In order to improve the atom spin gyroscope's operational accuracy and compensate the random error caused by the nonlinear and weak-stability characteristic of the random atomic spin gyroscope (ASG) drift, the hybrid random drift error model based on autoregressive (AR) and genetic programming (GP) + genetic algorithm (GA) technique is established. The time series of random ASG drift is taken as the study object. The time series of random ASG drift is acquired by analyzing and preprocessing the measured data of ASG. The linear section model is established based on AR technique. After that, the nonlinear section model is built based on GP technique and GA is used to optimize the coefficients of the mathematic expression acquired by GP in order to obtain a more accurate model. The simulation result indicates that this hybrid model can effectively reflect the characteristics of the ASG's random drift. The square error of the ASG's random drift is reduced by 92.40%. Comparing with the AR technique and the GP + GA technique, the random drift is reduced by 9.34% and 5.06%, respectively. The hybrid modeling method can effectively compensate the ASG's random drift and improve the stability of the system.

  4. Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl

    This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular we show that the Bridge estimator is oracle efficient. It can correctly distinguish between relevant...... and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation. In the case of more explanatory variables than observations......, we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables. We do this without restricting the dependence between covariates and without assuming sub Gaussianity of the error terms thereby generalizing the results...

  5. Presence of psychoactive substances in oral fluid from randomly selected drivers in Denmark

    DEFF Research Database (Denmark)

    Simonsen, K. Wiese; Steentoft, A.; Hels, Tove

    2012-01-01

    . The percentage of drivers positive for medicinal drugs above the Danish legal concentration limit was 0.4%; while, 0.3% of the drivers tested positive for one or more illicit drug at concentrations exceeding the Danish legal limit. Tetrahydrocannabinol, cocaine, and amphetamine were the most frequent illicit......This roadside study is the Danish part of the EU-project DRUID (Driving under the Influence of Drugs, Alcohol, and Medicines) and included three representative regions in Denmark. Oral fluid samples (n = 3002) were collected randomly from drivers using a sampling scheme stratified by time, season......, and road type. The oral fluid samples were screened for 29 illegal and legal psychoactive substances and metabolites as well as ethanol. Fourteen (0.5%) drivers were positive for ethanol alone or in combination with drugs) at concentrations above 0.53 g/l (0.5 mg/g), which is the Danish legal limit...

  6. Linear feature selection in texture analysis - A PLS based method

    DEFF Research Database (Denmark)

    Marques, Joselene; Igel, Christian; Lillholm, Martin

    2013-01-01

    We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... and considering all CV groups, the methods selected 36 % of the original features available. The diagnosis evaluation reached a generalization area-under-the-ROC curve of 0.92, which was higher than established cartilage-based markers known to relate to OA diagnosis....

  7. Phonon structures of GaN-based random semiconductor alloys

    Science.gov (United States)

    Zhou, Mei; Chen, Xiaobin; Li, Gang; Zheng, Fawei; Zhang, Ping

    2017-12-01

    Accurate modeling of thermal properties is strikingly important for developing next-generation electronics with high performance. Many thermal properties are closely related to phonon dispersions, such as sound velocity. However, random substituted semiconductor alloys AxB1-x usually lack translational symmetry, and simulation with periodic boundary conditions often requires large supercells, which makes phonon dispersion highly folded and hardly comparable with experimental results. Here, we adopt a large supercell with randomly distributed A and B atoms to investigate substitution effect on the phonon dispersions of semiconductor alloys systematically by using phonon unfolding method [F. Zheng, P. Zhang, Comput. Mater. Sci. 125, 218 (2016)]. The results reveal the extent to which phonon band characteristics in (In,Ga)N and Ga(N,P) are preserved or lost at different compositions and q points. Generally, most characteristics of phonon dispersions can be preserved with indium substitution of gallium in GaN, while substitution of nitrogen with phosphorus strongly perturbs the phonon dispersion of GaN, showing a rapid disintegration of the Bloch characteristics of optical modes and introducing localized impurity modes. In addition, the sound velocities of both (In,Ga)N and Ga(N,P) display a nearly linear behavior as a function of substitution compositions. Supplementary material in the form of one pdf file available from the Journal web page at http://https://doi.org/10.1140/epjb/e2017-80481-0.

  8. Embedded Memory Hierarchy Exploration Based on Magnetic Random Access Memory

    Directory of Open Access Journals (Sweden)

    Luís Vitório Cargnini

    2014-08-01

    Full Text Available Static random access memory (SRAM is the most commonly employed semiconductor in the design of on-chip processor memory. However, it is unlikely that the SRAM technology will have a cell size that will continue to scale below 45 nm, due to the leakage current that is caused by the quantum tunneling effect. Magnetic random access memory (MRAM is a candidate technology to replace SRAM, assuming appropriate dimensioning given an operating threshold voltage. The write current of spin transfer torque (STT-MRAM is a known limitation; however, this has been recently mitigated by leveraging perpendicular magnetic tunneling junctions. In this article, we present a comprehensive comparison of spin transfer torque-MRAM (STT-MRAM and SRAM cache set banks. The non-volatility of STT-MRAM allows the definition of new instant on/off policies and leakage current optimizations. Through our experiments, we demonstrate that STT-MRAM is a candidate for the memory hierarchy of embedded systems, due to the higher densities and reduced leakage of MRAM.We demonstrate that adopting STT-MRAM in L1 and L2 caches mitigates the impact of higher write latencies and increased current draw due to the use of MRAM. With the correct system-on-chip (SoC design, we believe that STT-MRAM is a viable alternative to SRAM, which minimizes leakage current and the total power consumed by the SoC.

  9. Correlates of smoking with socioeconomic status, leisure time physical activity and alcohol consumption among Polish adults from randomly selected regions.

    Science.gov (United States)

    Woitas-Slubowska, Donata; Hurnik, Elzbieta; Skarpańska-Stejnborn, Anna

    2010-12-01

    To determine the association between smoking status and leisure time physical activity (LTPA), alcohol consumption, and socioeconomic status (SES) among Polish adults. 466 randomly selected men and women (aged 18-66 years) responded to an anonymous questionnaire regarding smoking, alcohol consumption, LTPA, and SES. Multiple logistic regression was used to examine the association of smoking status with six socioeconomic measures, level of LTPA, and frequency and type of alcohol consumed. Smokers were defined as individuals smoking occasionally or daily. The odds of being smoker were 9 times (men) and 27 times (women) higher among respondents who drink alcohol several times/ week or everyday in comparison to non-drinkers (p times higher compared to those with the high educational attainment (p = 0.007). Among women we observed that students were the most frequent smokers. Female students were almost three times more likely to smoke than non-professional women, and two times more likely than physical workers (p = 0.018). The findings of this study indicated that among randomly selected Polish man and women aged 18-66 smoking and alcohol consumption tended to cluster. These results imply that intervention strategies need to target multiple risk factors simultaneously. The highest risk of smoking was observed among low educated men, female students, and both men and women drinking alcohol several times a week or every day. Information on subgroups with the high risk of smoking will help in planning future preventive strategies.

  10. Index Fund Selections with GAs and Classifications Based on Turnover

    Science.gov (United States)

    Orito, Yukiko; Motoyama, Takaaki; Yamazaki, Genji

    It is well known that index fund selections are important for the risk hedge of investment in a stock market. The`selection’means that for`stock index futures’, n companies of all ones in the market are selected. For index fund selections, Orito et al.(6) proposed a method consisting of the following two steps : Step 1 is to select N companies in the market with a heuristic rule based on the coefficient of determination between the return rate of each company in the market and the increasing rate of the stock price index. Step 2 is to construct a group of n companies by applying genetic algorithms to the set of N companies. We note that the rule of Step 1 is not unique. The accuracy of the results using their method depends on the length of time data (price data) in the experiments. The main purpose of this paper is to introduce a more`effective rule’for Step 1. The rule is based on turnover. The method consisting of Step 1 based on turnover and Step 2 is examined with numerical experiments for the 1st Section of Tokyo Stock Exchange. The results show that with our method, it is possible to construct the more effective index fund than the results of Orito et al.(6). The accuracy of the results using our method depends little on the length of time data (turnover data). The method especially works well when the increasing rate of the stock price index over a period can be viewed as a linear time series data.

  11. A fuzzy logic based PROMETHEE method for material selection problems

    Directory of Open Access Journals (Sweden)

    Muhammet Gul

    2018-03-01

    Full Text Available Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper presents a fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation method based on trapezoidal fuzzy interval numbers that can be applied to the selection of materials for an automotive instrument panel. Also, it presents uniqueness in making a significant contribution to the literature in terms of the application of fuzzy decision-making approach to material selection problems. The method is illustrated, validated, and compared against three different fuzzy MCDM methods (fuzzy VIKOR, fuzzy TOPSIS, and fuzzy ELECTRE in terms of its ranking performance. Also, the relationships between the compared methods and the proposed scenarios for fuzzy PROMETHEE are evaluated via the Spearman’s correlation coefficient. Styrene Maleic Anhydride and Polypropylene are determined optionally as suitable materials for the automotive instrument panel case. We propose a generic fuzzy MCDM methodology that can be practically implemented to material selection problem. The main advantages of the methodology are consideration of the vagueness, uncertainty, and fuzziness to decision making environment.

  12. SELECTION OF FISÁLIS POPULATIONS FOR HIBRIDIZATIONS, BASED ON FRUIT TRAITS

    Directory of Open Access Journals (Sweden)

    NICOLE TREVISANI

    2016-01-01

    Full Text Available ABSTRACT The objective of this study was to characterize the genetic variability in fisális populations and select promising parents based on fruit traits. The experimental design consisted of randomized blocks, with six populations. Five plants per treatment were sampled. The evaluated traits were fruit weight, capsule weight, 1000- seed weight and fruit diameter. The data were subjected to multivariate analysis of variance with error specification between and within (p <0.05. Mahalanobis’ distance was used as a measure of genetic dissimilarity. Significant differences for the assessed traits were detected between fisális populations. The ratio error among by within indicated no need for sampling within the experimental unit. Dissimilarity was greatest between Lages and Vacaria. The most discriminating traits were capsule weight, fruit weight and fruit diameter. The multivariate contrasts indicated differences between the populations of Vacaria and from Caçador, Lages and Peru, selected for hybridizations.

  13. Quantum random number generator based on quantum nature of vacuum fluctuations

    Science.gov (United States)

    Ivanova, A. E.; Chivilikhin, S. A.; Gleim, A. V.

    2017-11-01

    Quantum random number generator (QRNG) allows obtaining true random bit sequences. In QRNG based on quantum nature of vacuum, optical beam splitter with two inputs and two outputs is normally used. We compare mathematical descriptions of spatial beam splitter and fiber Y-splitter in the quantum model for QRNG, based on homodyne detection. These descriptions were identical, that allows to use fiber Y-splitters in practical QRNG schemes, simplifying the setup. Also we receive relations between the input radiation and the resulting differential current in homodyne detector. We experimentally demonstrate possibility of true random bits generation by using QRNG based on homodyne detection with Y-splitter.

  14. On the design of henon and logistic map-based random number generator

    Science.gov (United States)

    Magfirawaty; Suryadi, M. T.; Ramli, Kalamullah

    2017-10-01

    The key sequence is one of the main elements in the cryptosystem. True Random Number Generators (TRNG) method is one of the approaches to generating the key sequence. The randomness source of the TRNG divided into three main groups, i.e. electrical noise based, jitter based and chaos based. The chaos based utilizes a non-linear dynamic system (continuous time or discrete time) as an entropy source. In this study, a new design of TRNG based on discrete time chaotic system is proposed, which is then simulated in LabVIEW. The principle of the design consists of combining 2D and 1D chaotic systems. A mathematical model is implemented for numerical simulations. We used comparator process as a harvester method to obtain the series of random bits. Without any post processing, the proposed design generated random bit sequence with high entropy value and passed all NIST 800.22 statistical tests.

  15. High-speed true random number generation based on paired memristors for security electronics

    Science.gov (United States)

    Zhang, Teng; Yin, Minghui; Xu, Changmin; Lu, Xiayan; Sun, Xinhao; Yang, Yuchao; Huang, Ru

    2017-11-01

    True random number generator (TRNG) is a critical component in hardware security that is increasingly important in the era of mobile computing and internet of things. Here we demonstrate a TRNG using intrinsic variation of memristors as a natural source of entropy that is otherwise undesirable in most applications. The random bits were produced by cyclically switching a pair of tantalum oxide based memristors and comparing their resistance values in the off state, taking advantage of the more pronounced resistance variation compared with that in the on state. Using an alternating read scheme in the designed TRNG circuit, the unbiasedness of the random numbers was significantly improved, and the bitstream passed standard randomness tests. The Pt/TaO x /Ta memristors fabricated in this work have fast programming/erasing speeds of ˜30 ns, suggesting a high random number throughput. The approach proposed here thus holds great promise for physically-implemented random number generation.

  16. Fiber-Type Random Laser Based on a Cylindrical Waveguide with a Disordered Cladding Layer.

    Science.gov (United States)

    Zhang, Wei Li; Zheng, Meng Ya; Ma, Rui; Gong, Chao Yang; Yang, Zhao Ji; Peng, Gang Ding; Rao, Yun Jiang

    2016-05-25

    This letter reports a fiber-type random laser (RL) which is made from a capillary coated with a disordered layer at its internal surface and filled with a gain (laser dye) solution in the core region. This fiber-type optical structure, with the disordered layer providing randomly scattered light into the gain region and the cylindrical waveguide providing confinement of light, assists the formation of random lasing modes and enables a flexible and efficient way of making random lasers. We found that the RL is sensitive to laser dye concentration in the core region and there exists a fine exponential relationship between the lasing intensity and particle concentration in the gain solution. The proposed structure could be a fine platform of realizing random lasing and random lasing based sensing.

  17. Object width modulates object-based attentional selection.

    Science.gov (United States)

    Nah, Joseph C; Neppi-Modona, Marco; Strother, Lars; Behrmann, Marlene; Shomstein, Sarah

    2018-04-24

    Visual input typically includes a myriad of objects, some of which are selected for further processing. While these objects vary in shape and size, most evidence supporting object-based guidance of attention is drawn from paradigms employing two identical objects. Importantly, object size is a readily perceived stimulus dimension, and whether it modulates the distribution of attention remains an open question. Across four experiments, the size of the objects in the display was manipulated in a modified version of the two-rectangle paradigm. In Experiment 1, two identical parallel rectangles of two sizes (thin or thick) were presented. Experiments 2-4 employed identical trapezoids (each having a thin and thick end), inverted in orientation. In the experiments, one end of an object was cued and participants performed either a T/L discrimination or a simple target-detection task. Combined results show that, in addition to the standard object-based attentional advantage, there was a further attentional benefit for processing information contained in the thick versus thin end of objects. Additionally, eye-tracking measures demonstrated increased saccade precision towards thick object ends, suggesting that Fitts's Law may play a role in object-based attentional shifts. Taken together, these results suggest that object-based attentional selection is modulated by object width.

  18. Titanium-based spectrally selective surfaces for solar thermal systems

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, A D; Holmes, J P

    1983-10-01

    A study of spectrally selective surfaces based on anodic oxide films on titanium is presented. These surfaces have low values of solar absorptance, 0.77, due to the nonideal optical properties of the anodic TiO2 for antireflection of titanium. A simple chemical etching process is described which gives a textured surface with dimensions similar to the wavelengths of solar radiation, leading to spectral selectivity. The performance of this dark-etched surface can be further improved by anodising, and optimum absorbers have been produced with alpha(s) 0.935 and hemispherical emittances (400 K) 0.23. The surface texturing effects a significant improvement in alpha(s) at oblique incidence.

  19. A Reliability Based Model for Wind Turbine Selection

    Directory of Open Access Journals (Sweden)

    A.K. Rajeevan

    2013-06-01

    Full Text Available A wind turbine generator output at a specific site depends on many factors, particularly cut- in, rated and cut-out wind speed parameters. Hence power output varies from turbine to turbine. The objective of this paper is to develop a mathematical relationship between reliability and wind power generation. The analytical computation of monthly wind power is obtained from weibull statistical model using cubic mean cube root of wind speed. Reliability calculation is based on failure probability analysis. There are many different types of wind turbinescommercially available in the market. From reliability point of view, to get optimum reliability in power generation, it is desirable to select a wind turbine generator which is best suited for a site. The mathematical relationship developed in this paper can be used for site-matching turbine selection in reliability point of view.

  20. Participant-selected music and physical activity in older adults following cardiac rehabilitation: a randomized controlled trial.

    Science.gov (United States)

    Clark, Imogen N; Baker, Felicity A; Peiris, Casey L; Shoebridge, Georgie; Taylor, Nicholas F

    2017-03-01

    To evaluate effects of participant-selected music on older adults' achievement of activity levels recommended in the physical activity guidelines following cardiac rehabilitation. A parallel group randomized controlled trial with measurements at Weeks 0, 6 and 26. A multisite outpatient rehabilitation programme of a publicly funded metropolitan health service. Adults aged 60 years and older who had completed a cardiac rehabilitation programme. Experimental participants selected music to support walking with guidance from a music therapist. Control participants received usual care only. The primary outcome was the proportion of participants achieving activity levels recommended in physical activity guidelines. Secondary outcomes compared amounts of physical activity, exercise capacity, cardiac risk factors, and exercise self-efficacy. A total of 56 participants, mean age 68.2 years (SD = 6.5), were randomized to the experimental ( n = 28) and control groups ( n = 28). There were no differences between groups in proportions of participants achieving activity recommended in physical activity guidelines at Week 6 or 26. Secondary outcomes demonstrated between-group differences in male waist circumference at both measurements (Week 6 difference -2.0 cm, 95% CI -4.0 to 0; Week 26 difference -2.8 cm, 95% CI -5.4 to -0.1), and observed effect sizes favoured the experimental group for amounts of physical activity (d = 0.30), exercise capacity (d = 0.48), and blood pressure (d = -0.32). Participant-selected music did not increase the proportion of participants achieving recommended amounts of physical activity, but may have contributed to exercise-related benefits.

  1. A randomized controlled trial investigating the use of a predictive nomogram for the selection of the FSH starting dose in IVF/ICSI cycles.

    Science.gov (United States)

    Allegra, Adolfo; Marino, Angelo; Volpes, Aldo; Coffaro, Francesco; Scaglione, Piero; Gullo, Salvatore; La Marca, Antonio

    2017-04-01

    The number of oocytes retrieved is a relevant intermediate outcome in women undergoing IVF/intracytoplasmic sperm injection (ICSI). This trial compared the efficiency of the selection of the FSH starting dose according to a nomogram based on multiple biomarkers (age, day 3 FSH, anti-Müllerian hormone) versus an age-based strategy. The primary outcome measure was the proportion of women with an optimal number of retrieved oocytes defined as 8-14. At their first IVF/ICSI cycle, 191 patients underwent a long gonadotrophin-releasing hormone agonist protocol and were randomized to receive a starting dose of recombinant (human) FSH, based on their age (150 IU if ≤35 years, 225 IU if >35 years) or based on the nomogram. Optimal response was observed in 58/92 patients (63%) in the nomogram group and in 42/99 (42%) in the control group (+21%, 95% CI = 0.07 to 0.35, P = 0.0037). No significant differences were found in the clinical pregnancy rate or the number of embryos cryopreserved per patient. The study showed that the FSH starting dose selected according to ovarian reserve is associated with an increase in the proportion of patients with an optimal response: large trials are recommended to investigate any possible effect on the live-birth rate. Copyright © 2017 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

  2. Frequency selective surfaces based high performance microstrip antenna

    CERN Document Server

    Narayan, Shiv; Jha, Rakesh Mohan

    2016-01-01

    This book focuses on performance enhancement of printed antennas using frequency selective surfaces (FSS) technology. The growing demand of stealth technology in strategic areas requires high-performance low-RCS (radar cross section) antennas. Such requirements may be accomplished by incorporating FSS into the antenna structure either in its ground plane or as the superstrate, due to the filter characteristics of FSS structure. In view of this, a novel approach based on FSS technology is presented in this book to enhance the performance of printed antennas including out-of-band structural RCS reduction. In this endeavor, the EM design of microstrip patch antennas (MPA) loaded with FSS-based (i) high impedance surface (HIS) ground plane, and (ii) the superstrates are discussed in detail. The EM analysis of proposed FSS-based antenna structures have been carried out using transmission line analogy, in combination with the reciprocity theorem. Further, various types of novel FSS structures are considered in desi...

  3. Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

    Science.gov (United States)

    Marques, Yuri Bento; de Paiva Oliveira, Alcione; Ribeiro Vasconcelos, Ana Tereza; Cerqueira, Fabio Ribeiro

    2016-12-15

    MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs). The current ab initio approaches, however, have selectivity issues, i.e., a high number of false positives is reported, which can lead to laborious and costly attempts to provide biological validation. This study presents an extension of the ab initio method miRNAFold, with the aim of improving selectivity through machine learning techniques, namely, random forest combined with the SMOTE procedure that copes with imbalance datasets. By comparing our method, termed Mirnacle, with other important approaches in the literature, we demonstrate that Mirnacle substantially improves selectivity without compromising sensitivity. For the three datasets used in our experiments, our method achieved at least 97% of sensitivity and could deliver a two-fold, 20-fold, and 6-fold increase in selectivity, respectively, compared with the best results of current computational tools. The extension of miRNAFold by the introduction of machine learning techniques, significantly increases selectivity in pre-miRNA ab initio prediction, which optimally contributes to advanced studies on miRNAs, as the need of biological validations is diminished. Hopefully, new research, such as studies of severe diseases caused by miRNA malfunction, will benefit from the proposed computational tool.

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

    Science.gov (United States)

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

    2016-07-11

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

  5. Distance based control system for machine vision-based selective spraying

    NARCIS (Netherlands)

    Steward, B.L.; Tian, L.F.; Tang, L.

    2002-01-01

    For effective operation of a selective sprayer with real-time local weed sensing, herbicides must be delivered, accurately to weed targets in the field. With a machine vision-based selective spraying system, acquiring sequential images and switching nozzles on and off at the correct locations are

  6. Reduced plasma aldosterone concentrations in randomly selected patients with insulin-dependent diabetes mellitus.

    LENUS (Irish Health Repository)

    Cronin, C C

    2012-02-03

    Abnormalities of the renin-angiotensin system have been reported in patients with diabetes mellitus and with diabetic complications. In this study, plasma concentrations of prorenin, renin, and aldosterone were measured in a stratified random sample of 110 insulin-dependent (Type 1) diabetic patients attending our outpatient clinic. Fifty-four age- and sex-matched control subjects were also examined. Plasma prorenin concentration was higher in patients without complications than in control subjects when upright (geometric mean (95% confidence intervals (CI): 75.9 (55.0-105.6) vs 45.1 (31.6-64.3) mU I-1, p < 0.05). There was no difference in plasma prorenin concentration between patients without and with microalbuminuria and between patients without and with background retinopathy. Plasma renin concentration, both when supine and upright, was similar in control subjects, in patients without complications, and in patients with varying degrees of diabetic microangiopathy. Plasma aldosterone was suppressed in patients without complications in comparison to control subjects (74 (58-95) vs 167 (140-199) ng I-1, p < 0.001) and was also suppressed in patients with microvascular disease. Plasma potassium was significantly higher in patients than in control subjects (mean +\\/- standard deviation: 4.10 +\\/- 0.36 vs 3.89 +\\/- 0.26 mmol I-1; p < 0.001) and plasma sodium was significantly lower (138 +\\/- 4 vs 140 +\\/- 2 mmol I-1; p < 0.001). We conclude that plasma prorenin is not a useful early marker for diabetic microvascular disease. Despite apparently normal plasma renin concentrations, plasma aldosterone is suppressed in insulin-dependent diabetic patients.

  7. Cross-covariance functions for multivariate random fields based on latent dimensions

    KAUST Repository

    Apanasovich, T. V.; Genton, M. G.

    2010-01-01

    The problem of constructing valid parametric cross-covariance functions is challenging. We propose a simple methodology, based on latent dimensions and existing covariance models for univariate random fields, to develop flexible, interpretable

  8. Core Business Selection Based on Ant Colony Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Yu Lan

    2014-01-01

    Full Text Available Core business is the most important business to the enterprise in diversified business. In this paper, we first introduce the definition and characteristics of the core business and then descript the ant colony clustering algorithm. In order to test the effectiveness of the proposed method, Tianjin Port Logistics Development Co., Ltd. is selected as the research object. Based on the current situation of the development of the company, the core business of the company can be acquired by ant colony clustering algorithm. Thus, the results indicate that the proposed method is an effective way to determine the core business for company.

  9. Multichannel Selective Femtosecond Coherent Control Based on Symmetry Properties

    International Nuclear Information System (INIS)

    Amitay, Zohar; Gandman, Andrey; Chuntonov, Lev; Rybak, Leonid

    2008-01-01

    We present and implement a new scheme for extended multichannel selective femtosecond coherent control based on symmetry properties of the excitation channels. Here, an atomic nonresonant two-photon absorption channel is coherently incorporated in a resonance-mediated (2+1) three-photon absorption channel. By proper pulse shaping, utilizing the invariance of the two-photon absorption to specific phase transformations of the pulse, the three-photon absorption is tuned independently over an order-of-magnitude yield range for any possible two-photon absorption yield. Noticeable is a set of ''two-photon dark pulses'' inducing widely tunable three-photon absorption

  10. Markov random field based automatic image alignment for electron tomography.

    Science.gov (United States)

    Amat, Fernando; Moussavi, Farshid; Comolli, Luis R; Elidan, Gal; Downing, Kenneth H; Horowitz, Mark

    2008-03-01

    We present a method for automatic full-precision alignment of the images in a tomographic tilt series. Full-precision automatic alignment of cryo electron microscopy images has remained a difficult challenge to date, due to the limited electron dose and low image contrast. These facts lead to poor signal to noise ratio (SNR) in the images, which causes automatic feature trackers to generate errors, even with high contrast gold particles as fiducial features. To enable fully automatic alignment for full-precision reconstructions, we frame the problem probabilistically as finding the most likely particle tracks given a set of noisy images, using contextual information to make the solution more robust to the noise in each image. To solve this maximum likelihood problem, we use Markov Random Fields (MRF) to establish the correspondence of features in alignment and robust optimization for projection model estimation. The resulting algorithm, called Robust Alignment and Projection Estimation for Tomographic Reconstruction, or RAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as good as the manual approach by an expert user. We are able to automatically map complete and partial marker trajectories and thus obtain highly accurate image alignment. Our method has been applied to challenging cryo electron tomographic datasets with low SNR from intact bacterial cells, as well as several plastic section and X-ray datasets.

  11. Focal plane based wavefront sensing with random DM probes

    Science.gov (United States)

    Pluzhnik, Eugene; Sirbu, Dan; Belikov, Ruslan; Bendek, Eduardo; Dudinov, Vladimir N.

    2017-09-01

    An internal coronagraph with an adaptive optical system for wavefront control is being considered for direct imaging of exoplanets with upcoming space missions and concepts, including WFIRST, HabEx, LUVOIR, EXCEDE and ACESat. The main technical challenge associated with direct imaging of exoplanets is to control of both diffracted and scattered light from the star so that even a dim planetary companion can be imaged. For a deformable mirror (DM) to create a dark hole with 10-10 contrast in the image plane, wavefront errors must be accurately measured on the science focal plane detector to ensure a common optical path. We present here a method that uses a set of random phase probes applied to the DM to obtain a high accuracy wavefront estimate even for a dynamically changing optical system. The presented numerical simulations and experimental results show low noise sensitivity, high reliability, and robustness of the proposed approach. The method does not use any additional optics or complex calibration procedures and can be used during the calibration stage of any direct imaging mission. It can also be used in any optical experiment that uses a DM as an active optical element in the layout.

  12. Nitrates and bone turnover (NABT) - trial to select the best nitrate preparation: study protocol for a randomized controlled trial.

    Science.gov (United States)

    Bucur, Roxana C; Reid, Lauren S; Hamilton, Celeste J; Cummings, Steven R; Jamal, Sophie A

    2013-09-08

    comparisons with the best' approach for data analyses, as this strategy allows practical considerations of ease of use and tolerability to guide selection of the preparation for future studies. Data from this protocol will be used to develop a randomized, controlled trial of nitrates to prevent osteoporotic fractures. ClinicalTrials.gov Identifier: NCT01387672. Controlled-Trials.com: ISRCTN08860742.

  13. Carbon Nanotube-Based Ion Selective Sensors for Wearable Applications.

    Science.gov (United States)

    Roy, Soumyendu; David-Pur, Moshe; Hanein, Yael

    2017-10-11

    Wearable electronics offer new opportunities in a wide range of applications, especially sweat analysis using skin sensors. A fundamental challenge in these applications is the formation of sensitive and stable electrodes. In this article we report the development of a wearable sensor based on carbon nanotube (CNT) electrode arrays for sweat sensing. Solid-state ion selective electrodes (ISEs), sensitive to Na + ions, were prepared by drop coating plasticized poly(vinyl chloride) (PVC) doped with ionophore and ion exchanger on CNT electrodes. The ion selective membrane (ISM) filled the intertubular spaces of the highly porous CNT film and formed an attachment that was stronger than that achieved with flat Au, Pt, or carbon electrodes. Concentration of the ISM solution used influenced the attachment to the CNT film, the ISM surface morphology, and the overall performance of the sensor. Sensitivity of 56 ± 3 mV/decade to Na + ions was achieved. Optimized solid-state reference electrodes (REs), suitable for wearable applications, were prepared by coating CNT electrodes with colloidal dispersion of Ag/AgCl, agarose hydrogel with 0.5 M NaCl, and a passivation layer of PVC doped with NaCl. The CNT-based REs had low sensitivity (-1.7 ± 1.2 mV/decade) toward the NaCl solution and high repeatability and were superior to bare Ag/AgCl, metals, carbon, and CNT films, reported previously as REs. CNT-based ISEs were calibrated against CNT-based REs, and the short-term stability of the system was tested. We demonstrate that CNT-based devices implemented on a flexible support are a very attractive platform for future wearable technology devices.

  14. Patch-based visual tracking with online representative sample selection

    Science.gov (United States)

    Ou, Weihua; Yuan, Di; Li, Donghao; Liu, Bin; Xia, Daoxun; Zeng, Wu

    2017-05-01

    Occlusion is one of the most challenging problems in visual object tracking. Recently, a lot of discriminative methods have been proposed to deal with this problem. For the discriminative methods, it is difficult to select the representative samples for the target template updating. In general, the holistic bounding boxes that contain tracked results are selected as the positive samples. However, when the objects are occluded, this simple strategy easily introduces the noises into the training data set and the target template and then leads the tracker to drift away from the target seriously. To address this problem, we propose a robust patch-based visual tracker with online representative sample selection. Different from previous works, we divide the object and the candidates into several patches uniformly and propose a score function to calculate the score of each patch independently. Then, the average score is adopted to determine the optimal candidate. Finally, we utilize the non-negative least square method to find the representative samples, which are used to update the target template. The experimental results on the object tracking benchmark 2013 and on the 13 challenging sequences show that the proposed method is robust to the occlusion and achieves promising results.

  15. Tyrosinase-Based Biosensors for Selective Dopamine Detection

    Directory of Open Access Journals (Sweden)

    Monica Florescu

    2017-06-01

    Full Text Available A novel tyrosinase-based biosensor was developed for the detection of dopamine (DA. For increased selectivity, gold electrodes were previously modified with cobalt (II-porphyrin (CoP film with electrocatalytic activity, to act both as an electrochemical mediator and an enzyme support, upon which the enzyme tyrosinase (Tyr was cross-linked. Differential pulse voltammetry was used for electrochemical detection and the reduction current of dopamine-quinone was measured as a function of dopamine concentration. Our experiments demonstrated that the presence of CoP improves the selectivity of the electrode towards dopamine in the presence of ascorbic acid (AA, with a linear trend of concentration dependence in the range of 2–30 µM. By optimizing the conditioning parameters, a separation of 130 mV between the peak potentials for ascorbic acid AA and DA was obtained, allowing the selective detection of DA. The biosensor had a sensitivity of 1.22 ± 0.02 µA·cm−2·µM−1 and a detection limit of 0.43 µM. Biosensor performances were tested in the presence of dopamine medication, with satisfactory results in terms of recovery (96%, and relative standard deviation values below 5%. These results confirmed the applicability of the biosensors in real samples such as human urine and blood serum.

  16. Road Network Selection Based on Road Hierarchical Structure Control

    Directory of Open Access Journals (Sweden)

    HE Haiwei

    2015-04-01

    Full Text Available A new road network selection method based on hierarchical structure is studied. Firstly, road network is built as strokes which are then classified into hierarchical collections according to the criteria of betweenness centrality value (BC value. Secondly, the hierarchical structure of the strokes is enhanced using structural characteristic identification technique. Thirdly, the importance calculation model was established according to the relationships among the hierarchical structure of the strokes. Finally, the importance values of strokes are got supported with the model's hierarchical calculation, and with which the road network is selected. Tests are done to verify the advantage of this method by comparing it with other common stroke-oriented methods using three kinds of typical road network data. Comparision of the results show that this method had few need to semantic data, and could eliminate the negative influence of edge strokes caused by the criteria of BC value well. So, it is better to maintain the global hierarchical structure of road network, and suitable to meet with the selection of various kinds of road network at the same time.

  17. Development of a Layered Conditional Random Field Based ...

    African Journals Online (AJOL)

    PROF. OLIVER OSUAGWA

    2014-12-01

    Dec 1, 2014 ... The recent denial of service attacks on major Internet sites has shown that no open ..... of a single record, which further degrades attack detection accuracy. ... distributed intrusion detection framework based on mobile agents.

  18. Assessment of fracture risk: value of random population-based samples--the Geelong Osteoporosis Study.

    Science.gov (United States)

    Henry, M J; Pasco, J A; Seeman, E; Nicholson, G C; Sanders, K M; Kotowicz, M A

    2001-01-01

    Fracture risk is determined by bone mineral density (BMD). The T-score, a measure of fracture risk, is the position of an individual's BMD in relation to a reference range. The aim of this study was to determine the magnitude of change in the T-score when different sampling techniques were used to produce the reference range. Reference ranges were derived from three samples, drawn from the same region: (1) an age-stratified population-based random sample, (2) unselected volunteers, and (3) a selected healthy subset of the population-based sample with no diseases or drugs known to affect bone. T-scores were calculated using the three reference ranges for a cohort of women who had sustained a fracture and as a group had a low mean BMD (ages 35-72 yr; n = 484). For most comparisons, the T-scores for the fracture cohort were more negative using the population reference range. The difference in T-scores reached 1.0 SD. The proportion of the fracture cohort classified as having osteoporosis at the spine was 26, 14, and 23% when the population, volunteer, and healthy reference ranges were applied, respectively. The use of inappropriate reference ranges results in substantial changes to T-scores and may lead to inappropriate management.

  19. Address-based versus random-digit-dial surveys: comparison of key health and risk indicators.

    Science.gov (United States)

    Link, Michael W; Battaglia, Michael P; Frankel, Martin R; Osborn, Larry; Mokdad, Ali H

    2006-11-15

    Use of random-digit dialing (RDD) for conducting health surveys is increasingly problematic because of declining participation rates and eroding frame coverage. Alternative survey modes and sampling frames may improve response rates and increase the validity of survey estimates. In a 2005 pilot study conducted in six states as part of the Behavioral Risk Factor Surveillance System, the authors administered a mail survey to selected household members sampled from addresses in a US Postal Service database. The authors compared estimates based on data from the completed mail surveys (n = 3,010) with those from the Behavioral Risk Factor Surveillance System telephone surveys (n = 18,780). The mail survey data appeared reasonably complete, and estimates based on data from the two survey modes were largely equivalent. Differences found, such as differences in the estimated prevalences of binge drinking (mail = 20.3%, telephone = 13.1%) or behaviors linked to human immunodeficiency virus transmission (mail = 7.1%, telephone = 4.2%), were consistent with previous research showing that, for questions about sensitive behaviors, self-administered surveys generally produce higher estimates than interviewer-administered surveys. The mail survey also provided access to cell-phone-only households and households without telephones, which cannot be reached by means of standard RDD surveys.

  20. NMR diffusion simulation based on conditional random walk.

    Science.gov (United States)

    Gudbjartsson, H; Patz, S

    1995-01-01

    The authors introduce here a new, very fast, simulation method for free diffusion in a linear magnetic field gradient, which is an extension of the conventional Monte Carlo (MC) method or the convolution method described by Wong et al. (in 12th SMRM, New York, 1993, p.10). In earlier NMR-diffusion simulation methods, such as the finite difference method (FD), the Monte Carlo method, and the deterministic convolution method, the outcome of the calculations depends on the simulation time step. In the authors' method, however, the results are independent of the time step, although, in the convolution method the step size has to be adequate for spins to diffuse to adjacent grid points. By always selecting the largest possible time step the computation time can therefore be reduced. Finally the authors point out that in simple geometric configurations their simulation algorithm can be used to reduce computation time in the simulation of restricted diffusion.

  1. Effects of choice architecture and chef-enhanced meals on the selection and consumption of healthier school foods: a randomized clinical trial.

    Science.gov (United States)

    Cohen, Juliana F W; Richardson, Scott A; Cluggish, Sarah A; Parker, Ellen; Catalano, Paul J; Rimm, Eric B

    2015-05-01

    Little is known about the long-term effect of a chef-enhanced menu on healthier food selection and consumption in school lunchrooms. In addition, it remains unclear if extended exposure to other strategies to promote healthier foods (eg, choice architecture) also improves food selection or consumption. To evaluate the short- and long-term effects of chef-enhanced meals and extended exposure to choice architecture on healthier school food selection and consumption. A school-based randomized clinical trial was conducted during the 2011-2012 school year among 14 elementary and middle schools in 2 urban, low-income school districts (intent-to-treat analysis). Included in the study were 2638 students in grades 3 through 8 attending participating schools (38.4% of eligible participants). Schools were first randomized to receive a professional chef to improve school meal palatability (chef schools) or to a delayed intervention (control group). To assess the effect of choice architecture (smart café), all schools after 3 months were then randomized to the smart café intervention or to the control group. School food selection was recorded, and consumption was measured using plate waste methods. After 3 months, vegetable selection increased in chef vs control schools (odds ratio [OR], 1.75; 95% CI, 1.36-2.24), but there was no effect on the selection of other components or on meal consumption. After long-term or extended exposure to the chef or smart café intervention, fruit selection increased in the chef (OR, 3.08; 95% CI, 2.23-4.25), smart café (OR, 1.45; 95% CI, 1.13-1.87), and chef plus smart café (OR, 3.10; 95% CI, 2.26-4.25) schools compared with the control schools, and consumption increased in the chef schools (OR, 0.17; 95% CI, 0.03-0.30 cups/d). Vegetable selection increased in the chef (OR, 2.54; 95% CI, 1.83-3.54), smart café (OR, 1.91; 95% CI, 1.46-2.50), and chef plus smart café schools (OR, 7.38, 95% CI, 5.26-10.35) compared with the control schools

  2. Fuzzy Axiomatic Design approach based green supplier selection

    DEFF Research Database (Denmark)

    Kannan, Devika; Govindan, Kannan; Rajendran, Sivakumar

    2015-01-01

    proposes a multi-criteria decision-making (MCDM) approach called Fuzzy Axiomatic Design (FAD) to select the best green supplier for Singapore-based plastic manufacturing company. At first, the environmental criteria was developed along with the traditional criteria based on the literature review......Abstract Green Supply Chain Management (GSCM) is a developing concept recently utilized by manufacturing firms of all sizes. All industries, small or large, seek improvements in the purchasing of raw materials, manufacturing, allocation, transportation efficiency, in curbing storage time, importing...... responsible in addition to being efficiently managed. A significant way to implement responsible GSCM is to reconsider, in innovative ways, the purchase and supply cycle, and a preliminary step would be to ensure that the supplier of goods successfully incorporates green criteria. Therefore, this paper...

  3. Tunable antenna radome based on graphene frequency selective surface

    Science.gov (United States)

    Qu, Meijun; Rao, Menglou; Li, Shufang; Deng, Li

    2017-09-01

    In this paper, a graphene-based frequency selective surface (FSS) is proposed. The proposed FSS exhibits a tunable bandpass filtering characteristic due to the alterable conductivity of the graphene strips which is controlled by chemical potential. Based on the reconfigurable bandpass property of the proposed FSS, a cylindrical antenna radome is designed using the FSS unit cells. A conventional omnidirectional dipole can realize a two-beam directional pattern when it is placed into the proposed antenna radome. Forward and backward endfire radiations of the dipole loaded with the radome is realized by properly adjusting the chemical potential. The proposed antenna radome is extremely promising for beam-scanning in terahertz and mid-infrared plasmonic devices and systems when the gain of a conventional antenna needs to be enhanced.

  4. SELECTION OF RECIPIENTS FOR HEART TRANSPLANTATION BASED ON URGENCY STATUS

    Directory of Open Access Journals (Sweden)

    O. A. Sujayeva

    2014-01-01

    Full Text Available The article provides the overview of current international recommendations dedicated to selection of heart transplantation recipients based on urgency status. Authors found that cardiopulmonary bicycle stress test allowed to reveal additional criteria of high death risk within 1 year. These additional criteria were: the maximal oxygen consumption VO2max < 30% of the expected considering the age; VD/VT (ratio of physiologic dead space over tidal volume increasing during the test; maximal tolerance to physical loading ≤50 Wt and/or < 20% of the expected considering the age. Authors created mathematical model for prediction of death within 1 year based on above mentioned data. Special software estimating the probability of death within 1 year was also created.

  5. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    Directory of Open Access Journals (Sweden)

    Sungho Kim

    2016-07-01

    Full Text Available Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR images or infrared (IR images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter and an asymmetric morphological closing filter (AMCF, post-filter into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic

  6. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    Science.gov (United States)

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-01-01

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  7. The influence of extrinsic motivation on competition-based selection.

    Science.gov (United States)

    Sänger, Jessica; Wascher, Edmund

    2011-10-10

    The biased competition approach to visuo-spatial attention proposes that the selection of competing information is effected by the saliency of the stimulus as well as by an intention-based bias of attention towards behavioural goals. Wascher and Beste (2010) [32] showed that the detection of relevant information depends on its relative saliency compared to irrelevant conflicting stimuli. Furthermore the N1pc, N2pc and N2 of the EEG varied with the strength of the conflict. However, this system could also be modulated by rather global mechanisms like attentional effort. The present study investigates such modulations by testing the influence of extrinsic motivation on the selection of competing stimuli. Participants had to detect a luminance change in various conditions among others against an irrelevant orientation change. Half of the participants were motivated to maximize their performance by the announcement of a monetary reward for correct responses. Participants who were motivated had lower error rates than participants who were not motivated. The event-related lateralizations of the EEG showed no motivation-related effect on the N1pc, which reflects the initial saliency driven orientation of attention towards the more salient stimulus. The subsequent N2pc was enhanced in the motivation condition. Extrinsic motivation was also accompanied by enhanced fronto-central negativities. Thus, the data provide evidence that the improvement of selection performance when participants were extrinsically motivated by announcing a reward was not due to changes in the initial saliency based processing of information but was foremost mediated by improved higher-level mechanisms. Copyright © 2011 Elsevier B.V. All rights reserved.

  8. Selection of Vendor Based on Intuitionistic Fuzzy Analytical Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Prabjot Kaur

    2014-01-01

    Full Text Available Business environment is characterized by greater domestic and international competitive position in the global market. Vendors play a key role in achieving the so-called corporate competition. It is not easy however to identify good vendors because evaluation is based on multiple criteria. In practice, for VSP most of the input information about the criteria is not known precisely. Intuitionistic fuzzy set is an extension of the classical fuzzy set theory (FST, which is a suitable way to deal with impreciseness. In other words, the application of intuitionistic fuzzy sets instead of fuzzy sets means the introduction of another degree of freedom called nonmembership function into the set description. In this paper, we proposed a triangular intuitionistic fuzzy number based approach for the vendor selection problem using analytical hierarchy process. The crisp data of the vendors is represented in the form of triangular intuitionistic fuzzy numbers. By applying AHP which involves decomposition, pairwise comparison, and deriving priorities for the various levels of the hierarchy, an overall crisp priority is obtained for ranking the best vendor. A numerical example illustrates our method. Lastly a sensitivity analysis is performed to find the most critical criterion on the basis of which vendor is selected.

  9. Selectively Encrypted Pull-Up Based Watermarking of Biometric data

    Science.gov (United States)

    Shinde, S. A.; Patel, Kushal S.

    2012-10-01

    Biometric authentication systems are becoming increasingly popular due to their potential usage in information security. However, digital biometric data (e.g. thumb impression) are themselves vulnerable to security attacks. There are various methods are available to secure biometric data. In biometric watermarking the data are embedded in an image container and are only retrieved if the secrete key is available. This container image is encrypted to have more security against the attack. As wireless devices are equipped with battery as their power supply, they have limited computational capabilities; therefore to reduce energy consumption we use the method of selective encryption of container image. The bit pull-up-based biometric watermarking scheme is based on amplitude modulation and bit priority which reduces the retrieval error rate to great extent. By using selective Encryption mechanism we expect more efficiency in time at the time of encryption as well as decryption. Significant reduction in error rate is expected to be achieved by the bit pull-up method.

  10. True random number generation from mobile telephone photo based on chaotic cryptography

    International Nuclear Information System (INIS)

    Zhao Liang; Liao Xiaofeng; Xiao Di; Xiang Tao; Zhou Qing; Duan Shukai

    2009-01-01

    A cheap, convenient and universal TRNG based on mobile telephone photo for producing random bit sequence is proposed. To settle the problem of sequential pixels and comparability, three chaos-based approaches are applied to post-process the generated binary image. The random numbers produced by three users are tested using US NIST RNG statistical test software. The experimental results indicate that the Arnold cat map is the fastest way to generate a random bit sequence and can be accepted on general PC. The 'MASK' algorithm also performs well. Finally, comparing with the TRNG of Hu et al. [Hu Y, Liao X, Wong KW, Zhou Q. A true random number generator based on mouse movement and chaotic cryptography. Chaos, Solitons and Fractals 2007. doi: 10.1016/j.chaos.2007.10.022] which is presented by Hu et al., many merits of the proposed TRNG in this paper has been found.

  11. Preferential selection based on degree difference in the spatial prisoner's dilemma games

    Science.gov (United States)

    Huang, Changwei; Dai, Qionglin; Cheng, Hongyan; Li, Haihong

    2017-10-01

    Strategy evolution in spatial evolutionary games is generally implemented through imitation processes between individuals. In most previous studies, it is assumed that individuals pick up one of their neighbors randomly to learn from. However, by considering the heterogeneity of individuals' influence in the real society, preferential selection is more realistic. Here, we introduce a preferential selection mechanism based on degree difference into spatial prisoner's dilemma games on Erdös-Rényi networks and Barabási-Albert scale-free networks and investigate the effects of the preferential selection on cooperation. The results show that, when the individuals prefer to choose the neighbors who have small degree difference with themselves to imitate, cooperation is hurt by the preferential selection. In contrast, when the individuals prefer to choose those large degree difference neighbors to learn from, there exists optimal preference strength resulting in the maximal cooperation level no matter what the network structure is. In addition, we investigate the robustness of the results against variations of the noise, the average degree and the size of network in the model, and find that the qualitative features of the results are unchanged.

  12. A Data Management System Integrating Web-based Training and Randomized Trials: Requirements, Experiences and Recommendations.

    Science.gov (United States)

    Muroff, Jordana; Amodeo, Maryann; Larson, Mary Jo; Carey, Margaret; Loftin, Ralph D

    2011-01-01

    This article describes a data management system (DMS) developed to support a large-scale randomized study of an innovative web-course that was designed to improve substance abuse counselors' knowledge and skills in applying a substance abuse treatment method (i.e., cognitive behavioral therapy; CBT). The randomized trial compared the performance of web-course-trained participants (intervention group) and printed-manual-trained participants (comparison group) to determine the effectiveness of the web-course in teaching CBT skills. A single DMS was needed to support all aspects of the study: web-course delivery and management, as well as randomized trial management. The authors briefly reviewed several other systems that were described as built either to handle randomized trials or to deliver and evaluate web-based training. However it was clear that these systems fell short of meeting our needs for simultaneous, coordinated management of the web-course and the randomized trial. New England Research Institute's (NERI) proprietary Advanced Data Entry and Protocol Tracking (ADEPT) system was coupled with the web-programmed course and customized for our purposes. This article highlights the requirements for a DMS that operates at the intersection of web-based course management systems and randomized clinical trial systems, and the extent to which the coupled, customized ADEPT satisfied those requirements. Recommendations are included for institutions and individuals considering conducting randomized trials and web-based training programs, and seeking a DMS that can meet similar requirements.

  13. Condition-Based Conveyor Belt Replacement Strategy in Lignite Mines with Random Belt Deterioration

    Science.gov (United States)

    Blazej, Ryszard; Jurdziak, Leszek

    2017-12-01

    In Polish lignite surface mines, condition-based belt replacement strategies are applied in order to assure profitable refurbishment of worn out belts performed by external firms specializing in belt maintenance. In two of three lignite mines, staff asses belt condition subjectively during visual inspections. Only one mine applies specialized diagnostic device (HRDS) allowing objective magnetic evaluation of belt core condition in order to choose the most profitable moment for the dismantling of worn out belt segments from conveyors and sending them to the maintenance firm which provides their refurbishment. This article describes the advantages of a new diagnostic device called DiagBelt. It was developed at the Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology. Economic gains from its application are calculated for the lignite mine and for the belt maintenance firm, taking into account random life (durability) of new and reconditioned belts (after the 1st and the 2nd refurbishment). Recursive calculations for following years allow the estimation of the length and costs of replaced, reconditioned and purchased belts on an annual basis, while the use of the Monte Carlo method allows the estimation of their variability caused by random deterioration of belts. Savings are obtained due to better selection of moments (times) for the replacement of belt segments and die to the possibility to qualify worn out belts for refurbishment without the need to remove their covers. In effect, increased belt durability and lowered share of waste belts (which were not qualified for reconditioning) create savings which can quickly cover expenditures on new diagnostic tools and regular belt inspections in the mine.

  14. SHER: A Colored Petri Net Based Random Mobility Model for Wireless Communications

    Science.gov (United States)

    Khan, Naeem Akhtar; Ahmad, Farooq; Khan, Sher Afzal

    2015-01-01

    In wireless network research, simulation is the most imperative technique to investigate the network’s behavior and validation. Wireless networks typically consist of mobile hosts; therefore, the degree of validation is influenced by the underlying mobility model, and synthetic models are implemented in simulators because real life traces are not widely available. In wireless communications, mobility is an integral part while the key role of a mobility model is to mimic the real life traveling patterns to study. The performance of routing protocols and mobility management strategies e.g. paging, registration and handoff is highly dependent to the selected mobility model. In this paper, we devise and evaluate the Show Home and Exclusive Regions (SHER), a novel two-dimensional (2-D) Colored Petri net (CPN) based formal random mobility model, which exhibits sociological behavior of a user. The model captures hotspots where a user frequently visits and spends time. Our solution eliminates six key issues of the random mobility models, i.e., sudden stops, memoryless movements, border effect, temporal dependency of velocity, pause time dependency, and speed decay in a single model. The proposed model is able to predict the future location of a mobile user and ultimately improves the performance of wireless communication networks. The model follows a uniform nodal distribution and is a mini simulator, which exhibits interesting mobility patterns. The model is also helpful to those who are not familiar with the formal modeling, and users can extract meaningful information with a single mouse-click. It is noteworthy that capturing dynamic mobility patterns through CPN is the most challenging and virulent activity of the presented research. Statistical and reachability analysis techniques are presented to elucidate and validate the performance of our proposed mobility model. The state space methods allow us to algorithmically derive the system behavior and rectify the

  15. A cluster-based randomized controlled trial promoting community participation in arsenic mitigation efforts in Bangladesh.

    Science.gov (United States)

    George, Christine Marie; van Geen, Alexander; Slavkovich, Vesna; Singha, Ashit; Levy, Diane; Islam, Tariqul; Ahmed, Kazi Matin; Moon-Howard, Joyce; Tarozzi, Alessandro; Liu, Xinhua; Factor-Litvak, Pam; Graziano, Joseph

    2012-06-19

    To reduce arsenic (As) exposure, we evaluated the effectiveness of training community members to perform water arsenic (WAs) testing and provide As education compared to sending representatives from outside communities to conduct these tasks. We conducted a cluster based randomized controlled trial of 20 villages in Singair, Bangladesh. Fifty eligible respondents were randomly selected in each village. In 10 villages, a community member provided As education and WAs testing. In a second set of 10 villages an outside representative performed these tasks. Overall, 53% of respondents using As contaminated wells, relative to the Bangladesh As standard of 50 μg/L, at baseline switched after receiving the intervention. Further, when there was less than 60% arsenic contaminated wells in a village, the classification used by the Bangladeshi and UNICEF, 74% of study households in the community tester villages, and 72% of households in the outside tester villages reported switching to an As safe drinking water source. Switching was more common in the outside-tester (63%) versus community-tester villages (44%). However, after adjusting for the availability of arsenic safe drinking water sources, well switching did not differ significantly by type of As tester (Odds ratio = 0.86[95% confidence interval 0.42-1.77). At follow-up, among those using As contaminated wells who switched to safe wells, average urinary As concentrations significantly decreased. The overall intervention was effective in reducing As exposure provided there were As-safe drinking water sources available. However, there was not a significant difference observed in the ability of the community and outside testers to encourage study households to use As-safe water sources. The findings of this study suggest that As education and WAs testing programs provided by As testers, irrespective of their residence, could be used as an effective, low cost approach to reduce As exposure in many As-affected areas of

  16. A cluster-based randomized controlled trial promoting community participation in arsenic mitigation efforts in Bangladesh

    Directory of Open Access Journals (Sweden)

    George Christine

    2012-06-01

    Full Text Available Abstract Objective To reduce arsenic (As exposure, we evaluated the effectiveness of training community members to perform water arsenic (WAs testing and provide As education compared to sending representatives from outside communities to conduct these tasks. Methods We conducted a cluster based randomized controlled trial of 20 villages in Singair, Bangladesh. Fifty eligible respondents were randomly selected in each village. In 10 villages, a community member provided As education and WAs testing. In a second set of 10 villages an outside representative performed these tasks. Results Overall, 53% of respondents using As contaminated wells, relative to the Bangladesh As standard of 50 μg/L, at baseline switched after receiving the intervention. Further, when there was less than 60% arsenic contaminated wells in a village, the classification used by the Bangladeshi and UNICEF, 74% of study households in the community tester villages, and 72% of households in the outside tester villages reported switching to an As safe drinking water source . Switching was more common in the outside-tester (63% versus community-tester villages (44%. However, after adjusting for the availability of arsenic safe drinking water sources, well switching did not differ significantly by type of As tester (Odds ratio =0.86[95% confidence interval 0.42-1.77. At follow-up, among those using As contaminated wells who switched to safe wells, average urinary As concentrations significantly decreased. Conclusion The overall intervention was effective in reducing As exposure provided there were As-safe drinking water sources available. However, there was not a significant difference observed in the ability of the community and outside testers to encourage study households to use As-safe water sources. The findings of this study suggest that As education and WAs testing programs provided by As testers, irrespective of their residence, could be used as an effective, low cost

  17. Optimizing block-based maintenance under random machine usage

    NARCIS (Netherlands)

    de Jonge, Bram; Jakobsons, Edgars

    Existing studies on maintenance optimization generally assume that machines are either used continuously, or that times until failure do not depend on the actual usage. In practice, however, these assumptions are often not realistic. In this paper, we consider block-based maintenance optimization

  18. A true random number generator based on mouse movement and chaotic cryptography

    International Nuclear Information System (INIS)

    Hu Yue; Liao Xiaofeng; Wong, Kwok-wo; Zhou Qing

    2009-01-01

    True random number generators are in general more secure than pseudo random number generators. In this paper, we propose a novel true random number generator which generates a 256-bit random number by computer mouse movement. It is cheap, convenient and universal for personal computers. To eliminate the effect of similar movement patterns generated by the same user, three chaos-based approaches, namely, discretized 2D chaotic map permutation, spatiotemporal chaos and 'MASK' algorithm, are adopted to post-process the captured mouse movements. Random bits generated by three users are tested using NIST statistical tests. Both the spatiotemporal chaos approach and the 'MASK' algorithm pass the tests successfully. However, the latter has a better performance in terms of efficiency and effectiveness and so is more practical for common personal computer applications.

  19. Post-processing Free Quantum Random Number Generator Based on Avalanche Photodiode Array

    International Nuclear Information System (INIS)

    Li Yang; Liao Sheng-Kai; Liang Fu-Tian; Shen Qi; Liang Hao; Peng Cheng-Zhi

    2016-01-01

    Quantum random number generators adopting single photon detection have been restricted due to the non-negligible dead time of avalanche photodiodes (APDs). We propose a new approach based on an APD array to improve the generation rate of random numbers significantly. This method compares the detectors' responses to consecutive optical pulses and generates the random sequence. We implement a demonstration experiment to show its simplicity, compactness and scalability. The generated numbers are proved to be unbiased, post-processing free, ready to use, and their randomness is verified by using the national institute of standard technology statistical test suite. The random bit generation efficiency is as high as 32.8% and the potential generation rate adopting the 32 × 32 APD array is up to tens of Gbits/s. (paper)

  20. Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

    Science.gov (United States)

    Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

    2017-01-01

    We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

  1. Selective Sequential Zero-Base Budgeting Procedures Based on Total Factor Productivity Indicators

    OpenAIRE

    A. Ishikawa; E. F. Sudit

    1981-01-01

    The authors' purpose in this paper is to develop productivity-based sequential budgeting procedures designed to expedite identification of major problem areas in bugetary performance, as well as to reduce the costs associated with comprehensive zero-base analyses. The concept of total factor productivity is reviewed and its relations to ordinary and zero-based budgeting are discussed in detail. An outline for a selective sequential analysis based on monitoring of three key indicators of (a) i...

  2. Mindfulness-based prevention for eating disorders: A school-based cluster randomized controlled study.

    Science.gov (United States)

    Atkinson, Melissa J; Wade, Tracey D

    2015-11-01

    Successful prevention of eating disorders represents an important goal due to damaging long-term impacts on health and well-being, modest treatment outcomes, and low treatment seeking among individuals at risk. Mindfulness-based approaches have received early support in the treatment of eating disorders, but have not been evaluated as a prevention strategy. This study aimed to assess the feasibility, acceptability, and efficacy of a novel mindfulness-based intervention for reducing the risk of eating disorders among adolescent females, under both optimal (trained facilitator) and task-shifted (non-expert facilitator) conditions. A school-based cluster randomized controlled trial was conducted in which 19 classes of adolescent girls (N = 347) were allocated to a three-session mindfulness-based intervention, dissonance-based intervention, or classes as usual control. A subset of classes (N = 156) receiving expert facilitation were analyzed separately as a proxy for delivery under optimal conditions. Task-shifted facilitation showed no significant intervention effects across outcomes. Under optimal facilitation, students receiving mindfulness demonstrated significant reductions in weight and shape concern, dietary restraint, thin-ideal internalization, eating disorder symptoms, and psychosocial impairment relative to control by 6-month follow-up. Students receiving dissonance showed significant reductions in socio-cultural pressures. There were no statistically significant differences between the two interventions. Moderate intervention acceptability was reported by both students and teaching staff. Findings show promise for the application of mindfulness in the prevention of eating disorders; however, further work is required to increase both impact and acceptability, and to enable successful outcomes when delivered by less expert providers. © 2015 Wiley Periodicals, Inc.

  3. Performance of Universal Adhesive in Primary Molars After Selective Removal of Carious Tissue: An 18-Month Randomized Clinical Trial.

    Science.gov (United States)

    Lenzi, Tathiane Larissa; Pires, Carine Weber; Soares, Fabio Zovico Maxnuck; Raggio, Daniela Prócida; Ardenghi, Thiago Machado; de Oliveira Rocha, Rachel

    2017-09-15

    To evaluate the 18-month clinical performance of a universal adhesive, applied under different adhesion strategies, after selective carious tissue removal in primary molars. Forty-four subjects (five to 10 years old) contributed with 90 primary molars presenting moderately deep dentin carious lesions on occlusal or occluso-proximal surfaces, which were randomly assigned following either self-etch or etch-and-rinse protocol of Scotchbond Universal Adhesive (3M ESPE). Resin composite was incrementally inserted for all restorations. Restorations were evaluated at one, six, 12, and 18 months using the modified United States Public Health Service criteria. Survival estimates for restorations' longevity were evaluated using the Kaplan-Meier method. Multivariate Cox regression analysis with shared frailty to assess the factors associated with failures (Padhesion strategy did not influence the restorations' longevity (P=0.06; 72.2 percent and 89.7 percent with etch-and-rinse and self-etch mode, respectively). Self-etch and etch-and-rinse strategies did not influence the clinical behavior of universal adhesive used in primary molars after selective carious tissue removal; although there was a tendency for better outcome of the self-etch strategy.

  4. Selective carbon monoxide oxidation over Ag-based composite oxides

    Energy Technology Data Exchange (ETDEWEB)

    Guldur, C. [Gazi University, Ankara (Turkey). Chemical Engineering Department; Balikci, F. [Gazi University, Ankara (Turkey). Institute of Science and Technology, Environmental Science Department

    2002-02-01

    We report our results of the synthesis of 1 : 1 molar ratio of the silver cobalt and silver manganese composite oxide catalysts to remove carbon monoxide from hydrogen-rich fuels by the catalytic oxidation reaction. Catalysts were synthesized by the co-precipitation method. XRD, BET, TGA, catalytic activity and catalyst deactivation studies were used to identify active catalysts. Both CO oxidation and selective CO oxidation were carried out in a microreactor using a reaction gas mixture of 1 vol% CO in air and another gas mixture was prepared by mixing 1 vol% CO, 2 vol% O{sub 2}, 84 vol% H{sub 2}, the balance being He. 15 vol% CO{sub 2} was added to the reactant gas mixture in order to determine the effect of CO{sub 2}, reaction gases were passed through the humidifier to determine the effect of the water vapor on the oxidation reaction. It was demonstrated that metal oxide base was decomposed to the metallic phase and surface areas of the catalysts were decreased when the calcination temperature increased from 200{sup o}C to 500{sup o}C. Ag/Co composite oxide catalyst calcined at 200{sup o}C gave good activity at low temperatures and 90% of CO conversion at 180{sup o}C was obtained for the selective CO oxidation reaction. The addition of the impurities (CO{sub 2} or H{sub 2}O) decreased the activity of catalyst for selective CO oxidation in order to get highly rich hydrogen fuels. (author)

  5. Implementation of evidence-based antenatal care in Mozambique: a cluster randomized controlled trial: study protocol.

    Science.gov (United States)

    Chavane, Leonardo; Merialdi, Mario; Betrán, Ana Pilar; Requejo-Harris, Jennifer; Bergel, Eduardo; Aleman, Alicia; Colomar, Mercedes; Cafferata, Maria Luisa; Carbonell, Alicia; Crahay, Beatrice; Delvaux, Therese; Geelhoed, Diederike; Gülmezoglu, Metin; Malapende, Celsa Regina; Melo, Armando; Nguyen, My Huong; Osman, Nafissa Bique; Widmer, Mariana; Temmerman, Marleen; Althabe, Fernando

    2014-05-21

    Antenatal care (ANC) reduces maternal and perinatal morbidity and mortality directly through the detection and treatment of pregnancy-related illnesses, and indirectly through the detection of women at increased risk of delivery complications. The potential benefits of quality antenatal care services are most significant in low-resource countries where morbidity and mortality levels among women of reproductive age and neonates are higher.WHO developed an ANC model that recommended the delivery of services scientifically proven to improve maternal, perinatal and neonatal outcomes. The aim of this study is to determine the effect of an intervention designed to increase the use of the package of evidence-based services included in the WHO ANC model in Mozambique. The primary hypothesis is that the intervention will increase the use of evidence-based practices during ANC visits in comparison to the standard dissemination channels currently used in the country. This is a demonstration project to be developed through a facility-based cluster randomized controlled trial with a stepped wedge design. The intervention was tailored, based on formative research findings, to be readily applicable to local prenatal care services and acceptable to local pregnant women and health providers. The intervention includes four components: the provision of kits with all necessary medicines and laboratory supplies for ANC (medical and non-medical equipment), a storage system, a tracking system, and training sessions for health care providers. Ten clinics were selected and will start receiving the intervention in a random order. Outcomes will be computed at each time point when a new clinic starts the intervention. The primary outcomes are the delivery of selected health care practices to women attending the first ANC visit, and secondary outcomes are the delivery of selected health care practices to women attending second and higher ANC visits as well as the attitude of midwives in

  6. Robust portfolio selection based on asymmetric measures of variability of stock returns

    Science.gov (United States)

    Chen, Wei; Tan, Shaohua

    2009-10-01

    This paper addresses a new uncertainty set--interval random uncertainty set for robust optimization. The form of interval random uncertainty set makes it suitable for capturing the downside and upside deviations of real-world data. These deviation measures capture distributional asymmetry and lead to better optimization results. We also apply our interval random chance-constrained programming to robust mean-variance portfolio selection under interval random uncertainty sets in the elements of mean vector and covariance matrix. Numerical experiments with real market data indicate that our approach results in better portfolio performance.

  7. A prototype of behavior selection mechanism based on emotion

    Science.gov (United States)

    Zhang, Guofeng; Li, Zushu

    2007-12-01

    In bionic methodology rather than in design methodology more familiar with, summarizing the psychological researches of emotion, we propose the biologic mechanism of emotion, emotion selection role in creature evolution and a anima framework including emotion similar to the classical control structure; and consulting Prospect Theory, build an Emotion Characteristic Functions(ECF) that computer emotion; two more emotion theories are added to them that higher emotion is preferred and middle emotion makes brain run more efficiently, emotional behavior mechanism comes into being. A simulation of proposed mechanism are designed and carried out on Alife Swarm software platform. In this simulation, a virtual grassland ecosystem is achieved where there are two kinds of artificial animals: herbivore and preyer. These artificial animals execute four types of behavior: wandering, escaping, finding food, finding sex partner in their lives. According the theories of animal ethnology, escaping from preyer is prior to other behaviors for its existence, finding food is secondly important behavior, rating is third one and wandering is last behavior. In keeping this behavior order, based on our behavior characteristic function theory, the specific functions of emotion computing are built of artificial autonomous animals. The result of simulation confirms the behavior selection mechanism.

  8. A Random-Dot Kinematogram for Web-Based Vision Research

    Directory of Open Access Journals (Sweden)

    Sivananda Rajananda

    2018-01-01

    Full Text Available Web-based experiments using visual stimuli have become increasingly common in recent years, but many frequently-used stimuli in vision research have yet to be developed for online platforms. Here, we introduce the first open access random-dot kinematogram (RDK for use in web browsers. This fully customizable RDK offers options to implement several different types of noise (random position, random walk, random direction and parameters to control aperture shape, coherence level, the number of dots, and other features. We include links to commented JavaScript code for easy implementation in web-based experiments, as well as an example of how this stimulus can be integrated as a plugin with a JavaScript library for online studies (jsPsych.

  9. A data based random number generator for a multivariate distribution (using stochastic interpolation)

    Science.gov (United States)

    Thompson, J. R.; Taylor, M. S.

    1982-01-01

    Let X be a K-dimensional random variable serving as input for a system with output Y (not necessarily of dimension k). given X, an outcome Y or a distribution of outcomes G(Y/X) may be obtained either explicitly or implicity. The situation is considered in which there is a real world data set X sub j sub = 1 (n) and a means of simulating an outcome Y. A method for empirical random number generation based on the sample of observations of the random variable X without estimating the underlying density is discussed.

  10. Novel β-lactamase-random peptide fusion libraries for phage display selection of cancer cell-targeting agents suitable for enzyme prodrug therapy

    Science.gov (United States)

    Shukla, Girja S.; Krag, David N.

    2010-01-01

    Novel phage-displayed random linear dodecapeptide (X12) and cysteine-constrained decapeptide (CX10C) libraries constructed in fusion to the amino-terminus of P99 β-lactamase molecules were used for identifying β-lactamase-linked cancer cell-specific ligands. The size and quality of both libraries were comparable to the standards of other reported phage display systems. Using the single-round panning method based on phage DNA recovery, we identified severalβ-lactamase fusion peptides that specifically bind to live human breast cancer MDA-MB-361 cells. The β-lactamase fusion to the peptides helped in conducting the enzyme activity-based clone normalization and cell-binding screening in a very time- and cost-efficient manner. The methods were suitable for 96-well readout as well as microscopic imaging. The success of the biopanning was indicated by the presence of ~40% cancer cell-specific clones among recovered phages. One of the binding clones appeared multiple times. The cancer cell-binding fusion peptides also shared several significant motifs. This opens a new way of preparing and selecting phage display libraries. The cancer cell-specific β-lactamase-linked affinity reagents selected from these libraries can be used for any application that requires a reporter for tracking the ligand molecules. Furthermore, these affinity reagents have also a potential for their direct use in the targeted enzyme prodrug therapy of cancer. PMID:19751096

  11. Do Culture-based Segments Predict Selection of Market Strategy?

    Directory of Open Access Journals (Sweden)

    Veronika Jadczaková

    2015-01-01

    Full Text Available Academists and practitioners have already acknowledged the importance of unobservable segmentation bases (such as psychographics yet still focusing on how well these bases are capable of describing relevant segments (the identifiability criterion rather than on how precisely these segments can predict (the predictability criterion. Therefore, this paper intends to add a debate to this topic by exploring whether culture-based segments do account for a selection of market strategy. To do so, a set of market strategy variables over a sample of 251 manufacturing firms was first regressed on a set of 19 cultural variables using canonical correlation analysis. Having found significant relationship in the first canonical function, it was further examined by means of correspondence analysis which cultural segments – if any – are linked to which market strategies. However, as correspondence analysis failed to find a significant relationship, it may be concluded that business culture might relate to the adoption of market strategy but not to the cultural groupings presented in the paper.

  12. Feature selection gait-based gender classification under different circumstances

    Science.gov (United States)

    Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah

    2014-05-01

    This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.

  13. Selective Osmotic Shock (SOS)-Based Islet Isolation for Microencapsulation.

    Science.gov (United States)

    Enck, Kevin; McQuilling, John Patrick; Orlando, Giuseppe; Tamburrini, Riccardo; Sivanandane, Sittadjody; Opara, Emmanuel C

    2017-01-01

    Islet transplantation (IT) has recently been shown to be a promising alternative to pancreas transplantation for reversing diabetes. IT requires the isolation of the islets from the pancreas, and these islets can be used to fabricate a bio-artificial pancreas. Enzymatic digestion is the current gold standard procedure for islet isolation but has lingering concerns. One such concern is that it has been shown to damage the islets due to nonselective tissue digestion. This chapter provides a detailed description of a nonenzymatic method that we are exploring in our lab as an alternative to current enzymatic digestion procedures for islet isolation from human and nonhuman pancreatic tissues. This method is based on selective destruction and protection of specific cell types and has been shown to leave the extracellular matrix (ECM) of islets intact, which may thus enhance islet viability and functionality. We also show that these SOS-isolated islets can be microencapsulated for transplantation.

  14. Analysis of Trust-Based Approaches for Web Service Selection

    DEFF Research Database (Denmark)

    Dragoni, Nicola; Miotto, Nicola

    2011-01-01

    The basic tenet of Service-Oriented Computing (SOC) is the possibility of building distributed applications on the Web by using Web services as fundamental building blocks. The proliferation of such services is considered the second wave of evolution in the Internet age, moving the Web from...... a collection of pages to a collections of services. Consensus is growing that this Web service revolution wont eventuate until we resolve trust-related issues. Indeed, the intrinsic openness of the SOC vision makes crucial to locate useful services and recognize them as trustworthy. In this paper we review...... the field of trust-based Web service selection, providing a structured classification of current approaches and highlighting the main limitations of each class and of the overall field....

  15. Wave impedance selection for passivity-based bilateral teleoperation

    Science.gov (United States)

    D'Amore, Nicholas John

    When a task must be executed in a remote or dangerous environment, teleoperation systems may be employed to extend the influence of the human operator. In the case of manipulation tasks, haptic feedback of the forces experienced by the remote (slave) system is often highly useful in improving an operator's ability to perform effectively. In many of these cases (especially teleoperation over the internet and ground-to-space teleoperation), substantial communication latency exists in the control loop and has the strong tendency to cause instability of the system. The first viable solution to this problem in the literature was based on a scattering/wave transformation from transmission line theory. This wave transformation requires the designer to select a wave impedance parameter appropriate to the teleoperation system. It is widely recognized that a small value of wave impedance is well suited to free motion and a large value is preferable for contact tasks. Beyond this basic observation, however, very little guidance exists in the literature regarding the selection of an appropriate value. Moreover, prior research on impedance selection generally fails to account for the fact that in any realistic contact task there will simultaneously exist contact considerations (perpendicular to the surface of contact) and quasi-free-motion considerations (parallel to the surface of contact). The primary contribution of the present work is to introduce an approximate linearized optimum for the choice of wave impedance and to apply this quasi-optimal choice to the Cartesian reality of such a contact task, in which it cannot be expected that a given joint will be either perfectly normal to or perfectly parallel to the motion constraint. The proposed scheme selects a wave impedance matrix that is appropriate to the conditions encountered by the manipulator. This choice may be implemented as a static wave impedance value or as a time-varying choice updated according to the

  16. Effectiveness of Wii-based rehabilitation in stroke: A randomized controlled study

    OpenAIRE

    Ayça Utkan Karasu; Elif Balevi Batur; Gülçin Kaymak Karataş

    2018-01-01

    Objective: To investigate the efficacy of Nintendo Wii Fit®-based balance rehabilitation as an adjunc-tive therapy to conventional rehabilitation in stroke patients. Methods: During the study period, 70 stroke patients were evaluated. Of these, 23 who met the study criteria were randomly assigned to either the experimental group (n = 12) or the control group (n = 11) by block randomization. Primary outcome measures were Berg Balance Scale, Functional Reach Test, Postural Asses...

  17. A new randomized Kaczmarz based kernel canonical correlation analysis algorithm with applications to information retrieval.

    Science.gov (United States)

    Cai, Jia; Tang, Yi

    2018-02-01

    Canonical correlation analysis (CCA) is a powerful statistical tool for detecting the linear relationship between two sets of multivariate variables. Kernel generalization of it, namely, kernel CCA is proposed to describe nonlinear relationship between two variables. Although kernel CCA can achieve dimensionality reduction results for high-dimensional data feature selection problem, it also yields the so called over-fitting phenomenon. In this paper, we consider a new kernel CCA algorithm via randomized Kaczmarz method. The main contributions of the paper are: (1) A new kernel CCA algorithm is developed, (2) theoretical convergence of the proposed algorithm is addressed by means of scaled condition number, (3) a lower bound which addresses the minimum number of iterations is presented. We test on both synthetic dataset and several real-world datasets in cross-language document retrieval and content-based image retrieval to demonstrate the effectiveness of the proposed algorithm. Numerical results imply the performance and efficiency of the new algorithm, which is competitive with several state-of-the-art kernel CCA methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. A Joint Land Cover Mapping and Image Registration Algorithm Based on a Markov Random Field Model

    Directory of Open Access Journals (Sweden)

    Apisit Eiumnoh

    2013-10-01

    Full Text Available Traditionally, image registration of multi-modal and multi-temporal images is performed satisfactorily before land cover mapping. However, since multi-modal and multi-temporal images are likely to be obtained from different satellite platforms and/or acquired at different times, perfect alignment is very difficult to achieve. As a result, a proper land cover mapping algorithm must be able to correct registration errors as well as perform an accurate classification. In this paper, we propose a joint classification and registration technique based on a Markov random field (MRF model to simultaneously align two or more images and obtain a land cover map (LCM of the scene. The expectation maximization (EM algorithm is employed to solve the joint image classification and registration problem by iteratively estimating the map parameters and approximate posterior probabilities. Then, the maximum a posteriori (MAP criterion is used to produce an optimum land cover map. We conducted experiments on a set of four simulated images and one pair of remotely sensed images to investigate the effectiveness and robustness of the proposed algorithm. Our results show that, with proper selection of a critical MRF parameter, the resulting LCMs derived from an unregistered image pair can achieve an accuracy that is as high as when images are perfectly aligned. Furthermore, the registration error can be greatly reduced.

  19. Randomized pharmacokinetic study comparing subcutaneous and intravenous palonosetron in cancer patients treated with platinum based chemotherapy.

    Directory of Open Access Journals (Sweden)

    Belen Sadaba

    Full Text Available Palonosetron is a potent second generation 5- hydroxytryptamine-3 selective antagonist which can be administered by either intravenous (IV or oral routes, but subcutaneous (SC administration of palonosetron has never been studied, even though it could have useful clinical applications. In this study, we evaluate the bioavailability of SC palonosetron.Patients treated with platinum-based chemotherapy were randomized to receive SC or IV palonosetron, followed by the alternative route in a crossover manner, during the first two cycles of chemotherapy. Blood samples were collected at baseline and 10, 15, 30, 45, 60, 90 minutes and 2, 3, 4, 6, 8, 12 and 24 h after palonosetron administration. Urine was collected during 12 hours following palonosetron. We compared pharmacokinetic parameters including AUC0-24h, t1/2, and Cmax observed with each route of administration by analysis of variance (ANOVA.From October 2009 to July 2010, 25 evaluable patients were included. AUC0-24h for IV and SC palonosetron were respectively 14.1 and 12.7 ng × h/ml (p=0.160. Bioavalability of SC palonosetron was 118% (95% IC: 69-168. Cmax was lower with SC than with IV route and was reached 15 minutes following SC administration.Palonosetron bioavailability was similar when administered by either SC or IV route. This new route of administration might be specially useful for outpatient management of emesis and for administration of oral chemotherapy.ClinicalTrials.gov NCT01046240.

  20. Feature Selection based on Machine Learning in MRIs for Hippocampal Segmentation

    Science.gov (United States)

    Tangaro, Sabina; Amoroso, Nicola; Brescia, Massimo; Cavuoti, Stefano; Chincarini, Andrea; Errico, Rosangela; Paolo, Inglese; Longo, Giuseppe; Maglietta, Rosalia; Tateo, Andrea; Riccio, Giuseppe; Bellotti, Roberto

    2015-01-01

    Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic resonance imaging (MRI) scans can show these variations and therefore can be used as a supportive feature for a number of neurodegenerative diseases. The hippocampus has been known to be a biomarker for Alzheimer disease and other neurological and psychiatric diseases. However, it requires accurate, robust, and reproducible delineation of hippocampal structures. Fully automatic methods are usually the voxel based approach; for each voxel a number of local features were calculated. In this paper, we compared four different techniques for feature selection from a set of 315 features extracted for each voxel: (i) filter method based on the Kolmogorov-Smirnov test; two wrapper methods, respectively, (ii) sequential forward selection and (iii) sequential backward elimination; and (iv) embedded method based on the Random Forest Classifier on a set of 10 T1-weighted brain MRIs and tested on an independent set of 25 subjects. The resulting segmentations were compared with manual reference labelling. By using only 23 feature for each voxel (sequential backward elimination) we obtained comparable state-of-the-art performances with respect to the standard tool FreeSurfer.

  1. IMRT QA: Selecting gamma criteria based on error detection sensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Steers, Jennifer M. [Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California 90048 and Physics and Biology in Medicine IDP, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90095 (United States); Fraass, Benedick A., E-mail: benedick.fraass@cshs.org [Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California 90048 (United States)

    2016-04-15

    Purpose: The gamma comparison is widely used to evaluate the agreement between measurements and treatment planning system calculations in patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA). However, recent publications have raised concerns about the lack of sensitivity when employing commonly used gamma criteria. Understanding the actual sensitivity of a wide range of different gamma criteria may allow the definition of more meaningful gamma criteria and tolerance limits in IMRT QA. We present a method that allows the quantitative determination of gamma criteria sensitivity to induced errors which can be applied to any unique combination of device, delivery technique, and software utilized in a specific clinic. Methods: A total of 21 DMLC IMRT QA measurements (ArcCHECK®, Sun Nuclear) were compared to QA plan calculations with induced errors. Three scenarios were studied: MU errors, multi-leaf collimator (MLC) errors, and the sensitivity of the gamma comparison to changes in penumbra width. Gamma comparisons were performed between measurements and error-induced calculations using a wide range of gamma criteria, resulting in a total of over 20 000 gamma comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using 36 different gamma criteria. Results: This study demonstrates that systematic errors and case-specific errors can be detected by the error curve analysis. Depending on the location of the error curve peak (e.g., not centered about zero), 3%/3 mm threshold = 10% at 90% pixels passing may miss errors as large as 15% MU errors and ±1 cm random MLC errors for some cases. As the dose threshold parameter was increased for a given %Diff/distance-to-agreement (DTA) setting, error sensitivity was increased by up to a factor of two for select cases. This increased sensitivity with increasing dose

  2. Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms

    Directory of Open Access Journals (Sweden)

    Fernando A. Auat Cheein

    2013-01-01

    Full Text Available Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance. In this article, a non-arbitrary measurement selection criterion for Gaussian-based algorithms is proposed. The measurement selection criterion is based on the determination of the most significant measurement from both an estimation convergence perspective and the covariance matrix associated with the measurement. The selection criterion is independent from the nature of the measured variable. This criterion is used in conjunction with three Gaussian-based algorithms: the EIF (Extended Information Filter, the EKF (Extended Kalman Filter and the UKF (Unscented Kalman Filter. Nevertheless, the measurement selection criterion shown herein can also be applied to other Gaussian-based algorithms. Although this work is focused on environment modeling, the results shown herein can be applied to other Gaussian-based algorithm implementations. Mathematical descriptions and implementation results that validate the proposal are also included in this work.

  3. Effects of Video Game Training on Measures of Selective Attention and Working Memory in Older Adults: Results from a Randomized Controlled Trial

    Science.gov (United States)

    Ballesteros, Soledad; Mayas, Julia; Prieto, Antonio; Ruiz-Marquez, Eloísa; Toril, Pilar; Reales, José M.

    2017-01-01

    Video game training with older adults potentially enhances aspects of cognition that decline with aging and could therefore offer a promising training approach. Although, previous published studies suggest that training can produce transfer, many of them have certain shortcomings. This randomized controlled trial (RCT; Clinicaltrials.gov ID: NCT02796508) tried to overcome some of these limitations by incorporating an active control group and the assessment of motivation and expectations. Seventy-five older volunteers were randomly assigned to the experimental group trained for 16 sessions with non-action video games from Lumosity, a commercial platform (http://www.lumosity.com/) or to an active control group trained for the same number of sessions with simulation strategy games. The final sample included 55 older adults (30 in the experimental group and 25 in the active control group). Participants were tested individually before and after training to assess working memory (WM) and selective attention and also reported their perceived improvement, motivation and engagement. The results showed improved performance across the training sessions. The main results were: (1) the experimental group did not show greater improvements in measures of selective attention and working memory than the active control group (the opposite occurred in the oddball task); (2) a marginal training effect was observed for the N-back task, but not for the Stroop task while both groups improved in the Corsi Blocks task. Based on these results, one can conclude that training with non-action games provide modest benefits for untrained tasks. The effect is not specific for that kind of training as a similar effect was observed for strategy video games. Groups did not differ in motivation, engagement or expectations. PMID:29163136

  4. Effects of Video Game Training on Measures of Selective Attention and Working Memory in Older Adults: Results from a Randomized Controlled Trial

    Directory of Open Access Journals (Sweden)

    Soledad Ballesteros

    2017-11-01

    Full Text Available Video game training with older adults potentially enhances aspects of cognition that decline with aging and could therefore offer a promising training approach. Although, previous published studies suggest that training can produce transfer, many of them have certain shortcomings. This randomized controlled trial (RCT; Clinicaltrials.gov ID: NCT02796508 tried to overcome some of these limitations by incorporating an active control group and the assessment of motivation and expectations. Seventy-five older volunteers were randomly assigned to the experimental group trained for 16 sessions with non-action video games from Lumosity, a commercial platform (http://www.lumosity.com/ or to an active control group trained for the same number of sessions with simulation strategy games. The final sample included 55 older adults (30 in the experimental group and 25 in the active control group. Participants were tested individually before and after training to assess working memory (WM and selective attention and also reported their perceived improvement, motivation and engagement. The results showed improved performance across the training sessions. The main results were: (1 the experimental group did not show greater improvements in measures of selective attention and working memory than the active control group (the opposite occurred in the oddball task; (2 a marginal training effect was observed for the N-back task, but not for the Stroop task while both groups improved in the Corsi Blocks task. Based on these results, one can conclude that training with non-action games provide modest benefits for untrained tasks. The effect is not specific for that kind of training as a similar effect was observed for strategy video games. Groups did not differ in motivation, engagement or expectations.

  5. Effects of Video Game Training on Measures of Selective Attention and Working Memory in Older Adults: Results from a Randomized Controlled Trial.

    Science.gov (United States)

    Ballesteros, Soledad; Mayas, Julia; Prieto, Antonio; Ruiz-Marquez, Eloísa; Toril, Pilar; Reales, José M

    2017-01-01

    Video game training with older adults potentially enhances aspects of cognition that decline with aging and could therefore offer a promising training approach. Although, previous published studies suggest that training can produce transfer, many of them have certain shortcomings. This randomized controlled trial (RCT; Clinicaltrials.gov ID: NCT02796508) tried to overcome some of these limitations by incorporating an active control group and the assessment of motivation and expectations. Seventy-five older volunteers were randomly assigned to the experimental group trained for 16 sessions with non-action video games from Lumosity , a commercial platform (http://www.lumosity.com/) or to an active control group trained for the same number of sessions with simulation strategy games. The final sample included 55 older adults (30 in the experimental group and 25 in the active control group). Participants were tested individually before and after training to assess working memory (WM) and selective attention and also reported their perceived improvement, motivation and engagement. The results showed improved performance across the training sessions. The main results were: (1) the experimental group did not show greater improvements in measures of selective attention and working memory than the active control group (the opposite occurred in the oddball task); (2) a marginal training effect was observed for the N -back task, but not for the Stroop task while both groups improved in the Corsi Blocks task. Based on these results, one can conclude that training with non-action games provide modest benefits for untrained tasks. The effect is not specific for that kind of training as a similar effect was observed for strategy video games. Groups did not differ in motivation, engagement or expectations.

  6. Selective mutism: a consensus based care pathway of good practice.

    Science.gov (United States)

    Keen, D V; Fonseca, S; Wintgens, A

    2008-10-01

    Selective mutism (SM) now acknowledged as an anxiety condition, tends to be a poorly understood, highly complex and vastly under-recognised clinical entity. Children with SM are a vulnerable group as the condition is not the remit of any one professional group. This inevitably leads to delay in formal diagnosis and management. There is a lack of systematic research on which to base guidelines for management. To develop, agree and validate key principles underlying the management of SM through a consensus process involving international experts, in order to create a local care pathway. A local multi-agency consultation process developed 11 statements, which were felt to be the key principles underpinning a potential care pathway for managing SM. Thirteen recognised experts from North America, Europe and Australia participated in a modified Delphi process involving two rounds using a Likert-scale and free commentary. Both quantitative and qualitative analyses were used in the validation or revision of the statements at each stage. Response rates were 100% for Round 1 and 84.6% for Round 2. Despite the differing professional backgrounds and service contexts, by successive revision and/or revalidation of statements, it was possible to arrive at a consensus about key principles relating to early recognition, assessment and intervention. The agreed key principles are presented together with the resulting local care pathway. Through a Delphi process, agreement was reached by a multidisciplinary group of professionals, on key principles that underpin the timely identification, assessment and management of children with SM. These include the potential for staff in school/preschool settings to identify SM and that intervention programmes should generally be based in these settings. Children with SM should receive assessment for possible coexisting disorders, whether developmental, emotional or behavioural and additional specific intervention given for these. Agreement was

  7. Preferential selection based on strategy persistence and memory promotes cooperation in evolutionary prisoner's dilemma games

    Science.gov (United States)

    Liu, Yuanming; Huang, Changwei; Dai, Qionglin

    2018-06-01

    Strategy imitation plays a crucial role in evolutionary dynamics when we investigate the spontaneous emergence of cooperation under the framework of evolutionary game theory. Generally, when an individual updates his strategy, he needs to choose a role model whom he will learn from. In previous studies, individuals choose role models randomly from their neighbors. In recent works, researchers have considered that individuals choose role models according to neighbors' attractiveness characterized by the present network topology or historical payoffs. Here, we associate an individual's attractiveness with the strategy persistence, which characterizes how frequently he changes his strategy. We introduce a preferential parameter α to describe the nonlinear correlation between the selection probability and the strategy persistence and the memory length of individuals M into the evolutionary games. We investigate the effects of α and M on cooperation. Our results show that cooperation could be promoted when α > 0 and at the same time M > 1, which corresponds to the situation that individuals are inclined to select their neighbors with relatively higher persistence levels during the evolution. Moreover, we find that the cooperation level could reach the maximum at an optimal memory length when α > 0. Our work sheds light on how to promote cooperation through preferential selection based on strategy persistence and a limited memory length.

  8. A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

    Directory of Open Access Journals (Sweden)

    Wang Lily

    2008-07-01

    Full Text Available Abstract Background Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate classification algorithms available for microarray gene expression data is a critical ingredient in order to develop the best possible molecular signatures for patient care. As suggested by a large body of literature to date, support vector machines can be considered "best of class" algorithms for classification of such data. Recent work, however, suggests that random forest classifiers may outperform support vector machines in this domain. Results In the present paper we identify methodological biases of prior work comparing random forests and support vector machines and conduct a new rigorous evaluation of the two algorithms that corrects these limitations. Our experiments use 22 diagnostic and prognostic datasets and show that support vector machines outperform random forests, often by a large margin. Our data also underlines the importance of sound research design in benchmarking and comparison of bioinformatics algorithms. Conclusion We found that both on average and in the majority of microarray datasets, random forests are outperformed by support vector machines both in the settings when no gene selection is performed and when several popular gene selection methods are used.

  9. Multiple Attribute Decision Making Based Relay Vehicle Selection for Electric Vehicle Communication

    Directory of Open Access Journals (Sweden)

    Zhao Qiang

    2015-01-01

    Full Text Available Large-scale electric vehicle integration into power grid and charging randomly will cause serious impacts on the normal operation of power grid. Therefore, it is necessary to control the charging behavior of electric vehicle, while information transmission for electric vehicle is significant. Due to the highly mobile characteristics of vehicle, transferring information to power grid directly might be inaccessible. Relay vehicle (RV can be used for supporting multi-hop connection between SV and power grid. This paper proposes a multiple attribute decision making (MADM-based RV selection algorithm, which considers multiple attribute, including data transfer rate, delay, route duration. It takes the characteristics of electric vehicle communication into account, which can provide protection for the communication services of electric vehicle charging and discharging. Numerical results demonstrate that compared to previous algorithm, the proposed algorithm offer better performance in terms of throughput, transmission delay.

  10. The Fault Diagnosis of Rolling Bearing Based on Ensemble Empirical Mode Decomposition and Random Forest

    OpenAIRE

    Qin, Xiwen; Li, Qiaoling; Dong, Xiaogang; Lv, Siqi

    2017-01-01

    Accurate diagnosis of rolling bearing fault on the normal operation of machinery and equipment has a very important significance. A method combining Ensemble Empirical Mode Decomposition (EEMD) and Random Forest (RF) is proposed. Firstly, the original signal is decomposed into several intrinsic mode functions (IMFs) by EEMD, and the effective IMFs are selected. Then their energy entropy is calculated as the feature. Finally, the classification is performed by RF. In addition, the wavelet meth...

  11. ANALYSIS OF FUZZY QUEUES: PARAMETRIC PROGRAMMING APPROACH BASED ON RANDOMNESS - FUZZINESS CONSISTENCY PRINCIPLE

    Directory of Open Access Journals (Sweden)

    Dhruba Das

    2015-04-01

    Full Text Available In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM/M/1 and M/FM/1 has been studied and constructed their membership functions of the system characteristics based on the aforesaid principle. The former represents a queue with fuzzy exponential arrivals and exponential service rate while the latter represents a queue with exponential arrival rate and fuzzy exponential service rate.

  12. Effects of psychological therapies in randomized trials and practice-based studies.

    Science.gov (United States)

    Barkham, Michael; Stiles, William B; Connell, Janice; Twigg, Elspeth; Leach, Chris; Lucock, Mike; Mellor-Clark, John; Bower, Peter; King, Michael; Shapiro, David A; Hardy, Gillian E; Greenberg, Leslie; Angus, Lynne

    2008-11-01

    Randomized trials of the effects of psychological therapies seek internal validity via homogeneous samples and standardized treatment protocols. In contrast, practice-based studies aim for clinical realism and external validity via heterogeneous samples of clients treated under routine practice conditions. We compared indices of treatment effects in these two types of studies. Using published transformation formulas, the Beck Depression Inventory (BDI) scores from five randomized trials of depression (N = 477 clients) were transformed into Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) scores and compared with CORE-OM data collected in four practice-based studies (N = 4,196 clients). Conversely, the practice-based studies' CORE-OM scores were transformed into BDI scores and compared with randomized trial data. Randomized trials showed a modest advantage over practice-based studies in amount of pre-post improvement. This difference was compressed or exaggerated depending on the direction of the transformation but averaged about 12%. There was a similarly sized advantage to randomized trials in rates of reliable and clinically significant improvement (RCSI). The largest difference was yielded by comparisons of effect sizes which suggested an advantage more than twice as large, reflecting narrower pre-treatment distributions in the randomized trials. Outcomes of completed treatments for depression in randomized trials appeared to be modestly greater than those in routine care settings. The size of the difference may be distorted depending on the method for calculating degree of change. Transforming BDI scores into CORE-OM scores and vice versa may be a preferable alternative to effect sizes for comparisons of studies using these measures.

  13. Species-specific audio detection: a comparison of three template-based detection algorithms using random forests

    Directory of Open Access Journals (Sweden)

    Carlos J. Corrada Bravo

    2017-04-01

    Full Text Available We developed a web-based cloud-hosted system that allow users to archive, listen, visualize, and annotate recordings. The system also provides tools to convert these annotations into datasets that can be used to train a computer to detect the presence or absence of a species. The algorithm used by the system was selected after comparing the accuracy and efficiency of three variants of a template-based detection. The algorithm computes a similarity vector by comparing a template of a species call with time increments across the spectrogram. Statistical features are extracted from this vector and used as input for a Random Forest classifier that predicts presence or absence of the species in the recording. The fastest algorithm variant had the highest average accuracy and specificity; therefore, it was implemented in the ARBIMON web-based system.

  14. Wavelength Selection Method Based on Differential Evolution for Precise Quantitative Analysis Using Terahertz Time-Domain Spectroscopy.

    Science.gov (United States)

    Li, Zhi; Chen, Weidong; Lian, Feiyu; Ge, Hongyi; Guan, Aihong

    2017-12-01

    Quantitative analysis of component mixtures is an important application of terahertz time-domain spectroscopy (THz-TDS) and has attracted broad interest in recent research. Although the accuracy of quantitative analysis using THz-TDS is affected by a host of factors, wavelength selection from the sample's THz absorption spectrum is the most crucial component. The raw spectrum consists of signals from the sample and scattering and other random disturbances that can critically influence the quantitative accuracy. For precise quantitative analysis using THz-TDS, the signal from the sample needs to be retained while the scattering and other noise sources are eliminated. In this paper, a novel wavelength selection method based on differential evolution (DE) is investigated. By performing quantitative experiments on a series of binary amino acid mixtures using THz-TDS, we demonstrate the efficacy of the DE-based wavelength selection method, which yields an error rate below 5%.

  15. Prevalence of at-risk genotypes for genotoxic effects decreases with age in a randomly selected population in Flanders: a cross sectional study

    Directory of Open Access Journals (Sweden)

    van Delft Joost HM

    2011-10-01

    Full Text Available Abstract Background We hypothesized that in Flanders (Belgium, the prevalence of at-risk genotypes for genotoxic effects decreases with age due to morbidity and mortality resulting from chronic diseases. Rather than polymorphisms in single genes, the interaction of multiple genetic polymorphisms in low penetrance genes involved in genotoxic effects might be of relevance. Methods Genotyping was performed on 399 randomly selected adults (aged 50-65 and on 442 randomly selected adolescents. Based on their involvement in processes relevant to genotoxicity, 28 low penetrance polymorphisms affecting the phenotype in 19 genes were selected (xenobiotic metabolism, oxidative stress defense and DNA repair, respectively 13, 6 and 9 polymorphisms. Polymorphisms which, based on available literature, could not clearly be categorized a priori as leading to an 'increased risk' or a 'protective effect' were excluded. Results The mean number of risk alleles for all investigated polymorphisms was found to be lower in the 'elderly' (17.0 ± 2.9 than the 'adolescent' (17.6 ± 3.1 subpopulation (P = 0.002. These results were not affected by gender nor smoking. The prevalence of a high (> 17 = median number of risk alleles was less frequent in the 'elderly' (40.6% than the 'adolescent' (51.4% subpopulation (P = 0.002. In particular for phase II enzymes, the mean number of risk alleles was lower in the 'elderly' (4.3 ± 1.6 than the 'adolescent' age group (4.8 ± 1.9 P 4 = median number of risk alleles was less frequent in the 'elderly' (41.3% than the adolescent subpopulation (56.3%, P 8 = median number of risk alleles for DNA repair enzyme-coding genes was lower in the 'elderly' (37,3% than the 'adolescent' subpopulation (45.6%, P = 0.017. Conclusions These observations are consistent with the hypothesis that, in Flanders, the prevalence of at-risk alleles in genes involved in genotoxic effects decreases with age, suggesting that persons carrying a higher number of

  16. Selection for Surgical Training: An Evidence-Based Review.

    Science.gov (United States)

    Schaverien, Mark V

    2016-01-01

    The predictive relationship between candidate selection criteria for surgical training programs and future performance during and at the completion of training has been investigated for several surgical specialties, however there is no interspecialty agreement regarding which selection criteria should be used. Better understanding the predictive reliability between factors at selection and future performance may help to optimize the process and lead to greater standardization of the surgical selection process. PubMed and Ovid MEDLINE databases were searched. Over 560 potentially relevant publications were identified using the search strategy and screened using the Cochrane Collaboration Data Extraction and Assessment Template. 57 studies met the inclusion criteria. Several selection criteria used in the traditional selection demonstrated inconsistent correlation with subsequent performance during and at the end of surgical training. The following selection criteria, however, demonstrated good predictive relationships with subsequent resident performance: USMLE examination scores, Letters of Recommendation (LOR) including the Medical Student Performance Evaluation (MSPE), academic performance during clinical clerkships, the interview process, displaying excellence in extracurricular activities, and the use of unadjusted rank lists. This systematic review supports that the current selection process needs to be further evaluated and improved. Multicenter studies using standardized outcome measures of success are now required to improve the reliability of the selection process to select the best trainees. Published by Elsevier Inc.

  17. Biased random key genetic algorithm with insertion and gender selection for capacitated vehicle routing problem with time windows

    Science.gov (United States)

    Rochman, Auliya Noor; Prasetyo, Hari; Nugroho, Munajat Tri

    2017-06-01

    Vehicle Routing Problem (VRP) often occurs when the manufacturers need to distribute their product to some customers/outlets. The distribution process is typically restricted by the capacity of the vehicle and the working hours at the distributor. This type of VRP is also known as Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). A Biased Random Key Genetic Algorithm (BRKGA) was designed and coded in MATLAB to solve the CVRPTW case of soft drink distribution. The standard BRKGA was then modified by applying chromosome insertion into the initial population and defining chromosome gender for parent undergoing crossover operation. The performance of the established algorithms was then compared to a heuristic procedure for solving a soft drink distribution. Some findings are revealed (1) the total distribution cost of BRKGA with insertion (BRKGA-I) results in a cost saving of 39% compared to the total cost of heuristic method, (2) BRKGA with the gender selection (BRKGA-GS) could further improve the performance of the heuristic method. However, the BRKGA-GS tends to yield worse results compared to that obtained from the standard BRKGA.

  18. 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.

  19. An AES chip with DPA resistance using hardware-based random order execution

    International Nuclear Information System (INIS)

    Yu Bo; Li Xiangyu; Chen Cong; Sun Yihe; Wu Liji; Zhang Xiangmin

    2012-01-01

    This paper presents an AES (advanced encryption standard) chip that combats differential power analysis (DPA) side-channel attack through hardware-based random order execution. Both decryption and encryption procedures of an AES are implemented on the chip. A fine-grained dataflow architecture is proposed, which dynamically exploits intrinsic byte-level independence in the algorithm. A novel circuit called an HMF (Hold-Match-Fetch) unit is proposed for random control, which randomly sets execution orders for concurrent operations. The AES chip was manufactured in SMIC 0.18 μm technology. The average energy for encrypting one group of plain texts (128 bits secrete keys) is 19 nJ. The core area is 0.43 mm 2 . A sophisticated experimental setup was built to test the DPA resistance. Measurement-based experimental results show that one byte of a secret key cannot be disclosed from our chip under random mode after 64000 power traces were used in the DPA attack. Compared with the corresponding fixed order execution, the hardware based random order execution is improved by at least 21 times the DPA resistance. (semiconductor integrated circuits)

  20. An AES chip with DPA resistance using hardware-based random order execution

    Science.gov (United States)

    Bo, Yu; Xiangyu, Li; Cong, Chen; Yihe, Sun; Liji, Wu; Xiangmin, Zhang

    2012-06-01

    This paper presents an AES (advanced encryption standard) chip that combats differential power analysis (DPA) side-channel attack through hardware-based random order execution. Both decryption and encryption procedures of an AES are implemented on the chip. A fine-grained dataflow architecture is proposed, which dynamically exploits intrinsic byte-level independence in the algorithm. A novel circuit called an HMF (Hold-Match-Fetch) unit is proposed for random control, which randomly sets execution orders for concurrent operations. The AES chip was manufactured in SMIC 0.18 μm technology. The average energy for encrypting one group of plain texts (128 bits secrete keys) is 19 nJ. The core area is 0.43 mm2. A sophisticated experimental setup was built to test the DPA resistance. Measurement-based experimental results show that one byte of a secret key cannot be disclosed from our chip under random mode after 64000 power traces were used in the DPA attack. Compared with the corresponding fixed order execution, the hardware based random order execution is improved by at least 21 times the DPA resistance.

  1. Sol-gel based sensor for selective formaldehyde determination

    Energy Technology Data Exchange (ETDEWEB)

    Bunkoed, Opas [Trace Analysis and Biosensor Research Center, Prince of Songkla University, Hat Yai, Songkhla 90112 (Thailand); Department of Chemistry and Center for Innovation in Chemistry, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla 90112 (Thailand); Davis, Frank [Cranfield Health, Cranfield University, Bedford MK43 0AL (United Kingdom); Kanatharana, Proespichaya, E-mail: proespichaya.K@psu.ac.th [Trace Analysis and Biosensor Research Center, Prince of Songkla University, Hat Yai, Songkhla 90112 (Thailand); Department of Chemistry and Center for Innovation in Chemistry, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla 90112 (Thailand); Thavarungkul, Panote [Trace Analysis and Biosensor Research Center, Prince of Songkla University, Hat Yai, Songkhla 90112 (Thailand); Department of Physics, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla 90112 (Thailand); Higson, Seamus P.J., E-mail: s.p.j.higson@cranfield.ac.uk [Cranfield Health, Cranfield University, Bedford MK43 0AL (United Kingdom)

    2010-02-05

    We report the development of transparent sol-gels with entrapped sensitive and selective reagents for the detection of formaldehyde. The sampling method is based on the adsorption of formaldehyde from the air and reaction with {beta}-diketones (for example acetylacetone) in a sol-gel matrix to produce a yellow product, lutidine, which was detected directly. The proposed method does not require preparation of samples prior to analysis and allows both screening by visual detection and quantitative measurement by simple spectrophotometry. The detection limit of 0.03 ppmv formaldehyde is reported which is lower than the maximum exposure concentrations recommended by both the World Health Organisation (WHO) and the Occupational Safety and Health Administration (OSHA). This sampling method was found to give good reproducibility, the relative standard deviation at 0.2 and 1 ppmv being 6.3% and 4.6%, respectively. Other carbonyl compounds i.e. acetaldehyde, benzaldehyde, acetone and butanone do not interfere with this analytical approach. Results are provided for the determination of formaldehyde in indoor air.

  2. Sol-gel based sensor for selective formaldehyde determination

    International Nuclear Information System (INIS)

    Bunkoed, Opas; Davis, Frank; Kanatharana, Proespichaya; Thavarungkul, Panote; Higson, Seamus P.J.

    2010-01-01

    We report the development of transparent sol-gels with entrapped sensitive and selective reagents for the detection of formaldehyde. The sampling method is based on the adsorption of formaldehyde from the air and reaction with β-diketones (for example acetylacetone) in a sol-gel matrix to produce a yellow product, lutidine, which was detected directly. The proposed method does not require preparation of samples prior to analysis and allows both screening by visual detection and quantitative measurement by simple spectrophotometry. The detection limit of 0.03 ppmv formaldehyde is reported which is lower than the maximum exposure concentrations recommended by both the World Health Organisation (WHO) and the Occupational Safety and Health Administration (OSHA). This sampling method was found to give good reproducibility, the relative standard deviation at 0.2 and 1 ppmv being 6.3% and 4.6%, respectively. Other carbonyl compounds i.e. acetaldehyde, benzaldehyde, acetone and butanone do not interfere with this analytical approach. Results are provided for the determination of formaldehyde in indoor air.

  3. A Lightweight Structure Redesign Method Based on Selective Laser Melting

    Directory of Open Access Journals (Sweden)

    Li Tang

    2016-11-01

    Full Text Available The purpose of this paper is to present a new design method of lightweight parts fabricated by selective laser melting (SLM based on the “Skin-Frame” and to explore the influence of fabrication defects on SLM parts with different sizes. Some standard lattice parts were designed according to the Chinese GB/T 1452-2005 standard and manufactured by SLM. Then these samples were tested in an MTS Insight 30 compression testing machine to study the trends of the yield process with different structure sizes. A set of standard cylinder samples were also designed according to the Chinese GB/T 228-2010 standard. These samples, which were made of iron-nickel alloy (IN718, were also processed by SLM, and then tested in the universal material testing machine INSTRON 1346 to obtain their tensile strength. Furthermore, a lightweight redesigned method was researched. Then some common parts such as a stopper and connecting plate were redesigned using this method. These redesigned parts were fabricated and some application tests have already been performed. The compression testing results show that when the minimum structure size is larger than 1.5 mm, the mechanical characteristics will hardly be affected by process defects. The cylinder parts were fractured by the universal material testing machine at about 1069.6 MPa. These redesigned parts worked well in application tests, with both the weight and fabrication time of these parts reduced more than 20%.

  4. Moldless PEGDA-Based Optoelectrofluidic Platform for Microparticle Selection

    Directory of Open Access Journals (Sweden)

    Shih-Mo Yang

    2011-01-01

    Full Text Available This paper reports on an optoelectrofluidic platform which consists of the organic photoconductive material, titanium oxide phthalocyanine (TiOPc, and the photocrosslinkable polymer, poly (ethylene glycol diacrylate (PEGDA. TiOPc simplifies the fabrication process of the optoelectronic chip due to requiring only a single spin-coating step. PEGDA is applied to embed the moldless PEGDA-based microchannel between the top ITO glass and the bottom TiOPc substrate. A real-time control interface via a touch panel screen is utilized to select the target 15 μm polystyrene particles. When the microparticles flow to an illuminating light bar, which is oblique to the microfluidic flow path, the lateral driving force diverts the microparticles. Two light patterns, the switching oblique light bar and the optoelectronic ladder phenomenon, are designed to demonstrate the features. This work integrating the new material design, TiOPc and PEGDA, and the ability of mobile microparticle manipulation demonstrates the potential of optoelectronic approach.

  5. Towards Identify Selective Antibacterial Peptides Based on Abstracts Meaning

    Directory of Open Access Journals (Sweden)

    Liliana I. Barbosa-Santillán

    2016-01-01

    Full Text Available We present an Identify Selective Antibacterial Peptides (ISAP approach based on abstracts meaning. Laboratories and researchers have significantly increased the report of their discoveries related to antibacterial peptides in primary publications. It is important to find antibacterial peptides that have been reported in primary publications because they can produce antibiotics of different generations that attack and destroy the bacteria. Unfortunately, researchers used heterogeneous forms of natural language to describe their discoveries (sometimes without the sequence of the peptides. Thus, we propose that learning the words meaning instead of the antibacterial peptides sequence is possible to identify and predict antibacterial peptides reported in the PubMed engine. The ISAP approach consists of two stages: training and discovering. ISAP founds that the 35% of the abstracts sample had antibacterial peptides and we tested in the updated Antimicrobial Peptide Database 2 (APD2. ISAP predicted that 45% of the abstracts had antibacterial peptides. That is, ISAP found that 810 antibacterial peptides were not classified like that, so they are not reported in APD2. As a result, this new search tool would complement the APD2 with a set of peptides that are candidates to be antibacterial. Finally, 20% of the abstracts were not semantic related to APD2.

  6. Route Selection with Unspecified Sites Using Knowledge Based Genetic Algorithm

    Science.gov (United States)

    Kanoh, Hitoshi; Nakamura, Nobuaki; Nakamura, Tomohiro

    This paper addresses the problem of selecting a route to a given destination that traverses several non-specific sites (e.g. a bank, a gas station) as requested by a driver. The proposed solution uses a genetic algorithm that includes viral infection. The method is to generate two populations of viruses as domain specific knowledge in addition to a population of routes. A part of an arterial road is regarded as a main virus, and a road that includes a site is regarded as a site virus. An infection occurs between two points common to a candidate route and the virus, and involves the substitution of the intersections carried by the virus for those on the existing candidate route. Crossover and infection determine the easiest-to-drive and quasi-shortest route through the objective landmarks. Experiments using actual road maps show that this infection-based mechanism is an effective way of solving the problem. Our strategy is general, and can be effectively used in other optimization problems.

  7. Towards the generation of random bits at terahertz rates based on a chaotic semiconductor laser

    International Nuclear Information System (INIS)

    Kanter, Ido; Aviad, Yaara; Reidler, Igor; Cohen, Elad; Rosenbluh, Michael

    2010-01-01

    Random bit generators (RBGs) are important in many aspects of statistical physics and crucial in Monte-Carlo simulations, stochastic modeling and quantum cryptography. The quality of a RBG is measured by the unpredictability of the bit string it produces and the speed at which the truly random bits can be generated. Deterministic algorithms generate pseudo-random numbers at high data rates as they are only limited by electronic hardware speed, but their unpredictability is limited by the very nature of their deterministic origin. It is widely accepted that the core of any true RBG must be an intrinsically non-deterministic physical process, e.g. measuring thermal noise from a resistor. Owing to low signal levels, such systems are highly susceptible to bias, introduced by amplification, and to small nonrandom external perturbations resulting in a limited generation rate, typically less than 100M bit/s. We present a physical random bit generator, based on a chaotic semiconductor laser, having delayed optical feedback, which operates reliably at rates up to 300Gbit/s. The method uses a high derivative of the digitized chaotic laser intensity and generates the random sequence by retaining a number of the least significant bits of the high derivative value. The method is insensitive to laser operational parameters and eliminates the necessity for all external constraints such as incommensurate sampling rates and laser external cavity round trip time. The randomness of long bit strings is verified by standard statistical tests.

  8. Towards the generation of random bits at terahertz rates based on a chaotic semiconductor laser

    Science.gov (United States)

    Kanter, Ido; Aviad, Yaara; Reidler, Igor; Cohen, Elad; Rosenbluh, Michael

    2010-06-01

    Random bit generators (RBGs) are important in many aspects of statistical physics and crucial in Monte-Carlo simulations, stochastic modeling and quantum cryptography. The quality of a RBG is measured by the unpredictability of the bit string it produces and the speed at which the truly random bits can be generated. Deterministic algorithms generate pseudo-random numbers at high data rates as they are only limited by electronic hardware speed, but their unpredictability is limited by the very nature of their deterministic origin. It is widely accepted that the core of any true RBG must be an intrinsically non-deterministic physical process, e.g. measuring thermal noise from a resistor. Owing to low signal levels, such systems are highly susceptible to bias, introduced by amplification, and to small nonrandom external perturbations resulting in a limited generation rate, typically less than 100M bit/s. We present a physical random bit generator, based on a chaotic semiconductor laser, having delayed optical feedback, which operates reliably at rates up to 300Gbit/s. The method uses a high derivative of the digitized chaotic laser intensity and generates the random sequence by retaining a number of the least significant bits of the high derivative value. The method is insensitive to laser operational parameters and eliminates the necessity for all external constraints such as incommensurate sampling rates and laser external cavity round trip time. The randomness of long bit strings is verified by standard statistical tests.

  9. A universal algorithm to generate pseudo-random numbers based on uniform mapping as homeomorphism

    International Nuclear Information System (INIS)

    Fu-Lai, Wang

    2010-01-01

    A specific uniform map is constructed as a homeomorphism mapping chaotic time series into [0,1] to obtain sequences of standard uniform distribution. With the uniform map, a chaotic orbit and a sequence orbit obtained are topologically equivalent to each other so the map can preserve the most dynamic properties of chaotic systems such as permutation entropy. Based on the uniform map, a universal algorithm to generate pseudo random numbers is proposed and the pseudo random series is tested to follow the standard 0–1 random distribution both theoretically and experimentally. The algorithm is not complex, which does not impose high requirement on computer hard ware and thus computation speed is fast. The method not only extends the parameter spaces but also avoids the drawback of small function space caused by constraints on chaotic maps used to generate pseudo random numbers. The algorithm can be applied to any chaotic system and can produce pseudo random sequence of high quality, thus can be a good universal pseudo random number generator. (general)

  10. A universal algorithm to generate pseudo-random numbers based on uniform mapping as homeomorphism

    Science.gov (United States)

    Wang, Fu-Lai

    2010-09-01

    A specific uniform map is constructed as a homeomorphism mapping chaotic time series into [0,1] to obtain sequences of standard uniform distribution. With the uniform map, a chaotic orbit and a sequence orbit obtained are topologically equivalent to each other so the map can preserve the most dynamic properties of chaotic systems such as permutation entropy. Based on the uniform map, a universal algorithm to generate pseudo random numbers is proposed and the pseudo random series is tested to follow the standard 0-1 random distribution both theoretically and experimentally. The algorithm is not complex, which does not impose high requirement on computer hard ware and thus computation speed is fast. The method not only extends the parameter spaces but also avoids the drawback of small function space caused by constraints on chaotic maps used to generate pseudo random numbers. The algorithm can be applied to any chaotic system and can produce pseudo random sequence of high quality, thus can be a good universal pseudo random number generator.

  11. A Bidirectional Generalized Synchronization Theorem-Based Chaotic Pseudo-random Number Generator

    Directory of Open Access Journals (Sweden)

    Han Shuangshuang

    2013-07-01

    Full Text Available Based on a bidirectional generalized synchronization theorem for discrete chaos system, this paper introduces a new 5-dimensional bidirectional generalized chaos synchronization system (BGCSDS, whose prototype is a novel chaotic system introduced in [12]. Numerical simulation showed that two pair variables of the BGCSDS achieve generalized chaos synchronization via a transform H.A chaos-based pseudo-random number generator (CPNG was designed by the new BGCSDS. Using the FIPS-140-2 tests issued by the National Institute of Standard and Technology (NIST verified the randomness of the 1000 binary number sequences generated via the CPNG and the RC4 algorithm respectively. The results showed that all the tested sequences passed the FIPS-140-2 tests. The confidence interval analysis showed the statistical properties of the randomness of the sequences generated via the CPNG and the RC4 algorithm do not have significant differences.

  12. A theory-based video messaging mobile phone intervention for smoking cessation: randomized controlled trial.

    Science.gov (United States)

    Whittaker, Robyn; Dorey, Enid; Bramley, Dale; Bullen, Chris; Denny, Simon; Elley, C Raina; Maddison, Ralph; McRobbie, Hayden; Parag, Varsha; Rodgers, Anthony; Salmon, Penny

    2011-01-21

    Advances in technology allowed the development of a novel smoking cessation program delivered by video messages sent to mobile phones. This social cognitive theory-based intervention (called "STUB IT") used observational learning via short video diary messages from role models going through the quitting process to teach behavioral change techniques. The objective of our study was to assess the effectiveness of a multimedia mobile phone intervention for smoking cessation. A randomized controlled trial was conducted with 6-month follow-up. Participants had to be 16 years of age or over, be current daily smokers, be ready to quit, and have a video message-capable phone. Recruitment targeted younger adults predominantly through radio and online advertising. Registration and data collection were completed online, prompted by text messages. The intervention group received an automated package of video and text messages over 6 months that was tailored to self-selected quit date, role model, and timing of messages. Extra messages were available on demand to beat cravings and address lapses. The control group also set a quit date and received a general health video message sent to their phone every 2 weeks. The target sample size was not achieved due to difficulty recruiting young adult quitters. Of the 226 randomized participants, 47% (107/226) were female and 24% (54/226) were Maori (indigenous population of New Zealand). Their mean age was 27 years (SD 8.7), and there was a high level of nicotine addiction. Continuous abstinence at 6 months was 26.4% (29/110) in the intervention group and 27.6% (32/116) in the control group (P = .8). Feedback from participants indicated that the support provided by the video role models was important and appreciated. This study was not able to demonstrate a statistically significant effect of the complex video messaging mobile phone intervention compared with simple general health video messages via mobile phone. However, there was

  13. Change-based test selection : An empirical evaluation

    NARCIS (Netherlands)

    Soetens, Quinten; Demeyer, Serge; Zaidman, A.E.; Perez, Javier

    2015-01-01

    Regression test selection (i.e., selecting a subset of a given regression test suite) is a problem that has been studied intensely over the last decade. However, with the increasing popularity of developer tests as the driver of the test process, more fine-grained solutions that work well within the

  14. Selecting a Good Conference Location Based on Participants' Interests

    Science.gov (United States)

    Miah, Muhammed

    2011-01-01

    Selecting a good conference location within budget constraints to attract paper authors and participants is a very difficult job for the conference organizers. A conference location is also very important along with other issues such as ranking of the conference. Selecting a bad conference location may reduce the number of paper submissions and…

  15. Registry-based randomized controlled trials merged the strength of randomized controlled trails and observational studies and give rise to more pragmatic trials.

    Science.gov (United States)

    Mathes, Tim; Buehn, Stefanie; Prengel, Peggy; Pieper, Dawid

    2018-01-01

    The objective of this study was to analyze the features of registry-based randomized trials (rRCTs). We systematically searched PubMed for rRCTs. Study selection was performed independently by two reviewers. We extracted all data in standardized tables and prepared descriptive summary statistics. The search resulted in 1,202 hits. We included 71 rRCTs. Most rRCTs were from Denmark and Sweden. Chronic conditions were considered in 82.2%. A preventive intervention was examined in 45.1%. The median of included patients was 2,000 (range: 69-246,079). Definition of the study population was mostly broad. Study procedures were regularly little standardized. The number of included and analyzed patients was the same in 82.1%. In half of the rRCTs, more than one registry was utilized. Various linkage techniques were used. In median, two outcomes were collected from the registry/ies. The median follow-up of the rRCTs was 5.3 years (range: 6 weeks to 27 years). Information on quality of registry data was reported in 11.3%. rRCTs can provide valid (randomization, low lost-to-follow-up rates, generalizable) patient important long-term comparative-effectiveness data for relative little effort. Researchers planning an RCT should always check whether existing registries can be used for data collection. Reporting on data quality must be improved for use in evidence synthesis. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. The Long-Term Effectiveness of a Selective, Personality-Targeted Prevention Program in Reducing Alcohol Use and Related Harms: A Cluster Randomized Controlled Trial

    Science.gov (United States)

    Newton, Nicola C.; Conrod, Patricia J.; Slade, Tim; Carragher, Natacha; Champion, Katrina E.; Barrett, Emma L.; Kelly, Erin V.; Nair, Natasha K.; Stapinski, Lexine; Teesson, Maree

    2016-01-01

    Background: This study investigated the long-term effectiveness of Preventure, a selective personality-targeted prevention program, in reducing the uptake of alcohol, harmful use of alcohol, and alcohol-related harms over a 3-year period. Methods: A cluster randomized controlled trial was conducted to assess the effectiveness of Preventure.…

  17. Performance Measurement Model for the Supplier Selection Based on AHP

    Directory of Open Access Journals (Sweden)

    Fabio De Felice

    2015-10-01

    Full Text Available The performance of the supplier is a crucial factor for the success or failure of any company. Rational and effective decision making in terms of the supplier selection process can help the organization to optimize cost and quality functions. The nature of supplier selection processes is generally complex, especially when the company has a large variety of products and vendors. Over the years, several solutions and methods have emerged for addressing the supplier selection problem (SSP. Experience and studies have shown that there is no best way for evaluating and selecting a specific supplier process, but that it varies from one organization to another. The aim of this research is to demonstrate how a multiple attribute decision making approach can be effectively applied for the supplier selection process.

  18. Development of radiopharmaceuticals based on aptamers: selection and characterization of DNA aptamers for CEA

    International Nuclear Information System (INIS)

    Correa, C.R.; Andrade, A.S.R.; Augusto-Pinto, L.; Goes, A.M.

    2011-01-01

    Colorectal cancer is among the top four causes of cancer deaths worldwide. Carcinoembryonic antigen (CEA) is a complex intracellular glycoprotein produced by about 90% of colorectal cancers. CEA has been identified as an attractive target for cancer research because of its pattern of expression in the surface cell and its likely functional role in tumorigenesis. Research on the rapid selection of ligands based on the SELEX (systematic evolution of ligands by exponential enrichment) forms the basis for the development of high affinity and high specificity molecules, which can bind to surface determinants of tumour cells, like CEA. The oligonucleotides ligands generated in this technique are called aptamers. Aptamers can potentially find applications as therapeutic or diagnostic tools for many kind of diseases, like a tumor. Aptamers offer low immunogenicity, good tumour penetration, rapid uptake and fast systemic clearance, which favour their application as effective vehicles for radiotherapy. In addition aptamers can be labeled with different radioactive isotopes. The aim of this work was select aptamers binding to the CEA tumor marker. The aptamers are obtained through by SELEX, in which aptamers are selected from a library of random sequences of synthetic DNA by repetitive binding of the oligonucleotides to target molecule (CEA). Analyses of the secondary structure of the aptamers were determined using the m fold toll. Three aptamers were selected to binding assay with target cells. These aptamers were confirmed to have affinity and specific binding for T84 cell line (target cell), showed by confocal imaging. We are currently studying the potential efficacy of these aptamers as targeted radiopharmaceuticals, for use as imaging agents or therapeutic applications. The development of aptamers specific to CEA open new perspectives for colorectal cancer diagnosis and treatment. Acknowledgments: This investigation was supported by the Centro de Desenvolvimento da

  19. Development of radiopharmaceuticals based on aptamers: selection and characterization of DNA aptamers for CEA

    Energy Technology Data Exchange (ETDEWEB)

    Correa, C.R.; Andrade, A.S.R., E-mail: antero@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil); Augusto-Pinto, L. [BioAptus, Belo Horizonte, MG (Brazil); Goes, A.M., E-mail: goes@icb.ufmg.br [Departamento de Imunologia e Bioquimica. Instituto de Ciencias Biologicas. Universidade Federal de Minas Gerais. Belo Horizonte, MG (Brazil)

    2011-07-01

    Colorectal cancer is among the top four causes of cancer deaths worldwide. Carcinoembryonic antigen (CEA) is a complex intracellular glycoprotein produced by about 90% of colorectal cancers. CEA has been identified as an attractive target for cancer research because of its pattern of expression in the surface cell and its likely functional role in tumorigenesis. Research on the rapid selection of ligands based on the SELEX (systematic evolution of ligands by exponential enrichment) forms the basis for the development of high affinity and high specificity molecules, which can bind to surface determinants of tumour cells, like CEA. The oligonucleotides ligands generated in this technique are called aptamers. Aptamers can potentially find applications as therapeutic or diagnostic tools for many kind of diseases, like a tumor. Aptamers offer low immunogenicity, good tumour penetration, rapid uptake and fast systemic clearance, which favour their application as effective vehicles for radiotherapy. In addition aptamers can be labeled with different radioactive isotopes. The aim of this work was select aptamers binding to the CEA tumor marker. The aptamers are obtained through by SELEX, in which aptamers are selected from a library of random sequences of synthetic DNA by repetitive binding of the oligonucleotides to target molecule (CEA). Analyses of the secondary structure of the aptamers were determined using the m fold toll. Three aptamers were selected to binding assay with target cells. These aptamers were confirmed to have affinity and specific binding for T84 cell line (target cell), showed by confocal imaging. We are currently studying the potential efficacy of these aptamers as targeted radiopharmaceuticals, for use as imaging agents or therapeutic applications. The development of aptamers specific to CEA open new perspectives for colorectal cancer diagnosis and treatment. Acknowledgments: This investigation was supported by the Centro de Desenvolvimento da

  20. Evolution of Randomized Trials in Advanced/Metastatic Soft Tissue Sarcoma: End Point Selection, Surrogacy, and Quality of Reporting.

    Science.gov (United States)

    Zer, Alona; Prince, Rebecca M; Amir, Eitan; Abdul Razak, Albiruni

    2016-05-01

    Randomized controlled trials (RCTs) in soft tissue sarcoma (STS) have used varying end points. The surrogacy of intermediate end points, such as progression-free survival (PFS), response rate (RR), and 3-month and 6-month PFS (3moPFS and 6moPFS) with overall survival (OS), remains unknown. The quality of efficacy and toxicity reporting in these studies is also uncertain. A systematic review of systemic therapy RCTs in STS was performed. Surrogacy between intermediate end points and OS was explored using weighted linear regression for the hazard ratio for OS with the hazard ratio for PFS or the odds ratio for RR, 3moPFS, and 6moPFS. The quality of reporting for efficacy and toxicity was also evaluated. Fifty-two RCTs published between 1974 and 2014, comprising 9,762 patients, met the inclusion criteria. There were significant correlations between PFS and OS (R = 0.61) and between RR and OS (R = 0.51). Conversely, there were nonsignificant correlations between 3moPFS and 6moPFS with OS. A reduction in the use of RR as the primary end point was observed over time, favoring time-based events (P for trend = .02). In 14% of RCTs, the primary end point was not met, but the study was reported as being positive. Toxicity was comprehensively reported in 47% of RCTs, whereas 14% inadequately reported toxicity. In advanced STS, PFS and RR seem to be appropriate surrogates for OS. There is poor correlation between OS and both 3moPFS and 6moPFS. As such, caution is urged with the use of these as primary end points in randomized STS trials. The quality of toxicity reporting and interpretation of results is suboptimal. © 2016 by American Society of Clinical Oncology.

  1. Effectiveness in practice-based research: Looking for alternatives to the randomized controlled trial (RCT)

    NARCIS (Netherlands)

    Tavecchio, L.

    2015-01-01

    Over the last decade, the status of the randomized controlled trial (RCT), hallmark of evidence-based medicine (research), has been growing strongly in general practice, social work and public health. But this type of research is only practicable under strictly controlled and well-defined settings

  2. The Hidden Flow Structure and Metric Space of Network Embedding Algorithms Based on Random Walks.

    Science.gov (United States)

    Gu, Weiwei; Gong, Li; Lou, Xiaodan; Zhang, Jiang

    2017-10-13

    Network embedding which encodes all vertices in a network as a set of numerical vectors in accordance with it's local and global structures, has drawn widespread attention. Network embedding not only learns significant features of a network, such as the clustering and linking prediction but also learns the latent vector representation of the nodes which provides theoretical support for a variety of applications, such as visualization, link prediction, node classification, and recommendation. As the latest progress of the research, several algorithms based on random walks have been devised. Although those algorithms have drawn much attention for their high scores in learning efficiency and accuracy, there is still a lack of theoretical explanation, and the transparency of those algorithms has been doubted. Here, we propose an approach based on the open-flow network model to reveal the underlying flow structure and its hidden metric space of different random walk strategies on networks. We show that the essence of embedding based on random walks is the latent metric structure defined on the open-flow network. This not only deepens our understanding of random- walk-based embedding algorithms but also helps in finding new potential applications in network embedding.

  3. Mindfulness-based stress reduction for residents: A randomized controlled trial

    NARCIS (Netherlands)

    Verweij, H.; Ravesteijn, H.J. van; Hooff, M.L.M. van; Lagro-Janssen, A.L.M.; Speckens, A.E.M.

    2018-01-01

    Background: Burnout is highly prevalent in residents. No randomized controlled trials have been conducted measuring the effects of Mindfulness-Based Stress Reduction (MBSR) on burnout in residents. Objective: To determine the effectiveness of MBSR in reducing burnout in residents. Design: A

  4. Assessing the Promise of Standards-Based Performance Evaluation for Principals: Results from a Randomized Trial

    Science.gov (United States)

    Kimball, Steven Miller; Milanowski, Anthony; McKinney, Sarah A.

    2009-01-01

    Principals (N = 76) in a large western U.S. school district were randomly assigned to be evaluated using either a new standards-based system or to continue with the old system. It was hypothesized that principals evaluated with the new system would report clearer performance expectations, better feedback, greater fairness and system satisfaction,…

  5. Reinforcing Sampling Distributions through a Randomization-Based Activity for Introducing ANOVA

    Science.gov (United States)

    Taylor, Laura; Doehler, Kirsten

    2015-01-01

    This paper examines the use of a randomization-based activity to introduce the ANOVA F-test to students. The two main goals of this activity are to successfully teach students to comprehend ANOVA F-tests and to increase student comprehension of sampling distributions. Four sections of students in an advanced introductory statistics course…

  6. Generalized Selectivity Description for Polymeric Ion-Selective Electrodes Based on the Phase Boundary Potential Model.

    Science.gov (United States)

    Bakker, Eric

    2010-02-15

    A generalized description of the response behavior of potentiometric polymer membrane ion-selective electrodes is presented on the basis of ion-exchange equilibrium considerations at the sample-membrane interface. This paper includes and extends on previously reported theoretical advances in a more compact yet more comprehensive form. Specifically, the phase boundary potential model is used to derive the origin of the Nernstian response behavior in a single expression, which is valid for a membrane containing any charge type and complex stoichiometry of ionophore and ion-exchanger. This forms the basis for a generalized expression of the selectivity coefficient, which may be used for the selectivity optimization of ion-selective membranes containing electrically charged and neutral ionophores of any desired stoichiometry. It is shown to reduce to expressions published previously for specialized cases, and may be effectively applied to problems relevant in modern potentiometry. The treatment is extended to mixed ion solutions, offering a comprehensive yet formally compact derivation of the response behavior of ion-selective electrodes to a mixture of ions of any desired charge. It is compared to predictions by the less accurate Nicolsky-Eisenman equation. The influence of ion fluxes or any form of electrochemical excitation is not considered here, but may be readily incorporated if an ion-exchange equilibrium at the interface may be assumed in these cases.

  7. Quantum authentication based on the randomness of measurement bases in BB84

    International Nuclear Information System (INIS)

    Dang Minh Dung; Bellot, P.; Alleaume, R.

    2005-01-01

    Full text: The establishment of a secret key between two legitimate end points of a communication link, let us name them Alice and Bob, using Quantum key distribution (QKD) is unconditionally secure thanks to Quantum Physics laws.However, the various QKD protocols do not intend to provide the authentication of the end points: Alice cannot be sure that she is communicating with Bob and reciprocally. Therefore, these protocols are subjects to various attacks. The most obvious attack is the man-in-the-middle attack in which an eavesdropper, let us name her Eve, stands in the middle of the communication link. Alice communicates with Eve meanwhile she thinks she communicate with Bob. And Bob communicates with Eve meanwhile he thinks he is communicating with Alice. Eve, acting as a relay, can read all the communications between Alice and Bob and retransmit them. To prevent this kind of attack, the solution is to authenticate the two end points of the communication link. One solution is that Alice and Bob share an authentication key prior to the communication. In order to improve the security, Alice and Bob must share a set of authentication one-time keys. One-time key means that the key has to be used only once because each time a key is used, the eavesdropper Eve can gain a few information on the key. Re-using the same key many times would finally reveal the key to Eve. However, Eve can simulate many times the authentication process with Alice. Each time Eve simulates the authentication process, one of the pre-positioned keys is depleted leading to the exhaustion of the set of pre-positioned keys. This type of attack is named Denial of Service attack. In this work, we propose to use the randomness of the measurement bases in BB84 to build an authentication scheme based on the existence of a prepositioned authentication key. This authentication scheme can be used with BB84 but also with any other Quantum Key Distribution protocols. It is protected against the Denial of

  8. Gender differences and a school-based obesity prevention program in Argentina: a randomized trial.

    Science.gov (United States)

    Rausch Herscovici, Cecile; Kovalskys, Irina; De Gregorio, María José

    2013-08-01

    To evaluate the impact of a school-based obesity prevention program that seeks to change food intake among students at schools in Rosario, Argentina. This was a prospective study involving 405 children 9-11 years of age at six schools in the poor areas of Rosario, Argentina, in May-October 2008. After matching for socioeconomic status, schools were selected by simple randomization; participants were assessed at baseline (T1) and again 6 months later, after completion of the intervention (T2). The program focused on increasing the children's knowledge of healthy nutrition and exercise through four workshops; educating the parents/caregivers; and offering healthy options at the school snack bar. The main outcome measures were the children's intake of healthy and unhealthy foods (assessed with a weekly food frequency questionnaire) and their body mass index (BMI). Of the 387 children assessed at T1, 369 were reassessed at T2 (205 intervention; 164 control). Girls at the schools where the intervention occurred increased their intake of three of the five healthy food items promoted by the program (fruits, vegetables, low-sugar cereals). Statistical significance was reached for skim milk (P = 0.03) and for pure orange juice (P = 0.05). Boys of both the intervention and control groups failed to improve their intake of healthy foods, but those of the intervention arm significantly reduced their intake of hamburgers and hot dogs (P = 0.001). Girls were more amenable to improving their dietary intake. Overall, the program was more likely to increase consumption of healthy food than to decrease intake of unhealthy foods. Gender differences should be taken into account when designing preventive interventions.

  9. Gender differences and a school-based obesity prevention program in Argentina: a randomized trial

    Directory of Open Access Journals (Sweden)

    Cecile Rausch Herscovici

    2013-08-01

    Full Text Available OBJECTIVE: To evaluate the impact of a school-based obesity prevention program that seeks to change food intake among students at schools in Rosario, Argentina. METHODS: This was a prospective study involving 405 children 9-11 years of age at six schools in the poor areas of Rosario, Argentina, in May-October 2008. After matching for socioeconomic status, schools were selected by simple randomization; participants were assessed at baseline (T1 and again 6 months later, after completion of the intervention (T2. The program focused on increasing the children's knowledge of healthy nutrition and exercise through four workshops; educating the parents/caregivers; and offering healthy options at the school snack bar. The main outcome measures were the children's intake of healthy and unhealthy foods (assessed with a weekly food frequency questionnaire and their body mass index (BMI. RESULTS: Of the 387 children assessed at T1, 369 were reassessed at T2 (205 intervention; 164 control. Girls at the schools where the intervention occurred increased their intake of three of the five healthy food items promoted by the program (fruits, vegetables, low-sugar cereals. Statistical significance was reached for skim milk (P = 0.03 and for pure orange juice (P = 0.05. Boys of both the intervention and control groups failed to improve their intake of healthy foods, but those of the intervention arm significantly reduced their intake of hamburgers and hot dogs (P = 0.001. CONCLUSIONS: Girls were more amenable to improving their dietary intake. Overall, the program was more likely to increase consumption of healthy food than to decrease intake of unhealthy foods. Gender differences should be taken into account when designing preventive interventions.

  10. OBSERVATIONAL SELECTION EFFECTS WITH GROUND-BASED GRAVITATIONAL WAVE DETECTORS

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Hsin-Yu; Holz, Daniel E. [University of Chicago, Chicago, Illinois 60637 (United States); Essick, Reed; Vitale, Salvatore; Katsavounidis, Erik [LIGO, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States)

    2017-01-20

    Ground-based interferometers are not perfect all-sky instruments, and it is important to account for their behavior when considering the distribution of detected events. In particular, the LIGO detectors are most sensitive to sources above North America and the Indian Ocean, and as the Earth rotates, the sensitive regions are swept across the sky. However, because the detectors do not acquire data uniformly over time, there is a net bias on detectable sources’ right ascensions. Both LIGO detectors preferentially collect data during their local night; it is more than twice as likely to be local midnight than noon when both detectors are operating. We discuss these selection effects and how they impact LIGO’s observations and electromagnetic (EM) follow-up. Beyond galactic foregrounds associated with seasonal variations, we find that equatorial observatories can access over 80% of the localization probability, while mid-latitudes will access closer to 70%. Facilities located near the two LIGO sites can observe sources closer to their zenith than their analogs in the south, but the average observation will still be no closer than 44° from zenith. We also find that observatories in Africa or the South Atlantic will wait systematically longer before they can begin observing compared to the rest of the world; though, there is a preference for longitudes near the LIGOs. These effects, along with knowledge of the LIGO antenna pattern, can inform EM follow-up activities and optimization, including the possibility of directing observations even before gravitational-wave events occur.

  11. OBSERVATIONAL SELECTION EFFECTS WITH GROUND-BASED GRAVITATIONAL WAVE DETECTORS

    International Nuclear Information System (INIS)

    Chen, Hsin-Yu; Holz, Daniel E.; Essick, Reed; Vitale, Salvatore; Katsavounidis, Erik

    2017-01-01

    Ground-based interferometers are not perfect all-sky instruments, and it is important to account for their behavior when considering the distribution of detected events. In particular, the LIGO detectors are most sensitive to sources above North America and the Indian Ocean, and as the Earth rotates, the sensitive regions are swept across the sky. However, because the detectors do not acquire data uniformly over time, there is a net bias on detectable sources’ right ascensions. Both LIGO detectors preferentially collect data during their local night; it is more than twice as likely to be local midnight than noon when both detectors are operating. We discuss these selection effects and how they impact LIGO’s observations and electromagnetic (EM) follow-up. Beyond galactic foregrounds associated with seasonal variations, we find that equatorial observatories can access over 80% of the localization probability, while mid-latitudes will access closer to 70%. Facilities located near the two LIGO sites can observe sources closer to their zenith than their analogs in the south, but the average observation will still be no closer than 44° from zenith. We also find that observatories in Africa or the South Atlantic will wait systematically longer before they can begin observing compared to the rest of the world; though, there is a preference for longitudes near the LIGOs. These effects, along with knowledge of the LIGO antenna pattern, can inform EM follow-up activities and optimization, including the possibility of directing observations even before gravitational-wave events occur.

  12. FPGA-based RF spectrum merging and adaptive hopset selection

    Science.gov (United States)

    McLean, R. K.; Flatley, B. N.; Silvius, M. D.; Hopkinson, K. M.

    The radio frequency (RF) spectrum is a limited resource. Spectrum allotment disputes stem from this scarcity as many radio devices are confined to a fixed frequency or frequency sequence. One alternative is to incorporate cognition within a reconfigurable radio platform, therefore enabling the radio to adapt to dynamic RF spectrum environments. In this way, the radio is able to actively sense the RF spectrum, decide, and act accordingly, thereby sharing the spectrum and operating in more flexible manner. In this paper, we present a novel solution for merging many distributed RF spectrum maps into one map and for subsequently creating an adaptive hopset. We also provide an example of our system in operation, the result of which is a pseudorandom adaptive hopset. The paper then presents a novel hardware design for the frequency merger and adaptive hopset selector, both of which are written in VHDL and implemented as a custom IP core on an FPGA-based embedded system using the Xilinx Embedded Development Kit (EDK) software tool. The design of the custom IP core is optimized for area, and it can process a high-volume digital input via a low-latency circuit architecture. The complete embedded system includes the Xilinx PowerPC microprocessor, UART serial connection, and compact flash memory card IP cores, and our custom map merging/hopset selection IP core, all of which are targeted to the Virtex IV FPGA. This system is then incorporated into a cognitive radio prototype on a Rice University Wireless Open Access Research Platform (WARP) reconfigurable radio.

  13. Global stocks of selected mineral-based commodities

    Science.gov (United States)

    Wilburn, David R.; Bleiwas, Donald I.; Karl, Nick A.

    2016-12-05

    IntroductionThe U.S. Geological Survey, National Minerals Information Center, analyzes mineral and metal supply chains by identifying and describing major components of mineral and material flows from ore extraction, through intermediate forms, to a final product. This report focuses on an important component of the world’s supply chain: the amounts and global distribution of major consumer, producer, and exchange stocks of selected mineral commodities. In this report, the term “stock” is used instead of “inventory” and refers to accumulations of mined ore, intermediate products, and refined mineral-based commodities that are in a form that meets the agreed-upon specifications of a buyer or processor of intermediate products. These may include certain ores such as bauxite, concentrates, smelter products, and refined metals. Materials sometimes referred to as inventory for accounting purposes, such as ore contained in a deposit or in a leach pile, or materials that need to be further processed before they can be shipped to a consumer, are not considered. Stocks may be held (owned) by consumers, governments, investors, producers, and traders. They may serve as (1) a means to achieve economic, social, and strategic goals through government policies; (2) a secure source of supply to meet demand and to mitigate potential shortages in the supply chain; (3) a hedge to mitigate price volatility; and (4) vehicles for speculative investment.The paucity and uneven reliability of data for stocks of ores and concentrates and for material held by producers, consumers, and merchants hinder the accurate estimating of the size and distribution of this portion of the supply chain for certain commodities. This paper reviews the more visible stocks held in commodity exchange warehouses distributed throughout the world.

  14. Validation and selection of ODE based systems biology models: how to arrive at more reliable decisions.

    Science.gov (United States)

    Hasdemir, Dicle; Hoefsloot, Huub C J; Smilde, Age K

    2015-07-08

    Most ordinary differential equation (ODE) based modeling studies in systems biology involve a hold-out validation step for model validation. In this framework a pre-determined part of the data is used as validation data and, therefore it is not used for estimating the parameters of the model. The model is assumed to be validated if the model predictions on the validation dataset show good agreement with the data. Model selection between alternative model structures can also be performed in the same setting, based on the predictive power of the model structures on the validation dataset. However, drawbacks associated with this approach are usually under-estimated. We have carried out simulations by using a recently published High Osmolarity Glycerol (HOG) pathway from S.cerevisiae to demonstrate these drawbacks. We have shown that it is very important how the data is partitioned and which part of the data is used for validation purposes. The hold-out validation strategy leads to biased conclusions, since it can lead to different validation and selection decisions when different partitioning schemes are used. Furthermore, finding sensible partitioning schemes that would lead to reliable decisions are heavily dependent on the biology and unknown model parameters which turns the problem into a paradox. This brings the need for alternative validation approaches that offer flexible partitioning of the data. For this purpose, we have introduced a stratified random cross-validation (SRCV) approach that successfully overcomes these limitations. SRCV leads to more stable decisions for both validation and selection which are not biased by underlying biological phenomena. Furthermore, it is less dependent on the specific noise realization in the data. Therefore, it proves to be a promising alternative to the standard hold-out validation strategy.

  15. Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks.

    Science.gov (United States)

    Zheng, Guanglou; Fang, Gengfa; Shankaran, Rajan; Orgun, Mehmet A; Zhou, Jie; Qiao, Li; Saleem, Kashif

    2017-05-01

    Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of N bits, and each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, and T peaks. Time intervals between them, including RR, RQ, RS, RP, and RT intervals, are then calculated based on this arrival time, and are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, and can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system.

  16. Selective extraction and detection of noble metal based on ionic ...

    Indian Academy of Sciences (India)

    ClPrNTf2) was developed for selective detection of gold(III) by use of inductively coupled ... The importance to develop pre- ... attention. Ionic liquids (ILs) immobilized onto SG have been successfully applied as solid phase adsorbents for.

  17. Fluorescent naphthalene-based benzene tripod for selective ...

    Indian Academy of Sciences (India)

    The sensing property was extended for practical utility to sense fluoride in tap water, pond water and river water. Keywords. ... Development of selective optical signalling systems for ... contaminant level defined by the US Environmental.

  18. Selecting the optimum plot size for a California design-based stream and wetland mapping program.

    Science.gov (United States)

    Lackey, Leila G; Stein, Eric D

    2014-04-01

    Accurate estimates of the extent and distribution of wetlands and streams are the foundation of wetland monitoring, management, restoration, and regulatory programs. Traditionally, these estimates have relied on comprehensive mapping. However, this approach is prohibitively resource-intensive over large areas, making it both impractical and statistically unreliable. Probabilistic (design-based) approaches to evaluating status and trends provide a more cost-effective alternative because, compared with comprehensive mapping, overall extent is inferred from mapping a statistically representative, randomly selected subset of the target area. In this type of design, the size of sample plots has a significant impact on program costs and on statistical precision and accuracy; however, no consensus exists on the appropriate plot size for remote monitoring of stream and wetland extent. This study utilized simulated sampling to assess the performance of four plot sizes (1, 4, 9, and 16 km(2)) for three geographic regions of California. Simulation results showed smaller plot sizes (1 and 4 km(2)) were most efficient for achieving desired levels of statistical accuracy and precision. However, larger plot sizes were more likely to contain rare and spatially limited wetland subtypes. Balancing these considerations led to selection of 4 km(2) for the California status and trends program.

  19. An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

    Science.gov (United States)

    Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

    2016-01-01

    For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

  20. Water-Based Aerobic Training Successfully Improves Lipid Profile of Dyslipidemic Women: A Randomized Controlled Trial

    Science.gov (United States)

    Costa, Rochelle Rocha; Pilla, Carmen; Buttelli, Adriana Cristine Koch; Barreto, Michelle Flores; Vieiro, Priscila Azevedo; Alberton, Cristine Lima; Bracht, Cláudia Gomes; Kruel, Luiz Fernando Martins

    2018-01-01

    Purpose: This study aimed to investigate the effects of water-based aerobic training on the lipid profile and lipoprotein lipase (LPL) levels in premenopausal women with dyslipidemia. Method: Forty women were randomly assigned to: aquatic training (WA; n = 20) or a control group (CG; n = 20). The WA group underwent 12 weeks of water-based interval…

  1. Web-Based and Mobile Stress Management Intervention for Employees: A Randomized Controlled Trial

    OpenAIRE

    Heber, Elena; Lehr, Dirk; Ebert, David Daniel; Berking, Matthias; Riper, Heleen

    2016-01-01

    Background: Work-related stress is highly prevalent among employees and is associated with adverse mental health consequences. Web-based interventions offer the opportunity to deliver effective solutions on a large scale; however, the evidence is limited and the results conflicting. Objective: This randomized controlled trial evaluated the efficacy of guided Web-and mobile-based stress management training for employees. Methods: A total of 264 employees with elevated symptoms of stress (Perce...

  2. A novel attack method about double-random-phase-encoding-based image hiding method

    Science.gov (United States)

    Xu, Hongsheng; Xiao, Zhijun; Zhu, Xianchen

    2018-03-01

    By using optical image processing techniques, a novel text encryption and hiding method applied by double-random phase-encoding technique is proposed in the paper. The first step is that the secret message is transformed into a 2-dimension array. The higher bits of the elements in the array are used to fill with the bit stream of the secret text, while the lower bits are stored specific values. Then, the transformed array is encoded by double random phase encoding technique. Last, the encoded array is embedded on a public host image to obtain the image embedded with hidden text. The performance of the proposed technique is tested via analytical modeling and test data stream. Experimental results show that the secret text can be recovered either accurately or almost accurately, while maintaining the quality of the host image embedded with hidden data by properly selecting the method of transforming the secret text into an array and the superimposition coefficient.

  3. Innovation in values based public health nursing student selection: A qualitative evaluation of candidate and selection panel member perspectives.

    Science.gov (United States)

    McGraw, Caroline; Abbott, Stephen; Brook, Judy

    2018-02-19

    Values based recruitment emerges from the premise that a high degree of value congruence, or the extent to which an individual's values are similar to those of the health organization in which they work, leads to organizational effectiveness. The aim of this evaluation was to explore how candidates and selection panel members experienced and perceived innovative methods of values based public health nursing student selection. The evaluation was framed by a qualitative exploratory design involving semi-structured interviews and a group exercise. Data were thematically analyzed. Eight semi-structured interviews were conducted with selection panel members. Twenty-two successful candidates took part in a group exercise. The use of photo elicitation interviews and situational judgment questions in the context of selection to a university-run public health nursing educational program was explored. While candidates were ambivalent about the use of photo elicitation interviews, with some misunderstanding the task, selection panel members saw the benefits for improving candidate expression and reducing gaming and deception. Situational interview questions were endorsed by candidates and selection panel members due to their fidelity to real-life problems and the ability of panel members to discern value congruence from candidates' responses. Both techniques offered innovative solutions to candidate selection for entry to the public health nursing education program. © 2018 Wiley Periodicals, Inc.

  4. Theory of mind selectively predicts preschoolers’ knowledge-based selective word learning

    Science.gov (United States)

    Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane

    2015-01-01

    Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory of mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children’s preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children’s developing social cognition and early learning. PMID:26211504

  5. Theory of mind selectively predicts preschoolers' knowledge-based selective word learning.

    Science.gov (United States)

    Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane

    2015-11-01

    Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory-of-mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children's preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children's developing social cognition and early learning. © 2015 The British Psychological Society.

  6. A Community-Based Randomized Trial of Hepatitis B Screening Among High-Risk Vietnamese Americans.

    Science.gov (United States)

    Ma, Grace X; Fang, Carolyn Y; Seals, Brenda; Feng, Ziding; Tan, Yin; Siu, Philip; Yeh, Ming Chin; Golub, Sarit A; Nguyen, Minhhuyen T; Tran, Tam; Wang, Minqi

    2017-03-01

    To evaluate the effectiveness of a community-based liver cancer prevention program on hepatitis B virus (HBV) screening among low-income, underserved Vietnamese Americans at high risk. We conducted a cluster randomized trial involving 36 Vietnamese community-based organizations and 2337 participants in Pennsylvania, New Jersey, and New York City between 2009 and 2014. We randomly assigned 18 community-based organizations to a community-based multilevel HBV screening intervention (n = 1131). We randomly assigned the remaining 18 community-based organizations to a general cancer education program (n = 1206), which included information about HBV-related liver cancer prevention. We assessed HBV screening rates at 6-month follow-up. Intervention participants were significantly more likely to have undergone HBV screening (88.1%) than were control group participants (4.6%). In a Cochran-Mantel-Haenszel analysis, the intervention effect on screening outcomes remained statistically significant after adjustment for demographic and health care access variables, including income, having health insurance, having a regular health provider, and English proficiency. A community-based, culturally appropriate, multilevel HBV screening intervention effectively increases screening rates in a high-risk, hard-to-reach Vietnamese American population.

  7. A robust random number generator based on differential comparison of chaotic laser signals.

    Science.gov (United States)

    Zhang, Jianzhong; Wang, Yuncai; Liu, Ming; Xue, Lugang; Li, Pu; Wang, Anbang; Zhang, Mingjiang

    2012-03-26

    We experimentally realize a robust real-time random number generator by differentially comparing the signal from a chaotic semiconductor laser and its delayed signal through a 1-bit analog-to-digital converter. The probability density distribution of the output chaotic signal based on the differential comparison method possesses an extremely small coefficient of Pearson's median skewness (1.5 × 10⁻⁶), which can yield a balanced random sequence much easily than the previously reported method that compares the signal from the chaotic laser with a certain threshold value. Moveover, we experimently demonstrate that our method can stably generate good random numbers at rates of 1.44 Gbit/s with excellent immunity from external perturbations while the previously reported method fails.

  8. Experimental study of a quantum random-number generator based on two independent lasers

    Science.gov (United States)

    Sun, Shi-Hai; Xu, Feihu

    2017-12-01

    A quantum random-number generator (QRNG) can produce true randomness by utilizing the inherent probabilistic nature of quantum mechanics. Recently, the spontaneous-emission quantum phase noise of the laser has been widely deployed for quantum random-number generation, due to its high rate, its low cost, and the feasibility of chip-scale integration. Here, we perform a comprehensive experimental study of a phase-noise-based QRNG with two independent lasers, each of which operates in either continuous-wave (CW) or pulsed mode. We implement the QRNG by operating the two lasers in three configurations, namely, CW + CW, CW + pulsed, and pulsed + pulsed, and demonstrate their trade-offs, strengths, and weaknesses.

  9. Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

    Directory of Open Access Journals (Sweden)

    Hideki Katagiri

    2017-10-01

    Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.

  10. A Simple K-Map Based Variable Selection Scheme in the Direct ...

    African Journals Online (AJOL)

    A multiplexer with (n-l) data select inputs can realise directly a function of n variables. In this paper, a simple k-map based variable selection scheme is proposed such that an n variable logic function can be synthesised using a multiplexer with (n-q) data input variables and q data select variables. The procedure is based on ...

  11. Impact of Menu Sequencing on Internet-Based Educational Module Selection

    Science.gov (United States)

    Bensley, Robert; Brusk, John J.; Rivas, Jason; Anderson, Judith V.

    2006-01-01

    Patterns of Internet-based menu item selection can occur for a number of reasons, many of which may not be based on interest in topic. It then becomes important to ensure menu order is devised in a way that ensures the greatest accuracy in matching user need with selection. This study examined the impact of menu rotation on the selection of…

  12. A Distributed Dynamic Super Peer Selection Method Based on Evolutionary Game for Heterogeneous P2P Streaming Systems

    Directory of Open Access Journals (Sweden)

    Jing Chen

    2013-01-01

    Full Text Available Due to high efficiency and good scalability, hierarchical hybrid P2P architecture has drawn more and more attention in P2P streaming research and application fields recently. The problem about super peer selection, which is the key problem in hybrid heterogeneous P2P architecture, is becoming highly challenging because super peers must be selected from a huge and dynamically changing network. A distributed super peer selection (SPS algorithm for hybrid heterogeneous P2P streaming system based on evolutionary game is proposed in this paper. The super peer selection procedure is modeled based on evolutionary game framework firstly, and its evolutionarily stable strategies are analyzed. Then a distributed Q-learning algorithm (ESS-SPS according to the mixed strategies by analysis is proposed for the peers to converge to the ESSs based on its own payoff history. Compared to the traditional randomly super peer selection scheme, experiments results show that the proposed ESS-SPS algorithm achieves better performance in terms of social welfare and average upload rate of super peers and keeps the upload capacity of the P2P streaming system increasing steadily with the number of peers increasing.

  13. Selective Distance-Based K+ Quantification on Paper-Based Microfluidics.

    Science.gov (United States)

    Gerold, Chase T; Bakker, Eric; Henry, Charles S

    2018-04-03

    In this study, paper-based microfluidic devices (μPADs) capable of K + quantification in aqueous samples, as well as in human serum, using both colorimetric and distance-based methods are described. A lipophilic phase containing potassium ionophore I (valinomycin) was utilized to achieve highly selective quantification of K + in the presence of Na + , Li + , and Mg 2+ ions. Successful addition of a suspended lipophilic phase to a wax printed paper-based device is described and offers a solution to current approaches that rely on organic solvents, which damage wax barriers. The approach provides an avenue for future alkali/alkaline quantification utilizing μPADs. Colorimetric spot tests allowed for K + quantification from 0.1-5.0 mM using only 3.00 μL of sample solution. Selective distance-based quantification required small sample volumes (6.00 μL) and gave responses sensitive enough to distinguish between 1.0 and 2.5 mM of sample K + . μPADs using distance-based methods were also capable of differentiating between 4.3 and 6.9 mM K + in human serum samples. Distance-based methods required no digital analysis, electronic hardware, or pumps; any steps required for quantification could be carried out using the naked eye.

  14. Who participates in a randomized trial of mindfulness-based stress reduction (MBSR) after breast cancer?

    DEFF Research Database (Denmark)

    Würtzen, Hanne; Oksbjerg Dalton, Susanne; Kaae Andersen, Klaus

    2013-01-01

    Danish population-based registries and clinical databases to determine differences in demographics, breast cancer and co-morbidity among 1208 women eligible for a randomized controlled trial (www.clinicaltrials.gov identifier: NCT00990977) of mindfulness-based stress reduction MBSR. RESULTS: Participants......BACKGROUND: Discussion regarding the necessity to identify patients with both the need and motivation for psychosocial intervention is ongoing. Evidence for an effect of mindfulness-based interventions among cancer patients is based on few studies with no systematic enrollment. METHODS: We used...

  15. Developing evidence-based dentistry skills: how to interpret randomized clinical trials and systematic reviews.

    Science.gov (United States)

    Kiriakou, Juliana; Pandis, Nikolaos; Madianos, Phoebus; Polychronopoulou, Argy

    2014-10-30

    Decision-making based on reliable evidence is more likely to lead to effective and efficient treatments. Evidence-based dentistry was developed, similarly to evidence-based medicine, to help clinicians apply current and valid research findings into their own clinical practice. Interpreting and appraising the literature is fundamental and involves the development of evidence-based dentistry (EBD) skills. Systematic reviews (SRs) of randomized controlled trials (RCTs) are considered to be evidence of the highest level in evaluating the effectiveness of interventions. Furthermore, the assessment of the report of a RCT, as well as a SR, can lead to an estimation of how the study was designed and conducted.

  16. Calculating radiotherapy margins based on Bayesian modelling of patient specific random errors

    International Nuclear Information System (INIS)

    Herschtal, A; Te Marvelde, L; Mengersen, K; Foroudi, F; Ball, D; Devereux, T; Pham, D; Greer, P B; Pichler, P; Eade, T; Kneebone, A; Bell, L; Caine, H; Hindson, B; Kron, T; Hosseinifard, Z

    2015-01-01

    Collected real-life clinical target volume (CTV) displacement data show that some patients undergoing external beam radiotherapy (EBRT) demonstrate significantly more fraction-to-fraction variability in their displacement (‘random error’) than others. This contrasts with the common assumption made by historical recipes for margin estimation for EBRT, that the random error is constant across patients. In this work we present statistical models of CTV displacements in which random errors are characterised by an inverse gamma (IG) distribution in order to assess the impact of random error variability on CTV-to-PTV margin widths, for eight real world patient cohorts from four institutions, and for different sites of malignancy. We considered a variety of clinical treatment requirements and penumbral widths. The eight cohorts consisted of a total of 874 patients and 27 391 treatment sessions. Compared to a traditional margin recipe that assumes constant random errors across patients, for a typical 4 mm penumbral width, the IG based margin model mandates that in order to satisfy the common clinical requirement that 90% of patients receive at least 95% of prescribed RT dose to the entire CTV, margins be increased by a median of 10% (range over the eight cohorts −19% to +35%). This substantially reduces the proportion of patients for whom margins are too small to satisfy clinical requirements. (paper)

  17. When to base clinical policies on observational versus randomized trial data.

    Science.gov (United States)

    Hornberger, J; Wrone, E

    1997-10-15

    Physicians must decide when the evidence is sufficient to adopt a new clinical policy. Analysis of large clinical and administrative databases is becoming an important source of evidence for changing clinical policies. Because such analysis cannot control for the effects of all potential confounding variables, physicians risk drawing the wrong conclusion about the cause-and-effect relation between a change in clinical policy and outcomes. Randomized studies offer protection against drawing a conclusion that would lead to adoption of an inferior policy. However, a randomized study may be difficult to justify because of the extra costs of collecting data for a randomized study and concerns that a study will not directly benefit the patients enrolled in the study. This article reviews the advantages and disadvantages of basing clinical policy on analysis of large databases compared with conducting a randomized study. A technique is described and illustrated for accessing the potential costs and benefits of conducting such a study. This type of analysis formed the basis for a physician-managed health care organization deciding to sponsor a randomized study among patients with end-stage renal disease as part of a quality-improvement initiative.

  18. The role of repetition and reinforcement in school-based oral health education-a cluster randomized controlled trial.

    Science.gov (United States)

    Haleem, Abdul; Khan, Muhammad Khalil; Sufia, Shamta; Chaudhry, Saima; Siddiqui, Muhammad Irfanullah; Khan, Ayyaz Ali

    2016-01-04

    Repetition and reinforcement have been shown to play a crucial role in the sustainability of the effect of Oral Health Education (OHE) programs. However, its relevance to school-based OHE imparted by different personnel is not depicted by the existing dental literature. The present study was undertaken to determine the effectiveness of the repeated and reinforced OHE (RR-OHE) compared to one-time OHE intervention and to assess its role in school-based OHE imparted by dentist, teachers and peers. The study was a cluster randomized controlled trial that involved 935 adolescents aged 10-11 years. Twenty four boys' and girls' schools selected at random in two towns of Karachi, Pakistan were randomly assigned to three groups to receive OHE by dentist (DL), teachers (TL) and peer-leaders (PL). The groups received a single OHE session and were evaluated post-intervention and 6 months after. The three groups were then exposed to OHE for 6 months followed by 1 year of no OHE activity. Two further evaluations at 6-month and 12-month intervals were conducted. The data were collected by a self-administered questionnaire preceded by a structured interview and followed by oral examination of participants. The adolescents' oral health knowledge (OHK) in the DL and PL groups increased significantly by a single OHE session compared to their baseline knowledge (p strategy. Although the OHK scores of the DL and PL groups decreased significantly at 12-month evaluation of RR-OHE (p play a key role in school-based OHE irrespective of educators. The trained teachers and peers can play a complementary role in RR-OHE.

  19. Process observation in fiber laser-based selective laser melting

    Science.gov (United States)

    Thombansen, Ulrich; Gatej, Alexander; Pereira, Milton

    2015-01-01

    The process observation in selective laser melting (SLM) focuses on observing the interaction point where the powder is processed. To provide process relevant information, signals have to be acquired that are resolved in both time and space. Especially in high-power SLM, where more than 1 kW of laser power is used, processing speeds of several meters per second are required for a high-quality processing results. Therefore, an implementation of a suitable process observation system has to acquire a large amount of spatially resolved data at low sampling speeds or it has to restrict the acquisition to a predefined area at a high sampling speed. In any case, it is vitally important to synchronously record the laser beam position and the acquired signal. This is a prerequisite that allows the recorded data become information. Today, most SLM systems employ f-theta lenses to focus the processing laser beam onto the powder bed. This report describes the drawbacks that result for process observation and suggests a variable retro-focus system which solves these issues. The beam quality of fiber lasers delivers the processing laser beam to the powder bed at relevant focus diameters, which is a key prerequisite for this solution to be viable. The optical train we present here couples the processing laser beam and the process observation coaxially, ensuring consistent alignment of interaction zone and observed area. With respect to signal processing, we have developed a solution that synchronously acquires signals from a pyrometer and the position of the laser beam by sampling the data with a field programmable gate array. The relevance of the acquired signals has been validated by the scanning of a sample filament. Experiments with grooved samples show a correlation between different powder thicknesses and the acquired signals at relevant processing parameters. This basic work takes a first step toward self-optimization of the manufacturing process in SLM. It enables the

  20. Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy.

    Directory of Open Access Journals (Sweden)

    Lina Zhang

    Full Text Available Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant proteins could contribute to revealing physiological processes of oxidation/antioxidation balance and developing novel antioxidation-based drugs. In this study, an ensemble method is presented to predict antioxidant proteins with hybrid features, incorporating SSI (Secondary Structure Information, PSSM (Position Specific Scoring Matrix, RSA (Relative Solvent Accessibility, and CTD (Composition, Transition, Distribution. The prediction results of the ensemble predictor are determined by an average of prediction results of multiple base classifiers. Based on a classifier selection strategy, we obtain an optimal ensemble classifier composed of RF (Random Forest, SMO (Sequential Minimal Optimization, NNA (Nearest Neighbor Algorithm, and J48 with an accuracy of 0.925. A Relief combined with IFS (Incremental Feature Selection method is adopted to obtain optimal features from hybrid features. With the optimal features, the ensemble method achieves improved performance with a sensitivity of 0.95, a specificity of 0.93, an accuracy of 0.94, and an MCC (Matthew's Correlation Coefficient of 0.880, far better than the existing method. To evaluate the prediction performance objectively, the proposed method is compared with existing methods on the same independent testing dataset. Encouragingly, our method performs better than previous studies. In addition, our method achieves more balanced performance with a sensitivity of 0.878 and a specificity of 0.860. These results suggest that the proposed ensemble method can be a potential candidate for antioxidant protein prediction. For public access, we develop a user-friendly web server for antioxidant protein identification that is freely accessible at http://antioxidant.weka.cc.

  1. The Fault Diagnosis of Rolling Bearing Based on Ensemble Empirical Mode Decomposition and Random Forest

    Directory of Open Access Journals (Sweden)

    Xiwen Qin

    2017-01-01

    Full Text Available Accurate diagnosis of rolling bearing fault on the normal operation of machinery and equipment has a very important significance. A method combining Ensemble Empirical Mode Decomposition (EEMD and Random Forest (RF is proposed. Firstly, the original signal is decomposed into several intrinsic mode functions (IMFs by EEMD, and the effective IMFs are selected. Then their energy entropy is calculated as the feature. Finally, the classification is performed by RF. In addition, the wavelet method is also used in the proposed process, the same as EEMD. The results of the comparison show that the EEMD method is more accurate than the wavelet method.

  2. Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

    Science.gov (United States)

    Hong, Liang

    2013-10-01

    The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

  3. Cryptographic analysis on the key space of optical phase encryption algorithm based on the design of discrete random phase mask

    Science.gov (United States)

    Lin, Chao; Shen, Xueju; Li, Zengyan

    2013-07-01

    The key space of phase encryption algorithm using discrete random phase mask is investigated by numerical simulation in this paper. Random phase mask with finite and discrete phase levels is considered as the core component in most practical optical encryption architectures. The key space analysis is based on the design criteria of discrete random phase mask. The role of random amplitude mask and random phase mask in optical encryption system is identified from the perspective of confusion and diffusion. The properties of discrete random phase mask in a practical double random phase encoding scheme working in both amplitude encoding (AE) and phase encoding (PE) modes are comparably analyzed. The key space of random phase encryption algorithm is evaluated considering both the encryption quality and the brute-force attack resistibility. A method for enlarging the key space of phase encryption algorithm is also proposed to enhance the security of optical phase encryption techniques.

  4. GoDisco: Selective Gossip Based Dissemination of Information in Social Community Based Overlays

    Science.gov (United States)

    Datta, Anwitaman; Sharma, Rajesh

    We propose and investigate a gossip based, social principles and behavior inspired decentralized mechanism (GoDisco) to disseminate information in online social community networks, using exclusively social links and exploiting semantic context to keep the dissemination process selective to relevant nodes. Such a designed dissemination scheme using gossiping over a egocentric social network is unique and is arguably a concept whose time has arrived, emulating word of mouth behavior and can have interesting applications like probabilistic publish/subscribe, decentralized recommendation and contextual advertisement systems, to name a few. Simulation based experiments show that despite using only local knowledge and contacts, the system has good global coverage and behavior.

  5. Metasurface-based angle-selective multichannel acoustic refractor

    Science.gov (United States)

    Liu, Bingyi; Jiang, Yongyuan

    2018-05-01

    We theoretically study the angle-selective refractions of an impedance-matched acoustic gradient-index metasurface, which is integrated with a rigid bar array of a deep subwavelength period. An interesting refraction order appears under the all-angle incidence despite the existence of a critical angle, and notably, the odevity of the phase-discretization level apparently selects the transmitted diffraction orders. We utilize the strategy of multilayered media design to realize a three-channel acoustic refractor, which shows good promise for constructing multifunctional diffractive acoustic elements for acoustic communication.

  6. [Plaque segmentation of intracoronary optical coherence tomography images based on K-means and improved random walk algorithm].

    Science.gov (United States)

    Wang, Guanglei; Wang, Pengyu; Han, Yechen; Liu, Xiuling; Li, Yan; Lu, Qian

    2017-06-01

    In recent years, optical coherence tomography (OCT) has developed into a popular coronary imaging technology at home and abroad. The segmentation of plaque regions in coronary OCT images has great significance for vulnerable plaque recognition and research. In this paper, a new algorithm based on K -means clustering and improved random walk is proposed and Semi-automated segmentation of calcified plaque, fibrotic plaque and lipid pool was achieved. And the weight function of random walk is improved. The distance between the edges of pixels in the image and the seed points is added to the definition of the weight function. It increases the weak edge weights and prevent over-segmentation. Based on the above methods, the OCT images of 9 coronary atherosclerotic patients were selected for plaque segmentation. By contrasting the doctor's manual segmentation results with this method, it was proved that this method had good robustness and accuracy. It is hoped that this method can be helpful for the clinical diagnosis of coronary heart disease.

  7. CHARACTERIZING THE OPTICAL VARIABILITY OF BRIGHT BLAZARS: VARIABILITY-BASED SELECTION OF FERMI ACTIVE GALACTIC NUCLEI

    International Nuclear Information System (INIS)

    Ruan, John J.; Anderson, Scott F.; MacLeod, Chelsea L.; Becker, Andrew C.; Davenport, James R. A.; Ivezić, Željko; Burnett, T. H.; Kochanek, Christopher S.; Plotkin, Richard M.; Sesar, Branimir; Stuart, J. Scott

    2012-01-01

    We investigate the use of optical photometric variability to select and identify blazars in large-scale time-domain surveys, in part to aid in the identification of blazar counterparts to the ∼30% of γ-ray sources in the Fermi 2FGL catalog still lacking reliable associations. Using data from the optical LINEAR asteroid survey, we characterize the optical variability of blazars by fitting a damped random walk model to individual light curves with two main model parameters, the characteristic timescales of variability τ, and driving amplitudes on short timescales σ-circumflex. Imposing cuts on minimum τ and σ-circumflex allows for blazar selection with high efficiency E and completeness C. To test the efficacy of this approach, we apply this method to optically variable LINEAR objects that fall within the several-arcminute error ellipses of γ-ray sources in the Fermi 2FGL catalog. Despite the extreme stellar contamination at the shallow depth of the LINEAR survey, we are able to recover previously associated optical counterparts to Fermi active galactic nuclei with E ≥ 88% and C = 88% in Fermi 95% confidence error ellipses having semimajor axis r < 8'. We find that the suggested radio counterpart to Fermi source 2FGL J1649.6+5238 has optical variability consistent with other γ-ray blazars and is likely to be the γ-ray source. Our results suggest that the variability of the non-thermal jet emission in blazars is stochastic in nature, with unique variability properties due to the effects of relativistic beaming. After correcting for beaming, we estimate that the characteristic timescale of blazar variability is ∼3 years in the rest frame of the jet, in contrast with the ∼320 day disk flux timescale observed in quasars. The variability-based selection method presented will be useful for blazar identification in time-domain optical surveys and is also a probe of jet physics.

  8. Characterizing the Optical Variability of Bright Blazars: Variability-based Selection of Fermi Active Galactic Nuclei

    Science.gov (United States)

    Ruan, John J.; Anderson, Scott F.; MacLeod, Chelsea L.; Becker, Andrew C.; Burnett, T. H.; Davenport, James R. A.; Ivezić, Željko; Kochanek, Christopher S.; Plotkin, Richard M.; Sesar, Branimir; Stuart, J. Scott

    2012-11-01

    We investigate the use of optical photometric variability to select and identify blazars in large-scale time-domain surveys, in part to aid in the identification of blazar counterparts to the ~30% of γ-ray sources in the Fermi 2FGL catalog still lacking reliable associations. Using data from the optical LINEAR asteroid survey, we characterize the optical variability of blazars by fitting a damped random walk model to individual light curves with two main model parameters, the characteristic timescales of variability τ, and driving amplitudes on short timescales \\hat{\\sigma }. Imposing cuts on minimum τ and \\hat{\\sigma } allows for blazar selection with high efficiency E and completeness C. To test the efficacy of this approach, we apply this method to optically variable LINEAR objects that fall within the several-arcminute error ellipses of γ-ray sources in the Fermi 2FGL catalog. Despite the extreme stellar contamination at the shallow depth of the LINEAR survey, we are able to recover previously associated optical counterparts to Fermi active galactic nuclei with E >= 88% and C = 88% in Fermi 95% confidence error ellipses having semimajor axis r beaming. After correcting for beaming, we estimate that the characteristic timescale of blazar variability is ~3 years in the rest frame of the jet, in contrast with the ~320 day disk flux timescale observed in quasars. The variability-based selection method presented will be useful for blazar identification in time-domain optical surveys and is also a probe of jet physics.

  9. Directory of selected forestry-related bibliographic data bases

    Science.gov (United States)

    Peter A. Evans

    1979-01-01

    This compilation lists 117 bibliographic data bases maintained by scientists of the Forest Service, U.S. Department of Agriculture. For each data base, the following information is provided; name of the data base; originator; date started; coverage by subject; geographic area, and size of collection; base format; retrieval format; ways to query; who to query; and...

  10. Selecting a risk-based tool to aid in decision making

    Energy Technology Data Exchange (ETDEWEB)

    Bendure, A.O.

    1995-03-01

    Selecting a risk-based tool to aid in decision making is as much of a challenge as properly using the tool once it has been selected. Failure to consider customer and stakeholder requirements and the technical bases and differences in risk-based decision making tools will produce confounding and/or politically unacceptable results when the tool is used. Selecting a risk-based decisionmaking tool must therefore be undertaken with the same, if not greater, rigor than the use of the tool once it is selected. This paper presents a process for selecting a risk-based tool appropriate to a set of prioritization or resource allocation tasks, discusses the results of applying the process to four risk-based decision-making tools, and identifies the ``musts`` for successful selection and implementation of a risk-based tool to aid in decision making.

  11. Moment Conditions Selection Based on Adaptive Penalized Empirical Likelihood

    Directory of Open Access Journals (Sweden)

    Yunquan Song

    2014-01-01

    Full Text Available Empirical likelihood is a very popular method and has been widely used in the fields of artificial intelligence (AI and data mining as tablets and mobile application and social media dominate the technology landscape. This paper proposes an empirical likelihood shrinkage method to efficiently estimate unknown parameters and select correct moment conditions simultaneously, when the model is defined by moment restrictions in which some are possibly misspecified. We show that our method enjoys oracle-like properties; that is, it consistently selects the correct moment conditions and at the same time its estimator is as efficient as the empirical likelihood estimator obtained by all correct moment conditions. Moreover, unlike the GMM, our proposed method allows us to carry out confidence regions for the parameters included in the model without estimating the covariances of the estimators. For empirical implementation, we provide some data-driven procedures for selecting the tuning parameter of the penalty function. The simulation results show that the method works remarkably well in terms of correct moment selection and the finite sample properties of the estimators. Also, a real-life example is carried out to illustrate the new methodology.

  12. MySQL based selection of appropriate indexing technique in ...

    African Journals Online (AJOL)

    This paper deals with selection of appropriate indexing technique applied on MySQL Database for a health care system and related performance issues using multiclass support vector machine (SVM). The patient database is generally huge and contains lot of variations. For the quick search or fast retrieval of the desired ...

  13. Emotion of Physiological Signals Classification Based on TS Feature Selection

    Institute of Scientific and Technical Information of China (English)

    Wang Yujing; Mo Jianlin

    2015-01-01

    This paper propose a method of TS-MLP about emotion recognition of physiological signal.It can recognize emotion successfully by Tabu search which selects features of emotion’s physiological signals and multilayer perceptron that is used to classify emotion.Simulation shows that it has achieved good emotion classification performance.

  14. Functional Assessment-Based Intervention for Selective Mutism

    Science.gov (United States)

    Kern, Lee; Starosta, Kristin M.; Bambara, Linda M.; Cook, Clayton R.; Gresham, Frank R.

    2007-01-01

    The process of functional assessment has emerged as an essential component for intervention development. Applications across divergent types of problem behavior, however, remain limited. This study evaluated the applicability of this promising approach to students with selective mutism. Two middle school students served as participants. The…

  15. based 2D dynamic metal-organic framework showing selective

    Indian Academy of Sciences (India)

    materials have been extensively studied for storage, separation, magnetism, sensing, biomedical and very recently for ion conduction applications.14–21 Hydrogen ... thesis of dynamic MOF with high affinity for water becomes handy in separation applications. Also, for a material to be smart sorbent, in addition to selective ...

  16. A CORPUS-BASED STYLISTIC ANALYSIS OF SELECTED RADIO ...

    African Journals Online (AJOL)

    NGOZI

    from Pendants of Rhythm: A Selection of Radio Nigeria Network News ... social roles we have to fill in everyday life and where the meaning processes, or discourses .... Antonymy: Some words opposite in meaning are juxtaposed to underscore .... Hyperbole: The ignorant man is greedy and stuffs his mouth with food until his ...

  17. Automatic Trading Agent. RMT Based Portfolio Theory and Portfolio Selection

    Science.gov (United States)

    Snarska, M.; Krzych, J.

    2006-11-01

    Portfolio theory is a very powerful tool in the modern investment theory. It is helpful in estimating risk of an investor's portfolio, arosen from lack of information, uncertainty and incomplete knowledge of reality, which forbids a perfect prediction of future price changes. Despite of many advantages this tool is not known and not widely used among investors on Warsaw Stock Exchange. The main reason for abandoning this method is a high level of complexity and immense calculations. The aim of this paper is to introduce an automatic decision-making system, which allows a single investor to use complex methods of Modern Portfolio Theory (MPT). The key tool in MPT is an analysis of an empirical covariance matrix. This matrix, obtained from historical data, biased by such a high amount of statistical uncertainty, that it can be seen as random. By bringing into practice the ideas of Random Matrix Theory (RMT), the noise is removed or significantly reduced, so the future risk and return are better estimated and controlled. These concepts are applied to the Warsaw Stock Exchange Simulator {http://gra.onet.pl}. The result of the simulation is 18% level of gains in comparison with respective 10% loss of the Warsaw Stock Exchange main index WIG.

  18. Synthesis and characterization of sugar-based methacrylates and their random copolymers by ATRP

    Directory of Open Access Journals (Sweden)

    G. Acik

    2017-10-01

    Full Text Available Various sugar-based methacrylate monomers have been prepared and randomly copolymerized with methyl methacrylate (MMA using classical atom transfer radical polymerization (ATRP. Firstly, four different sugar-based methacrylates are synthesized by two-step method: (i etherification of protected monosaccharides with epichlorohydrin and (ii following ring-opening reaction of obtained epoxides with methacrylic acid (MAA in the presence of triethylamine. Next, these monomers are copolymerized with MMA via ATRP at 90 °C to obtain corresponding random copolymers. The molecular weights of the copolymers are determined by both GPC (gel permeation chromatography and 1H-NMR (nuclear magnetic resonance spectroscopy analyses and found as 10600~16800 and 12200~18500 g/mol, respectively. Moreover, the copolymer compositions are also determined by 1H-NMR analysis using characteristic signals of the monomers and found as about 94.1~97.8%, which are good agreement with feeding ratio. In addition, the glass transition temperatures of copolymers are found as 101.2~102.9 °C by changing type and composition of sugar-based methacrylate monomers. Overall, a series of well-defined random copolymers comprising different sugar-based methacrylates and methyl methacrylates were successfully synthesized by classical ATRP method.

  19. A Unified 3D Mesh Segmentation Framework Based on Markov Random Field

    OpenAIRE

    Z.F. Shi; L.Y. Lu; D. Le; X.M. Niu

    2012-01-01

    3D Mesh segmentation has become an important research field in computer graphics during the past decades. Many geometry based and semantic oriented approaches for 3D mesh segmentation has been presented. In this paper, we present a definition of mesh segmentation according to labeling problem. Inspired by the Markov Random Field (MRF) based image segmentation, we propose a new framework of 3D mesh segmentation based on MRF and use graph cuts to solve it. Any features of 3D mesh can be integra...

  20. Feature Selection and Blind Source Separation in an EEG-Based Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    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 “yes” or “no” 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 “yes”/“no” 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 “direct,” single-session BCI.

  1. A Simple Density with Distance Based Initial Seed Selection Technique for K Means Algorithm

    Directory of Open Access Journals (Sweden)

    Sajidha Syed Azimuddin

    2017-01-01

    Full Text Available Open issues with respect to K means algorithm are identifying the number of clusters, initial seed concept selection, clustering tendency, handling empty clusters, identifying outliers etc. In this paper we propose a novel and a simple technique considering both density and distance of the concepts in a dataset to identify initial seed concepts for clustering. Many authors have proposed different techniques to identify initial seed concepts; but our method ensures that the initial seed concepts are chosen from different clusters that are to be generated by the clustering solution. The hallmark of our algorithm is that it is a single pass algorithm that does not require any extra parameters to be estimated. Further, our seed concepts are one among the actual concepts and not the mean of representative concepts as is the case in many other algorithms. We have implemented our proposed algorithm and compared the results with the interval based technique of Fouad Khan. We see that our method outperforms the interval based method. We have also compared our method with the original random K means and K Means++ algorithms.

  2. Comparative studies of praseodymium(III) selective sensors based on newly synthesized Schiff's bases

    International Nuclear Information System (INIS)

    Gupta, Vinod K.; Goyal, Rajendra N.; Pal, Manoj K.; Sharma, Ram A.

    2009-01-01

    Praseodymium ion selective polyvinyl chloride (PVC) membrane sensors, based on two new Schiff's bases 1,3-diphenylpropane-1,3-diylidenebis(azan-1-ylidene)diphenol (M 1 ) and N,N'-bis(pyridoxylideneiminato) ethylene (M 2 ) have been developed and studied. The sensor having membrane composition of PVC: o-NPOE: ionophore (M 1 ): NaTPB (w/w; mg) of 150: 300: 8: 5 showed best performances in comparison to M 2 based membranes. The sensor based on (M 1 ) exhibits the working concentration range 1.0 x 10 -8 to 1.0 x 10 -2 M with a detection limit of 5.0 x 10 -9 M and a Nernstian slope 20.0 ± 0.3 mV decade -1 of activity. It exhibited a quick response time as <8 s and its potential responses were pH independent across the range of 3.5-8.5.The influence of the membrane composition and possible interfering ions have also been investigated on the response properties of the electrode. The sensor has been found to work satisfactorily in partially non-aqueous media up to 15% (v/v) content of methanol, ethanol or acetonitrile and could be used for a period of 3 months. The selectivity coefficients determined by using fixed interference method (FIM) indicate high selectivity for praseodymium(III) ions over wide variety of other cations. To asses its analytical applicability the prepared sensor was successfully applied for determination of praseodymium(III) in spiked water samples.

  3. Physically transient photonics: random versus distributed feedback lasing based on nanoimprinted DNA.

    Science.gov (United States)

    Camposeo, Andrea; Del Carro, Pompilio; Persano, Luana; Cyprych, Konrad; Szukalski, Adam; Sznitko, Lech; Mysliwiec, Jaroslaw; Pisignano, Dario

    2014-10-28

    Room-temperature nanoimprinted, DNA-based distributed feedback (DFB) laser operation at 605 nm is reported. The laser is made of a pure DNA host matrix doped with gain dyes. At high excitation densities, the emission of the untextured dye-doped DNA films is characterized by a broad emission peak with an overall line width of 12 nm and superimposed narrow peaks, characteristic of random lasing. Moreover, direct patterning of the DNA films is demonstrated with a resolution down to 100 nm, enabling the realization of both surface-emitting and edge-emitting DFB lasers with a typical line width of <0.3 nm. The resulting emission is polarized, with a ratio between the TE- and TM-polarized intensities exceeding 30. In addition, the nanopatterned devices dissolve in water within less than 2 min. These results demonstrate the possibility of realizing various physically transient nanophotonics and laser architectures, including random lasing and nanoimprinted devices, based on natural biopolymers.

  4. Synchronization of random bit generators based on coupled chaotic lasers and application to cryptography.

    Science.gov (United States)

    Kanter, Ido; Butkovski, Maria; Peleg, Yitzhak; Zigzag, Meital; Aviad, Yaara; Reidler, Igor; Rosenbluh, Michael; Kinzel, Wolfgang

    2010-08-16

    Random bit generators (RBGs) constitute an important tool in cryptography, stochastic simulations and secure communications. The later in particular has some difficult requirements: high generation rate of unpredictable bit strings and secure key-exchange protocols over public channels. Deterministic algorithms generate pseudo-random number sequences at high rates, however, their unpredictability is limited by the very nature of their deterministic origin. Recently, physical RBGs based on chaotic semiconductor lasers were shown to exceed Gbit/s rates. Whether secure synchronization of two high rate physical RBGs is possible remains an open question. Here we propose a method, whereby two fast RBGs based on mutually coupled chaotic lasers, are synchronized. Using information theoretic analysis we demonstrate security against a powerful computational eavesdropper, capable of noiseless amplification, where all parameters are publicly known. The method is also extended to secure synchronization of a small network of three RBGs.

  5. Convergence analysis for Latin-hypercube lattice-sample selection strategies for 3D correlated random hydraulic-conductivity fields

    OpenAIRE

    Simuta-Champo, R.; Herrera-Zamarrón, G. S.

    2010-01-01

    The Monte Carlo technique provides a natural method for evaluating uncertainties. The uncertainty is represented by a probability distribution or by related quantities such as statistical moments. When the groundwater flow and transport governing equations are solved and the hydraulic conductivity field is treated as a random spatial function, the hydraulic head, velocities and concentrations also become random spatial functions. When that is the case, for the stochastic simulation of groundw...

  6. BIM-Based Decision Support System for Material Selection Based on Supplier Rating

    Directory of Open Access Journals (Sweden)

    Abiola Akanmu

    2015-12-01

    Full Text Available Material selection is a delicate process, typically hinged on a number of factors which can be either cost or environmental related. This process becomes more complicated when designers are faced with several material options of building elements and each option can be supplied by different suppliers whose selection criteria may affect the budgetary and environmental requirements of the project. This paper presents the development of a decision support system based on the integration of building information models, a modified harmony search algorithm and supplier performance rating. The system is capable of producing the cost and environmental implications of different material combinations or building designs. A case study is presented to illustrate the functionality of the developed system.

  7. Making evidence-based selections of influenza vaccines

    OpenAIRE

    Childress, Billy-Clyde; Montney, Joshua D; Albro, Elise A

    2014-01-01

    Years ago, intramuscular influenza vaccines were the only option for those who wanted to arm themselves against the flu. Today there are alternatives, including intradermal injections and intranasal sprays. In order to select the right influenza vaccine for their patients, pharmacists, and other healthcare professionals must have a basic understanding of the immune system. Influenza vaccines elicit different levels of immune response involving innate and adaptive immunity, which are critical ...

  8. Neural bases of selective attention in action video game players

    OpenAIRE

    Bavelier, D; Achtman, RL; Mani, M; Föcker, J

    2011-01-01

    Over the past few years, the very act of playing action video games has been shown to enhance several different aspects of visual selective attention. Yet little is known about the neural mechanisms that mediate such attentional benefits. A review of the aspects of attention enhanced in action game players suggests there are changes in the mechanisms that control attention allocation and its efficiency (Hubert-Wallander et al., 2010). The present study used brain imaging to test this hypothes...

  9. Thermal behavior for a nanoscale two ferromagnetic phase system based on random anisotropy model

    International Nuclear Information System (INIS)

    Muraca, D.; Sanchez, F.H.; Pampillo, L.G.; Saccone, F.D.

    2010-01-01

    Advances in theory that explain the magnetic behavior as function of temperature for two phase nanocrystalline soft magnetic materials are presented. The theory developed is based on the well known random anisotropy model, which includes the crystalline exchange stiffness and anisotropy energies in both amorphous and crystalline phases. The phenomenological behavior of the coercivity was obtained in the temperature range between the amorphous phase Curie temperature and the crystalline phase one.

  10. Post-stratification based on a choice of a randomization device

    Directory of Open Access Journals (Sweden)

    Sarjinder Singh

    2014-06-01

    Full Text Available In this paper, we use the idea of post-stratification based on the respondents’ choice of a particular randomization device in order to estimate the population proportion of a sensitive characteristic. The proposed idea gives full freedom to the respondents and is expected to result in greater cooperation from them as well as to provide some increase in the relative efficiency of the newly proposed estimator.

  11. Computer-Based Cognitive Training for Mild Cognitive Impairment: Results from a Pilot Randomized, Controlled Trial

    OpenAIRE

    Barnes, Deborah E.; Yaffe, Kristine; Belfor, Nataliya; Jagust, William J.; DeCarli, Charles; Reed, Bruce R.; Kramer, Joel H.

    2009-01-01

    We performed a pilot randomized, controlled trial of intensive, computer-based cognitive training in 47 subjects with mild cognitive impairment (MCI). The intervention group performed exercises specifically designed to improve auditory processing speed and accuracy for 100 minutes/day, 5 days/week for 6 weeks; the control group performed more passive computer activities (reading, listening, visuospatial game) for similar amounts of time. Subjects had a mean age of 74 years and 60% were men; 7...

  12. The Effectiveness of School-Based Nutritional Education Program among Obese Adolescents: A Randomized Controlled Study

    OpenAIRE

    In-Iw, Supinya; Saetae, Tridsanun; Manaboriboon, Boonying

    2012-01-01

    The purpose of the study was to determine the change in body weight and body mass index (BMI), as well as diet behaviors at 4 months after intervention between obese adolescent girls who participated in the school-based nutritional education program, addressed by pediatrician, compared to those who attended regular nutritional class. Methods. 49 obese girls were recruited from a secondary school. Those, were randomized into 2 groups of intervention and control. The intensive interactive nutri...

  13. Reducing procrastination using a smartphone-based treatment program: A randomized controlled pilot study

    OpenAIRE

    Christian Aljoscha Lukas; Matthias Berking

    2018-01-01

    Background: Procrastination affects a large number of individuals and is associated with significant mental health problems. Despite the deleterious consequences individuals afflicted with procrastination have to bear, there is a surprising paucity of well-researched treatments for procrastination. To fill this gap, this study evaluated the efficacy of an easy-to-use smartphone-based treatment for procrastination. Method: N=31 individuals with heightened procrastination scores were randomly a...

  14. Mindfulness-Based Cognitive Therapy as a Treatment for Chronic Tinnitus: A Randomized Controlled Trial

    OpenAIRE

    McKenna, L.; Marks, E. M.; Hallsworth, C. A.; Schaette, R.

    2017-01-01

    BACKGROUND: Tinnitus is experienced by up to 15% of the population and can lead to significant disability and distress. There is rarely a medical or surgical target and psychological therapies are recommended. We investigated whether mindfulness-based cognitive therapy (MBCT) could offer an effective new therapy for tinnitus. METHODS: This single-site randomized controlled trial compared MBCT to intensive relaxation training (RT) for chronic, distressing tinnitus in adults. Both treatments in...

  15. Selective recognition of Pr3+ based on fluorescence enhancement sensor

    International Nuclear Information System (INIS)

    Ganjali, M.R.; Hosseini, M.; Ghafarloo, A.; Khoobi, M.; Faridbod, F.; Shafiee, A.; Norouzi, P.

    2013-01-01

    (E)-2-(1-(4-hydroxy-2-oxo-2H-chromen-3-yl)ethylidene) hydrazinecarbothioamide (L) has been used to detect trace amounts of praseodymium ion in acetonitrile–water solution (MeCN/H 2 O) by fluorescence spectroscopy. The fluorescent probe undergoes fluorescent emission intensity enhancement upon binding to Pr 3+ ions in MeCN/H 2 O (9/1:v/v) solution. The fluorescence enhancement of L is attributed to a 1:1 complex formation between L and Pr 3+ , which has been utilized as the basis for selective detection of Pr 3+ . The sensor can be applied to the quantification of praseodymium ion with a linear range of 1.6 × 10 −7 to 1.0 × 10 −5 M. The limit of detection was 8.3 × 10 −8 M. The sensor exhibits high selectivity toward praseodymium ions in comparison with common metal ions. The proposed fluorescent sensor was successfully used for determination of Pr 3+ in water samples. - Highlights: • A new fluorescent sensor is introduced as a selective probe for Pr 3+ detection. • Fluorescent intensity of the chemical probe enhances upon binding to Pr 3+ ion. • The sensor can be used for Pr 3+ determination in the range of 1.6 × 10 −7 –1.0 × 10 −5 M

  16. Multilevel selection in a resource-based model

    Science.gov (United States)

    Ferreira, Fernando Fagundes; Campos, Paulo R. A.

    2013-07-01

    In the present work we investigate the emergence of cooperation in a multilevel selection model that assumes limiting resources. Following the work by R. J. Requejo and J. Camacho [Phys. Rev. Lett.0031-900710.1103/PhysRevLett.108.038701 108, 038701 (2012)], the interaction among individuals is initially ruled by a prisoner's dilemma (PD) game. The payoff matrix may change, influenced by the resource availability, and hence may also evolve to a non-PD game. Furthermore, one assumes that the population is divided into groups, whose local dynamics is driven by the payoff matrix, whereas an intergroup competition results from the nonuniformity of the growth rate of groups. We study the probability that a single cooperator can invade and establish in a population initially dominated by defectors. Cooperation is strongly favored when group sizes are small. We observe the existence of a critical group size beyond which cooperation becomes counterselected. Although the critical size depends on the parameters of the model, it is seen that a saturation value for the critical group size is achieved. The results conform to the thought that the evolutionary history of life repeatedly involved transitions from smaller selective units to larger selective units.

  17. Self-Powered Random Number Generator Based on Coupled Triboelectric and Electrostatic Induction Effects at the Liquid-Dielectric Interface.

    Science.gov (United States)

    Yu, Aifang; Chen, Xiangyu; Cui, Haotian; Chen, Libo; Luo, Jianjun; Tang, Wei; Peng, Mingzeng; Zhang, Yang; Zhai, Junyi; Wang, Zhong Lin

    2016-12-27

    Modern cryptography increasingly employs random numbers generated from physical sources in lieu of conventional software-based pseudorandom numbers, primarily owing to the great demand of unpredictable, indecipherable cryptographic keys from true random numbers for information security. Thus, far, the sole demonstration of true random numbers has been generated through thermal noise and/or quantum effects, which suffers from expensive and complex equipment. In this paper, we demonstrate a method for self-powered creation of true random numbers by using triboelectric technology to collect random signals from nature. This random number generator based on coupled triboelectric and electrostatic induction effects at the liquid-dielectric interface includes an elaborately designed triboelectric generator (TENG) with an irregular grating structure, an electronic-optical device, and an optical-electronic device. The random characteristics of raindrops are harvested through TENG and consequently transformed and converted by electronic-optical device and an optical-electronic device with a nonlinear characteristic. The cooperation of the mechanical, electrical, and optical signals ensures that the generator possesses complex nonlinear input-output behavior and contributes to increased randomness. The random number sequences are deduced from final electrical signals received by an optical-electronic device using a familiar algorithm. These obtained random number sequences exhibit good statistical characteristics, unpredictability, and unrepeatability. Our study supplies a simple, practical, and effective method to generate true random numbers, which can be widely used in cryptographic protocols, digital signatures, authentication, identification, and other information security fields.

  18. Affinity selection of Nipah and Hendra virus-related vaccine candidates from a complex random peptide library displayed on bacteriophage virus-like particles

    Energy Technology Data Exchange (ETDEWEB)

    Peabody, David S.; Chackerian, Bryce; Ashley, Carlee; Carnes, Eric; Negrete, Oscar

    2017-01-24

    The invention relates to virus-like particles of bacteriophage MS2 (MS2 VLPs) displaying peptide epitopes or peptide mimics of epitopes of Nipah Virus envelope glycoprotein that elicit an immune response against Nipah Virus upon vaccination of humans or animals. Affinity selection on Nipah Virus-neutralizing monoclonal antibodies using random sequence peptide libraries on MS2 VLPs selected peptides with sequence similarity to peptide sequences found within the envelope glycoprotein of Nipah itself, thus identifying the epitopes the antibodies recognize. The selected peptide sequences themselves are not necessarily identical in all respects to a sequence within Nipah Virus glycoprotein, and therefore may be referred to as epitope mimics VLPs displaying these epitope mimics can serve as vaccine. On the other hand, display of the corresponding wild-type sequence derived from Nipah Virus and corresponding to the epitope mapped by affinity selection, may also be used as a vaccine.

  19. Recruitment strategies should not be randomly selected: empirically improving recruitment success and diversity in developmental psychology research

    Science.gov (United States)

    Sugden, Nicole A.; Moulson, Margaret C.

    2015-01-01

    Psychological and developmental research have been critiqued for the lack of diversity of research samples. Because differences in culture, race, and ethnicity can influence participant behavior, limited diversity limits the generalizability of the findings. These differences may also impact how participants behave in response to recruitment attempts, which suggests that recruitment itself may be leveraged to increase sample diversity. The goal of the current study was to determine what factors, within a recruitment interaction, could be leveraged to increase success and diversity when recruiting families with children for developmental research. Study 1 found three factors influenced success: (1) recruitment was more successful when other potential participants were also interested (i.e., recruiters were busy), (2) recruiters of particular races were more successful than recruiters of other races, and (3) differences in success were related to what the recruiter said to engage the potential participant (i.e., the script). The latter two factors interacted, suggesting some recruiters were using less optimal scripts. To improve success rates, study 2 randomly assigned scripts to recruiters and encouraged them to recruit more vigorously during busy periods. Study 2 found that two factors influenced success: (1) some scripts were more successful than others and (2) we were more successful at recruiting non-White potential participants than White participants. These two interacted, with some scripts being more successful with White and other scripts being more successful with non-White families. This intervention significantly increased recruitment success rate by 8.1% and the overall number of families recruited by 15.3%. These findings reveal that empirically evaluating and tailoring recruitment efforts based on the most successful strategies is effective in boosting diversity through increased participation of children from non-White families. PMID:25972829

  20. TU-CD-BRA-05: Atlas Selection for Multi-Atlas-Based Image Segmentation Using Surrogate Modeling

    International Nuclear Information System (INIS)

    Zhao, T; Ruan, D

    2015-01-01

    Purpose: The growing size and heterogeneity in training atlas necessitates sophisticated schemes to identify only the most relevant atlases for the specific multi-atlas-based image segmentation problem. This study aims to develop a model to infer the inaccessible oracle geometric relevance metric from surrogate image similarity metrics, and based on such model, provide guidance to atlas selection in multi-atlas-based image segmentation. Methods: We relate the oracle geometric relevance metric in label space to the surrogate metric in image space, by a monotonically non-decreasing function with additive random perturbations. Subsequently, a surrogate’s ability to prognosticate the oracle order for atlas subset selection is quantified probabilistically. Finally, important insights and guidance are provided for the design of fusion set size, balancing the competing demands to include the most relevant atlases and to exclude the most irrelevant ones. A systematic solution is derived based on an optimization framework. Model verification and performance assessment is performed based on clinical prostate MR images. Results: The proposed surrogate model was exemplified by a linear map with normally distributed perturbation, and verified with several commonly-used surrogates, including MSD, NCC and (N)MI. The derived behaviors of different surrogates in atlas selection and their corresponding performance in ultimate label estimate were validated. The performance of NCC and (N)MI was similarly superior to MSD, with a 10% higher atlas selection probability and a segmentation performance increase in DSC by 0.10 with the first and third quartiles of (0.83, 0.89), compared to (0.81, 0.89). The derived optimal fusion set size, valued at 7/8/8/7 for MSD/NCC/MI/NMI, agreed well with the appropriate range [4, 9] from empirical observation. Conclusion: This work has developed an efficacious probabilistic model to characterize the image-based surrogate metric on atlas selection

  1. An efficient ERP-based brain-computer interface using random set presentation and face familiarity.

    Directory of Open Access Journals (Sweden)

    Seul-Ki Yeom

    Full Text Available Event-related potential (ERP-based P300 spellers are commonly used in the field of brain-computer interfaces as an alternative channel of communication for people with severe neuro-muscular diseases. This study introduces a novel P300 based brain-computer interface (BCI stimulus paradigm using a random set presentation pattern and exploiting the effects of face familiarity. The effect of face familiarity is widely studied in the cognitive neurosciences and has recently been addressed for the purpose of BCI. In this study we compare P300-based BCI performances of a conventional row-column (RC-based paradigm with our approach that combines a random set presentation paradigm with (non- self-face stimuli. Our experimental results indicate stronger deflections of the ERPs in response to face stimuli, which are further enhanced when using the self-face images, and thereby improving P300-based spelling performance. This lead to a significant reduction of stimulus sequences required for correct character classification. These findings demonstrate a promising new approach for improving the speed and thus fluency of BCI-enhanced communication with the widely used P300-based BCI setup.

  2. Conditional Mutual Information Based Feature Selection for Classification Task

    Czech Academy of Sciences Publication Activity Database

    Novovičová, Jana; Somol, Petr; Haindl, Michal; Pudil, Pavel

    2007-01-01

    Roč. 45, č. 4756 (2007), s. 417-426 ISSN 0302-9743 R&D Projects: GA MŠk 1M0572; GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Pattern classification * feature selection * conditional mutual information * text categorization Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.402, year: 2005

  3. Fuzzy Investment Portfolio Selection Models Based on Interval Analysis Approach

    Directory of Open Access Journals (Sweden)

    Haifeng Guo

    2012-01-01

    Full Text Available This paper employs fuzzy set theory to solve the unintuitive problem of the Markowitz mean-variance (MV portfolio model and extend it to a fuzzy investment portfolio selection model. Our model establishes intervals for expected returns and risk preference, which can take into account investors' different investment appetite and thus can find the optimal resolution for each interval. In the empirical part, we test this model in Chinese stocks investment and find that this model can fulfill different kinds of investors’ objectives. Finally, investment risk can be decreased when we add investment limit to each stock in the portfolio, which indicates our model is useful in practice.

  4. Portfolio Selection Based on Distance between Fuzzy Variables

    Directory of Open Access Journals (Sweden)

    Weiyi Qian

    2014-01-01

    Full Text Available This paper researches portfolio selection problem in fuzzy environment. We introduce a new simple method in which the distance between fuzzy variables is used to measure the divergence of fuzzy investment return from a prior one. Firstly, two new mathematical models are proposed by expressing divergence as distance, investment return as expected value, and risk as variance and semivariance, respectively. Secondly, the crisp forms of the new models are also provided for different types of fuzzy variables. Finally, several numerical examples are given to illustrate the effectiveness of the proposed approach.

  5. School-Based Smoking Prevention Programs for Middle School Students in Nowshahr- Iran: a Randomized Controlled Trial

    Directory of Open Access Journals (Sweden)

    Maryam Khazaee-Pool

    2016-11-01

    Full Text Available Background: Smoking among youths is a main public health concern, and detecting predictors of smoking is essential for designing preventive programs. Any interventional program should plan with highlighting on behavioral change models and based on operative interventional program. So, this study aimed to investigate school-based smoking prevention programs for middle school students in Nowshahr, Iran.Materials and Methods: A quasi-experimental study was performed with 280 male students aged 15-17 years selected by multistage sampling. For this purpose, 6 middle schools were randomly recruited from male students in Nowshahr- Iran. Then, 140 students were randomly chosen for each the experimental and the control groups. After pretest, educational program based on Health Belief Model were performed in experimental group. Also, post-test was applied four months after interventional program in both experimental and control group.Results: Based on the results, the prevalence of smoking was higher at age 14 old in both experimental (38.7% and control (30 % groups. About 35% of participants in the experimental group and 33.6% in control group had smoker father. Additionally, 10% in experimental group and 7.8% in control group had smoker mother. Most main cause for smoking in 57.9% of the experimental group and 52.63% of the control group was reducing anxiety. Results also shown that there was a significant difference between students in the experimental and control groups after performing educational program in the mean scores of perceived susceptibility, perceived severity, perceived benefits, perceived barriers, perceived self-efficacy, and preventive behaviors of smoking (P < 0.05.Conclusion: By performing educational program, it was found that the prevalence of cigarette smoking was decreased in the intervention group. So, with a better understanding of factors affecting on this complex behavior (cigarette smoking, it can be a valuable phase to

  6. Dynamic Educational e-Content Selection Using Multiple Criteria in Web-Based Personalized Learning Environments.

    Science.gov (United States)

    Manouselis, Nikos; Sampson, Demetrios

    This paper focuses on the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects' educational description. In this way, selection of…

  7. Supplier selection based on improved MOGA and its application in nuclear power equipment procurement

    International Nuclear Information System (INIS)

    Yan Zhaojun; Wang Dezhong; Zhou Lei

    2007-01-01

    Considering the fact that there are few objective and available methods supporting the supplier selection in nuclear power equipment purchasing process, a supplier selection method based on improved multi-objective genetic algorithm (MOGA) is proposed. The simulation results demonstrate the effectiveness and efficiency of this method for the supplier selection in nuclear power equipment procurement process. (authors)

  8. Improved methods in Agrobacterium-mediated transformation of almond using positive (mannose/pmi) or negative (kanamycin resistance) selection-based protocols.

    Science.gov (United States)

    Ramesh, Sunita A; Kaiser, Brent N; Franks, Tricia; Collins, Graham; Sedgley, Margaret

    2006-08-01

    A protocol for Agrobacterium-mediated transformation with either kanamycin or mannose selection was developed for leaf explants of the cultivar Prunus dulcis cv. Ne Plus Ultra. Regenerating shoots were selected on medium containing 15 muM kanamycin (negative selection), while in the positive selection strategy, shoots were selected on 2.5 g/l mannose supplemented with 15 g/l sucrose. Transformation efficiencies based on PCR analysis of individual putative transformed shoots from independent lines relative to the initial numbers of leaf explants tested were 5.6% for kanamycin/nptII and 6.8% for mannose/pmi selection, respectively. Southern blot analysis on six randomly chosen PCR-positive shoots confirmed the presence of the nptII transgene in each, and five randomly chosen lines identified to contain the pmi transgene by PCR showed positive hybridisation to a pmi DNA probe. The positive (mannose/pmi) and the negative (kanamycin) selection protocols used in this study have greatly improved transformation efficiency in almond, which were confirmed with PCR and Southern blot. This study also demonstrates that in almond the mannose/pmi selection protocol is appropriate and can result in higher transformation efficiencies over that of kanamycin/nptII selection protocols.

  9. Evidence-based recommendations for analgesic efficacy to treat pain of endodontic origin: A systematic review of randomized controlled trials.

    Science.gov (United States)

    Aminoshariae, Anita; Kulild, James C; Donaldson, Mark; Hersh, Elliot V

    2016-10-01

    The purpose of this investigation was to identify evidence-based clinical trials to aid dental clinicians in establishing the efficacy for recommending or prescribing analgesics for pain of endodontic origin. The authors prepared and registered a protocol on PROSPERO and conducted electronic searches in MEDLINE, Scopus, the Cochrane Library, and ClinicalTrials.gov. In addition, the authors manually searched the bibliographies of all relevant articles, the gray literature, and textbooks for randomized controlled trials. Two authors selected the relevant articles independently. There were no disagreements between the authors. The authors analyzed 27 randomized, placebo-controlled trials. The authors divided the studies into 2 groups: preoperative and postoperative analgesic treatments. There was moderate evidence to support the use of steroids for patients with symptomatic irreversible pulpitis. Also, there was moderate evidence to support nonsteroidal anti-inflammatory drugs (NSAIDs) preoperatively or postoperatively to control pain of endodontic origin. When NSAIDs were not effective, a combination of NSAIDs with acetaminophen, tramadol, or an opioid appeared beneficial. NSAIDs should be considered as the drugs of choice to alleviate or minimize pain of endodontic origin if there are no contraindications for the patient to ingest an NSAID. In situations in which NSAIDs alone are not effective, the combination of an NSAID with acetaminophen or a centrally acting drug is recommended. Steroids appear effective in irreversible pulpitis. Copyright © 2016 American Dental Association. Published by Elsevier Inc. All rights reserved.

  10. Samarium (III Selective Membrane Sensor Based on Tin (IV Boratophosphate

    Directory of Open Access Journals (Sweden)

    Ashok S. K. Kumar

    2004-08-01

    Full Text Available Abstract: A number of Sm (III selective membranes of varying compositions using tin (IV boratophosphate as electroactive material were prepared. Polyvinyl chloride, polystyrene and epoxy resin were used as binding materials. Membrane having composition of 40% exchanger and 60% epoxy resin exhibited best performance. This membrane worked well over a wide concentration range of 1x10-5M to 1x10-1 M of samarium ions with a Super-Nernstian slope of 40 mV/decade. It has a fast response time of less than 10 seconds and can be used for at least six months without any considerable divergence in potentials. The proposed sensor revealed good selectivities with respect to alkali, alkaline earth, some transition and rare earth metal ions and can be used in the pH range of 4.0-10.0. It was used as an indicator electrode in the potentiometric titration of Sm (III ions against EDTA. Effect of internal solution was studied and the electrode was successfully used in non-aqueous media, too.

  11. A mindfulness-based stress prevention training for medical students (MediMind): study protocol for a randomized controlled trial.

    Science.gov (United States)

    Kuhlmann, Sophie Merle; Bürger, Arne; Esser, Günter; Hammerle, Florian

    2015-02-08

    Medical training is very demanding and associated with a high prevalence of psychological distress. Compared to the general population, medical students are at a greater risk of developing a psychological disorder. Various attempts of stress management training in medical school have achieved positive results on minimizing psychological distress; however, there are often limitations. Therefore, the use of a rigorous scientific method is needed. The present study protocol describes a randomized controlled trial to examine the effectiveness of a specifically developed mindfulness-based stress prevention training for medical students that includes selected elements of cognitive behavioral strategies (MediMind). This study protocol presents a prospective randomized controlled trial, involving four assessment time points: baseline, post-intervention, one-year follow-up and five-year follow-up. The aims include evaluating the effect on stress, coping, psychological morbidity and personality traits with validated measures. Participants are allocated randomly to one of three conditions: MediMind, Autogenic Training or control group. Eligible participants are medical or dental students in the second or eighth semester of a German university. They form a population of approximately 420 students in each academic term. A final total sample size of 126 (at five-year follow-up) is targeted. The trainings (MediMind and Autogenic Training) comprise five weekly sessions lasting 90 minutes each. MediMind will be offered to participants of the control group once the five-year follow-up is completed. The allotment is randomized with a stratified allocation ratio by course of studies, semester, and gender. After descriptive statistics have been evaluated, inferential statistical analysis will be carried out with a repeated measures ANOVA-design with interactions between time and group. Effect sizes will be calculated using partial η-square values. Potential limitations of this study

  12. Reporting of Positive Results in Randomized Controlled Trials of Mindfulness-Based Mental Health Interventions.

    Directory of Open Access Journals (Sweden)

    Stephanie Coronado-Montoya

    Full Text Available A large proportion of mindfulness-based therapy trials report statistically significant results, even in the context of very low statistical power. The objective of the present study was to characterize the reporting of "positive" results in randomized controlled trials of mindfulness-based therapy. We also assessed mindfulness-based therapy trial registrations for indications of possible reporting bias and reviewed recent systematic reviews and meta-analyses to determine whether reporting biases were identified.CINAHL, Cochrane CENTRAL, EMBASE, ISI, MEDLINE, PsycInfo, and SCOPUS databases were searched for randomized controlled trials of mindfulness-based therapy. The number of positive trials was described and compared to the number that might be expected if mindfulness-based therapy were similarly effective compared to individual therapy for depression. Trial registries were searched for mindfulness-based therapy registrations. CINAHL, Cochrane CENTRAL, EMBASE, ISI, MEDLINE, PsycInfo, and SCOPUS were also searched for mindfulness-based therapy systematic reviews and meta-analyses.108 (87% of 124 published trials reported ≥1 positive outcome in the abstract, and 109 (88% concluded that mindfulness-based therapy was effective, 1.6 times greater than the expected number of positive trials based on effect size d = 0.55 (expected number positive trials = 65.7. Of 21 trial registrations, 13 (62% remained unpublished 30 months post-trial completion. No trial registrations adequately specified a single primary outcome measure with time of assessment. None of 36 systematic reviews and meta-analyses concluded that effect estimates were overestimated due to reporting biases.The proportion of mindfulness-based therapy trials with statistically significant results may overstate what would occur in practice.

  13. An effective approach to attenuate random noise based on compressive sensing and curvelet transform

    International Nuclear Information System (INIS)

    Liu, Wei; Cao, Siyuan; Zu, Shaohuan; Chen, Yangkang

    2016-01-01

    Random noise attenuation is an important step in seismic data processing. In this paper, we propose a novel denoising approach based on compressive sensing and the curvelet transform. We formulate the random noise attenuation problem as an L _1 norm regularized optimization problem. We propose to use the curvelet transform as the sparse transform in the optimization problem to regularize the sparse coefficients in order to separate signal and noise and to use the gradient projection for sparse reconstruction (GPSR) algorithm to solve the formulated optimization problem with an easy implementation and a fast convergence. We tested the performance of our proposed approach on both synthetic and field seismic data. Numerical results show that the proposed approach can effectively suppress the distortion near the edge of seismic events during the noise attenuation process and has high computational efficiency compared with the traditional curvelet thresholding and iterative soft thresholding based denoising methods. Besides, compared with f-x deconvolution, the proposed denoising method is capable of eliminating the random noise more effectively while preserving more useful signals. (paper)

  14. Threshold-Based Random Charging Scheme for Decentralized PEV Charging Operation in a Smart Grid.

    Science.gov (United States)

    Kwon, Ojin; Kim, Pilkee; Yoon, Yong-Jin

    2016-12-26

    Smart grids have been introduced to replace conventional power distribution systems without real time monitoring for accommodating the future market penetration of plug-in electric vehicles (PEVs). When a large number of PEVs require simultaneous battery charging, charging coordination techniques have become one of the most critical factors to optimize the PEV charging performance and the conventional distribution system. In this case, considerable computational complexity of a central controller and exchange of real time information among PEVs may occur. To alleviate these problems, a novel threshold-based random charging (TBRC) operation for a decentralized charging system is proposed. Using PEV charging thresholds and random access rates, the PEVs themselves can participate in the charging requests. As PEVs with a high battery state do not transmit the charging requests to the central controller, the complexity of the central controller decreases due to the reduction of the charging requests. In addition, both the charging threshold and the random access rate are statistically calculated based on the average of supply power of the PEV charging system that do not require a real time update. By using the proposed TBRC with a tolerable PEV charging degradation, a 51% reduction of the PEV charging requests is achieved.

  15. Assessing the predictive capability of randomized tree-based ensembles in streamflow modelling

    Science.gov (United States)

    Galelli, S.; Castelletti, A.

    2013-07-01

    Combining randomization methods with ensemble prediction is emerging as an effective option to balance accuracy and computational efficiency in data-driven modelling. In this paper, we investigate the prediction capability of extremely randomized trees (Extra-Trees), in terms of accuracy, explanation ability and computational efficiency, in a streamflow modelling exercise. Extra-Trees are a totally randomized tree-based ensemble method that (i) alleviates the poor generalisation property and tendency to overfitting of traditional standalone decision trees (e.g. CART); (ii) is computationally efficient; and, (iii) allows to infer the relative importance of the input variables, which might help in the ex-post physical interpretation of the model. The Extra-Trees potential is analysed on two real-world case studies - Marina catchment (Singapore) and Canning River (Western Australia) - representing two different morphoclimatic contexts. The evaluation is performed against other tree-based methods (CART and M5) and parametric data-driven approaches (ANNs and multiple linear regression). Results show that Extra-Trees perform comparatively well to the best of the benchmarks (i.e. M5) in both the watersheds, while outperforming the other approaches in terms of computational requirement when adopted on large datasets. In addition, the ranking of the input variable provided can be given a physically meaningful interpretation.

  16. Mapping Deforestation in North Korea Using Phenology-Based Multi-Index and Random Forest

    Directory of Open Access Journals (Sweden)

    Yihua Jin

    2016-12-01

    Full Text Available Phenology-based multi-index with the random forest (RF algorithm can be used to overcome the shortcomings of traditional deforestation mapping that involves pixel-based classification, such as ISODATA or decision trees, and single images. The purpose of this study was to investigate methods to identify specific types of deforestation in North Korea, and to increase the accuracy of classification, using phenological characteristics extracted with multi-index and random forest algorithms. The mapping of deforestation area based on RF was carried out by merging phenology-based multi-indices (i.e., normalized difference vegetation index (NDVI, normalized difference water index (NDWI, and normalized difference soil index (NDSI derived from MODIS (Moderate Resolution Imaging Spectroradiometer products and topographical variables. Our results showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87. In particular, for forest and farm land categories with similar phenological characteristic (e.g., paddy, plateau vegetation, unstocked forest, hillside field, this approach improved the classification accuracy in comparison with pixel-based methods and other classes. The deforestation types were identified by incorporating point data from high-resolution imagery, outcomes of image classification, and slope data. Our study demonstrated that the proposed methodology could be used for deciding on the restoration priority and monitoring the expansion of deforestation areas.

  17. Controlling Chronic Diseases Through Evidence-Based Decision Making: A Group-Randomized Trial.

    Science.gov (United States)

    Brownson, Ross C; Allen, Peg; Jacob, Rebekah R; deRuyter, Anna; Lakshman, Meenakshi; Reis, Rodrigo S; Yan, Yan

    2017-11-30

    Although practitioners in state health departments are ideally positioned to implement evidence-based interventions, few studies have examined how to build their capacity to do so. The objective of this study was to explore how to increase the use of evidence-based decision-making processes at both the individual and organization levels. We conducted a 2-arm, group-randomized trial with baseline data collection and follow-up at 18 to 24 months. Twelve state health departments were paired and randomly assigned to intervention or control condition. In the 6 intervention states, a multiday training on evidence-based decision making was conducted from March 2014 through March 2015 along with a set of supplemental capacity-building activities. Individual-level outcomes were evidence-based decision making skills of public health practitioners; organization-level outcomes were access to research evidence and participatory decision making. Mixed analysis of covariance models was used to evaluate the intervention effect by accounting for the cluster randomized trial design. Analysis was performed from March through May 2017. Participation 18 to 24 months after initial training was 73.5%. In mixed models adjusted for participant and state characteristics, the intervention group improved significantly in the overall skill gap (P = .01) and in 6 skill areas. Among the 4 organizational variables, only access to evidence and skilled staff showed an intervention effect (P = .04). Tailored and active strategies are needed to build capacity at the individual and organization levels for evidence-based decision making. Our study suggests several dissemination interventions for consideration by leaders seeking to improve public health practice.

  18. Impulse attack-free four random phase mask encryption based on a 4-f optical system.

    Science.gov (United States)

    Kumar, Pramod; Joseph, Joby; Singh, Kehar

    2009-04-20

    Optical encryption methods based on double random phase encryption (DRPE) have been shown to be vulnerable to different types of attacks. The Fourier plane random phase mask (RPM), which is the most important key, can be cracked with a single impulse function attack. Such an attack is viable because the Fourier transform of a delta function is a unity function. Formation of a unity function can be avoided if RPMs are placed in front of both lenses in a 4-f optical setup, thereby protecting the DRPE from an impulse attack. We have performed numerical simulations to verify the proposed scheme. Resistance of this scheme is checked against the brute force and the impulse function attacks. The experimental results validate the feasibility of the scheme.

  19. A novel root-index based prioritized random access scheme for 5G cellular networks

    Directory of Open Access Journals (Sweden)

    Taehoon Kim

    2015-12-01

    Full Text Available Cellular networks will play an important role in realizing the newly emerging Internet-of-Everything (IoE. One of the challenging issues is to support the quality of service (QoS during the access phase, while accommodating a massive number of machine nodes. In this paper, we show a new paradigm of multiple access priorities in random access (RA procedure and propose a novel root-index based prioritized random access (RIPRA scheme that implicitly embeds the access priority in the root index of the RA preambles. The performance evaluation shows that the proposed RIPRA scheme can successfully support differentiated performance for different access priority levels, even though there exist a massive number of machine nodes.

  20. Research on electricity consumption forecast based on mutual information and random forests algorithm

    Science.gov (United States)

    Shi, Jing; Shi, Yunli; Tan, Jian; Zhu, Lei; Li, Hu

    2018-02-01

    Traditional power forecasting models cannot efficiently take various factors into account, neither to identify the relation factors. In this paper, the mutual information in information theory and the artificial intelligence random forests algorithm are introduced into the medium and long-term electricity demand prediction. Mutual information can identify the high relation factors based on the value of average mutual information between a variety of variables and electricity demand, different industries may be highly associated with different variables. The random forests algorithm was used for building the different industries forecasting models according to the different correlation factors. The data of electricity consumption in Jiangsu Province is taken as a practical example, and the above methods are compared with the methods without regard to mutual information and the industries. The simulation results show that the above method is scientific, effective, and can provide higher prediction accuracy.

  1. Study on Stationarity of Random Load Spectrum Based on the Special Road

    Science.gov (United States)

    Yan, Huawen; Zhang, Weigong; Wang, Dong

    2017-09-01

    In the special road quality assessment method, there is a method using a wheel force sensor, the essence of this method is collecting the load spectrum of the car to reflect the quality of road. According to the definition of stochastic process, it is easy to find that the load spectrum is a stochastic process. However, the analysis method and application range of different random processes are very different, especially in engineering practice, which will directly affect the design and development of the experiment. Therefore, determining the type of a random process has important practical significance. Based on the analysis of the digital characteristics of road load spectrum, this paper determines that the road load spectrum in this experiment belongs to a stationary stochastic process, paving the way for the follow-up modeling and feature extraction of the special road.

  2. Analysis in nuclear power accident emergency based on random network and particle swarm optimization

    International Nuclear Information System (INIS)

    Gong Dichen; Fang Fang; Ding Weicheng; Chen Zhi

    2014-01-01

    The GERT random network model of nuclear power accident emergency was built in this paper, and the intelligent computation was combined with the random network based on the analysis of Fukushima nuclear accident in Japan. The emergency process was divided into the series link and parallel link, and the parallel link was the part of series link. The overall allocation of resources was firstly optimized, and then the parallel link was analyzed. The effect of the resources for emergency used in different links was analyzed, and it was put forward that the corresponding particle velocity vector was limited under the condition of limited emergency resources. The resource-constrained particle swarm optimization was obtained by using velocity projection matrix to correct the motion of particles. The optimized allocation of resources in emergency process was obtained and the time consumption of nuclear power accident emergency was reduced. (authors)

  3. Random Access for Machine-Type Communication based on Bloom Filtering

    DEFF Research Database (Denmark)

    Pratas, Nuno; Stefanovic, Cedomir; Madueño, Germán Corrales

    2016-01-01

    utilizes the system resources more efficiently and achieves similar or lower latency of connection establishment in case of synchronous arrivals, compared to the variant of the LTE-A access protocol that is optimized for MTC traffic. A dividend of the proposed method is that allows the base station (BS......We present a random access method inspired on Bloom filters that is suited for Machine-Type Communications (MTC). Each accessing device sends a signature during the contention process. A signature is constructed using the Bloom filtering method and contains information on the device identity...... and the connection establishment cause. We instantiate the proposed method over the current LTE-A access protocol. However, the method is applicable to a more general class of random access protocols that use preambles or other reservation sequences, as expected to be the case in 5G systems. We show that our method...

  4. Chaotic Dynamical State Variables Selection Procedure Based Image Encryption Scheme

    Directory of Open Access Journals (Sweden)

    Zia Bashir

    2017-12-01

    Full Text Available Nowadays, in the modern digital era, the use of computer technologies such as smartphones, tablets and the Internet, as well as the enormous quantity of confidential information being converted into digital form have resulted in raised security issues. This, in turn, has led to rapid developments in cryptography, due to the imminent need for system security. Low-dimensional chaotic systems have low complexity and key space, yet they achieve high encryption speed. An image encryption scheme is proposed that, without compromising the security, uses reasonable resources. We introduced a chaotic dynamic state variables selection procedure (CDSVSP to use all state variables of a hyper-chaotic four-dimensional dynamical system. As a result, less iterations of the dynamical system are required, and resources are saved, thus making the algorithm fast and suitable for practical use. The simulation results of security and other miscellaneous tests demonstrate that the suggested algorithm excels at robustness, security and high speed encryption.

  5. Risk-based selection of SSCs at Peach Bottom

    International Nuclear Information System (INIS)

    Krueger, G.A.; Marie, A.J.

    1993-01-01

    The purpose of identifying risk significant systems, structures, and components (SSCS) that are within the scope of the maintenance rule is to bring a higher level of attention to a subset of those SSCS. These risk-significant SSCs will have specific performance criteria established for them, and failure to meet this performance criteria will result in establishing goals to ensure the necessary improvement in performance. The Peach Bottom individual plant examination (IPE) results were used to provide insights for the verification of proposed probabilistic risk assessment (PRA) methods set forth in the Industry Maintenance Guidelines for Implementation of the Maintenance Rule. The objective of reviewing the methods for selection of SSCs that are considered risk significant was to ensure the methods used are logical, reproducible, and can be consistently applied

  6. Nanoparticle array based optical frequency selective surfaces: theory and design.

    Science.gov (United States)

    Saeidi, Chiya; van der Weide, Daniel

    2013-07-01

    We demonstrate a synthesis procedure for designing a bandstop optical frequency selective surface (FSS) composed of nanoparticle (NP) elements. The proposed FSS uses two-dimensional (2-D) periodic arrays of NPs with subwavelength unit-cell dimensions. We derive equivalent circuit for a nanoparticle array (NPA) using the closed-form solution for a 2-D NPA excited by a plane wave in the limit of the dipole approximation, which includes contribution from both individual and collective plasmon modes. Using the extracted equivalent circuit, we demonstrate synthesis of an optical FSS using cascaded NPA layers as coupled resonators, which we validate with both circuit model and full-wave simulation for a third-order Butterworth bandstop prototype.

  7. Supplier Selection based on the Performance by using PROMETHEE Method

    Science.gov (United States)

    Sinaga, T. S.; Siregar, K.

    2017-03-01

    Generally, companies faced problem to identify vendors that can provide excellent service in availability raw material and on time delivery. The performance of suppliers in a company have to be monitored to ensure the availability to fulfill the company needs. This research is intended to explain how to assess suppliers to improve manufacturing performance. The criteria that considered in evaluating suppliers is criteria of Dickson. There are four main criteria which further split into seven sub-criteria, namely compliance with accuracy, consistency, on-time delivery, right quantity order, flexibility and negotiation, timely of order confirmation, and responsiveness. This research uses PROMETHEE methodology in assessing the supplier performances and obtaining a selected supplier as the best one that shown from the degree of alternative comparison preference between suppliers.

  8. Expected utility violations evolve under status-based selection mechanisms.

    Science.gov (United States)

    Dickson, Eric S

    2008-10-07

    The expected utility theory of decision making under uncertainty, a cornerstone of modern economics, assumes that humans linearly weight "utilities" for different possible outcomes by the probabilities with which these outcomes occur. Despite the theory's intuitive appeal, both from normative and from evolutionary perspectives, many experiments demonstrate systematic, though poorly understood, patterns of deviation from EU predictions. This paper offers a novel theoretical account of such patterns of deviation by demonstrating that EU violations can emerge from evolutionary selection when individual "status" affects inclusive fitness. In humans, battles for resources and social standing involve high-stakes decision making, and assortative mating ensures that status matters for fitness outcomes. The paper therefore proposes grounding the study of decision making under uncertainty in an evolutionary game-theoretic framework.

  9. A novel image encryption algorithm based on synchronized random bit generated in cascade-coupled chaotic semiconductor ring lasers

    Science.gov (United States)

    Li, Jiafu; Xiang, Shuiying; Wang, Haoning; Gong, Junkai; Wen, Aijun

    2018-03-01

    In this paper, a novel image encryption algorithm based on synchronization of physical random bit generated in a cascade-coupled semiconductor ring lasers (CCSRL) system is proposed, and the security analysis is performed. In both transmitter and receiver parts, the CCSRL system is a master-slave configuration consisting of a master semiconductor ring laser (M-SRL) with cross-feedback and a solitary SRL (S-SRL). The proposed image encryption algorithm includes image preprocessing based on conventional chaotic maps, pixel confusion based on control matrix extracted from physical random bit, and pixel diffusion based on random bit stream extracted from physical random bit. Firstly, the preprocessing method is used to eliminate the correlation between adjacent pixels. Secondly, physical random bit with verified randomness is generated based on chaos in the CCSRL system, and is used to simultaneously generate the control matrix and random bit stream. Finally, the control matrix and random bit stream are used for the encryption algorithm in order to change the position and the values of pixels, respectively. Simulation results and security analysis demonstrate that the proposed algorithm is effective and able to resist various typical attacks, and thus is an excellent candidate for secure image communication application.

  10. The CAP study, evaluation of integrated universal and selective prevention strategies for youth alcohol misuse: study protocol of a cluster randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Newton Nicola C

    2012-08-01

    Full Text Available Abstract Background Alcohol misuse amongst young people is a serious concern. The need for effective prevention is clear, yet there appear to be few evidenced-based programs that prevent alcohol misuse and none that target both high and low-risk youth. The CAP study addresses this gap by evaluating the efficacy of an integrated approach to alcohol misuse prevention, which combines the effective universal internet-based Climate Schools program with the effective selective personality-targeted Preventure program. This article describes the development and protocol of the CAP study which aims to prevent alcohol misuse and related harms in Australian adolescents. Methods/Design A cluster randomized controlled trial (RCT is being conducted with Year 8 students aged 13 to 14-years-old from 27 secondary schools in New South Wales and Victoria, Australia. Blocked randomisation was used to assign schools to one of four groups; Climate Schools only, Preventure only, CAP (Climate Schools and Preventure, or Control (alcohol, drug and health education as usual. The primary outcomes of the trial will be the uptake and harmful use of alcohol and alcohol related harms. Secondary outcomes will include alcohol and cannabis related knowledge, cannabis related harms, intentions to use, and mental health symptomatology. All participants will complete assessments on five occasions; baseline; immediately post intervention, and at 12, 24 and 36 months post baseline. Discussion This study protocol presents the design and current implementation of a cluster RCT to evaluate the efficacy of the CAP study; an integrated universal and selective approach to prevent alcohol use and related harms among adolescents. Compared to students who receive the stand-alone universal Climate Schools program or alcohol and drug education as usual (Controls, we expect the students who receive the CAP intervention to have significantly less uptake of alcohol use, a reduction in average

  11. Nurse-Moderated Internet-Based Support for New Mothers: Non-Inferiority, Randomized Controlled Trial.

    Science.gov (United States)

    Sawyer, Michael G; Reece, Christy E; Bowering, Kerrie; Jeffs, Debra; Sawyer, Alyssa C P; Mittinty, Murthy; Lynch, John W

    2017-07-24

    Internet-based interventions moderated by community nurses have the potential to improve support offered to new mothers, many of whom now make extensive use of the Internet to obtain information about infant care. However, evidence from population-based randomized controlled trials is lacking. The aim of this study was to test the non-inferiority of outcomes for mothers and infants who received a clinic-based postnatal health check plus nurse-moderated, Internet-based group support when infants were aged 1-7 months as compared with outcomes for those who received standard care consisting of postnatal home-based support provided by a community nurse. The design of the study was a pragmatic, preference, non-inferiority randomized control trial. Participants were recruited from mothers contacted for their postnatal health check, which is offered to all mothers in South Australia. Mothers were assigned either (1) on the basis of their preference to clinic+Internet or home-based support groups (n=328), or (2) randomly assigned to clinic+Internet or home-based groups if they declared no strong preference (n=491). The overall response rate was 44.8% (819/1827). The primary outcome was parenting self-competence, as measured by the Parenting Stress Index (PSI) Competence subscale, and the Karitane Parenting Confidence Scale scores. Secondary outcome measures included PSI Isolation, Interpersonal Support Evaluation List-Short Form, Maternal Support Scale, Ages and Stages Questionnaire-Social-Emotional and MacArthur Communicative Development Inventory (MCDI) scores. Assessments were completed offline via self-assessment questionnaires at enrolment (mean child age=4.1 weeks, SD 1.3) and again when infants were aged 9, 15, and 21 months. Generalized estimating equations adjusting for post-randomization baseline imbalances showed that differences in outcomes between mothers in the clinic+Internet and home-based support groups did not exceed the pre-specified margin of

  12. Isoniazid release from suppositories compounded with selected bases.

    Science.gov (United States)

    Hudson, Kristofer C; Asbill, C Scott; Webster, Andrew A

    2007-01-01

    There is an increasing need for an alternative route of isoniazid adminstration for prophylaxis and treatment of tuberculosis in children. The purpose of this study is to evaluate the in vitro release of isoniazid from extemporaneously compounded isoniazid suppositories with a goal of optimizing the suppository dosage form for this indication. Suppositories were compounded using three different base formulations (cocoa butter, Witepsol H15 Base F, and a combination of polyethylene glycols 3350, 1000, and 400). The release profiles of six compounded suppositories with isoniazid (100 mg) were tested with a United States Pharmacopeial Convention-approved dissolution apparatus. Isoniazid concentrations at predetermined time points were determined using high-performance liquid chromatographic analysis. The results show that drug release from the water-solutble base (mixed polyethylene glycols) was significantly greater than that from the lipophilic bases (cocoa butter and Witepsol H15). The percentage of isoniazid release form the polyethylene glycol suppository formulation (70 +/- 1.4 mg/mL) was greater than that from the cocoa butter (55 +/- 1.1 mg/mL) and Witepsol H15 Base F (18 +/- 0.36 mg/mL) suppository formulations.

  13. Performance Analysis of a Threshold-Based Parallel Multiple Beam Selection Scheme for WDM FSO Systems

    KAUST Repository

    Nam, Sung Sik; Alouini, Mohamed-Slim; Ko, Young-Chai

    2018-01-01

    In this paper, we statistically analyze the performance of a threshold-based parallel multiple beam selection scheme for a free-space optical (FSO) based system with wavelength division multiplexing (WDM) in cases where a pointing error has occurred

  14. Randomized trial of switching from prescribed non-selective non-steroidal anti-inflammatory drugs to prescribed celecoxib

    DEFF Research Database (Denmark)

    Macdonald, Thomas M; Hawkey, Chris J; Ford, Ian

    2017-01-01

    BACKGROUND: Selective cyclooxygenase-2 inhibitors and conventional non-selective non-steroidal anti-inflammatory drugs (nsNSAIDs) have been associated with adverse cardiovascular (CV) effects. We compared the CV safety of switching to celecoxib vs. continuing nsNSAID therapy in a European setting...

  15. Empirical versus Random Item Selection in the Design of Intelligence Test Short Forms--The WISC-R Example.

    Science.gov (United States)

    Goh, David S.

    1979-01-01

    The advantages of using psychometric thoery to design short forms of intelligence tests are demonstrated by comparing such usage to a systematic random procedure that has previously been used. The Wechsler Intelligence Scale for Children Revised (WISC-R) Short Form is presented as an example. (JKS)

  16. SNRFCB: sub-network based random forest classifier for predicting chemotherapy benefit on survival for cancer treatment.

    Science.gov (United States)

    Shi, Mingguang; He, Jianmin

    2016-04-01

    Adjuvant chemotherapy (CTX) should be individualized to provide potential survival benefit and avoid potential harm to cancer patients. Our goal was to establish a computational approach for making personalized estimates of the survival benefit from adjuvant CTX. We developed Sub-Network based Random Forest classifier for predicting Chemotherapy Benefit (SNRFCB) based gene expression datasets of lung cancer. The SNRFCB approach was then validated in independent test cohorts for identifying chemotherapy responder cohorts and chemotherapy non-responder cohorts. SNRFCB involved the pre-selection of gene sub-network signatures based on the mutations and on protein-protein interaction data as well as the application of the random forest algorithm to gene expression datasets. Adjuvant CTX was significantly associated with the prolonged overall survival of lung cancer patients in the chemotherapy responder group (P = 0.008), but it was not beneficial to patients in the chemotherapy non-responder group (P = 0.657). Adjuvant CTX was significantly associated with the prolonged overall survival of lung cancer squamous cell carcinoma (SQCC) subtype patients in the chemotherapy responder cohorts (P = 0.024), but it was not beneficial to patients in the chemotherapy non-responder cohorts (P = 0.383). SNRFCB improved prediction performance as compared to the machine learning method, support vector machine (SVM). To test the general applicability of the predictive model, we further applied the SNRFCB approach to human breast cancer datasets and also observed superior performance. SNRFCB could provide recurrent probability for individual patients and identify which patients may benefit from adjuvant CTX in clinical trials.

  17. A Randomized Controlled Trial of COMPASS Web-Based and Face-to-Face Teacher Coaching in Autism

    Science.gov (United States)

    Ruble, Lisa A.; McGrew, John H.; Toland, Michael D.; Dalrymple, Nancy J.; Jung, Lee Ann

    2013-01-01

    Objective Most children with autism rely on schools as their primary source of intervention, yet research has suggested that teachers rarely use evidence-based practices. To address the need for improved educational outcomes, a previously tested consultation intervention called the Collaborative Model for Promoting Competence and Success (COMPASS; Ruble, Dalrymple, & McGrew, 2010; Ruble, Dalrymple, & McGrew, 2012) was evaluated in a 2nd randomized controlled trial, with the addition of a web-based group. Method Forty-nine teacher–child dyads were randomized into 1 of 3 groups: (1) a placebo control (PBO) group, (2) COMPASS followed by face-to-face (FF) coaching sessions, and (3) COMPASS followed by web-based (WEB) coaching sessions. Three individualized goals (social, communication, and independence skills) were selected for intervention for each child. The primary outcome of independent ratings of child goal attainment and several process measures (e.g., consultant and teacher fidelity) were evaluated. Results Using an intent-to-treat approach, findings replicated earlier results with a very large effect size (d = 1.41) for the FF group and a large effect size (d = 1.12) for the WEB group relative to the PBO group. There were no differences in overall change across goal domains between the FF and WEB groups, suggesting the efficacy of videoconferencing technology. Conclusions COMPASS is effective and results in improved educational outcomes for young children with autism. Videoconferencing technology, as a scalable tool, has promise for facilitating access to autism specialists and bridging the research-to-practice gap. PMID:23438314

  18. Natural ingredients based cosmetics. Content of selected fragrance sensitizers

    DEFF Research Database (Denmark)

    Rastogi, Suresh Chandra; Johansen, J D; Menné, T

    1996-01-01

    In the present study, we have investigated 42 cosmetic products based on natural ingredients for content of 11 fragrance substances: geraniol, hydroxycitronellal, eugenol, isoeugenol, cinnamic aldehyde, cinnamic alcohol, alpha-amylcinnamic aldehyde, citral, coumarin, dihydrocoumarin and alpha......-hexylcinnamic aldehyde. The study revealed that the 91% (20/22) of the natural ingredients based perfumes contained 0.027%-7.706% of 1 to 7 of the target fragrances. Between 1 and 5 of the chemically defined synthetic constituents of fragrance mix were found in 82% (18/22) of the perfumes. 35% (7/20) of the other...... of hydroxycitronellal and alpha-hexylcinnamic aldehyde in some of the products demonstrates that artificial fragrances, i.e., compounds not yet regarded as natural substances, may be present in products claimed to be based on natural ingredients....

  19. An empirical approach to selecting community-based alcohol interventions: combining research evidence, rural community views and professional opinion

    Directory of Open Access Journals (Sweden)

    Shakeshaft Anthony

    2012-01-01

    Full Text Available Abstract Background Given limited research evidence for community-based alcohol interventions, this study examines the intervention preferences of rural communities and alcohol professionals, and factors that influence their choices. Method Community preferences were identified by a survey of randomly selected individuals across 20 regional Australian communities. The preferences of alcohol professionals were identified by a survey of randomly selected members of the Australasian Professional Society on Alcohol and Other Drugs. To identify preferred interventions and the extent of support for them, a budget allocation exercise was embedded in both surveys, asking respondents to allocate a given budget to different interventions. Tobit regression models were estimated to identify the characteristics that explain differences in intervention preferences. Results Community respondents selected school programs most often (88.0% and allocated it the largest proportion of funds, followed by promotion of safer drinking (71.3%, community programs (61.4% and police enforcement of alcohol laws (60.4%. Professionals selected GP training most often (61.0% and allocated it the largest proportion of funds, followed by school programs (36.6%, community programs (33.8% and promotion of safer drinking (31.7%. Community views were susceptible to response bias. There were no significant predictors of professionals' preferences. Conclusions In the absence of sufficient research evidence for effective community-based alcohol interventions, rural communities and professionals both strongly support school programs, promotion of safer drinking and community programs. Rural communities also supported police enforcement of alcohol laws and professionals supported GP training. The impact of a combination of these strategies needs to be rigorously evaluated.

  20. Strategies for implementing genomic selection in family-based aquaculture breeding schemes: double haploid sib test populations

    Directory of Open Access Journals (Sweden)

    Nirea Kahsay G

    2012-10-01

    Full Text Available Abstract Background Simulation studies have shown that accuracy and genetic gain are increased in genomic selection schemes compared to traditional aquaculture sib-based schemes. In genomic selection, accuracy of selection can be maximized by increasing the precision of the estimation of SNP effects and by maximizing the relationships between test sibs and candidate sibs. Another means of increasing the accuracy of the estimation of SNP effects is to create individuals in the test population with extreme genotypes. The latter approach was studied here with creation of double haploids and use of non-random mating designs. Methods Six alternative breeding schemes were simulated in which the design of the test population was varied: test sibs inherited maternal (Mat, paternal (Pat or a mixture of maternal and paternal (MatPat double haploid genomes or test sibs were obtained by maximum coancestry mating (MaxC, minimum coancestry mating (MinC, or random (RAND mating. Three thousand test sibs and 3000 candidate sibs were genotyped. The test sibs were recorded for a trait that could not be measured on the candidates and were used to estimate SNP effects. Selection was done by truncation on genome-wide estimated breeding values and 100 individuals were selected as parents each generation, equally divided between both sexes. Results Results showed a 7 to 19% increase in selection accuracy and a 6 to 22% increase in genetic gain in the MatPat scheme compared to the RAND scheme. These increases were greater with lower heritabilities. Among all other scenarios, i.e. Mat, Pat, MaxC, and MinC, no substantial differences in selection accuracy and genetic gain were observed. Conclusions In conclusion, a test population designed with a mixture of paternal and maternal double haploids, i.e. the MatPat scheme, increases substantially the accuracy of selection and genetic gain. This will be particularly interesting for traits that cannot be recorded on the