Multisource least-squares reverse-time migration with structure-oriented filtering

NASA Astrophysics Data System (ADS)

Fan, Jing-Wen; Li, Zhen-Chun; Zhang, Kai; Zhang, Min; Liu, Xue-Tong

2016-09-01

The technology of simultaneous-source acquisition of seismic data excited by several sources can significantly improve the data collection efficiency. However, direct imaging of simultaneous-source data or blended data may introduce crosstalk noise and affect the imaging quality. To address this problem, we introduce a structure-oriented filtering operator as preconditioner into the multisource least-squares reverse-time migration (LSRTM). The structure-oriented filtering operator is a nonstationary filter along structural trends that suppresses crosstalk noise while maintaining structural information. The proposed method uses the conjugate-gradient method to minimize the mismatch between predicted and observed data, while effectively attenuating the interference noise caused by exciting several sources simultaneously. Numerical experiments using synthetic data suggest that the proposed method can suppress the crosstalk noise and produce highly accurate images.

Simultaneous calibration phantom commission and geometry calibration in cone beam CT

NASA Astrophysics Data System (ADS)

Xu, Yuan; Yang, Shuai; Ma, Jianhui; Li, Bin; Wu, Shuyu; Qi, Hongliang; Zhou, Linghong

2017-09-01

Geometry calibration is a vital step for describing the geometry of a cone beam computed tomography (CBCT) system and is a prerequisite for CBCT reconstruction. In current methods, calibration phantom commission and geometry calibration are divided into two independent tasks. Small errors in ball-bearing (BB) positioning in the phantom-making step will severely degrade the quality of phantom calibration. To solve this problem, we propose an integrated method to simultaneously realize geometry phantom commission and geometry calibration. Instead of assuming the accuracy of the geometry phantom, the integrated method considers BB centers in the phantom as an optimized parameter in the workflow. Specifically, an evaluation phantom and the corresponding evaluation contrast index are used to evaluate geometry artifacts for optimizing the BB coordinates in the geometry phantom. After utilizing particle swarm optimization, the CBCT geometry and BB coordinates in the geometry phantom are calibrated accurately and are then directly used for the next geometry calibration task in other CBCT systems. To evaluate the proposed method, both qualitative and quantitative studies were performed on simulated and realistic CBCT data. The spatial resolution of reconstructed images using dental CBCT can reach up to 15 line pair cm-1. The proposed method is also superior to the Wiesent method in experiments. This paper shows that the proposed method is attractive for simultaneous and accurate geometry phantom commission and geometry calibration.

Robust estimation of partially linear models for longitudinal data with dropouts and measurement error.

PubMed

Qin, Guoyou; Zhang, Jiajia; Zhu, Zhongyi; Fung, Wing

2016-12-20

Outliers, measurement error, and missing data are commonly seen in longitudinal data because of its data collection process. However, no method can address all three of these issues simultaneously. This paper focuses on the robust estimation of partially linear models for longitudinal data with dropouts and measurement error. A new robust estimating equation, simultaneously tackling outliers, measurement error, and missingness, is proposed. The asymptotic properties of the proposed estimator are established under some regularity conditions. The proposed method is easy to implement in practice by utilizing the existing standard generalized estimating equations algorithms. The comprehensive simulation studies show the strength of the proposed method in dealing with longitudinal data with all three features. Finally, the proposed method is applied to data from the Lifestyle Education for Activity and Nutrition study and confirms the effectiveness of the intervention in producing weight loss at month 9. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparative study between derivative spectrophotometry and multivariate calibration as analytical tools applied for the simultaneous quantitation of Amlodipine, Valsartan and Hydrochlorothiazide.

PubMed

Darwish, Hany W; Hassan, Said A; Salem, Maissa Y; El-Zeany, Badr A

2013-09-01

Four simple, accurate and specific methods were developed and validated for the simultaneous estimation of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in commercial tablets. The derivative spectrophotometric methods include Derivative Ratio Zero Crossing (DRZC) and Double Divisor Ratio Spectra-Derivative Spectrophotometry (DDRS-DS) methods, while the multivariate calibrations used are Principal Component Regression (PCR) and Partial Least Squares (PLSs). The proposed methods were applied successfully in the determination of the drugs in laboratory-prepared mixtures and in commercial pharmaceutical preparations. The validity of the proposed methods was assessed using the standard addition technique. The linearity of the proposed methods is investigated in the range of 2-32, 4-44 and 2-20 μg/mL for AML, VAL and HCT, respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

A simultaneously calibration approach for installation and attitude errors of an INS/GPS/LDS target tracker.

PubMed

Cheng, Jianhua; Chen, Daidai; Sun, Xiangyu; Wang, Tongda

2015-02-04

To obtain the absolute position of a target is one of the basic topics for non-cooperated target tracking problems. In this paper, we present a simultaneously calibration method for an Inertial navigation system (INS)/Global position system (GPS)/Laser distance scanner (LDS) integrated system based target positioning approach. The INS/GPS integrated system provides the attitude and position of observer, and LDS offers the distance between the observer and the target. The two most significant errors are taken into jointly consideration and analyzed: (1) the attitude measure error of INS/GPS; (2) the installation error between INS/GPS and LDS subsystems. Consequently, a INS/GPS/LDS based target positioning approach considering these two errors is proposed. In order to improve the performance of this approach, a novel calibration method is designed to simultaneously estimate and compensate these two main errors. Finally, simulations are conducted to access the performance of the proposed target positioning approach and the designed simultaneously calibration method.

K-edge ratio method for identification of multiple nanoparticulate contrast agents by spectral CT imaging

PubMed Central

Ghadiri, H; Ay, M R; Shiran, M B; Soltanian-Zadeh, H

2013-01-01

Objective: Recently introduced energy-sensitive X-ray CT makes it feasible to discriminate different nanoparticulate contrast materials. The purpose of this work is to present a K-edge ratio method for differentiating multiple simultaneous contrast agents using spectral CT. Methods: The ratio of two images relevant to energy bins straddling the K-edge of the materials is calculated using an analytic CT simulator. In the resulting parametric map, the selected contrast agent regions can be identified using a thresholding algorithm. The K-edge ratio algorithm is applied to spectral images of simulated phantoms to identify and differentiate up to four simultaneous and targeted CT contrast agents. Results: We show that different combinations of simultaneous CT contrast agents can be identified by the proposed K-edge ratio method when energy-sensitive CT is used. In the K-edge parametric maps, the pixel values for biological tissues and contrast agents reach a maximum of 0.95, whereas for the selected contrast agents, the pixel values are larger than 1.10. The number of contrast agents that can be discriminated is limited owing to photon starvation. For reliable material discrimination, minimum photon counts corresponding to 140 kVp, 100 mAs and 5-mm slice thickness must be used. Conclusion: The proposed K-edge ratio method is a straightforward and fast method for identification and discrimination of multiple simultaneous CT contrast agents. Advances in knowledge: A new spectral CT-based algorithm is proposed which provides a new concept of molecular CT imaging by non-iteratively identifying multiple contrast agents when they are simultaneously targeting different organs. PMID:23934964

Spectra resolution for simultaneous spectrophotometric determination of lamivudine and zidovudine components in pharmaceutical formulation of human immunodeficiency virus drug based on using continuous wavelet transform and derivative transform techniques.

PubMed

Sohrabi, Mahmoud Reza; Tayefeh Zarkesh, Mahshid

2014-05-01

In the present paper, two spectrophotometric methods based on signal processing are proposed for the simultaneous determination of two components of an anti-HIV drug called lamivudine (LMV) and zidovudine (ZDV). The proposed methods are applied to synthetic binary mixtures and commercial pharmaceutical tablets without the need for any chemical separation procedures. The developed methods are based on the application of Continuous Wavelet Transform (CWT) and Derivative Spectrophotometry (DS) combined with the zero cross point technique. The Daubechies (db5) wavelet family (242 nm) and Dmey wavelet family (236 nm) were found to give the best results under optimum conditions for simultaneous analysis of lamivudine and zidovudine, respectively. In addition, the first derivative absorption spectra were selected for the determination of lamivudine and zidovudine at 266 nm and 248 nm, respectively. Assaying various synthetic mixtures of the components validated the presented methods. Mean recovery values were found to be between 100.31% and 100.2% for CWT and 99.42% and 97.37% for DS, respectively for determination of LMV and ZDV. The results obtained from analyzing the real samples by the proposed methods were compared to the HPLC reference method. One-way ANOVA test at 95% confidence level was applied to the results. The statistical data from comparing the proposed methods with the reference method showed no significant differences. Copyright © 2014 Elsevier B.V. All rights reserved.

Sparse distance-based learning for simultaneous multiclass classification and feature selection of metagenomic data.

PubMed

Liu, Zhenqiu; Hsiao, William; Cantarel, Brandi L; Drábek, Elliott Franco; Fraser-Liggett, Claire

2011-12-01

Direct sequencing of microbes in human ecosystems (the human microbiome) has complemented single genome cultivation and sequencing to understand and explore the impact of commensal microbes on human health. As sequencing technologies improve and costs decline, the sophistication of data has outgrown available computational methods. While several existing machine learning methods have been adapted for analyzing microbiome data recently, there is not yet an efficient and dedicated algorithm available for multiclass classification of human microbiota. By combining instance-based and model-based learning, we propose a novel sparse distance-based learning method for simultaneous class prediction and feature (variable or taxa, which is used interchangeably) selection from multiple treatment populations on the basis of 16S rRNA sequence count data. Our proposed method simultaneously minimizes the intraclass distance and maximizes the interclass distance with many fewer estimated parameters than other methods. It is very efficient for problems with small sample sizes and unbalanced classes, which are common in metagenomic studies. We implemented this method in a MATLAB toolbox called MetaDistance. We also propose several approaches for data normalization and variance stabilization transformation in MetaDistance. We validate this method on several real and simulated 16S rRNA datasets to show that it outperforms existing methods for classifying metagenomic data. This article is the first to address simultaneous multifeature selection and class prediction with metagenomic count data. The MATLAB toolbox is freely available online at http://metadistance.igs.umaryland.edu/. zliu@umm.edu Supplementary data are available at Bioinformatics online.

Optimal Price Decision Problem for Simultaneous Multi-article Auction and Its Optimal Price Searching Method by Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Masuda, Kazuaki; Aiyoshi, Eitaro

We propose a method for solving optimal price decision problems for simultaneous multi-article auctions. An auction problem, originally formulated as a combinatorial problem, determines both every seller's whether or not to sell his/her article and every buyer's which article(s) to buy, so that the total utility of buyers and sellers will be maximized. Due to the duality theory, we transform it equivalently into a dual problem in which Lagrange multipliers are interpreted as articles' transaction price. As the dual problem is a continuous optimization problem with respect to the multipliers (i.e., the transaction prices), we propose a numerical method to solve it by applying heuristic global search methods. In this paper, Particle Swarm Optimization (PSO) is used to solve the dual problem, and experimental results are presented to show the validity of the proposed method.

Simultaneous Local Binary Feature Learning and Encoding for Homogeneous and Heterogeneous Face Recognition.

PubMed

Lu, Jiwen; Erin Liong, Venice; Zhou, Jie

2017-08-09

In this paper, we propose a simultaneous local binary feature learning and encoding (SLBFLE) approach for both homogeneous and heterogeneous face recognition. Unlike existing hand-crafted face descriptors such as local binary pattern (LBP) and Gabor features which usually require strong prior knowledge, our SLBFLE is an unsupervised feature learning approach which automatically learns face representation from raw pixels. Unlike existing binary face descriptors such as the LBP, discriminant face descriptor (DFD), and compact binary face descriptor (CBFD) which use a two-stage feature extraction procedure, our SLBFLE jointly learns binary codes and the codebook for local face patches so that discriminative information from raw pixels from face images of different identities can be obtained by using a one-stage feature learning and encoding procedure. Moreover, we propose a coupled simultaneous local binary feature learning and encoding (C-SLBFLE) method to make the proposed approach suitable for heterogeneous face matching. Unlike most existing coupled feature learning methods which learn a pair of transformation matrices for each modality, we exploit both the common and specific information from heterogeneous face samples to characterize their underlying correlations. Experimental results on six widely used face datasets are presented to demonstrate the effectiveness of the proposed method.

Sensitive analytical method for simultaneous analysis of some vasoconstrictors with highly overlapped analytical signals

NASA Astrophysics Data System (ADS)

Nikolić, G. S.; Žerajić, S.; Cakić, M.

2011-10-01

Multivariate calibration method is a powerful mathematical tool that can be applied in analytical chemistry when the analytical signals are highly overlapped. The method with regression by partial least squares is proposed for the simultaneous spectrophotometric determination of adrenergic vasoconstrictors in decongestive solution containing two active components: phenyleprine hydrochloride and trimazoline hydrochloride. These sympathomimetic agents are that frequently associated in pharmaceutical formulations against the common cold. The proposed method, which is, simple and rapid, offers the advantages of sensitivity and wide range of determinations without the need for extraction of the vasoconstrictors. In order to minimize the optimal factors necessary to obtain the calibration matrix by multivariate calibration, different parameters were evaluated. The adequate selection of the spectral regions proved to be important on the number of factors. In order to simultaneously quantify both hydrochlorides among excipients, the spectral region between 250 and 290 nm was selected. A recovery for the vasoconstrictor was 98-101%. The developed method was applied to assay of two decongestive pharmaceutical preparations.

Easy, fast and environmental friendly method for the simultaneous extraction of the 16 EPA PAHs using magnetic molecular imprinted polymers (mag-MIPs).

PubMed

Villar-Navarro, Mercedes; Martín-Valero, María Jesús; Fernández-Torres, Rut Maria; Callejón-Mochón, Manuel; Bello-López, Miguel Ángel

2017-02-15

An easy and environmental friendly method, based on the use of magnetic molecular imprinted polymers (mag-MIPs) is proposed for the simultaneous extraction of the 16 U.S. EPA polycyclic aromatic hydrocarbons (PAHs) priority pollutants. The mag-MIPs based extraction protocol is simple, more sensitive and low organic solvent consuming compared to official methods and also adequate for those PAHs more retained in the particulate matter. The new proposed extraction method followed by HPLC determination has been validated and applied to different types of water samples: tap water, river water, lake water and mineral water. Copyright © 2017 Elsevier B.V. All rights reserved.

Proposal on Calculation of Ventilation Threshold Using Non-contact Respiration Measurement with Pattern Light Projection

NASA Astrophysics Data System (ADS)

Aoki, Hirooki; Ichimura, Shiro; Fujiwara, Toyoki; Kiyooka, Satoru; Koshiji, Kohji; Tsuzuki, Keishi; Nakamura, Hidetoshi; Fujimoto, Hideo

We proposed a calculation method of the ventilation threshold using the non-contact respiration measurement with dot-matrix pattern light projection under pedaling exercise. The validity and effectiveness of our proposed method is examined by simultaneous measurement with the expiration gas analyzer. The experimental result showed that the correlation existed between the quasi ventilation thresholds calculated by our proposed method and the ventilation thresholds calculated by the expiration gas analyzer. This result indicates the possibility of the non-contact measurement of the ventilation threshold by the proposed method.

Simultaneous Tumor Segmentation, Image Restoration, and Blur Kernel Estimation in PET Using Multiple Regularizations

PubMed Central

Li, Laquan; Wang, Jian; Lu, Wei; Tan, Shan

2016-01-01

Accurate tumor segmentation from PET images is crucial in many radiation oncology applications. Among others, partial volume effect (PVE) is recognized as one of the most important factors degrading imaging quality and segmentation accuracy in PET. Taking into account that image restoration and tumor segmentation are tightly coupled and can promote each other, we proposed a variational method to solve both problems simultaneously in this study. The proposed method integrated total variation (TV) semi-blind de-convolution and Mumford-Shah segmentation with multiple regularizations. Unlike many existing energy minimization methods using either TV or L2 regularization, the proposed method employed TV regularization over tumor edges to preserve edge information, and L2 regularization inside tumor regions to preserve the smooth change of the metabolic uptake in a PET image. The blur kernel was modeled as anisotropic Gaussian to address the resolution difference in transverse and axial directions commonly seen in a clinic PET scanner. The energy functional was rephrased using the Γ-convergence approximation and was iteratively optimized using the alternating minimization (AM) algorithm. The performance of the proposed method was validated on a physical phantom and two clinic datasets with non-Hodgkin’s lymphoma and esophageal cancer, respectively. Experimental results demonstrated that the proposed method had high performance for simultaneous image restoration, tumor segmentation and scanner blur kernel estimation. Particularly, the recovery coefficients (RC) of the restored images of the proposed method in the phantom study were close to 1, indicating an efficient recovery of the original blurred images; for segmentation the proposed method achieved average dice similarity indexes (DSIs) of 0.79 and 0.80 for two clinic datasets, respectively; and the relative errors of the estimated blur kernel widths were less than 19% in the transversal direction and 7% in the axial direction. PMID:28603407

Context-Dependent Upper Limb Prosthesis Control for Natural and Robust Use.

PubMed

Amsuess, Sebastian; Vujaklija, Ivan; Goebel, Peter; Roche, Aidan D; Graimann, Bernhard; Aszmann, Oskar C; Farina, Dario

2016-07-01

Pattern recognition and regression methods applied to the surface EMG have been used for estimating the user intended motor tasks across multiple degrees of freedom (DOF), for prosthetic control. While these methods are effective in several conditions, they are still characterized by some shortcomings. In this study we propose a methodology that combines these two approaches for mutually alleviating their limitations. This resulted in a control method capable of context-dependent movement estimation that switched automatically between sequential (one DOF at a time) or simultaneous (multiple DOF) prosthesis control, based on an online estimation of signal dimensionality. The proposed method was evaluated in scenarios close to real-life situations, with the control of a physical prosthesis in applied tasks of varying difficulties. Test prostheses were individually manufactured for both able-bodied and transradial amputee subjects. With these prostheses, two amputees performed the Southampton Hand Assessment Procedure test with scores of 58 and 71 points. The five able-bodied individuals performed standardized tests, such as the box&block and clothes pin test, reducing the completion times by up to 30%, with respect to using a state-of-the-art pure sequential control algorithm. Apart from facilitating fast simultaneous movements, the proposed control scheme was also more intuitive to use, since human movements are predominated by simultaneous activations across joints. The proposed method thus represents a significant step towards intelligent, intuitive and natural control of upper limb prostheses.

Evaluating Simultaneous Integrals

ERIC Educational Resources Information Center

Kwong, Harris

2012-01-01

Many integrals require two successive applications of integration by parts. During the process, another integral of similar type is often invoked. We propose a method which can integrate these two integrals simultaneously. All we need is to solve a linear system of equations.

Coarse-graining time series data: Recurrence plot of recurrence plots and its application for music

NASA Astrophysics Data System (ADS)

Fukino, Miwa; Hirata, Yoshito; Aihara, Kazuyuki

2016-02-01

We propose a nonlinear time series method for characterizing two layers of regularity simultaneously. The key of the method is using the recurrence plots hierarchically, which allows us to preserve the underlying regularities behind the original time series. We demonstrate the proposed method with musical data. The proposed method enables us to visualize both the local and the global musical regularities or two different features at the same time. Furthermore, the determinism scores imply that the proposed method may be useful for analyzing emotional response to the music.

Coarse-graining time series data: Recurrence plot of recurrence plots and its application for music.

PubMed

Fukino, Miwa; Hirata, Yoshito; Aihara, Kazuyuki

2016-02-01

We propose a nonlinear time series method for characterizing two layers of regularity simultaneously. The key of the method is using the recurrence plots hierarchically, which allows us to preserve the underlying regularities behind the original time series. We demonstrate the proposed method with musical data. The proposed method enables us to visualize both the local and the global musical regularities or two different features at the same time. Furthermore, the determinism scores imply that the proposed method may be useful for analyzing emotional response to the music.

A Framework for Final Drive Simultaneous Failure Diagnosis Based on Fuzzy Entropy and Sparse Bayesian Extreme Learning Machine

PubMed Central

Ye, Qing; Pan, Hao; Liu, Changhua

2015-01-01

This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction module, adopt wavelet package transform and fuzzy entropy to reduce noise interference and extract representative features of failure mode. Use single failure sample to construct probability classifiers based on paired sparse Bayesian extreme learning machine which is trained only by single failure modes and have high generalization and sparsity of sparse Bayesian learning approach. To generate optimal decision threshold which can convert probability output obtained from classifiers into final simultaneous failure modes, this research proposes using samples containing both single and simultaneous failure modes and Grid search method which is superior to traditional techniques in global optimization. Compared with other frequently used diagnostic approaches based on support vector machine and probability neural networks, experiment results based on F 1-measure value verify that the diagnostic accuracy and efficiency of the proposed framework which are crucial for simultaneous failure diagnosis are superior to the existing approach. PMID:25722717

A microfluidic device for simultaneous measurement of viscosity and flow rate of blood in a complex fluidic network

PubMed Central

Jun Kang, Yang; Yeom, Eunseop; Lee, Sang-Joon

2013-01-01

Blood viscosity has been considered as one of important biophysical parameters for effectively monitoring variations in physiological and pathological conditions of circulatory disorders. Standard previous methods make it difficult to evaluate variations of blood viscosity under cardiopulmonary bypass procedures or hemodialysis. In this study, we proposed a unique microfluidic device for simultaneously measuring viscosity and flow rate of whole blood circulating in a complex fluidic network including a rat, a reservoir, a pinch valve, and a peristaltic pump. To demonstrate the proposed method, a twin-shaped microfluidic device, which is composed of two half-circular chambers, two side channels with multiple indicating channels, and one bridge channel, was carefully designed. Based on the microfluidic device, three sequential flow controls were applied to identify viscosity and flow rate of blood, with label-free and sensorless detection. The half-circular chamber was employed to achieve mechanical membrane compliance for flow stabilization in the microfluidic device. To quantify the effect of flow stabilization on flow fluctuations, a formula of pulsation index (PI) was analytically derived using a discrete fluidic circuit model. Using the PI formula, the time constant contributed by the half-circular chamber is estimated to be 8 s. Furthermore, flow fluctuations resulting from the peristaltic pumps are completely removed, especially under periodic flow conditions within short periods (T < 10 s). For performance demonstrations, the proposed method was applied to evaluate blood viscosity with respect to varying flow rate conditions [(a) known blood flow rate via a syringe pump, (b) unknown blood flow rate via a peristaltic pump]. As a result, the flow rate and viscosity of blood can be simultaneously measured with satisfactory accuracy. In addition, the proposed method was successfully applied to identify the viscosity of rat blood, which circulates in a complex fluidic network. These observations confirm that the proposed method can be used for simultaneous measurement of viscosity and flow rate of whole blood circulating in the complex fluid network, with sensorless and label-free detection. Furthermore, the proposed method will be used in evaluating variations in the viscosity of human blood during cardiopulmonary bypass procedures or hemodialysis. PMID:24404074

A microfluidic device for simultaneous measurement of viscosity and flow rate of blood in a complex fluidic network.

PubMed

Jun Kang, Yang; Yeom, Eunseop; Lee, Sang-Joon

2013-01-01

Blood viscosity has been considered as one of important biophysical parameters for effectively monitoring variations in physiological and pathological conditions of circulatory disorders. Standard previous methods make it difficult to evaluate variations of blood viscosity under cardiopulmonary bypass procedures or hemodialysis. In this study, we proposed a unique microfluidic device for simultaneously measuring viscosity and flow rate of whole blood circulating in a complex fluidic network including a rat, a reservoir, a pinch valve, and a peristaltic pump. To demonstrate the proposed method, a twin-shaped microfluidic device, which is composed of two half-circular chambers, two side channels with multiple indicating channels, and one bridge channel, was carefully designed. Based on the microfluidic device, three sequential flow controls were applied to identify viscosity and flow rate of blood, with label-free and sensorless detection. The half-circular chamber was employed to achieve mechanical membrane compliance for flow stabilization in the microfluidic device. To quantify the effect of flow stabilization on flow fluctuations, a formula of pulsation index (PI) was analytically derived using a discrete fluidic circuit model. Using the PI formula, the time constant contributed by the half-circular chamber is estimated to be 8 s. Furthermore, flow fluctuations resulting from the peristaltic pumps are completely removed, especially under periodic flow conditions within short periods (T < 10 s). For performance demonstrations, the proposed method was applied to evaluate blood viscosity with respect to varying flow rate conditions [(a) known blood flow rate via a syringe pump, (b) unknown blood flow rate via a peristaltic pump]. As a result, the flow rate and viscosity of blood can be simultaneously measured with satisfactory accuracy. In addition, the proposed method was successfully applied to identify the viscosity of rat blood, which circulates in a complex fluidic network. These observations confirm that the proposed method can be used for simultaneous measurement of viscosity and flow rate of whole blood circulating in the complex fluid network, with sensorless and label-free detection. Furthermore, the proposed method will be used in evaluating variations in the viscosity of human blood during cardiopulmonary bypass procedures or hemodialysis.

Net analyte signal standard addition method (NASSAM) as a novel spectrofluorimetric and spectrophotometric technique for simultaneous determination, application to assay of melatonin and pyridoxine

NASA Astrophysics Data System (ADS)

Asadpour-Zeynali, Karim; Bastami, Mohammad

2010-02-01

In this work a new modification of the standard addition method called "net analyte signal standard addition method (NASSAM)" is presented for the simultaneous spectrofluorimetric and spectrophotometric analysis. The proposed method combines the advantages of standard addition method with those of net analyte signal concept. The method can be applied for the determination of analyte in the presence of known interferents. The accuracy of the predictions against H-point standard addition method is not dependent on the shape of the analyte and interferent spectra. The method was successfully applied to simultaneous spectrofluorimetric and spectrophotometric determination of pyridoxine (PY) and melatonin (MT) in synthetic mixtures and in a pharmaceutical formulation.

Simultaneous determination of eight water-soluble vitamins in supplemented foods by liquid chromatography.

PubMed

Zafra-Gómez, Alberto; Garballo, Antonio; Morales, Juan C; García-Ayuso, Luis E

2006-06-28

A fast, simple, and reliable method for the isolation and determination of the vitamins thiamin, riboflavin, niacin, pantothenic acid, pyridoxine, folic acid, cyanocobalamin, and ascorbic acid in food samples is proposed. The most relevant advantages of the proposed method are the simultaneous determination of the eight more common vitamins in enriched food products and a reduction of the time required for quantitative extraction, because the method consists merely of the addition of a precipitation solution and centrifugation of the sample. Furthermore, this method saves a substantial amount of reagents as compared with official methods, and minimal sample manipulation is achieved due to the few steps required. The chromatographic separation is carried out on a reverse phase C18 column, and the vitamins are detected at different wavelengths by either fluorescence or UV-visible detection. The proposed method was applied to the determination of water-soluble vitamins in supplemented milk, infant nutrition products, and milk powder certified reference material (CRM 421, BCR) with recoveries ranging from 90 to 100%.

Simultaneous spectrophotometric determination of salbutamol and bromhexine in tablets.

PubMed

Habib, I H I; Hassouna, M E M; Zaki, G A

2005-03-01

Typical anti-mucolytic drugs called salbutamol hydrochloride and bromhexine sulfate encountered in tablets were determined simultaneously either by using linear regression at zero-crossing wavelengths of the first derivation of UV-spectra or by application of multiple linear partial least squares regression method. The results obtained by the two proposed mathematical methods were compared with those obtained by the HPLC technique.

A comparative study of smart spectrophotometric methods for simultaneous determination of sitagliptin phosphate and metformin hydrochloride in their binary mixture.

PubMed

Lotfy, Hayam M; Mohamed, Dalia; Mowaka, Shereen

2015-01-01

Simple, specific, accurate and precise spectrophotometric methods were developed and validated for the simultaneous determination of the oral antidiabetic drugs; sitagliptin phosphate (STG) and metformin hydrochloride (MET) in combined pharmaceutical formulations. Three methods were manipulating ratio spectra namely; ratio difference (RD), ratio subtraction (RS) and a novel approach of induced amplitude modulation (IAM) methods. The first two methods were used for determination of STG, while MET was directly determined by measuring its absorbance at λmax 232 nm. However, (IAM) was used for the simultaneous determination of both drugs. Moreover, another three methods were developed based on derivative spectroscopy followed by mathematical manipulation steps namely; amplitude factor (P-factor), amplitude subtraction (AS) and modified amplitude subtraction (MAS). In addition, in this work the novel sample enrichment technique named spectrum addition was adopted. The proposed spectrophotometric methods did not require any preliminary separation step. The accuracy, precision and linearity ranges of the proposed methods were determined. The selectivity of the developed methods was investigated by analyzing laboratory prepared mixtures of the drugs and their combined pharmaceutical formulations. Standard deviation values were less than 1.5 in the assay of raw materials and tablets. The obtained results were statistically compared to that of a reported spectrophotometric method. The statistical comparison showed that there was no significant difference between the proposed methods and the reported one regarding both accuracy and precision. Copyright © 2015 Elsevier B.V. All rights reserved.

Single shot multi-wavelength phase retrieval with coherent modulation imaging.

PubMed

Dong, Xue; Pan, Xingchen; Liu, Cheng; Zhu, Jianqiang

2018-04-15

A single shot multi-wavelength phase retrieval method is proposed by combining common coherent modulation imaging (CMI) and a low rank mixed-state algorithm together. A radiation beam consisting of multi-wavelength is illuminated on the sample to be observed, and the exiting field is incident on a random phase plate to form speckle patterns, which is the incoherent superposition of diffraction patterns of each wavelength. The exiting complex amplitude of the sample including both the modulus and phase of each wavelength can be reconstructed simultaneously from the recorded diffraction intensity using a low rank mixed-state algorithm. The feasibility of this proposed method was verified with visible light experimentally. This proposed method not only makes CMI realizable with partially coherent illumination but also can extend its application to various traditionally unrelated fields, where several wavelengths should be considered simultaneously.

Simultaneous determination of atorvastatin calcium and olmesartan medoxomil in a pharmaceutical formulation by reversed phase high-performance liquid chromatography, high-performance thin-layer chromatography, and UV spectrophotometric methods.

PubMed

Soni, Hiral; Kothari, Charmy; Khatri, Deepak; Mehta, Priti

2014-01-01

Validated RP-HPLC, HPTLC, and UV spectrophotometric methods have been developed for the simultaneous determination of atorvastatin calcium (ATV) and olmesartan medoxomil (OLM) in a pharmaceutical formulation. The RP-HPLC separation was achieved on a Kromasil C18 column (250 x 4.6 mm, 5 microm particle size) using 0.01 M potassium dihydrogen o-phosphate (pH 4 adjusted with o-phosphoric acid)-acetonitrile (50 + 50, v/v) as the mobile phase at a flow rate of 1.5 mL/min. Quantification was achieved by UV detection at 276 nm. The HPTLC separation was achieved on precoated silica gel 60F254 plates using chloroform-methanol-acetonitrile (4 + 2+ 4, v/v/v) mobile phase. Quantification was achieved with UV detection at 276 nm. The UV-Vis spectrophotometric method was based on the simultaneous equation method that involves measurement of absorbance at two wavelengths, i.e., 255 nm (lambda max of OLM) and 246.2 nm (lambda max of ATV) in methanol. All three methods were validated as per International Conference on Harmonization guidelines. The proposed methods were simple, precise, accurate, and applicable for the simultaneous determination of ATV and OLM in a marketed formulation. The results obtained by applying the proposed methods were statistically analyzed and were found satisfactory.

H-point standard additions method for simultaneous determination of sulfamethoxazole and trimethoprim in pharmaceutical formulations and biological fluids with simultaneous addition of two analytes

NASA Astrophysics Data System (ADS)

Givianrad, M. H.; Saber-Tehrani, M.; Aberoomand-Azar, P.; Mohagheghian, M.

2011-03-01

The applicability of H-point standard additions method (HPSAM) to the resolving of overlapping spectra corresponding to the sulfamethoxazole and trimethoprim is verified by UV-vis spectrophotometry. The results show that the H-point standard additions method with simultaneous addition of both analytes is suitable for the simultaneous determination of sulfamethoxazole and trimethoprim in aqueous media. The results of applying the H-point standard additions method showed that the two drugs could be determined simultaneously with the concentration ratios of sulfamethoxazole to trimethoprim varying from 1:18 to 16:1 in the mixed samples. Also, the limits of detections were 0.58 and 0.37 μmol L -1 for sulfamethoxazole and trimethoprim, respectively. In addition the means of the calculated RSD (%) were 1.63 and 2.01 for SMX and TMP, respectively in synthetic mixtures. The proposed method has been successfully applied to the simultaneous determination of sulfamethoxazole and trimethoprim in some synthetic, pharmaceutical formulation and biological fluid samples.

H-point standard additions method for simultaneous determination of sulfamethoxazole and trimethoprim in pharmaceutical formulations and biological fluids with simultaneous addition of two analytes.

PubMed

Givianrad, M H; Saber-Tehrani, M; Aberoomand-Azar, P; Mohagheghian, M

2011-03-01

The applicability of H-point standard additions method (HPSAM) to the resolving of overlapping spectra corresponding to the sulfamethoxazole and trimethoprim is verified by UV-vis spectrophotometry. The results show that the H-point standard additions method with simultaneous addition of both analytes is suitable for the simultaneous determination of sulfamethoxazole and trimethoprim in aqueous media. The results of applying the H-point standard additions method showed that the two drugs could be determined simultaneously with the concentration ratios of sulfamethoxazole to trimethoprim varying from 1:18 to 16:1 in the mixed samples. Also, the limits of detections were 0.58 and 0.37 μmol L(-1) for sulfamethoxazole and trimethoprim, respectively. In addition the means of the calculated RSD (%) were 1.63 and 2.01 for SMX and TMP, respectively in synthetic mixtures. The proposed method has been successfully applied to the simultaneous determination of sulfamethoxazole and trimethoprim in some synthetic, pharmaceutical formulation and biological fluid samples. Copyright © 2011 Elsevier B.V. All rights reserved.

Iterative deblending of simultaneous-source data using a coherency-pass shaping operator

NASA Astrophysics Data System (ADS)

Zu, Shaohuan; Zhou, Hui; Mao, Weijian; Zhang, Dong; Li, Chao; Pan, Xiao; Chen, Yangkang

2017-10-01

Simultaneous-source acquisition helps greatly boost an economic saving, while it brings an unprecedented challenge of removing the crosstalk interference in the recorded seismic data. In this paper, we propose a novel iterative method to separate the simultaneous source data based on a coherency-pass shaping operator. The coherency-pass filter is used to constrain the model, that is, the unblended data to be estimated, in the shaping regularization framework. In the simultaneous source survey, the incoherent interference from adjacent shots greatly increases the rank of the frequency domain Hankel matrix that is formed from the blended record. Thus, the method based on rank reduction is capable of separating the blended record to some extent. However, the shortcoming is that it may cause residual noise when there is strong blending interference. We propose to cascade the rank reduction and thresholding operators to deal with this issue. In the initial iterations, we adopt a small rank to severely separate the blended interference and a large thresholding value as strong constraints to remove the residual noise in the time domain. In the later iterations, since more and more events have been recovered, we weaken the constraint by increasing the rank and shrinking the threshold to recover weak events and to guarantee the convergence. In this way, the combined rank reduction and thresholding strategy acts as a coherency-pass filter, which only passes the coherent high-amplitude component after rank reduction instead of passing both signal and noise in traditional rank reduction based approaches. Two synthetic examples are tested to demonstrate the performance of the proposed method. In addition, the application on two field data sets (common receiver gathers and stacked profiles) further validate the effectiveness of the proposed method.

Simultaneous Calibration: A Joint Optimization Approach for Multiple Kinect and External Cameras.

PubMed

Liao, Yajie; Sun, Ying; Li, Gongfa; Kong, Jianyi; Jiang, Guozhang; Jiang, Du; Cai, Haibin; Ju, Zhaojie; Yu, Hui; Liu, Honghai

2017-06-24

Camera calibration is a crucial problem in many applications, such as 3D reconstruction, structure from motion, object tracking and face alignment. Numerous methods have been proposed to solve the above problem with good performance in the last few decades. However, few methods are targeted at joint calibration of multi-sensors (more than four devices), which normally is a practical issue in the real-time systems. In this paper, we propose a novel method and a corresponding workflow framework to simultaneously calibrate relative poses of a Kinect and three external cameras. By optimizing the final cost function and adding corresponding weights to the external cameras in different locations, an effective joint calibration of multiple devices is constructed. Furthermore, the method is tested in a practical platform, and experiment results show that the proposed joint calibration method can achieve a satisfactory performance in a project real-time system and its accuracy is higher than the manufacturer's calibration.

Simultaneous Calibration: A Joint Optimization Approach for Multiple Kinect and External Cameras

PubMed Central

Liao, Yajie; Sun, Ying; Li, Gongfa; Kong, Jianyi; Jiang, Guozhang; Jiang, Du; Cai, Haibin; Ju, Zhaojie; Yu, Hui; Liu, Honghai

2017-01-01

Camera calibration is a crucial problem in many applications, such as 3D reconstruction, structure from motion, object tracking and face alignment. Numerous methods have been proposed to solve the above problem with good performance in the last few decades. However, few methods are targeted at joint calibration of multi-sensors (more than four devices), which normally is a practical issue in the real-time systems. In this paper, we propose a novel method and a corresponding workflow framework to simultaneously calibrate relative poses of a Kinect and three external cameras. By optimizing the final cost function and adding corresponding weights to the external cameras in different locations, an effective joint calibration of multiple devices is constructed. Furthermore, the method is tested in a practical platform, and experiment results show that the proposed joint calibration method can achieve a satisfactory performance in a project real-time system and its accuracy is higher than the manufacturer’s calibration. PMID:28672823

Quantifying rainfall-derived inflow and infiltration in sanitary sewer systems based on conductivity monitoring

NASA Astrophysics Data System (ADS)

Zhang, Mingkai; Liu, Yanchen; Cheng, Xun; Zhu, David Z.; Shi, Hanchang; Yuan, Zhiguo

2018-03-01

Quantifying rainfall-derived inflow and infiltration (RDII) in a sanitary sewer is difficult when RDII and overflow occur simultaneously. This study proposes a novel conductivity-based method for estimating RDII. The method separately decomposes rainfall-derived inflow (RDI) and rainfall-induced infiltration (RII) on the basis of conductivity data. Fast Fourier transform was adopted to analyze variations in the flow and water quality during dry weather. Nonlinear curve fitting based on the least squares algorithm was used to optimize parameters in the proposed RDII model. The method was successfully applied to real-life case studies, in which inflow and infiltration were successfully estimated for three typical rainfall events with total rainfall volumes of 6.25 mm (light), 28.15 mm (medium), and 178 mm (heavy). Uncertainties of model parameters were estimated using the generalized likelihood uncertainty estimation (GLUE) method and were found to be acceptable. Compared with traditional flow-based methods, the proposed approach exhibits distinct advantages in estimating RDII and overflow, particularly when the two processes happen simultaneously.

A comparative study of smart spectrophotometric methods for simultaneous determination of a skeletal muscle relaxant and an analgesic in combined dosage form

NASA Astrophysics Data System (ADS)

Salem, Hesham; Mohamed, Dalia

2015-04-01

Six simple, specific, accurate and precise spectrophotometric methods were developed and validated for the simultaneous determination of the analgesic drug; paracetamol (PARA) and the skeletal muscle relaxant; dantrolene sodium (DANT). Three methods are manipulating ratio spectra namely; ratio difference (RD), ratio subtraction (RS) and mean centering (MC). The other three methods are utilizing the isoabsorptive point either at zero order namely; absorbance ratio (AR) and absorbance subtraction (AS) or at ratio spectrum namely; amplitude modulation (AM). The proposed spectrophotometric procedures do not require any preliminary separation step. The accuracy, precision and linearity ranges of the proposed methods were determined. The selectivity of the developed methods was investigated by analyzing laboratory prepared mixtures of the drugs and their combined dosage form. Standard deviation values are less than 1.5 in the assay of raw materials and capsules. The obtained results were statistically compared with each other and with those of reported spectrophotometric ones. The comparison showed that there is no significant difference between the proposed methods and the reported methods regarding both accuracy and precision.

Joint Segmentation of Anatomical and Functional Images: Applications in Quantification of Lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT Images

PubMed Central

Bagci, Ulas; Udupa, Jayaram K.; Mendhiratta, Neil; Foster, Brent; Xu, Ziyue; Yao, Jianhua; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. PMID:23837967

The application of artificial neural networks and support vector regression for simultaneous spectrophotometric determination of commercial eye drop contents

NASA Astrophysics Data System (ADS)

Valizadeh, Maryam; Sohrabi, Mahmoud Reza

2018-03-01

In the present study, artificial neural networks (ANNs) and support vector regression (SVR) as intelligent methods coupled with UV spectroscopy for simultaneous quantitative determination of Dorzolamide (DOR) and Timolol (TIM) in eye drop. Several synthetic mixtures were analyzed for validating the proposed methods. At first, neural network time series, which one type of network from the artificial neural network was employed and its efficiency was evaluated. Afterwards, the radial basis network was applied as another neural network. Results showed that the performance of this method is suitable for predicting. Finally, support vector regression was proposed to construct the Zilomole prediction model. Also, root mean square error (RMSE) and mean recovery (%) were calculated for SVR method. Moreover, the proposed methods were compared to the high-performance liquid chromatography (HPLC) as a reference method. One way analysis of variance (ANOVA) test at the 95% confidence level applied to the comparison results of suggested and reference methods that there were no significant differences between them. Also, the effect of interferences was investigated in spike solutions.

Achieving bifunctional cloak via combination of passive and active schemes

NASA Astrophysics Data System (ADS)

Lan, Chuwen; Bi, Ke; Gao, Zehua; Li, Bo; Zhou, Ji

2016-11-01

In this study, a simple and delicate approach to realizing manipulation of multi-physics field simultaneously through combination of passive and active schemes is proposed. In the design, one physical field is manipulated with passive scheme while the other with active scheme. As a proof of this concept, a bifunctional device is designed and fabricated to behave as electric and thermal invisibility cloak simultaneously. It is found that the experimental results are consistent with the simulated ones well, confirming the feasibility of our method. Furthermore, the proposed method could also be extended to other multi-physics fields, which might lead to potential applications in thermal, electric, and acoustic areas.

Simultaneous separation of copper, cadmium and cobalt from sea-water by co-flotation with octadecylamine and ferric hydroxide as collectors.

PubMed

Cabezon, L M; Caballero, M; Cela, R; Perez-Bustamante, J A

1984-08-01

A method is proposed for the simultaneous quantitative separation of traces ofCu(II), Cd(II) and Co(II) from sea-water samples by means of the co-flotation (adsorbing colloid flotation) technique with ferric hydroxide as co-precipitant and octadecylamine as collector. The experimental parameters have been studied and optimized. The drawbacks arising from the low solubility of octadecylamine and the corresponding sublates in water have been avoided by use of a 6M hydrochloric acid-MIBK-ethanol (1:2:2 v v ) mixture. The results obtained by means of the proposed method have been compared with those given by the usual ammonium pyrrolidine dithiocarbamate/MIBK extraction method.

A comparative study of the novel spectrophotometric methods versus conventional ones for the simultaneous determination of Esomeprazole magnesium trihydrate and Naproxen in their binary mixture.

PubMed

Lotfy, Hayam M; Amer, Sawsan M; Zaazaa, Hala E; Mostafa, Noha S

2015-01-01

Two novel simple, specific, accurate and precise spectrophotometric methods manipulating ratio spectra are developed and validated for simultaneous determination of Esomeprazole magnesium trihydrate (ESO) and Naproxen (NAP) namely; absorbance subtraction and ratio difference. The results were compared to that of the conventional spectrophotometric methods namely; dual wavelength and isoabsorptive point coupled with first derivative of ratio spectra and derivative ratio. The suggested methods were validated in compliance with the ICH guidelines and were successfully applied for determination of ESO and NAP in their laboratory prepared mixtures and pharmaceutical preparation. No preliminary separation steps are required for the proposed spectrophotometeric procedures. The statistical comparison showed that there is no significant difference between the proposed methods and the reported method with respect to both accuracy and precision. Copyright © 2015 Elsevier B.V. All rights reserved.

Spectrophotometric Determination of Iron(II) and Cobalt(II) by Direct, Derivative, and Simultaneous Methods Using 2-Hydroxy-1-Naphthaldehyde-p-Hydroxybenzoichydrazone

PubMed Central

Devi, V. S. Anusuya; Reddy, V. Krishna

2012-01-01

Optimized and validated spectrophotometric methods have been proposed for the determination of iron and cobalt individually and simultaneously. 2-hydroxy-1-naphthaldehyde-p-hydroxybenzoichydrazone (HNAHBH) reacts with iron(II) and cobalt(II) to form reddish-brown and yellow-coloured [Fe(II)-HNAHBH] and [Co(II)-HNAHBH] complexes, respectively. The maximum absorbance of these complexes was found at 405 nm and 425 nm, respectively. For [Fe(II)-HNAHBH], Beer's law is obeyed over the concentration range of 0.055–1.373 μg mL−1 with a detection limit of 0.095 μg mL−1 and molar absorptivity ɛ, 5.6 × 104 L mol−1 cm−1. [Co(II)-HNAHBH] complex obeys Beer's law in 0.118–3.534 μg mL−1 range with a detection limit of 0.04 μg mL−1 and molar absorptivity, ɛ of 2.3 × 104 L mol−1 cm−1. Highly sensitive and selective first-, second- and third-order derivative methods are described for the determination of iron and cobalt. A simultaneous second-order derivative spectrophotometric method is proposed for the determination of these metals. All the proposed methods are successfully employed in the analysis of various biological, water, and alloy samples for the determination of iron and cobalt content. PMID:22505925

Detection of dependence patterns with delay.

PubMed

Chevallier, Julien; Laloë, Thomas

2015-11-01

The Unitary Events (UE) method is a popular and efficient method used this last decade to detect dependence patterns of joint spike activity among simultaneously recorded neurons. The first introduced method is based on binned coincidence count (Grün, 1996) and can be applied on two or more simultaneously recorded neurons. Among the improvements of the methods, a transposition to the continuous framework has recently been proposed by Muiño and Borgelt (2014) and fully investigated by Tuleau-Malot et al. (2014) for two neurons. The goal of the present paper is to extend this study to more than two neurons. The main result is the determination of the limit distribution of the coincidence count. This leads to the construction of an independence test between L≥2 neurons. Finally, we propose a multiple test procedure via a Benjamini and Hochberg approach (Benjamini and Hochberg, 1995). All the theoretical results are illustrated by a simulation study, and compared to the UE method proposed by Grün et al. (2002). Furthermore our method is applied on real data. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simultaneous spectrophotometric determination of valsartan and hydrochlorothiazide by H-point standard addition method and partial least squares regression.

PubMed

Lakshmi, Karunanidhi Santhana; Lakshmi, Sivasubramanian

2011-03-01

Simultaneous determination of valsartan and hydrochlorothiazide by the H-point standard additions method (HPSAM) and partial least squares (PLS) calibration is described. Absorbances at a pair of wavelengths, 216 and 228 nm, were monitored with the addition of standard solutions of valsartan. Results of applying HPSAM showed that valsartan and hydrochlorothiazide can be determined simultaneously at concentration ratios varying from 20:1 to 1:15 in a mixed sample. The proposed PLS method does not require chemical separation and spectral graphical procedures for quantitative resolution of mixtures containing the titled compounds. The calibration model was based on absorption spectra in the 200-350 nm range for 25 different mixtures of valsartan and hydrochlorothiazide. Calibration matrices contained 0.5-3 μg mL-1 of both valsartan and hydrochlorothiazide. The standard error of prediction (SEP) for valsartan and hydrochlorothiazide was 0.020 and 0.038 μg mL-1, respectively. Both proposed methods were successfully applied to the determination of valsartan and hydrochlorothiazide in several synthetic and real matrix samples.

Methods for Multiloop Identification of Visual and Neuromuscular Pilot Responses.

PubMed

Olivari, Mario; Nieuwenhuizen, Frank M; Venrooij, Joost; Bülthoff, Heinrich H; Pollini, Lorenzo

2015-12-01

In this paper, identification methods are proposed to estimate the neuromuscular and visual responses of a multiloop pilot model. A conventional and widely used technique for simultaneous identification of the neuromuscular and visual systems makes use of cross-spectral density estimates. This paper shows that this technique requires a specific noninterference hypothesis, often implicitly assumed, that may be difficult to meet during actual experimental designs. A mathematical justification of the necessity of the noninterference hypothesis is given. Furthermore, two methods are proposed that do not have the same limitations. The first method is based on autoregressive models with exogenous inputs, whereas the second one combines cross-spectral estimators with interpolation in the frequency domain. The two identification methods are validated by offline simulations and contrasted to the classic method. The results reveal that the classic method fails when the noninterference hypothesis is not fulfilled; on the contrary, the two proposed techniques give reliable estimates. Finally, the three identification methods are applied to experimental data from a closed-loop control task with pilots. The two proposed techniques give comparable estimates, different from those obtained by the classic method. The differences match those found with the simulations. Thus, the two identification methods provide a good alternative to the classic method and make it possible to simultaneously estimate human's neuromuscular and visual responses in cases where the classic method fails.

Simultaneous voltammetric determination of dopamine and epinephrine in human body fluid samples using a glassy carbon electrode modified with nickel oxide nanoparticles and carbon nanotubes within a dihexadecylphosphate film.

PubMed

Figueiredo-Filho, Luiz C S; Silva, Tiago A; Vicentini, Fernando C; Fatibello-Filho, Orlando

2014-06-07

A simple and highly selective electrochemical method was developed for the single or simultaneous determination of dopamine (DA) and epinephrine (EP) in human body fluids using a glassy carbon electrode modified with nickel oxide nanoparticles and carbon nanotubes within a dihexadecylphosphate film using square-wave voltammetry (SWV) or differential-pulse voltammetry (DPV). Using DPV with the proposed electrode, a separation of ca. 360 mV between the peak reduction potentials of DA and EP present in binary mixtures was obtained. The analytical curves for the simultaneous determination of dopamine and epinephrine showed an excellent linear response, ranging from 7.0 × 10(-8) to 4.8 × 10(-6) and 3.0 × 10(-7) to 9.5 × 10(-6) mol L(-1) for DA and EP, respectively. The detection limits for the simultaneous determination of DA and EP were 5.0 × 10(-8) mol L(-1) and 8.2 × 10(-8) mol L(-1), respectively. The proposed method was successfully applied in the simultaneous determination of these analytes in human body fluid samples of cerebrospinal fluid, human serum and lung fluid.

Identifying hidden common causes from bivariate time series: a method using recurrence plots.

PubMed

Hirata, Yoshito; Aihara, Kazuyuki

2010-01-01

We propose a method for inferring the existence of hidden common causes from observations of bivariate time series. We detect related time series by excessive simultaneous recurrences in the corresponding recurrence plots. We also use a noncoverage property of a recurrence plot by the other to deny the existence of a directional coupling. We apply the proposed method to real wind data.

Simultaneous gas chromatographic determination of chlorpyrifos and its impurity sulfotep in liquid pesticide formulations.

PubMed

Płonka, Marlena; Walorczyk, Stanisław; Miszczyk, Marek; Kronenbach-Dylong, Dorota

2016-11-01

An analytical method for simultaneous determination of the active substance (chlorpyrifos) and its relevant impurity (sulfotep) in commercial pesticide formulations has been developed and validated. The proposed method entails extraction of the analytes from samples by sonication with acetone and analysis by gas chromatography-flame ionization detection (GC-FID). The proposed method was characterized by satisfactory accuracy and precision. The repeatability expressed as relative standard deviation (RSD) was lower than the acceptable values calculated from the modified Horwitz equation whereas individual recoveries were in the range of 98-102% and 80-120% for chlorpyrifos and sulfotep, respectively. The limit of quantification (LOQ) for the impurity (sulfotep) was 0.003 mg mL(-1) corresponding to the maximum permitted level according to Food and Agricultural Organization of the United Nations (FAO) specifications for the active substance (chlorpyrifos) being 3 g kg(-1) of the chlorpyrifos content found. The main advantage of the proposed method was a considerable reduction in the analysis time since both analytes were determined based on a single injection into the GC-FID. Analysis of real samples of commercial pesticide formulations confirmed fitness-for-purpose of the proposed method.

Fourth-order derivative spectrophotometric method for simultaneous determination of pseudoephedrine and naproxen in pharmaceutical dosage forms

PubMed Central

Souri, Effat; Mosafer, Amir; Tehrani, Maliheh Barazandeh

2016-01-01

Combination dosage forms of naproxen sodium and pseudoephedrine hydrochloride are used for symptomatic treatment of cold and sinus disorders. In this study, fourth-order derivative spectrophotometric method was used for simultaneous determination of naproxen sodium and pseudoephedrine hydrochloride. The method was linear over the range of 2-28 μg/ml for pseudoephedrine hydrochloride and 4-200 μg/ml for naproxen sodium. The within-day and between-day coefficient of variation values were less than 5.8% and 2.5% for pseudoephedrine hydrochloride and naproxen sodium, respectively. The application of the proposed method for simultaneous determination of naproxen and pseudoephedrine in dosage forms was demonstrated without any special pretreatment. PMID:27168748

A "three-in-one" sample preparation method for simultaneous determination of B-group water-soluble vitamins in infant formula using VitaFast(®) kits.

PubMed

Zhang, Heng; Lan, Fang; Shi, Yupeng; Wan, Zhi-Gang; Yue, Zhen-Feng; Fan, Fang; Lin, Yan-Kui; Tang, Mu-Jin; Lv, Jing-Zhang; Xiao, Tan; Yi, Changqing

2014-06-15

VitaFast(®) test kits designed for the microbiological assay in microtiter plate format can be applied to quantitative determination of B-group water-soluble vitamins such as vitamin B12, folic acid and biotin, et al. Compared to traditional microbiological methods, VitaFast(®) kits significantly reduce sample processing time and provide greater reliability, higher productivity and better accuracy. Recently, simultaneous determination of vitamin B12, folic acid and biotin in one sample is urgently required when evaluating the quality of infant formulae in our practical work. However, the present sample preparation protocols which are developed for individual test systems, are incompatible with simultaneous determination of several analytes. To solve this problem, a novel "three-in-one" sample preparation method is herein developed for simultaneous determination of B-group water-soluble vitamins using VitaFast(®) kits. The performance of this novel "three-in-one" sample preparation method was systematically evaluated through comparing with individual sample preparation protocols. The experimental results of the assays which employed "three-in-one" sample preparation method were in good agreement with those obtained from conventional VitaFast(®) extraction methods, indicating that the proposed "three-in-one" sample preparation method is applicable to the present three VitaFast(®) vitamin test systems, thus offering a promising alternative for the three independent sample preparation methods. The proposed new sample preparation method will significantly improve the efficiency of infant formulae inspection. Copyright © 2013 Elsevier Ltd. All rights reserved.

Simultaneous determination of selected biogenic amines in alcoholic beverage samples by isotachophoretic and chromatographic methods.

PubMed

Jastrzębska, Aneta; Piasta, Anna; Szłyk, Edward

2014-01-01

A simple and useful method for the determination of biogenic amines in beverage samples based on isotachophoretic separation is described. The proposed procedure permitted simultaneous analysis of histamine, tyramine, cadaverine, putrescine, tryptamine, 2-phenylethylamine, spermine and spermidine. The data presented demonstrate the utility, simplicity, flexibility, sensitivity and environmentally friendly character of the proposed method. The precision of the method expressed as coefficient of variations varied from 0.1% to 5.9% for beverage samples, whereas recoveries varied from 91% to 101%. The results for the determination of biogenic amines were compared with an HPLC procedure based on a pre-column derivatisation reaction of biogenic amines with dansyl chloride. Furthermore, the derivatisation procedure was optimised by verification of concentration and pH of the buffer, the addition of organic solvents, reaction time and temperature.

A comparative study of smart spectrophotometric methods for simultaneous determination of a skeletal muscle relaxant and an analgesic in combined dosage form.

PubMed

Salem, Hesham; Mohamed, Dalia

2015-04-05

Six simple, specific, accurate and precise spectrophotometric methods were developed and validated for the simultaneous determination of the analgesic drug; paracetamol (PARA) and the skeletal muscle relaxant; dantrolene sodium (DANT). Three methods are manipulating ratio spectra namely; ratio difference (RD), ratio subtraction (RS) and mean centering (MC). The other three methods are utilizing the isoabsorptive point either at zero order namely; absorbance ratio (AR) and absorbance subtraction (AS) or at ratio spectrum namely; amplitude modulation (AM). The proposed spectrophotometric procedures do not require any preliminary separation step. The accuracy, precision and linearity ranges of the proposed methods were determined. The selectivity of the developed methods was investigated by analyzing laboratory prepared mixtures of the drugs and their combined dosage form. Standard deviation values are less than 1.5 in the assay of raw materials and capsules. The obtained results were statistically compared with each other and with those of reported spectrophotometric ones. The comparison showed that there is no significant difference between the proposed methods and the reported methods regarding both accuracy and precision. Copyright © 2015 Elsevier B.V. All rights reserved.

Global Output-Feedback Control for Simultaneous Tracking and Stabilization of Wheeled Mobile Robots

NASA Astrophysics Data System (ADS)

Chang, J.; Zhang, L. J.; Xue, D.

A time-varying global output-feedback controller is presented that solves both tracking and stabilization for wheeled mobile robots simultaneously at the torque level. The controller synthesis is based on a coordinate transformation, Lyapunov direct method and backstepping technique. The performance of the proposed controller is demonstrated by simulation.

Spectral characterization of near-infrared acousto-optic tunable filter (AOTF) hyperspectral imaging systems using standard calibration materials.

PubMed

Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2011-04-01

In this study, we propose and evaluate a method for spectral characterization of acousto-optic tunable filter (AOTF) hyperspectral imaging systems in the near-infrared (NIR) spectral region from 900 nm to 1700 nm. The proposed spectral characterization method is based on the SRM-2035 standard reference material, exhibiting distinct spectral features, which enables robust non-rigid matching of the acquired and reference spectra. The matching is performed by simultaneously optimizing the parameters of the AOTF tuning curve, spectral resolution, baseline, and multiplicative effects. In this way, the tuning curve (frequency-wavelength characteristics) and the corresponding spectral resolution of the AOTF hyperspectral imaging system can be characterized simultaneously. Also, the method enables simple spectral characterization of the entire imaging plane of hyperspectral imaging systems. The results indicate that the method is accurate and efficient and can easily be integrated with systems operating in diffuse reflection or transmission modes. Therefore, the proposed method is suitable for characterization, calibration, or validation of AOTF hyperspectral imaging systems. © 2011 Society for Applied Spectroscopy

Simultaneous digital super-resolution and nonuniformity correction for infrared imaging systems.

PubMed

Meza, Pablo; Machuca, Guillermo; Torres, Sergio; Martin, Cesar San; Vera, Esteban

2015-07-20

In this article, we present a novel algorithm to achieve simultaneous digital super-resolution and nonuniformity correction from a sequence of infrared images. We propose to use spatial regularization terms that exploit nonlocal means and the absence of spatial correlation between the scene and the nonuniformity noise sources. We derive an iterative optimization algorithm based on a gradient descent minimization strategy. Results from infrared image sequences corrupted with simulated and real fixed-pattern noise show a competitive performance compared with state-of-the-art methods. A qualitative analysis on the experimental results obtained with images from a variety of infrared cameras indicates that the proposed method provides super-resolution images with significantly less fixed-pattern noise.

Efficient sidelobe ASK based dual-function radar-communications

NASA Astrophysics Data System (ADS)

Hassanien, Aboulnasr; Amin, Moeness G.; Zhang, Yimin D.; Ahmad, Fauzia

2016-05-01

Recently, dual-function radar-communications (DFRC) has been proposed as means to mitigate the spectrum congestion problem. Existing amplitude-shift keying (ASK) methods for information embedding do not take full advantage of the highest permissable sidelobe level. In this paper, a new ASK-based signaling strategy for enhancing the signal-to-noise ratio (SNR) at the communication receiver is proposed. The proposed method employs one reference waveform and simultaneously transmits a number of orthogonal waveforms equals to the number of 1's in the binary sequence being embedded. 3 dB SNR gain is achieved using the proposed method as compared to existing sidelobe ASK methods. The effectiveness of the proposed information embedding strategy is verified using simulations examples.

Evaluating the efficiency of spectral resolution of univariate methods manipulating ratio spectra and comparing to multivariate methods: An application to ternary mixture in common cold preparation

NASA Astrophysics Data System (ADS)

Moustafa, Azza Aziz; Salem, Hesham; Hegazy, Maha; Ali, Omnia

2015-02-01

Simple, accurate, and selective methods have been developed and validated for simultaneous determination of a ternary mixture of Chlorpheniramine maleate (CPM), Pseudoephedrine HCl (PSE) and Ibuprofen (IBF), in tablet dosage form. Four univariate methods manipulating ratio spectra were applied, method A is the double divisor-ratio difference spectrophotometric method (DD-RD). Method B is double divisor-derivative ratio spectrophotometric method (DD-RD). Method C is derivative ratio spectrum-zero crossing method (DRZC), while method D is mean centering of ratio spectra (MCR). Two multivariate methods were also developed and validated, methods E and F are Principal Component Regression (PCR) and Partial Least Squares (PLSs). The proposed methods have the advantage of simultaneous determination of the mentioned drugs without prior separation steps. They were successfully applied to laboratory-prepared mixtures and to commercial pharmaceutical preparation without any interference from additives. The proposed methods were validated according to the ICH guidelines. The obtained results were statistically compared with the official methods where no significant difference was observed regarding both accuracy and precision.

Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

PubMed

Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

2016-10-05

Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

Estimation of the viscous properties of skin and subcutaneous tissue in uniaxial stress relaxation tests.

PubMed

Wu, John Z; Cutlip, Robert G; Welcome, Daniel; Dong, Ren G

2006-01-01

Knowledge of viscoelastic properties of soft tissues is essential for the finite element modelling of the stress/strain distributions in finger-pad during vibratory loading, which is important in exploring the mechanism of hand-arm vibration syndrome. In conventional procedures, skin and subcutaneous tissue have to be separated for testing the viscoelastic properties. In this study, a novel method has been proposed to simultaneously determine the viscoelastic properties of skin and subcutaneous tissue in uniaxial stress relaxation tests. A mathematical approach has been derived to obtain the creep and relaxation characteristics of skin and subcutaneous tissue using uniaxial stress relaxation data of skin/subcutaneous composite specimens. The micro-structures of collagen fiber networks in the soft tissue, which underline the tissue mechanical characteristics, will be intact in the proposed method. Therefore, the viscoelastic properties of soft tissues obtained using the proposed method would be more physiologically relevant than those obtained using the conventional method. The proposed approach has been utilized to measure the viscoelastic properties of soft tissues of pig. The relaxation curves of pig skin and subcutaneous tissue obtained in the current study agree well with those in literature. Using the proposed approach, reliable material properties of soft tissues can be obtained in a cost- and time-efficient manner, which simultaneously improves the physiological relevance.

Simultaneous spectrophotometric determination of indacaterol and glycopyrronium in a newly approved pharmaceutical formulation using different signal processing techniques of ratio spectra

NASA Astrophysics Data System (ADS)

Abdel Ghany, Maha F.; Hussein, Lobna A.; Magdy, Nancy; Yamani, Hend Z.

2016-03-01

Three spectrophotometric methods have been developed and validated for determination of indacaterol (IND) and glycopyrronium (GLY) in their binary mixtures and novel pharmaceutical dosage form. The proposed methods are considered to be the first methods to determine the investigated drugs simultaneously. The developed methods are based on different signal processing techniques of ratio spectra namely; Numerical Differentiation (ND), Savitsky-Golay (SG) and Fourier Transform (FT). The developed methods showed linearity over concentration range 1-30 and 10-35 (μg/mL) for IND and GLY, respectively. The accuracy calculated as percentage recoveries were in the range of 99.00%-100.49% with low value of RSD% (< 1.5%) demonstrating an excellent accuracy of the proposed methods. The developed methods were proved to be specific, sensitive and precise for quality control of the investigated drugs in their pharmaceutical dosage form without the need for any separation process.

Visual measurement of the evaporation process of a sessile droplet by dual-channel simultaneous phase-shifting interferometry.

PubMed

Sun, Peng; Zhong, Liyun; Luo, Chunshu; Niu, Wenhu; Lu, Xiaoxu

2015-07-16

To perform the visual measurement of the evaporation process of a sessile droplet, a dual-channel simultaneous phase-shifting interferometry (DCSPSI) method is proposed. Based on polarization components to simultaneously generate a pair of orthogonal interferograms with the phase shifts of π/2, the real-time phase of a dynamic process can be retrieved with two-step phase-shifting algorithm. Using this proposed DCSPSI system, the transient mass (TM) of the evaporation process of a sessile droplet with different initial mass were presented through measuring the real-time 3D shape of a droplet. Moreover, the mass flux density (MFD) of the evaporating droplet and its regional distribution were also calculated and analyzed. The experimental results show that the proposed DCSPSI will supply a visual, accurate, noncontact, nondestructive, global tool for the real-time multi-parameter measurement of the droplet evaporation.

A simple model to predict the biodiesel blend density as simultaneous function of blend percent and temperature.

PubMed

Gaonkar, Narayan; Vaidya, R G

2016-05-01

A simple method to estimate the density of biodiesel blend as simultaneous function of temperature and volume percent of biodiesel is proposed. Employing the Kay's mixing rule, we developed a model and investigated theoretically the density of different vegetable oil biodiesel blends as a simultaneous function of temperature and volume percent of biodiesel. Key advantage of the proposed model is that it requires only a single set of density values of components of biodiesel blends at any two different temperatures. We notice that the density of blend linearly decreases with increase in temperature and increases with increase in volume percent of the biodiesel. The lower values of standard estimate of error (SEE = 0.0003-0.0022) and absolute average deviation (AAD = 0.03-0.15 %) obtained using the proposed model indicate the predictive capability. The predicted values found good agreement with the recent available experimental data.

Bivariate versus multivariate smart spectrophotometric calibration methods for the simultaneous determination of a quaternary mixture of mosapride, pantoprazole and their degradation products.

PubMed

Hegazy, M A; Yehia, A M; Moustafa, A A

2013-05-01

The ability of bivariate and multivariate spectrophotometric methods was demonstrated in the resolution of a quaternary mixture of mosapride, pantoprazole and their degradation products. The bivariate calibrations include bivariate spectrophotometric method (BSM) and H-point standard addition method (HPSAM), which were able to determine the two drugs, simultaneously, but not in the presence of their degradation products, the results showed that simultaneous determinations could be performed in the concentration ranges of 5.0-50.0 microg/ml for mosapride and 10.0-40.0 microg/ml for pantoprazole by bivariate spectrophotometric method and in the concentration ranges of 5.0-45.0 microg/ml for both drugs by H-point standard addition method. Moreover, the applied multivariate calibration methods were able for the determination of mosapride, pantoprazole and their degradation products using concentration residuals augmented classical least squares (CRACLS) and partial least squares (PLS). The proposed multivariate methods were applied to 17 synthetic samples in the concentration ranges of 3.0-12.0 microg/ml mosapride, 8.0-32.0 microg/ml pantoprazole, 1.5-6.0 microg/ml mosapride degradation products and 2.0-8.0 microg/ml pantoprazole degradation products. The proposed bivariate and multivariate calibration methods were successfully applied to the determination of mosapride and pantoprazole in their pharmaceutical preparations.

Integral reinforcement learning for continuous-time input-affine nonlinear systems with simultaneous invariant explorations.

PubMed

Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

2015-05-01

This paper focuses on a class of reinforcement learning (RL) algorithms, named integral RL (I-RL), that solve continuous-time (CT) nonlinear optimal control problems with input-affine system dynamics. First, we extend the concepts of exploration, integral temporal difference, and invariant admissibility to the target CT nonlinear system that is governed by a control policy plus a probing signal called an exploration. Then, we show input-to-state stability (ISS) and invariant admissibility of the closed-loop systems with the policies generated by integral policy iteration (I-PI) or invariantly admissible PI (IA-PI) method. Based on these, three online I-RL algorithms named explorized I-PI and integral Q -learning I, II are proposed, all of which generate the same convergent sequences as I-PI and IA-PI under the required excitation condition on the exploration. All the proposed methods are partially or completely model free, and can simultaneously explore the state space in a stable manner during the online learning processes. ISS, invariant admissibility, and convergence properties of the proposed methods are also investigated, and related with these, we show the design principles of the exploration for safe learning. Neural-network-based implementation methods for the proposed schemes are also presented in this paper. Finally, several numerical simulations are carried out to verify the effectiveness of the proposed methods.

Online Solution of Two-Player Zero-Sum Games for Continuous-Time Nonlinear Systems With Completely Unknown Dynamics.

PubMed

Fu, Yue; Chai, Tianyou

2016-12-01

Regarding two-player zero-sum games of continuous-time nonlinear systems with completely unknown dynamics, this paper presents an online adaptive algorithm for learning the Nash equilibrium solution, i.e., the optimal policy pair. First, for known systems, the simultaneous policy updating algorithm (SPUA) is reviewed. A new analytical method to prove the convergence is presented. Then, based on the SPUA, without using a priori knowledge of any system dynamics, an online algorithm is proposed to simultaneously learn in real time either the minimal nonnegative solution of the Hamilton-Jacobi-Isaacs (HJI) equation or the generalized algebraic Riccati equation for linear systems as a special case, along with the optimal policy pair. The approximate solution to the HJI equation and the admissible policy pair is reexpressed by the approximation theorem. The unknown constants or weights of each are identified simultaneously by resorting to the recursive least square method. The convergence of the online algorithm to the optimal solutions is provided. A practical online algorithm is also developed. Simulation results illustrate the effectiveness of the proposed method.

Frequency-domain elastic full waveform inversion using encoded simultaneous sources

NASA Astrophysics Data System (ADS)

Jeong, W.; Son, W.; Pyun, S.; Min, D.

2011-12-01

Currently, numerous studies have endeavored to develop robust full waveform inversion and migration algorithms. These processes require enormous computational costs, because of the number of sources in the survey. To avoid this problem, the phase encoding technique for prestack migration was proposed by Romero (2000) and Krebs et al. (2009) proposed the encoded simultaneous-source inversion technique in the time domain. On the other hand, Ben-Hadj-Ali et al. (2011) demonstrated the robustness of the frequency-domain full waveform inversion with simultaneous sources for noisy data changing the source assembling. Although several studies on simultaneous-source inversion tried to estimate P- wave velocity based on the acoustic wave equation, seismic migration and waveform inversion based on the elastic wave equations are required to obtain more reliable subsurface information. In this study, we propose a 2-D frequency-domain elastic full waveform inversion technique using phase encoding methods. In our algorithm, the random phase encoding method is employed to calculate the gradients of the elastic parameters, source signature estimation and the diagonal entries of approximate Hessian matrix. The crosstalk for the estimated source signature and the diagonal entries of approximate Hessian matrix are suppressed with iteration as for the gradients. Our 2-D frequency-domain elastic waveform inversion algorithm is composed using the back-propagation technique and the conjugate-gradient method. Source signature is estimated using the full Newton method. We compare the simultaneous-source inversion with the conventional waveform inversion for synthetic data sets of the Marmousi-2 model. The inverted results obtained by simultaneous sources are comparable to those obtained by individual sources, and source signature is successfully estimated in simultaneous source technique. Comparing the inverted results using the pseudo Hessian matrix with previous inversion results provided by the approximate Hessian matrix, it is noted that the latter are better than the former for deeper parts of the model. This work was financially supported by the Brain Korea 21 project of Energy System Engineering, by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0006155), by the Energy Efficiency & Resources of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Knowledge Economy (No. 2010T100200133).

Simultaneous maximum a posteriori longitudinal PET image reconstruction

NASA Astrophysics Data System (ADS)

Ellis, Sam; Reader, Andrew J.

2017-09-01

Positron emission tomography (PET) is frequently used to monitor functional changes that occur over extended time scales, for example in longitudinal oncology PET protocols that include routine clinical follow-up scans to assess the efficacy of a course of treatment. In these contexts PET datasets are currently reconstructed into images using single-dataset reconstruction methods. Inspired by recently proposed joint PET-MR reconstruction methods, we propose to reconstruct longitudinal datasets simultaneously by using a joint penalty term in order to exploit the high degree of similarity between longitudinal images. We achieved this by penalising voxel-wise differences between pairs of longitudinal PET images in a one-step-late maximum a posteriori (MAP) fashion, resulting in the MAP simultaneous longitudinal reconstruction (SLR) method. The proposed method reduced reconstruction errors and visually improved images relative to standard maximum likelihood expectation-maximisation (ML-EM) in simulated 2D longitudinal brain tumour scans. In reconstructions of split real 3D data with inserted simulated tumours, noise across images reconstructed with MAP-SLR was reduced to levels equivalent to doubling the number of detected counts when using ML-EM. Furthermore, quantification of tumour activities was largely preserved over a variety of longitudinal tumour changes, including changes in size and activity, with larger changes inducing larger biases relative to standard ML-EM reconstructions. Similar improvements were observed for a range of counts levels, demonstrating the robustness of the method when used with a single penalty strength. The results suggest that longitudinal regularisation is a simple but effective method of improving reconstructed PET images without using resolution degrading priors.

Measurement system and model for simultaneously measuring 6DOF geometric errors.

PubMed

Zhao, Yuqiong; Zhang, Bin; Feng, Qibo

2017-09-04

A measurement system to simultaneously measure six degree-of-freedom (6DOF) geometric errors is proposed. The measurement method is based on a combination of mono-frequency laser interferometry and laser fiber collimation. A simpler and more integrated optical configuration is designed. To compensate for the measurement errors introduced by error crosstalk, element fabrication error, laser beam drift, and nonparallelism of two measurement beam, a unified measurement model, which can improve the measurement accuracy, is deduced and established using the ray-tracing method. A numerical simulation using the optical design software Zemax is conducted, and the results verify the correctness of the model. Several experiments are performed to demonstrate the feasibility and effectiveness of the proposed system and measurement model.

Neural network based online simultaneous policy update algorithm for solving the HJI equation in nonlinear H∞ control.

PubMed

Wu, Huai-Ning; Luo, Biao

2012-12-01

It is well known that the nonlinear H∞ state feedback control problem relies on the solution of the Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation that has proven to be impossible to solve analytically. In this paper, a neural network (NN)-based online simultaneous policy update algorithm (SPUA) is developed to solve the HJI equation, in which knowledge of internal system dynamics is not required. First, we propose an online SPUA which can be viewed as a reinforcement learning technique for two players to learn their optimal actions in an unknown environment. The proposed online SPUA updates control and disturbance policies simultaneously; thus, only one iterative loop is needed. Second, the convergence of the online SPUA is established by proving that it is mathematically equivalent to Newton's method for finding a fixed point in a Banach space. Third, we develop an actor-critic structure for the implementation of the online SPUA, in which only one critic NN is needed for approximating the cost function, and a least-square method is given for estimating the NN weight parameters. Finally, simulation studies are provided to demonstrate the effectiveness of the proposed algorithm.

Simultaneous Rapid Determination of the Solubility and Diffusion Coefficients of a Poorly Water-Soluble Drug Based on a Novel UV Imaging System.

PubMed

Lu, Yan; Li, Mingzhong

2016-01-01

The solubility and diffusion coefficient are two of the most important physicochemical properties of a drug compound. In practice, both have been measured separately, which is time consuming. This work utilizes a novel technique of UV imaging to determine the solubility and diffusion coefficients of poorly water-soluble drugs simultaneously. A 2-step optimal method is proposed to determine the solubility and diffusion coefficients of a poorly water-soluble pharmaceutical substance based on the Fick's second law of diffusion and UV imaging measurements. Experimental results demonstrate that the proposed method can be used to determine the solubility and diffusion coefficients of a drug with reasonable accuracy, indicating that UV imaging may provide a new opportunity to accurately measure the solubility and diffusion coefficients of a poorly water-soluble drug simultaneously and rapidly. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Robust extraction of basis functions for simultaneous and proportional myoelectric control via sparse non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Lin, Chuang; Wang, Binghui; Jiang, Ning; Farina, Dario

2018-04-01

Objective. This paper proposes a novel simultaneous and proportional multiple degree of freedom (DOF) myoelectric control method for active prostheses. Approach. The approach is based on non-negative matrix factorization (NMF) of surface EMG signals with the inclusion of sparseness constraints. By applying a sparseness constraint to the control signal matrix, it is possible to extract the basis information from arbitrary movements (quasi-unsupervised approach) for multiple DOFs concurrently. Main Results. In online testing based on target hitting, able-bodied subjects reached a greater throughput (TP) when using sparse NMF (SNMF) than with classic NMF or with linear regression (LR). Accordingly, the completion time (CT) was shorter for SNMF than NMF or LR. The same observations were made in two patients with unilateral limb deficiencies. Significance. The addition of sparseness constraints to NMF allows for a quasi-unsupervised approach to myoelectric control with superior results with respect to previous methods for the simultaneous and proportional control of multi-DOF. The proposed factorization algorithm allows robust simultaneous and proportional control, is superior to previous supervised algorithms, and, because of minimal supervision, paves the way to online adaptation in myoelectric control.

Simultaneous stable carbon isotopic analysis of wine glycerol and ethanol by liquid chromatography coupled to isotope ratio mass spectrometry.

PubMed

Cabañero, Ana I; Recio, Jose L; Rupérez, Mercedes

2010-01-27

A novel procedure was established for the simultaneous characterization of wine glycerol and ethanol (13)C/(12)C isotope ratio, using liquid chromatography/isotope ratio mass spectrometry (LC-IRMS). Several parameters influencing separation of glycerol and ethanol from wine matrix were optimized. Results obtained for 35 Spanish samples exposed no significant differences and very strong correlations (r = 0.99) between the glycerol (13)C/(12)C ratios obtained by an alternative method (gas chromatography/isotope ratio mass spectrometry) and the proposed new methodology, and between the ethanol (13)C/(12)C ratios obtained by the official method (elemental analyzer/isotope ratio mass spectrometry) and the proposed new methodology. The accuracy of the proposed method varied from 0.01 to 0.19 per thousand, and the analytical precision was better than 0.25 per thousand. The new developed LC-IRMS method it is the first isotopic method that allows (13)C/(12)C determination of both analytes in the same run directly from a liquid sample with no previous glycerol or ethanol isolation, overcoming technical difficulties associated with complex sample treatment and improving in terms of simplicity and speed.

SIRF: Simultaneous Satellite Image Registration and Fusion in a Unified Framework.

PubMed

Chen, Chen; Li, Yeqing; Liu, Wei; Huang, Junzhou

2015-11-01

In this paper, we propose a novel method for image fusion with a high-resolution panchromatic image and a low-resolution multispectral (Ms) image at the same geographical location. The fusion is formulated as a convex optimization problem which minimizes a linear combination of a least-squares fitting term and a dynamic gradient sparsity regularizer. The former is to preserve accurate spectral information of the Ms image, while the latter is to keep sharp edges of the high-resolution panchromatic image. We further propose to simultaneously register the two images during the fusing process, which is naturally achieved by virtue of the dynamic gradient sparsity property. An efficient algorithm is then devised to solve the optimization problem, accomplishing a linear computational complexity in the size of the output image in each iteration. We compare our method against six state-of-the-art image fusion methods on Ms image data sets from four satellites. Extensive experimental results demonstrate that the proposed method substantially outperforms the others in terms of both spatial and spectral qualities. We also show that our method can provide high-quality products from coarsely registered real-world IKONOS data sets. Finally, a MATLAB implementation is provided to facilitate future research.

Simultaneous prediction of enzyme orthologs from chemical transformation patterns for de novo metabolic pathway reconstruction

PubMed Central

Tabei, Yasuo; Yamanishi, Yoshihiro; Kotera, Masaaki

2016-01-01

Motivation: Metabolic pathways are an important class of molecular networks consisting of compounds, enzymes and their interactions. The understanding of global metabolic pathways is extremely important for various applications in ecology and pharmacology. However, large parts of metabolic pathways remain unknown, and most organism-specific pathways contain many missing enzymes. Results: In this study we propose a novel method to predict the enzyme orthologs that catalyze the putative reactions to facilitate the de novo reconstruction of metabolic pathways from metabolome-scale compound sets. The algorithm detects the chemical transformation patterns of substrate–product pairs using chemical graph alignments, and constructs a set of enzyme-specific classifiers to simultaneously predict all the enzyme orthologs that could catalyze the putative reactions of the substrate–product pairs in the joint learning framework. The originality of the method lies in its ability to make predictions for thousands of enzyme orthologs simultaneously, as well as its extraction of enzyme-specific chemical transformation patterns of substrate–product pairs. We demonstrate the usefulness of the proposed method by applying it to some ten thousands of metabolic compounds, and analyze the extracted chemical transformation patterns that provide insights into the characteristics and specificities of enzymes. The proposed method will open the door to both primary (central) and secondary metabolism in genomics research, increasing research productivity to tackle a wide variety of environmental and public health matters. Availability and Implementation: Contact: maskot@bio.titech.ac.jp PMID:27307627

Simultaneous Two-Way Clustering of Multiple Correspondence Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Dillon, William R.

2010-01-01

A 2-way clustering approach to multiple correspondence analysis is proposed to account for cluster-level heterogeneity of both respondents and variable categories in multivariate categorical data. Specifically, in the proposed method, multiple correspondence analysis is combined with k-means in a unified framework in which "k"-means is…

[Joint correction for motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging].

PubMed

Wu, Wenchuan; Fang, Sheng; Guo, Hua

2014-06-01

Aiming at motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging (MRI), we proposed a joint correction method in this paper to correct the two kinds of artifacts simultaneously without additional acquisition of navigation data and field map. We utilized the proposed method using multi-shot variable density spiral sequence to acquire MRI data and used auto-focusing technique for image deblurring. We also used direct method or iterative method to correct motion induced phase errors in the process of deblurring. In vivo MRI experiments demonstrated that the proposed method could effectively suppress motion artifacts and off-resonance artifacts and achieve images with fine structures. In addition, the scan time was not increased in applying the proposed method.

Analytical Eco-Scale for Assessing the Greenness of a Developed RP-HPLC Method Used for Simultaneous Analysis of Combined Antihypertensive Medications.

PubMed

Mohamed, Heba M; Lamie, Nesrine T

2016-09-01

In the past few decades the analytical community has been focused on eliminating or reducing the usage of hazardous chemicals and solvents, in different analytical methodologies, that have been ascertained to be extremely dangerous to human health and environment. In this context, environmentally friendly, green, or clean practices have been implemented in different research areas. This study presents a greener alternative of conventional RP-HPLC methods for the simultaneous determination and quantitative analysis of a pharmaceutical ternary mixture composed of telmisartan, hydrochlorothiazide, and amlodipine besylate, using an ecofriendly mobile phase and short run time with the least amount of waste production. This solvent-replacement approach was feasible without compromising method performance criteria, such as separation efficiency, peak symmetry, and chromatographic retention. The greenness profile of the proposed method was assessed and compared with reported conventional methods using the analytical Eco-Scale as an assessment tool. The proposed method was found to be greener in terms of usage of hazardous chemicals and solvents, energy consumption, and production of waste. The proposed method can be safely used for the routine analysis of the studied pharmaceutical ternary mixture with a minimal detrimental impact on human health and the environment.

Method of Making Large Area Nanostructures

NASA Technical Reports Server (NTRS)

Marks, Alvin M.

1995-01-01

A method which enables the high speed formation of nanostructures on large area surfaces is described. The method uses a super sub-micron beam writer (Supersebter). The Supersebter uses a large area multi-electrode (Spindt type emitter source) to produce multiple electron beams simultaneously scanned to form a pattern on a surface in an electron beam writer. A 100,000 x 100,000 array of electron point sources, demagnified in a long electron beam writer to simultaneously produce 10 billion nano-patterns on a 1 meter squared surface by multi-electron beam impact on a 1 cm squared surface of an insulating material is proposed.

Limited angle CT reconstruction by simultaneous spatial and Radon domain regularization based on TV and data-driven tight frame

NASA Astrophysics Data System (ADS)

Zhang, Wenkun; Zhang, Hanming; Wang, Linyuan; Cai, Ailong; Li, Lei; Yan, Bin

2018-02-01

Limited angle computed tomography (CT) reconstruction is widely performed in medical diagnosis and industrial testing because of the size of objects, engine/armor inspection requirements, and limited scan flexibility. Limited angle reconstruction necessitates usage of optimization-based methods that utilize additional sparse priors. However, most of conventional methods solely exploit sparsity priors of spatial domains. When CT projection suffers from serious data deficiency or various noises, obtaining reconstruction images that meet the requirement of quality becomes difficult and challenging. To solve this problem, this paper developed an adaptive reconstruction method for limited angle CT problem. The proposed method simultaneously uses spatial and Radon domain regularization model based on total variation (TV) and data-driven tight frame. Data-driven tight frame being derived from wavelet transformation aims at exploiting sparsity priors of sinogram in Radon domain. Unlike existing works that utilize pre-constructed sparse transformation, the framelets of the data-driven regularization model can be adaptively learned from the latest projection data in the process of iterative reconstruction to provide optimal sparse approximations for given sinogram. At the same time, an effective alternating direction method is designed to solve the simultaneous spatial and Radon domain regularization model. The experiments for both simulation and real data demonstrate that the proposed algorithm shows better performance in artifacts depression and details preservation than the algorithms solely using regularization model of spatial domain. Quantitative evaluations for the results also indicate that the proposed algorithm applying learning strategy performs better than the dual domains algorithms without learning regularization model

SU-C-9A-03: Simultaneous Deconvolution and Segmentation for PET Tumor Delineation Using a Variational Method

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

Li, L; Tan, S; Lu, W

2014-06-01

Purpose: To implement a new method that integrates deconvolution with segmentation under the variational framework for PET tumor delineation. Methods: Deconvolution and segmentation are both challenging problems in image processing. The partial volume effect (PVE) makes tumor boundaries in PET image blurred which affects the accuracy of tumor segmentation. Deconvolution aims to obtain a PVE-free image, which can help to improve the segmentation accuracy. Conversely, a correct localization of the object boundaries is helpful to estimate the blur kernel, and thus assist in the deconvolution. In this study, we proposed to solve the two problems simultaneously using a variational methodmore » so that they can benefit each other. The energy functional consists of a fidelity term and a regularization term, and the blur kernel was limited to be the isotropic Gaussian kernel. We minimized the energy functional by solving the associated Euler-Lagrange equations and taking the derivative with respect to the parameters of the kernel function. An alternate minimization method was used to iterate between segmentation, deconvolution and blur-kernel recovery. The performance of the proposed method was tested on clinic PET images of patients with non-Hodgkin's lymphoma, and compared with seven other segmentation methods using the dice similarity index (DSI) and volume error (VE). Results: Among all segmentation methods, the proposed one (DSI=0.81, VE=0.05) has the highest accuracy, followed by the active contours without edges (DSI=0.81, VE=0.25), while other methods including the Graph Cut and the Mumford-Shah (MS) method have lower accuracy. A visual inspection shows that the proposed method localizes the real tumor contour very well. Conclusion: The result showed that deconvolution and segmentation can contribute to each other. The proposed variational method solve the two problems simultaneously, and leads to a high performance for tumor segmentation in PET. This work was supported in part by National Natural Science Foundation of China (NNSFC), under Grant Nos. 60971112 and 61375018, and Fundamental Research Funds for the Central Universities, under Grant No. 2012QN086. Wei Lu was supported in part by the National Institutes of Health (NIH) Grant No. R01 CA172638.« less

Foveation: an alternative method to simultaneously preserve privacy and information in face images

NASA Astrophysics Data System (ADS)

Alonso, Víctor E.; Enríquez-Caldera, Rogerio; Sucar, Luis Enrique

2017-03-01

This paper presents a real-time foveation technique proposed as an alternative method for image obfuscation while simultaneously preserving privacy in face deidentification. Relevance of the proposed technique is discussed through a comparative study of the most common distortions methods in face images and an assessment on performance and effectiveness of privacy protection. All the different techniques presented here are evaluated when they go through a face recognition software. Evaluating the data utility preservation was carried out under gender and facial expression classification. Results on quantifying the tradeoff between privacy protection and image information preservation at different obfuscation levels are presented. Comparative results using the facial expression subset of the FERET database show that the technique achieves a good tradeoff between privacy and awareness with 30% of recognition rate and a classification accuracy as high as 88% obtained from the common figures of merit using the privacy-awareness map.

Development of a new HPLC method for the simultaneous determination of ticarcillin and clavulanic acid in pharmaceutical formulations.

PubMed

Tsou, Tai-Li; Lee, Chiu-Wey; Wang, Hsian-Jenn; Cheng, Ya-Chung; Liu, Yu-Tien; Chen, Su-Hwei

2009-01-01

A new HPLC method has been developed and validated for the simultaneous determination of ticarcillin (TIC) and clavulanic acid (CA) in pharmaceutical formulations. The HPLC separation was achieved on a beta-cyclodextrin column (Cyclobond I, 250 x 4.6 mm, 5 microm) with methanol-16 mM pH 6.0 ammonium acetate buffer (50 + 50, v/v) mobile phase at a flow rate of 0.8 mL/min. Detection was at 220 nm. Validation of the method was performed by evaluating specificity, robustness, accuracy, and precision. The calibration curves were linear in the range of 1-100 microg/mL for CA and 2-200 microg/mL for TIC. The LOQs based on the standard regression lines were 0.42 and 1.42 microg/mL for CA and TIC, respectively, and the LOD were 0.14 and 0.47 microg/mL, respectively. Total recoveries of synthetic mixtures (CA:TIC = 1:10, 1:15, and 1:30) were 99.25-100.99% for CA and 99.54-100.82% for TIC. Compared with the U.S. Pharmacopeia method, the proposed method has the advantage of a relatively low flow rate and short analysis time. The proposed method was successfully applied for the simultaneous determination of these two drugs in sterilized H20 and 5% dextrose injection solutions.

Network immunization under limited budget using graph spectra

NASA Astrophysics Data System (ADS)

Zahedi, R.; Khansari, M.

2016-03-01

In this paper, we propose a new algorithm that minimizes the worst expected growth of an epidemic by reducing the size of the largest connected component (LCC) of the underlying contact network. The proposed algorithm is applicable to any level of available resources and, despite the greedy approaches of most immunization strategies, selects nodes simultaneously. In each iteration, the proposed method partitions the LCC into two groups. These are the best candidates for communities in that component, and the available resources are sufficient to separate them. Using Laplacian spectral partitioning, the proposed method performs community detection inference with a time complexity that rivals that of the best previous methods. Experiments show that our method outperforms targeted immunization approaches in both real and synthetic networks.

Direct and simultaneous estimation of cardiac four chamber volumes by multioutput sparse regression.

PubMed

Zhen, Xiantong; Zhang, Heye; Islam, Ali; Bhaduri, Mousumi; Chan, Ian; Li, Shuo

2017-02-01

Cardiac four-chamber volume estimation serves as a fundamental and crucial role in clinical quantitative analysis of whole heart functions. It is a challenging task due to the huge complexity of the four chambers including great appearance variations, huge shape deformation and interference between chambers. Direct estimation has recently emerged as an effective and convenient tool for cardiac ventricular volume estimation. However, existing direct estimation methods were specifically developed for one single ventricle, i.e., left ventricle (LV), or bi-ventricles; they can not be directly used for four chamber volume estimation due to the great combinatorial variability and highly complex anatomical interdependency of the four chambers. In this paper, we propose a new, general framework for direct and simultaneous four chamber volume estimation. We have addressed two key issues, i.e., cardiac image representation and simultaneous four chamber volume estimation, which enables accurate and efficient four-chamber volume estimation. We generate compact and discriminative image representations by supervised descriptor learning (SDL) which can remove irrelevant information and extract discriminative features. We propose direct and simultaneous four-chamber volume estimation by the multioutput sparse latent regression (MSLR), which enables jointly modeling nonlinear input-output relationships and capturing four-chamber interdependence. The proposed method is highly generalized, independent of imaging modalities, which provides a general regression framework that can be extensively used for clinical data prediction to achieve automated diagnosis. Experiments on both MR and CT images show that our method achieves high performance with a correlation coefficient of up to 0.921 with ground truth obtained manually by human experts, which is clinically significant and enables more accurate, convenient and comprehensive assessment of cardiac functions. Copyright © 2016 Elsevier B.V. All rights reserved.

Joint Feature Selection and Classification for Multilabel Learning.

PubMed

Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

2018-03-01

Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

Chemometrics-assisted simultaneous determination of cobalt(II) and chromium(III) with flow-injection chemiluminescence method

NASA Astrophysics Data System (ADS)

Li, Baoxin; Wang, Dongmei; Lv, Jiagen; Zhang, Zhujun

2006-09-01

In this paper, a flow-injection chemiluminescence (CL) system is proposed for simultaneous determination of Co(II) and Cr(III) with partial least squares calibration. This method is based on the fact that both Co(II) and Cr(III) catalyze the luminol-H 2O 2 CL reaction, and that their catalytic activities are significantly different on the same reaction condition. The CL intensity of Co(II) and Cr(III) was measured and recorded at different pH of reaction medium, and the obtained data were processed by the chemometric approach of partial least squares. The experimental calibration set was composed with nine sample solutions using orthogonal calibration design for two component mixtures. The calibration curve was linear over the concentration range of 2 × 10 -7 to 8 × 10 -10 and 2 × 10 -6 to 4 × 10 -9 g/ml for Co(II) and Cr(III), respectively. The proposed method offers the potential advantages of high sensitivity, simplicity and rapidity for Co(II) and Cr(III) determination, and was successfully applied to the simultaneous determination of both analytes in real water sample.

A sensitive and efficient method for trace analysis of some phenolic compounds using simultaneous derivatization and air-assisted liquid-liquid microextraction from human urine and plasma samples followed by gas chromatography-nitrogen phosphorous detection.

PubMed

Farajzadeh, Mir Ali; Afshar Mogaddam, Mohammad Reza; Alizadeh Nabil, Ali Akbar

2015-12-01

In present study, a simultaneous derivatization and air-assisted liquid-liquid microextraction method combined with gas chromatography-nitrogen phosphorous detection has been developed for the determination of some phenolic compounds in biological samples. The analytes are derivatized and extracted simultaneously by a fast reaction with 1-flouro-2,4-dinitrobenzene under mild conditions. Under optimal conditions low limits of detection in the range of 0.05-0.34 ng mL(-1) are achievable. The obtained extraction recoveries are between 84 and 97% and the relative standard deviations are less than 7.2% for intraday (n = 6) and interday (n = 4) precisions. The proposed method was demonstrated to be a simple and efficient method for the analysis of phenols in biological samples. Copyright © 2015 John Wiley & Sons, Ltd.

Simultaneous Tensor Decomposition and Completion Using Factor Priors.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting Candy; Liao, Hong-Yuan Mark

2013-08-27

Tensor completion, which is a high-order extension of matrix completion, has generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use either factorization or completion schemes to recover the missing parts. However, as the number of missing entries increases, factorization schemes may overfit the model because of incorrectly predefined ranks, while completion schemes may fail to interpret the model factors. In this paper, we introduce a novel concept: complete the missing entries and simultaneously capture the underlying model structure. To this end, we propose a method called Simultaneous Tensor Decomposition and Completion (STDC) that combines a rank minimization technique with Tucker model decomposition. Moreover, as the model structure is implicitly included in the Tucker model, we use factor priors, which are usually known a priori in real-world tensor objects, to characterize the underlying joint-manifold drawn from the model factors. We conducted experiments to empirically verify the convergence of our algorithm on synthetic data, and evaluate its effectiveness on various kinds of real-world data. The results demonstrate the efficacy of the proposed method and its potential usage in tensor-based applications. It also outperforms state-of-the-art methods on multilinear model analysis and visual data completion tasks.

Development of new method for simultaneous analysis of piracetam and levetiracetam in pharmaceuticals and biological fluids: application in stability studies.

PubMed

Siddiqui, Farhan Ahmed; Sher, Nawab; Shafi, Nighat; Wafa Sial, Alisha; Ahmad, Mansoor; Mehjebeen; Naseem, Huma

2014-01-01

RP-HPLC ultraviolet detection simultaneous quantification of piracetam and levetiracetam has been developed and validated. The chromatography was obtained on a Nucleosil C18 column of 25 cm×0.46 cm, 10 μm, dimension. The mobile phase was a (70:30 v/v) mixture of 0.1 g/L of triethylamine and acetonitrile. Smooth flow of mobile phase at 1 mL/min was set and 205 nm wavelength was selected. Results were evaluated through statistical parameters which qualify the method reproducibility and selectivity for the quantification of piracetam, levetiracetam, and their impurities hence proving stability-indicating properties. The proposed method is significantly important, permitting the separation of the main constituent piracetam from levetiracetam. Linear behavior was observed between 20 ng/mL and 10,000 ng/mL for both drugs. The proposed method was checked in bulk drugs, dosage formulations, physiological condition, and clinical investigations and excellent outcome was witnessed.

Simultaneous determination of amino acids and carbohydrates in culture media of Clostridium thermocellum by valve-switching ion chromatography.

PubMed

Fa, Yun; Yang, Haiyan; Ji, Chengshuai; Cui, He; Zhu, Xinshu; Du, Juan; Gao, Jun

2013-10-10

An improved method for the simultaneous determination of 20 amino acids and 7 carbohydrates using one-valve switching after injection, ion chromatography, and integrated pulsed amperometric detection is proposed. The resolution of the amino acids and carbohydrates in the cation trap column was investigated. In addition, parameters including flow liquid type, flow rate, concentration, and valve-switch timing were optimized. The method is time-saving, effective, and accurate for the simultaneous separation of amino acids and carbohydrates, with a mean correlation coefficient of >0.99 and repeatability of 0.5-4.6% for eight replicates. The method was successfully applied in the analysis of amino acids and carbohydrates in aseptic media and in extracellular culture media of three phenotypes of Clostridium thermocellum. Copyright © 2013 Elsevier B.V. All rights reserved.

Simultaneous estimation of multiple phases in digital holographic interferometry using state space analysis

NASA Astrophysics Data System (ADS)

Kulkarni, Rishikesh; Rastogi, Pramod

2018-05-01

A new approach is proposed for the multiple phase estimation from a multicomponent exponential phase signal recorded in multi-beam digital holographic interferometry. It is capable of providing multidimensional measurements in a simultaneous manner from a single recording of the exponential phase signal encoding multiple phases. Each phase within a small window around each pixel is appproximated with a first order polynomial function of spatial coordinates. The problem of accurate estimation of polynomial coefficients, and in turn the unwrapped phases, is formulated as a state space analysis wherein the coefficients and signal amplitudes are set as the elements of a state vector. The state estimation is performed using the extended Kalman filter. An amplitude discrimination criterion is utilized in order to unambiguously estimate the coefficients associated with the individual signal components. The performance of proposed method is stable over a wide range of the ratio of signal amplitudes. The pixelwise phase estimation approach of the proposed method allows it to handle the fringe patterns that may contain invalid regions.

Scatter correction in cone-beam CT via a half beam blocker technique allowing simultaneous acquisition of scatter and image information

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

Lee, Ho; Xing Lei; Lee, Rena

2012-05-15

Purpose: X-ray scatter incurred to detectors degrades the quality of cone-beam computed tomography (CBCT) and represents a problem in volumetric image guided and adaptive radiation therapy. Several methods using a beam blocker for the estimation and subtraction of scatter have been proposed. However, due to missing information resulting from the obstruction of the blocker, such methods require dual scanning or dynamically moving blocker to obtain a complete volumetric image. Here, we propose a half beam blocker-based approach, in conjunction with a total variation (TV) regularized Feldkamp-Davis-Kress (FDK) algorithm, to correct scatter-induced artifacts by simultaneously acquiring image and scatter information frommore » a single-rotation CBCT scan. Methods: A half beam blocker, comprising lead strips, is used to simultaneously acquire image data on one side of the projection data and scatter data on the other half side. One-dimensional cubic B-Spline interpolation/extrapolation is applied to derive patient specific scatter information by using the scatter distributions on strips. The estimated scatter is subtracted from the projection image acquired at the opposite view. With scatter-corrected projections where this subtraction is completed, the FDK algorithm based on a cosine weighting function is performed to reconstruct CBCT volume. To suppress the noise in the reconstructed CBCT images produced by geometric errors between two opposed projections and interpolated scatter information, total variation regularization is applied by a minimization using a steepest gradient descent optimization method. The experimental studies using Catphan504 and anthropomorphic phantoms were carried out to evaluate the performance of the proposed scheme. Results: The scatter-induced shading artifacts were markedly suppressed in CBCT using the proposed scheme. Compared with CBCT without a blocker, the nonuniformity value was reduced from 39.3% to 3.1%. The root mean square error relative to values inside the regions of interest selected from a benchmark scatter free image was reduced from 50 to 11.3. The TV regularization also led to a better contrast-to-noise ratio. Conclusions: An asymmetric half beam blocker-based FDK acquisition and reconstruction technique has been established. The proposed scheme enables simultaneous detection of patient specific scatter and complete volumetric CBCT reconstruction without additional requirements such as prior images, dual scans, or moving strips.« less

A method for simultaneous linear optics and coupling correction for storage rings with turn-by-turn beam position monitor data

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

Yang, Xi; Huang, Xiaobiao

2016-05-13

Here, we propose a method to simultaneously correct linear optics errors and linear coupling for storage rings using turn-by-turn (TbT) beam position monitor (BPM) data. The independent component analysis (ICA) method is used to isolate the betatron normal modes from the measured TbT BPM data. The betatron amplitudes and phase advances of the projections of the normal modes on the horizontal and vertical planes are then extracted, which, combined with dispersion measurement, are used to fit the lattice model. The fitting results are used for lattice correction. Finally, the method has been successfully demonstrated on the NSLS-II storage ring.

A method for simultaneous linear optics and coupling correction for storage rings with turn-by-turn beam position monitor data

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

Yang, Xi; Huang, Xiaobiao

2016-08-01

We propose a method to simultaneously correct linear optics errors and linear coupling for storage rings using turn-by-turn (TbT) beam position monitor (BPM) data. The independent component analysis (ICA) method is used to isolate the betatron normal modes from the measured TbT BPM data. The betatron amplitudes and phase advances of the projections of the normal modes on the horizontal and vertical planes are then extracted, which, combined with dispersion measurement, are used to fit the lattice model. Furthermore, the fitting results are used for lattice correction. Our method has been successfully demonstrated on the NSLS-II storage ring.

A method for simultaneous linear optics and coupling correction for storage rings with turn-by-turn beam position monitor data

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

Yang, Xi; Huang, Xiaobiao

2016-08-01

We propose a method to simultaneously correct linear optics errors and linear coupling for storage rings using turn-by-turn (TbT) beam position monitor (BPM) data. The independent component analysis (ICA) method is used to isolate the betatron normal modes from the measured TbT BPM data. The betatron amplitudes and phase advances of the projections of the normal modes on the horizontal and vertical planes are then extracted, which, combined with dispersion measurement, are used to fit the lattice model. The fitting results are used for lattice correction. The method has been successfully demonstrated on the NSLS-II storage ring.

A biphasic parameter estimation method for quantitative analysis of dynamic renal scintigraphic data

NASA Astrophysics Data System (ADS)

Koh, T. S.; Zhang, Jeff L.; Ong, C. K.; Shuter, B.

2006-06-01

Dynamic renal scintigraphy is an established method in nuclear medicine, commonly used for the assessment of renal function. In this paper, a biphasic model fitting method is proposed for simultaneous estimation of both vascular and parenchymal parameters from renal scintigraphic data. These parameters include the renal plasma flow, vascular and parenchymal mean transit times, and the glomerular extraction rate. Monte Carlo simulation was used to evaluate the stability and confidence of the parameter estimates obtained by the proposed biphasic method, before applying the method on actual patient study cases to compare with the conventional fitting approach and other established renal indices. The various parameter estimates obtained using the proposed method were found to be consistent with the respective pathologies of the study cases. The renal plasma flow and extraction rate estimated by the proposed method were in good agreement with those previously obtained using dynamic computed tomography and magnetic resonance imaging.

Layered clustering multi-fault diagnosis for hydraulic piston pump

NASA Astrophysics Data System (ADS)

Du, Jun; Wang, Shaoping; Zhang, Haiyan

2013-04-01

Efficient diagnosis is very important for improving reliability and performance of aircraft hydraulic piston pump, and it is one of the key technologies in prognostic and health management system. In practice, due to harsh working environment and heavy working loads, multiple faults of an aircraft hydraulic pump may occur simultaneously after long time operations. However, most existing diagnosis methods can only distinguish pump faults that occur individually. Therefore, new method needs to be developed to realize effective diagnosis of simultaneous multiple faults on aircraft hydraulic pump. In this paper, a new method based on the layered clustering algorithm is proposed to diagnose multiple faults of an aircraft hydraulic pump that occur simultaneously. The intensive failure mechanism analyses of the five main types of faults are carried out, and based on these analyses the optimal combination and layout of diagnostic sensors is attained. The three layered diagnosis reasoning engine is designed according to the faults' risk priority number and the characteristics of different fault feature extraction methods. The most serious failures are first distinguished with the individual signal processing. To the desultory faults, i.e., swash plate eccentricity and incremental clearance increases between piston and slipper, the clustering diagnosis algorithm based on the statistical average relative power difference (ARPD) is proposed. By effectively enhancing the fault features of these two faults, the ARPDs calculated from vibration signals are employed to complete the hypothesis testing. The ARPDs of the different faults follow different probability distributions. Compared with the classical fast Fourier transform-based spectrum diagnosis method, the experimental results demonstrate that the proposed algorithm can diagnose the multiple faults, which occur synchronously, with higher precision and reliability.

Simultaneously Discovering and Localizing Common Objects in Wild Images.

PubMed

Wang, Zhenzhen; Yuan, Junsong

2018-09-01

Motivated by the recent success of supervised and weakly supervised common object discovery, in this paper, we move forward one step further to tackle common object discovery in a fully unsupervised way. Generally, object co-localization aims at simultaneously localizing objects of the same class across a group of images. Traditional object localization/detection usually trains specific object detectors which require bounding box annotations of object instances, or at least image-level labels to indicate the presence/absence of objects in an image. Given a collection of images without any annotations, our proposed fully unsupervised method is to simultaneously discover images that contain common objects and also localize common objects in corresponding images. Without requiring to know the total number of common objects, we formulate this unsupervised object discovery as a sub-graph mining problem from a weighted graph of object proposals, where nodes correspond to object proposals, and edges represent the similarities between neighbouring proposals. The positive images and common objects are jointly discovered by finding sub-graphs of strongly connected nodes, with each sub-graph capturing one object pattern. The optimization problem can be efficiently solved by our proposed maximal-flow-based algorithm. Instead of assuming that each image contains only one common object, our proposed solution can better address wild images where each image may contain multiple common objects or even no common object. Moreover, our proposed method can be easily tailored to the task of image retrieval in which the nodes correspond to the similarity between query and reference images. Extensive experiments on PASCAL VOC 2007 and Object Discovery data sets demonstrate that even without any supervision, our approach can discover/localize common objects of various classes in the presence of scale, view point, appearance variation, and partial occlusions. We also conduct broad experiments on image retrieval benchmarks, Holidays and Oxford5k data sets, to show that our proposed method, which considers both the similarity between query and reference images and also similarities among reference images, can help to improve the retrieval results significantly.

Half-quadratic variational regularization methods for speckle-suppression and edge-enhancement in SAR complex image

NASA Astrophysics Data System (ADS)

Zhao, Xia; Wang, Guang-xin

2008-12-01

Synthetic aperture radar (SAR) is an active remote sensing sensor. It is a coherent imaging system, the speckle is its inherent default, which affects badly the interpretation and recognition of the SAR targets. Conventional methods of removing the speckle is studied usually in real SAR image, which reduce the edges of the images at the same time as depressing the speckle. Morever, Conventional methods lost the information about images phase. Removing the speckle and enhancing the target and edge simultaneously are still a puzzle. To suppress the spckle and enhance the targets and the edges simultaneously, a half-quadratic variational regularization method in complex SAR image is presented, which is based on the prior knowledge of the targets and the edge. Due to the non-quadratic and non- convex quality and the complexity of the cost function, a half-quadratic variational regularization variation is used to construct a new cost function,which is solved by alternate optimization. In the proposed scheme, the construction of the model, the solution of the model and the selection of the model peremeters are studied carefully. In the end, we validate the method using the real SAR data.Theoretic analysis and the experimental results illustrate the the feasibility of the proposed method. Further more, the proposed method can preserve the information about images phase.

Development of a simple system for simultaneously measuring 6DOF geometric motion errors of a linear guide.

PubMed

Qibo, Feng; Bin, Zhang; Cunxing, Cui; Cuifang, Kuang; Yusheng, Zhai; Fenglin, You

2013-11-04

A simple method for simultaneously measuring the 6DOF geometric motion errors of the linear guide was proposed. The mechanisms for measuring straightness and angular errors and for enhancing their resolution are described in detail. A common-path method for measuring the laser beam drift was proposed and it was used to compensate the errors produced by the laser beam drift in the 6DOF geometric error measurements. A compact 6DOF system was built. Calibration experiments with certain standard measurement meters showed that our system has a standard deviation of 0.5 µm in a range of ± 100 µm for the straightness measurements, and standard deviations of 0.5", 0.5", and 1.0" in the range of ± 100" for pitch, yaw, and roll measurements, respectively.

Different Spectrophotometric Methods for Simultaneous Determination of Trelagliptin and Its Acid Degradation Product

PubMed Central

Hassan, Mostafa A.; Zaghary, Wafaa A.

2018-01-01

New spectrophotometric and chemometric methods were carried out for the simultaneous assay of trelagliptin (TRG) and its acid degradation product (TAD) and applied successfully as a stability indicating assay to recently approved Zafatek® tablets. TAD was monitored using TLC to ensure complete degradation. Furthermore, HPLC was used to confirm dealing with one major acid degradation product. The proposed methods were developed by manipulating zero-order, first-derivative, and ratio spectra of TRG and TAD using simultaneous equation, first-derivative, and mean-centering methods, respectively. Using Spectra Manager II and Minitab v.14 software, the absorbance at 274 nm–260.4 nm, amplitudes at 260.4 nm–274.0 nm, and mean-centered values at 287.6 nm–257.2 nm were measured against methanol as a blank for TRG and TAD, respectively. Linearity and the other validation parameters were acceptable at concentration ranges of 5–50 μg/mL and 2.5–25 μg/mL for TRG and TAD, respectively. Using one-way analysis of variance (ANOVA), the optimized methods were compared and proved to be accurate for the simultaneous assay of TRG and TAD. PMID:29629213

Different Spectrophotometric Methods for Simultaneous Determination of Trelagliptin and Its Acid Degradation Product.

PubMed

Mowaka, Shereen; Ayoub, Bassam M; Hassan, Mostafa A; Zaghary, Wafaa A

2018-01-01

New spectrophotometric and chemometric methods were carried out for the simultaneous assay of trelagliptin (TRG) and its acid degradation product (TAD) and applied successfully as a stability indicating assay to recently approved Zafatek® tablets. TAD was monitored using TLC to ensure complete degradation. Furthermore, HPLC was used to confirm dealing with one major acid degradation product. The proposed methods were developed by manipulating zero-order, first-derivative, and ratio spectra of TRG and TAD using simultaneous equation, first-derivative, and mean-centering methods, respectively. Using Spectra Manager II and Minitab v.14 software, the absorbance at 274 nm-260.4 nm, amplitudes at 260.4 nm-274.0 nm, and mean-centered values at 287.6 nm-257.2 nm were measured against methanol as a blank for TRG and TAD, respectively. Linearity and the other validation parameters were acceptable at concentration ranges of 5-50  μ g/mL and 2.5-25  μ g/mL for TRG and TAD, respectively. Using one-way analysis of variance (ANOVA), the optimized methods were compared and proved to be accurate for the simultaneous assay of TRG and TAD.

Simultaneous Spectrophotometric Determination of Elbasvir and Grazoprevir in a Pharmaceutical Preparation.

PubMed

Attia, Khalid A M; El-Abasawi, Nasr M; El-Olemy, Ahmed; Abdelazim, Ahmed H

2018-03-01

Three UV spectrophotometric methods have been developed for the simultaneous determination of two new Food and Drug Administration-approved drugs, elbasvir (EBV) and grazoprevir (GRV), in their combined pharmaceutical dosage form. These methods include dual wavelength (DW), classic least-squares (CLS), and principal component regression (PCR). To achieve the DW method, two wavelengths were chosen for each drug in a way to ensure the difference in absorbance was zero from one drug to the other. GRV revealed equal absorbance at 351 and 315 nm, for which the distinctions in absorbance were measured for the determination of EBV. In the same way, distinctions in absorbance at 375 and 334.5 nm were measured for the determination of GRV. Alternatively, the CLS and PCR models were applied to the spectra analysis because the synchronous inclusion of many unreal wavelengths rather than using a single wavelength greatly increased the precision and predictive ability of the methods. The proposed methods were successfully applied to the assay of these drugs in their pharmaceutical formulation. The obtained results were statistically compared with manufacturing methods. The results conclude that there was no significant difference between the proposed methods and the manufacturing method with respect to accuracy and precision.

Proposing a New Framework and an Innovative Approach to Teaching Reengineering and ERP Implementation Concepts

ERIC Educational Resources Information Center

Pellerin, Robert; Hadaya, Pierre

2008-01-01

Recognizing the need to teach ERP implementation and business process reengineering (BPR) concepts simultaneously, as well as the pedagogical limitations of the case teaching method and simulation tools, the objective of this study is to propose a new framework and an innovative teaching approach to improve the ERP training experience for IS…

An adjoint-based simultaneous estimation method of the asthenosphere's viscosity and afterslip using a fast and scalable finite-element adjoint solver

NASA Astrophysics Data System (ADS)

Agata, Ryoichiro; Ichimura, Tsuyoshi; Hori, Takane; Hirahara, Kazuro; Hashimoto, Chihiro; Hori, Muneo

2018-04-01

The simultaneous estimation of the asthenosphere's viscosity and coseismic slip/afterslip is expected to improve largely the consistency of the estimation results to observation data of crustal deformation collected in widely spread observation points, compared to estimations of slips only. Such an estimate can be formulated as a non-linear inverse problem of material properties of viscosity and input force that is equivalent to fault slips based on large-scale finite-element (FE) modeling of crustal deformation, in which the degree of freedom is in the order of 109. We formulated and developed a computationally efficient adjoint-based estimation method for this inverse problem, together with a fast and scalable FE solver for the associated forward and adjoint problems. In a numerical experiment that imitates the 2011 Tohoku-Oki earthquake, the advantage of the proposed method is confirmed by comparing the estimated results with those obtained using simplified estimation methods. The computational cost required for the optimization shows that the proposed method enabled the targeted estimation to be completed with moderate amount of computational resources.

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

Rebay, S.

This work is devoted to the description of an efficient unstructured mesh generation method entirely based on the Delaunay triangulation. The distinctive characteristic of the proposed method is that point positions and connections are computed simultaneously. This result is achieved by taking advantage of the sequential way in which the Bowyer-Watson algorithm computes the Delaunay triangulation. Two methods are proposed which have great geometrical flexibility, in that they allow us to treat domains of arbitrary shape and topology and to generate arbitrarily nonuniform meshes. The methods are computationally efficient and are applicable both in two and three dimensions. 11 refs.,more » 20 figs., 1 tab.« less

Visual brain activity patterns classification with simultaneous EEG-fMRI: A multimodal approach.

PubMed

Ahmad, Rana Fayyaz; Malik, Aamir Saeed; Kamel, Nidal; Reza, Faruque; Amin, Hafeez Ullah; Hussain, Muhammad

2017-01-01

Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map the brain activity. For getting a high spatial and temporal resolution of the brain at the same time, simultaneous EEG-fMRI seems to be fruitful. In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes. Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature. The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.

Simultaneous determination of Magnolol and Honokiol by amino acid ionic liquid synchronous fluorescence spectrometry

NASA Astrophysics Data System (ADS)

Liu, Wei; Zhu, Xiashi

2018-05-01

A novel method based on amino acid ionic liquids (AAILs) as an additive synchronous fluorescence spectrometry is proposed for simultaneous determination of magnolol (MN) and honokiol (HN) in traditional Chinese medicine Houpu. The overlapping fluorescence spectrum of MN and HN could be completely separated in the AAILs medium. Experiment parameters (the type and concentration of AAILs, pH values and temperature) were discussed. The detection limits of MN and HN reached 1.46 ng/mL, 0.92 ng/mL and the recovery rates ranged from 98.6%-100.7%, 99.7%-100.6%, respectively. This methods was successfully employed for simultaneously determination of MN and HN in real samples. No significant differences could be found in the results of this method and the pharmacopoeia of People's Republic of China 2015 (Ch.P.2015). The experiment mechanisms were discussed by the Gaussian simulation and fluorescence quantum yield.

Simultaneous determination of 12 chemical constituents in the traditional Chinese Medicinal Prescription Xiao-Yao-San-Jia-Wei by HPLC coupled with photodiode array detection.

PubMed

Zhang, Hongmin; Chen, Shiwei; Qin, Feng; Huang, Xi; Ren, Ping; Gu, Xinqi

2008-12-15

An HPLC-photodiode array (PDA) detection method was established for the simultaneous determination of 12 components in Xiao-Yao-San-Jia-Wei (XYSJW): geniposide, puerarin, paeoniflorin, ferulic acid, liquiritin, hesperidin, naringin, paeonol, daidzein, glycyrrhizic acid, honokiol, and magnolol. These were separated in less than 70 min using a Waters Symmetry Shield RP 18 column with gradient elution using (A) acetonitrile, (B) water, and (C) acetic acid at a flow rate of 1 ml/min, and with a PDA detector. All calibration curves showed good linear regression (r(2)>0.9992) within the test ranges. The method was validated for specificity, accuracy, precision, and limits of detection. The proposed method enables in a single run the simultaneous identification and determination for quality control of 12 multi-structural components of XYSJW forming the basis of its therapeutic effect.

Simultaneous separation of water- and fat-soluble vitamins in isocratic pressure-assisted capillary electrochromatography using a methacrylate-based monolithic column.

PubMed

Yamada, Hiroki; Kitagawa, Shinya; Ohtani, Hajime

2013-06-01

A method of simultaneous separation of water- and fat-soluble vitamins using pressure-assisted CEC with a methacrylate-based capillary monolithic column was developed. In the proposed method, water-soluble vitamins were mainly separated electrophoretically, while fat soluble-ones were separated chromatographically by the interaction with a methacrylate-based monolith. A mixture of six water-soluble and four fat-soluble vitamins was separated simultaneously within 20 min with an isocratic elution using 1 M formic acid (pH 1.9)/acetonitrile (30:70, v/v) containing 10 mM ammonium formate as a mobile phase. When the method was applied to a commercial multivitamin tablet and a spiked one, the vitamins were successfully analyzed, and no influence of the matrix contained in the tablet was observed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii using excitation-emission matrix fluorescence coupled with chemometrics methods

NASA Astrophysics Data System (ADS)

Bai, Xue-Mei; Liu, Tie; Liu, De-Long; Wei, Yong-Ju

2018-02-01

A chemometrics-assisted excitation-emission matrix (EEM) fluorescence method was proposed for simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii. Using the strategy of combining EEM data with chemometrics methods, the simultaneous determination of α-asarone and β-asarone in the complex Traditional Chinese medicine system was achieved successfully, even in the presence of unexpected interferents. The physical or chemical separation step was avoided due to the use of ;mathematical separation;. Six second-order calibration methods were used including parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), alternating penalty trilinear decomposition (APTLD), self-weighted alternating trilinear decomposition (SWATLD), the unfolded partial least-squares (U-PLS) and multidimensional partial least-squares (N-PLS) with residual bilinearization (RBL). In addition, HPLC method was developed to further validate the presented strategy. Consequently, for the validation samples, the analytical results obtained by six second-order calibration methods were almost accurate. But for the Acorus tatarinowii samples, the results indicated a slightly better predictive ability of N-PLS/RBL procedure over other methods.

Graph Structure-Based Simultaneous Localization and Mapping Using a Hybrid Method of 2D Laser Scan and Monocular Camera Image in Environments with Laser Scan Ambiguity

PubMed Central

Oh, Taekjun; Lee, Donghwa; Kim, Hyungjin; Myung, Hyun

2015-01-01

Localization is an essential issue for robot navigation, allowing the robot to perform tasks autonomously. However, in environments with laser scan ambiguity, such as long corridors, the conventional SLAM (simultaneous localization and mapping) algorithms exploiting a laser scanner may not estimate the robot pose robustly. To resolve this problem, we propose a novel localization approach based on a hybrid method incorporating a 2D laser scanner and a monocular camera in the framework of a graph structure-based SLAM. 3D coordinates of image feature points are acquired through the hybrid method, with the assumption that the wall is normal to the ground and vertically flat. However, this assumption can be relieved, because the subsequent feature matching process rejects the outliers on an inclined or non-flat wall. Through graph optimization with constraints generated by the hybrid method, the final robot pose is estimated. To verify the effectiveness of the proposed method, real experiments were conducted in an indoor environment with a long corridor. The experimental results were compared with those of the conventional GMappingapproach. The results demonstrate that it is possible to localize the robot in environments with laser scan ambiguity in real time, and the performance of the proposed method is superior to that of the conventional approach. PMID:26151203

Simultaneous determination of Fluticasone propionate and Azelastine hydrochloride in the presence of pharmaceutical dosage form additives

NASA Astrophysics Data System (ADS)

Merey, Hanan A.; El-Mosallamy, Sally S.; Hassan, Nagiba Y.; El-Zeany, Badr A.

2016-05-01

Fluticasone propionate (FLU) and Azelastine hydrochloride (AZE) are co-formulated with phenylethyl alcohol (PEA) and Benzalkonium chloride (BENZ) (as preservatives) in pharmaceutical dosage form for treatment of seasonal allergies. Different spectrophotometric methods were used for the simultaneous determination of cited drugs in the dosage form. Direct spectrophotometric method was used for determining of AZE, while Derivative of double divisor of ratio spectra (DD-RS), Ratio subtraction coupled with ratio difference method (RS-RD) and Mean centering of the ratio spectra (MCR) are used for the determination of FLU. The linearity of the proposed methods was investigated in the range of 5.00-40.00 and 5.00-80.00 μg/mL for FLU and AZE, respectively. The specificity of the developed methods was investigated by analyzing laboratory prepared mixtures containing different ratios of cited drugs in addition to PEA and their pharmaceutical dosage form. The validity of the proposed methods was assessed using the standard addition technique. The obtained results were statistically compared with those obtained by official or the reported method for FLU or AZE, respectively showing no significant difference with respect to accuracy and precision at p = 0.05.

Multiple feature extraction by using simultaneous wavelet transforms

NASA Astrophysics Data System (ADS)

Mazzaferri, Javier; Ledesma, Silvia; Iemmi, Claudio

2003-07-01

We propose here a method to optically perform multiple feature extraction by using wavelet transforms. The method is based on obtaining the optical correlation by means of a Vander Lugt architecture, where the scene and the filter are displayed on spatial light modulators (SLMs). Multiple phase filters containing the information about the features that we are interested in extracting are designed and then displayed on an SLM working in phase mostly mode. We have designed filters to simultaneously detect edges and corners or different characteristic frequencies contained in the input scene. Simulated and experimental results are shown.

A simple X-ray source of two orthogonal beams for small samples imaging

NASA Astrophysics Data System (ADS)

Hrdý, J.

2018-04-01

A simple method for simultaneous imaging of small samples by two orthogonal beams is proposed. The method is based on one channel-cut crystal which is oriented such that the beam is diffracted on two crystallographic planes simultaneously. These planes are symmetrically inclined to the crystal surface. The beams are three times diffracted. After the first diffraction the beam is split. After the second diffraction the split beams become parallel. Finally, after the third diffraction the beams become convergent and may be used for imaging. The corresponding angular relations to obtain orthogonal beams are derived.

Research on segmentation based on multi-atlas in brain MR image

NASA Astrophysics Data System (ADS)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

Model and reconstruction of a K-edge contrast agent distribution with an X-ray photon-counting detector

PubMed Central

Meng, Bo; Cong, Wenxiang; Xi, Yan; De Man, Bruno; Yang, Jian; Wang, Ge

2017-01-01

Contrast-enhanced computed tomography (CECT) helps enhance the visibility for tumor imaging. When a high-Z contrast agent interacts with X-rays across its K-edge, X-ray photoelectric absorption would experience a sudden increment, resulting in a significant difference of the X-ray transmission intensity between the left and right energy windows of the K-edge. Using photon-counting detectors, the X-ray intensity data in the left and right windows of the K-edge can be measured simultaneously. The differential information of the two kinds of intensity data reflects the contrast-agent concentration distribution. K-edge differences between various matters allow opportunities for the identification of contrast agents in biomedical applications. In this paper, a general radon transform is established to link the contrast-agent concentration to X-ray intensity measurement data. An iterative algorithm is proposed to reconstruct a contrast-agent distribution and tissue attenuation background simultaneously. Comprehensive numerical simulations are performed to demonstrate the merits of the proposed method over the existing K-edge imaging methods. Our results show that the proposed method accurately quantifies a distribution of a contrast agent, optimizing the contrast-to-noise ratio at a high dose efficiency. PMID:28437900

Simultaneous Nonrigid Registration, Segmentation, and Tumor Detection in MRI Guided Cervical Cancer Radiation Therapy

PubMed Central

Lu, Chao; Chelikani, Sudhakar; Jaffray, David A.; Milosevic, Michael F.; Staib, Lawrence H.; Duncan, James S.

2013-01-01

External beam radiation therapy (EBRT) for the treatment of cancer enables accurate placement of radiation dose on the cancerous region. However, the deformation of soft tissue during the course of treatment, such as in cervical cancer, presents significant challenges for the delineation of the target volume and other structures of interest. Furthermore, the presence and regression of pathologies such as tumors may violate registration constraints and cause registration errors. In this paper, automatic segmentation, nonrigid registration and tumor detection in cervical magnetic resonance (MR) data are addressed simultaneously using a unified Bayesian framework. The proposed novel method can generate a tumor probability map while progressively identifying the boundary of an organ of interest based on the achieved nonrigid transformation. The method is able to handle the challenges of significant tumor regression and its effect on surrounding tissues. The new method was compared to various currently existing algorithms on a set of 36 MR data from six patients, each patient has six T2-weighted MR cervical images. The results show that the proposed approach achieves an accuracy comparable to manual segmentation and it significantly outperforms the existing registration algorithms. In addition, the tumor detection result generated by the proposed method has a high agreement with manual delineation by a qualified clinician. PMID:22328178

Thermal Conductivity Measurement of Anisotropic Biological Tissue In Vitro

NASA Astrophysics Data System (ADS)

Yue, Kai; Cheng, Liang; Yang, Lina; Jin, Bitao; Zhang, Xinxin

2017-06-01

The accurate determination of the thermal conductivity of biological tissues has implications on the success of cryosurgical/hyperthermia treatments. In light of the evident anisotropy in some biological tissues, a new modified stepwise transient method was proposed to simultaneously measure the transverse and longitudinal thermal conductivities of anisotropic biological tissues. The physical and mathematical models were established, and the analytical solution was derived. Sensitivity analysis and experimental simulation were performed to determine the feasibility and measurement accuracy of simultaneously measuring the transverse and longitudinal thermal conductivities. The experimental system was set up, and its measurement accuracy was verified by measuring the thermal conductivity of a reference standard material. The thermal conductivities of the pork tenderloin and bovine muscles were measured using the traditional 1D and proposed methods, respectively, at different temperatures. Results indicate that the thermal conductivities of the bovine muscle are lower than those of the pork tenderloin muscle, whereas the bovine muscle was determined to exhibit stronger anisotropy than the pork tenderloin muscle. Moreover, the longitudinal thermal conductivity is larger than the transverse thermal conductivity for the two tissues and all thermal conductivities increase with the increase in temperature. Compared with the traditional 1D method, results obtained by the proposed method are slightly higher although the relative deviation is below 5 %.

Beam Design and User Scheduling for Nonorthogonal Multiple Access With Multiple Antennas Based on Pareto Optimality

NASA Astrophysics Data System (ADS)

Seo, Junyeong; Sung, Youngchul

2018-06-01

In this paper, an efficient transmit beam design and user scheduling method is proposed for multi-user (MU) multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) downlink, based on Pareto-optimality. The proposed beam design and user scheduling method groups simultaneously-served users into multiple clusters with practical two users in each cluster, and then applies spatical zeroforcing (ZF) across clusters to control inter-cluster interference (ICI) and Pareto-optimal beam design with successive interference cancellation (SIC) to two users in each cluster to remove interference to strong users and leverage signal-to-interference-plus-noise ratios (SINRs) of interference-experiencing weak users. The proposed method has flexibility to control the rates of strong and weak users and numerical results show that the proposed method yields good performance.

A denoising algorithm for CT image using low-rank sparse coding

NASA Astrophysics Data System (ADS)

Lei, Yang; Xu, Dong; Zhou, Zhengyang; Wang, Tonghe; Dong, Xue; Liu, Tian; Dhabaan, Anees; Curran, Walter J.; Yang, Xiaofeng

2018-03-01

We propose a denoising method of CT image based on low-rank sparse coding. The proposed method constructs an adaptive dictionary of image patches and estimates the sparse coding regularization parameters using the Bayesian interpretation. A low-rank approximation approach is used to simultaneously construct the dictionary and achieve sparse representation through clustering similar image patches. A variable-splitting scheme and a quadratic optimization are used to reconstruct CT image based on achieved sparse coefficients. We tested this denoising technology using phantom, brain and abdominal CT images. The experimental results showed that the proposed method delivers state-of-art denoising performance, both in terms of objective criteria and visual quality.

Development of a Rapid Derivative Spectrophotometric Method for Simultaneous Determination of Acetaminophen, Diphenhydramine and Pseudoephedrine in Tablets

PubMed Central

Souri, Effat; Rahimi, Aghil; Shabani Ravari, Nazanin; Barazandeh Tehrani, Maliheh

2015-01-01

A mixture of acetaminophen, diphenhydramine hydrochloride and pseudoephedrine hydrochloride is used for the symptomatic treatment of common cold. In this study, a derivative spectrophotometric method based on zero-crossing technique was proposed for simultaneous determination of acetaminophen, diphenhydramine hydrochloride and pseudoephedrine hydrochloride. Determination of these drugs was performed using the 1D value of acetaminophen at 281.5 nm, 2D value of diphenhydramine hydrochloride at 226.0 nm and 4D value of pseudoephedrine hydrochloride at 218.0 nm. The analysis method was linear over the range of 5-50, 0.25-4, and 0.5-5 µg/mL for acetaminophen, diphenhydramine hydrochloride and pseudoephedrine hydrochloride, respectively. The within-day and between-day CV and error values for all three compounds were within an acceptable range (CV<2.2% and error<3%). The developed method was used for simultaneous determination of these drugs in pharmaceutical dosage forms and no interference from excipients was observed. PMID:25901150

Regardless-of-Speed Superconducting LSM Controlled-Repulsive MAGLEV Vehicle

NASA Technical Reports Server (NTRS)

Yoshida, Kinjiro; Egashira, Tatsuya; Hirai, Ryuichi

1996-01-01

This paper proposes a new repulsive Maglev vehicle which a superconducting linear synchronous motor (LSM) can levitate and propel simultaneously, independently of the vehicle speeds. The combined levitation and propulsion control is carried out by controlling mechanical-load angle and armature-current. Dynamic simulations show successful operations with good ride-quality by using a compact control method proposed here.

Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles.

PubMed

He, Bo; Liu, Yang; Dong, Diya; Shen, Yue; Yan, Tianhong; Nian, Rui

2015-08-13

In this paper, a novel iterative sparse extended information filter (ISEIF) was proposed to solve the simultaneous localization and mapping problem (SLAM), which is very crucial for autonomous vehicles. The proposed algorithm solves the measurement update equations with iterative methods adaptively to reduce linearization errors. With the scalability advantage being kept, the consistency and accuracy of SEIF is improved. Simulations and practical experiments were carried out with both a land car benchmark and an autonomous underwater vehicle. Comparisons between iterative SEIF (ISEIF), standard EKF and SEIF are presented. All of the results convincingly show that ISEIF yields more consistent and accurate estimates compared to SEIF and preserves the scalability advantage over EKF, as well.

Simultaneous tensor decomposition and completion using factor priors.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting; Liao, Hong-Yuan Mark

2014-03-01

The success of research on matrix completion is evident in a variety of real-world applications. Tensor completion, which is a high-order extension of matrix completion, has also generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use either factorization or completion schemes to recover the missing parts. However, as the number of missing entries increases, factorization schemes may overfit the model because of incorrectly predefined ranks, while completion schemes may fail to interpret the model factors. In this paper, we introduce a novel concept: complete the missing entries and simultaneously capture the underlying model structure. To this end, we propose a method called simultaneous tensor decomposition and completion (STDC) that combines a rank minimization technique with Tucker model decomposition. Moreover, as the model structure is implicitly included in the Tucker model, we use factor priors, which are usually known a priori in real-world tensor objects, to characterize the underlying joint-manifold drawn from the model factors. By exploiting this auxiliary information, our method leverages two classic schemes and accurately estimates the model factors and missing entries. We conducted experiments to empirically verify the convergence of our algorithm on synthetic data and evaluate its effectiveness on various kinds of real-world data. The results demonstrate the efficacy of the proposed method and its potential usage in tensor-based applications. It also outperforms state-of-the-art methods on multilinear model analysis and visual data completion tasks.

Simultaneous determination of V, Ni and Fe in fuel fly ash using solid sampling high resolution continuum source graphite furnace atomic absorption spectrometry.

PubMed

Cárdenas Valdivia, A; Vereda Alonso, E; López Guerrero, M M; Gonzalez-Rodriguez, J; Cano Pavón, J M; García de Torres, A

2018-03-01

A green and simple method has been proposed in this work for the simultaneous determination of V, Ni and Fe in fuel ash samples by solid sampling high resolution continuum source graphite furnace atomic absorption spectrometry (SS HR CS GFAAS). The application of fast programs in combination with direct solid sampling allows eliminating pretreatment steps, involving minimal manipulation of sample. Iridium treated platforms were applied throughout the present study, enabling the use of aqueous standards for calibration. Correlation coefficients for the calibration curves were typically better than 0.9931. The concentrations found in the fuel ash samples analysed ranged from 0.66% to 4.2% for V, 0.23-0.7% for Ni and 0.10-0.60% for Fe. Precision (%RSD) were 5.2%, 10.0% and 9.8% for V, Ni and Fe, respectively, obtained as the average of the %RSD of six replicates of each fuel ash sample. The optimum conditions established were applied to the determination of the target analytes in fuel ash samples. In order to test the accuracy and applicability of the proposed method in the analysis of samples, five ash samples from the combustion of fuel in power stations, were analysed. The method accuracy was evaluated by comparing the results obtained using the proposed method with the results obtained by ICP OES previous acid digestion. The results showed good agreement between them. The goal of this work has been to develop a fast and simple methodology that permits the use of aqueous standards for straightforward calibration and the simultaneous determination of V, Ni and Fe in fuel ash samples by direct SS HR CS GFAAS. Copyright © 2017 Elsevier B.V. All rights reserved.

[Simultaneous determination of delta13C values of glycerol and ethanol in wine by liquid chromatography coupled with isotope ratio mass spectrometry].

PubMed

Li, Xuemin; Jia, Guangqun; Cao, Yanzhong; Zhang, Jinjie; Wang, Lei; Sun, Huiyuan

2013-12-01

A novel procedure was established for the characterization of delta13C values of glycerol and ethanol in wine by liquid chromatography-isotope ratio mass spectrometry (LC-IRMS). Several parameters influencing the separation of glycerol and ethanol from wine matrix were optimized. The precision and accuracy of the proposed method were 0.15 per thousand to 0.26 per thousand and 0.11 per thousand to 0.28 per thousand, respectively. The results obtained for 40 wine samples displayed that the delta13C value of glycerol ranged from--26.87 per thousand to--32.96 per thousand and that of ethanol ranged from--24.06 per thousand to--28.29 per thousand. Close correlations (R = 0.82) were obtained between the delta13C values of glycerol and ethanol. The proposed method didn't need complex sample treatment, and the delta13C values of glycerol and ethanol in wine can be simultaneously determined, thus improving the method in terms of simplicity and speed compared with traditional methods.

A level set-based topology optimization method for simultaneous design of elastic structure and coupled acoustic cavity using a two-phase material model

NASA Astrophysics Data System (ADS)

Noguchi, Yuki; Yamamoto, Takashi; Yamada, Takayuki; Izui, Kazuhiro; Nishiwaki, Shinji

2017-09-01

This papers proposes a level set-based topology optimization method for the simultaneous design of acoustic and structural material distributions. In this study, we develop a two-phase material model that is a mixture of an elastic material and acoustic medium, to represent an elastic structure and an acoustic cavity by controlling a volume fraction parameter. In the proposed model, boundary conditions at the two-phase material boundaries are satisfied naturally, avoiding the need to express these boundaries explicitly. We formulate a topology optimization problem to minimize the sound pressure level using this two-phase material model and a level set-based method that obtains topologies free from grayscales. The topological derivative of the objective functional is approximately derived using a variational approach and the adjoint variable method and is utilized to update the level set function via a time evolutionary reaction-diffusion equation. Several numerical examples present optimal acoustic and structural topologies that minimize the sound pressure generated from a vibrating elastic structure.

Development of New Method for Simultaneous Analysis of Piracetam and Levetiracetam in Pharmaceuticals and Biological Fluids: Application in Stability Studies

PubMed Central

Siddiqui, Farhan Ahmed; Sher, Nawab; Shafi, Nighat; Wafa Sial, Alisha; Ahmad, Mansoor; Mehjebeen

2014-01-01

RP-HPLC ultraviolet detection simultaneous quantification of piracetam and levetiracetam has been developed and validated. The chromatography was obtained on a Nucleosil C18 column of 25 cm × 0.46 cm, 10 μm, dimension. The mobile phase was a (70 : 30 v/v) mixture of 0.1 g/L of triethylamine and acetonitrile. Smooth flow of mobile phase at 1 mL/min was set and 205 nm wavelength was selected. Results were evaluated through statistical parameters which qualify the method reproducibility and selectivity for the quantification of piracetam, levetiracetam, and their impurities hence proving stability-indicating properties. The proposed method is significantly important, permitting the separation of the main constituent piracetam from levetiracetam. Linear behavior was observed between 20 ng/mL and 10000 ng/mL for both drugs. The proposed method was checked in bulk drugs, dosage formulations, physiological condition, and clinical investigations and excellent outcome was witnessed. PMID:25114921

Interference-free spectrofluorometric quantification of aristolochic acid I and aristololactam I in five Chinese herbal medicines using chemical derivatization enhancement and second-order calibration methods

NASA Astrophysics Data System (ADS)

Hu, Yong; Wu, Hai-Long; Yin, Xiao-Li; Gu, Hui-Wen; Xiao, Rong; Wang, Li; Fang, Huan; Yu, Ru-Qin

2017-03-01

A rapid interference-free spectrofluorometric method combined with the excitation-emission matrix fluorescence and the second-order calibration methods based on the alternating penalty trilinear decomposition (APTLD) and the self-weighted alternating trilinear decomposition (SWATLD) algorithms, was proposed for the simultaneous determination of nephrotoxic aristolochic acid I (AA-I) and aristololactam I (AL-I) in five Chinese herbal medicines. The method was based on a chemical derivatization that converts the non-fluorescent AA-I to high-fluorescent AL-I, achieving a high sensitive and simultaneous quantification of the analytes. The variables of the derivatization reaction that conducted by using zinc powder in acetose methanol aqueous solution, were studied and optimized for best quantification results of AA-I and AL-I. The satisfactory results of AA-I and AL-I for the spiked recovery assay were achieved with average recoveries in the range of 100.4-103.8% and RMSEPs < 0.78 ng mL- 1, which validate the accuracy and reliability of the proposed method. The contents of AA-I and AL-I in five herbal medicines obtained from the proposed method were also in good accordance with those of the validated LC-MS/MS method. In light of high sensitive fluorescence detection, the limits of detection (LODs) of AA-I and AL-I for the proposed method compare favorably with that of the LC-MS/MS method, with the LODs < 0.35 and 0.29 ng mL- 1, respectively. The proposed strategy based on the APTLD and SWATLD algorithms by virtue of the "second-order advantage", can be considered as an attractive and green alternative for the quantification of AA-I and AL-I in complex herbal medicine matrices without any prior separations and clear-up processes.

A decision directed detector for the phase incoherent Gaussian channel

NASA Technical Reports Server (NTRS)

Kazakos, D.

1975-01-01

A vector digital signalling scheme is proposed for simultaneous adaptive data transmission and phase estimation. The use of maximum likelihood estimation methods predicts a better performance than the phase-locked loop. The phase estimate is shown to converge to the true value, so that the adaptive nature of the detector effectively achieves phase acquisition and improvement in performance. No separate synchronization interval is required and phase fluctuations can be tracked simultaneously with the transmission of information.

A Local Fast Marching-Based Diffusion Tensor Image Registration Algorithm by Simultaneously Considering Spatial Deformation and Tensor Orientation

PubMed Central

Xue, Zhong; Li, Hai; Guo, Lei; Wong, Stephen T.C.

2010-01-01

It is a key step to spatially align diffusion tensor images (DTI) to quantitatively compare neural images obtained from different subjects or the same subject at different timepoints. Different from traditional scalar or multi-channel image registration methods, tensor orientation should be considered in DTI registration. Recently, several DTI registration methods have been proposed in the literature, but deformation fields are purely dependent on the tensor features not the whole tensor information. Other methods, such as the piece-wise affine transformation and the diffeomorphic non-linear registration algorithms, use analytical gradients of the registration objective functions by simultaneously considering the reorientation and deformation of tensors during the registration. However, only relatively local tensor information such as voxel-wise tensor-similarity, is utilized. This paper proposes a new DTI image registration algorithm, called local fast marching (FM)-based simultaneous registration. The algorithm not only considers the orientation of tensors during registration but also utilizes the neighborhood tensor information of each voxel to drive the deformation, and such neighborhood tensor information is extracted from a local fast marching algorithm around the voxels of interest. These local fast marching-based tensor features efficiently reflect the diffusion patterns around each voxel within a spherical neighborhood and can capture relatively distinctive features of the anatomical structures. Using simulated and real DTI human brain data the experimental results show that the proposed algorithm is more accurate compared with the FA-based registration and is more efficient than its counterpart, the neighborhood tensor similarity-based registration. PMID:20382233

Learning multiple relative attributes with humans in the loop.

PubMed

Qian, Buyue; Wang, Xiang; Cao, Nan; Jiang, Yu-Gang; Davidson, Ian

2014-12-01

Semantic attributes have been recognized as a more spontaneous manner to describe and annotate image content. It is widely accepted that image annotation using semantic attributes is a significant improvement to the traditional binary or multiclass annotation due to its naturally continuous and relative properties. Though useful, existing approaches rely on an abundant supervision and high-quality training data, which limit their applicability. Two standard methods to overcome small amounts of guidance and low-quality training data are transfer and active learning. In the context of relative attributes, this would entail learning multiple relative attributes simultaneously and actively querying a human for additional information. This paper addresses the two main limitations in existing work: 1) it actively adds humans to the learning loop so that minimal additional guidance can be given and 2) it learns multiple relative attributes simultaneously and thereby leverages dependence amongst them. In this paper, we formulate a joint active learning to rank framework with pairwise supervision to achieve these two aims, which also has other benefits such as the ability to be kernelized. The proposed framework optimizes over a set of ranking functions (measuring the strength of the presence of attributes) simultaneously and dependently on each other. The proposed pairwise queries take the form of which one of these two pictures is more natural? These queries can be easily answered by humans. Extensive empirical study on real image data sets shows that our proposed method, compared with several state-of-the-art methods, achieves superior retrieval performance while requires significantly less human inputs.

A novel paper-based assay for the simultaneous determination of Rh typing and forward and reverse ABO blood groups.

PubMed

Noiphung, Julaluk; Talalak, Kwanrutai; Hongwarittorrn, Irin; Pupinyo, Naricha; Thirabowonkitphithan, Pannawich; Laiwattanapaisal, Wanida

2015-05-15

We propose a new, paper-based analytical device (PAD) for blood typing that allows for the simultaneous determination of ABO and Rh blood groups on the same device. The device was successfully fabricated by using a combination of wax printing and wax dipping methods. A 1:2 blood dilution was used for forward grouping, whereas whole blood could be used for reverse grouping. A 30% cell suspension of A-cells or B-cells was used for haemagglutination on the reverse grouping side. The total assay time was 10 min. The ratio between the distance of red blood cell movement and plasma separation is the criterion for agglutination and indicates the presence of the corresponding antigen or antibody. The proposed PAD has excellent reproducibility in that the same blood groups, namely A, AB, and O, were reported by using different PADs that were fabricated on the same day (n=10). The accuracy for detecting blood group A (n=12), B (n=13), AB (n=9), O (n=14), and Rh (n=48) typing were 92%, 85%, 89%, 93%, and 96%, respectively, in comparison with the conventional slide test method. The haematocrit of the sample affects the accuracy of the results, and appropriate dilution is suggested before typing. In conclusion, this study proposes a novel method that is straightforward, time-saving, and inexpensive for the simultaneous determination of ABO and Rh blood groups, which is promising for use in developing countries. Copyright © 2015 Elsevier B.V. All rights reserved.

Tractography from HARDI using an Intrinsic Unscented Kalman Filter

PubMed Central

Cheng, Guang; Salehian, Hesamoddin; Forder, John R.; Vemuri, Baba C.

2014-01-01

A novel adaptation of the unscented Kalman filter (UKF) was recently introduced in literature for simultaneous multi-tensor estimation and fiber tractography from diffusion MRI. This technique has the advantage over other tractography methods in terms of computational efficiency, due to the fact that the UKF simultaneously estimates the diffusion tensors and propagates the most consistent direction to track along. This UKF and its variants reported later in literature however are not intrinsic to the space of diffusion tensors. Lack of this key property can possibly lead to inaccuracies in the multi-tensor estimation as well as in the tractography. In this paper, we propose a novel intrinsic unscented Kalman filter (IUKF) in the space of diffusion tensors which are symmetric positive definite matrices, that can be used for simultaneous recursive estimation of multi-tensors and propagation of directional information for use in fiber tractography from diffusion weighted MR data. In addition to being more accurate, IUKF retains all the advantages of UKF mentioned above. We demonstrate the accuracy and effectiveness of the proposed method via experiments publicly available phantom data from the fiber cup-challenge (MICCAI 2009) and diffusion weighted MR scans acquired from human brains and rat spinal cords. PMID:25203986

Simultaneous sonication-assisted extraction, and determination by gas chromatography-mass spectrometry, of di-(2-ethylhexyl)phthalate, nonylphenol, nonylphenol ethoxylates and polychlorinated biphenyls in sludge from wastewater treatment plants.

PubMed

Aparicio, I; Santos, J L; Alonso, E

2007-02-19

Di-(2-ethyl-hexyl)phthalate (DEHP), nonylphenol, nonylphenol mono- and diethoxylates (NPEs) and polychlorinated biphenyls (PCBs) are organic pollutants in sewage sludge which have to be monitored in the European Union according to a future Sludge Directive. In the present work, an analytical method for the simultaneous extraction and determination of DEHP, NPEs and PCBs is proposed for the routine analysis of these compounds in sludge from wastewater treatment plants. All the compounds were simultaneously extracted by sonication with hexane and analysed by gas chromatography-mass spectrometry (GC-MS) in electronic impact mode. Recoveries achieved were 105% for DEHP, 61.4-88.6% for NPEs and 55.8-108.3% for PCBs with relative standard deviation bellow 10%. Limits of quantification were 65 microg kg(-1) for DEHP, from 630 to 2504 microg kg(-1) for NPEs and from 5.4 to 10.6 microg kg(-1) for PCBs in dried sludge. The applicability of the proposed method was evaluated by the determination of these compounds in sludge from wastewater treatment plants in Seville (South Spain).

Formation Flying/Satellite Swarm Concept Project

NASA Technical Reports Server (NTRS)

Youngquist, Robert C.

2014-01-01

NASA needs a method of not only propelling and rotating small satellites, but also to track their position and orientation. We propose a concept that will, for the first time, demonstrate both tracking and propulsion simultaneously in the same system.

Nonimaging optical concentrators using graded-index dielectric.

PubMed

Zitelli, M

2014-04-01

A new generation of inhomogeneous nonimaging optical concentrators is proposed, able to achieve simultaneously high optical efficiency and acceptance solid angle at a given geometrical concentration factor. General design methods are given, and concentrators are numerically investigated and optimized.

Improved atmospheric effect elimination method for the roughness estimation of painted surfaces.

PubMed

Zhang, Ying; Xuan, Jiabin; Zhao, Huijie; Song, Ping; Zhang, Yi; Xu, Wujian

2018-03-01

We propose a method for eliminating the atmospheric effect in polarimetric imaging remote sensing by using polarimetric imagers to simultaneously detect ground targets and skylight, which does not need calibrated targets. In addition, calculation efficiencies are improved by the skylight division method without losing estimation accuracy. Outdoor experiments are performed to obtain the polarimetric bidirectional reflectance distribution functions of painted surfaces and skylight under different weather conditions. Finally, the roughness of the painted surfaces is estimated. We find that the estimation accuracy with the proposed method is 6% on cloudy weather, while it is 30.72% without atmospheric effect elimination.

Demodulation of moire fringes in digital holographic interferometry using an extended Kalman filter.

PubMed

Ramaiah, Jagadesh; Rastogi, Pramod; Rajshekhar, Gannavarpu

2018-03-10

This paper presents a method for extracting multiple phases from a single moire fringe pattern in digital holographic interferometry. The method relies on component separation using singular value decomposition and an extended Kalman filter for demodulating the moire fringes. The Kalman filter is applied by modeling the interference field locally as a multi-component polynomial phase signal and extracting the associated multiple polynomial coefficients using the state space approach. In addition to phase, the corresponding multiple phase derivatives can be simultaneously extracted using the proposed method. The applicability of the proposed method is demonstrated using simulation and experimental results.

Validation of four different spectrophotometric methods for simultaneous determination of Domperidone and Ranitidine in bulk and pharmaceutical formulation.

PubMed

Abdel-Ghany, Maha F; Abdel-Aziz, Omar; Mohammed, Yomna Y

2015-01-01

Four simple, specific, accurate and precise spectrophotometric methods were developed and validated for simultaneous determination of Domperidone (DP) and Ranitidine Hydrochloride (RT) in bulk powder and pharmaceutical formulation. The first method was simultaneous ratio subtraction (SRS), the second was ratio subtraction (RS) coupled with zero order spectrophotometry (D(0)), the third was first derivative of the ratio spectra ((1)DD) and the fourth method was mean centering of ratio spectra (MCR). The calibration curve is linear over the concentration range of 0.5-5 and 1-45 μg mL(-1) for DP and RT, respectively. The proposed spectrophotometric methods can analyze both drugs without any prior separation steps. The selectivity of the adopted methods was tested by analyzing synthetic mixtures of the investigated drugs, also in their pharmaceutical formulation. The suggested methods were validated according to International Conference of Harmonization (ICH) guidelines and the results revealed that; they were precise and reproducible. All the obtained results were statistically compared with those of the reported method, where there was no significant difference. Copyright © 2015 Elsevier B.V. All rights reserved.

In silico optimization of pharmacokinetic properties and receptor binding affinity simultaneously: a 'parallel progression approach to drug design' applied to β-blockers.

PubMed

Advani, Poonam; Joseph, Blessy; Ambre, Premlata; Pissurlenkar, Raghuvir; Khedkar, Vijay; Iyer, Krishna; Gabhe, Satish; Iyer, Radhakrishnan P; Coutinho, Evans

2016-01-01

The present work exploits the potential of in silico approaches for minimizing attrition of leads in the later stages of drug development. We propose a theoretical approach, wherein 'parallel' information is generated to simultaneously optimize the pharmacokinetics (PK) and pharmacodynamics (PD) of lead candidates. β-blockers, though in use for many years, have suboptimal PKs; hence are an ideal test series for the 'parallel progression approach'. This approach utilizes molecular modeling tools viz. hologram quantitative structure activity relationships, homology modeling, docking, predictive metabolism, and toxicity models. Validated models have been developed for PK parameters such as volume of distribution (log Vd) and clearance (log Cl), which together influence the half-life (t1/2) of a drug. Simultaneously, models for PD in terms of inhibition constant pKi have been developed. Thus, PK and PD properties of β-blockers were concurrently analyzed and after iterative cycling, modifications were proposed that lead to compounds with optimized PK and PD. We report some of the resultant re-engineered β-blockers with improved half-lives and pKi values comparable with marketed β-blockers. These were further analyzed by the docking studies to evaluate their binding poses. Finally, metabolic and toxicological assessment of these molecules was done through in silico methods. The strategy proposed herein has potential universal applicability, and can be used in any drug discovery scenario; provided that the data used is consistent in terms of experimental conditions, endpoints, and methods employed. Thus the 'parallel progression approach' helps to simultaneously fine-tune various properties of the drug and would be an invaluable tool during the drug development process.

Simultaneous learning of instantaneous and time-delayed genetic interactions using novel information theoretic scoring technique

PubMed Central

2012-01-01

Background Understanding gene interactions is a fundamental question in systems biology. Currently, modeling of gene regulations using the Bayesian Network (BN) formalism assumes that genes interact either instantaneously or with a certain amount of time delay. However in reality, biological regulations, both instantaneous and time-delayed, occur simultaneously. A framework that can detect and model both these two types of interactions simultaneously would represent gene regulatory networks more accurately. Results In this paper, we introduce a framework based on the Bayesian Network (BN) formalism that can represent both instantaneous and time-delayed interactions between genes simultaneously. A novel scoring metric having firm mathematical underpinnings is also proposed that, unlike other recent methods, can score both interactions concurrently and takes into account the reality that multiple regulators can regulate a gene jointly, rather than in an isolated pair-wise manner. Further, a gene regulatory network (GRN) inference method employing an evolutionary search that makes use of the framework and the scoring metric is also presented. Conclusion By taking into consideration the biological fact that both instantaneous and time-delayed regulations can occur among genes, our approach models gene interactions with greater accuracy. The proposed framework is efficient and can be used to infer gene networks having multiple orders of instantaneous and time-delayed regulations simultaneously. Experiments are carried out using three different synthetic networks (with three different mechanisms for generating synthetic data) as well as real life networks of Saccharomyces cerevisiae, E. coli and cyanobacteria gene expression data. The results show the effectiveness of our approach. PMID:22691450

Simultaneous injection-effective mixing analysis of palladium.

PubMed

Teshima, Norio; Noguchi, Daisuke; Joichi, Yasutaka; Lenghor, Narong; Ohno, Noriko; Sakai, Tadao; Motomizu, Shoji

2010-01-01

A novel concept of simultaneous injection-effective mixing analysis (SIEMA) is proposed, and a SIEMA method applied to the spectrophotometric determination of palladium using a water-soluble chromogenic reagent has been demonstrated. The flow configuration of SIEMA is a hybrid format of flow injection analysis (FIA), sequential injection analysis (SIA) and multicommutation in flow-based analysis. Sample and reagent solutions are aspirated into each holding coil through each solenoid valve by a syringe pump, and then the zones are simultaneously dispensed (injected) into a mixing coil by reversed flow toward a detector through a confluence point. This results in effective mixing and rapid detection with low reagent consumption.

An improved chaotic fruit fly optimization based on a mutation strategy for simultaneous feature selection and parameter optimization for SVM and its applications.

PubMed

Ye, Fei; Lou, Xin Yuan; Sun, Lin Fu

2017-01-01

This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. In the improved FOA, the chaotic particle initializes the fruit fly swarm location and replaces the expression of distance for the fruit fly to find the food source. However, the proposed mutation strategy uses two distinct generative mechanisms for new food sources at the osphresis phase, allowing the algorithm procedure to search for the optimal solution in both the whole solution space and within the local solution space containing the fruit fly swarm location. In an evaluation based on a group of ten benchmark problems, the proposed algorithm's performance is compared with that of other well-known algorithms, and the results support the superiority of the proposed algorithm. Moreover, this algorithm is successfully applied in a SVM to perform both parameter setting turning for the SVM and feature selection to solve real-world classification problems. This method is called chaotic fruit fly optimization algorithm (CIFOA)-SVM and has been shown to be a more robust and effective optimization method than other well-known methods, particularly in terms of solving the medical diagnosis problem and the credit card problem.

Neural spike sorting using iterative ICA and a deflation-based approach.

PubMed

Tiganj, Z; Mboup, M

2012-12-01

We propose a spike sorting method for multi-channel recordings. When applied in neural recordings, the performance of the independent component analysis (ICA) algorithm is known to be limited, since the number of recording sites is much lower than the number of neurons. The proposed method uses an iterative application of ICA and a deflation technique in two nested loops. In each iteration of the external loop, the spiking activity of one neuron is singled out and then deflated from the recordings. The internal loop implements a sequence of ICA and sorting for removing the noise and all the spikes that are not fired by the targeted neuron. Then a final step is appended to the two nested loops in order to separate simultaneously fired spikes. We solve this problem by taking all possible pairs of the sorted neurons and apply ICA only on the segments of the signal during which at least one of the neurons in a given pair was active. We validate the performance of the proposed method on simulated recordings, but also on a specific type of real recordings: simultaneous extracellular-intracellular. We quantify the sorting results on the extracellular recordings for the spikes that come from the neurons recorded intracellularly. The results suggest that the proposed solution significantly improves the performance of ICA in spike sorting.

An improved chaotic fruit fly optimization based on a mutation strategy for simultaneous feature selection and parameter optimization for SVM and its applications

PubMed Central

Lou, Xin Yuan; Sun, Lin Fu

2017-01-01

This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. In the improved FOA, the chaotic particle initializes the fruit fly swarm location and replaces the expression of distance for the fruit fly to find the food source. However, the proposed mutation strategy uses two distinct generative mechanisms for new food sources at the osphresis phase, allowing the algorithm procedure to search for the optimal solution in both the whole solution space and within the local solution space containing the fruit fly swarm location. In an evaluation based on a group of ten benchmark problems, the proposed algorithm’s performance is compared with that of other well-known algorithms, and the results support the superiority of the proposed algorithm. Moreover, this algorithm is successfully applied in a SVM to perform both parameter setting turning for the SVM and feature selection to solve real-world classification problems. This method is called chaotic fruit fly optimization algorithm (CIFOA)-SVM and has been shown to be a more robust and effective optimization method than other well-known methods, particularly in terms of solving the medical diagnosis problem and the credit card problem. PMID:28369096

Automated and simultaneous fovea center localization and macula segmentation using the new dynamic identification and classification of edges model.

PubMed

Onal, Sinan; Chen, Xin; Satamraju, Veeresh; Balasooriya, Maduka; Dabil-Karacal, Humeyra

2016-07-01

Detecting the position of retinal structures, including the fovea center and macula, in retinal images plays a key role in diagnosing eye diseases such as optic nerve hypoplasia, amblyopia, diabetic retinopathy, and macular edema. However, current detection methods are unreliable for infants or certain ethnic populations. Thus, a methodology is proposed here that may be useful for infants and across ethnicities that automatically localizes the fovea center and segments the macula on digital fundus images. First, dark structures and bright artifacts are removed from the input image using preprocessing operations, and the resulting image is transformed to polar space. Second, the fovea center is identified, and the macula region is segmented using the proposed dynamic identification and classification of edges (DICE) model. The performance of the method was evaluated using 1200 fundus images obtained from the relatively large, diverse, and publicly available Messidor database. In 96.1% of these 1200 cases, the distance between the fovea center identified manually by ophthalmologists and automatically using the proposed method remained within 0 to 8 pixels. The dice similarity index comparing the manually obtained results with those of the model for macula segmentation was 96.12% for these 1200 cases. Thus, the proposed method displayed a high degree of accuracy. The methodology using the DICE model is unique and advantageous over previously reported methods because it simultaneously determines the fovea center and segments the macula region without using any structural information, such as optic disc or blood vessel location, and it may prove useful for all populations, including infants.

Cluster Correspondence Analysis.

PubMed

van de Velden, M; D'Enza, A Iodice; Palumbo, F

2017-03-01

A method is proposed that combines dimension reduction and cluster analysis for categorical data by simultaneously assigning individuals to clusters and optimal scaling values to categories in such a way that a single between variance maximization objective is achieved. In a unified framework, a brief review of alternative methods is provided and we show that the proposed method is equivalent to GROUPALS applied to categorical data. Performance of the methods is appraised by means of a simulation study. The results of the joint dimension reduction and clustering methods are compared with the so-called tandem approach, a sequential analysis of dimension reduction followed by cluster analysis. The tandem approach is conjectured to perform worse when variables are added that are unrelated to the cluster structure. Our simulation study confirms this conjecture. Moreover, the results of the simulation study indicate that the proposed method also consistently outperforms alternative joint dimension reduction and clustering methods.

Application of Savitzky-Golay differentiation filters and Fourier functions to simultaneous determination of cefepime and the co-administered drug, levofloxacin, in spiked human plasma

NASA Astrophysics Data System (ADS)

Abdel-Aziz, Omar; Abdel-Ghany, Maha F.; Nagi, Reham; Abdel-Fattah, Laila

2015-03-01

The present work is concerned with simultaneous determination of cefepime (CEF) and the co-administered drug, levofloxacin (LEV), in spiked human plasma by applying a new approach, Savitzky-Golay differentiation filters, and combined trigonometric Fourier functions to their ratio spectra. The different parameters associated with the calculation of Savitzky-Golay and Fourier coefficients were optimized. The proposed methods were validated and applied for determination of the two drugs in laboratory prepared mixtures and spiked human plasma. The results were statistically compared with reported HPLC methods and were found accurate and precise.

3D digital image correlation using a single 3CCD colour camera and dichroic filter

NASA Astrophysics Data System (ADS)

Zhong, F. Q.; Shao, X. X.; Quan, C.

2018-04-01

In recent years, three-dimensional digital image correlation methods using a single colour camera have been reported. In this study, we propose a simplified system by employing a dichroic filter (DF) to replace the beam splitter and colour filters. The DF can be used to combine two views from different perspectives reflected by two planar mirrors and eliminate their interference. A 3CCD colour camera is then used to capture two different views simultaneously via its blue and red channels. Moreover, the measurement accuracy of the proposed method is higher since the effect of refraction is reduced. Experiments are carried out to verify the effectiveness of the proposed method. It is shown that the interference between the blue and red views is insignificant. In addition, the measurement accuracy of the proposed method is validated on the rigid body displacement. The experimental results demonstrate that the measurement accuracy of the proposed method is higher compared with the reported methods using a single colour camera. Finally, the proposed method is employed to measure the in- and out-of-plane displacements of a loaded plastic board. The re-projection errors of the proposed method are smaller than those of the reported methods using a single colour camera.

Improved Method Of Bending Concentric Pipes

NASA Technical Reports Server (NTRS)

Schroeder, James E.

1995-01-01

Proposed method for bending two concentric pipes simultaneously while maintaining void between them replaces present tedious, messy, and labor-intensive method. Array of rubber tubes inserted in gap between concentric pipes. Tubes then inflated with relatively incompressible liquid to fill gap. Enables bending to be done faster and more cleanly, and amenable to automation of significant portion of bending process on computer numerically controlled (CNC) tube-bending machinery.

Simultaneous beam sampling and aperture shape optimization for SPORT

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

Zarepisheh, Masoud; Li, Ruijiang; Xing, Lei, E-mail: Lei@stanford.edu

Purpose: Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: The authors build a mathematical model with the fundamental station point parameters as the decisionmore » variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution. Results: A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and neck and a prostate case. It significantly improved the target conformality and at the same time critical structure sparing compared with conventional intensity modulated radiation therapy (IMRT). In the head and neck case, for example, the average PTV coverage D99% for two PTVs, cord and brainstem max doses, and right parotid gland mean dose were improved, respectively, by about 7%, 37%, 12%, and 16%. Conclusions: The proposed method automatically determines the number of the stations required to generate a satisfactory plan and optimizes simultaneously the involved station parameters, leading to improved quality of the resultant treatment plans as compared with the conventional IMRT plans.« less

Enhancement of DRPE performance with a novel scheme based on new RAC: Principle, security analysis and FPGA implementation

NASA Astrophysics Data System (ADS)

Neji, N.; Jridi, M.; Alfalou, A.; Masmoudi, N.

2016-02-01

The double random phase encryption (DRPE) method is a well-known all-optical architecture which has many advantages especially in terms of encryption efficiency. However, the method presents some vulnerabilities against attacks and requires a large quantity of information to encode the complex output plane. In this paper, we present an innovative hybrid technique to enhance the performance of DRPE method in terms of compression and encryption. An optimized simultaneous compression and encryption method is applied simultaneously on the real and imaginary components of the DRPE output plane. The compression and encryption technique consists in using an innovative randomized arithmetic coder (RAC) that can well compress the DRPE output planes and at the same time enhance the encryption. The RAC is obtained by an appropriate selection of some conditions in the binary arithmetic coding (BAC) process and by using a pseudo-random number to encrypt the corresponding outputs. The proposed technique has the capabilities to process video content and to be standard compliant with modern video coding standards such as H264 and HEVC. Simulations demonstrate that the proposed crypto-compression system has presented the drawbacks of the DRPE method. The cryptographic properties of DRPE have been enhanced while a compression rate of one-sixth can be achieved. FPGA implementation results show the high performance of the proposed method in terms of maximum operating frequency, hardware occupation, and dynamic power consumption.

Simultaneous and Comparable Numerical Indicators of International, National and Local Collaboration Practices in English-Medium Astrophysics Research Papers

ERIC Educational Resources Information Center

Méndez, David I.; Alcaraz, M. Ángeles

2016-01-01

Introduction: We report an investigation on collaboration practices in research papers published in the most prestigious English-medium astrophysics journals. Method: We propose an evaluation method based on three numerical indicators to study and compare, in absolute terms, three different types of collaboration (international, national and…

Simultaneous determination of a binary mixture of pantoprazole sodium and itopride hydrochloride by four spectrophotometric methods.

PubMed

Ramadan, Nesrin K; El-Ragehy, Nariman A; Ragab, Mona T; El-Zeany, Badr A

2015-02-25

Four simple, sensitive, accurate and precise spectrophotometric methods were developed for the simultaneous determination of a binary mixture containing Pantoprazole Sodium Sesquihydrate (PAN) and Itopride Hydrochloride (ITH). Method (A) is the derivative ratio method ((1)DD), method (B) is the mean centering of ratio spectra method (MCR), method (C) is the ratio difference method (RD) and method (D) is the isoabsorptive point coupled with third derivative method ((3)D). Linear correlation was obtained in range 8-44 μg/mL for PAN by the four proposed methods, 8-40 μg/mL for ITH by methods A, B and C and 10-40 μg/mL for ITH by method D. The suggested methods were validated according to ICH guidelines. The obtained results were statistically compared with those obtained by the official and a reported method for PAN and ITH, respectively, showing no significant difference with respect to accuracy and precision. Copyright © 2014 Elsevier B.V. All rights reserved.

Simultaneous determination of a binary mixture of pantoprazole sodium and itopride hydrochloride by four spectrophotometric methods

NASA Astrophysics Data System (ADS)

Ramadan, Nesrin K.; El-Ragehy, Nariman A.; Ragab, Mona T.; El-Zeany, Badr A.

2015-02-01

Four simple, sensitive, accurate and precise spectrophotometric methods were developed for the simultaneous determination of a binary mixture containing Pantoprazole Sodium Sesquihydrate (PAN) and Itopride Hydrochloride (ITH). Method (A) is the derivative ratio method (1DD), method (B) is the mean centering of ratio spectra method (MCR), method (C) is the ratio difference method (RD) and method (D) is the isoabsorptive point coupled with third derivative method (3D). Linear correlation was obtained in range 8-44 μg/mL for PAN by the four proposed methods, 8-40 μg/mL for ITH by methods A, B and C and 10-40 μg/mL for ITH by method D. The suggested methods were validated according to ICH guidelines. The obtained results were statistically compared with those obtained by the official and a reported method for PAN and ITH, respectively, showing no significant difference with respect to accuracy and precision.

Fast and effective low-temperature freezing extraction technique to determine organotin compounds in edible vegetable oil.

PubMed

Liu, Yingxia; Ma, Yaqian; Wan, Yiqun; Guo, Lan; Wan, Xiaofen

2016-06-01

Most organotin compounds that have been widely used in food packaging materials and production process show serious toxicity effects to human health. In this study, a simple and low-cost method based on high-performance liquid chromatography with inductively coupled plasma mass spectrometry for the simultaneous determination of four organotins in edible vegetable oil samples was developed. Four organotins including dibutyltin dichloride, tributyltin chloride, diphenyltin dichloride, and triphenyltin chloride were simultaneously extracted with methanol using the low-temperature precipitation process. After being concentrated, the extracts were purified by matrix solid-phase dispersion using graphitized carbon black. The experimental parameters such as extraction solvent and clean-up material were optimized. To evaluate the accuracy of the new method, the recoveries were investigated. In addition, a liquid chromatography with tandem mass spectrometry method was also proposed for comparison. The procedures of extracting and purifying samples for the analysis were simple and easy to perform batch operations, also showed good efficiency with lower relative standard deviation. The limits of detection of the four organotins were 0.28-0.59 μg/L, and the limits of quantification of the four organotins were 0.93-1.8 μg/L, respectively. The proposed method was successfully applied to the simultaneous analysis of the four organotins in edible vegetable oil. Some analytes were detected at the level of 2.5-28.8 μg/kg. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A quick method based on SIMPLISMA-KPLS for simultaneously selecting outlier samples and informative samples for model standardization in near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Li, Li-Na; Ma, Chang-Ming; Chang, Ming; Zhang, Ren-Cheng

2017-12-01

A novel method based on SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) and Kernel Partial Least Square (KPLS), named as SIMPLISMA-KPLS, is proposed in this paper for selection of outlier samples and informative samples simultaneously. It is a quick algorithm used to model standardization (or named as model transfer) in near infrared (NIR) spectroscopy. The NIR experiment data of the corn for analysis of the protein content is introduced to evaluate the proposed method. Piecewise direct standardization (PDS) is employed in model transfer. And the comparison of SIMPLISMA-PDS-KPLS and KS-PDS-KPLS is given in this research by discussion of the prediction accuracy of protein content and calculation speed of each algorithm. The conclusions include that SIMPLISMA-KPLS can be utilized as an alternative sample selection method for model transfer. Although it has similar accuracy to Kennard-Stone (KS), it is different from KS as it employs concentration information in selection program. This means that it ensures analyte information is involved in analysis, and the spectra (X) of the selected samples is interrelated with concentration (y). And it can be used for outlier sample elimination simultaneously by validation of calibration. According to the statistical data results of running time, it is clear that the sample selection process is more rapid when using KPLS. The quick algorithm of SIMPLISMA-KPLS is beneficial to improve the speed of online measurement using NIR spectroscopy.

Simultaneous determination of rosuvastatin and propranolol in their binary mixture by synchronous spectrofluorimetry

NASA Astrophysics Data System (ADS)

El-Abasawi, Nasr M.; Attia, Khalid A. M.; Abo-serie, Ahmad A. M.; Morshedy, Samir; Abdel-Fattah, Ashraf

2018-06-01

Simultaneous determination of rosuvastatin calcium and propranolol hydrochloride using the first derivative synchronous spectrofluorimetry was described. This method involves measuring the synchronous fluorescence of both drugs in ethanol using, Δ λ = 60 nm then the first derivative was recorded and the peak amplitudes were measured at 350 and 374 nm for rosuvastatin calcium and propranolol hydrochloride, respectively. Under the optimum conditions, the linear ranges of rosuvastatin calcium and propranolol hydrochloride were 0.2-2 μg/mL and 0.1-1 μg/mL, respectively. The method was used for quantitative analysis of the drugs in raw materials and pharmaceutical dosage form. The validity of the proposed method was assessed according to an international conference on harmonization (ICH) guidelines.

A small-plane heat source method for measuring the thermal conductivities of anisotropic materials

NASA Astrophysics Data System (ADS)

Cheng, Liang; Yue, Kai; Wang, Jun; Zhang, Xinxin

2017-07-01

A new small-plane heat source method was proposed in this study to simultaneously measure the in-plane and cross-plane thermal conductivities of anisotropic insulating materials. In this method the size of the heat source element is smaller than the sample size and the boundary condition is thermal insulation due to no heat flux at the edge of the sample during the experiment. A three-dimensional model in a rectangular coordinate system was established to exactly describe the heat transfer process of the measurement system. Using the Laplace transform, variable separation, and Laplace inverse transform methods, the analytical solution of the temperature rise of the sample was derived. The temperature rises calculated by the analytical solution agree well with the results of numerical calculation. The result of the sensitivity analysis shows that the sensitivity coefficients of the estimated thermal conductivities are high and uncorrelated to each other. At room temperature and in a high-temperature environment, experimental measurements of anisotropic silica aerogel were carried out using the traditional one-dimensional plane heat source method and the proposed method, respectively. The results demonstrate that the measurement method developed in this study is effective and feasible for simultaneously obtaining the in-plane and cross-plane thermal conductivities of the anisotropic materials.

Implementing N-quantum phase gate via circuit QED with qubit-qubit interaction

NASA Astrophysics Data System (ADS)

Said, T.; Chouikh, A.; Essammouni, K.; Bennai, M.

2016-02-01

We propose a method for realizing a quantum phase gate of one qubit simultaneously controlling N target qubits based on the qubit-qubit interaction. We show how to implement the proposed gate with one transmon qubit simultaneously controlling N transmon qubits in a circuit QED driven by a strong microwave field. In our scheme, the operation time of this phase gate is independent of the number N of qubits. On the other hand, this gate can be realized in a time of nanosecond-scale much smaller than the decoherence time and dephasing time both being the time of microsecond-scale. Numerical simulation of the occupation probabilities of the second excited lever shows that the scheme could be achieved efficiently within current technology.

Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles

PubMed Central

He, Bo; Liu, Yang; Dong, Diya; Shen, Yue; Yan, Tianhong; Nian, Rui

2015-01-01

In this paper, a novel iterative sparse extended information filter (ISEIF) was proposed to solve the simultaneous localization and mapping problem (SLAM), which is very crucial for autonomous vehicles. The proposed algorithm solves the measurement update equations with iterative methods adaptively to reduce linearization errors. With the scalability advantage being kept, the consistency and accuracy of SEIF is improved. Simulations and practical experiments were carried out with both a land car benchmark and an autonomous underwater vehicle. Comparisons between iterative SEIF (ISEIF), standard EKF and SEIF are presented. All of the results convincingly show that ISEIF yields more consistent and accurate estimates compared to SEIF and preserves the scalability advantage over EKF, as well. PMID:26287194

UV Spectrophotometric Simultaneous Determination of Paracetamol and Ibuprofen in Combined Tablets by Derivative and Wavelet Transforms

PubMed Central

Hoang, Vu Dang; Ly, Dong Thi Ha; Tho, Nguyen Huu; Minh Thi Nguyen, Hue

2014-01-01

The application of first-order derivative and wavelet transforms to UV spectra and ratio spectra was proposed for the simultaneous determination of ibuprofen and paracetamol in their combined tablets. A new hybrid approach on the combined use of first-order derivative and wavelet transforms to spectra was also discussed. In this application, DWT (sym6 and haar), CWT (mexh), and FWT were optimized to give the highest spectral recoveries. Calibration graphs in the linear concentration ranges of ibuprofen (12–32 mg/L) and paracetamol (20–40 mg/L) were obtained by measuring the amplitudes of the transformed signals. Our proposed spectrophotometric methods were statistically compared to HPLC in terms of precision and accuracy. PMID:24949492

UV spectrophotometric simultaneous determination of paracetamol and ibuprofen in combined tablets by derivative and wavelet transforms.

PubMed

Hoang, Vu Dang; Ly, Dong Thi Ha; Tho, Nguyen Huu; Nguyen, Hue Minh Thi

2014-01-01

The application of first-order derivative and wavelet transforms to UV spectra and ratio spectra was proposed for the simultaneous determination of ibuprofen and paracetamol in their combined tablets. A new hybrid approach on the combined use of first-order derivative and wavelet transforms to spectra was also discussed. In this application, DWT (sym6 and haar), CWT (mexh), and FWT were optimized to give the highest spectral recoveries. Calibration graphs in the linear concentration ranges of ibuprofen (12-32 mg/L) and paracetamol (20-40 mg/L) were obtained by measuring the amplitudes of the transformed signals. Our proposed spectrophotometric methods were statistically compared to HPLC in terms of precision and accuracy.

Rapid, simultaneous and interference-free determination of three rhodamine dyes illegally added into chilli samples using excitation-emission matrix fluorescence coupled with second-order calibration method.

PubMed

Chang, Yue-Yue; Wu, Hai-Long; Fang, Huan; Wang, Tong; Liu, Zhi; Ouyang, Yang-Zi; Ding, Yu-Jie; Yu, Ru-Qin

2018-06-15

In this study, a smart and green analytical method based on the second-order calibration algorithm coupled with excitation-emission matrix (EEM) fluorescence was developed for the determination of rhodamine dyes illegally added into chilli samples. The proposed method not only has the advantage of high sensitivity over the traditional fluorescence method but also fully displays the "second-order advantage". Pure signals of analytes were successfully extracted from severely interferential EEMs profiles via using alternating trilinear decomposition (ATLD) algorithm even in the presence of common fluorescence problems such as scattering, peak overlaps and unknown interferences. It is worth noting that the unknown interferents can denote different kinds of backgrounds, not only refer to a constant background. In addition, the method using interpolation method could avoid the information loss of analytes of interest. The use of "mathematical separation" instead of complicated "chemical or physical separation" strategy can be more effective and environmentally friendly. A series of statistical parameters including figures of merit and RSDs of intra- (≤1.9%) and inter-day (≤6.6%) were calculated to validate the accuracy of the proposed method. Furthermore, the authoritative method of HPLC-FLD was adopted to verify the qualitative and quantitative results of the proposed method. Compared with the two methods, it also showed that the ATLD-EEMs method has the advantages of accuracy, rapidness, simplicity and green, which is expected to be developed as an attractive alternative method for simultaneous and interference-free determination of rhodamine dyes illegally added into complex matrices. Copyright © 2018. Published by Elsevier B.V.

Reduced field-of-view imaging for single-shot MRI with an amplitude-modulated chirp pulse excitation and Fourier transform reconstruction.

PubMed

Li, Jing; Zhang, Miao; Chen, Lin; Cai, Congbo; Sun, Huijun; Cai, Shuhui

2015-06-01

We employ an amplitude-modulated chirp pulse to selectively excite spins in one or more regions of interest (ROIs) to realize reduced field-of-view (rFOV) imaging based on single-shot spatiotemporally encoded (SPEN) sequence and Fourier transform reconstruction. The proposed rFOV imaging method was theoretically analyzed and illustrated with numerical simulation and tested with phantom experiments and in vivo rat experiments. In addition, point spread function was applied to demonstrate the feasibility of the proposed method. To evaluate the proposed method, the rFOV results were compared with those obtained using the EPI method with orthogonal RF excitation. The simulation and experimental results show that the proposed method can image one or two separated ROIs along the SPEN dimension in a single shot with higher spatial resolution, less sensitive to field inhomogeneity, and practically no aliasing artifacts. In addition, the proposed method may produce rFOV images with comparable signal-to-noise ratio to the rFOV EPI images. The proposed method is promising for the applications under severe susceptibility heterogeneities and for imaging separate ROIs simultaneously. Copyright © 2015 Elsevier Inc. All rights reserved.

Real-Time GNSS-Based Attitude Determination in the Measurement Domain.

PubMed

Zhao, Lin; Li, Na; Li, Liang; Zhang, Yi; Cheng, Chun

2017-02-05

A multi-antenna-based GNSS receiver is capable of providing high-precision and drift-free attitude solution. Carrier phase measurements need be utilized to achieve high-precision attitude. The traditional attitude determination methods in the measurement domain and the position domain resolve the attitude and the ambiguity sequentially. The redundant measurements from multiple baselines have not been fully utilized to enhance the reliability of attitude determination. A multi-baseline-based attitude determination method in the measurement domain is proposed to estimate the attitude parameters and the ambiguity simultaneously. Meanwhile, the redundancy of attitude resolution has also been increased so that the reliability of ambiguity resolution and attitude determination can be enhanced. Moreover, in order to further improve the reliability of attitude determination, we propose a partial ambiguity resolution method based on the proposed attitude determination model. The static and kinematic experiments were conducted to verify the performance of the proposed method. When compared with the traditional attitude determination methods, the static experimental results show that the proposed method can improve the accuracy by at least 0.03° and enhance the continuity by 18%, at most. The kinematic result has shown that the proposed method can obtain an optimal balance between accuracy and reliability performance.

Deblending of simultaneous-source data using iterative seislet frame thresholding based on a robust slope estimation

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Han, Chunying; Chi, Yue

2018-06-01

In a simultaneous source survey, no limitation is required for the shot scheduling of nearby sources and thus a huge acquisition efficiency can be obtained but at the same time making the recorded seismic data contaminated by strong blending interference. In this paper, we propose a multi-dip seislet frame based sparse inversion algorithm to iteratively separate simultaneous sources. We overcome two inherent drawbacks of traditional seislet transform. For the multi-dip problem, we propose to apply a multi-dip seislet frame thresholding strategy instead of the traditional seislet transform for deblending simultaneous-source data that contains multiple dips, e.g., containing multiple reflections. The multi-dip seislet frame strategy solves the conflicting dip problem that degrades the performance of the traditional seislet transform. For the noise issue, we propose to use a robust dip estimation algorithm that is based on velocity-slope transformation. Instead of calculating the local slope directly using the plane-wave destruction (PWD) based method, we first apply NMO-based velocity analysis and obtain NMO velocities for multi-dip components that correspond to multiples of different orders, then a fairly accurate slope estimation can be obtained using the velocity-slope conversion equation. An iterative deblending framework is given and validated through a comprehensive analysis over both numerical synthetic and field data examples.

Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA.

PubMed

Javed, Ehtasham; Faye, Ibrahima; Malik, Aamir Saeed; Abdullah, Jafri Malin

2017-11-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance image (fMRI) acquisitions provide better insight into brain dynamics. Some artefacts due to simultaneous acquisition pose a threat to the quality of the data. One such problematic artefact is the ballistocardiogram (BCG) artefact. We developed a hybrid algorithm that combines features of empirical mode decomposition (EMD) with principal component analysis (PCA) to reduce the BCG artefact. The algorithm does not require extra electrocardiogram (ECG) or electrooculogram (EOG) recordings to extract the BCG artefact. The method was tested with both simulated and real EEG data of 11 participants. From the simulated data, the similarity index between the extracted BCG and the simulated BCG showed the effectiveness of the proposed method in BCG removal. On the other hand, real data were recorded with two conditions, i.e. resting state (eyes closed dataset) and task influenced (event-related potentials (ERPs) dataset). Using qualitative (visual inspection) and quantitative (similarity index, improved normalized power spectrum (INPS) ratio, power spectrum, sample entropy (SE)) evaluation parameters, the assessment results showed that the proposed method can efficiently reduce the BCG artefact while preserving the neuronal signals. Compared with conventional methods, namely, average artefact subtraction (AAS), optimal basis set (OBS) and combined independent component analysis and principal component analysis (ICA-PCA), the statistical analyses of the results showed that the proposed method has better performance, and the differences were significant for all quantitative parameters except for the power and sample entropy. The proposed method does not require any reference signal, prior information or assumption to extract the BCG artefact. It will be very useful in circumstances where the reference signal is not available. Copyright © 2017 Elsevier B.V. All rights reserved.

Simultaneous determination of hydroquinone, resorcinol, phenol, m-cresol and p-cresol in untreated air samples using spectrofluorimetry and a custom multiple linear regression-successive projection algorithm.

PubMed

Pistonesi, Marcelo F; Di Nezio, María S; Centurión, María E; Lista, Adriana G; Fragoso, Wallace D; Pontes, Márcio J C; Araújo, Mário C U; Band, Beatriz S Fernández

2010-12-15

In this study, a novel, simple, and efficient spectrofluorimetric method to determine directly and simultaneously five phenolic compounds (hydroquinone, resorcinol, phenol, m-cresol and p-cresol) in air samples is presented. For this purpose, variable selection by the successive projections algorithm (SPA) is used in order to obtain simple multiple linear regression (MLR) models based on a small subset of wavelengths. For comparison, partial least square (PLS) regression is also employed in full-spectrum. The concentrations of the calibration matrix ranged from 0.02 to 0.2 mg L(-1) for hydroquinone, from 0.05 to 0.6 mg L(-1) for resorcinol, and from 0.05 to 0.4 mg L(-1) for phenol, m-cresol and p-cresol; incidentally, such ranges are in accordance with the Argentinean environmental legislation. To verify the accuracy of the proposed method a recovery study on real air samples of smoking environment was carried out with satisfactory results (94-104%). The advantage of the proposed method is that it requires only spectrofluorimetric measurements of samples and chemometric modeling for simultaneous determination of five phenols. With it, air is simply sampled and no pre-treatment sample is needed (i.e., separation steps and derivatization reagents are avoided) that means a great saving of time. Copyright © 2010 Elsevier B.V. All rights reserved.

An improved wavelet-Galerkin method for dynamic response reconstruction and parameter identification of shear-type frames

NASA Astrophysics Data System (ADS)

Bu, Haifeng; Wang, Dansheng; Zhou, Pin; Zhu, Hongping

2018-04-01

An improved wavelet-Galerkin (IWG) method based on the Daubechies wavelet is proposed for reconstructing the dynamic responses of shear structures. The proposed method flexibly manages wavelet resolution level according to excitation, thereby avoiding the weakness of the wavelet-Galerkin multiresolution analysis (WGMA) method in terms of resolution and the requirement of external excitation. IWG is implemented by this work in certain case studies, involving single- and n-degree-of-freedom frame structures subjected to a determined discrete excitation. Results demonstrate that IWG performs better than WGMA in terms of accuracy and computation efficiency. Furthermore, a new method for parameter identification based on IWG and an optimization algorithm are also developed for shear frame structures, and a simultaneous identification of structural parameters and excitation is implemented. Numerical results demonstrate that the proposed identification method is effective for shear frame structures.

Spatio-temporal alignment of multiple sensors

NASA Astrophysics Data System (ADS)

Zhang, Tinghua; Ni, Guoqiang; Fan, Guihua; Sun, Huayan; Yang, Biao

2018-01-01

Aiming to achieve the spatio-temporal alignment of multi sensor on the same platform for space target observation, a joint spatio-temporal alignment method is proposed. To calibrate the parameters and measure the attitude of cameras, an astronomical calibration method is proposed based on star chart simulation and collinear invariant features of quadrilateral diagonal between the observed star chart. In order to satisfy a temporal correspondence and spatial alignment similarity simultaneously, the method based on the astronomical calibration and attitude measurement in this paper formulates the video alignment to fold the spatial and temporal alignment into a joint alignment framework. The advantage of this method is reinforced by exploiting the similarities and prior knowledge of velocity vector field between adjacent frames, which is calculated by the SIFT Flow algorithm. The proposed method provides the highest spatio-temporal alignment accuracy compared to the state-of-the-art methods on sequences recorded from multi sensor at different times.

SU-E-T-295: Simultaneous Beam Sampling and Aperture Shape Optimization for Station Parameter Optimized Radiation Therapy (SPORT)

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

Zarepisheh, M; Li, R; Xing, L

Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) andmore » aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves quality of resultant treatment plans as compared with conventional VMAT or IMRT treatments.« less

MIP models and hybrid algorithms for simultaneous job splitting and scheduling on unrelated parallel machines.

PubMed

Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.

Simultaneous Determination of Glass Transition Temperatures of Several Polymers.

PubMed

He, Jiang; Liu, Wei; Huang, Yao-Xiong

2016-01-01

A simple and easy optical method is proposed for the determination of glass transition temperature (Tg) of polymers. Tg was determined using the technique of microsphere imaging to monitor the variation of the refractive index of polymer microsphere as a function of temperature. It was demonstrated that the method can eliminate most thermal lag and has sensitivity about six fold higher than the conventional method in Tg determination. So the determined Tg is more accurate and varies less with cooling/heating rate than that obtained by conventional methods. The most attractive character of the method is that it can simultaneously determine the Tg of several polymers in a single experiment, so it can greatly save experimental time and heating energy. The method is not only applicable for polymer microspheres, but also for the materials with arbitrary shapes. Therefore, it is expected to be broadly applied to different fundamental researches and practical applications of polymers.

Simultaneous quantitative analysis of olmesartan, amlodipine and hydrochlorothiazide in their combined dosage form utilizing classical and alternating least squares based chemometric methods.

PubMed

Darwish, Hany W; Bakheit, Ahmed H; Abdelhameed, Ali S

2016-03-01

Simultaneous spectrophotometric analysis of a multi-component dosage form of olmesartan, amlodipine and hydrochlorothiazide used for the treatment of hypertension has been carried out using various chemometric methods. Multivariate calibration methods include classical least squares (CLS) executed by net analyte processing (NAP-CLS), orthogonal signal correction (OSC-CLS) and direct orthogonal signal correction (DOSC-CLS) in addition to multivariate curve resolution-alternating least squares (MCR-ALS). Results demonstrated the efficiency of the proposed methods as quantitative tools of analysis as well as their qualitative capability. The three analytes were determined precisely using the aforementioned methods in an external data set and in a dosage form after optimization of experimental conditions. Finally, the efficiency of the models was validated via comparison with the partial least squares (PLS) method in terms of accuracy and precision.

Hydrodistillation-adsorption method for the isolation of water-soluble, non-soluble and high volatile compounds from plant materials.

PubMed

Mastelić, J; Jerković, I; Blazević, I; Radonić, A; Krstulović, L

2008-08-15

Proposed method of hydrodistillation-adsorption (HDA) on activated carbon and hydrodistillation (HD) with solvent trap were compared for the isolation of water-soluble, non-soluble and high volatile compounds, such as acids, monoterpenes, isothiocyanates and others from carob (Certonia siliqua L.), rosemary (Rosmarinus officinalis L.) and rocket (Eruca sativa L.). Isolated volatiles were analyzed by GC and GC/MS. The main advantages of HDA method over ubiquitous HD method were higher yields of volatile compounds and their simultaneous separation in three fractions that enabled more detail analyses. This method is particularly suitable for the isolation and analysis of the plant volatiles with high amounts of water-soluble compounds. In distinction from previously published adsorption of remaining volatile compounds from distillation water on activated carbon, this method offers simultaneous hydrodistillation and adsorption in the same apparatus.

Plasmonic metasurface cavity for simultaneous enhancement of optical electric and magnetic fields in deep subwavelength volume.

PubMed

Hong, Jongwoo; Kim, Sun-Je; Kim, Inki; Yun, Hansik; Mun, Sang-Eun; Rho, Junsuk; Lee, Byoungho

2018-05-14

It has been hard to achieve simultaneous plasmonic enhancement of nanoscale light-matter interactions in terms of both electric and magnetic manners with easily reproducible fabrication method and systematic theoretical design rule. In this paper, a novel concept of a flat nanofocusing device is proposed for simultaneously squeezing both electric and magnetic fields in deep-subwavelength volume (~λ 3 /538) in a large area. Based on the funneled unit cell structures and surface plasmon-assisted coherent interactions between them, the array of rectangular nanocavity connected to a tapered nanoantenna, plasmonic metasurface cavity, is constructed by periodic arrangement of the unit cell. The average enhancement factors of electric and magnetic field intensities reach about 60 and 22 in nanocavities, respectively. The proposed outstanding performance of the device is verified numerically and experimentally. We expect that this work would expand methodologies involving optical near-field manipulations in large areas and related potential applications including nanophotonic sensors, nonlinear responses, and quantum interactions.

Simultaneous Measurement of Multiple Mechanical Properties of Single Cells Using AFM by Indentation and Vibration.

PubMed

Zhang, Chuang; Shi, Jialin; Wang, Wenxue; Xi, Ning; Wang, Yuechao; Liu, Lianqing

2017-12-01

The mechanical properties of cells, which are the main characteristics determining their physical performance and physiological functions, have been actively studied in the fields of cytobiology and biomedical engineering and for the development of medicines. In this study, an indentation-vibration-based method is proposed to simultaneously measure the mechanical properties of cells in situ, including cellular mass (m), elasticity (k), and viscosity (c). The proposed measurement method is implemented based on the principle of forced vibration stimulated by simple harmonic force using an atomic force microscope (AFM) system integrated with a piezoelectric transducer as the substrate vibrator. The corresponding theoretical model containing the three mechanical properties is derived and used to perform simulations and calculations. Living and fixed human embryonic kidney 293 (HEK 293) cells were subjected to indentation and vibration to measure and compare their mechanical parameters and verify the proposed approach. The results that the fixed sample cells are more viscous and elastic than the living sample cells and the measured mechanical properties of cell are consistent within, but not outside of the central region of the cell, are in accordance with the previous studies. This work provides an approach to simultaneous measurement of the multiple mechanical properties of single cells using an integrated AFM system based on the principle force vibration and thickness-corrected Hertz model. This study should contribute to progress in biomedical engineering, cytobiology, medicine, early diagnosis, specific therapy and cell-powered robots.

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

PubMed

Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

2018-01-01

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

Conversion of a Rhotrix to a "Coupled Matrix"

ERIC Educational Resources Information Center

Sani, B.

2008-01-01

In this note, a method of converting a rhotrix to a special form of matrix termed a "coupled matrix" is proposed. The special matrix can be used to solve various problems involving n x n and (n - 1) x (n - 1) matrices simultaneously.

Proposal for the measuring molecular velocity vector with single-pulse coherent Raman spectroscopy

NASA Technical Reports Server (NTRS)

She, C. Y.

1983-01-01

Methods for simultaneous measurements of more than one flow velocity component using coherent Raman spectroscopy are proposed. It is demonstrated that using a kilowatt broad-band probe pulse (3-30 GHz) along with a megawatt narrow-band pump pulse (approximately 100 MHz), coherent Raman signal resulting from a single laser pulse is sufficient to produce a high-resolution Raman spectrum for a velocity measurement.

Double-wavelength overlapping resonance Rayleigh scattering technique for the simultaneous quantitative analysis of three β-adrenergic blockade

NASA Astrophysics Data System (ADS)

Tan, Xuanping; Yang, Jidong; Li, Qin; Yang, Qiong; Shen, Yizhong

2016-05-01

Four simple and accurate spectrophotometric methods were proposed for the simultaneous determination of three β-adrenergic blockade, e.g. atenolol, metoprolol and propranolol. The methods were based on the reaction of the three drugs with erythrosine B (EB) in a Britton-Robinson buffer solution at pH 4.6. EB could combine with the drugs to form three ion-association complexes, which resulted in the resonance Rayleigh scattering (RRS) intensity that is enhanced significantly with new RRS peaks that appeared at 337 nm and 370 nm, respectively. In addition, the fluorescence intensity of EB was also quenched. The enhanced scattering intensities of the two peaks and the fluorescence quenched intensity of EB were proportional to the concentrations of the drugs, respectively. What is more, the RRS intensity overlapped with the double-wavelength of 337 nm and 370 nm (so short for DW-RRS) was also proportional to the drugs concentrations. So, a new method with highly sensitive for simultaneous determination of three bisoprolol drugs was established. Finally, the optimum reaction conditions, influencing factors and spectral enhanced mechanism were investigated. The new DW-RRS method has been applied to simultaneously detect the three β-blockers in fresh serum with satisfactory results.

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

PubMed

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.

Method of simultaneous stir bar sorptive extraction of phenethylamines and THC metabolite from urine.

PubMed

Goto, Yoshiyuki; Takeda, Shiho; Araki, Toshinori; Fuchigami, Takayuki

2011-10-01

Stir bar sorptive extraction is a technique used for extracting target substances from various aqueous matrixes such as environmental water, food, and biological samples. This type of extraction is carried out by rotating a coated stir bar is rotated in the sample solution. In particular, Twister bar is a commercial stir bar that is coated with polydimethylsiloxane (PDMS) and used to perform sorptive extraction. In this study, we developed a method for simultaneous detection of amphetamine, methamphetamine, 3,4-methylenedioxyamphetamine, 3,4-methylenedioxymethamphetamine, and a Δ(9)-tetrahydrocannabiniol (THC) metabolite in human urine. For extracting the target analytes, the Twister bar was simply stirred in the sample in the presence of a derivatizing agent. Using this technique, phenethylamines and the acidic THC metabolite can be simultaneously extracted from human urine. This method also enables the extraction of trace amounts of these substances with good reproducibility and high selectivity. The proposed method offers many advantages over other extraction-based approaches and is therefore well suited for screening psychoactive substances in urine specimens.

Development and Validation of a New HPLC Method for the Simultaneous Determination of Paracetamol, Ascorbic Acid, and Pseudoephedrine HCl in their Co-formulated Tablets. Application to in vitro Dissolution Testing.

PubMed

Ibrahim, Fawzia; El-Enany, Nahed; El-Shaheny, Rania N; Mikhail, Ibraam E

2015-01-01

The first HPLC method was developed for the simultaneous determination of paracetamol (PC), ascorbic acid (AA), and pseudoephedrine HCl (PE) in their co-formulated tablets. Separation was achieved on a C18 column in 5 min using a mobile phase composed of methanol-0.05 M phosphate buffer (35:65, v/v) at pH 2.5 with UV detection at 220 nm. Linear calibration curves were constructed over concentration ranges of 1.0 - 50.0, 3.0 - 60.0 and 3.0 - 80.0 μg mL(-1) for PC, AA, and PE, respectively. The method was validated and applied for the simultaneous determination of these drugs in their tablets with average % recoveries of 101.17 ± 0.67, 98.34 ± 0.77, and 98.95 ± 1.11%, for PC, AA, and PE, respectively. The proposed method was also used to construct in vitro dissolution profiles of the co-formulated tablets containing the three drugs.

A matched filter approach for blind joint detection of galaxy clusters in X-ray and SZ surveys

NASA Astrophysics Data System (ADS)

Tarrío, P.; Melin, J.-B.; Arnaud, M.

2018-06-01

The combination of X-ray and Sunyaev-Zeldovich (SZ) observations can potentially improve the cluster detection efficiency, when compared to using only one of these probes, since both probe the same medium, the hot ionized gas of the intra-cluster medium. We present a method based on matched multifrequency filters (MMF) for detecting galaxy clusters from SZ and X-ray surveys. This method builds on a previously proposed joint X-ray-SZ extraction method and allows the blind detection of clusters, that is finding new clusters without knowing their position, size, or redshift, by searching on SZ and X-ray maps simultaneously. The proposed method is tested using data from the ROSAT all-sky survey and from the Planck survey. The evaluation is done by comparison with existing cluster catalogues in the area of the sky covered by the deep SPT survey. Thanks to the addition of the X-ray information, the joint detection method is able to achieve simultaneously better purity, better detection efficiency, and better position accuracy than its predecessor Planck MMF, which is based on SZ maps alone. For a purity of 85%, the X-ray-SZ method detects 141 confirmed clusters in the SPT region; to detect the same number of confirmed clusters with Planck MMF, we would need to decrease its purity to 70%. We provide a catalogue of 225 sources selected by the proposed method in the SPT footprint, with masses ranging between 0.7 and 14.5 ×1014 M⊙ and redshifts between 0.01 and 1.2.

Proposal for a recovery prediction method for patients affected by acute mediastinitis

PubMed Central

2012-01-01

Background An attempt to find a prediction method of death risk in patients affected by acute mediastinitis. There is not such a tool described in available literature for that serious disease. Methods The study comprised 44 consecutive cases of acute mediastinitis. General anamnesis and biochemical data were included. Factor analysis was used to extract the risk characteristic for the patients. The most valuable results were obtained for 8 parameters which were selected for further statistical analysis (all collected during few hours after admission). Three factors reached Eigenvalue >1. Clinical explanations of these combined statistical factors are: Factor1 - proteinic status (serum total protein, albumin, and hemoglobin level), Factor2 - inflammatory status (white blood cells, CRP, procalcitonin), and Factor3 - general risk (age, number of coexisting diseases). Threshold values of prediction factors were estimated by means of statistical analysis (factor analysis, Statgraphics Centurion XVI). Results The final prediction result for the patients is constructed as simultaneous evaluation of all factor scores. High probability of death should be predicted if factor 1 value decreases with simultaneous increase of factors 2 and 3. The diagnostic power of the proposed method was revealed to be high [sensitivity =90%, specificity =64%], for Factor1 [SNC = 87%, SPC = 79%]; for Factor2 [SNC = 87%, SPC = 50%] and for Factor3 [SNC = 73%, SPC = 71%]. Conclusion The proposed prediction method seems a useful emergency signal during acute mediastinitis control in affected patients. PMID:22574625

A Novel Multilayered RFID Tagged Cargo Integrity Assurance Scheme

PubMed Central

Yang, Ming Hour; Luo, Jia Ning; Lu, Shao Yong

2015-01-01

To minimize cargo theft during transport, mobile radio frequency identification (RFID) grouping proof methods are generally employed to ensure the integrity of entire cargo loads. However, conventional grouping proofs cannot simultaneously generate grouping proofs for a specific group of RFID tags. The most serious problem of these methods is that nonexistent tags are included in the grouping proofs because of the considerable amount of time it takes to scan a high number of tags. Thus, applying grouping proof methods in the current logistics industry is difficult. To solve this problem, this paper proposes a method for generating multilayered offline grouping proofs. The proposed method provides tag anonymity; moreover, resolving disputes between recipients and transporters over the integrity of cargo deliveries can be expedited by generating grouping proofs and automatically authenticating the consistency between the receipt proof and pick proof. The proposed method can also protect against replay attacks, multi-session attacks, and concurrency attacks. Finally, experimental results verify that, compared with other methods for generating grouping proofs, the proposed method can efficiently generate offline grouping proofs involving several parties in a supply chain using mobile RFID. PMID:26512673

Structural health monitoring using DOG multi-scale space: an approach for analyzing damage characteristics

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-03-01

Measurement noise is inevitable in practice; thus, it is difficult to identify defects, cracks or damage in a structure while suppressing noise simultaneously. In this work, a novel method is introduced to detect multiple damage in noisy environments. Based on multi-scale space analysis for discrete signals, a method for extracting damage characteristics from the measured displacement mode shape is illustrated. Moreover, the proposed method incorporates a data fusion algorithm to further eliminate measurement noise-based interference. The effectiveness of the method is verified by numerical and experimental methods applied to different structural types. The results demonstrate that there are two advantages to the proposed method. First, damage features are extracted by the difference of the multi-scale representation; this step is taken such that the interference of noise amplification can be avoided. Second, a data fusion technique applied to the proposed method provides a global decision, which retains the damage features while maximally eliminating the uncertainty. Monte Carlo simulations are utilized to validate that the proposed method has a higher accuracy in damage detection.

Dealing with noise and physiological artifacts in human EEG recordings: empirical mode methods

NASA Astrophysics Data System (ADS)

Runnova, Anastasiya E.; Grubov, Vadim V.; Khramova, Marina V.; Hramov, Alexander E.

2017-04-01

In the paper we propose the new method for removing noise and physiological artifacts in human EEG recordings based on empirical mode decomposition (Hilbert-Huang transform). As physiological artifacts we consider specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the proposed method with steps including empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing these empirical modes and reconstructing of initial EEG signal. We show the efficiency of the method on the example of filtration of human EEG signal from eye-moving artifacts.

Partial F-tests with multiply imputed data in the linear regression framework via coefficient of determination.

PubMed

Chaurasia, Ashok; Harel, Ofer

2015-02-10

Tests for regression coefficients such as global, local, and partial F-tests are common in applied research. In the framework of multiple imputation, there are several papers addressing tests for regression coefficients. However, for simultaneous hypothesis testing, the existing methods are computationally intensive because they involve calculation with vectors and (inversion of) matrices. In this paper, we propose a simple method based on the scalar entity, coefficient of determination, to perform (global, local, and partial) F-tests with multiply imputed data. The proposed method is evaluated using simulated data and applied to suicide prevention data. Copyright © 2014 John Wiley & Sons, Ltd.

TU-H-CAMPUS-IeP3-01: Simultaneous PET Restoration and PET/CT Co-Segmentation Using a Variational Method

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

Li, L; Tan, S; Lu, W

Purpose: PET images are usually blurred due to the finite spatial resolution, while CT images suffer from low contrast. Segment a tumor from either a single PET or CT image is thus challenging. To make full use of the complementary information between PET and CT, we propose a novel variational method for simultaneous PET image restoration and PET/CT images co-segmentation. Methods: The proposed model was constructed based on the Γ-convergence approximation of Mumford-Shah (MS) segmentation model for PET/CT co-segmentation. Moreover, a PET de-blur process was integrated into the MS model to improve the segmentation accuracy. An interaction edge constraint termmore » over the two modalities were specially designed to share the complementary information. The energy functional was iteratively optimized using an alternate minimization (AM) algorithm. The performance of the proposed method was validated on ten lung cancer cases and five esophageal cancer cases. The ground truth were manually delineated by an experienced radiation oncologist using the complementary visual features of PET and CT. The segmentation accuracy was evaluated by Dice similarity index (DSI) and volume error (VE). Results: The proposed method achieved an expected restoration result for PET image and satisfactory segmentation results for both PET and CT images. For lung cancer dataset, the average DSI (0.72) increased by 0.17 and 0.40 than single PET and CT segmentation. For esophageal cancer dataset, the average DSI (0.85) increased by 0.07 and 0.43 than single PET and CT segmentation. Conclusion: The proposed method took full advantage of the complementary information from PET and CT images. This work was supported in part by the National Cancer Institute Grants R01CA172638. Shan Tan and Laquan Li were supported in part by the National Natural Science Foundation of China, under Grant Nos. 60971112 and 61375018.« less

Simultaneous determination of vitamins A and D3 in dairy products by liquid chromatography-tandem mass spectrometry (LC-MS/MS)

NASA Astrophysics Data System (ADS)

Barakat, I. S. A.; Hammouri, M. K.; Habib, I.

2015-10-01

A potential method for simultaneous determination of vitamin A and vitamin D3 (25- hydroxyvitamin D3) in fresh milk samples is addressed. The method is based on combination of high performance liquid chromatography and mass spectrometry during the course of analysis. The method applied for determination of vitamins A and D3 on eighteen (18) different fresh milk samples using liquid chromatography along with tandem -mass spectrometry. The work describes the suitability of the proposed method for the simultaneous determination of both vitamins using LC-MS/MS as a specific and quantitative technique. The vitamins of milk were separated by C18 Thermo gold column(100mm × 4.6mm × 5 μm) with a flow rate of 1ml/min (using an isocratic mobile phase). The method was validated using duplicate analyses, relative recovery experiment, and comparative analysis with control samples. Liquid- liquid extraction was employed as a pre-concentration step with n-hexane - dichloromethane mixture (90%:10%) as an extraction solvent. The molecular ions (m/z) appeared near 286 and 385nm and for the base peaks were appeared near 255 and 355nm for vitamins A and D3. Good correlation coefficients were obtained, 0.9999 for vitamin D3 and 0.9994 for vitamin A. The limit of detection and the limit of quantification were found to be 0.09ng/ml and 0.54ng/ml for vitamin D3 and 0.32ng/ml and 1.8ng/ml and for vitamin A. The proposed method showed excellent recoveries, about 98% for both vitamins A and D3.

AUV SLAM and Experiments Using a Mechanical Scanning Forward-Looking Sonar

PubMed Central

He, Bo; Liang, Yan; Feng, Xiao; Nian, Rui; Yan, Tianhong; Li, Minghui; Zhang, Shujing

2012-01-01

Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings simultaneously, namely the simultaneous localization and mapping (SLAM) problem, is a key prerequisite of truly autonomous robots. In this paper, a modified-FastSLAM algorithm is proposed and used in the navigation for our C-Ranger research platform, an open-frame AUV. A mechanical scanning imaging sonar is chosen as the active sensor for the AUV. The modified-FastSLAM implements the update relying on the on-board sensors of C-Ranger. On the other hand, the algorithm employs the data association which combines the single particle maximum likelihood method with modified negative evidence method, and uses the rank-based resampling to overcome the particle depletion problem. In order to verify the feasibility of the proposed methods, both simulation experiments and sea trials for C-Ranger are conducted. The experimental results show the modified-FastSLAM employed for the navigation of the C-Ranger AUV is much more effective and accurate compared with the traditional methods. PMID:23012549

AUV SLAM and experiments using a mechanical scanning forward-looking sonar.

PubMed

He, Bo; Liang, Yan; Feng, Xiao; Nian, Rui; Yan, Tianhong; Li, Minghui; Zhang, Shujing

2012-01-01

Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings simultaneously, namely the simultaneous localization and mapping (SLAM) problem, is a key prerequisite of truly autonomous robots. In this paper, a modified-FastSLAM algorithm is proposed and used in the navigation for our C-Ranger research platform, an open-frame AUV. A mechanical scanning imaging sonar is chosen as the active sensor for the AUV. The modified-FastSLAM implements the update relying on the on-board sensors of C-Ranger. On the other hand, the algorithm employs the data association which combines the single particle maximum likelihood method with modified negative evidence method, and uses the rank-based resampling to overcome the particle depletion problem. In order to verify the feasibility of the proposed methods, both simulation experiments and sea trials for C-Ranger are conducted. The experimental results show the modified-FastSLAM employed for the navigation of the C-Ranger AUV is much more effective and accurate compared with the traditional methods.

Derivative emission spectrofluorimetry for the simultaneous determination of guaifenesin and phenylephrine hydrochloride in pharmaceutical tablets.

PubMed

Maher, Hadir M; Alshehri, Mona M; Al-taweel, Shorog M

2015-05-01

Rapid, simple and sensitive derivative emission spectrofluorimetric methods have been developed for the simultaneous analysis of binary mixtures of guaifenesin (GUA) and phenylephrine hydrochloride (PHE). The methods are based upon measurement of the native fluorescence intensity of the two drugs at λex = 275 nm in methanolic solutions, followed by differentiation using first (D1) and second (D2) derivative techniques. The derivative fluorescence intensity-concentration plots were rectilinear over a range of 0.1-2 µg/mL for both GUA and PHE. The limits of detection were 0.027 (D1, GUA), 0.025 (D2, GUA), 0.031 (D1, PHE) and 0.033 (D2, PHE) µg/mL and limits of quantitation were 0.089 (D1, GUA), 0.083 (D2, GUA), 0.095 (D1, PHE) and 0.097 (D2, PHE) µg/mL. The proposed derivative emission spectrofluorimetric methods (D1 and D2) were successfully applied for the determination of the two compounds in binary mixtures and tablets with high precision and accuracy. The proposed methods were fully validated as per ICH guidelines. Copyright © 2014 John Wiley & Sons, Ltd.

Three-dimensional sensing methodology combining stereo vision and phase-measuring profilometry based on dynamic programming

NASA Astrophysics Data System (ADS)

Lee, Hyunki; Kim, Min Young; Moon, Jeon Il

2017-12-01

Phase measuring profilometry and moiré methodology have been widely applied to the three-dimensional shape measurement of target objects, because of their high measuring speed and accuracy. However, these methods suffer from inherent limitations called a correspondence problem, or 2π-ambiguity problem. Although a kind of sensing method to combine well-known stereo vision and phase measuring profilometry (PMP) technique simultaneously has been developed to overcome this problem, it still requires definite improvement for sensing speed and measurement accuracy. We propose a dynamic programming-based stereo PMP method to acquire more reliable depth information and in a relatively small time period. The proposed method efficiently fuses information from two stereo sensors in terms of phase and intensity simultaneously based on a newly defined cost function of dynamic programming. In addition, the important parameters are analyzed at the view point of the 2π-ambiguity problem and measurement accuracy. To analyze the influence of important hardware and software parameters related to the measurement performance and to verify its efficiency, accuracy, and sensing speed, a series of experimental tests were performed with various objects and sensor configurations.

Joint sparse representation for robust multimodal biometrics recognition.

PubMed

Shekhar, Sumit; Patel, Vishal M; Nasrabadi, Nasser M; Chellappa, Rama

2014-01-01

Traditional biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attention. We propose a multimodal sparse representation method, which represents the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. Thus, we simultaneously take into account correlations as well as coupling information among biometric modalities. A multimodal quality measure is also proposed to weigh each modality as it gets fused. Furthermore, we also kernelize the algorithm to handle nonlinearity in data. The optimization problem is solved using an efficient alternative direction method. Various experiments show that the proposed method compares favorably with competing fusion-based methods.

Total generalized variation-regularized variational model for single image dehazing

NASA Astrophysics Data System (ADS)

Shu, Qiao-Ling; Wu, Chuan-Sheng; Zhong, Qiu-Xiang; Liu, Ryan Wen

2018-04-01

Imaging quality is often significantly degraded under hazy weather condition. The purpose of this paper is to recover the latent sharp image from its hazy version. It is well known that the accurate estimation of depth information could assist in improving dehazing performance. In this paper, a detail-preserving variational model was proposed to simultaneously estimate haze-free image and depth map. In particular, the total variation (TV) and total generalized variation (TGV) regularizers were introduced to restrain haze-free image and depth map, respectively. The resulting nonsmooth optimization problem was efficiently solved using the alternating direction method of multipliers (ADMM). Comprehensive experiments have been conducted on realistic datasets to compare our proposed method with several state-of-the-art dehazing methods. Results have illustrated the superior performance of the proposed method in terms of visual quality evaluation.

Prestack density inversion using the Fatti equation constrained by the P- and S-wave impedance and density

NASA Astrophysics Data System (ADS)

Liang, Li-Feng; Zhang, Hong-Bing; Dan, Zhi-Wei; Xu, Zi-Qiang; Liu, Xiu-Juan; Cao, Cheng-Hao

2017-03-01

Simultaneous prestack inversion is based on the modified Fatti equation and uses the ratio of the P- and S-wave velocity as constraints. We use the relation of P-wave impedance and density (PID) and S-wave impedance and density (SID) to replace the constant Vp/Vs constraint, and we propose the improved constrained Fatti equation to overcome the effect of P-wave impedance on density. We compare the sensitivity of both methods using numerical simulations and conclude that the density inversion sensitivity improves when using the proposed method. In addition, the random conjugate-gradient method is used in the inversion because it is fast and produces global solutions. The use of synthetic and field data suggests that the proposed inversion method is effective in conventional and nonconventional lithologies.

Weakly supervised image semantic segmentation based on clustering superpixels

NASA Astrophysics Data System (ADS)

Yan, Xiong; Liu, Xiaohua

2018-04-01

In this paper, we propose an image semantic segmentation model which is trained from image-level labeled images. The proposed model starts with superpixel segmenting, and features of the superpixels are extracted by trained CNN. We introduce a superpixel-based graph followed by applying the graph partition method to group correlated superpixels into clusters. For the acquisition of inter-label correlations between the image-level labels in dataset, we not only utilize label co-occurrence statistics but also exploit visual contextual cues simultaneously. At last, we formulate the task of mapping appropriate image-level labels to the detected clusters as a problem of convex minimization. Experimental results on MSRC-21 dataset and LableMe dataset show that the proposed method has a better performance than most of the weakly supervised methods and is even comparable to fully supervised methods.

Simultaneous beam sampling and aperture shape optimization for SPORT.

PubMed

Zarepisheh, Masoud; Li, Ruijiang; Ye, Yinyu; Xing, Lei

2015-02-01

Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes. The authors build a mathematical model with the fundamental station point parameters as the decision variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution. A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and neck and a prostate case. It significantly improved the target conformality and at the same time critical structure sparing compared with conventional intensity modulated radiation therapy (IMRT). In the head and neck case, for example, the average PTV coverage D99% for two PTVs, cord and brainstem max doses, and right parotid gland mean dose were improved, respectively, by about 7%, 37%, 12%, and 16%. The proposed method automatically determines the number of the stations required to generate a satisfactory plan and optimizes simultaneously the involved station parameters, leading to improved quality of the resultant treatment plans as compared with the conventional IMRT plans.

A localized Richardson-Lucy algorithm for fiber orientation estimation in high angular resolution diffusion imaging.

PubMed

Liu, Xiaozheng; Yuan, Zhenming; Guo, Zhongwei; Xu, Dongrong

2015-05-01

Diffusion tensor imaging is widely used for studying neural fiber trajectories in white matter and for quantifying changes in tissue using diffusion properties at each voxel in the brain. To better model the nature of crossing fibers within complex architectures, rather than using a simplified tensor model that assumes only a single fiber direction at each image voxel, a model mixing multiple diffusion tensors is used to profile diffusion signals from high angular resolution diffusion imaging (HARDI) data. Based on the HARDI signal and a multiple tensors model, spherical deconvolution methods have been developed to overcome the limitations of the diffusion tensor model when resolving crossing fibers. The Richardson-Lucy algorithm is a popular spherical deconvolution method used in previous work. However, it is based on a Gaussian distribution, while HARDI data are always very noisy, and the distribution of HARDI data follows a Rician distribution. This current work aims to present a novel solution to address these issues. By simultaneously considering both the Rician bias and neighbor correlation in HARDI data, the authors propose a localized Richardson-Lucy (LRL) algorithm to estimate fiber orientations for HARDI data. The proposed method can simultaneously reduce noise and correct the Rician bias. Mean angular error (MAE) between the estimated Fiber orientation distribution (FOD) field and the reference FOD field was computed to examine whether the proposed LRL algorithm offered any advantage over the conventional RL algorithm at various levels of noise. Normalized mean squared error (NMSE) was also computed to measure the similarity between the true FOD field and the estimated FOD filed. For MAE comparisons, the proposed LRL approach obtained the best results in most of the cases at different levels of SNR and b-values. For NMSE comparisons, the proposed LRL approach obtained the best results in most of the cases at b-value = 3000 s/mm(2), which is the recommended schema for HARDI data acquisition. In addition, the FOD fields estimated by the proposed LRL approach in regions of fiber crossing regions using real data sets also showed similar fiber structures which agreed with common acknowledge in these regions. The novel spherical deconvolution method for improved accuracy in investigating crossing fibers can simultaneously reduce noise and correct Rician bias. With the noise smoothed and bias corrected, this algorithm is especially suitable for estimation of fiber orientations in HARDI data. Experimental results using both synthetic and real imaging data demonstrated the success and effectiveness of the proposed LRL algorithm.

Simultaneous Estimation of Withaferin A and Z-Guggulsterone in Marketed Formulation by RP-HPLC.

PubMed

Agrawal, Poonam; Vegda, Rashmi; Laddha, Kirti

2015-07-01

A simple, rapid, precise and accurate high-performance liquid chromatography (HPLC) method was developed for simultaneous estimation of withaferin A and Z-guggulsterone in a polyherbal formulation containing Withania somnifera and Commiphora wightii. The chromatographic separation was achieved on a Purosphere RP-18 column (particle size 5 µm) with a mobile phase consisting of Solvent A (acetonitrile) and Solvent B (water) with the following gradients: 0-7 min, 50% A in B; 7-9 min, 50-80% A in B; 9-20 min, 80% A in B at a flow rate of 1 mL/min and detection at 235 nm. The marker compounds were well separated on the chromatogram within 20 min. The results obtained indicate accuracy and reliability of the developed simultaneous HPLC method for the quantification of withaferin A and Z-guggulsterone. The proposed method was found to be reproducible, specific, precise and accurate for simultaneous estimation of these marker compounds in a combined dosage form. The HPLC method was appropriate and the two markers are well resolved, enabling efficient quantitative analysis of withaferin A and Z-guggulsterone. The method can be successively used for quantitative analysis of these two marker constituents in combination of marketed polyherbal formulation. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Experimental verification of a real-time tuning method of a model-based controller by perturbations to its poles

NASA Astrophysics Data System (ADS)

Kajiwara, Itsuro; Furuya, Keiichiro; Ishizuka, Shinichi

2018-07-01

Model-based controllers with adaptive design variables are often used to control an object with time-dependent characteristics. However, the controller's performance is influenced by many factors such as modeling accuracy and fluctuations in the object's characteristics. One method to overcome these negative factors is to tune model-based controllers. Herein we propose an online tuning method to maintain control performance for an object that exhibits time-dependent variations. The proposed method employs the poles of the controller as design variables because the poles significantly impact performance. Specifically, we use the simultaneous perturbation stochastic approximation (SPSA) to optimize a model-based controller with multiple design variables. Moreover, a vibration control experiment of an object with time-dependent characteristics as the temperature is varied demonstrates that the proposed method allows adaptive control and stably maintains the closed-loop characteristics.

Component isolation for multi-component signal analysis using a non-parametric gaussian latent feature model

NASA Astrophysics Data System (ADS)

Yang, Yang; Peng, Zhike; Dong, Xingjian; Zhang, Wenming; Clifton, David A.

2018-03-01

A challenge in analysing non-stationary multi-component signals is to isolate nonlinearly time-varying signals especially when they are overlapped in time and frequency plane. In this paper, a framework integrating time-frequency analysis-based demodulation and a non-parametric Gaussian latent feature model is proposed to isolate and recover components of such signals. The former aims to remove high-order frequency modulation (FM) such that the latter is able to infer demodulated components while simultaneously discovering the number of the target components. The proposed method is effective in isolating multiple components that have the same FM behavior. In addition, the results show that the proposed method is superior to generalised demodulation with singular-value decomposition-based method, parametric time-frequency analysis with filter-based method and empirical model decomposition base method, in recovering the amplitude and phase of superimposed components.

A risk-adjusted O-E CUSUM with monitoring bands for monitoring medical outcomes.

PubMed

Sun, Rena Jie; Kalbfleisch, John D

2013-03-01

In order to monitor a medical center's survival outcomes using simple plots, we introduce a risk-adjusted Observed-Expected (O-E) Cumulative SUM (CUSUM) along with monitoring bands as decision criterion.The proposed monitoring bands can be used in place of a more traditional but complicated V-shaped mask or the simultaneous use of two one-sided CUSUMs. The resulting plot is designed to simultaneously monitor for failure time outcomes that are "worse than expected" or "better than expected." The slopes of the O-E CUSUM provide direct estimates of the relative risk (as compared to a standard or expected failure rate) for the data being monitored. Appropriate rejection regions are obtained by controlling the false alarm rate (type I error) over a period of given length. Simulation studies are conducted to illustrate the performance of the proposed method. A case study is carried out for 58 liver transplant centers. The use of CUSUM methods for quality improvement is stressed. Copyright © 2013, The International Biometric Society.

A novel fiber-free technique for brain activity imaging in multiple freely behaving mice

NASA Astrophysics Data System (ADS)

Inagaki, Shigenori; Agetsuma, Masakazu; Nagai, Takeharu

2018-02-01

Brain functions and related psychiatric disorders have been investigated by recording electrophysiological field potential. When recording it, a conventional method requires fiber-based apparatus connected to the brain, which however hampers the simultaneous measurement in multiple animals (e.g. by a tangle of fibers). Here, we propose a fiber-free recording technique in conjunction with a ratiometric bioluminescent voltage indicator. Our method allows investigation of electrophysiological filed potential dynamics in multiple freely behaving animals simultaneously over a long time period. Therefore, this fiber-free technique opens up the way to investigate a new mechanism of brain function that governs social behaviors and animal-to-animal interaction.

Application of Savitzky-Golay differentiation filters and Fourier functions to simultaneous determination of cefepime and the co-administered drug, levofloxacin, in spiked human plasma.

PubMed

Abdel-Aziz, Omar; Abdel-Ghany, Maha F; Nagi, Reham; Abdel-Fattah, Laila

2015-03-15

The present work is concerned with simultaneous determination of cefepime (CEF) and the co-administered drug, levofloxacin (LEV), in spiked human plasma by applying a new approach, Savitzky-Golay differentiation filters, and combined trigonometric Fourier functions to their ratio spectra. The different parameters associated with the calculation of Savitzky-Golay and Fourier coefficients were optimized. The proposed methods were validated and applied for determination of the two drugs in laboratory prepared mixtures and spiked human plasma. The results were statistically compared with reported HPLC methods and were found accurate and precise. Copyright © 2014 Elsevier B.V. All rights reserved.

A statistical assessment of differences and equivalences between genetically modified and reference plant varieties

PubMed Central

2011-01-01

Background Safety assessment of genetically modified organisms is currently often performed by comparative evaluation. However, natural variation of plant characteristics between commercial varieties is usually not considered explicitly in the statistical computations underlying the assessment. Results Statistical methods are described for the assessment of the difference between a genetically modified (GM) plant variety and a conventional non-GM counterpart, and for the assessment of the equivalence between the GM variety and a group of reference plant varieties which have a history of safe use. It is proposed to present the results of both difference and equivalence testing for all relevant plant characteristics simultaneously in one or a few graphs, as an aid for further interpretation in safety assessment. A procedure is suggested to derive equivalence limits from the observed results for the reference plant varieties using a specific implementation of the linear mixed model. Three different equivalence tests are defined to classify any result in one of four equivalence classes. The performance of the proposed methods is investigated by a simulation study, and the methods are illustrated on compositional data from a field study on maize grain. Conclusions A clear distinction of practical relevance is shown between difference and equivalence testing. The proposed tests are shown to have appropriate performance characteristics by simulation, and the proposed simultaneous graphical representation of results was found to be helpful for the interpretation of results from a practical field trial data set. PMID:21324199

Multimodal Spatial Calibration for Accurately Registering EEG Sensor Positions

PubMed Central

Chen, Shengyong; Xiao, Gang; Li, Xiaoli

2014-01-01

This paper proposes a fast and accurate calibration method to calibrate multiple multimodal sensors using a novel photogrammetry system for fast localization of EEG sensors. The EEG sensors are placed on human head and multimodal sensors are installed around the head to simultaneously obtain all EEG sensor positions. A multiple views' calibration process is implemented to obtain the transformations of multiple views. We first develop an efficient local repair algorithm to improve the depth map, and then a special calibration body is designed. Based on them, accurate and robust calibration results can be achieved. We evaluate the proposed method by corners of a chessboard calibration plate. Experimental results demonstrate that the proposed method can achieve good performance, which can be further applied to EEG source localization applications on human brain. PMID:24803954

Sieve estimation of Cox models with latent structures.

PubMed

Cao, Yongxiu; Huang, Jian; Liu, Yanyan; Zhao, Xingqiu

2016-12-01

This article considers sieve estimation in the Cox model with an unknown regression structure based on right-censored data. We propose a semiparametric pursuit method to simultaneously identify and estimate linear and nonparametric covariate effects based on B-spline expansions through a penalized group selection method with concave penalties. We show that the estimators of the linear effects and the nonparametric component are consistent. Furthermore, we establish the asymptotic normality of the estimator of the linear effects. To compute the proposed estimators, we develop a modified blockwise majorization descent algorithm that is efficient and easy to implement. Simulation studies demonstrate that the proposed method performs well in finite sample situations. We also use the primary biliary cirrhosis data to illustrate its application. © 2016, The International Biometric Society.

Validated spectrophotometric methods for simultaneous determination of Omeprazole, Tinidazole and Doxycycline in their ternary mixture

NASA Astrophysics Data System (ADS)

Lotfy, Hayam M.; Hegazy, Maha A.; Mowaka, Shereen; Mohamed, Ekram Hany

2016-01-01

A comparative study of smart spectrophotometric techniques for the simultaneous determination of Omeprazole (OMP), Tinidazole (TIN) and Doxycycline (DOX) without prior separation steps is developed. These techniques consist of several consecutive steps utilizing zero/or ratio/or derivative spectra. The proposed techniques adopt nine simple different methods, namely direct spectrophotometry, dual wavelength, first derivative-zero crossing, amplitude factor, spectrum subtraction, ratio subtraction, derivative ratio-zero crossing, constant center, and successive derivative ratio method. The calibration graphs are linear over the concentration range of 1-20 μg/mL, 5-40 μg/mL and 2-30 μg/mL for OMP, TIN and DOX, respectively. These methods are tested by analyzing synthetic mixtures of the above drugs and successfully applied to commercial pharmaceutical preparation. The methods that are validated according to the ICH guidelines, accuracy, precision, and repeatability, were found to be within the acceptable limits.

Advanced scatter search approach and its application in a sequencing problem of mixed-model assembly lines in a case company

NASA Astrophysics Data System (ADS)

Liu, Qiong; Wang, Wen-xi; Zhu, Ke-ren; Zhang, Chao-yong; Rao, Yun-qing

2014-11-01

Mixed-model assembly line sequencing is significant in reducing the production time and overall cost of production. To improve production efficiency, a mathematical model aiming simultaneously to minimize overtime, idle time and total set-up costs is developed. To obtain high-quality and stable solutions, an advanced scatter search approach is proposed. In the proposed algorithm, a new diversification generation method based on a genetic algorithm is presented to generate a set of potentially diverse and high-quality initial solutions. Many methods, including reference set update, subset generation, solution combination and improvement methods, are designed to maintain the diversification of populations and to obtain high-quality ideal solutions. The proposed model and algorithm are applied and validated in a case company. The results indicate that the proposed advanced scatter search approach is significant for mixed-model assembly line sequencing in this company.

Energy resolved actinometry for simultaneous measurement of atomic oxygen densities and local mean electron energies in radio-frequency driven plasmas

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

Greb, Arthur, E-mail: ag941@york.ac.uk; Niemi, Kari; O'Connell, Deborah

2014-12-08

A diagnostic method for the simultaneous determination of atomic oxygen densities and mean electron energies is demonstrated for an atmospheric pressure radio-frequency plasma jet. The proposed method is based on phase resolved optical emission measurements of the direct and dissociative electron-impact excitation dynamics of three distinct emission lines, namely, Ar 750.4 nm, O 777.4 nm, and O 844.6 nm. The energy dependence of these lines serves as basis for analysis by taking into account two line ratios. In this frame, the method is highly adaptable with regard to pressure and gas composition. Results are benchmarked against independent numerical simulations and two-photon absorption laser-inducedmore » fluorescence experiments.« less

Simultaneous multi-component seismic denoising and reconstruction via K-SVD

NASA Astrophysics Data System (ADS)

Hou, Sian; Zhang, Feng; Li, Xiangyang; Zhao, Qiang; Dai, Hengchang

2018-06-01

Data denoising and reconstruction play an increasingly significant role in seismic prospecting for their value in enhancing effective signals, dealing with surface obstacles and reducing acquisition costs. In this paper, we propose a novel method to denoise and reconstruct multicomponent seismic data simultaneously. This method lies within the framework of machine learning and the key points are defining a suitable weight function and a modified inner product operator. The purpose of these two processes are to perform missing data machine learning when the random noise deviation is unknown, and building a mathematical relationship for each component to incorporate all the information of multi-component data. Two examples, using synthetic and real multicomponent data, demonstrate that the new method is a feasible alternative for multi-component seismic data processing.

A method for joint routing, wavelength dimensioning and fault tolerance for any set of simultaneous failures on dynamic WDM optical networks

NASA Astrophysics Data System (ADS)

Jara, Nicolás; Vallejos, Reinaldo; Rubino, Gerardo

2017-11-01

The design of optical networks decomposes into different tasks, where the engineers must basically organize the way the main system's resources are used, minimizing the design and operation costs and respecting critical performance constraints. More specifically, network operators face the challenge of solving routing and wavelength dimensioning problems while aiming to simultaneously minimize the network cost and to ensure that the network performance meets the level established in the Service Level Agreement (SLA). We call this the Routing and Wavelength Dimensioning (R&WD) problem. Another important problem to be solved is how to deal with failures of links when the network is operating. When at least one link fails, a high rate of data loss may occur. To avoid it, the network must be designed in such a manner that upon one or multiple failures, the affected connections can still communicate using alternative routes, a mechanism known as Fault Tolerance (FT). When the mechanism allows to deal with an arbitrary number of faults, we speak about Multiple Fault Tolerance (MFT). The different tasks before mentioned are usually solved separately, or in some cases by pairs, leading to solutions that are not necessarily close to optimal ones. This paper proposes a novel method to simultaneously solve all of them, that is, the Routing, the Wavelength Dimensioning, and the Multiple Fault Tolerance problems. The method allows to obtain: a) all the primary routes by which each connection normally transmits its information, b) the additional routes, called secondary routes, used to keep each user connected in cases where one or more simultaneous failures occur, and c) the number of wavelengths available at each link of the network, calculated such that the blocking probability of each connection is lower than a pre-determined threshold (which is a network design parameter), despite the occurrence of simultaneous link failures. The solution obtained by the new algorithm is significantly more efficient than current methods, its implementation is notably simple and its on-line operation is very fast. In the paper, different examples illustrate the results provided by the proposed technique.

Segmentation of MR images via discriminative dictionary learning and sparse coding: application to hippocampus labeling.

PubMed

Tong, Tong; Wolz, Robin; Coupé, Pierrick; Hajnal, Joseph V; Rueckert, Daniel

2013-08-01

We propose a novel method for the automatic segmentation of brain MRI images by using discriminative dictionary learning and sparse coding techniques. In the proposed method, dictionaries and classifiers are learned simultaneously from a set of brain atlases, which can then be used for the reconstruction and segmentation of an unseen target image. The proposed segmentation strategy is based on image reconstruction, which is in contrast to most existing atlas-based labeling approaches that rely on comparing image similarities between atlases and target images. In addition, we propose a Fixed Discriminative Dictionary Learning for Segmentation (F-DDLS) strategy, which can learn dictionaries offline and perform segmentations online, enabling a significant speed-up in the segmentation stage. The proposed method has been evaluated for the hippocampus segmentation of 80 healthy ICBM subjects and 202 ADNI images. The robustness of the proposed method, especially of our F-DDLS strategy, was validated by training and testing on different subject groups in the ADNI database. The influence of different parameters was studied and the performance of the proposed method was also compared with that of the nonlocal patch-based approach. The proposed method achieved a median Dice coefficient of 0.879 on 202 ADNI images and 0.890 on 80 ICBM subjects, which is competitive compared with state-of-the-art methods. Copyright © 2013 Elsevier Inc. All rights reserved.

Second-derivative synchronous fluorescence spectroscopy for the simultaneous determination of cinnarizine and nicergoline in pharmaceutical preparations.

PubMed

Walash, Mohamed I; Belal, Fathalla; El-Enany, Nahed; Abdelal, Amina

2008-01-01

A rapid, simple, and highly sensitive second-derivative synchronous fluorometric method has been developed for the simultaneous analysis of binary mixtures of cinnarizine (CN) and nicergoline (NIC). The method is based upon measurement of the native fluorescence of these drugs at constant wavelength difference (Deltalambda) = 80 nm in aqueous methanol (50%, v/v). The different experimental parameters affecting the native fluorescence of the studied drugs were carefully studied and optimized. The fluorescence-concentration plots were rectilinear over the range of 0.025-1.5 and 0.25-5.5 microg/mL for CN and NIC, respectively, with lower detection limits of 0.58 and 0.82 ng/mL and quantitation limits of 1.93 and 2.73 ng/mL for CN and NIC, respectively. The proposed method was successfully applied for the determination of the studied compounds in synthetic mixtures and in commercial tablets. The results obtained were in good agreement with those obtained with reference methods. The high sensitivity attained by the proposed method allowed the determination of CN in real and spiked human plasma. The mean recovery in the case of spiked human plasma [number of trials (n) = 3] was 102.82 +/- 2.17%, while that in real human plasma (n = 3) was 105.25 +/- 2.05.

New spatial diversity equalizer based on PLL

NASA Astrophysics Data System (ADS)

Rao, Wei

2011-10-01

A new Spatial Diversity Equalizer (SDE) based on phase-locked loop (PLL) is proposed to overcome the inter-symbol interference (ISI) and phase rotations simultaneously in the digital communication system. The proposed SDE consists of equal gain combining technique based on a famous blind equalization algorithm constant modulus algorithm (CMA) and a PLL. Compared with conventional SDE, the proposed SDE has not only faster convergence rate and lower residual error but also the ability to recover carrier phase rotation. The efficiency of the method is proved by computer simulation.

A general spectral transformation simultaneously including a Fourier transformation and a Laplace transformation

NASA Technical Reports Server (NTRS)

Marko, H.

1978-01-01

A general spectral transformation is proposed and described. Its spectrum can be interpreted as a Fourier spectrum or a Laplace spectrum. The laws and functions of the method are discussed in comparison with the known transformations, and a sample application is shown.

Feature point based 3D tracking of multiple fish from multi-view images

PubMed Central

Qian, Zhi-Ming

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly. PMID:28665966

Polarization-multiplexing ghost imaging

NASA Astrophysics Data System (ADS)

Dongfeng, Shi; Jiamin, Zhang; Jian, Huang; Yingjian, Wang; Kee, Yuan; Kaifa, Cao; Chenbo, Xie; Dong, Liu; Wenyue, Zhu

2018-03-01

A novel technique for polarization-multiplexing ghost imaging is proposed to simultaneously obtain multiple polarimetric information by a single detector. Here, polarization-division multiplexing speckles are employed for object illumination. The light reflected from the objects is detected by a single-pixel detector. An iterative reconstruction method is used to restore the fused image containing the different polarimetric information by using the weighted sum of the multiplexed speckles based on the correlation coefficients obtained from the detected intensities. Next, clear images of the different polarimetric information are recovered by demultiplexing the fused image. The results clearly demonstrate that the proposed method is effective.

Feature point based 3D tracking of multiple fish from multi-view images.

PubMed

Qian, Zhi-Ming; Chen, Yan Qiu

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly.

An Information Transmission Measure for the Analysis of Effective Connectivity among Cortical Neurons

PubMed Central

Law, Andrew J.; Sharma, Gaurav; Schieber, Marc H.

2014-01-01

We present a methodology for detecting effective connections between simultaneously recorded neurons using an information transmission measure to identify the presence and direction of information flow from one neuron to another. Using simulated and experimentally-measured data, we evaluate the performance of our proposed method and compare it to the traditional transfer entropy approach. In simulations, our measure of information transmission outperforms transfer entropy in identifying the effective connectivity structure of a neuron ensemble. For experimentally recorded data, where ground truth is unavailable, the proposed method also yields a more plausible connectivity structure than transfer entropy. PMID:21096617

Real-Time GNSS-Based Attitude Determination in the Measurement Domain

PubMed Central

Zhao, Lin; Li, Na; Li, Liang; Zhang, Yi; Cheng, Chun

2017-01-01

A multi-antenna-based GNSS receiver is capable of providing high-precision and drift-free attitude solution. Carrier phase measurements need be utilized to achieve high-precision attitude. The traditional attitude determination methods in the measurement domain and the position domain resolve the attitude and the ambiguity sequentially. The redundant measurements from multiple baselines have not been fully utilized to enhance the reliability of attitude determination. A multi-baseline-based attitude determination method in the measurement domain is proposed to estimate the attitude parameters and the ambiguity simultaneously. Meanwhile, the redundancy of attitude resolution has also been increased so that the reliability of ambiguity resolution and attitude determination can be enhanced. Moreover, in order to further improve the reliability of attitude determination, we propose a partial ambiguity resolution method based on the proposed attitude determination model. The static and kinematic experiments were conducted to verify the performance of the proposed method. When compared with the traditional attitude determination methods, the static experimental results show that the proposed method can improve the accuracy by at least 0.03° and enhance the continuity by 18%, at most. The kinematic result has shown that the proposed method can obtain an optimal balance between accuracy and reliability performance. PMID:28165434

Microwave-assisted extraction with water for fast extraction and simultaneous RP-HPLC determination of phenolic acids in radix Salviae Miltiorrhizae.

PubMed

Fang, Xinsheng; Wang, Jianhua; Zhou, Hongying; Jiang, Xingkai; Zhu, Lixiang; Gao, Xin

2009-07-01

An optimized microwave-assisted extraction method using water (MAE-W) as the extractant and an efficient HPLC analysis method were first developed for the fast extraction and simultaneous determination of D(+)-(3,4-dihydroxyphenyl) lactic acid (Dla), salvianolic acid B (SaB), and lithospermic acid (La) in radix Salviae Miltiorrhizae. The key parameters of MAE-W were optimized. It was found that the degradation of SaB was inhibited when using the optimized MAE-W and the stable content of Dla, La, and SaB in danshen was obtained. Furthermore, compared to the conventional extraction methods, the proposed MAE-W is a more rapid method with higher yield and lower solvent consumption with a reproducibility (RSD <6%). In addition, using water as extractant is safe and helpful for environment protection, which could be referred to as green extraction. The separation and quantitative determination of the three compounds was carried out by a developed reverse-phase high-performance liquid chromatographic (RP-HPLC) method with UV detection. Highly efficient separation was obtained using gradient solvent system. The optimized HPLC analysis method was validated to have specificity, linearity, precision, and accuracy. The results indicated that MAE-W followed by HPLC-UV determination is an appropriate alternative to previously proposed method for quality control of radix Salviae Miltiorrhizae.

Development and Validation of UV-Visible Spectrophotometric Method for Simultaneous Determination of Eperisone and Paracetamol in Solid Dosage Form.

PubMed

Khanage, Shantaram Gajanan; Mohite, Popat Baban; Jadhav, Sandeep

2013-01-01

Eperisone Hydrochloride (EPE) is a potent new generation antispasmodic drug which is used in the treatment of moderate to severe pain in combination with Paracetamol (PAR). Both drugs are available in tablet dosage form in combination with a dose of 50 mg for EPE and 325 mg PAR respectively. The method is based upon Q-absorption ratio method for the simultaneous determination of the EPE and PAR. Absorption ratio method is used for the ratio of the absorption at two selected wavelength one of which is the iso-absorptive point and other being the λmax of one of the two components. EPE and PAR shows their iso-absorptive point at 260 nm in methanol, the second wavelength used is 249 nm which is the λmax of PAR in methanol. The linearity was obtained in the concentration range of 5-25 μg/mL for EPE and 2-10 μg/mL for PAR. The proposed method was effectively applied to tablet dosage form for estimation of both drugs. The accuracy and reproducibility results are close to 100% with 2% RSD. RESULTS of the analysis were validated statistically and found to be satisfactory. The results of proposed method have been validated as per ICH guidelines. A simple, precise and economical spectrophotometric method has been developed for the estimation of EPE and PAR in pharmaceutical formulation.

A New Method to Comprehensively Diagnose Shock Waves in the Solar Atmosphere Based on Simultaneous Spectroscopic and Imaging Observations

NASA Astrophysics Data System (ADS)

Ruan, Wenzhi; Yan, Limei; He, Jiansen; Zhang, Lei; Wang, Linghua; Wei, Yong

2018-06-01

Shock waves are believed to play an important role in plasma heating. The shock-like temporal jumps in radiation intensity and Doppler shift have been identified in the solar atmosphere. However, a quantitative diagnosis of the shocks in the solar atmosphere is still lacking, seriously hindering the understanding of shock dissipative heating of the solar atmosphere. Here, we propose a new method to realize the goal of the shock quantitative diagnosis, based on Rankine–Hugoniot equations and taking the advantages of simultaneous imaging and spectroscopic observations from, e.g., IRIS (Interface Region Imaging Spectrograph). Because of this method, the key parameters of shock candidates can be derived, such as the bulk velocity and temperature of the plasma in the upstream and downstream, the propagation speed and direction. The method is applied to the shock candidates observed by IRIS, and the overall characteristics of the shocks are revealed quantitatively for the first time. This method is also tested with the help of forward modeling, i.e., virtual observations of simulated shocks. The parameters obtained from the method are consistent with the parameters of the shock formed in the model and are independent of the viewing direction. Therefore, the method we proposed here is applicable to the quantitative and comprehensive diagnosis of the observed shocks in the solar atmosphere.

Chemometrics-assisted spectrophotometric method for simultaneous determination of Pb²⁺ and Cu²⁺ ions in different foodstuffs, soil and water samples using 2-benzylspiro [isoindoline-1,5'-oxazolidine]-2',3,4'-trione using continuous wavelet transformation and partial least squares - calculation of pKf of complexes with rank annihilation factor analysis.

PubMed

Abbasi Tarighat, Maryam; Nabavi, Masoume; Mohammadizadeh, Mohammad Reza

2015-06-15

A new multi-component analysis method based on zero-crossing point-continuous wavelet transformation (CWT) was developed for simultaneous spectrophotometric determination of Cu(2+) and Pb(2+) ions based on the complex formation with 2-benzyl espiro[isoindoline-1,5 oxasolidine]-2,3,4 trione (BSIIOT). The absorption spectra were evaluated with respect to synthetic ligand concentration, time of complexation and pH. Therefore according the absorbance values, 0.015 mmol L(-1) BSIIOT, 10 min after mixing and pH 8.0 were used as optimum values. The complex formation between BSIIOT ligand and the cations Cu(2+) and Pb(2+) by application of rank annihilation factor analysis (RAFA) were investigated. Daubechies-4 (db4), discrete Meyer (dmey), Morlet (morl) and Symlet-8 (sym8) continuous wavelet transforms for signal treatments were found to be suitable among the wavelet families. The applicability of new synthetic ligand and selected mother wavelets were used for the simultaneous determination of strongly overlapped spectra of species without using any pre-chemical treatment. Therefore, CWT signals together with zero crossing technique were directly applied to the overlapping absorption spectra of Cu(2+) and Pb(2+). The calibration graphs for estimation of Pb(2+) and Cu (2+)were obtained by measuring the CWT amplitudes at zero crossing points for Cu(2+) and Pb(2+) at the wavelet domain, respectively. The proposed method was validated by simultaneous determination of Cu(2+) and Pb(2+) ions in red beans, walnut, rice, tea and soil samples. The obtained results of samples with proposed method have been compared with those predicted by partial least squares (PLS) and flame atomic absorption spectrophotometry (FAAS). Copyright © 2015 Elsevier B.V. All rights reserved.

An Improved Distributed Secondary Control Method for DC Microgrids With Enhanced Dynamic Current Sharing Performance

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

Wang, Panbao; Lu, Xiaonan; Yang, Xu

This paper proposes an improved distributed secondary control scheme for dc microgrids (MGs), aiming at overcoming the drawbacks of conventional droop control method. The proposed secondary control scheme can remove the dc voltage deviation and improve the current sharing accuracy by using voltage-shifting and slope-adjusting approaches simultaneously. Meanwhile, the average value of droop coefficients is calculated, and then it is controlled by an additional controller included in the distributed secondary control layer to ensure that each droop coefficient converges at a reasonable value. Hence, by adjusting the droop coefficient, each participating converter has equal output impedance, and the accurate proportionalmore » load current sharing can be achieved with different line resistances. Furthermore, the current sharing performance in steady and transient states can be enhanced by using the proposed method. The effectiveness of the proposed method is verified by detailed experimental tests based on a 3 × 1 kW prototype with three interface converters.« less

Magnetic immunoassay coupled with inductively coupled plasma mass spectrometry for simultaneous quantification of alpha-fetoprotein and carcinoembryonic antigen in human serum

NASA Astrophysics Data System (ADS)

Zhang, Xing; Chen, Beibei; He, Man; Zhang, Yiwen; Xiao, Guangyang; Hu, Bin

2015-04-01

The absolute quantification of glycoproteins in complex biological samples is a challenge and of great significance. Herein, 4-mercaptophenylboronic acid functionalized magnetic beads were prepared to selectively capture glycoproteins, while antibody conjugated gold and silver nanoparticles were synthesized as element tags to label two different glycoproteins. Based on that, a new approach of magnetic immunoassay-inductively coupled plasma mass spectrometry (ICP-MS) was established for simultaneous quantitative analysis of glycoproteins. Taking biomarkers of alpha-fetoprotein (AFP) and carcinoembryonic antigen (CEA) as two model glycoproteins, experimental parameters involved in the immunoassay procedure were carefully optimized and analytical performance of the proposed method was evaluated. The limits of detection (LODs) for AFP and CEA were 0.086 μg L- 1 and 0.054 μg L- 1 with the relative standard deviations (RSDs, n = 7, c = 5 μg L- 1) of 6.5% and 6.2% for AFP and CEA, respectively. Linear range for both AFP and CEA was 0.2-50 μg L- 1. To validate the applicability of the proposed method, human serum samples were analyzed, and the obtained results were in good agreement with that obtained by the clinical chemiluminescence immunoassay. The developed method exhibited good selectivity and sensitivity for the simultaneous determination of AFP and CEA, and extended the applicability of metal nanoparticle tags based on ICP-MS methodology in multiple glycoprotein quantifications.

Artificial neural network assisted kinetic spectrophotometric technique for simultaneous determination of paracetamol and p-aminophenol in pharmaceutical samples using localized surface plasmon resonance band of silver nanoparticles

NASA Astrophysics Data System (ADS)

Khodaveisi, Javad; Dadfarnia, Shayessteh; Haji Shabani, Ali Mohammad; Rohani Moghadam, Masoud; Hormozi-Nezhad, Mohammad Reza

2015-03-01

Spectrophotometric analysis method based on the combination of the principal component analysis (PCA) with the feed-forward neural network (FFNN) and the radial basis function network (RBFN) was proposed for the simultaneous determination of paracetamol (PAC) and p-aminophenol (PAP). This technique relies on the difference between the kinetic rates of the reactions between analytes and silver nitrate as the oxidizing agent in the presence of polyvinylpyrrolidone (PVP) which is the stabilizer. The reactions are monitored at the analytical wavelength of 420 nm of the localized surface plasmon resonance (LSPR) band of the formed silver nanoparticles (Ag-NPs). Under the optimized conditions, the linear calibration graphs were obtained in the concentration range of 0.122-2.425 μg mL-1 for PAC and 0.021-5.245 μg mL-1 for PAP. The limit of detection in terms of standard approach (LODSA) and upper limit approach (LODULA) were calculated to be 0.027 and 0.032 μg mL-1 for PAC and 0.006 and 0.009 μg mL-1 for PAP. The important parameters were optimized for the artificial neural network (ANN) models. Statistical parameters indicated that the ability of the both methods is comparable. The proposed method was successfully applied to the simultaneous determination of PAC and PAP in pharmaceutical preparations.

Development of a piecewise linear omnidirectional 3D image registration method

NASA Astrophysics Data System (ADS)

Bae, Hyunsoo; Kang, Wonjin; Lee, SukGyu; Kim, Youngwoo

2016-12-01

This paper proposes a new piecewise linear omnidirectional image registration method. The proposed method segments an image captured by multiple cameras into 2D segments defined by feature points of the image and then stitches each segment geometrically by considering the inclination of the segment in the 3D space. Depending on the intended use of image registration, the proposed method can be used to improve image registration accuracy or reduce the computation time in image registration because the trade-off between the computation time and image registration accuracy can be controlled for. In general, nonlinear image registration methods have been used in 3D omnidirectional image registration processes to reduce image distortion by camera lenses. The proposed method depends on a linear transformation process for omnidirectional image registration, and therefore it can enhance the effectiveness of the geometry recognition process, increase image registration accuracy by increasing the number of cameras or feature points of each image, increase the image registration speed by reducing the number of cameras or feature points of each image, and provide simultaneous information on shapes and colors of captured objects.

Fast conjugate phase image reconstruction based on a Chebyshev approximation to correct for B0 field inhomogeneity and concomitant gradients.

PubMed

Chen, Weitian; Sica, Christopher T; Meyer, Craig H

2008-11-01

Off-resonance effects can cause image blurring in spiral scanning and various forms of image degradation in other MRI methods. Off-resonance effects can be caused by both B0 inhomogeneity and concomitant gradient fields. Previously developed off-resonance correction methods focus on the correction of a single source of off-resonance. This work introduces a computationally efficient method of correcting for B0 inhomogeneity and concomitant gradients simultaneously. The method is a fast alternative to conjugate phase reconstruction, with the off-resonance phase term approximated by Chebyshev polynomials. The proposed algorithm is well suited for semiautomatic off-resonance correction, which works well even with an inaccurate or low-resolution field map. The proposed algorithm is demonstrated using phantom and in vivo data sets acquired by spiral scanning. Semiautomatic off-resonance correction alone is shown to provide a moderate amount of correction for concomitant gradient field effects, in addition to B0 imhomogeneity effects. However, better correction is provided by the proposed combined method. The best results were produced using the semiautomatic version of the proposed combined method.

Discriminative dictionary learning for abdominal multi-organ segmentation.

PubMed

Tong, Tong; Wolz, Robin; Wang, Zehan; Gao, Qinquan; Misawa, Kazunari; Fujiwara, Michitaka; Mori, Kensaku; Hajnal, Joseph V; Rueckert, Daniel

2015-07-01

An automated segmentation method is presented for multi-organ segmentation in abdominal CT images. Dictionary learning and sparse coding techniques are used in the proposed method to generate target specific priors for segmentation. The method simultaneously learns dictionaries which have reconstructive power and classifiers which have discriminative ability from a set of selected atlases. Based on the learnt dictionaries and classifiers, probabilistic atlases are then generated to provide priors for the segmentation of unseen target images. The final segmentation is obtained by applying a post-processing step based on a graph-cuts method. In addition, this paper proposes a voxel-wise local atlas selection strategy to deal with high inter-subject variation in abdominal CT images. The segmentation performance of the proposed method with different atlas selection strategies are also compared. Our proposed method has been evaluated on a database of 150 abdominal CT images and achieves a promising segmentation performance with Dice overlap values of 94.9%, 93.6%, 71.1%, and 92.5% for liver, kidneys, pancreas, and spleen, respectively. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Efficient 3D multi-region prostate MRI segmentation using dual optimization.

PubMed

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2013-01-01

Efficient and accurate extraction of the prostate, in particular its clinically meaningful sub-regions from 3D MR images, is of great interest in image-guided prostate interventions and diagnosis of prostate cancer. In this work, we propose a novel multi-region segmentation approach to simultaneously locating the boundaries of the prostate and its two major sub-regions: the central gland and the peripheral zone. The proposed method utilizes the prior knowledge of the spatial region consistency and employs a customized prostate appearance model to simultaneously segment multiple clinically meaningful regions. We solve the resulted challenging combinatorial optimization problem by means of convex relaxation, for which we introduce a novel spatially continuous flow-maximization model and demonstrate its duality to the investigated convex relaxed optimization problem with the region consistency constraint. Moreover, the proposed continuous max-flow model naturally leads to a new and efficient continuous max-flow based algorithm, which enjoys great advantages in numerics and can be readily implemented on GPUs. Experiments using 15 T2-weighted 3D prostate MR images, by inter- and intra-operator variability, demonstrate the promising performance of the proposed approach.

Chaos-Based Simultaneous Compression and Encryption for Hadoop.

PubMed

Usama, Muhammad; Zakaria, Nordin

2017-01-01

Data compression and encryption are key components of commonly deployed platforms such as Hadoop. Numerous data compression and encryption tools are presently available on such platforms and the tools are characteristically applied in sequence, i.e., compression followed by encryption or encryption followed by compression. This paper focuses on the open-source Hadoop framework and proposes a data storage method that efficiently couples data compression with encryption. A simultaneous compression and encryption scheme is introduced that addresses an important implementation issue of source coding based on Tent Map and Piece-wise Linear Chaotic Map (PWLM), which is the infinite precision of real numbers that result from their long products. The approach proposed here solves the implementation issue by removing fractional components that are generated by the long products of real numbers. Moreover, it incorporates a stealth key that performs a cyclic shift in PWLM without compromising compression capabilities. In addition, the proposed approach implements a masking pseudorandom keystream that enhances encryption quality. The proposed algorithm demonstrated a congruent fit within the Hadoop framework, providing robust encryption security and compression.

Chaos-Based Simultaneous Compression and Encryption for Hadoop

PubMed Central

Zakaria, Nordin

2017-01-01

Data compression and encryption are key components of commonly deployed platforms such as Hadoop. Numerous data compression and encryption tools are presently available on such platforms and the tools are characteristically applied in sequence, i.e., compression followed by encryption or encryption followed by compression. This paper focuses on the open-source Hadoop framework and proposes a data storage method that efficiently couples data compression with encryption. A simultaneous compression and encryption scheme is introduced that addresses an important implementation issue of source coding based on Tent Map and Piece-wise Linear Chaotic Map (PWLM), which is the infinite precision of real numbers that result from their long products. The approach proposed here solves the implementation issue by removing fractional components that are generated by the long products of real numbers. Moreover, it incorporates a stealth key that performs a cyclic shift in PWLM without compromising compression capabilities. In addition, the proposed approach implements a masking pseudorandom keystream that enhances encryption quality. The proposed algorithm demonstrated a congruent fit within the Hadoop framework, providing robust encryption security and compression. PMID:28072850

Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion.

PubMed

Zhao, Wenyi; Zhang, Chao

2008-07-01

We propose a framework for scene-based nonuniformity correction (NUC) and nonuniformity correction and enhancement (NUCE) that is required for focal-plane array-like sensors to obtain clean and enhanced-quality images. The core of the proposed framework is a novel registration-based nonuniformity correction super-resolution (NUCSR) method that is bootstrapped by statistical scene-based NUC methods. Based on a comprehensive imaging model and an accurate parametric motion estimation, we are able to remove severe/structured nonuniformity and in the presence of subpixel motion to simultaneously improve image resolution. One important feature of our NUCSR method is the adoption of a parametric motion model that allows us to (1) handle many practical scenarios where parametric motions are present and (2) carry out perfect super-resolution in principle by exploring available subpixel motions. Experiments with real data demonstrate the efficiency of the proposed NUCE framework and the effectiveness of the NUCSR method.

Development and Validation of an Analytical Methodology Based on Liquid Chromatography-Electrospray Tandem Mass Spectrometry for the Simultaneous Determination of Phenolic Compounds in Olive Leaf Extract.

PubMed

Cittan, Mustafa; Çelik, Ali

2018-04-01

A simple method was validated for the analysis of 31 phenolic compounds using liquid chromatography-electrospray tandem mass spectrometry. Proposed method was successfully applied to the determination of phenolic compounds in an olive leaf extract and 24 compounds were analyzed quantitatively. Olive biophenols were extracted from olive leaves by using microwave-assisted extraction with acceptable recovery values between 78.1 and 108.7%. Good linearities were obtained with correlation coefficients over 0.9916 from calibration curves of the phenolic compounds. The limits of quantifications were from 0.14 to 3.2 μg g-1. Intra-day and inter-day precision studies indicated that the proposed method was repeatable. As a result, it was confirmed that the proposed method was highly reliable for determination of the phenolic species in olive leaf extracts.

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Simultaneous Determination of Glass Transition Temperatures of Several Polymers

PubMed Central

He, Jiang; Liu, Wei; Huang, Yao-Xiong

2016-01-01

Aims A simple and easy optical method is proposed for the determination of glass transition temperature (Tg) of polymers. Methods & Results Tg was determined using the technique of microsphere imaging to monitor the variation of the refractive index of polymer microsphere as a function of temperature. It was demonstrated that the method can eliminate most thermal lag and has sensitivity about six fold higher than the conventional method in Tg determination. So the determined Tg is more accurate and varies less with cooling/heating rate than that obtained by conventional methods. The most attractive character of the method is that it can simultaneously determine the Tg of several polymers in a single experiment, so it can greatly save experimental time and heating energy. Conclusion The method is not only applicable for polymer microspheres, but also for the materials with arbitrary shapes. Therefore, it is expected to be broadly applied to different fundamental researches and practical applications of polymers. PMID:26985670

Evaluation of a method for the simultaneous quantification of N-nitrosamines in water samples based on stir bar sorptive extraction combined with high-performance liquid chromatography and diode array detection.

PubMed

Talebpour, Zahra; Rostami, Simindokht; Rezadoost, Hassan

2015-05-01

A simple, sensitive, and reliable procedure based on stir bar sorptive extraction coupled with high-performance liquid chromatography was applied to simultaneously extract and determine three semipolar nitrosamines including N-nitrosodibutylamine, N-nitrosodiphenylamine, and N-nitrosodicyclohexylamine. To achieve the optimum conditions, the effective parameters on the extraction efficiency including desorption solvent and time, ionic strength of sample, extraction time, and sample volume were systematically investigated. The optimized extraction procedure was carried out by stir bars coated with polydimethylsiloxane. Under optimum extraction conditions, the performance of the proposed method was studied. The linear dynamic range was obtained in the range of 0.95-1000 ng/mL (r = 0.9995), 0.26-1000 ng/mL (r = 0.9988) and both 0.32-100 ng/mL (r = 0.9999) and 100-1000 ng/mL (r = 0.9998) with limits of detection of 0.28, 0.08, and 0.09 ng/mL for N-nitrosodibutylamine, N-nitrosodiphenylamine, and N-nitrosodicyclohexylamine, respectively. The average recoveries were obtained >81%, and the reproducibility of the proposed method presented as intra- and interday precision were also found with a relative standard deviation <6%. Finally, the proposed method was successfully applied to the determination of trace amounts of selected nitrosamines in various water and wastewater samples and the obtained results were confirmed using mass spectrometry. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

In Search of Easy-to-Use Methods for Calibrating ADCP's for Velocity and Discharge Measurements

USGS Publications Warehouse

Oberg, K.; ,

2002-01-01

A cost-effective procedure for calibrating acoustic Doppler current profilers (ADCP) in the field was presented. The advantages and disadvantages of various methods which are used for calibrating ADCP were discussed. The proposed method requires the use of differential global positioning system (DGPS) with sub-meter accuracy and standard software for collecting ADCP data. The method involves traversing a long (400-800 meter) course at a constant compass heading and speed, while collecting simultaneous DGPS and ADCP data.

Study of aluminum particle combustion in solid propellant plumes using digital in-line holography and imaging pyrometry

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

Chen, Yi; Guildenbecher, Daniel R.; Hoffmeister, Kathryn N. G.

The combustion of molten metals is an important area of study with applications ranging from solid aluminized rocket propellants to fireworks displays. Our work uses digital in-line holography (DIH) to experimentally quantify the three-dimensional position, size, and velocity of aluminum particles during combustion of ammonium perchlorate (AP) based solid-rocket propellants. Additionally, spatially resolved particle temperatures are simultaneously measured using two-color imaging pyrometry. To allow for fast characterization of the properties of tens of thousands of particles, automated data processing routines are proposed. In using these methods, statistics from aluminum particles with diameters ranging from 15 to 900 µm are collectedmore » at an ambient pressure of 83 kPa. In the first set of DIH experiments, increasing initial propellant temperature is shown to enhance the agglomeration of nascent aluminum at the burning surface, resulting in ejection of large molten aluminum particles into the exhaust plume. The resulting particle number and volume distributions are quantified. In the second set of simultaneous DIH and pyrometry experiments, particle size and velocity relationships as well as temperature statistics are explored. The average measured temperatures are found to be 2640 ± 282 K, which compares well with previous estimates of the range of particle and gas-phase temperatures. The novel methods proposed here represent new capabilities for simultaneous quantification of the joint size, velocity, and temperature statistics during the combustion of molten metal particles. The proposed techniques are expected to be useful for detailed performance assessment of metalized solid-rocket propellants.« less

Study of aluminum particle combustion in solid propellant plumes using digital in-line holography and imaging pyrometry

DOE PAGES

Chen, Yi; Guildenbecher, Daniel R.; Hoffmeister, Kathryn N. G.; ...

2017-05-05

The combustion of molten metals is an important area of study with applications ranging from solid aluminized rocket propellants to fireworks displays. Our work uses digital in-line holography (DIH) to experimentally quantify the three-dimensional position, size, and velocity of aluminum particles during combustion of ammonium perchlorate (AP) based solid-rocket propellants. Additionally, spatially resolved particle temperatures are simultaneously measured using two-color imaging pyrometry. To allow for fast characterization of the properties of tens of thousands of particles, automated data processing routines are proposed. In using these methods, statistics from aluminum particles with diameters ranging from 15 to 900 µm are collectedmore » at an ambient pressure of 83 kPa. In the first set of DIH experiments, increasing initial propellant temperature is shown to enhance the agglomeration of nascent aluminum at the burning surface, resulting in ejection of large molten aluminum particles into the exhaust plume. The resulting particle number and volume distributions are quantified. In the second set of simultaneous DIH and pyrometry experiments, particle size and velocity relationships as well as temperature statistics are explored. The average measured temperatures are found to be 2640 ± 282 K, which compares well with previous estimates of the range of particle and gas-phase temperatures. The novel methods proposed here represent new capabilities for simultaneous quantification of the joint size, velocity, and temperature statistics during the combustion of molten metal particles. The proposed techniques are expected to be useful for detailed performance assessment of metalized solid-rocket propellants.« less

Robust check loss-based variable selection of high-dimensional single-index varying-coefficient model

NASA Astrophysics Data System (ADS)

Song, Yunquan; Lin, Lu; Jian, Ling

2016-07-01

Single-index varying-coefficient model is an important mathematical modeling method to model nonlinear phenomena in science and engineering. In this paper, we develop a variable selection method for high-dimensional single-index varying-coefficient models using a shrinkage idea. The proposed procedure can simultaneously select significant nonparametric components and parametric components. Under defined regularity conditions, with appropriate selection of tuning parameters, the consistency of the variable selection procedure and the oracle property of the estimators are established. Moreover, due to the robustness of the check loss function to outliers in the finite samples, our proposed variable selection method is more robust than the ones based on the least squares criterion. Finally, the method is illustrated with numerical simulations.

Formative Research in Attention and Appeal: A Series of Proposals.

ERIC Educational Resources Information Center

Mielke, Keith W.; Bryant, Jennings, Jr.

Methods are suggested to measure the program appeal and audience attention of Children's Television Workshop productions. Among these are distractor techniques, one which permits subjects to discriminate between two simultaneously broadcast programs by selecting the audio track they most prefer and one used to rank order several programs.…

Simultaneous chromatic dispersion, polarization-mode-dispersion and OSNR monitoring at 40Gbit/s.

PubMed

Baker-Meflah, Lamia; Thomsen, Benn; Mitchell, John; Bayvel, Polina

2008-09-29

A novel method for independent and simultaneous monitoring of chromatic dispersion (CD), first-order PMD and OSNR in 40Gbit/s systems is proposed and demonstrated. This is performed using in-band tone monitoring of 5GHz, optically down-converted to a low intermediate-frequency (IF) of 10kHz. The measurement provides a large monitoring range with good accuracies for CD (4742+/-100ps/nm), differential group delay (DGD) (200+/-4ps) and OSNR (23+/-1dB), independently of the bit-rate. In addition, the use of electro-absorption modulators (EAM) for the simultaneous down-conversion of all channels and the use of low-speed detectors makes it cost effective for multi-channel operation.

Novel spectrophotometric methods for simultaneous determination of Amlodipine, Valsartan and Hydrochlorothiazide in their ternary mixture

NASA Astrophysics Data System (ADS)

Lotfy, Hayam M.; Hegazy, Maha A.; Mowaka, Shereen; Mohamed, Ekram Hany

2015-04-01

This work represents a comparative study of two smart spectrophotometric techniques namely; successive resolution and progressive resolution for the simultaneous determination of ternary mixtures of Amlodipine (AML), Hydrochlorothiazide (HCT) and Valsartan (VAL) without prior separation steps. These techniques consist of several consecutive steps utilizing zero and/or ratio and/or derivative spectra. By applying successive spectrum subtraction coupled with constant multiplication method, the proposed drugs were obtained in their zero order absorption spectra and determined at their maxima 237.6 nm, 270.5 nm and 250 nm for AML, HCT and VAL, respectively; while by applying successive derivative subtraction they were obtained in their first derivative spectra and determined at P230.8-246, P261.4-278.2, P233.7-246.8 for AML, HCT and VAL respectively. While in the progressive resolution, the concentrations of the components were determined progressively from the same zero order absorption spectrum using absorbance subtraction coupled with absorptivity factor methods or from the same ratio spectrum using only one divisor via amplitude modulation method can be used for the determination of ternary mixtures using only one divisor where the concentrations of the components are determined progressively. The proposed methods were checked using laboratory-prepared mixtures and were successfully applied for the analysis of pharmaceutical formulation containing the cited drugs. Moreover comparative study between spectrum addition technique as a novel enrichment technique and a well established one namely spiking technique was adopted for the analysis of pharmaceutical formulations containing low concentration of AML. The methods were validated as per ICH guidelines where accuracy, precision and specificity were found to be within their acceptable limits. The results obtained from the proposed methods were statistically compared with the reported one where no significant difference was observed.

Real time quantitative phase microscopy based on single-shot transport of intensity equation (ssTIE) method

NASA Astrophysics Data System (ADS)

Yu, Wei; Tian, Xiaolin; He, Xiaoliang; Song, Xiaojun; Xue, Liang; Liu, Cheng; Wang, Shouyu

2016-08-01

Microscopy based on transport of intensity equation provides quantitative phase distributions which opens another perspective for cellular observations. However, it requires multi-focal image capturing while mechanical and electrical scanning limits its real time capacity in sample detections. Here, in order to break through this restriction, real time quantitative phase microscopy based on single-shot transport of the intensity equation method is proposed. A programmed phase mask is designed to realize simultaneous multi-focal image recording without any scanning; thus, phase distributions can be quantitatively retrieved in real time. It is believed the proposed method can be potentially applied in various biological and medical applications, especially for live cell imaging.

Abnormality detection of mammograms by discriminative dictionary learning on DSIFT descriptors.

PubMed

Tavakoli, Nasrin; Karimi, Maryam; Nejati, Mansour; Karimi, Nader; Reza Soroushmehr, S M; Samavi, Shadrokh; Najarian, Kayvan

2017-07-01

Detection and classification of breast lesions using mammographic images are one of the most difficult studies in medical image processing. A number of learning and non-learning methods have been proposed for detecting and classifying these lesions. However, the accuracy of the detection/classification still needs improvement. In this paper we propose a powerful classification method based on sparse learning to diagnose breast cancer in mammograms. For this purpose, a supervised discriminative dictionary learning approach is applied on dense scale invariant feature transform (DSIFT) features. A linear classifier is also simultaneously learned with the dictionary which can effectively classify the sparse representations. Our experimental results show the superior performance of our method compared to existing approaches.

Wavelength-division-multiplexing method of polarized low-coherence interferometry for fiber Fabry-Perot interferometric sensors.

PubMed

Yin, Jinde; Liu, Tiegen; Jiang, Junfeng; Liu, Kun; Wang, Shuang; Wu, Fan; Ding, Zhenyang

2013-10-01

We propose a new wavelength-division-multiplexing method for extrinsic fiber Fabry-Perot interferometric (EFPI) sensing in a polarized low-coherence interferometer configuration. In the proposed method, multiple LED sources are used with different center wavelengths, and each LED is used by a specific sensing channel, and therefore the spatial frequency of the low-coherence interferogram of each channel can be separated. A bandpass filter is used to extract the low-coherence interferogram of each EFPI channel, and thus the cavity length of each EFPI channel can be identified through demultiplexing. We successfully demonstrate the simultaneous demodulation of EFPI sensors with same nominal cavity length while maintaining high measurement precision.

General design method of ultra-broadband perfect absorbers based on magnetic polaritons.

PubMed

Liu, Yuanbin; Qiu, Jun; Zhao, Junming; Liu, Linhua

2017-10-02

Starting from one-dimensional gratings and the theory of magnetic polaritons (MPs), we propose a general design method of ultra-broadband perfect absorbers. Based on the proposed design method, the obtained absorber can keep the spectrum-average absorptance over 99% at normal incidence in a wide range of wavelengths; this work simultaneously reveals the robustness of the absorber to incident angles and polarization angles of incident light. Furthermore, this work shows that the spectral band of perfect absorption can be flexibly extended to near the infrared regime by adjusting the structure dimension. The findings of this work may facilitate the active design of ultra-broadband absorbers based on plasmonic nanostructures.

Multi-views storage model and access methods of conversation history in converged IP messaging system

NASA Astrophysics Data System (ADS)

Lu, Meilian; Yang, Dong; Zhou, Xing

2013-03-01

Based on the analysis of the requirements of conversation history storage in CPM (Converged IP Messaging) system, a Multi-views storage model and access methods of conversation history are proposed. The storage model separates logical views from physical storage and divides the storage into system managed region and user managed region. It simultaneously supports conversation view, system pre-defined view and user-defined view of storage. The rationality and feasibility of multi-view presentation, the physical storage model and access methods are validated through the implemented prototype. It proves that, this proposal has good scalability, which will help to optimize the physical data storage structure and improve storage performance.

Multiple defocused coherent diffraction imaging: method for simultaneously reconstructing objects and probe using X-ray free-electron lasers.

PubMed

Hirose, Makoto; Shimomura, Kei; Suzuki, Akihiro; Burdet, Nicolas; Takahashi, Yukio

2016-05-30

The sample size must be less than the diffraction-limited focal spot size of the incident beam in single-shot coherent X-ray diffraction imaging (CXDI) based on a diffract-before-destruction scheme using X-ray free electron lasers (XFELs). This is currently a major limitation preventing its wider applications. We here propose multiple defocused CXDI, in which isolated objects are sequentially illuminated with a divergent beam larger than the objects and the coherent diffraction pattern of each object is recorded. This method can simultaneously reconstruct both objects and a probe from the coherent X-ray diffraction patterns without any a priori knowledge. We performed a computer simulation of the prposed method and then successfully demonstrated it in a proof-of-principle experiment at SPring-8. The prposed method allows us to not only observe broad samples but also characterize focused XFEL beams.

Doubly negative isotropic elastic metamaterial for sub-wavelength focusing: Design and realization

NASA Astrophysics Data System (ADS)

Oh, Joo Hwan; Seung, Hong Min; Kim, Yoon Young

2017-12-01

In spite of much progress in elastic metamaterials, tuning the effective density and stiffness to desired values ranging from negatives to large positives is still difficult. In particular, simultaneous realization of double negativity and isotropy, critical in sub-wavelength focusing, is very challenging since anisotropy is usually unavoidable in resonance-based metamaterials. The main difficulty is that there is no established systematic design method for simultaneous achieving of double negativity and isotropy. Thus, we propose a unique elastic metamaterial unit cell with which simultaneous realization can be achieved by an explicit step-by-step approach. The unit cell of the proposed metamaterial can be accurately modeled as an equivalent mass-spring system so that the effective properties can be easily controlled with the design parameters. The actual realization was carried out by acquiring the desired properties in sequential steps which is in detail. The specific application for this study is on sub-wavelength focusing, which will be demonstrated by waves from a single point source focused on a region smaller than half the wavelength. Actual experiments were performed on an aluminum plate where the designed metamaterial flat lens was imbedded. The results acquired through simulations and experiments suggest potential applications of the proposed metamaterial and the systematic design approach in advanced acoustic surgery or non-destructive testing.

MIP Models and Hybrid Algorithms for Simultaneous Job Splitting and Scheduling on Unrelated Parallel Machines

PubMed Central

Ozmutlu, H. Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204

Object Tracking and Target Reacquisition Based on 3-D Range Data for Moving Vehicles

PubMed Central

Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

2013-01-01

In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle component analysis (PCA) of shape information is proposed. In the proposed method, if the target disappears out of frame, shape similarity energy is used to detect target candidates that match a template shape learned online from previously observed frames. Thus, we require no a priori knowledge of the target’s shape. Experimental results show the practical applicability and robustness of the proposed algorithm in realistic tracking scenarios. PMID:21486717

Three-dimensional face pose detection and tracking using monocular videos: tool and application.

PubMed

Dornaika, Fadi; Raducanu, Bogdan

2009-08-01

Recently, we have proposed a real-time tracker that simultaneously tracks the 3-D head pose and facial actions in monocular video sequences that can be provided by low quality cameras. This paper has two main contributions. First, we propose an automatic 3-D face pose initialization scheme for the real-time tracker by adopting a 2-D face detector and an eigenface system. Second, we use the proposed methods-the initialization and tracking-for enhancing the human-machine interaction functionality of an AIBO robot. More precisely, we show how the orientation of the robot's camera (or any active vision system) can be controlled through the estimation of the user's head pose. Applications based on head-pose imitation such as telepresence, virtual reality, and video games can directly exploit the proposed techniques. Experiments on real videos confirm the robustness and usefulness of the proposed methods.

A Heckman selection model for the safety analysis of signalized intersections

PubMed Central

Wong, S. C.; Zhu, Feng; Pei, Xin; Huang, Helai; Liu, Youjun

2017-01-01

Purpose The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously. Methods This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI), respectively. The model uses 555 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during two years. Results The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels. Conclusions A comparison with the existing approaches suggests that the Heckman selection model offers an efficient and convenient alternative method for evaluating the safety performance at signalized intersections. PMID:28732050

Simultaneous extraction, identification and quantification of phenolic compounds in Eclipta prostrata using microwave-assisted extraction combined with HPLC-DAD-ESI-MS/MS.

PubMed

Fang, Xinsheng; Wang, Jianhua; Hao, Jifu; Li, Xueke; Guo, Ning

2015-12-01

A simple and rapid method was developed using microwave-assisted extraction (MAE) combined with HPLC-DAD-ESI-MS/MS for the simultaneous extraction, identification, and quantification of phenolic compounds in Eclipta prostrata, a common herb and vegetable in China. The optimized parameters of MAE were: employing 50% ethanol as solvent, microwave power 400 W, temperature 70 °C, ratio of liquid/solid 30 mL/g and extraction time 2 min. Compared to conventional extraction methods, the optimized MAE can avoid the degradation of the phenolic compounds and simultaneously obtained the highest yields of all components faster with less consumption of solvent and energy. Six phenolic acids, six flavonoid glycosides and one coumarin were firstly identified. The phenolic compounds were quantified by HPLC-DAD with good linearity, precision, and accuracy. The extract obtained by MAE showed significant antioxidant activity. The proposed method provides a valuable and green analytical methodology for the investigation of phenolic components in natural plants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Simultaneous determination of flavonoids, isochlorogenic acids and triterpenoids in Ilex hainanensis Using high performance liquid chromatography coupled with diode array and evaporative light scattering detection.

PubMed

Peng, Bo; Qiao, Chun-Feng; Zhao, Jing; Huang, Wei-Hua; Hu, De-Jun; Liu, Hua-Gang; Li, Shao-Ping

2013-03-04

A high performance liquid chromatography coupled with diode array and evaporative light scattering detection (HPLC-DAD-ELSD) method for simultaneous determination of eight major bioactive compounds including two flavonoids (rutin and eriodictyol-7-O-β-D-glucopyranoside), two isochlorogenic acids (isochlorogenic acid A and isochlorogenic acid C) and four triterpenoids (ilexhainanoside D, ilexsaponin A1, ilexgenin A and ursolic acid) in Ilex hainanensis has been developed for the first time. The 283 nm wavelength was chosen for determination of two flavonoids and two isochlorogenic acids. ELSD was applied to determine four triterpenoids. The analysis was performed on an Agilent Zorbax SB-C18 column (250 × 4.6 mm i.d., 5 µm) with gradient elution of 0.2% formic acid in water and acetonitrile. The method was validated for linearity, limit of detection, limit of quantification, precision, repeatability and accuracy. The proposed method has been successfully applied for simultaneous quantification of the analytes in four samples of Ilex hainanensis, which is helpful for quality control of this plant.

A method of bias correction for maximal reliability with dichotomous measures.

PubMed

Penev, Spiridon; Raykov, Tenko

2010-02-01

This paper is concerned with the reliability of weighted combinations of a given set of dichotomous measures. Maximal reliability for such measures has been discussed in the past, but the pertinent estimator exhibits a considerable bias and mean squared error for moderate sample sizes. We examine this bias, propose a procedure for bias correction, and develop a more accurate asymptotic confidence interval for the resulting estimator. In most empirically relevant cases, the bias correction and mean squared error correction can be performed simultaneously. We propose an approximate (asymptotic) confidence interval for the maximal reliability coefficient, discuss the implementation of this estimator, and investigate the mean squared error of the associated asymptotic approximation. We illustrate the proposed methods using a numerical example.

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering

PubMed Central

Almeida, Fernando R.; Brayner, Angelo; Rodrigues, Joel J. P. C.; Maia, Jose E. Bessa

2017-01-01

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering. To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE). PMID:28590450

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering.

PubMed

Almeida, Fernando R; Brayner, Angelo; Rodrigues, Joel J P C; Maia, Jose E Bessa

2017-06-07

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering . To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE).

A dynamic multi-level optimal design method with embedded finite-element modeling for power transformers

NASA Astrophysics Data System (ADS)

Zhang, Yunpeng; Ho, Siu-lau; Fu, Weinong

2018-05-01

This paper proposes a dynamic multi-level optimal design method for power transformer design optimization (TDO) problems. A response surface generated by second-order polynomial regression analysis is updated dynamically by adding more design points, which are selected by Shifted Hammersley Method (SHM) and calculated by finite-element method (FEM). The updating stops when the accuracy requirement is satisfied, and optimized solutions of the preliminary design are derived simultaneously. The optimal design level is modulated through changing the level of error tolerance. Based on the response surface of the preliminary design, a refined optimal design is added using multi-objective genetic algorithm (MOGA). The effectiveness of the proposed optimal design method is validated through a classic three-phase power TDO problem.

Kinetic analysis of non-isothermal solid-state reactions: multi-stage modeling without assumptions in the reaction mechanism.

PubMed

Pomerantsev, Alexey L; Kutsenova, Alla V; Rodionova, Oxana Ye

2017-02-01

A novel non-linear regression method for modeling non-isothermal thermogravimetric data is proposed. Experiments for several heating rates are analyzed simultaneously. The method is applicable to complex multi-stage processes when the number of stages is unknown. Prior knowledge of the type of kinetics is not required. The main idea is a consequent estimation of parameters when the overall model is successively changed from one level of modeling to another. At the first level, the Avrami-Erofeev functions are used. At the second level, the Sestak-Berggren functions are employed with the goal to broaden the overall model. The method is tested using both simulated and real-world data. A comparison of the proposed method with a recently published 'model-free' deconvolution method is presented.

Development and Validation of Eco-Friendly Liquid Chromatographic and Spectrophotometric Methods for Simultaneous Determination of Coformulated Drugs: Phenylephrine Hydrochloride and Prednisolone Acetate.

PubMed

Mostafa, Nadia M; Elsayed, Ghada M; Hassan, Nagiba Y; El Mously, Dina A

2017-11-01

Five simple, sensitive, and eco-friendly LC and UV spectrophotometric methods have been developed for the simultaneous determination of phenylephrine hydrochloride (PHE) and prednisolone acetate (PRD) in their combined dosage form. The first method was reversed-phase (RP) LC using methanol-water-heptane-1-sulfonic acid sodium salt (75 + 25 + 0.1, v/v/w) as a mobile phase. Separation was achieved using an XSelect HSS reversed-phase C18 analytical column (250 × 4.6 mm, 5µm). The flow rate was 1.0 mL/min and UV detection was done at 230 nm. Quantification was achieved over the concentration ranges of 5-50 µg/mL for PHE and 2-90 µg/mL for PRD. Four spectrophotometric methods were proposed, namely dual wavelength, first derivative of ratio spectra, ratio difference, and mean-centering of ratio spectra. Linearity was observed in the concentration ranges of 10-120 and 5-35 µg/mL for PHE and PRD, respectively, for the spectrophotometric methods. Green solvents were used in the proposed methods because they play a vital role in the analytical methods' influence on the environment. The suggested methods were validated regarding linearity, accuracy, and precision according to the International Conference on Harmonization guidelines, with satisfactory results. These methods could be used as harmless substitutes for routine analysis of the mentioned drugs, with no interference from excipients.

Simultaneous determination of macronutrients, micronutrients and trace elements in mineral fertilizers by inductively coupled plasma optical emission spectrometry

NASA Astrophysics Data System (ADS)

de Oliveira Souza, Sidnei; da Costa, Silvânio Silvério Lopes; Santos, Dayane Melo; dos Santos Pinto, Jéssica; Garcia, Carlos Alexandre Borges; Alves, José do Patrocínio Hora; Araujo, Rennan Geovanny Oliveira

2014-06-01

An analytical method for simultaneous determination of macronutrients (Ca, Mg, Na and P), micronutrients (Cu, Fe, Mn and Zn) and trace elements (Al, As, Cd, Pb and V) in mineral fertilizers was optimized. Two-level full factorial design was applied to evaluate the optimal proportions of reagents used in the sample digestion on hot plate. A Doehlert design for two variables was used to evaluate the operating conditions of the inductively coupled plasma optical emission spectrometer in order to accomplish the simultaneous determination of the analyte concentrations. The limits of quantification (LOQs) ranged from 2.0 mg kg- 1 for Mn to 77.3 mg kg- 1 for P. The accuracy and precision of the proposed method were evaluated by analysis of standard reference materials (SRMs) of Western phosphate rock (NIST 694), Florida phosphate rock (NIST 120C) and Trace elements in multi-nutrient fertilizer (NIST 695), considered to be adequate for simultaneous determination. Twenty-one samples of mineral fertilizers collected in Sergipe State, Brazil, were analyzed. For all samples, the As, Ca, Cd and Pb concentrations were below the LOQ values of the analytical method. For As, Cd and Pb the obtained LOQ values were below the maximum limit allowed by the Brazilian Ministry of Agriculture, Livestock and Food Supply (Ministério da Agricultura, Pecuária e Abastecimento - MAPA). The optimized method presented good accuracy and was effectively applied to quantitative simultaneous determination of the analytes in mineral fertilizers by inductively coupled plasma optical emission spectrometry (ICP OES).

Simultaneous fault detection and control design for switched systems with two quantized signals.

PubMed

Li, Jian; Park, Ju H; Ye, Dan

2017-01-01

The problem of simultaneous fault detection and control design for switched systems with two quantized signals is presented in this paper. Dynamic quantizers are employed, respectively, before the output is passed to fault detector, and before the control input is transmitted to the switched system. Taking the quantized errors into account, the robust performance for this kind of system is given. Furthermore, sufficient conditions for the existence of fault detector/controller are presented in the framework of linear matrix inequalities, and fault detector/controller gains and the supremum of quantizer range are derived by a convex optimized method. Finally, two illustrative examples demonstrate the effectiveness of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Simultaneous tracking and regulation visual servoing of wheeled mobile robots with uncalibrated extrinsic parameters

NASA Astrophysics Data System (ADS)

Lu, Qun; Yu, Li; Zhang, Dan; Zhang, Xuebo

2018-01-01

This paper presentsa global adaptive controller that simultaneously solves tracking and regulation for wheeled mobile robots with unknown depth and uncalibrated camera-to-robot extrinsic parameters. The rotational angle and the scaled translation between the current camera frame and the reference camera frame, as well as the ones between the desired camera frame and the reference camera frame can be calculated in real time by using the pose estimation techniques. A transformed system is first obtained, for which an adaptive controller is then designed to accomplish both tracking and regulation tasks, and the controller synthesis is based on Lyapunov's direct method. Finally, the effectiveness of the proposed method is illustrated by a simulation study.

A fast, reliable, ultra high performance liquid chromatography method for the simultaneous determination of amino acids, biogenic amines and ammonium ions in cheese, using diethyl ethoxymethylenemalonate as a derivatising agent.

PubMed

Redruello, Begoña; Ladero, Victor; Cuesta, Isabel; Álvarez-Buylla, Jorge R; Martín, María Cruz; Fernández, María; Alvarez, Miguel A

2013-08-15

Derivatisation treatment with diethyl ethoxymethylenemalonate followed by ultra-HPLC allowed the simultaneous quantification of 22 amino acids, 7 biogenic amines and ammonium ions in cheese samples in under 10 min. This is the fastest elution time ever reported for such a resolution. The proposed method shows good linearity (R(2)>0.995) and sensitivity (detection limit 0.08-3.91 μM; quantification limit <13.02 μM). Intra- and inter-day repeatability ranged from 0.35% to 1.25% and from 0.85% to 5.2%, respectively. No significant effect of the cheese matrix was observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Simultaneous auto-calibration and gradient delays estimation (SAGE) in non-Cartesian parallel MRI using low-rank constraints.

PubMed

Jiang, Wenwen; Larson, Peder E Z; Lustig, Michael

2018-03-09

To correct gradient timing delays in non-Cartesian MRI while simultaneously recovering corruption-free auto-calibration data for parallel imaging, without additional calibration scans. The calibration matrix constructed from multi-channel k-space data should be inherently low-rank. This property is used to construct reconstruction kernels or sensitivity maps. Delays between the gradient hardware across different axes and RF receive chain, which are relatively benign in Cartesian MRI (excluding EPI), lead to trajectory deviations and hence data inconsistencies for non-Cartesian trajectories. These in turn lead to higher rank and corrupted calibration information which hampers the reconstruction. Here, a method named Simultaneous Auto-calibration and Gradient delays Estimation (SAGE) is proposed that estimates the actual k-space trajectory while simultaneously recovering the uncorrupted auto-calibration data. This is done by estimating the gradient delays that result in the lowest rank of the calibration matrix. The Gauss-Newton method is used to solve the non-linear problem. The method is validated in simulations using center-out radial, projection reconstruction and spiral trajectories. Feasibility is demonstrated on phantom and in vivo scans with center-out radial and projection reconstruction trajectories. SAGE is able to estimate gradient timing delays with high accuracy at a signal to noise ratio level as low as 5. The method is able to effectively remove artifacts resulting from gradient timing delays and restore image quality in center-out radial, projection reconstruction, and spiral trajectories. The low-rank based method introduced simultaneously estimates gradient timing delays and provides accurate auto-calibration data for improved image quality, without any additional calibration scans. © 2018 International Society for Magnetic Resonance in Medicine.

Simultaneous determination of rosuvastatin and propranolol in their binary mixture by synchronous spectrofluorimetry.

PubMed

El-Abasawi, Nasr M; Attia, Khalid A M; Abo-Serie, Ahmad A M; Morshedy, Samir; Abdel-Fattah, Ashraf

2018-06-05

Simultaneous determination of rosuvastatin calcium and propranolol hydrochloride using the first derivative synchronous spectrofluorimetry was described. This method involves measuring the synchronous fluorescence of both drugs in ethanol using, ∆ λ = 60 nm then the first derivative was recorded and the peak amplitudes were measured at 350 and 374 nm for rosuvastatin calcium and propranolol hydrochloride, respectively. Under the optimum conditions, the linear ranges of rosuvastatin calcium and propranolol hydrochloride were 0.2-2 μg/mL and 0.1-1 μg/mL, respectively. The method was used for quantitative analysis of the drugs in raw materials and pharmaceutical dosage form. The validity of the proposed method was assessed according to an international conference on harmonization (ICH) guidelines. Copyright © 2018 Elsevier B.V. All rights reserved.

A New Computational Technique for the Generation of Optimised Aircraft Trajectories

NASA Astrophysics Data System (ADS)

Chircop, Kenneth; Gardi, Alessandro; Zammit-Mangion, David; Sabatini, Roberto

2017-12-01

A new computational technique based on Pseudospectral Discretisation (PSD) and adaptive bisection ɛ-constraint methods is proposed to solve multi-objective aircraft trajectory optimisation problems formulated as nonlinear optimal control problems. This technique is applicable to a variety of next-generation avionics and Air Traffic Management (ATM) Decision Support Systems (DSS) for strategic and tactical replanning operations. These include the future Flight Management Systems (FMS) and the 4-Dimensional Trajectory (4DT) planning and intent negotiation/validation tools envisaged by SESAR and NextGen for a global implementation. In particular, after describing the PSD method, the adaptive bisection ɛ-constraint method is presented to allow an efficient solution of problems in which two or multiple performance indices are to be minimized simultaneously. Initial simulation case studies were performed adopting suitable aircraft dynamics models and addressing a classical vertical trajectory optimisation problem with two objectives simultaneously. Subsequently, a more advanced 4DT simulation case study is presented with a focus on representative ATM optimisation objectives in the Terminal Manoeuvring Area (TMA). The simulation results are analysed in-depth and corroborated by flight performance analysis, supporting the validity of the proposed computational techniques.

A 2.5D Map-Based Mobile Robot Localization via Cooperation of Aerial and Ground Robots

PubMed Central

Nam, Tae Hyeon; Shim, Jae Hong; Cho, Young Im

2017-01-01

Recently, there has been increasing interest in studying the task coordination of aerial and ground robots. When a robot begins navigation in an unknown area, it has no information about the surrounding environment. Accordingly, for robots to perform tasks based on location information, they need a simultaneous localization and mapping (SLAM) process that uses sensor information to draw a map of the environment, while simultaneously estimating the current location of the robot on the map. This paper aims to present a localization method based in cooperation between aerial and ground robots in an indoor environment. The proposed method allows a ground robot to reach accurate destination by using a 2.5D elevation map built by a low-cost RGB-D (Red Green and Blue-Depth) sensor and 2D Laser sensor attached onto an aerial robot. A 2.5D elevation map is formed by projecting height information of an obstacle using depth information obtained by the RGB-D sensor onto a grid map, which is generated by using the 2D Laser sensor and scan matching. Experimental results demonstrate the effectiveness of the proposed method for its accuracy in location recognition and computing speed. PMID:29186843

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

NASA Astrophysics Data System (ADS)

Zakšek, K.; Hort, M.; Zaletelj, J.; Langmann, B.

2012-09-01

Volcanic ash cloud top height (ACTH) can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach over 30 km which implies ACTH of more than 12 km in the beginning of the eruption. In the end of April eruption ACTH of 3-4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

NASA Astrophysics Data System (ADS)

Zakšek, K.; Hort, M.; Zaletelj, J.; Langmann, B.

2013-03-01

Volcanic ash cloud-top height (ACTH) can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach 30 km, which implies an ACTH of approximately 12 km at the beginning of the eruption. At the end of April eruption an ACTH of 3-4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

Simultaneous grouping pursuit and feature selection over an undirected graph*

PubMed Central

Zhu, Yunzhang; Shen, Xiaotong; Pan, Wei

2013-01-01

Summary In high-dimensional regression, grouping pursuit and feature selection have their own merits while complementing each other in battling the curse of dimensionality. To seek a parsimonious model, we perform simultaneous grouping pursuit and feature selection over an arbitrary undirected graph with each node corresponding to one predictor. When the corresponding nodes are reachable from each other over the graph, regression coefficients can be grouped, whose absolute values are the same or close. This is motivated from gene network analysis, where genes tend to work in groups according to their biological functionalities. Through a nonconvex penalty, we develop a computational strategy and analyze the proposed method. Theoretical analysis indicates that the proposed method reconstructs the oracle estimator, that is, the unbiased least squares estimator given the true grouping, leading to consistent reconstruction of grouping structures and informative features, as well as to optimal parameter estimation. Simulation studies suggest that the method combines the benefit of grouping pursuit with that of feature selection, and compares favorably against its competitors in selection accuracy and predictive performance. An application to eQTL data is used to illustrate the methodology, where a network is incorporated into analysis through an undirected graph. PMID:24098061

A 2.5D Map-Based Mobile Robot Localization via Cooperation of Aerial and Ground Robots.

PubMed

Nam, Tae Hyeon; Shim, Jae Hong; Cho, Young Im

2017-11-25

Recently, there has been increasing interest in studying the task coordination of aerial and ground robots. When a robot begins navigation in an unknown area, it has no information about the surrounding environment. Accordingly, for robots to perform tasks based on location information, they need a simultaneous localization and mapping (SLAM) process that uses sensor information to draw a map of the environment, while simultaneously estimating the current location of the robot on the map. This paper aims to present a localization method based in cooperation between aerial and ground robots in an indoor environment. The proposed method allows a ground robot to reach accurate destination by using a 2.5D elevation map built by a low-cost RGB-D (Red Green and Blue-Depth) sensor and 2D Laser sensor attached onto an aerial robot. A 2.5D elevation map is formed by projecting height information of an obstacle using depth information obtained by the RGB-D sensor onto a grid map, which is generated by using the 2D Laser sensor and scan matching. Experimental results demonstrate the effectiveness of the proposed method for its accuracy in location recognition and computing speed.

Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

PubMed Central

Xu, Xin; Gui, Rong; Pu, Fangling

2018-01-01

Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods. PMID:29510499

Transfer Learning for Class Imbalance Problems with Inadequate Data.

PubMed

Al-Stouhi, Samir; Reddy, Chandan K

2016-07-01

A fundamental problem in data mining is to effectively build robust classifiers in the presence of skewed data distributions. Class imbalance classifiers are trained specifically for skewed distribution datasets. Existing methods assume an ample supply of training examples as a fundamental prerequisite for constructing an effective classifier. However, when sufficient data is not readily available, the development of a representative classification algorithm becomes even more difficult due to the unequal distribution between classes. We provide a unified framework that will potentially take advantage of auxiliary data using a transfer learning mechanism and simultaneously build a robust classifier to tackle this imbalance issue in the presence of few training samples in a particular target domain of interest. Transfer learning methods use auxiliary data to augment learning when training examples are not sufficient and in this paper we will develop a method that is optimized to simultaneously augment the training data and induce balance into skewed datasets. We propose a novel boosting based instance-transfer classifier with a label-dependent update mechanism that simultaneously compensates for class imbalance and incorporates samples from an auxiliary domain to improve classification. We provide theoretical and empirical validation of our method and apply to healthcare and text classification applications.

Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks.

PubMed

Wang, Lei; Xu, Xin; Dong, Hao; Gui, Rong; Pu, Fangling

2018-03-03

Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods.

Data multiplexing in radio interferometric calibration

NASA Astrophysics Data System (ADS)

Yatawatta, Sarod; Diblen, Faruk; Spreeuw, Hanno; Koopmans, L. V. E.

2018-03-01

New and upcoming radio interferometers will produce unprecedented amount of data that demand extremely powerful computers for processing. This is a limiting factor due to the large computational power and energy costs involved. Such limitations restrict several key data processing steps in radio interferometry. One such step is calibration where systematic errors in the data are determined and corrected. Accurate calibration is an essential component in reaching many scientific goals in radio astronomy and the use of consensus optimization that exploits the continuity of systematic errors across frequency significantly improves calibration accuracy. In order to reach full consensus, data at all frequencies need to be calibrated simultaneously. In the SKA regime, this can become intractable if the available compute agents do not have the resources to process data from all frequency channels simultaneously. In this paper, we propose a multiplexing scheme that is based on the alternating direction method of multipliers with cyclic updates. With this scheme, it is possible to simultaneously calibrate the full data set using far fewer compute agents than the number of frequencies at which data are available. We give simulation results to show the feasibility of the proposed multiplexing scheme in simultaneously calibrating a full data set when a limited number of compute agents are available.

Simultaneous topography imaging and broadband nanomechanical mapping on atomic force microscope

NASA Astrophysics Data System (ADS)

Li, Tianwei; Zou, Qingze

2017-12-01

In this paper, an approach is proposed to achieve simultaneous imaging and broadband nanomechanical mapping of soft materials in air by using an atomic force microscope. Simultaneous imaging and nanomechanical mapping are needed, for example, to correlate the morphological and mechanical evolutions of the sample during dynamic phenomena such as the cell endocytosis process. Current techniques for nanomechanical mapping, however, are only capable of capturing static elasticity of the material, or the material viscoelasticity in a narrow frequency band around the resonant frequency(ies) of the cantilever used, not competent for broadband nanomechanical mapping, nor acquiring topography image of the sample simultaneously. These limitations are addressed in this work by enabling the augmentation of an excitation force stimuli of rich frequency spectrum for nanomechanical mapping in the imaging process. Kalman-filtering technique is exploited to decouple and split the mixed signals for imaging and mapping, respectively. Then the sample indentation generated is quantified online via a system-inversion method, and the effects of the indentation generated and the topography tracking error on the topography quantification are taken into account. Moreover, a data-driven feedforward-feedback control is utilized to track the sample topography. The proposed approach is illustrated through experimental implementation on a polydimethylsiloxane sample with a pre-fabricated pattern.

SiC nanoparticles-modified glassy carbon electrodes for simultaneous determination of purine and pyrimidine DNA bases.

PubMed

Ghavami, Raouf; Salimi, Abdollah; Navaee, Aso

2011-05-15

For the first time a novel and simple electrochemical method was used for simultaneous detection of DNA bases (guanine, adenine, thymine and cytosine) without any pretreatment or separation process. Glassy carbon electrode modified with silicon carbide nanoparticles (SiCNP/GC), have been used for electrocatalytic oxidation of purine (guanine and adenine) and pyrimidine bases (thymine and cytosine) nucleotides. Field emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM) techniques were used to examine the structure of the SiCNP/GC modified electrode. The modified electrode shows excellent electrocatalytic activity toward guanine, adenine, thymine and cytosine. Differential pulse voltammetry (DPV) was proposed for simultaneous determination of four DNA bases. The effects of different parameters such as the thickness of SiC layer, pulse amplitude, scan rate, supporting electrolyte composition and pH were optimized to obtain the best peak potential separation and higher sensitivity. Detection limit, sensitivity and linear concentration range of the modified electrode toward proposed analytes were calculated for, guanine, adenine, thymine and cytosine, respectively. As shown this sensor can be used for nanomolar or micromolar detection of different DNA bases simultaneously or individually. This sensor also exhibits good stability, reproducibility and long lifetime. Copyright © 2011 Elsevier B.V. All rights reserved.

A novel GMO biosensor for rapid ultrasensitive and simultaneous detection of multiple DNA components in GMO products.

PubMed

Huang, Lin; Zheng, Lei; Chen, Yinji; Xue, Feng; Cheng, Lin; Adeloju, Samuel B; Chen, Wei

2015-04-15

Since the introduction of genetically modified organisms (GMOs), there has been on-going and continuous concern and debates on the commercialization of products derived from GMOs. There is an urgent need for development of highly efficient analytical methods for rapid and high throughput screening of GMOs components, as required for appropriate labeling of GMO-derived foods, as well as for on-site inspection and import/export quarantine. In this study, we describe, for the first time, a multi-labeling based electrochemical biosensor for simultaneous detection of multiple DNA components of GMO products on the same sensing interface. Two-round signal amplification was applied by using both an exonuclease enzyme catalytic reaction and gold nanoparticle-based bio-barcode related strategies, respectively. Simultaneous multiple detections of different DNA components of GMOs were successfully achieved with satisfied sensitivity using this electrochemical biosensor. Furthermore, the robustness and effectiveness of the proposed approach was successfully demonstrated by application to various GMO products, including locally obtained and confirmed commercial GMO seeds and transgenetic plants. The proposed electrochemical biosensor demonstrated unique merits that promise to gain more interest in its use for rapid and on-site simultaneous multiple screening of different components of GMO products. Copyright © 2014 Elsevier B.V. All rights reserved.

A technique for simultaneous detection of individual vortex states of Laguerre-Gaussian beams transmitted through an aqueous suspension of microparticles

NASA Astrophysics Data System (ADS)

Khonina, S. N.; Karpeev, S. V.; Paranin, V. D.

2018-06-01

A technique for simultaneous detection of individual vortex states of the beams propagating in a randomly inhomogeneous medium is proposed. The developed optical system relies on the correlation method that is invariant to the beam wandering. The intensity distribution formed at the optical system output does not require digital processing. The proposed technique based on a multi-order phase diffractive optical element (DOE) is studied numerically and experimentally. The developed detection technique is used for the analysis of Laguerre-Gaussian vortex beams propagating under conditions of intense absorption, reflection, and scattering in transparent and opaque microparticles in aqueous suspensions. The performed experimental studies confirm the relevance of the vortex phase dependence of a laser beam under conditions of significant absorption, reflection, and scattering of the light.

3D-shape of objects with straight line-motion by simultaneous projection of color coded patterns

NASA Astrophysics Data System (ADS)

Flores, Jorge L.; Ayubi, Gaston A.; Di Martino, J. Matías; Castillo, Oscar E.; Ferrari, Jose A.

2018-05-01

In this work, we propose a novel technique to retrieve the 3D shape of dynamic objects by the simultaneous projection of a fringe pattern and a homogeneous light pattern which are both coded in two of the color channels of a RGB image. The fringe pattern, red channel, is used to retrieve the phase by phase-shift algorithms with arbitrary phase-step, while the homogeneous pattern, blue channel, is used to match pixels from the test object in consecutive images, which are acquired at different positions, and thus, to determine the speed of the object. The proposed method successfully overcomes the standard requirement of projecting fringes of two different frequencies; one frequency to extract object information and the other one to retrieve the phase. Validation experiments are presented.

Interface and permittivity simultaneous reconstruction in electrical capacitance tomography based on boundary and finite-elements coupling method

PubMed Central

Ren, Shangjie; Dong, Feng

2016-01-01

Electrical capacitance tomography (ECT) is a non-destructive detection technique for imaging the permittivity distributions inside an observed domain from the capacitances measurements on its boundary. Owing to its advantages of non-contact, non-radiation, high speed and low cost, ECT is promising in the measurements of many industrial or biological processes. However, in the practical industrial or biological systems, a deposit is normally seen in the inner wall of its pipe or vessel. As the actual region of interest (ROI) of ECT is surrounded by the deposit layer, the capacitance measurements become weakly sensitive to the permittivity perturbation occurring at the ROI. When there is a major permittivity difference between the deposit and the ROI, this kind of shielding effect is significant, and the permittivity reconstruction becomes challenging. To deal with the issue, an interface and permittivity simultaneous reconstruction approach is proposed. Both the permittivity at the ROI and the geometry of the deposit layer are recovered using the block coordinate descent method. The boundary and finite-elements coupling method is employed to improve the computational efficiency. The performance of the proposed method is evaluated with the simulation tests. This article is part of the themed issue ‘Supersensing through industrial process tomography’. PMID:27185960

Non-null annular subaperture stitching interferometry for aspheric test

NASA Astrophysics Data System (ADS)

Zhang, Lei; Liu, Dong; Shi, Tu; Yang, Yongying; Chong, Shiyao; Miao, Liang; Huang, Wei; Shen, Yibing; Bai, Jian

2015-10-01

A non-null annular subaperture stitching interferometry (NASSI), combining the subaperture stitching idea and non-null test method, is proposed for steep aspheric testing. Compared with standard annular subaperture stitching interferometry (ASSI), a partial null lens (PNL) is employed as an alternative to the transmission sphere, to generate different aspherical wavefronts as the references. The coverage subaperture number would thus be reduced greatly for the better performance of aspherical wavefronts in matching the local slope of aspheric surfaces. Instead of various mathematical stitching algorithms, a simultaneous reverse optimizing reconstruction (SROR) method based on system modeling and ray tracing is proposed for full aperture figure error reconstruction. All the subaperture measurements are simulated simultaneously with a multi-configuration model in a ray-tracing program, including the interferometric system modeling and subaperture misalignments modeling. With the multi-configuration model, full aperture figure error would be extracted in form of Zernike polynomials from subapertures wavefront data by the SROR method. This method concurrently accomplishes subaperture retrace error and misalignment correction, requiring neither complex mathematical algorithms nor subaperture overlaps. A numerical simulation exhibits the comparison of the performance of the NASSI and standard ASSI, which demonstrates the high accuracy of the NASSI in testing steep aspheric. Experimental results of NASSI are shown to be in good agreement with that of Zygo® VerifireTM Asphere interferometer.

Simultaneous Detection and Tracking of Pedestrian from Panoramic Laser Scanning Data

NASA Astrophysics Data System (ADS)

Xiao, Wen; Vallet, Bruno; Schindler, Konrad; Paparoditis, Nicolas

2016-06-01

Pedestrian traffic flow estimation is essential for public place design and construction planning. Traditional data collection by human investigation is tedious, inefficient and expensive. Panoramic laser scanners, e.g. Velodyne HDL-64E, which scan surroundings repetitively at a high frequency, have been increasingly used for 3D object tracking. In this paper, a simultaneous detection and tracking (SDAT) method is proposed for precise and automatic pedestrian trajectory recovery. First, the dynamic environment is detected using two different methods, Nearest-point and Max-distance. Then, all the points on moving objects are transferred into a space-time (x, y, t) coordinate system. The pedestrian detection and tracking amounts to assign the points belonging to pedestrians into continuous trajectories in space-time. We formulate the point assignment task as an energy function which incorporates the point evidence, trajectory number, pedestrian shape and motion. A low energy trajectory will well explain the point observations, and have plausible trajectory trend and length. The method inherently filters out points from other moving objects and false detections. The energy function is solved by a two-step optimization process: tracklet detection in a short temporal window; and global tracklet association through the whole time span. Results demonstrate that the proposed method can automatically recover the pedestrians trajectories with accurate positions and low false detections and mismatches.

Spectrophotometric methods for simultaneous determination of betamethasone valerate and fusidic acid in their binary mixture.

PubMed

Lotfy, Hayam Mahmoud; Salem, Hesham; Abdelkawy, Mohammad; Samir, Ahmed

2015-04-05

Five spectrophotometric methods were successfully developed and validated for the determination of betamethasone valerate and fusidic acid in their binary mixture. Those methods are isoabsorptive point method combined with the first derivative (ISO Point--D1) and the recently developed and well established methods namely ratio difference (RD) and constant center coupled with spectrum subtraction (CC) methods, in addition to derivative ratio (1DD) and mean centering of ratio spectra (MCR). New enrichment technique called spectrum addition technique was used instead of traditional spiking technique. The proposed spectrophotometric procedures do not require any separation steps. Accuracy, precision and linearity ranges of the proposed methods were determined and the specificity was assessed by analyzing synthetic mixtures of both drugs. They were applied to their pharmaceutical formulation and the results obtained were statistically compared to that of official methods. The statistical comparison showed that there is no significant difference between the proposed methods and the official ones regarding both accuracy and precision. Copyright © 2015 Elsevier B.V. All rights reserved.

Idler-efficiency-enhanced long-wave infrared beam generation using aperiodic orientation-patterned GaAs gratings.

PubMed

Gürkan Figen, Ziya; Aytür, Orhan; Arıkan, Orhan

2016-03-20

In this paper, we design aperiodic gratings based on orientation-patterned gallium arsenide (OP-GaAs) for converting 2.1 μm pump laser radiation into long-wave infrared (8-12 μm) in an idler-efficiency-enhanced scheme. These single OP-GaAs gratings placed in an optical parametric oscillator (OPO) or an optical parametric generator (OPG) can simultaneously phase match two optical parametric amplification (OPA) processes, OPA 1 and OPA 2. We use two design methods that allow simultaneous phase matching of two arbitrary χ⁽²⁾ processes and also free adjustment of their relative strength. The first aperiodic grating design method (Method 1) relies on generating a grating structure that has domain walls located at the zeros of the summation of two cosine functions, each of which has a spatial frequency that equals one of the phase-mismatch terms of the two processes. Some of the domain walls are discarded considering the minimum domain length that is achievable in the production process. In this paper, we propose a second design method (Method 2) that relies on discretizing the crystal length with sample lengths that are much smaller than the minimum domain length and testing each sample's contribution in such a way that the sign of the nonlinearity maximizes the magnitude sum of the real and imaginary parts of the Fourier transform of the grating function at the relevant phase mismatches. Method 2 produces a similar performance as Method 1 in terms of the maximization of the height of either Fourier peak located at the relevant phase mismatch while allowing an adjustable relative height for the two peaks. To our knowledge, this is the first time that aperiodic OP-GaAs gratings have been proposed for efficient long-wave infrared beam generation based on simultaneous phase matching.

Simultaneous CT-MRI Reconstruction for Constrained Imaging Geometries using Structural Coupling and Compressive Sensing

PubMed Central

Xi, Yan; Zhao, Jun; Bennett, James R.; Stacy, Mitchel R.; Sinusas, Albert J.; Wang, Ge

2016-01-01

Objective A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. Significance Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. Methods In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and hence would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. Results Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset based experiments, and has yielded promising results. PMID:26672028

Simultaneous measurement of refractive index and temperature based on intensity demodulation using matching grating method.

PubMed

Qi, Liang; Zhao, Chun-Liu; Kang, Juan; Jin, Yongxing; Wang, Jianfeng; Ye, Manping; Jin, Shangzhong

2013-07-01

A solution refractive index (SRI) and temperature simultaneous measurement sensor with intensity-demodulation system based on matching grating method were demonstrated. Long period grating written in a photonic crystal fiber (LPG-PCF), provides temperature stable and wavelength dependent optical intensity transmission. The reflective peaks of two fiber Bragg gratings (FBGs), one of which is etched then sensitive to both SRI and temperature, another (FBG2) is only sensitive to temperature, were located in the same linear range of the LPG-PCF's transmission spectrum. An identical FBG with FBG2 was chosen as a matching FBG. When environments (SRI and temperature) change, the wavelength shifts of the FBGs are translated effectively to the reflection intensity changes. By monitoring output lights of unmatching and matching paths, the SRI and temperature were deduced by a signal processing unit. Experimental results show that the simultaneous refractive index and temperature measurement system work well. The proposed sensor system is compact and suitable for in situ applications at lower cost.

Scale-Free Brain-Wave Music from Simultaneously EEG and fMRI Recordings

PubMed Central

Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong

2012-01-01

In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain. PMID:23166768

Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models

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

Kravitz, Ben; MacMartin, Douglas G.; Rasch, Philip J.

We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state. We use this technique to determine the steady-state responses of low cloud fraction and latent heat flux to heating perturbations over 22 regions spanning Earth's oceans. We show that the response characteristics are similar to thosemore » of step-change simulations, but in this new method the responses for 22 regions can be characterized simultaneously. Moreover, we can estimate the timescale over which the steady-state response emerges. The proposed methodology could be useful for a wide variety of purposes in climate science, including characterization of teleconnections and uncertainty quantification to identify the effects of climate model tuning parameters.« less

Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models

DOE PAGES

Kravitz, Ben; MacMartin, Douglas G.; Rasch, Philip J.; ...

2017-02-17

We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state. We use this technique to determine the steady-state responses of low cloud fraction and latent heat flux to heating perturbations over 22 regions spanning Earth's oceans. We show that the response characteristics are similar to thosemore » of step-change simulations, but in this new method the responses for 22 regions can be characterized simultaneously. Moreover, we can estimate the timescale over which the steady-state response emerges. The proposed methodology could be useful for a wide variety of purposes in climate science, including characterization of teleconnections and uncertainty quantification to identify the effects of climate model tuning parameters.« less

Feature Grouping and Selection Over an Undirected Graph.

PubMed

Yang, Sen; Yuan, Lei; Lai, Ying-Cheng; Shen, Xiaotong; Wonka, Peter; Ye, Jieping

2012-01-01

High-dimensional regression/classification continues to be an important and challenging problem, especially when features are highly correlated. Feature selection, combined with additional structure information on the features has been considered to be promising in promoting regression/classification performance. Graph-guided fused lasso (GFlasso) has recently been proposed to facilitate feature selection and graph structure exploitation, when features exhibit certain graph structures. However, the formulation in GFlasso relies on pairwise sample correlations to perform feature grouping, which could introduce additional estimation bias. In this paper, we propose three new feature grouping and selection methods to resolve this issue. The first method employs a convex function to penalize the pairwise l ∞ norm of connected regression/classification coefficients, achieving simultaneous feature grouping and selection. The second method improves the first one by utilizing a non-convex function to reduce the estimation bias. The third one is the extension of the second method using a truncated l 1 regularization to further reduce the estimation bias. The proposed methods combine feature grouping and feature selection to enhance estimation accuracy. We employ the alternating direction method of multipliers (ADMM) and difference of convex functions (DC) programming to solve the proposed formulations. Our experimental results on synthetic data and two real datasets demonstrate the effectiveness of the proposed methods.

Skew-t partially linear mixed-effects models for AIDS clinical studies.

PubMed

Lu, Tao

2016-01-01

We propose partially linear mixed-effects models with asymmetry and missingness to investigate the relationship between two biomarkers in clinical studies. The proposed models take into account irregular time effects commonly observed in clinical studies under a semiparametric model framework. In addition, commonly assumed symmetric distributions for model errors are substituted by asymmetric distribution to account for skewness. Further, informative missing data mechanism is accounted for. A Bayesian approach is developed to perform parameter estimation simultaneously. The proposed model and method are applied to an AIDS dataset and comparisons with alternative models are performed.

A Full Dynamic Compound Inverse Method for output-only element-level system identification and input estimation from earthquake response signals

NASA Astrophysics Data System (ADS)

Pioldi, Fabio; Rizzi, Egidio

2016-08-01

This paper proposes a new output-only element-level system identification and input estimation technique, towards the simultaneous identification of modal parameters, input excitation time history and structural features at the element-level by adopting earthquake-induced structural response signals. The method, named Full Dynamic Compound Inverse Method (FDCIM), releases strong assumptions of earlier element-level techniques, by working with a two-stage iterative algorithm. Jointly, a Statistical Average technique, a modification process and a parameter projection strategy are adopted at each stage to achieve stronger convergence for the identified estimates. The proposed method works in a deterministic way and is completely developed in State-Space form. Further, it does not require continuous- to discrete-time transformations and does not depend on initialization conditions. Synthetic earthquake-induced response signals from different shear-type buildings are generated to validate the implemented procedure, also with noise-corrupted cases. The achieved results provide a necessary condition to demonstrate the effectiveness of the proposed identification method.

Vertical transportation systems embedded on shuffled frog leaping algorithm for manufacturing optimisation problems in industries.

PubMed

Aungkulanon, Pasura; Luangpaiboon, Pongchanun

2016-01-01

Response surface methods via the first or second order models are important in manufacturing processes. This study, however, proposes different structured mechanisms of the vertical transportation systems or VTS embedded on a shuffled frog leaping-based approach. There are three VTS scenarios, a motion reaching a normal operating velocity, and both reaching and not reaching transitional motion. These variants were performed to simultaneously inspect multiple responses affected by machining parameters in multi-pass turning processes. The numerical results of two machining optimisation problems demonstrated the high performance measures of the proposed methods, when compared to other optimisation algorithms for an actual deep cut design.

Improving image-quality of interference fringes of out-of-plane vibration using temporal speckle pattern interferometry and standard deviation for piezoelectric plates.

PubMed

Chien-Ching Ma; Ching-Yuan Chang

2013-07-01

Interferometry provides a high degree of accuracy in the measurement of sub-micrometer deformations; however, the noise associated with experimental measurement undermines the integrity of interference fringes. This study proposes the use of standard deviation in the temporal domain to improve the image quality of patterns obtained from temporal speckle pattern interferometry. The proposed method combines the advantages of both mean and subtractive methods to remove background noise and ambient disturbance simultaneously, resulting in high-resolution images of excellent quality. The out-of-plane vibration of a thin piezoelectric plate is the main focus of this study, providing information useful to the development of energy harvesters. First, ten resonant states were measured using the proposed method, and both mode shape and resonant frequency were investigated. We then rebuilt the phase distribution of the first resonant mode based on the clear interference patterns obtained using the proposed method. This revealed instantaneous deformations in the dynamic characteristics of the resonant state. The proposed method also provides a frequency-sweeping function, facilitating its practical application in the precise measurement of resonant frequency. In addition, the mode shapes and resonant frequencies obtained using the proposed method were recorded and compared with results obtained using finite element method and laser Doppler vibrometery, which demonstrated close agreement.

Dual-Objective Item Selection Criteria in Cognitive Diagnostic Computerized Adaptive Testing

ERIC Educational Resources Information Center

Kang, Hyeon-Ah; Zhang, Susu; Chang, Hua-Hua

2017-01-01

The development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery…

High-Efficiency Visible Transmitting Polarizations Devices Based on the GaN Metasurface.

PubMed

Guo, Zhongyi; Xu, Haisheng; Guo, Kai; Shen, Fei; Zhou, Hongping; Zhou, Qingfeng; Gao, Jun; Yin, Zhiping

2018-05-15

Metasurfaces are capable of tailoring the amplitude, phase, and polarization of incident light to design various polarization devices. Here, we propose a metasurface based on the novel dielectric material gallium nitride (GaN) to realize high-efficiency modulation for both of the orthogonal linear polarizations simultaneously in the visible range. Both modulated transmitted phases of the orthogonal linear polarizations can almost span the whole 2π range by tailoring geometric sizes of the GaN nanobricks, while maintaining high values of transmission (almost all over 90%). At the wavelength of 530 nm, we designed and realized the beam splitter and the focusing lenses successfully. To further prove that our proposed method is suitable for arbitrary orthogonal linear polarization, we also designed a three-dimensional (3D) metalens that can simultaneously focus the X -, Y -, 45°, and 135° linear polarizations on spatially symmetric positions, which can be applied to the linear polarization measurement. Our work provides a possible method to achieve high-efficiency multifunctional optical devices in visible light by extending the modulating dimensions.

Nonlinear dynamic analysis of cantilevered piezoelectric energy harvesters under simultaneous parametric and external excitations

NASA Astrophysics Data System (ADS)

Fang, Fei; Xia, Guanghui; Wang, Jianguo

2018-02-01

The nonlinear dynamics of cantilevered piezoelectric beams is investigated under simultaneous parametric and external excitations. The beam is composed of a substrate and two piezoelectric layers and assumed as an Euler-Bernoulli model with inextensible deformation. A nonlinear distributed parameter model of cantilevered piezoelectric energy harvesters is proposed using the generalized Hamilton's principle. The proposed model includes geometric and inertia nonlinearity, but neglects the material nonlinearity. Using the Galerkin decomposition method and harmonic balance method, analytical expressions of the frequency-response curves are presented when the first bending mode of the beam plays a dominant role. Using these expressions, we investigate the effects of the damping, load resistance, electromechanical coupling, and excitation amplitude on the frequency-response curves. We also study the difference between the nonlinear lumped-parameter and distributed-parameter model for predicting the performance of the energy harvesting system. Only in the case of parametric excitation, we demonstrate that the energy harvesting system has an initiation excitation threshold below which no energy can be harvested. We also illustrate that the damping and load resistance affect the initiation excitation threshold.

Nonlinear dynamic analysis of cantilevered piezoelectric energy harvesters under simultaneous parametric and external excitations

NASA Astrophysics Data System (ADS)

Fang, Fei; Xia, Guanghui; Wang, Jianguo

2018-06-01

The nonlinear dynamics of cantilevered piezoelectric beams is investigated under simultaneous parametric and external excitations. The beam is composed of a substrate and two piezoelectric layers and assumed as an Euler-Bernoulli model with inextensible deformation. A nonlinear distributed parameter model of cantilevered piezoelectric energy harvesters is proposed using the generalized Hamilton's principle. The proposed model includes geometric and inertia nonlinearity, but neglects the material nonlinearity. Using the Galerkin decomposition method and harmonic balance method, analytical expressions of the frequency-response curves are presented when the first bending mode of the beam plays a dominant role. Using these expressions, we investigate the effects of the damping, load resistance, electromechanical coupling, and excitation amplitude on the frequency-response curves. We also study the difference between the nonlinear lumped-parameter and distributed-parameter model for predicting the performance of the energy harvesting system. Only in the case of parametric excitation, we demonstrate that the energy harvesting system has an initiation excitation threshold below which no energy can be harvested. We also illustrate that the damping and load resistance affect the initiation excitation threshold.

Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.

PubMed

Banerjee, Abhirup; Maji, Pradipta

2015-12-01

The segmentation of brain MR images into different tissue classes is an important task for automatic image analysis technique, particularly due to the presence of intensity inhomogeneity artifact in MR images. In this regard, this paper presents a novel approach for simultaneous segmentation and bias field correction in brain MR images. It integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution. The intensity distribution of a tissue class is represented by SN distribution, where each tissue class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of brain MR image is modeled as a mixture of finite number of SN distributions and one uniform distribution. The proposed method incorporates both the expectation-maximization and hidden Markov random field frameworks to provide an accurate and robust segmentation. The performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images for different bias fields and noise levels.

Multifractal detrended cross-correlation analysis for two nonstationary signals.

PubMed

Zhou, Wei-Xing

2008-06-01

We propose a method called multifractal detrended cross-correlation analysis to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on. The method is validated with cross-correlated one- and two-dimensional binomial measures and multifractal random walks. As an example, we illustrate the method by analyzing two financial time series.

The selective cleanup of complex matrices and simultaneous separation of benzo[a]pyrene by solid-phase extraction with MgO microspheres as sorbents.

PubMed

Jin, Jing; Li, Yun; Zhang, Zhiping; Su, Fan; Qi, Peipei; Lu, Xianbo; Chen, Jiping

2011-12-23

A new method for the selective cleanup of complex matrices and simultaneous separation of benzo[a]pyrene (BaP) was developed in this study. This method was based on solid-phase extraction (SPE) using magnesium oxide microspheres as sorbents, and it eliminated interferences from various impurities, such as lipids, sulphur, pigments, halobenzenes, polychlorodibenzo-p-dioxins and polychlorodibenzofurans. Several parameters, including the volume of rinsing and eluting solvents, the type of loading solvents and SPE sorbents, were optimized systematically. The capability for impurity removal was verified by gel permeation chromatography, gas chromatography, and liquid chromatography. Compared to commercial sorbents (silica gel, florisil and alumina), MgO microspheres exhibited excellent performance in the selective isolation of BaP and removal of impurities. The proposed method was applied to detect BaP in complex samples (sediments, soils, fish, and porcine liver). The limit of quantification (LOQ) was 1.04 ngL(-1), and the resulting regression coefficient (r(2)) was greater than 0.999 over a broad concentration range (9.5-7600 ngL(-1)). In contrast to traditional methods, the proposed method can give rise to higher recovery (85.1-100.8%) and better selectivity with simpler operation and less consumption of organic solvents (20-40 mL). Copyright © 2011 Elsevier B.V. All rights reserved.

Research of facial feature extraction based on MMC

NASA Astrophysics Data System (ADS)

Xue, Donglin; Zhao, Jiufen; Tang, Qinhong; Shi, Shaokun

2017-07-01

Based on the maximum margin criterion (MMC), a new algorithm of statistically uncorrelated optimal discriminant vectors and a new algorithm of orthogonal optimal discriminant vectors for feature extraction were proposed. The purpose of the maximum margin criterion is to maximize the inter-class scatter while simultaneously minimizing the intra-class scatter after the projection. Compared with original MMC method and principal component analysis (PCA) method, the proposed methods are better in terms of reducing or eliminating the statistically correlation between features and improving recognition rate. The experiment results on Olivetti Research Laboratory (ORL) face database shows that the new feature extraction method of statistically uncorrelated maximum margin criterion (SUMMC) are better in terms of recognition rate and stability. Besides, the relations between maximum margin criterion and Fisher criterion for feature extraction were revealed.

Encryption method based on pseudo random spatial light modulation for single-fibre data transmission

NASA Astrophysics Data System (ADS)

Kowalski, Marcin; Zyczkowski, Marek

2017-11-01

Optical cryptosystems can provide encryption and sometimes compression simultaneously. They are increasingly attractive for information securing especially for image encryption. Our studies shown that the optical cryptosystems can be used to encrypt optical data transmission. We propose and study a new method for securing fibre data communication. The paper presents a method for optical encryption of data transmitted with a single optical fibre. The encryption process relies on pseudo-random spatial light modulation, combination of two encryption keys and the Compressed Sensing framework. A linear combination of light pulses with pseudo-random patterns provides a required encryption performance. We propose an architecture to transmit the encrypted data through the optical fibre. The paper describes the method, presents the theoretical analysis, design of physical model and results of experiment.

The development of methods of analysis of documents on the basis of the methods of Raman spectroscopy and fluorescence analysis

NASA Astrophysics Data System (ADS)

Gorshkova, Kseniia O.; Tumkin, Ilya I.; Kirillova, Elizaveta O.; Panov, Maxim S.; Kochemirovsky, Vladimir A.

2017-05-01

The investigation of natural aging of writing inks printed on paper using Raman spectroscopy was performed. Based on the obtained dependencies of the Raman peak intensities ratios on the exposure time, the dye degradation model was proposed. It was suggested that there are several competing bond breaking and bond forming reactions corresponding to the characteristic vibration frequencies of the dye molecule that simultaneously occur during ink aging process. Also we propose a methodology based on the study of the optical properties of paper, particularly changes in the fluorescence of optical brighteners included in its composition as well as the paper reflectivity using spectrophotometric methods. These results can be implemented to develop the novel and promising method of criminology.

Optimal Couple Projections for Domain Adaptive Sparse Representation-based Classification.

PubMed

Zhang, Guoqing; Sun, Huaijiang; Porikli, Fatih; Liu, Yazhou; Sun, Quansen

2017-08-29

In recent years, sparse representation based classification (SRC) is one of the most successful methods and has been shown impressive performance in various classification tasks. However, when the training data has a different distribution than the testing data, the learned sparse representation may not be optimal, and the performance of SRC will be degraded significantly. To address this problem, in this paper, we propose an optimal couple projections for domain-adaptive sparse representation-based classification (OCPD-SRC) method, in which the discriminative features of data in the two domains are simultaneously learned with the dictionary that can succinctly represent the training and testing data in the projected space. OCPD-SRC is designed based on the decision rule of SRC, with the objective to learn coupled projection matrices and a common discriminative dictionary such that the between-class sparse reconstruction residuals of data from both domains are maximized, and the within-class sparse reconstruction residuals of data are minimized in the projected low-dimensional space. Thus, the resulting representations can well fit SRC and simultaneously have a better discriminant ability. In addition, our method can be easily extended to multiple domains and can be kernelized to deal with the nonlinear structure of data. The optimal solution for the proposed method can be efficiently obtained following the alternative optimization method. Extensive experimental results on a series of benchmark databases show that our method is better or comparable to many state-of-the-art methods.

Concurrent fNIRS-fMRI measurement to validate a method for separating deep and shallow fNIRS signals by using multidistance optodes

PubMed Central

Funane, Tsukasa; Sato, Hiroki; Yahata, Noriaki; Takizawa, Ryu; Nishimura, Yukika; Kinoshita, Akihide; Katura, Takusige; Atsumori, Hirokazu; Fukuda, Masato; Kasai, Kiyoto; Koizumi, Hideaki; Kiguchi, Masashi

2015-01-01

Abstract. It has been reported that a functional near-infrared spectroscopy (fNIRS) signal can be contaminated by extracerebral contributions. Many algorithms using multidistance separations to address this issue have been proposed, but their spatial separation performance has rarely been validated with simultaneous measurements of fNIRS and functional magnetic resonance imaging (fMRI). We previously proposed a method for discriminating between deep and shallow contributions in fNIRS signals, referred to as the multidistance independent component analysis (MD-ICA) method. In this study, to validate the MD-ICA method from the spatial aspect, multidistance fNIRS, fMRI, and laser-Doppler-flowmetry signals were simultaneously obtained for 12 healthy adult males during three tasks. The fNIRS signal was separated into deep and shallow signals by using the MD-ICA method, and the correlation between the waveforms of the separated fNIRS signals and the gray matter blood oxygenation level–dependent signals was analyzed. A three-way analysis of variance (signal depth×Hb kind×task) indicated that the main effect of fNIRS signal depth on the correlation is significant [F(1,1286)=5.34, p<0.05]. This result indicates that the MD-ICA method successfully separates fNIRS signals into spatially deep and shallow signals, and the accuracy and reliability of the fNIRS signal will be improved with the method. PMID:26157983

Robust generative asymmetric GMM for brain MR image segmentation.

PubMed

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM algorithm is proposed which can simply and efficiently incorporate spatial constraints into an EM framework to simultaneously segment brain MR images and estimate the intensity inhomogeneity. The proposed algorithm is flexible to fit the data shapes, and can simultaneously overcome the influence of noise and intensity inhomogeneity, and hence is capable of improving over 5% segmentation accuracy comparing with several state-of-the-art algorithms. Copyright © 2017 Elsevier B.V. All rights reserved.

Simultaneous Stripping Detection of Pb(II), Cd(II) and Zn(II) Using a Bimetallic Hg-Bi/Single-Walled Carbon Nanotubes Composite Electrode

PubMed Central

Ouyang, Ruizhuo; Zhu, Zhenqian; Tatum, Clarissa E.; Chambers, James Q.; Xue, Zi-Ling

2011-01-01

A new, sensitive platform for the simultaneous electrochemical assay of Zn(II), Cd(II) and Pb(II) in aqueous solution has been developed. The platform is based on a new bimetallic Hg-Bi/single-walled carbon nanotubes (SWNTs) composite modified glassy carbon electrode (GCE), demonstrating remarkably improved performance for the anodic stripping assay of Zn(II), Cd(II) and Pb(II). The synergistic effect of Hg and Bi as well as the enlarged, activated surface and good electrical conductivity of SWNTs on GCE contribute to the enhanced activity of the proposed electrode. The analytical curves for Zn(II), Cd(II) an Pb(II) cover two linear ranges varying from 0.5 to 11 μg L-1 and 10 to 130 μg L-1 with correlation coefficients higher than 0.992. The limits of detection for Zn(II), Cd(II) are lower than 2 μg L-1 (S/N = 3). For Pb(II), moreover, there is another lower, linear range from 5 to 1100 ng L-1 with a coefficient of 0.987 and a detection limit of 0.12 ng L-1. By using the standard addition method, Zn(II), Cd(II) and Pb(II) ions in river samples were successfully determined. These results suggest that the proposed method can be applied as a simple, efficient alternative for the simultaneous monitoring of heavy metals in water samples. In addition, this method demonstrates the powerful application of carbon nanotubes in electrochemical analysis of heavy metals. PMID:21660117

Comparative study on the selectivity of various spectrophotometric techniques for the determination of binary mixture of fenbendazole and rafoxanide.

PubMed

Saad, Ahmed S; Attia, Ali K; Alaraki, Manal S; Elzanfaly, Eman S

2015-11-05

Five different spectrophotometric methods were applied for simultaneous determination of fenbendazole and rafoxanide in their binary mixture; namely first derivative, derivative ratio, ratio difference, dual wavelength and H-point standard addition spectrophotometric methods. Different factors affecting each of the applied spectrophotometric methods were studied and the selectivity of the applied methods was compared. The applied methods were validated as per the ICH guidelines and good accuracy; specificity and precision were proven within the concentration range of 5-50 μg/mL for both drugs. Statistical analysis using one-way ANOVA proved no significant differences among the proposed methods for the determination of the two drugs. The proposed methods successfully determined both drugs in laboratory prepared and commercially available binary mixtures, and were found applicable for the routine analysis in quality control laboratories. Copyright © 2015 Elsevier B.V. All rights reserved.

Dual-channel near-field control by polarizations using isotropic and inhomogeneous metasurface.

PubMed

Wan, Xiang; Cai, Ben Geng; Li, Yun Bo; Cui, Tie Jun

2015-11-03

We propose a method for dual-channel near-field manipulations by designing isotropic but inhomogeneous metasurfaces. As example, we present a dual-channel near-field focusing metasurface device. When the device is driven by surface waves from different channels on the metasurface, the near fields will be focused at the same spatial point with different polarizations. Conversely, if a linearly polarized source is radiated at the spatial focal point, different channels will be evoked on the metasurface controlled by polarization. We fabricated and measured the metasurface device in the microwave frequency. Well agreements between the simulation and measurement results are observed. The proposed method exhibits great flexibility in controlling the surface waves and spatial waves simultaneously. It is expected that the proposed method and dual-channel device will facilitate the manipulation of near electromagnetic or optical waves in different frequency regimes.

X-ray luminescence computed tomography imaging via multiple intensity weighted narrow beam irradiation

NASA Astrophysics Data System (ADS)

Feng, Bo; Gao, Feng; Zhao, Huijuan; Zhang, Limin; Li, Jiao; Zhou, Zhongxing

2018-02-01

The purpose of this work is to introduce and study a novel x-ray beam irradiation pattern for X-ray Luminescence Computed Tomography (XLCT), termed multiple intensity-weighted narrow-beam irradiation. The proposed XLCT imaging method is studied through simulations of x-ray and diffuse lights propagation. The emitted optical photons from X-ray excitable nanophosphors were collected by optical fiber bundles from the right-side surface of the phantom. The implementation of image reconstruction is based on the simulated measurements from 6 or 12 angular projections in terms of 3 or 5 x-ray beams scanning mode. The proposed XLCT imaging method is compared against the constant intensity weighted narrow-beam XLCT. From the reconstructed XLCT images, we found that the Dice similarity and quantitative ratio of targets have a certain degree of improvement. The results demonstrated that the proposed method can offer simultaneously high image quality and fast image acquisition.

Feature-Based Correlation and Topological Similarity for Interbeat Interval Estimation Using Ultrawideband Radar.

PubMed

Sakamoto, Takuya; Imasaka, Ryohei; Taki, Hirofumi; Sato, Toru; Yoshioka, Mototaka; Inoue, Kenichi; Fukuda, Takeshi; Sakai, Hiroyuki

2016-04-01

The objectives of this paper are to propose a method that can accurately estimate the human heart rate (HR) using an ultrawideband (UWB) radar system, and to determine the performance of the proposed method through measurements. The proposed method uses the feature points of a radar signal to estimate the HR efficiently and accurately. Fourier- and periodicity-based methods are inappropriate for estimation of instantaneous HRs in real time because heartbeat waveforms are highly variable, even within the beat-to-beat interval. We define six radar waveform features that enable correlation processing to be performed quickly and accurately. In addition, we propose a feature topology signal that is generated from a feature sequence without using amplitude information. This feature topology signal is used to find unreliable feature points, and thus, to suppress inaccurate HR estimates. Measurements were taken using UWB radar, while simultaneously performing electrocardiography measurements in an experiment that was conducted on nine participants. The proposed method achieved an average root-mean-square error in the interbeat interval of 7.17 ms for the nine participants. The results demonstrate the effectiveness and accuracy of the proposed method. The significance of this study for biomedical research is that the proposed method will be useful in the realization of a remote vital signs monitoring system that enables accurate estimation of HR variability, which has been used in various clinical settings for the treatment of conditions such as diabetes and arterial hypertension.

Toward a Smartphone Application for Estimation of Pulse Transit Time

PubMed Central

Liu, He; Ivanov, Kamen; Wang, Yadong; Wang, Lei

2015-01-01

Pulse transit time (PTT) is an important physiological parameter that directly correlates with the elasticity and compliance of vascular walls and variations in blood pressure. This paper presents a PTT estimation method based on photoplethysmographic imaging (PPGi). The method utilizes two opposing cameras for simultaneous acquisition of PPGi waveform signals from the index fingertip and the forehead temple. An algorithm for the detection of maxima and minima in PPGi signals was developed, which includes technology for interpolation of the real positions of these points. We compared our PTT measurements with those obtained from the current methodological standards. Statistical results indicate that the PTT measured by our proposed method exhibits a good correlation with the established method. The proposed method is especially suitable for implementation in dual-camera-smartphones, which could facilitate PTT measurement among populations affected by cardiac complications. PMID:26516861

Multi-camera digital image correlation method with distributed fields of view

NASA Astrophysics Data System (ADS)

Malowany, Krzysztof; Malesa, Marcin; Kowaluk, Tomasz; Kujawinska, Malgorzata

2017-11-01

A multi-camera digital image correlation (DIC) method and system for measurements of large engineering objects with distributed, non-overlapping areas of interest are described. The data obtained with individual 3D DIC systems are stitched by an algorithm which utilizes the positions of fiducial markers determined simultaneously by Stereo-DIC units and laser tracker. The proposed calibration method enables reliable determination of transformations between local (3D DIC) and global coordinate systems. The applicability of the method was proven during in-situ measurements of a hall made of arch-shaped (18 m span) self-supporting metal-plates. The proposed method is highly recommended for 3D measurements of shape and displacements of large and complex engineering objects made from multiple directions and it provides the suitable accuracy of data for further advanced structural integrity analysis of such objects.

Toward a Smartphone Application for Estimation of Pulse Transit Time.

PubMed

Liu, He; Ivanov, Kamen; Wang, Yadong; Wang, Lei

2015-10-27

Pulse transit time (PTT) is an important physiological parameter that directly correlates with the elasticity and compliance of vascular walls and variations in blood pressure. This paper presents a PTT estimation method based on photoplethysmographic imaging (PPGi). The method utilizes two opposing cameras for simultaneous acquisition of PPGi waveform signals from the index fingertip and the forehead temple. An algorithm for the detection of maxima and minima in PPGi signals was developed, which includes technology for interpolation of the real positions of these points. We compared our PTT measurements with those obtained from the current methodological standards. Statistical results indicate that the PTT measured by our proposed method exhibits a good correlation with the established method. The proposed method is especially suitable for implementation in dual-camera-smartphones, which could facilitate PTT measurement among populations affected by cardiac complications.

An improved maximum power point tracking method for a photovoltaic system

NASA Astrophysics Data System (ADS)

Ouoba, David; Fakkar, Abderrahim; El Kouari, Youssef; Dkhichi, Fayrouz; Oukarfi, Benyounes

2016-06-01

In this paper, an improved auto-scaling variable step-size Maximum Power Point Tracking (MPPT) method for photovoltaic (PV) system was proposed. To achieve simultaneously a fast dynamic response and stable steady-state power, a first improvement was made on the step-size scaling function of the duty cycle that controls the converter. An algorithm was secondly proposed to address wrong decision that may be made at an abrupt change of the irradiation. The proposed auto-scaling variable step-size approach was compared to some various other approaches from the literature such as: classical fixed step-size, variable step-size and a recent auto-scaling variable step-size maximum power point tracking approaches. The simulation results obtained by MATLAB/SIMULINK were given and discussed for validation.

Extracting TSK-type Neuro-Fuzzy model using the Hunting search algorithm

NASA Astrophysics Data System (ADS)

Bouzaida, Sana; Sakly, Anis; M'Sahli, Faouzi

2014-01-01

This paper proposes a Takagi-Sugeno-Kang (TSK) type Neuro-Fuzzy model tuned by a novel metaheuristic optimization algorithm called Hunting Search (HuS). The HuS algorithm is derived based on a model of group hunting of animals such as lions, wolves, and dolphins when looking for a prey. In this study, the structure and parameters of the fuzzy model are encoded into a particle. Thus, the optimal structure and parameters are achieved simultaneously. The proposed method was demonstrated through modeling and control problems, and the results have been compared with other optimization techniques. The comparisons indicate that the proposed method represents a powerful search approach and an effective optimization technique as it can extract the accurate TSK fuzzy model with an appropriate number of rules.

Fast conjugate phase image reconstruction based on a Chebyshev approximation to correct for B0 field inhomogeneity and concomitant gradients

PubMed Central

Chen, Weitian; Sica, Christopher T.; Meyer, Craig H.

2008-01-01

Off-resonance effects can cause image blurring in spiral scanning and various forms of image degradation in other MRI methods. Off-resonance effects can be caused by both B0 inhomogeneity and concomitant gradient fields. Previously developed off-resonance correction methods focus on the correction of a single source of off-resonance. This work introduces a computationally efficient method of correcting for B0 inhomogeneity and concomitant gradients simultaneously. The method is a fast alternative to conjugate phase reconstruction, with the off-resonance phase term approximated by Chebyshev polynomials. The proposed algorithm is well suited for semiautomatic off-resonance correction, which works well even with an inaccurate or low-resolution field map. The proposed algorithm is demonstrated using phantom and in vivo data sets acquired by spiral scanning. Semiautomatic off-resonance correction alone is shown to provide a moderate amount of correction for concomitant gradient field effects, in addition to B0 imhomogeneity effects. However, better correction is provided by the proposed combined method. The best results were produced using the semiautomatic version of the proposed combined method. PMID:18956462

SNPs selection using support vector regression and genetic algorithms in GWAS

PubMed Central

2014-01-01

Introduction This paper proposes a new methodology to simultaneously select the most relevant SNPs markers for the characterization of any measurable phenotype described by a continuous variable using Support Vector Regression with Pearson Universal kernel as fitness function of a binary genetic algorithm. The proposed methodology is multi-attribute towards considering several markers simultaneously to explain the phenotype and is based jointly on statistical tools, machine learning and computational intelligence. Results The suggested method has shown potential in the simulated database 1, with additive effects only, and real database. In this simulated database, with a total of 1,000 markers, and 7 with major effect on the phenotype and the other 993 SNPs representing the noise, the method identified 21 markers. Of this total, 5 are relevant SNPs between the 7 but 16 are false positives. In real database, initially with 50,752 SNPs, we have reduced to 3,073 markers, increasing the accuracy of the model. In the simulated database 2, with additive effects and interactions (epistasis), the proposed method matched to the methodology most commonly used in GWAS. Conclusions The method suggested in this paper demonstrates the effectiveness in explaining the real phenotype (PTA for milk), because with the application of the wrapper based on genetic algorithm and Support Vector Regression with Pearson Universal, many redundant markers were eliminated, increasing the prediction and accuracy of the model on the real database without quality control filters. The PUK demonstrated that it can replicate the performance of linear and RBF kernels. PMID:25573332

Highly Sensitive and High-Throughput Method for the Analysis of Bisphenol Analogues and Their Halogenated Derivatives in Breast Milk.

PubMed

Niu, Yumin; Wang, Bin; Zhao, Yunfeng; Zhang, Jing; Shao, Bing

2017-12-06

The structural analogs of bisphenol A (BPA) and their halogenated derivatives (together termed BPs) have been found in the environment, food, and even the human body. Limited research showed that some of them exhibited toxicities that were similar to or even greater than that of BPA. Therefore, adverse health effects for BPs were expected for humans with low-dose exposure in early life. Breast milk is an excellent matrix and could reflect fetuses' and babies' exposure to contaminants. Some of the emerging BPs may present with trace or ultratrace levels in humans. However, existing analytical methods for breast milk cannot quantify these BPs simultaneously with high sensitivity using a small sampling weight, which is important for human biomonitoring studies. In this paper, a method based on Bond Elut Enhanced Matrix Removal-Lipid purification, pyridine-3-sulfonyl chloride derivatization, and liquid chromatography electrospray tandem mass spectrometry was developed. The method requires only a small quantity of sample (200 μL) and allowed for the simultaneous determination of 24 BPs in breast milk with ultrahigh sensitivity. The limits of quantitation of the proposed method were 0.001-0.200 μg L -1 , which were 1-6.7 times lower than the only study for the simultaneous analysis of bisphenol analogs in breast milk based on a 3 g sample weight. The mean recoveries ranged from 86.11% to 119.05% with relative standard deviation (RSD) ≤ 19.5% (n = 6). Matrix effects were within 20% with RSD < 10% for six different lots of samples. The proposed method was successfully applied to 20 breast milk samples. BPA, bisphenol F (BPF), bisphenol S (BPS), and bisphenol AF (BPAF) were detected. BPA was still the dominant BP, followed by BPF. This is the first report describing the occurrence of BPF and BPAF in breast milk.

Simultaneous Determination of Eight Hypotensive Drugs of Various Chemical Groups in Pharmaceutical Preparations by HPLC-DAD.

PubMed

Stolarczyk, Mariusz; Hubicka, Urszula; Żuromska-Witek, Barbara; Krzek, Jan

2015-01-01

A new sensitive, simple, rapid, and precise HPLC method with diode array detection has been developed for separation and simultaneous determination of hydrochlorothiazide, furosemide, torasemide, losartane, quinapril, valsartan, spironolactone, and canrenone in combined pharmaceutical dosage forms. The chromatographic analysis of the tested drugs was performed on an ACE C18, 100 Å, 250×4.6 mm, 5 μm particle size column with 0.0.05 M phosphate buffer (pH=3.00)-acetonitrile-methanol (30+20+50 v/v/v) mobile phase at a flow rate of 1.0 mL/min. The column was thermostatted at 25°C. UV detection was performed at 230 nm. Analysis time was 10 min. The elaborated method meets the acceptance criteria for specificity, linearity, sensitivity, accuracy, and precision. The proposed method was successfully applied for the determination of the studied drugs in the selected combined dosage forms.

Application of ion chromatography to the determination of water-soluble inorganic and organic ions in atmospheric aerosols.

PubMed

Yu, Xue-Chun; He, Ke-Bin; Ma, Yong-Liang; Yang, Fu-Mo; Duan, Feng-Kui; Zheng, Ai-Hua; Zhao, Cheng-Yi

2004-01-01

A simple, sensitive and convenient ion chromatography(IC) method was established for the simultaneous determination of twelve water-soluble inorganic anions(F- , Cl- , NO2(-), NO3(-), SO3(2-), SO4(2-) , PO4(3-)), and fifteen water-soluble organic ions(formate, acetate, MSA, oxalate, malonate, succinate, phthalates, etc.) in atmospheric aerosols. The linear concentrations ranged from 0.005 microg/m3 to 500 microg/m3 ( r = 0.999-0.9999). The relative standard deviation (RSD) were 0.43%-2.00% and the detection limits were from 2.7 ng/m3 to 88 ng/m3. The proposed method was successfully applied to the simultaneous determination of those inorganic ions and organic ions in PM2.5 of Beijing.

Evaluation of multiple muscle loads through multi-objective optimization with prediction of subjective satisfaction level: illustration by an application to handrail position for standing.

PubMed

Chihara, Takanori; Seo, Akihiko

2014-03-01

Proposed here is an evaluation of multiple muscle loads and a procedure for determining optimum solutions to ergonomic design problems. The simultaneous muscle load evaluation is formulated as a multi-objective optimization problem, and optimum solutions are obtained for each participant. In addition, one optimum solution for all participants, which is defined as the compromise solution, is also obtained. Moreover, the proposed method provides both objective and subjective information to support the decision making of designers. The proposed method was applied to the problem of designing the handrail position for the sit-to-stand movement. The height and distance of the handrails were the design variables, and surface electromyograms of four muscles were measured. The optimization results suggest that the proposed evaluation represents the impressions of participants more completely than an independent use of muscle loads. In addition, the compromise solution is determined, and the benefits of the proposed method are examined. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

PubMed

Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

2017-09-01

Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.

Orthogonal projection approach and continuous wavelet transform-feed forward neural networks for simultaneous spectrophotometric determination of some heavy metals in diet samples.

PubMed

Abbasi Tarighat, Maryam

2016-02-01

Simultaneous spectrophotometric determination of a mixture of overlapped complexes of Fe(3+), Mn(2+), Cu(2+), and Zn(2+) ions with 2-(3-hydroxy-1-phenyl-but-2-enylideneamino) pyridine-3-ol(HPEP) by orthogonal projection approach-feed forward neural network (OPA-FFNN) and continuous wavelet transform-feed forward neural network (CWT-FFNN) is discussed. Ionic complexes HPEP were formulated with varying reagent concentration, pH and time of color formation for completion of complexation reactions. It was found that, at 5.0 × 10(-4) mol L(-1) of HPEP, pH 9.5 and 10 min after mixing the complexation reactions were completed. The spectral data were analyzed using partial response plots, and identified non-linearity modeled using FFNN. Reducing the number of OPA-FFNN and CWT-FFNN inputs were simplified using dissimilarity pure spectra of OPA and selected wavelet coefficients. Once the pure dissimilarity plots ad optimal wavelet coefficients are selected, different ANN models were employed for the calculation of the final calibration models. The performance of these two approaches were tested with regard to root mean square errors of prediction (RMSE %) values, using synthetic solutions. Under the working conditions, the proposed methods were successfully applied to the simultaneous determination of metal ions in different vegetable and foodstuff samples. The results show that, OPA-FFNN and CWT-FFNN were effective in simultaneously determining Fe(3+), Mn(2+), Cu(2+), and Zn(2+) concentration. Also, concentrations of metal ions in the samples were determined by flame atomic absorption spectrometry (FAAS). The amounts of metal ions obtained by the proposed methods were in good agreement with those obtained by FAAS. Copyright © 2015 Elsevier Ltd. All rights reserved.

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

Accurate determination of electronic transport properties of silicon wafers by nonlinear photocarrier radiometry with multiple pump beam sizes

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

Wang, Qian; University of the Chinese Academy of Sciences, Beijing 100039; Li, Bincheng, E-mail: bcli@uestc.ac.cn

2015-12-07

In this paper, photocarrier radiometry (PCR) technique with multiple pump beam sizes is employed to determine simultaneously the electronic transport parameters (the carrier lifetime, the carrier diffusion coefficient, and the front surface recombination velocity) of silicon wafers. By employing the multiple pump beam sizes, the influence of instrumental frequency response on the multi-parameter estimation is totally eliminated. A nonlinear PCR model is developed to interpret the PCR signal. Theoretical simulations are performed to investigate the uncertainties of the estimated parameter values by investigating the dependence of a mean square variance on the corresponding transport parameters and compared to that obtainedmore » by the conventional frequency-scan method, in which only the frequency dependences of the PCR amplitude and phase are recorded at single pump beam size. Simulation results show that the proposed multiple-pump-beam-size method can improve significantly the accuracy of the determination of the electronic transport parameters. Comparative experiments with a p-type silicon wafer with resistivity 0.1–0.2 Ω·cm are performed, and the electronic transport properties are determined simultaneously. The estimated uncertainties of the carrier lifetime, diffusion coefficient, and front surface recombination velocity are approximately ±10.7%, ±8.6%, and ±35.4% by the proposed multiple-pump-beam-size method, which is much improved than ±15.9%, ±29.1%, and >±50% by the conventional frequency-scan method. The transport parameters determined by the proposed multiple-pump-beam-size PCR method are in good agreement with that obtained by a steady-state PCR imaging technique.« less

Composite marginal quantile regression analysis for longitudinal adolescent body mass index data.

PubMed

Yang, Chi-Chuan; Chen, Yi-Hau; Chang, Hsing-Yi

2017-09-20

Childhood and adolescenthood overweight or obesity, which may be quantified through the body mass index (BMI), is strongly associated with adult obesity and other health problems. Motivated by the child and adolescent behaviors in long-term evolution (CABLE) study, we are interested in individual, family, and school factors associated with marginal quantiles of longitudinal adolescent BMI values. We propose a new method for composite marginal quantile regression analysis for longitudinal outcome data, which performs marginal quantile regressions at multiple quantile levels simultaneously. The proposed method extends the quantile regression coefficient modeling method introduced by Frumento and Bottai (Biometrics 2016; 72:74-84) to longitudinal data accounting suitably for the correlation structure in longitudinal observations. A goodness-of-fit test for the proposed modeling is also developed. Simulation results show that the proposed method can be much more efficient than the analysis without taking correlation into account and the analysis performing separate quantile regressions at different quantile levels. The application to the longitudinal adolescent BMI data from the CABLE study demonstrates the practical utility of our proposal. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Simultaneous mapping of water shift and B1 (WASABI)-Application to field-Inhomogeneity correction of CEST MRI data.

PubMed

Schuenke, Patrick; Windschuh, Johannes; Roeloffs, Volkert; Ladd, Mark E; Bachert, Peter; Zaiss, Moritz

2017-02-01

Together with the development of MRI contrasts that are inherently small in their magnitude, increased magnetic field accuracy is also required. Hence, mapping of the static magnetic field (B 0 ) and the excitation field (B 1 ) is not only important to feedback shim algorithms, but also for postprocess contrast-correction procedures. A novel field-inhomogeneity mapping method is presented that allows simultaneous mapping of the water shift and B 1 (WASABI) using an off-resonant rectangular preparation pulse. The induced Rabi oscillations lead to a sinc-like spectrum in the frequency-offset dimension and allow for determination of B 0 by its symmetry axis and of B 1 by its oscillation frequency. Stability of the WASABI method with regard to the influences of T 1 , T 2 , magnetization transfer, and repetition time was investigated and its convergence interval was verified. B 0 and B 1 maps obtained simultaneously by means of WASABI in the human brain at 3 T and 7 T can compete well with maps obtained by standard methods. Finally, the method was applied successfully for B 0 and B 1 correction of chemical exchange saturation transfer MRI (CEST-MRI) data of the human brain. The proposed WASABI method yields a novel simultaneous B 0 and B 1 mapping within 1 min that is robust and easy to implement. Magn Reson Med 77:571-580, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Chemometrics-enhanced high performance liquid chromatography-diode array detection strategy for simultaneous determination of eight co-eluted compounds in ten kinds of Chinese teas using second-order calibration method based on alternating trilinear decomposition algorithm.

PubMed

Yin, Xiao-Li; Wu, Hai-Long; Gu, Hui-Wen; Zhang, Xiao-Hua; Sun, Yan-Mei; Hu, Yong; Liu, Lu; Rong, Qi-Ming; Yu, Ru-Qin

2014-10-17

In this work, an attractive chemometrics-enhanced high performance liquid chromatography-diode array detection (HPLC-DAD) strategy was proposed for simultaneous and fast determination of eight co-eluted compounds including gallic acid, caffeine and six catechins in ten kinds of Chinese teas by using second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm. This new strategy proved to be a useful tool for handling the co-eluted peaks, uncalibrated interferences and baseline drifts existing in the process of chromatographic separation, which benefited from the "second-order advantages", making the determination of gallic acid, caffeine and six catechins in tea infusions within 8 min under a simple mobile phase condition. The average recoveries of the analytes on two selected tea samples ranged from 91.7 to 103.1% with standard deviations (SD) ranged from 1.9 to 11.9%. Figures of merit including sensitivity (SEN), selectivity (SEL), root-mean-square error of prediction (RMSEP) and limit of detection (LOD) have been calculated to validate the accuracy of the proposed method. To further confirm the reliability of the method, a multiple reaction monitoring (MRM) method based on LC-MS/MS was employed for comparison and the obtained results of both methods were consistent with each other. Furthermore, as a universal strategy, this new proposed analytical method was applied for the determination of gallic acid, caffeine and catechins in several other kinds of Chinese teas, including different levels and varieties. Finally, based on the quantitative results, principal component analysis (PCA) was used to conduct a cluster analysis for these Chinese teas. The green tea, Oolong tea and Pu-erh raw tea samples were classified successfully. All results demonstrated that the proposed method is accurate, sensitive, fast, universal and ideal for the rapid, routine analysis and discrimination of gallic acid, caffeine and catechins in Chinese tea samples. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel phase retrieval method from three-wavelength in-line phase-shifting interferograms based on positive negative 2π phase shifts

NASA Astrophysics Data System (ADS)

Xu, Xiaoqing; Wang, Yawei; Ji, Ying; Xu, Yuanyuan; Xie, Ming

2018-01-01

A new method to extract quantitative phases for each wavelength from three-wavelength in-line phase-shifting interferograms is proposed. Firstly, seven interferograms with positive negative 2π phase shifts are sequentially captured by using the phase-shifting technique. Secondly, six dc-term suppressed intensities can be achieved by the use of the algebraic algorithm. Finally, the wrapped phases at the three wavelengths can be acquired simultaneously from these six interferograms add-subtracting by employing the trigonometric function method. The surface morphology with increased ambiguity-free range at synthetic beat wavelength can be obtained, while maintaining the low noise precision of the single wavelength measurement, by combining this method with three-wavelength phase unwrapping method. We illustrate the principle of this algorithm, and the simulated experiments of the spherical cap and the HeLa cell are conducted to prove our proposed method, respectively.

HPLC and chemometrics-assisted UV-spectroscopy methods for the simultaneous determination of ambroxol and doxycycline in capsule

NASA Astrophysics Data System (ADS)

Hadad, Ghada M.; El-Gindy, Alaa; Mahmoud, Waleed M. M.

2008-08-01

High-performance liquid chromatography (HPLC) and multivariate spectrophotometric methods are described for the simultaneous determination of ambroxol hydrochloride (AM) and doxycycline (DX) in combined pharmaceutical capsules. The chromatographic separation was achieved on reversed-phase C 18 analytical column with a mobile phase consisting of a mixture of 20 mM potassium dihydrogen phosphate, pH 6-acetonitrile in ratio of (1:1, v/v) and UV detection at 245 nm. Also, the resolution has been accomplished by using numerical spectrophotometric methods as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS-1) applied to the UV spectra of the mixture and graphical spectrophotometric method as first derivative of the ratio spectra ( 1DD) method. Analytical figures of merit (FOM), such as sensitivity, selectivity, analytical sensitivity, limit of quantitation and limit of detection were determined for CLS, PLS-1 and PCR methods. The proposed methods were validated and successfully applied for the analysis of pharmaceutical formulation and laboratory-prepared mixtures containing the two component combination.

HPLC and chemometrics-assisted UV-spectroscopy methods for the simultaneous determination of ambroxol and doxycycline in capsule.

PubMed

Hadad, Ghada M; El-Gindy, Alaa; Mahmoud, Waleed M M

2008-08-01

High-performance liquid chromatography (HPLC) and multivariate spectrophotometric methods are described for the simultaneous determination of ambroxol hydrochloride (AM) and doxycycline (DX) in combined pharmaceutical capsules. The chromatographic separation was achieved on reversed-phase C(18) analytical column with a mobile phase consisting of a mixture of 20mM potassium dihydrogen phosphate, pH 6-acetonitrile in ratio of (1:1, v/v) and UV detection at 245 nm. Also, the resolution has been accomplished by using numerical spectrophotometric methods as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS-1) applied to the UV spectra of the mixture and graphical spectrophotometric method as first derivative of the ratio spectra ((1)DD) method. Analytical figures of merit (FOM), such as sensitivity, selectivity, analytical sensitivity, limit of quantitation and limit of detection were determined for CLS, PLS-1 and PCR methods. The proposed methods were validated and successfully applied for the analysis of pharmaceutical formulation and laboratory-prepared mixtures containing the two component combination.

A simultaneous all-optical half/full-subtraction strategy using cascaded highly nonlinear fibers

NASA Astrophysics Data System (ADS)

Singh, Karamdeep; Kaur, Gurmeet; Singh, Maninder Lal

2018-02-01

Using non-linear effects such as cross-gain modulation (XGM) and cross-phase modulation (XPM) inside two highly non-linear fibres (HNLF) arranged in cascaded configuration, a simultaneous half/full-subtracter is proposed. The proposed simultaneous half/full-subtracter design is attractive due to several features such as input data pattern independence and usage of minimal number of non-linear elements i.e. HNLFs. Proof of concept simulations have been conducted at 100 Gbps rate, indicating fine performance, as extinction ratio (dB) > 6.28 dB and eye opening factors (EO) > 77.1072% are recorded for each implemented output. The proposed simultaneous half/full-subtracter can be used as a key component in all-optical information processing circuits.

Robust sleep quality quantification method for a personal handheld device.

PubMed

Shin, Hangsik; Choi, Byunghun; Kim, Doyoon; Cho, Jaegeol

2014-06-01

The purpose of this study was to develop and validate a novel method for sleep quality quantification using personal handheld devices. The proposed method used 3- or 6-axes signals, including acceleration and angular velocity, obtained from built-in sensors in a smartphone and applied a real-time wavelet denoising technique to minimize the nonstationary noise. Sleep or wake status was decided on each axis, and the totals were finally summed to calculate sleep efficiency (SE), regarded as sleep quality in general. The sleep experiment was carried out for performance evaluation of the proposed method, and 14 subjects participated. An experimental protocol was designed for comparative analysis. The activity during sleep was recorded not only by the proposed method but also by well-known commercial applications simultaneously; moreover, activity was recorded on different mattresses and locations to verify the reliability in practical use. Every calculated SE was compared with the SE of a clinically certified medical device, the Philips (Amsterdam, The Netherlands) Actiwatch. In these experiments, the proposed method proved its reliability in quantifying sleep quality. Compared with the Actiwatch, accuracy and average bias error of SE calculated by the proposed method were 96.50% and -1.91%, respectively. The proposed method was vastly superior to other comparative applications with at least 11.41% in average accuracy and at least 6.10% in average bias; average accuracy and average absolute bias error of comparative applications were 76.33% and 17.52%, respectively.

A Moving Mesh Finite Element Algorithm for Singular Problems in Two and Three Space Dimensions

NASA Astrophysics Data System (ADS)

Li, Ruo; Tang, Tao; Zhang, Pingwen

2002-04-01

A framework for adaptive meshes based on the Hamilton-Schoen-Yau theory was proposed by Dvinsky. In a recent work (2001, J. Comput. Phys.170, 562-588), we extended Dvinsky's method to provide an efficient moving mesh algorithm which compared favorably with the previously proposed schemes in terms of simplicity and reliability. In this work, we will further extend the moving mesh methods based on harmonic maps to deal with mesh adaptation in three space dimensions. In obtaining the variational mesh, we will solve an optimization problem with some appropriate constraints, which is in contrast to the traditional method of solving the Euler-Lagrange equation directly. The key idea of this approach is to update the interior and boundary grids simultaneously, rather than considering them separately. Application of the proposed moving mesh scheme is illustrated with some two- and three-dimensional problems with large solution gradients. The numerical experiments show that our methods can accurately resolve detail features of singular problems in 3D.

Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery.

PubMed

Liu, Han; Wang, Lie; Zhao, Tuo

2015-08-01

We propose a calibrated multivariate regression method named CMR for fitting high dimensional multivariate regression models. Compared with existing methods, CMR calibrates regularization for each regression task with respect to its noise level so that it simultaneously attains improved finite-sample performance and tuning insensitiveness. Theoretically, we provide sufficient conditions under which CMR achieves the optimal rate of convergence in parameter estimation. Computationally, we propose an efficient smoothed proximal gradient algorithm with a worst-case numerical rate of convergence O (1/ ϵ ), where ϵ is a pre-specified accuracy of the objective function value. We conduct thorough numerical simulations to illustrate that CMR consistently outperforms other high dimensional multivariate regression methods. We also apply CMR to solve a brain activity prediction problem and find that it is as competitive as a handcrafted model created by human experts. The R package camel implementing the proposed method is available on the Comprehensive R Archive Network http://cran.r-project.org/web/packages/camel/.

Single camera photogrammetry system for EEG electrode identification and localization.

PubMed

Baysal, Uğur; Sengül, Gökhan

2010-04-01

In this study, photogrammetric coordinate measurement and color-based identification of EEG electrode positions on the human head are simultaneously implemented. A rotating, 2MP digital camera about 20 cm above the subject's head is used and the images are acquired at predefined stop points separated azimuthally at equal angular displacements. In order to realize full automation, the electrodes have been labeled by colored circular markers and an electrode recognition algorithm has been developed. The proposed method has been tested by using a plastic head phantom carrying 25 electrode markers. Electrode locations have been determined while incorporating three different methods: (i) the proposed photogrammetric method, (ii) conventional 3D radiofrequency (RF) digitizer, and (iii) coordinate measurement machine having about 6.5 mum accuracy. It is found that the proposed system automatically identifies electrodes and localizes them with a maximum error of 0.77 mm. It is suggested that this method may be used in EEG source localization applications in the human brain.

Induced subgraph searching for geometric model fitting

NASA Astrophysics Data System (ADS)

Xiao, Fan; Xiao, Guobao; Yan, Yan; Wang, Xing; Wang, Hanzi

2017-11-01

In this paper, we propose a novel model fitting method based on graphs to fit and segment multiple-structure data. In the graph constructed on data, each model instance is represented as an induced subgraph. Following the idea of pursuing the maximum consensus, the multiple geometric model fitting problem is formulated as searching for a set of induced subgraphs including the maximum union set of vertices. After the generation and refinement of the induced subgraphs that represent the model hypotheses, the searching process is conducted on the "qualified" subgraphs. Multiple model instances can be simultaneously estimated by solving a converted problem. Then, we introduce the energy evaluation function to determine the number of model instances in data. The proposed method is able to effectively estimate the number and the parameters of model instances in data severely corrupted by outliers and noises. Experimental results on synthetic data and real images validate the favorable performance of the proposed method compared with several state-of-the-art fitting methods.

Simultaneous determination of arsenic and mercury species in rice by ion-pairing reversed phase chromatography with inductively coupled plasma mass spectrometry.

PubMed

Fang, Yong; Pan, Yushi; Li, Peng; Xue, Mei; Pei, Fei; Yang, Wenjian; Ma, Ning; Hu, Qiuhui

2016-12-15

An analytical method using reversed phase chromatography-inductively coupled plasma mass spectrometry for arsenic and mercury speciation analysis was described. The effect of ion-pairing reagent on simultaneous separation of four arsenic (arsenite, arsenate, monomethlyarsonate and dimethylarsinate) and three mercury species (inorganic mercury (Hg(II)), methylmecury and ethylmercury) was investigated. Parameters including concentrations and pH of the mobile phase were optimized. The separation and re-equilibration time was attained within 20min. Meanwhile, a sequential extraction method for arsenic and mercury in rice was tested. Subsequently, 1% HNO3 microwave-assisted extraction was chosen. Calibration curves based on peak area measurements were linear with correlation coefficient greater than 0.9958 for each species in the range studied. The detection limits of the species were in the range of 0.84-2.41μg/L for arsenic and 0.01-0.04μg/L for mercury, respectively. The proposed method was then successfully applied for the simultaneous determination of arsenic and mercury species in rice flour standard material and two kinds of rice from local markets. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quality evaluation of Evodia rutaecarpa (Juss.) Benth by high performance liquid chromatography with photodiode-array detection.

PubMed

Zhao, Yang; Li, Zhangwan; Zhou, Xin; Cai, Zongwei; Gong, Xiaojian; Zhou, Chanyuan

2008-12-01

A simple, sensitive and accurate HPLC-DAD method was developed for simultaneous determination of wuchuyuamide-I, quercetin, limonin, evodiamine and rutaecarpine in Evodia rutaecarpa that has been widely used as one of the traditional Chinese medicines (TCMs). Chromatographic separations were performed on a reverse-phase C(18) column with the gradient elution of acetonitrile-water and the simultaneous detection at five wavelengths. Good linear behaviors over the investigated concentration ranges were observed with the values of r higher than 0.999 for all the analytes. The recoveries measured at three levels varied from 98.77 to 102.36%. The validated method was successfully applied for the simultaneous determination of the five chemical constituents in 36 batches of samples collected from different regions or time that were investigated and authenticated as E. rutaecarpa (Juss.) Benth. Hierarchical clustering analysis (HCA) and principal components analysis (PCA) were performed to differentiate and classify the samples based on the contents of the five characteristic constituents. The total contents of evodiamine and rutaecarpine in different samples were calculated and the blending method proposed was demonstrated to be very useful in saving resources and in guiding rational herb use.

Making the Most of What We Have: A Practical Application of Multidimensional Item Response Theory in Test Scoring

ERIC Educational Resources Information Center

de la Torre, Jimmy; Patz, Richard J.

2005-01-01

This article proposes a practical method that capitalizes on the availability of information from multiple tests measuring correlated abilities given in a single test administration. By simultaneously estimating different abilities with the use of a hierarchical Bayesian framework, more precise estimates for each ability dimension are obtained.…

Stability-Indicating TLC-Densitometric and HPLC Methods for the Simultaneous Determination of Piracetam and Vincamine in the Presence of Their Degradation Products.

PubMed

Ahmed, Amal B; Abdelrahman, Maha M; Abdelwahab, Nada S; Salama, Fathy M

2016-11-01

Newly established TLC-densitometric and RP-HPLC methods were developed and validated for the simultaneous determination of Piracetam (PIR) and Vincamine (VINC) in their pharmaceutical formulation and in the presence of PIR and VINC degradation products, PD and VD, respectively. The proposed TLC-densitometric method is based on the separation and quantitation of the studied components using a developing system that consists of chloroform-methanol-glacial acetic acid-triethylamine (8 + 2 + 0.1 + 0.1, v/v/v/v) on TLC silica gel 60 F254 plates, followed by densitometric scanning at 230 nm. On the other hand, the developed RP-HPLC method is based on the separation of the studied components using an isocratic elution of 0.05 M KH2PO4 (containing 0.1% triethylamine adjusted to pH 3 with orthophosphoric acid)-methanol (95 + 5, v/v) on a C8 column at a flow rate of 1 mL/min with diode-array detection at 230 nm. The developed methods were validated according to International Conference on Harmonization guidelines and demonstrated good accuracy and precision. Moreover, the developed TLC-densitometric and RP-HPLC methods are suitable as stability-indicating assay methods for the simultaneous determination of PD and VD either in bulk powder or pharmaceutical formulation. The results were statistically compared with those obtained by the reported RP-HPLC method using t- and F-tests.

A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles

PubMed Central

Xu, Jun; Wang, Jing; Li, Shiying; Cao, Binggang

2016-01-01

Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the current sensor fails, the SOE estimation may be confronted with large error. Therefore, this paper attempts to make the following contributions: Current sensor fault detection and SOE estimation method is realized simultaneously. Through using the proportional integral observer (PIO) based method, the current sensor fault could be accurately estimated. By taking advantage of the accurate estimated current sensor fault, the influence caused by the current sensor fault can be eliminated and compensated. As a result, the results of the SOE estimation will be influenced little by the fault. In addition, the simulation and experimental workbench is established to verify the proposed method. The results indicate that the current sensor fault can be estimated accurately. Simultaneously, the SOE can also be estimated accurately and the estimation error is influenced little by the fault. The maximum SOE estimation error is less than 2%, even though the large current error caused by the current sensor fault still exists. PMID:27548183

A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles.

PubMed

Xu, Jun; Wang, Jing; Li, Shiying; Cao, Binggang

2016-08-19

Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the current sensor fails, the SOE estimation may be confronted with large error. Therefore, this paper attempts to make the following contributions: Current sensor fault detection and SOE estimation method is realized simultaneously. Through using the proportional integral observer (PIO) based method, the current sensor fault could be accurately estimated. By taking advantage of the accurate estimated current sensor fault, the influence caused by the current sensor fault can be eliminated and compensated. As a result, the results of the SOE estimation will be influenced little by the fault. In addition, the simulation and experimental workbench is established to verify the proposed method. The results indicate that the current sensor fault can be estimated accurately. Simultaneously, the SOE can also be estimated accurately and the estimation error is influenced little by the fault. The maximum SOE estimation error is less than 2%, even though the large current error caused by the current sensor fault still exists.

Music-Based Magnetic Resonance Fingerprinting to Improve Patient Comfort During MRI Exams

PubMed Central

Ma, Dan; Pierre, Eric Y.; Jiang, Yun; Schluchter, Mark D.; Setsompop, Kawin; Gulani, Vikas; Griswold, Mark A.

2015-01-01

Purpose The unpleasant acoustic noise is an important drawback of almost every magnetic resonance imaging scan. Instead of reducing the acoustic noise to improve patient comfort, a method is proposed to mitigate the noise problem by producing musical sounds directly from the switching magnetic fields while simultaneously quantifying multiple important tissue properties. Theory and Methods MP3 music files were converted to arbitrary encoding gradients, which were then used with varying flip angles and TRs in both 2D and 3D MRF exam. This new acquisition method named MRF-Music was used to quantify T1, T2 and proton density maps simultaneously while providing pleasing sounds to the patients. Results The MRF-Music scans were shown to significantly improve the patients' comfort during the MRI scans. The T1 and T2 values measured from phantom are in good agreement with those from the standard spin echo measurements. T1 and T2 values from the brain scan are also close to previously reported values. Conclusions MRF-Music sequence provides significant improvement of the patient's comfort as compared to the MRF scan and other fast imaging techniques such as EPI and TSE scans. It is also a fast and accurate quantitative method that quantifies multiple relaxation parameter simultaneously. PMID:26178439

Simultaneous in-plane and out-of-plane displacement measurement based on a dual-camera imaging system and its application to inspection of large-scale space structures

NASA Astrophysics Data System (ADS)

Ri, Shien; Tsuda, Hiroshi; Yoshida, Takeshi; Umebayashi, Takashi; Sato, Akiyoshi; Sato, Eiichi

2015-07-01

Optical methods providing full-field deformation data have potentially enormous interest for mechanical engineers. In this study, an in-plane and out-of-plane displacement measurement method based on a dual-camera imaging system is proposed. The in-plane and out-of-plane displacements are determined simultaneously using two measured in-plane displacement data observed from two digital cameras at different view angles. The fundamental measurement principle and experimental results of accuracy confirmation are presented. In addition, we applied this method to the displacement measurement in a static loading and bending test of a solid rocket motor case (CFRP material; 2.2 m diameter and 2.3 m long) for an up-to-date Epsilon rocket developed by JAXA. The effectiveness and measurement accuracy is confirmed by comparing with conventional displacement sensor. This method could be useful to diagnose the reliability of large-scale space structures in the rocket development.

Simultaneous spectrophotometric determination of trace amounts of uranium, thorium, and zirconium using the partial least squares method after their preconcentration by alpha-benzoin oxime modified Amberlite XAD-2000 resin.

PubMed

Ghasemi, Jahan B; Zolfonoun, E

2010-01-15

A new solid phase extraction method for separation and preconcentration of trace amounts of uranium, thorium, and zirconium in water samples is proposed. The procedure is based on the adsorption of U(VI), Th(IV) and Zr(IV) ions on a column of Amberlite XAD-2000 resin loaded with alpha-benzoin oxime prior to their simultaneous spectrophotometric determination with Arsenazo III using orthogonal signal correction partial least squares method. The enrichment factor for preconcentration of uranium, thorium, and zirconium was found to be 100. The detection limits for U(VI), Th(IV) and Zr(IV) were 0.50, 0.54, and 0.48microgL(-1), respectively. The precision of the method, evaluated as the relative standard deviation obtained by analyzing a series of 10 replicates, was below 4% for all elements. The practical applicability of the developed sorbent was examined using synthetic seawater, natural waters and ceramic samples.

Simultaneous Determination of Iron, Copper and Cobalt in Food Samples by CCD-diode Array Detection-Flow Injection Analysis with Partial Least Squares Calibration Model

NASA Astrophysics Data System (ADS)

Mi, Jiaping; Li, Yuanqian; Zhou, Xiaoli; Zheng, Bo; Zhou, Ying

2006-01-01

A flow injection-CCD diode array detection spectrophotometry with partial least squares (PLS) program for simultaneous determination of iron, copper and cobalt in food samples has been established. The method was based on the chromogenic reaction of the three metal ions and 2- (5-Bromo-2-pyridylazo)-5-diethylaminophenol, 5-Br-PADAP in acetic acid - sodium acetate buffer solution (pH5) with Triton X-100 and ascorbic acid. The overlapped spectra of the colored complexes were collected by charge-coupled device (CCD) - diode array detector and the multi-wavelength absorbance data was processed using partial least squares (PLS) algorithm. Optimum reaction conditions and parameters of flow injection analysis were investigated. The samples of tea, sesame, laver, millet, cornmeal, mung bean and soybean powder were determined by the proposed method. The average recoveries of spiked samples were 91.80%~100.9% for Iron, 92.50%~108.0% for Copper, 93.00%~110.5% for Cobalt, respectively with relative standard deviation (R.S.D) of 1.1%~12.1%. The sampling rate is 45 samples h-1. The determination results of the food samples were in good agreement between the proposed method and ICP-AES.

Green approach using monolithic column for simultaneous determination of coformulated drugs.

PubMed

Yehia, Ali M; Mohamed, Heba M

2016-06-01

Green chemistry and sustainability is now entirely encompassed across the majority of pharmaceutical companies and research labs. Researchers' attention is careworn toward implementing the green analytical chemistry principles for more eco-friendly analytical methodologies. Solvents play a dominant role in determining the greenness of the analytical procedure. Using safer solvents, the greenness profile of the methodology could be increased remarkably. In this context, a green chromatographic method has been developed and validated for the simultaneous determination of phenylephrine, paracetamol, and guaifenesin in their ternary pharmaceutical mixture. The chromatographic separation was carried out using monolithic column and green solvents as mobile phase. The use of monolithic column allows efficient separation protocols at higher flow rates, which results in short time of analysis. Two-factor three-level experimental design was used to optimize the chromatographic conditions. The greenness profile of the proposed methodology was assessed using eco-scale as a green metrics and was found to be an excellent green method with regard to the usage and production of hazardous chemicals and solvents, energy consumption, and amount of produced waste. The proposed method improved the environmental impact without compromising the analytical performance criteria and could be used as a safer alternate for the routine analysis of the studied drugs. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A current-excited triple-time-voltage oversampling method for bio-impedance model for cost-efficient circuit system.

PubMed

Yan Hong; Yong Wang; Wang Ling Goh; Yuan Gao; Lei Yao

2015-08-01

This paper presents a mathematic method and a cost-efficient circuit to measure the value of each component of the bio-impedance model at electrode-electrolyte interface. The proposed current excited triple-time-voltage oversampling (TTVO) method deduces the component values by solving triple simultaneous electric equation (TSEE) at different time nodes during a current excitation, which are the voltage functions of time. The proposed triple simultaneous electric equations (TSEEs) allows random selections of the time nodes, hence numerous solutions can be obtained during a single current excitation. Following that, the oversampling approach is engaged by averaging all solutions of multiple TSEEs acquired after a single current excitation, which increases the practical measurement accuracy through the improvement of the signal-to-noise ratio (SNR). In addition, a print circuit board (PCB) that consists a switched current exciter and an analog-to-digital converter (ADC) is designed for signal acquisition. This presents a great cost reduction when compared against other instrument-based measurement data reported [1]. Through testing, the measured values of this work is proven to be in superb agreements on the true component values of the electrode-electrolyte interface model. This work is most suited and also useful for biological and biomedical applications, to perform tasks such as stimulations, recordings, impedance characterizations, etc.

Microparticles controllable accumulation, arrangement, and spatial shaping performed by tapered-fiber-based laser-induced convection flow.

PubMed

Zhang, Yu; Lei, Jiaojie; Zhang, Yaxun; Liu, Zhihai; Zhang, Jianzhong; Yang, Xinghua; Yang, Jun; Yuan, Libo

2017-10-30

The ability to arrange cells and/or microparticles into the desired pattern is critical in biological, chemical, and metamaterial studies and other applications. Researchers have developed a variety of patterning techniques, which either have a limited capacity to simultaneously trap massive particles or lack the spatial resolution necessary to manipulate individual particle. Several approaches have been proposed that combine both high spatial selectivity and high throughput simultaneously. However, those methods are complex and difficult to fabricate. In this article, we propose and demonstrate a simple method that combines the laser-induced convection flow and fiber-based optical trapping methods to perform both regular and special spatial shaping arrangement. Essentially, we combine a light field with a large optical intensity gradient distribution and a thermal field with a large temperature gradient distribution to perform the microparticles shaping arrangement. The tapered-fiber-based laser-induced convection flow provides not only the batch manipulation of massive particles, but also the finer manipulation of special one or several particles, which break out the limit of single-fiber-based massive/individual particles photothermal manipulation. The combination technique allows for microparticles quick accumulation, single-layer and multilayer arrangement; special spatial shaping arrangement/adjustment, and microparticles sorting.

A Variational Approach to Simultaneous Image Segmentation and Bias Correction.

PubMed

Zhang, Kaihua; Liu, Qingshan; Song, Huihui; Li, Xuelong

2015-08-01

This paper presents a novel variational approach for simultaneous estimation of bias field and segmentation of images with intensity inhomogeneity. We model intensity of inhomogeneous objects to be Gaussian distributed with different means and variances, and then introduce a sliding window to map the original image intensity onto another domain, where the intensity distribution of each object is still Gaussian but can be better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying the bias field with a piecewise constant signal within the sliding window. A maximum likelihood energy functional is then defined on each local region, which combines the bias field, the membership function of the object region, and the constant approximating the true signal from its corresponding object. The energy functional is then extended to the whole image domain by the Bayesian learning approach. An efficient iterative algorithm is proposed for energy minimization, via which the image segmentation and bias field correction are simultaneously achieved. Furthermore, the smoothness of the obtained optimal bias field is ensured by the normalized convolutions without extra cost. Experiments on real images demonstrated the superiority of the proposed algorithm to other state-of-the-art representative methods.

A new electrochemical sensor for the simultaneous determination of acetaminophen and codeine based on porous silicon/palladium nanostructure.

PubMed

Ensafi, Ali A; Ahmadi, Najmeh; Rezaei, Behzad; Abarghoui, Mehdi Mokhtari

2015-03-01

A porous silicon/palladium nanostructure was prepared and used as a new electrode material for the simultaneous determination of acetaminophen (ACT) and codeine (COD). Palladium nanoparticles were assembled on porous silicon (PSi) microparticles by a simple redox reaction between the Pd precursor and PSi in an aqueous solution of hydrofluoric acid. This novel nanostructure was characterized by different spectroscopic and electrochemical techniques including scanning electron microscopy, X-ray diffraction, energy dispersive X-ray spectroscopy, fourier transform infrared spectroscopy and cyclic voltammetry. The high electrochemical activity, fast electron transfer rate, high surface area and good antifouling properties of this nanostructure enhanced the oxidation peak currents and reduced the peak potentials of ACT and COD at the surface of the proposed sensor. Simultaneous determination of ACT and COD was explored using differential pulse voltammetry. A linear range of 1.0-700.0 µmol L(-1) was achieved for ACT and COD with detection limits of 0.4 and 0.3 µmol L(-1), respectively. Finally, the proposed method was used for the determination of ACT and COD in blood serum, urine and pharmaceutical compounds. Copyright © 2014 Elsevier B.V. All rights reserved.

Hybrid microarray based on double biomolecular markers of DNA and carbohydrate for simultaneous genotypic and phenotypic detection of cholera toxin-producing Vibrio cholerae.

PubMed

Shin, Hwa Hui; Seo, Jeong Hyun; Kim, Chang Sup; Hwang, Byeong Hee; Cha, Hyung Joon

2016-05-15

Life-threatening diarrheal cholera is usually caused by water or food contaminated with cholera toxin-producing Vibrio cholerae. For the prevention and surveillance of cholera, it is crucial to rapidly and precisely detect and identify the etiological causes, such as V. cholerae and/or its toxin. In the present work, we propose the use of a hybrid double biomolecular marker (DBM) microarray containing 16S rRNA-based DNA capture probe to genotypically identify V. cholerae and GM1 pentasaccharide capture probe to phenotypically detect cholera toxin. We employed a simple sample preparation method to directly obtain genomic DNA and secreted cholera toxin as target materials from bacterial cells. By utilizing the constructed DBM microarray and prepared samples, V. cholerae and cholera toxin were detected successfully, selectively, and simultaneously; the DBM microarray was able to analyze the pathogenicity of the identified V. cholerae regardless of whether the bacteria produces toxin. Therefore, our proposed DBM microarray is a new effective platform for identifying bacteria and analyzing bacterial pathogenicity simultaneously. Copyright © 2015 Elsevier B.V. All rights reserved.

Efficient direct yaw moment control: tyre slip power loss minimisation for four-independent wheel drive vehicle

NASA Astrophysics Data System (ADS)

Kobayashi, Takao; Katsuyama, Etsuo; Sugiura, Hideki; Ono, Eiichi; Yamamoto, Masaki

2018-05-01

This paper proposes an efficient direct yaw moment control (DYC) capable of minimising tyre slip power loss on contact patches for a four-independent wheel drive vehicle. Simulations identified a significant power loss reduction with a direct yaw moment due to a change in steer characteristics during acceleration or deceleration while turning. Simultaneously, the vehicle motion can be stabilised. As a result, the proposed control method can ensure compatibility between vehicle dynamics performance and energy efficiency. This paper also describes the results of a full-vehicle simulation that was conducted to examine the effectiveness of the proposed DYC.

A Modified Artificial Bee Colony Algorithm Application for Economic Environmental Dispatch

NASA Astrophysics Data System (ADS)

Tarafdar Hagh, M.; Baghban Orandi, Omid

2018-03-01

In conventional fossil-fuel power systems, the economic environmental dispatch (EED) problem is a major problem that optimally determines the output power of generating units in a way that cost of total production and emission level be minimized simultaneously, and at the same time all the constraints of units and system are satisfied properly. To solve EED problem which is a non-convex optimization problem, a modified artificial bee colony (MABC) algorithm is proposed in this paper. This algorithm by implementing weighted sum method is applied on two test systems, and eventually, obtained results are compared with other reported results. Comparison of results confirms superiority and efficiency of proposed method clearly.

Simultaneous Determination of Clidinium Bromide and Chlordiazepoxide in Combined Dosage Forms by High-Performance Liquid Chromatography.

PubMed

Ashour, Safwan; Kattan, Nuha

2013-01-01

A sensitive and precise RP-HPLC method has been developed for the simultaneous estimation of clidinium bromide (CDB) and chlordiazepoxide (CDZ) in pure and pharmaceutical formulations. The separation was achieved on a Nucleodur C8 (250 × 4.6 mm i.d., 5 μm particle size) column at 25°C. CH3CN-MeOH-NH4OAc 0.1M (30 : 40 : 30, v/v/v) was used as the mobile phase at a flow rate of 1.0 mL min(-1) and detector wavelength at 218 nm. Almotriptan (ALT) was used as internal standard. The validation of the proposed method was carried out for linearity, accuracy, precision, LOD, LOQ, and robustness. The method showed good linearity in the ranges of 2.5-300.0 and 3.0-500.0 μg mL(-1) for CDB and CDZ, respectively. The percentage recovery obtained for CDB and CDZ was 100.40-103.38 and 99.98-105.59%, respectively. LOD and LOQ were 0.088 and 0.294 μg mL(-1) for CDB and 0.121 and 0.403 μg mL(-1) for CDZ, respectively. The proposed method was successfully applied to the determination of CDB and CDZ in combined dosage forms and the results tallied well with the label claim.

Stratospheric solar geoengineering without ozone loss.

PubMed

Keith, David W; Weisenstein, Debra K; Dykema, John A; Keutsch, Frank N

2016-12-27

Injecting sulfate aerosol into the stratosphere, the most frequently analyzed proposal for solar geoengineering, may reduce some climate risks, but it would also entail new risks, including ozone loss and heating of the lower tropical stratosphere, which, in turn, would increase water vapor concentration causing additional ozone loss and surface warming. We propose a method for stratospheric aerosol climate modification that uses a solid aerosol composed of alkaline metal salts that will convert hydrogen halides and nitric and sulfuric acids into stable salts to enable stratospheric geoengineering while reducing or reversing ozone depletion. Rather than minimizing reactive effects by reducing surface area using high refractive index materials, this method tailors the chemical reactivity. Specifically, we calculate that injection of calcite (CaCO 3 ) aerosol particles might reduce net radiative forcing while simultaneously increasing column ozone toward its preanthropogenic baseline. A radiative forcing of -1 W⋅m -2 , for example, might be achieved with a simultaneous 3.8% increase in column ozone using 2.1 Tg⋅y -1 of 275-nm radius calcite aerosol. Moreover, the radiative heating of the lower stratosphere would be roughly 10-fold less than if that same radiative forcing had been produced using sulfate aerosol. Although solar geoengineering cannot substitute for emissions cuts, it may supplement them by reducing some of the risks of climate change. Further research on this and similar methods could lead to reductions in risks and improved efficacy of solar geoengineering methods.

Simultaneous interrogation of interferometric and Bragg grating sensors

NASA Astrophysics Data System (ADS)

Brady, G.; Kalli, K.; Webb, D. J.; Jackson, D. A.; Reekie, L.; Archambault, J. L.

1995-06-01

We propose a new method for the simultaneous interrogation of conventional two-beam interferometers and Bragg grating sensors. The technique employs an unbalanced Mach-Zehnder interferometer illuminated by a single low-coherence source, which acts as a wavelength-tunable source for the grating and as a path-matched filter for the Fizeau interferometer, thus providing a high phase resolution output for each sensor. The grating sensor demonstrates a dynamic strain resolution of \\similar 0.05 mu 3 / \\radical Hz \\end-radical at 20 Hz, while the interferometric phase resolution is better than 1mrad/ \\radical Hz \\end-radical at 20 Hz, corresponding to an rms mirror displacement of 0.08 nm.

Simultaneous electrochemical determination of L-cysteine and L-cysteine disulfide at carbon ionic liquid electrode.

PubMed

Safavi, Afsaneh; Ahmadi, Raheleh; Mahyari, Farzaneh Aghakhani

2014-04-01

A linear sweep voltammetric method is used for direct simultaneous determination of L-cysteine and L-cysteine disulfide (cystine) based on carbon ionic liquid electrode. With carbon ionic liquid electrode as a high performance electrode, two oxidation peaks for L-cysteine (0.62 V) and L-cysteine disulfide (1.3 V) were observed with a significant separation of about 680 mV (vs. Ag/AgCl) in phosphate buffer solution (pH 6.0). The linear ranges were obtained as 1.0-450 and 5.0-700 μM and detection limits were estimated to be 0.298 and 4.258 μM for L-cysteine and L-cysteine disulfide, respectively. This composite electrode was applied for simultaneous determination of L-cysteine and L-cysteine disulfide in two real samples, artificial urine and nutrient broth. Satisfactory results were obtained which clearly indicate the applicability of the proposed electrode for simultaneous determination of these compounds in complex matrices.

Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network.

PubMed

Pham, Tuyen Danh; Lee, Dong Eun; Park, Kang Ryoung

2017-07-08

Automatic recognition of banknotes is applied in payment facilities, such as automated teller machines (ATMs) and banknote counters. Besides the popular approaches that focus on studying the methods applied to various individual types of currencies, there have been studies conducted on simultaneous classification of banknotes from multiple countries. However, their methods were conducted with limited numbers of banknote images, national currencies, and denominations. To address this issue, we propose a multi-national banknote classification method based on visible-light banknote images captured by a one-dimensional line sensor and classified by a convolutional neural network (CNN) considering the size information of each denomination. Experiments conducted on the combined banknote image database of six countries with 62 denominations gave a classification accuracy of 100%, and results show that our proposed algorithm outperforms previous methods.

Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network

PubMed Central

Pham, Tuyen Danh; Lee, Dong Eun; Park, Kang Ryoung

2017-01-01

Automatic recognition of banknotes is applied in payment facilities, such as automated teller machines (ATMs) and banknote counters. Besides the popular approaches that focus on studying the methods applied to various individual types of currencies, there have been studies conducted on simultaneous classification of banknotes from multiple countries. However, their methods were conducted with limited numbers of banknote images, national currencies, and denominations. To address this issue, we propose a multi-national banknote classification method based on visible-light banknote images captured by a one-dimensional line sensor and classified by a convolutional neural network (CNN) considering the size information of each denomination. Experiments conducted on the combined banknote image database of six countries with 62 denominations gave a classification accuracy of 100%, and results show that our proposed algorithm outperforms previous methods. PMID:28698466

Analysis of Closely Related Antioxidant Nutraceuticals Using the Green Analytical Methodology of ANN and Smart Spectrophotometric Methods.

PubMed

Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F

2017-01-01

Two new, simple, and specific green analytical methods are proposed: zero-crossing first-derivative and chemometric-based spectrophotometric artificial neural network (ANN). The proposed methods were used for the simultaneous estimation of two closely related antioxidant nutraceuticals, coenzyme Q10 (Q10) and vitamin E, in their mixtures and pharmaceutical preparations. The first method is based on the handling of spectrophotometric data with the first-derivative technique, in which both nutraceuticals were determined in ethanol, each at the zero crossing of the other. The amplitudes of the first-derivative spectra for Q10 and vitamin E were recorded at 285 and 235 nm respectively, and correlated with their concentrations. The linearity ranges of Q10 and vitamin E were 10-60 and 5.6-70 μg⋅mL-1, respectively. The second method, ANN, is a multivariate calibration method and it was developed and applied for the simultaneous determination of both analytes. A training set of 90 different synthetic mixtures containing Q10 and vitamin E in the ranges of 0-100 and 0-556 μg⋅mL-1, respectively, was prepared in ethanol. The absorption spectra of the training set were recorded in the spectral region of 230-300 nm. By relating the concentration sets (x-block) with their corresponding absorption data (y-block), gradient-descent back-propagation ANN calibration could be computed. To validate the proposed network, a set of 45 synthetic mixtures of the two drugs was used. Both proposed methods were successfully applied for the assay of Q10 and vitamin E in their laboratory-prepared mixtures and in their pharmaceutical tablets with excellent recovery. These methods offer advantages over other methods because of low-cost equipment, time-saving measures, and environmentally friendly materials. In addition, no chemical separation prior to analysis was needed. The ANN method was superior to the derivative technique because ANN can determine both drugs under nonlinear experimental conditions. Consequently, ANN would be the method of choice in the routine analysis of Q10 and vitamin E tablets. No interference from common pharmaceutical additives was observed. Student's t-test and the F-test were used to compare the two methods. No significant difference was recorded.

Simultaneous Determination of Ursodeoxycholic Acid and Chenodeoxycholic Acid in Pharmaceutical Dosage Form by HPLC-UV Detection.

PubMed

Khairy, Mostafa A; Mansour, Fotouh R

2017-01-01

A reversed-phase HPLC method was developed for the simultaneous determination of ursodeoxycholic acid (UDCA) and the epimeric isomer, chenodeoxycholic acid (CDCA), in their synthetic mixtures and in tablet dosage form. The proposed HPLC method uses a C18 column and mobile phase consisting of an acetonitrile-phosphate buffer mixture (pH 2.3, 100 mM; 50 + 50, v/v) at a flow rate of 2.0 mL/min with UV detection at 210 nm. The method was validated according to the International Conference on Harmonization guidelines; and linearity, range, accuracy, precision, robustness, and system suitability were studied. The LOD and LOQ were also calculated and found to be 1.23 and 3.73 μg/mL for UDCA and 0.83 and 2.52 μg/mL for CDCA, respectively. The method was adapted for UHPLC, in which baseline separation was achieved in <2.5 min. The assay results of Ursomix tablets by the developed method were statistically compared with those obtained by the reference method using t- and F-tests, and no significant differences were observed.

A study of selective spectrophotometric methods for simultaneous determination of Itopride hydrochloride and Rabeprazole sodium binary mixture: Resolving sever overlapping spectra

NASA Astrophysics Data System (ADS)

Mohamed, Heba M.

2015-02-01

Itopride hydrochloride (IT) and Rabeprazole sodium (RB) are co-formulated together for the treatment of gastro-esophageal reflux disease. Three simple, specific and accurate spectrophotometric methods were applied and validated for simultaneous determination of Itopride hydrochloride (IT) and Rabeprazole sodium (RB) namely; constant center (CC), ratio difference (RD) and mean centering of ratio spectra (MCR) spectrophotometric methods. Linear correlations were obtained in range of 10-110 μg/μL for Itopride hydrochloride and 4-44 μg/mL for Rabeprazole sodium. No preliminary separation steps were required prior the analysis of the two drugs using the proposed methods. Specificity was investigated by analyzing the synthetic mixtures containing the two cited drugs and their capsules dosage form. The obtained results were statistically compared with those obtained by the reported method, no significant difference was obtained with respect to accuracy and precision. The three methods were validated in accordance with ICH guidelines and can be used for quality control laboratories for IT and RB.

A study of selective spectrophotometric methods for simultaneous determination of Itopride hydrochloride and Rabeprazole sodium binary mixture: Resolving sever overlapping spectra.

PubMed

Mohamed, Heba M

2015-02-05

Itopride hydrochloride (IT) and Rabeprazole sodium (RB) are co-formulated together for the treatment of gastro-esophageal reflux disease. Three simple, specific and accurate spectrophotometric methods were applied and validated for simultaneous determination of Itopride hydrochloride (IT) and Rabeprazole sodium (RB) namely; constant center (CC), ratio difference (RD) and mean centering of ratio spectra (MCR) spectrophotometric methods. Linear correlations were obtained in range of 10-110μg/μL for Itopride hydrochloride and 4-44μg/mL for Rabeprazole sodium. No preliminary separation steps were required prior the analysis of the two drugs using the proposed methods. Specificity was investigated by analyzing the synthetic mixtures containing the two cited drugs and their capsules dosage form. The obtained results were statistically compared with those obtained by the reported method, no significant difference was obtained with respect to accuracy and precision. The three methods were validated in accordance with ICH guidelines and can be used for quality control laboratories for IT and RB. Copyright © 2014 Elsevier B.V. All rights reserved.

Simultaneous Quantification of Gymnemic Acid as Gymnemagenin and Charantin as β-Sitosterol Using Validated HPTLC Densitometric Method.

PubMed

Ahamad, Javed; Amin, Saima; Mir, Showkat R

2015-08-01

Gymnemic acid and charantin are well-established antidiabetic phytosterols found in Gymnema sylvestre and Momordica charantia, respectively. The fact that these plants are often used together in antidiabetic poly-herbal formulations lured us to develop an HPTLC densitometric method for the simultaneous quantification of their bioactive compounds. Indirect estimation of gymnemic acid as gymnemagenin and charantin as β-sitosterol after hydrolysis has been proposed. Aluminum-backed silica gel 60 F254 plates (20 × 10 cm) were used as stationary phase and toluene-ethyl acetate-methanol-formic acid (60 : 20 : 15 : 5, v/v) as mobile phase. Developed chromatogram was scanned at 550 nm after derivatization with modified vanillin-sulfuric acid reagent. Regression analysis of the calibration data showed an excellent linear relationship between peak area versus concentration of the analytes. Linearity was found to be in the range of 500-2,500 and 100-500 ng/band for gymnemagenin and β-sitosterol, respectively. The suitability of the developed HPTLC method for simultaneous estimation of analytes was established by validating it as per the ICH guidelines. The limits of detection and quantification for gymnemagenin were found to be ≈60 and ≈190 ng/band, and those for β-sitosterol ≈30 and ≈90 ng/band, respectively. The developed method was found to be linear (r(2) = 0.9987 and 0.9943), precise (relative standard deviation <1.5 and <2% for intra- and interday precision) and accurate (mean recovery ranged between 98.43-101.44 and 98.68-100.20%) for gymnemagenin and β-sitosterol, respectively. The proposed method was also found specific and robust for quantification of both the analytes and was successfully applied to herbal drugs and in-house herbal formulation without any interference. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Constrained simultaneous multi-state reconfigurable wing structure configuration optimization

NASA Astrophysics Data System (ADS)

Snyder, Matthew

A reconfigurable aircraft is capable of in-flight shape change to increase mission performance or provide multi-mission capability. Reconfigurability has always been a consideration in aircraft design, from the Wright Flyer, to the F-14, and most recently the Lockheed-Martin folding wing concept. The Wright Flyer used wing-warping for roll control, the F-14 had a variable-sweep wing to improve supersonic flight capabilities, and the Lockheed-Martin folding wing demonstrated radical in-flight shape change. This dissertation will examine two questions that aircraft reconfigurability raises, especially as reconfiguration increases in complexity. First, is there an efficient method to develop a light weight structure which supports all the loads generated by each configuration? Second, can this method include the capability to propose a sub-structure topology that weighs less than other considered designs? The first question requires a method that will design and optimize multiple configurations of a reconfigurable aerostructure. Three options exist, this dissertation will show one is better than the others. Simultaneous optimization considers all configurations and their respective load cases and constraints at the same time. Another method is sequential optimization which considers each configuration of the vehicle one after the other - with the optimum design variable values from the first configuration becoming the lower bounds for subsequent configurations. This process repeats for each considered configuration and the lower bounds update as necessary. The third approach is aggregate combination — this method keeps the thickness or area of each member for the most critical configuration, the configuration that requires the largest cross-section. This research will show that simultaneous optimization produces a lower weight and different topology for the considered structures when compared to the sequential and aggregate techniques. To answer the second question, the developed optimization algorithm combines simultaneous optimization with a new method for determining the optimum location of the structural members of the sub-structure. The method proposed here considers an over-populated structural model, one in which there are initially more members than necessary. Using a unique iterative process, the optimization algorithm removes members from the design if they do not carry enough load to justify their presence. The initial set of members includes ribs, spars and a series of cross-members that diagonally connect the ribs and spars. The final result is a different structure, which is lower weight than one developed from sequential optimization or aggregate combination, and suggests the primary load paths. Chapter 1 contains background information on reconfigurable aircraft and a description of the new reconfigurable air vehicle being considered by the Air Vehicles Directorate of the Air Force Research Laboratory. This vehicle serves as a platform to test the proposed optimization process. Chapters 2 and 3 overview the optimization method and Chapter 4 provides some background analysis which is unique to this particular reconfigurable air vehicle. Chapter 5 contains the results of the optimizations and demonstrates how changing constraints or initial configuration impacts the final weight and topology of the wing structure. The final chapter contains conclusions and comments on some future work which would further enhance the effectiveness of the simultaneous reconfigurable structural topology optimization process developed and used in this dissertation.

A comparison of critical heat flux in tubes and bilaterally heated annuli

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

Doerffer, S.; Groeneveld, D.C.; Cheng, S.C.

1995-09-01

This paper examines the critical heat flux (CHF) behaviour for annular flow in bilaterally heated annuli and compares it to that in tubes and unilaterally heated annuli. It was found that the differences in CHF between bilaterally and unilaterally heated annuli or tubes strongly depend on pressure and quality. the CHF in bilaterally heated annuli can be predicted by tube CHF prediction methods for the simultaneous CHF occurrence at both surfaces, and the following flow conditions: pressure 7-10 MPa, mass flux 0.5-4.0 Mg/m{sup 2}s and critical quality 0.23-0.9. The effect on CHF of the outer-to-inner surface heat flux ratio, wasmore » also examined. The prediction of CHF for bilaterally heated annuli was based on the droplet-diffusion model proposed by Kirillov and Smogalev. While their model refers only to CHF occurrence at the inner surface, we extended it to cases where CHF occurs at the outer surface, and simultaneously at both surfaces, thus covering all cases of CHF occurrence in bilaterally heated annuli. From the annuli CHF data of Becker and Letzter, we derived empirical functions required by the model. the proposed equations provide good accuracy for the CHF data used in this study. Moreover, the equations can predict conditions at which CHF occurs simultaneously at both surfaces. Also, this method can be used for cases with only one heated surface.« less

An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations

PubMed Central

Majumdar, Arunabha; Haldar, Tanushree; Bhattacharya, Sourabh; Witte, John S.

2018-01-01

Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy). For a locus exhibiting overall pleiotropy, it is important to identify which specific traits underlie this association. We propose a Bayesian meta-analysis approach (termed CPBayes) that uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. This method uses a unified Bayesian statistical framework based on a spike and slab prior. CPBayes performs a fully Bayesian analysis by employing the Markov Chain Monte Carlo (MCMC) technique Gibbs sampling. It takes into account heterogeneity in the size and direction of the genetic effects across traits. It can be applied to both cohort data and separate studies of multiple traits having overlapping or non-overlapping subjects. Simulations show that CPBayes can produce higher accuracy in the selection of associated traits underlying a pleiotropic signal than the subset-based meta-analysis ASSET. We used CPBayes to undertake a genome-wide pleiotropic association study of 22 traits in the large Kaiser GERA cohort and detected six independent pleiotropic loci associated with at least two phenotypes. This includes a locus at chromosomal region 1q24.2 which exhibits an association simultaneously with the risk of five different diseases: Dermatophytosis, Hemorrhoids, Iron Deficiency, Osteoporosis and Peripheral Vascular Disease. We provide an R-package ‘CPBayes’ implementing the proposed method. PMID:29432419

Development and validation of new spectrophotometric ratio H-point standard addition method and application to gastrointestinal acting drugs mixtures.

PubMed

Yehia, Ali M

2013-05-15

New, simple, specific, accurate and precise spectrophotometric technique utilizing ratio spectra is developed for simultaneous determination of two different binary mixtures. The developed ratio H-point standard addition method (RHPSAM) was managed successfully to resolve the spectral overlap in itopride hydrochloride (ITO) and pantoprazole sodium (PAN) binary mixture, as well as, mosapride citrate (MOS) and PAN binary mixture. The theoretical background and advantages of the newly proposed method are presented. The calibration curves are linear over the concentration range of 5-60 μg/mL, 5-40 μg/mL and 4-24 μg/mL for ITO, MOS and PAN, respectively. Specificity of the method was investigated and relative standard deviations were less than 1.5. The accuracy, precision and repeatability were also investigated for the proposed method according to ICH guidelines. Copyright © 2013 Elsevier B.V. All rights reserved.

Development and validation of new spectrophotometric ratio H-point standard addition method and application to gastrointestinal acting drugs mixtures

NASA Astrophysics Data System (ADS)

Yehia, Ali M.

2013-05-01

New, simple, specific, accurate and precise spectrophotometric technique utilizing ratio spectra is developed for simultaneous determination of two different binary mixtures. The developed ratio H-point standard addition method (RHPSAM) was managed successfully to resolve the spectral overlap in itopride hydrochloride (ITO) and pantoprazole sodium (PAN) binary mixture, as well as, mosapride citrate (MOS) and PAN binary mixture. The theoretical background and advantages of the newly proposed method are presented. The calibration curves are linear over the concentration range of 5-60 μg/mL, 5-40 μg/mL and 4-24 μg/mL for ITO, MOS and PAN, respectively. Specificity of the method was investigated and relative standard deviations were less than 1.5. The accuracy, precision and repeatability were also investigated for the proposed method according to ICH guidelines.

Improved neural network based scene-adaptive nonuniformity correction method for infrared focal plane arrays.

PubMed

Lai, Rui; Yang, Yin-tang; Zhou, Duan; Li, Yue-jin

2008-08-20

An improved scene-adaptive nonuniformity correction (NUC) algorithm for infrared focal plane arrays (IRFPAs) is proposed. This method simultaneously estimates the infrared detectors' parameters and eliminates the nonuniformity causing fixed pattern noise (FPN) by using a neural network (NN) approach. In the learning process of neuron parameter estimation, the traditional LMS algorithm is substituted with the newly presented variable step size (VSS) normalized least-mean square (NLMS) based adaptive filtering algorithm, which yields faster convergence, smaller misadjustment, and lower computational cost. In addition, a new NN structure is designed to estimate the desired target value, which promotes the calibration precision considerably. The proposed NUC method reaches high correction performance, which is validated by the experimental results quantitatively tested with a simulative testing sequence and a real infrared image sequence.

Prediction of protein-protein interaction network using a multi-objective optimization approach.

PubMed

Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

2016-06-01

Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.

A solution procedure for mixed-integer nonlinear programming formulation of supply chain planning with quantity discounts under demand uncertainty

NASA Astrophysics Data System (ADS)

Yin, Sisi; Nishi, Tatsushi

2014-11-01

Quantity discount policy is decision-making for trade-off prices between suppliers and manufacturers while production is changeable due to demand fluctuations in a real market. In this paper, quantity discount models which consider selection of contract suppliers, production quantity and inventory simultaneously are addressed. The supply chain planning problem with quantity discounts under demand uncertainty is formulated as a mixed-integer nonlinear programming problem (MINLP) with integral terms. We apply an outer-approximation method to solve MINLP problems. In order to improve the efficiency of the proposed method, the problem is reformulated as a stochastic model replacing the integral terms by using a normalisation technique. We present numerical examples to demonstrate the efficiency of the proposed method.

An efficient method for generalized linear multiplicative programming problem with multiplicative constraints.

PubMed

Zhao, Yingfeng; Liu, Sanyang

2016-01-01

We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.

A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

PubMed

Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

2017-01-01

In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H ∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Sparse Covariance Matrix Estimation With Eigenvalue Constraints

PubMed Central

LIU, Han; WANG, Lie; ZHAO, Tuo

2014-01-01

We propose a new approach for estimating high-dimensional, positive-definite covariance matrices. Our method extends the generalized thresholding operator by adding an explicit eigenvalue constraint. The estimated covariance matrix simultaneously achieves sparsity and positive definiteness. The estimator is rate optimal in the minimax sense and we develop an efficient iterative soft-thresholding and projection algorithm based on the alternating direction method of multipliers. Empirically, we conduct thorough numerical experiments on simulated datasets as well as real data examples to illustrate the usefulness of our method. Supplementary materials for the article are available online. PMID:25620866

[The possibility for using the phenomenon of polarized light interference in treating amblyopia].

PubMed

Abramov, V G; Vakurina, A E; Kashchenko, T P; Pargina, N M

1996-01-01

A new method for treating amblyopia is proposed, making use of the phenomenon of polarized light interference. It helps act simultaneously on the brightness, contrast frequency, and color sensitivity in response to patterns. The method was used in the treatment of 36 children. In group 1 (n = 20) it was combined with the traditional methods. Such treatment was more effective than in controls treated routinely. Group 2 consisted of 16 children in whom previous therapy was of no avail. Visual function was improved in 7 of them.

Different mathematical processing of absorption, ratio and derivative spectra for quantification of mixtures containing minor component: An application to the analysis of the recently co-formulated antidiabetic drugs; canagliflozin and metformin

NASA Astrophysics Data System (ADS)

Lotfy, Hayam M.; Mohamed, Dalia; Elshahed, Mona S.

2018-01-01

In the presented work several spectrophotometric methods were performed for the quantification of canagliflozin (CGZ) and metformin hydrochloride (MTF) simultaneously in their binary mixture. Two of these methods; response correlation (RC) and advanced balance point-spectrum subtraction (ABP-SS) were developed and introduced for the first time in this work, where the latter method (ABP-SS) was performed on both the zero order and the first derivative spectra of the drugs. Besides, two recently established methods; advanced amplitude modulation (AAM) and advanced absorbance subtraction (AAS) were also accomplished. All the proposed methods were validated in accordance to the ICH guidelines, where all methods were proved to be accurate and precise. Additionally, the linearity range, limit of detection and limit of quantification were determined and the selectivity was examined through the analysis of laboratory prepared mixtures and the combined dosage form of the drugs. The proposed methods were capable of determining the two drugs in the ratio present in the pharmaceutical formulation CGZ:MTF (1:17) without the requirement of any preliminary separation, further dilution or standard spiking. The results obtained by the proposed methods were in compliance with the reported chromatographic method when compared statistically, proving the absence of any significant difference in accuracy and precision between the proposed and reported methods.

Meta-path based heterogeneous combat network link prediction

NASA Astrophysics Data System (ADS)

Li, Jichao; Ge, Bingfeng; Yang, Kewei; Chen, Yingwu; Tan, Yuejin

2017-09-01

The combat system-of-systems in high-tech informative warfare, composed of many interconnected combat systems of different types, can be regarded as a type of complex heterogeneous network. Link prediction for heterogeneous combat networks (HCNs) is of significant military value, as it facilitates reconfiguring combat networks to represent the complex real-world network topology as appropriate with observed information. This paper proposes a novel integrated methodology framework called HCNMP (HCN link prediction based on meta-path) to predict multiple types of links simultaneously for an HCN. More specifically, the concept of HCN meta-paths is introduced, through which the HCNMP can accumulate information by extracting different features of HCN links for all the six defined types. Next, an HCN link prediction model, based on meta-path features, is built to predict all types of links of the HCN simultaneously. Then, the solution algorithm for the HCN link prediction model is proposed, in which the prediction results are obtained by iteratively updating with the newly predicted results until the results in the HCN converge or reach a certain maximum iteration number. Finally, numerical experiments on the dataset of a real HCN are conducted to demonstrate the feasibility and effectiveness of the proposed HCNMP, in comparison with 30 baseline methods. The results show that the performance of the HCNMP is superior to those of the baseline methods.

A green chemometrics-assisted fluorimetric detection method for the direct and simultaneous determination of six polycyclic aromatic hydrocarbons in oil-field wastewaters

NASA Astrophysics Data System (ADS)

Gu, Hui-Wen; Zhang, Shan-Hui; Wu, Bai-Chun; Chen, Wu; Wang, Jing-Bo; Liu, Yang

2018-07-01

Oil-field wastewaters contain high level of polycyclic aromatic hydrocarbons (PAHs), which have to be analyzed to assess the environmental effects before discharge. In this work, a green fluorimetric detection method that combines excitation-emission matrix (EEM) fluorescence with parallel factor analysis (PARAFAC) algorithm was firstly developed to achieve the direct and simultaneous determination of six U.S. EPA PAHs in two different kinds of complex oil-field wastewaters. Due to the distinctive "second-order advantage", neither time-consuming sample pretreatments nor toxic organic reagents were involved in the determination. By using the environment-friendly "mathematical separation" of PARAFAC, satisfactory quantitative results and reasonable spectral profiles for six PAHs were successfully extracted from the total EEM signals of oil-field wastewaters without need of chromatographic separation. The limits of detection of six PAHs were in the range of 0.09-0.72 ng mL-1, and the average spiked recoveries were between (89.4 ± 4.8)% and (109.1 ± 5.8)%, with average relative predictive errors <2.93%. In order to further confirm the accuracy of the proposed method, the same batch oil-field wastewater samples were analyzed by the recognized GC-MS method. t-test demonstrated that no significant differences exist between the quantitative results of the two methods. Given the advantages of green, fast, low-cost and high-sensitivity, the proposed method is expected to be broadened as an appealing alternative method for multi-residue analysis of overlapped PAHs in complex wastewater samples.

Development of an innovative immunoassay for CP4EPSPS and Cry1AB genetically modified protein detection and quantification.

PubMed

Ermolli, M; Prospero, A; Balla, B; Querci, M; Mazzeo, A; Van Den Eede, G

2006-09-01

An innovative immunoassay, called enzyme-linked immunoabsorbant assay (ELISA) Reverse, based on a new conformation of the solid phase, was developed. The solid support was expressly designed to be immersed directly in liquid samples to detect the presence of protein targets. Its application is proposed in those cases where a large number of samples have to be screened simultaneously or when the simultaneous detection of different proteins is required. As a first application, a quantitative immunoassay for Cry1AB protein in genetically modified maize was optimized. The method was tested using genetically modified organism concentrations from 0.1 to 2.0%. The limit of detection and limit of quantitation of the method were determined as 0.0056 and 0.0168 (expressed as the percentage of genetically modified organisms content), respectively. A qualitative multiplex assay to assess the presence of two genetically modified proteins simultaneously was also established for the case of the Cry1AB and the CP4EPSPS (5-enolpyruvylshikimate-3-phosphate synthase) present in genetically modified maize and soy, respectively.

Weighted analysis of composite endpoints with simultaneous inference for flexible weight constraints.

PubMed

Duc, Anh Nguyen; Wolbers, Marcel

2017-02-10

Composite endpoints are widely used as primary endpoints of randomized controlled trials across clinical disciplines. A common critique of the conventional analysis of composite endpoints is that all disease events are weighted equally, whereas their clinical relevance may differ substantially. We address this by introducing a framework for the weighted analysis of composite endpoints and interpretable test statistics, which are applicable to both binary and time-to-event data. To cope with the difficulty of selecting an exact set of weights, we propose a method for constructing simultaneous confidence intervals and tests that asymptotically preserve the family-wise type I error in the strong sense across families of weights satisfying flexible inequality or order constraints based on the theory of χ¯2-distributions. We show that the method achieves the nominal simultaneous coverage rate with substantial efficiency gains over Scheffé's procedure in a simulation study and apply it to trials in cardiovascular disease and enteric fever. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Simultaneous measurement of in-plane and out-of-plane displacement derivatives using dual-wavelength digital holographic interferometry.

PubMed

Rajshekhar, Gannavarpu; Gorthi, Sai Siva; Rastogi, Pramod

2011-12-01

The paper introduces a method for simultaneously measuring the in-plane and out-of-plane displacement derivatives of a deformed object in digital holographic interferometry. In the proposed method, lasers of different wavelengths are used to simultaneously illuminate the object along various directions such that a unique wavelength is used for a given direction. The holograms formed by multiple reference-object beam pairs of different wavelengths are recorded by a 3-color CCD camera with red, green, and blue channels. Each channel stores the hologram related to the corresponding wavelength and hence for the specific direction. The complex reconstructed interference field is obtained for each wavelength by numerical reconstruction and digital processing of the recorded holograms before and after deformation. Subsequently, the phase derivative is estimated for a given wavelength using two-dimensional pseudo Wigner-Ville distribution and the in-plane and out-of-plane components are obtained from the estimated phase derivatives using the sensitivity vectors of the optical configuration. © 2011 Optical Society of America

Microwave-assisted ultraviolet digestion of petroleum coke for the simultaneous determination of nickel, vanadium and sulfur by ICP-OES.

PubMed

Oliveira, Jussiane S S; Picoloto, Rochele S; Bizzi, Cezar A; Mello, Paola A; Barin, Juliano S; Flores, Erico M M

2015-11-01

A method for the simultaneous determination of Ni, V and S in petroleum coke by inductively coupled plasma optical emission spectrometry (ICP-OES) after microwave-assisted ultraviolet digestion (MW-UV) in closed vessels was proposed. Digestion was performed using electrodeless discharge lamps positioned inside quartz vessels and turned on by microwave radiation. The following parameters were evaluated: HNO3 concentration (15 mL of 1, 4, 7, 10 or 14.4 mol L(-1)), volume of H2O2 (30%, 1 or 3 mL), sample mass (100, 250 or 500 mg) and heating time (40 or 60 min) with or without the use of UV lamps. Digestion efficiency was evaluated by the determination of the residual carbon content (RCC) in digests. Using UV lamps lower RCC was obtained and the combination of 4 mol L(-1) HNO3 with 3 mL of H2O2 and 60 min of heating allowed a suitable digestion of up to 500 mg of petroleum coke (RCC< 21%). The agreement with the reference values for Ni, V and S (obtained by digestion of petroleum coke by microwave-induced combustion) and with a certified reference material of petroleum coke was between 96 and 101%. The proposed method was considered as advantageous when compared to American Society for Testing and Materials method because it allowed the simultaneous determination of Ni, V and S with lower limit of detection (0.22, 0.12 and 8.7 µg g(-1) for Ni, V and S, respectively) avoiding the use of concentrated nitric acid and providing digests suitable for routine analysis by ICP-OES. Copyright © 2015 Elsevier B.V. All rights reserved.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

Efficient HPTLC-dual wavelength spectrodensitometric method for simultaneous determination of sofosbuvir and daclatasvir: Biological and pharmaceutical analysis.

PubMed

Abo-Zeid, Mohammad Nabil; El-Gizawy, Samia M; Atia, Noha N; El-Shaboury, Salwa R

2018-05-01

Sofosbuvir (SOF) and daclatasvir (DCS) are newly discovered anti-hepatitis C drugs that have direct antiviral activity. A novel and simple high-performance thin-layer chromatography (HPTLC) method was designed for simultaneous determination of SOF and DCS in miscellaneous matrices. The method adopts coupling HPTLC with dual wavelength spectrodensitometry. Consequently, this enabled sensitive, specific and cost-effective determination of the SOF-DCS mixture. The developed HPTLC procedure is based on a simple liquid-liquid extraction, enrichment of the analytes and subsequent chromatographic separation with UV detection. Separations were performed on HPTLC silica gel 60 F 254 aluminum plates with a mobile phase consisting of ethyl acetate-isopropanol (85:15, v/v). Dual wavelength scanning was carried out in the absorbance mode at 265 and 311 nm for SOF and DCS, respectively. The linear ranges were 40-640 and 20-320 ng band -1 for SOF and DCS, respectively with correlation coefficients of ≥0.9997. The detection limits were 11.3 and 6.5 ng band -1 for SOF and DCS, respectively indicating high sensitivity of the proposed method. Consequently, this permits in vitro and in vivo application of the proposed method in human plasma with good percentage recovery (94.1-103.5%). Validation parameters were assessed according to ICH guidelines and US-FDA guidelines. Furthermore, the application was extended to analysis of SOF and DCS in their pharmaceutical formulations. Copyright © 2018 Elsevier B.V. All rights reserved.

A fully automated method for simultaneous determination of aflatoxins and ochratoxin A in dried fruits by pressurized liquid extraction and online solid-phase extraction cleanup coupled to ultra-high-pressure liquid chromatography-tandem mass spectrometry.

PubMed

Campone, Luca; Piccinelli, Anna Lisa; Celano, Rita; Russo, Mariateresa; Valdés, Alberto; Ibáñez, Clara; Rastrelli, Luca

2015-04-01

According to current demands and future perspectives in food safety, this study reports a fast and fully automated analytical method for the simultaneous analysis of the mycotoxins with high toxicity and wide spread, aflatoxins (AFs) and ochratoxin A (OTA) in dried fruits, a high-risk foodstuff. The method is based on pressurized liquid extraction (PLE), with aqueous methanol (30%) at 110 °C, of the slurried dried fruit and online solid-phase extraction (online SPE) cleanup of the PLE extracts with a C18 cartridge. The purified sample was directly analysed by ultra-high-pressure liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) for sensitive and selective determination of AFs and OTA. The proposed analytical procedure was validated for different dried fruits (vine fruit, fig and apricot), providing method detection and quantification limits much lower than the AFs and OTA maximum levels imposed by EU regulation in dried fruit for direct human consumption. Also, recoveries (83-103%) and repeatability (RSD < 8, n = 3) meet the performance criteria required by EU regulation for the determination of the levels of mycotoxins in foodstuffs. The main advantage of the proposed method is full automation of the whole analytical procedure that reduces the time and cost of the analysis, sample manipulation and solvent consumption, enabling high-throughput analysis and highly accurate and precise results.

A novel method for the simultaneous measurement of temperature and strain using a three-wire connection

NASA Astrophysics Data System (ADS)

Cappa, Paolo; Marinozzi, Franco; Sciuto, Salvatore Andrea

2001-04-01

A novel methodology to simultaneously measure strain and temperature by means of an electrical resistance strain gauge powered by an ac signal and connected to a strain indicator by means of thermocouple wires is proposed. The experimental validation of the viability of this method is conducted by means of a purely electrical simulation of both strain and temperature signals, respectively from -2000 to 2000 µm m-1 and -250 to 230 °C. The results obtained showed that strain measurement is affected by an error always less than ±2 µm m-1 for the whole range of simulated strains, while the error in temperature evaluation is always less than 0.6 °C. The effect of cross-talk between the two signals was determined to be insignificant.

Multi-rendezvous low-thrust trajectory optimization using costate transforming and homotopic approach

NASA Astrophysics Data System (ADS)

Chen, Shiyu; Li, Haiyang; Baoyin, Hexi

2018-06-01

This paper investigates a method for optimizing multi-rendezvous low-thrust trajectories using indirect methods. An efficient technique, labeled costate transforming, is proposed to optimize multiple trajectory legs simultaneously rather than optimizing each trajectory leg individually. Complex inner-point constraints and a large number of free variables are one main challenge in optimizing multi-leg transfers via shooting algorithms. Such a difficulty is reduced by first optimizing each trajectory leg individually. The results may be, next, utilized as an initial guess in the simultaneous optimization of multiple trajectory legs. In this paper, the limitations of similar techniques in previous research is surpassed and a homotopic approach is employed to improve the convergence efficiency of the shooting process in multi-rendezvous low-thrust trajectory optimization. Numerical examples demonstrate that newly introduced techniques are valid and efficient.

Optical properties reconstruction using the adjoint method based on the radiative transfer equation

NASA Astrophysics Data System (ADS)

Addoum, Ahmad; Farges, Olivier; Asllanaj, Fatmir

2018-01-01

An efficient algorithm is proposed to reconstruct the spatial distribution of optical properties in heterogeneous media like biological tissues. The light transport through such media is accurately described by the radiative transfer equation in the frequency-domain. The adjoint method is used to efficiently compute the objective function gradient with respect to optical parameters. Numerical tests show that the algorithm is accurate and robust to retrieve simultaneously the absorption μa and scattering μs coefficients for lowly and highly absorbing medium. Moreover, the simultaneous reconstruction of μs and the anisotropy factor g of the Henyey-Greenstein phase function is achieved with a reasonable accuracy. The main novelty in this work is the reconstruction of g which might open the possibility to image this parameter in tissues as an additional contrast agent in optical tomography.

A Penalized Robust Method for Identifying Gene-Environment Interactions

PubMed Central

Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

2015-01-01

In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model mis-specification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications. PMID:24616063

Sequential fitting-and-separating reflectance components for analytical bidirectional reflectance distribution function estimation.

PubMed

Lee, Yu; Yu, Chanki; Lee, Sang Wook

2018-01-10

We present a sequential fitting-and-separating algorithm for surface reflectance components that separates individual dominant reflectance components and simultaneously estimates the corresponding bidirectional reflectance distribution function (BRDF) parameters from the separated reflectance values. We tackle the estimation of a Lafortune BRDF model, which combines a nonLambertian diffuse reflection and multiple specular reflectance components with a different specular lobe. Our proposed method infers the appropriate number of BRDF lobes and their parameters by separating and estimating each of the reflectance components using an interval analysis-based branch-and-bound method in conjunction with iterative K-ordered scale estimation. The focus of this paper is the estimation of the Lafortune BRDF model. Nevertheless, our proposed method can be applied to other analytical BRDF models such as the Cook-Torrance and Ward models. Experiments were carried out to validate the proposed method using isotropic materials from the Mitsubishi Electric Research Laboratories-Massachusetts Institute of Technology (MERL-MIT) BRDF database, and the results show that our method is superior to a conventional minimization algorithm.

Pseudo-color coding method for high-dynamic single-polarization SAR images

NASA Astrophysics Data System (ADS)

Feng, Zicheng; Liu, Xiaolin; Pei, Bingzhi

2018-04-01

A raw synthetic aperture radar (SAR) image usually has a 16-bit or higher bit depth, which cannot be directly visualized on 8-bit displays. In this study, we propose a pseudo-color coding method for high-dynamic singlepolarization SAR images. The method considers the characteristics of both SAR images and human perception. In HSI (hue, saturation and intensity) color space, the method carries out high-dynamic range tone mapping and pseudo-color processing simultaneously in order to avoid loss of details and to improve object identifiability. It is a highly efficient global algorithm.

Extension of electronic speckle correlation interferometry to large deformations

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.; Sciammarella, Federico M.

1998-07-01

The process of fringe formation under simultaneous illumination in two orthogonal directions is analyzed. Procedures to extend the applicability of this technique to large deformation and high density of fringes are introduced. The proposed techniques are applied to a number of technical problems. Good agreement is obtained when the experimental results are compared with results obtained by other methods.

A Method for the Comparison of Item Selection Rules in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Barrada, Juan Ramon; Olea, Julio; Ponsoda, Vicente; Abad, Francisco Jose

2010-01-01

In a typical study comparing the relative efficiency of two item selection rules in computerized adaptive testing, the common result is that they simultaneously differ in accuracy and security, making it difficult to reach a conclusion on which is the more appropriate rule. This study proposes a strategy to conduct a global comparison of two or…

Process Mining-Based Method of Designing and Optimizing the Layouts of Emergency Departments in Hospitals.

PubMed

Rismanchian, Farhood; Lee, Young Hoon

2017-07-01

This article proposes an approach to help designers analyze complex care processes and identify the optimal layout of an emergency department (ED) considering several objectives simultaneously. These objectives include minimizing the distances traveled by patients, maximizing design preferences, and minimizing the relocation costs. Rising demand for healthcare services leads to increasing demand for new hospital buildings as well as renovating existing ones. Operations management techniques have been successfully applied in both manufacturing and service industries to design more efficient layouts. However, high complexity of healthcare processes makes it challenging to apply these techniques in healthcare environments. Process mining techniques were applied to address the problem of complexity and to enhance healthcare process analysis. Process-related information, such as information about the clinical pathways, was extracted from the information system of an ED. A goal programming approach was then employed to find a single layout that would simultaneously satisfy several objectives. The layout identified using the proposed method improved the distances traveled by noncritical and critical patients by 42.2% and 47.6%, respectively, and minimized the relocation costs. This study has shown that an efficient placement of the clinical units yields remarkable improvements in the distances traveled by patients.

Real-time and encryption efficiency improvements of simultaneous fusion, compression and encryption method based on chaotic generators

NASA Astrophysics Data System (ADS)

Jridi, Maher; Alfalou, Ayman

2018-03-01

In this paper, enhancement of an existing optical simultaneous fusion, compression and encryption (SFCE) scheme in terms of real-time requirements, bandwidth occupation and encryption robustness is proposed. We have used and approximate form of the DCT to decrease the computational resources. Then, a novel chaos-based encryption algorithm is introduced in order to achieve the confusion and diffusion effects. In the confusion phase, Henon map is used for row and column permutations, where the initial condition is related to the original image. Furthermore, the Skew Tent map is employed to generate another random matrix in order to carry out pixel scrambling. Finally, an adaptation of a classical diffusion process scheme is employed to strengthen security of the cryptosystem against statistical, differential, and chosen plaintext attacks. Analyses of key space, histogram, adjacent pixel correlation, sensitivity, and encryption speed of the encryption scheme are provided, and favorably compared to those of the existing crypto-compression system. The proposed method has been found to be digital/optical implementation-friendly which facilitates the integration of the crypto-compression system on a very broad range of scenarios.

[Derivative synchronous fluorimetry for determination of synthetic food dyes in food].

PubMed

Xie, Zhi-Hai; Wang, Ling-Yan; Liu, Yu; Cai, Qing; Wang, Hai-Li; Yan, Hong-Tao

2014-05-01

The first order derivative synchronous fluoremetry was proposed for simultaneous determination of sunset yellow and ponceau 4R The effect of different experimental conditions, such as different pH for character of fluorescence spectra and the choosing of the optimal wavelength difference were studied. It was showed that the zero-crossing points were at 313. 6 nm for ponceau 4R and at 302. 8 nm for sunset yellow in first order derivative synchronous fluorescence spectra. Therefore, 313. 6 and 302. 8 nm were selected for the determination of sunset yellow and ponceau 4R when delta lambda= 130 nm. This method could minimize interference without preseparation. The linear ranges of sunset yellow and ponceau 4R were from 0. 1 to 2. 0 mg L-1 and from 0. 1 to 4. 0 mg L-1 with correlation coefficient 0. 996 6 and 0. 999 2, the detection limits were 0. 041 and 0. 019 mg L-1 , RS-Ds were 4. 6% and 4. 8% (n=6), respectively. The recoveries varied from 91. 0% to 110%. The proposed method was successfully applied in simultaneous determination of sunset yellow and Ponceau 4R in food.

Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

PubMed

Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

Simultaneous Helmert transformations among multiple frames considering all relevant measurements

NASA Astrophysics Data System (ADS)

Chang, Guobin; Lin, Peng; Bian, Hefang; Gao, Jingxiang

2018-03-01

Helmert or similarity models are widely employed to relate different coordinate frames. It is often encountered in practice to transform coordinates from more than one old frame into a new one. One may perform separate Helmert transformations for each old frame. However, although each transformation is locally optimal, this is not globally optimal. Transformations among three frames, namely one new and two old, are studied as an example. Simultaneous Helmert transformations among all frames are also studied. Least-squares estimation of the transformation parameters and the coordinates in the new frame of all stations involved is performed. A functional model for the transformations among multiple frames is developed. A realistic stochastic model is followed, in which not only non-common stations are taken into consideration, but also errors in all measurements are addressed. An algorithm of iterative linearizations and estimations is derived in detail. The proposed method is globally optimal, and, perhaps more importantly, it produces a unified network of the new frame providing coordinate estimates for all involved stations and the associated covariance matrix, with the latter being consistent with the true errors of the former. Simulations are conducted, and the results validate the superiority of the proposed combined method over separate approaches.

Efficient robust doubly adaptive regularized regression with applications.

PubMed

Karunamuni, Rohana J; Kong, Linglong; Tu, Wei

2018-01-01

We consider the problem of estimation and variable selection for general linear regression models. Regularized regression procedures have been widely used for variable selection, but most existing methods perform poorly in the presence of outliers. We construct a new penalized procedure that simultaneously attains full efficiency and maximum robustness. Furthermore, the proposed procedure satisfies the oracle properties. The new procedure is designed to achieve sparse and robust solutions by imposing adaptive weights on both the decision loss and the penalty function. The proposed method of estimation and variable selection attains full efficiency when the model is correct and, at the same time, achieves maximum robustness when outliers are present. We examine the robustness properties using the finite-sample breakdown point and an influence function. We show that the proposed estimator attains the maximum breakdown point. Furthermore, there is no loss in efficiency when there are no outliers or the error distribution is normal. For practical implementation of the proposed method, we present a computational algorithm. We examine the finite-sample and robustness properties using Monte Carlo studies. Two datasets are also analyzed.

Simultaneous measurement of refractive index and thickness by combining low-coherence interferometry and confocal optics.

PubMed

Kim, Seokhan; Na, Jihoon; Kim, Myoung Jin; Lee, Byeong Ha

2008-04-14

We propose and demonstrate novel methods that enable simultaneous measurements of the phase index, the group index, and the geometrical thickness of an optically transparent object by combining optical low-coherence interferometer and confocal optics. The low-coherence interferometer gives information relating the group index with the thickness, while the confocal optics allows access to the phase index related with the thickness of the sample. To relate these, two novel methods were devised. In the first method, the dispersion-induced broadening of the low-coherence envelop signal was utilized, and in the second method the frequency derivative of the phase index was directly obtained by taking the confocal measurements at several wavelengths. The measurements were made with eight different samples; B270, CaF2, two of BK7, two of fused silica, cover glass, and cigarette cover film. The average measurement errors of the first and the second methods were 0.123% and 0.061% in the geometrical thickness, 0.133% and 0.066% in the phase index, and 0.106% and 0.057% in the group index, respectively.

A PLS-based extractive spectrophotometric method for simultaneous determination of carbamazepine and carbamazepine-10,11-epoxide in plasma and comparison with HPLC

NASA Astrophysics Data System (ADS)

Hemmateenejad, Bahram; Rezaei, Zahra; Khabnadideh, Soghra; Saffari, Maryam

2007-11-01

Carbamazepine (CBZ) undergoes enzyme biotransformation through epoxidation with the formation of its metabolite, carbamazepine-10,11-epoxide (CBZE). A simple chemometrics-assisted spectrophotometric method has been proposed for simultaneous determination of CBZ and CBZE in plasma. A liquid extraction procedure was operated to separate the analytes from plasma, and the UV absorbance spectra of the resultant solutions were subjected to partial least squares (PLS) regression. The optimum number of PLS latent variables was selected according to the PRESS values of leave-one-out cross-validation. A HPLC method was also employed for comparison. The respective mean recoveries for analysis of CBZ and CBZE in synthetic mixtures were 102.57 (±0.25)% and 103.00 (±0.09)% for PLS and 99.40 (±0.15)% and 102.20 (±0.02)%. The concentrations of CBZ and CBZE were also determined in five patients using the PLS and HPLC methods. The results showed that the data obtained by PLS were comparable with those obtained by HPLC method.

Detection of Bursts and Pauses in Spike Trains

PubMed Central

Ko, D.; Wilson, C. J.; Lobb, C. J.; Paladini, C. A.

2012-01-01

Midbrain dopaminergic neurons in vivo exhibit a wide range of firing patterns. They normally fire constantly at a low rate, and speed up, firing a phasic burst when reward exceeds prediction, or pause when an expected reward does not occur. Therefore, the detection of bursts and pauses from spike train data is a critical problem when studying the role of phasic dopamine (DA) in reward related learning, and other DA dependent behaviors. However, few statistical methods have been developed that can identify bursts and pauses simultaneously. We propose a new statistical method, the Robust Gaussian Surprise (RGS) method, which performs an exhaustive search of bursts and pauses in spike trains simultaneously. We found that the RGS method is adaptable to various patterns of spike trains recorded in vivo, and is not influenced by baseline firing rate, making it applicable to all in vivo spike trains where baseline firing rates vary over time. We compare the performance of the RGS method to other methods of detecting bursts, such as the Poisson Surprise (PS), Rank Surprise (RS), and Template methods. Analysis of data using the RGS method reveals potential mechanisms underlying how bursts and pauses are controlled in DA neurons. PMID:22939922

A highly precise frequency-based method for estimating the tension of an inclined cable with unknown boundary conditions

NASA Astrophysics Data System (ADS)

Ma, Lin

2017-11-01

This paper develops a method for precisely determining the tension of an inclined cable with unknown boundary conditions. First, the nonlinear motion equation of an inclined cable is derived, and a numerical model of the motion of the cable is proposed using the finite difference method. The proposed numerical model includes the sag-extensibility, flexural stiffness, inclination angle and rotational stiffness at two ends of the cable. Second, the influence of the dynamic parameters of the cable on its frequencies is discussed in detail, and a method for precisely determining the tension of an inclined cable is proposed based on the derivatives of the eigenvalues of the matrices. Finally, a multiparameter identification method is developed that can simultaneously identify multiple parameters, including the rotational stiffness at two ends. This scheme is applicable to inclined cables with varying sag, varying flexural stiffness and unknown boundary conditions. Numerical examples indicate that the method provides good precision. Because the parameters of cables other than tension (e.g., the flexural stiffness and rotational stiffness at the ends) are not accurately known in practical engineering, the multiparameter identification method could further improve the accuracy of cable tension measurements.

RP-HPLC method development and validation for simultaneous estimation of atorvastatin calcium and pioglitazone hydrochloride in pharmaceutical dosage form.

PubMed

Peraman, Ramalingam; Mallikarjuna, Sasikala; Ammineni, Pravalika; Kondreddy, Vinod kumar

2014-10-01

A simple, selective, rapid, precise and economical reversed-phase high-performance liquid chromatographic (RP-HPLC) method has been developed for simultaneous estimation of atorvastatin calcium (ATV) and pioglitazone hydrochloride (PIO) from pharmaceutical formulation. The method is carried out on a C8 (25 cm × 4.6 mm i.d., 5 μm) column with a mobile phase consisting of acetonitrile (ACN):water (pH adjusted to 6.2 using o-phosphoric acid) in the ratio of 45:55 (v/v). The retention time of ATV and PIO is 4.1 and 8.1 min, respectively, with the flow rate of 1 mL/min with diode array detector detection at 232 nm. The linear regression analysis data from the linearity plot showed good linear relationship with a correlation coefficient (R(2)) value for ATV and PIO of 0.9998 and 0.9997 in the concentration range of 10-80 µg mL(-1), respectively. The relative standard deviation for intraday precision has been found to be <2.0%. The method is validated according to the ICH guidelines. The developed method is validated in terms of specificity, selectivity, accuracy, precision, linearity, limit of detection, limit of quantitation and solution stability. The proposed method can be used for simultaneous estimation of these drugs in marketed dosage forms. © The Author [2013]. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Analytical Method Development and Validation for the Simultaneous Estimation of Abacavir and Lamivudine by Reversed-phase High-performance Liquid Chromatography in Bulk and Tablet Dosage Forms.

PubMed

Raees Ahmad, Sufiyan Ahmad; Patil, Lalit; Mohammed Usman, Mohammed Rageeb; Imran, Mohammad; Akhtar, Rashid

2018-01-01

A simple rapid, accurate, precise, and reproducible validated reverse phase high performance liquid chromatography (HPLC) method was developed for the determination of Abacavir (ABAC) and Lamivudine (LAMI) in bulk and tablet dosage forms. The quantification was carried out using Symmetry Premsil C18 (250 mm × 4.6 mm, 5 μm) column run in isocratic way using mobile phase comprising methanol: water (0.05% orthophosphoric acid with pH 3) 83:17 v/v and a detection wavelength of 245 nm and injection volume of 20 μl, with a flow rate of 1 ml/min. In the developed method, the retention times of ABAC and LAMI were found to be 3.5 min and 7.4 min, respectively. The method was validated in terms of linearity, precision, accuracy, limits of detection, limits of quantitation, and robustness in accordance with the International Conference on Harmonization guidelines. The assay of the proposed method was found to be 99% - 101%. The recovery studies were also carried out and mean % recovery was found to be 99% - 101%. The % relative standard deviation from reproducibility was found to be <2%. The proposed method was statistically evaluated and can be applied for routine quality control analysis of ABAC and LAMI in bulk and in tablet dosage form. Attempts were made to develop RP-HPLC method for simultaneous estimation of Abacavir and Lamivudine for the RP-HPLC method. The developed method was validated according to the ICH guidelines. The linearity, precision, range, robustness were within the limits as specified by the ICH guidelines. Hence the method was found to be simple, accurate, precise, economic and reproducible. So the proposed methods can be used for the routine quality control analysis of Abacavir and Lamivudine in bulk drug as well as in formulations. Abbreviations Used: HPLC: High-performance liquid chromatography, UV: Ultraviolet, ICH: International Conference on Harmonization, ABAC: Abacavir, LAMI: Lamivudine, HIV: Human immunodeficiency virus, AIDS: Acquired immunodeficiency syndrome, NRTI: Nucleoside reverse transcriptase inhibitors, ARV: Antiretroviral, RSD: Relative standard deviation, RT: Retention time, SD: Standard deviation.

Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

NASA Astrophysics Data System (ADS)

Tamimi, E.; Ebadi, H.; Kiani, A.

2017-09-01

Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

Design and performance evaluation of a distributed OFDMA-based MAC protocol for MANETs.

PubMed

Park, Jaesung; Chung, Jiyoung; Lee, Hyungyu; Lee, Jung-Ryun

2014-01-01

In this paper, we propose a distributed MAC protocol for OFDMA-based wireless mobile ad hoc multihop networks, in which the resource reservation and data transmission procedures are operated in a distributed manner. A frame format is designed considering the characteristics of OFDMA that each node can transmit or receive data to or from multiple nodes simultaneously. Under this frame structure, we propose a distributed resource management method including network state estimation and resource reservation processes. We categorize five types of logical errors according to their root causes and show that two of the logical errors are inevitable while three of them are avoided under the proposed distributed MAC protocol. In addition, we provide a systematic method to determine the advertisement period of each node by presenting a clear relation between the accuracy of estimated network states and the signaling overhead. We evaluate the performance of the proposed protocol in respect of the reservation success rate and the success rate of data transmission. Since our method focuses on avoiding logical errors, it could be easily placed on top of the other resource allocation methods focusing on the physical layer issues of the resource management problem and interworked with them.

Identification-While-Scanning of a Multi-Aircraft Formation Based on Sparse Recovery for Narrowband Radar.

PubMed

Jiang, Yuan; Xu, Jia; Peng, Shi-Bao; Mao, Er-Ke; Long, Teng; Peng, Ying-Ning

2016-11-23

It is known that the identification performance of a multi-aircraft formation (MAF) of narrowband radar mainly depends on the time on target (TOT). To realize the identification task in one rotated scan with limited TOT, the paper proposes a novel identification-while-scanning (IWS) method based on sparse recovery to maintain high rotating speed and super-resolution for MAF identification, simultaneously. First, a multiple chirp signal model is established for MAF in a single scan, where different aircraft may have different Doppler centers and Doppler rates. Second, based on the sparsity of MAF in the Doppler parameter space, a novel hierarchical basis pursuit (HBP) method is proposed to obtain satisfactory sparse recovery performance as well as high computational efficiency. Furthermore, the parameter estimation performance of the proposed IWS identification method is analyzed with respect to recovery condition, signal-to-noise ratio and TOT. It is shown that an MAF can be effectively identified via HBP with a TOT of only about one hundred microseconds for IWS applications. Finally, some numerical experiment results are provided to demonstrate the effectiveness of the proposed method based on both simulated and real measured data.

Bayesian methods for outliers detection in GNSS time series

NASA Astrophysics Data System (ADS)

Qianqian, Zhang; Qingming, Gui

2013-07-01

This article is concerned with the problem of detecting outliers in GNSS time series based on Bayesian statistical theory. Firstly, a new model is proposed to simultaneously detect different types of outliers based on the conception of introducing different types of classification variables corresponding to the different types of outliers; the problem of outlier detection is converted into the computation of the corresponding posterior probabilities, and the algorithm for computing the posterior probabilities based on standard Gibbs sampler is designed. Secondly, we analyze the reasons of masking and swamping about detecting patches of additive outliers intensively; an unmasking Bayesian method for detecting additive outlier patches is proposed based on an adaptive Gibbs sampler. Thirdly, the correctness of the theories and methods proposed above is illustrated by simulated data and then by analyzing real GNSS observations, such as cycle slips detection in carrier phase data. Examples illustrate that the Bayesian methods for outliers detection in GNSS time series proposed by this paper are not only capable of detecting isolated outliers but also capable of detecting additive outlier patches. Furthermore, it can be successfully used to process cycle slips in phase data, which solves the problem of small cycle slips.

Image Search Reranking With Hierarchical Topic Awareness.

PubMed

Tian, Xinmei; Yang, Linjun; Lu, Yijuan; Tian, Qi; Tao, Dacheng

2015-10-01

With much attention from both academia and industrial communities, visual search reranking has recently been proposed to refine image search results obtained from text-based image search engines. Most of the traditional reranking methods cannot capture both relevance and diversity of the search results at the same time. Or they ignore the hierarchical topic structure of search result. Each topic is treated equally and independently. However, in real applications, images returned for certain queries are naturally in hierarchical organization, rather than simple parallel relation. In this paper, a new reranking method "topic-aware reranking (TARerank)" is proposed. TARerank describes the hierarchical topic structure of search results in one model, and seamlessly captures both relevance and diversity of the image search results simultaneously. Through a structured learning framework, relevance and diversity are modeled in TARerank by a set of carefully designed features, and then the model is learned from human-labeled training samples. The learned model is expected to predict reranking results with high relevance and diversity for testing queries. To verify the effectiveness of the proposed method, we collect an image search dataset and conduct comparison experiments on it. The experimental results demonstrate that the proposed TARerank outperforms the existing relevance-based and diversified reranking methods.

GPU accelerated edge-region based level set evolution constrained by 2D gray-scale histogram.

PubMed

Balla-Arabé, Souleymane; Gao, Xinbo; Wang, Bin

2013-07-01

Due to its intrinsic nature which allows to easily handle complex shapes and topological changes, the level set method (LSM) has been widely used in image segmentation. Nevertheless, LSM is computationally expensive, which limits its applications in real-time systems. For this purpose, we propose a new level set algorithm, which uses simultaneously edge, region, and 2D histogram information in order to efficiently segment objects of interest in a given scene. The computational complexity of the proposed LSM is greatly reduced by using the highly parallelizable lattice Boltzmann method (LBM) with a body force to solve the level set equation (LSE). The body force is the link with image data and is defined from the proposed LSE. The proposed LSM is then implemented using an NVIDIA graphics processing units to fully take advantage of the LBM local nature. The new algorithm is effective, robust against noise, independent to the initial contour, fast, and highly parallelizable. The edge and region information enable to detect objects with and without edges, and the 2D histogram information enable the effectiveness of the method in a noisy environment. Experimental results on synthetic and real images demonstrate subjectively and objectively the performance of the proposed method.

Simultaneous acquisition sequence for improved hepatic pharmacokinetics quantification accuracy (SAHA) for dynamic contrast-enhanced MRI of liver.

PubMed

Ning, Jia; Sun, Yongliang; Xie, Sheng; Zhang, Bida; Huang, Feng; Koken, Peter; Smink, Jouke; Yuan, Chun; Chen, Huijun

2018-05-01

To propose a simultaneous acquisition sequence for improved hepatic pharmacokinetics quantification accuracy (SAHA) method for liver dynamic contrast-enhanced MRI. The proposed SAHA simultaneously acquired high temporal-resolution 2D images for vascular input function extraction using Cartesian sampling and 3D large-coverage high spatial-resolution liver dynamic contrast-enhanced images using golden angle stack-of-stars acquisition in an interleaved way. Simulations were conducted to investigate the accuracy of SAHA in pharmacokinetic analysis. A healthy volunteer and three patients with cirrhosis or hepatocellular carcinoma were included in the study to investigate the feasibility of SAHA in vivo. Simulation studies showed that SAHA can provide closer results to the true values and lower root mean square error of estimated pharmacokinetic parameters in all of the tested scenarios. The in vivo scans of subjects provided fair image quality of both 2D images for arterial input function and portal venous input function and 3D whole liver images. The in vivo fitting results showed that the perfusion parameters of healthy liver were significantly different from those of cirrhotic liver and HCC. The proposed SAHA can provide improved accuracy in pharmacokinetic modeling and is feasible in human liver dynamic contrast-enhanced MRI, suggesting that SAHA is a potential tool for liver dynamic contrast-enhanced MRI. Magn Reson Med 79:2629-2641, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Simultaneous measurement for strain and temperature based on the twisted-tapering fiber structure

NASA Astrophysics Data System (ADS)

Ni, Wenjun; Lu, Ping; Liu, Deming; Zhang, Jiangshan

2017-10-01

A novel special fiber fabrication method based on a common single mode fiber (SMF) for dual-parameters measurement has been proposed and experimentally demonstrated. The fabrication setup is based on a three dimensional electric displacement platform which can realize the function of twisting and tapering at the same time. The proposed novel structure simultaneously undergoes the aforementioned two processes. Then a twisted-tapering fiber structure is formed. There are two dominant resonant wavelengths in the spectrum. Thus, simultaneous measurement for strain and temperature can be achieved. The following result shows that the strain measurement can be achieved by intensity demodulation, with the sensitivity of -0.01565 dB/μɛ and 0.00705 dB/μɛ corresponding to the dip1 and dip2, respectively. Therefore, the total sensitivity of the strain is 0.0227 dB/μɛ. Moreover, the cross impacts of the wavelength shift are - 0.772 pm/μɛ and 0.895 pm/μɛ. Similarly, the wavelength demodulation is selected to temperature measurement. The temperature sensitivity of 50.53pm/°C and 45.12pm/°C are obtained. The cross sensitivity of the intensity variation are 0.04058dB/°C and 0.02031 dB/°C. As a result, the dual-parameters can be described to a cross matrix of the sensitivity value. The proposed sensor has a great potential for engineering applications due to its compact structure, simple manufacture and low cost.

Technical note: Simultaneous carotenoid and vitamin analysis of milk from total mixed ration-fed cows optimized for xanthophyll detection.

PubMed

Stout, M A; Benoist, D M; Drake, M A

2018-06-01

Concentrations of retinol, α-tocopherol, and major carotenoids in dairy products are often determined simultaneously by liquid chromatography. These compounds have different polarity and solubility; thus, extracting them simultaneously can be difficult and inefficient. In milks with low carotenoid concentrations, the xanthophylls lutein and zeaxanthin may not be completely resolved using common extraction techniques. A simplified method was developed to optimize extraction efficiency and the limit of detection and limit of quantification (LoQ) of lutein and zeaxanthin in bovine milk without decreasing sensitivity to other vitamins or carotenoids. The developed method evaluates lutein, zeaxanthin, β-carotene, retinol, and α-tocopherol simultaneously by ultra-high performance liquid chromatography-photodiode array detection. Common saponification temperatures (40-60°C) and concentrations of KOH in water (10-50% KOH wt/vol) were evaluated. Multiple solvents were evaluated for optimal xanthophyll extraction (diethyl ether, dichloromethane, hexane, and tetrahydrofuran) following saponification. The limit of detection and LoQ were defined as 3:1 and 10:1 signal-to-noise ratio, respectively. All experiments were performed in triplicate. The optimal saponification procedure was a concentration of 25% KOH at either 40 or 50°C. Saponified extracts solubilized in solutions containing diethyl ether had greater concentrations of lutein- than hexane- or tetrahydrofuran-based solutions, with peak areas above LoQ values. The solution containing diethyl ether solubilized similar concentrations of retinol, α-tocopherol, and β-carotene when compared with other solutions. The proposed optimized method allows for the simultaneous determination of carotenoids from milk with increased lutein and zeaxanthin sensitivity without sacrificing recovery of retinol, α-tocopherol, and β-carotene. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Bayesian inversion analysis of nonlinear dynamics in surface heterogeneous reactions.

PubMed

Omori, Toshiaki; Kuwatani, Tatsu; Okamoto, Atsushi; Hukushima, Koji

2016-09-01

It is essential to extract nonlinear dynamics from time-series data as an inverse problem in natural sciences. We propose a Bayesian statistical framework for extracting nonlinear dynamics of surface heterogeneous reactions from sparse and noisy observable data. Surface heterogeneous reactions are chemical reactions with conjugation of multiple phases, and they have the intrinsic nonlinearity of their dynamics caused by the effect of surface-area between different phases. We adapt a belief propagation method and an expectation-maximization (EM) algorithm to partial observation problem, in order to simultaneously estimate the time course of hidden variables and the kinetic parameters underlying dynamics. The proposed belief propagation method is performed by using sequential Monte Carlo algorithm in order to estimate nonlinear dynamical system. Using our proposed method, we show that the rate constants of dissolution and precipitation reactions, which are typical examples of surface heterogeneous reactions, as well as the temporal changes of solid reactants and products, were successfully estimated only from the observable temporal changes in the concentration of the dissolved intermediate product.

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors

PubMed Central

Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng

2017-01-01

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model. PMID:28753912

A high-accuracy two-position alignment inertial navigation system for lunar rovers aided by a star sensor with a calibration and positioning function

NASA Astrophysics Data System (ADS)

Lu, Jiazhen; Lei, Chaohua; Yang, Yanqiang; Liu, Ming

2016-12-01

An integrated inertial/celestial navigation system (INS/CNS) has wide applicability in lunar rovers as it provides accurate and autonomous navigational information. Initialization is particularly vital for a INS. This paper proposes a two-position initialization method based on a standard Kalman filter. The difference between the computed star vector and the measured star vector is measured. With the aid of a star sensor and the two positions, the attitudinal and positional errors can be greatly reduced, and the biases of three gyros and accelerometers can also be estimated. The semi-physical simulation results show that the positional and attitudinal errors converge within 0.07″ and 0.1 m, respectively, when the given initial positional error is 1 km and the attitudinal error is 10°. These good results show that the proposed method can accomplish alignment, positioning and calibration functions simultaneously. Thus the proposed two-position initialization method has the potential for application in lunar rover navigation.

Aircraft engine sensor fault diagnostics using an on-line OBEM update method.

PubMed

Liu, Xiaofeng; Xue, Naiyu; Yuan, Ye

2017-01-01

This paper proposed a method to update the on-line health reference baseline of the On-Board Engine Model (OBEM) to maintain the effectiveness of an in-flight aircraft sensor Fault Detection and Isolation (FDI) system, in which a Hybrid Kalman Filter (HKF) was incorporated. Generated from a rapid in-flight engine degradation, a large health condition mismatch between the engine and the OBEM can corrupt the performance of the FDI. Therefore, it is necessary to update the OBEM online when a rapid degradation occurs, but the FDI system will lose estimation accuracy if the estimation and update are running simultaneously. To solve this problem, the health reference baseline for a nonlinear OBEM was updated using the proposed channel controller method. Simulations based on the turbojet engine Linear-Parameter Varying (LPV) model demonstrated the effectiveness of the proposed FDI system in the presence of substantial degradation, and the channel controller can ensure that the update process finishes without interference from a single sensor fault.

Aircraft engine sensor fault diagnostics using an on-line OBEM update method

PubMed Central

Liu, Xiaofeng; Xue, Naiyu; Yuan, Ye

2017-01-01

This paper proposed a method to update the on-line health reference baseline of the On-Board Engine Model (OBEM) to maintain the effectiveness of an in-flight aircraft sensor Fault Detection and Isolation (FDI) system, in which a Hybrid Kalman Filter (HKF) was incorporated. Generated from a rapid in-flight engine degradation, a large health condition mismatch between the engine and the OBEM can corrupt the performance of the FDI. Therefore, it is necessary to update the OBEM online when a rapid degradation occurs, but the FDI system will lose estimation accuracy if the estimation and update are running simultaneously. To solve this problem, the health reference baseline for a nonlinear OBEM was updated using the proposed channel controller method. Simulations based on the turbojet engine Linear-Parameter Varying (LPV) model demonstrated the effectiveness of the proposed FDI system in the presence of substantial degradation, and the channel controller can ensure that the update process finishes without interference from a single sensor fault. PMID:28182692

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors.

PubMed

Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng

2017-07-19

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model.

Ensemble of hybrid genetic algorithm for two-dimensional phase unwrapping

NASA Astrophysics Data System (ADS)

Balakrishnan, D.; Quan, C.; Tay, C. J.

2013-06-01

The phase unwrapping is the final and trickiest step in any phase retrieval technique. Phase unwrapping by artificial intelligence methods (optimization algorithms) such as hybrid genetic algorithm, reverse simulated annealing, particle swarm optimization, minimum cost matching showed better results than conventional phase unwrapping methods. In this paper, Ensemble of hybrid genetic algorithm with parallel populations is proposed to solve the branch-cut phase unwrapping problem. In a single populated hybrid genetic algorithm, the selection, cross-over and mutation operators are applied to obtain new population in every generation. The parameters and choice of operators will affect the performance of the hybrid genetic algorithm. The ensemble of hybrid genetic algorithm will facilitate to have different parameters set and different choice of operators simultaneously. Each population will use different set of parameters and the offspring of each population will compete against the offspring of all other populations, which use different set of parameters. The effectiveness of proposed algorithm is demonstrated by phase unwrapping examples and advantages of the proposed method are discussed.

Long-term effects of user preference-oriented recommendation method on the evolution of online system

NASA Astrophysics Data System (ADS)

Shi, Xiaoyu; Shang, Ming-Sheng; Luo, Xin; Khushnood, Abbas; Li, Jian

2017-02-01

As the explosion growth of Internet economy, recommender system has become an important technology to solve the problem of information overload. However, recommenders are not one-size-fits-all, different recommenders have different virtues, making them be suitable for different users. In this paper, we propose a novel personalized recommender based on user preferences, which allows multiple recommenders to exist in E-commerce system simultaneously. We find that output of a recommender to each user is quite different when using different recommenders, the recommendation accuracy can be significantly improved if each user is assigned with his/her optimal personalized recommender. Furthermore, different from previous works focusing on short-term effects on recommender, we also evaluate the long-term effect of the proposed method by modeling the evolution of mutual feedback between user and online system. Finally, compared with single recommender running on the online system, the proposed method can improve the accuracy of recommendation significantly and get better trade-offs between short- and long-term performances of recommendation.

The Value of Developing a Mixed-Methods Program of Research.

PubMed

Simonovich, Shannon

2017-07-01

This article contributes to the discussion of the value of utilizing mixed methodological approaches to conduct nursing research. To this end, the author of this article proposes creating a mixed-methods program of research over time, where both quantitative and qualitative data are collected and analyzed simultaneously, rather than focusing efforts on designing singular mixed-methods studies. A mixed-methods program of research would allow for the best of both worlds: precision through focus on one method at a time, and the benefits of creating a robust understanding of a phenomenon over the trajectory of one's career through examination from various methodological approaches.

Weierstrass method for quaternionic polynomial root-finding

NASA Astrophysics Data System (ADS)

Falcão, M. Irene; Miranda, Fernando; Severino, Ricardo; Soares, M. Joana

2018-01-01

Quaternions, introduced by Hamilton in 1843 as a generalization of complex numbers, have found, in more recent years, a wealth of applications in a number of different areas which motivated the design of efficient methods for numerically approximating the zeros of quaternionic polynomials. In fact, one can find in the literature recent contributions to this subject based on the use of complex techniques, but numerical methods relying on quaternion arithmetic remain scarce. In this paper we propose a Weierstrass-like method for finding simultaneously {\\sl all} the zeros of unilateral quaternionic polynomials. The convergence analysis and several numerical examples illustrating the performance of the method are also presented.

Successive spectrophotometric resolution as a novel technique for the analysis of ternary mixtures of pharmaceuticals

NASA Astrophysics Data System (ADS)

Lotfy, Hayam M.; Tawakkol, Shereen M.; Fahmy, Nesma M.; Shehata, Mostafa A.

2014-03-01

A novel spectrophotometric technique was developed for the simultaneous determination of ternary mixtures, without prior separation steps. This technique was called successive spectrophotometric resolution technique. The technique was based on either the successive ratio subtraction or successive derivative subtraction. The mathematical explanation of the procedure was illustrated. In order to evaluate the applicability of the methods a model data as well as an experimental data were tested. The results from experimental data related to the simultaneous spectrophotometric determination of lidocaine hydrochloride (LH), calcium dobesilate (CD) and dexamethasone acetate (DA); in the presence of hydroquinone (HQ), the degradation product of calcium dobesilate were discussed. The proposed drugs were determined at their maxima 202 nm, 305 nm, 239 nm and 225 nm for LH, CD, DA and HQ respectively; by successive ratio subtraction coupled with constant multiplication method to obtain the zero order absorption spectra, while by applying successive derivative subtraction they were determined at their first derivative spectra at 210 nm for LH, 320 nm or P292-320 for CD, 256 nm or P225-252 for DA and P220-233 for HQ respectively. The calibration curves were linear over the concentration range of 2-20 μg/mL for both LH and DA, 6-50 μg/mL for CD, and 3-40 μg/mL for HQ. The proposed methods were checked using laboratory-prepared mixtures and were successfully applied for the analysis of pharmaceutical formulation containing the cited drugs with no interference from other dosage form additives. The proposed methods were validated according to the ICH guidelines. The obtained results were statistically compared with those of the official BP methods for LH, DA, and CD, and with the official USP method for HQ; using student t-test, F-test, and one way ANOVA, showing no significant difference with respect to accuracy and precision.

Simultaneous macula detection and optic disc boundary segmentation in retinal fundus images

NASA Astrophysics Data System (ADS)

Girard, Fantin; Kavalec, Conrad; Grenier, Sébastien; Ben Tahar, Houssem; Cheriet, Farida

2016-03-01

The optic disc (OD) and the macula are important structures in automatic diagnosis of most retinal diseases inducing vision defects such as glaucoma, diabetic or hypertensive retinopathy and age-related macular degeneration. We propose a new method to detect simultaneously the macula and the OD boundary. First, the color fundus images are processed to compute several maps highlighting the different anatomical structures such as vessels, the macula and the OD. Then, macula candidates and OD candidates are found simultaneously and independently using seed detectors identified on the corresponding maps. After selecting a set of macula/OD pairs, the top candidates are sent to the OD segmentation method. The segmentation method is based on local K-means applied to color coordinates in polar space followed by a polynomial fitting regularization step. Pair scores are updated, resulting in the final best macula/OD pair. The method was evaluated on two public image databases: ONHSD and MESSIDOR. The results show an overlapping area of 0.84 on ONHSD and 0.90 on MESSIDOR, which is better than recent state of the art methods. Our segmentation method is robust to contrast and illumination problems and outputs the exact boundary of the OD, not just a circular or elliptical model. The macula detection has an accuracy of 94%, which again outperforms other macula detection methods. This shows that combining the OD and macula detections improves the overall accuracy. The computation time for the whole process is 6.4 seconds, which is faster than other methods in the literature.

High-bandwidth and flexible tracking control for precision motion with application to a piezo nanopositioner.

PubMed

Feng, Zhao; Ling, Jie; Ming, Min; Xiao, Xiao-Hui

2017-08-01

For precision motion, high-bandwidth and flexible tracking are the two important issues for significant performance improvement. Iterative learning control (ILC) is an effective feedforward control method only for systems that operate strictly repetitively. Although projection ILC can track varying references, the performance is still limited by the fixed-bandwidth Q-filter, especially for triangular waves tracking commonly used in a piezo nanopositioner. In this paper, a wavelet transform-based linear time-varying (LTV) Q-filter design for projection ILC is proposed to compensate high-frequency errors and improve the ability to tracking varying references simultaneously. The LVT Q-filter is designed based on the modulus maximum of wavelet detail coefficients calculated by wavelet transform to determine the high-frequency locations of each iteration with the advantages of avoiding cross-terms and segmenting manually. The proposed approach was verified on a piezo nanopositioner. Experimental results indicate that the proposed approach can locate the high-frequency regions accurately and achieve the best performance under varying references compared with traditional frequency-domain and projection ILC with a fixed-bandwidth Q-filter, which validates that through implementing the LTV filter on projection ILC, high-bandwidth and flexible tracking can be achieved simultaneously by the proposed approach.

Self-mixing instrument for simultaneous distance and speed measurement

NASA Astrophysics Data System (ADS)

Norgia, Michele; Melchionni, Dario; Pesatori, Alessandro

2017-12-01

A novel instrument based on Self-mixing interferometry is proposed to simultaneously measure absolute distance and velocity. The measurement method is designed for working directly on each kind of surface, in industrial environment, overcoming also problems due to speckle pattern effect. The laser pump current is modulated at quite high frequency (40 kHz) and the estimation of the induced fringes frequency allows an almost instantaneous measurement (measurement time equal to 25 μs). A real time digital elaboration processes the measurement data and discards unreliable measurements. The simultaneous measurement reaches a relative standard deviation of about 4·10-4 in absolute distance, and 5·10-3 in velocity measurement. Three different laser sources are tested and compared. The instrument shows good performances also in harsh environment, for example measuring the movement of an opaque iron tube rotating under a running water flow.

Simultaneous generation of high-efficiency broadband asymmetric anomalous refraction and reflection waves with few-layer anisotropic metasurface

PubMed Central

Li, Zhancheng; Liu, Wenwei; Cheng, Hua; Liu, Jieying; Chen, Shuqi; Tian, Jianguo

2016-01-01

Optical metasurfaces consisting of single-layer nanostructures have immensely promising applications in wavefront control because they can be used to arbitrarily manipulate wave phase, and polarization. However, anomalous refraction and reflection waves have not yet been simultaneously and asymmetrically generated, and the limited efficiency and bandwidth of pre-existing single-layer metasurfaces hinder their practical applications. Here, a few-layer anisotropic metasurface is presented for simultaneously generating high-efficiency broadband asymmetric anomalous refraction and reflection waves. Moreover, the normal transmission and reflection waves are low and the anomalous waves are the predominant ones, which is quite beneficial for practical applications such as beam deflectors. Our work provides an effective method of enhancing the performance of anomalous wave generation, and the asymmetric performance of the proposed metasurface shows endless possibilities in wavefront control for nanophotonics device design and optical communication applications. PMID:27762286

Graphene-multiwall carbon nanotube-gold nanocluster composites modified electrode for the simultaneous determination of ascorbic acid, dopamine, and uric acid.

PubMed

Liu, Xiaofang; Wei, Shaping; Chen, Shihong; Yuan, Dehua; Zhang, Wen

2014-08-01

In this paper, graphene-multiwall carbon nanotube-gold nanocluster (GP-MWCNT-AuNC) composites were synthesized and used as modifier to fabricate a sensor for simultaneous detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA). The electrochemical behavior of the sensor was investigated by electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and differential pulse voltammetry (DPV) techniques. The combination of GP, MWCNTs, and AuNCs endowed the electrode with a large surface area, good catalytic activity, and high selectivity and sensitivity. The linear response range for simultaneous detection of AA, DA, and UA at the sensor were 120-1,701, 2-213, and 0.7-88.3 μM, correspondingly, and the detection limits were 40, 0.67, and 0.23 μM (S/N=3), respectively. The proposed method offers a promise for simple, rapid, selective, and cost-effective analysis of small biomolecules.

Multiple delivery cesium oven system for negative ion sources

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

Bansal, G.; Bhartiya, S.; Pandya, K.

2012-02-15

Distribution of cesium in large negative ion beam sources to be operational in ITER, is presently based on the use of three or more cesium ovens, which operate simultaneously and are controlled remotely. However, use of multiple Cs ovens simultaneously is likely to pose difficulties in operation and maintenance of the ovens. An alternate method of Cs delivery, based on a single oven distribution system is proposed as one which could reduce the need of simultaneous operation of many ovens. A proof of principle experiment verifying the concept of a multinozzle distributor based Cs oven has been carried out atmore » Institute for Plasma Research. It is also observed that the Cs flux is not controlled by Cs reservoir temperature after few hours of operation but by the temperature of the distributor which starts behaving as a Cs reservoir.« less

Simultaneous measurement of temperature and strain using a phase-shifted fiber Bragg grating inscribed by femtosecond laser

NASA Astrophysics Data System (ADS)

Jiang, Yajun; Liu, Chi; Li, Dong; Yang, Dexing; Zhao, Jianlin

2018-04-01

A novel method for simultaneous measurement of temperature and strain using a single phase-shifted fiber Bragg grating (PS-FBG) is proposed. The PS-FBG is produced by exposing the fusion-spliced fiber with a femtosecond laser and uniform phase mask. Due to the non-uniform structure and strain distribution in the fusion-spliced region, the phase-shift changes with different responses during increases to the temperature and strain; by measuring the central wavelengths and the loss difference of two transmission dips, temperature and strain can be determined simultaneously. The resolutions of this particular sensor in measuring temperature and strain are estimated to be  ±1.5 °C and  ±12.2 µɛ in a range from  -50 °C to 150 °C and from 0 µɛ to 2070 µɛ.

Improving accuracy of simultaneously reconstructed activity and attenuation maps using deep learning.

PubMed

Hwang, Donghwi; Kim, Kyeong Yun; Kang, Seung Kwan; Seo, Seongho; Paeng, Jin Chul; Lee, Dong Soo; Lee, Jae Sung

2018-02-15

Simultaneous reconstruction of activity and attenuation using the maximum likelihood reconstruction of activity and attenuation (MLAA) augmented by time-of-flight (TOF) information is a promising method for positron emission tomography (PET) attenuation correction. However, it still suffers from several problems, including crosstalk artifacts, slow convergence speed, and noisy attenuation maps (μ-maps). In this work, we developed deep convolutional neural networks (CNNs) to overcome these MLAA limitations, and we verified their feasibility using a clinical brain PET data set. Methods: We applied the proposed method to one of the most challenging PET cases for simultaneous image reconstruction ( 18 F-FP-CIT PET scans with highly specific binding to striatum of the brain). Three different CNN architectures (convolutional autoencoder (CAE), U-net, hybrid of CAE and U-net) were designed and trained to learn x-ray computed tomography (CT) derived μ-map (μ-CT) from the MLAA-generated activity distribution and μ-map (μ-MLAA). PET/CT data of 40 patients with suspected Parkinson's disease were employed for five-fold cross-validation. For the training of CNNs, 800,000 transverse PET slices and CTs augmented from 32 patient data sets were used. The similarity to μ-CT of the CNN-generated μ-maps (μ-CAE, μ-Unet, and μ-Hybrid) and μ-MLAA was compared using Dice similarity coefficients. In addition, we compared the activity concentration of specific (striatum) and non-specific binding regions (cerebellum and occipital cortex) and the binding ratios in the striatum in the PET activity images reconstructed using those μ-maps. Results: The CNNs generated less noisy and more uniform μ-maps than original μ-MLAA. Moreover, the air cavities and bones were better resolved in the proposed CNN outputs. In addition, the proposed deep learning approach was useful for mitigating the crosstalk problem in the MLAA reconstruction. The hybrid network of CAE and U-net yielded the most similar μ-maps to μ-CT (Dice similarity coefficient in the whole head = 0.79 in the bone and 0.72 in air cavities), resulting in only approximately 5% errors in activity and biding ratio quantification. Conclusion: The proposed deep learning approach is promising for accurate attenuation correction of activity distribution in TOF PET systems. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Three-dimensional image acquisition and reconstruction system on a mobile device based on computer-generated integral imaging.

PubMed

Erdenebat, Munkh-Uchral; Kim, Byeong-Jun; Piao, Yan-Ling; Park, Seo-Yeon; Kwon, Ki-Chul; Piao, Mei-Lan; Yoo, Kwan-Hee; Kim, Nam

2017-10-01

A mobile three-dimensional image acquisition and reconstruction system using a computer-generated integral imaging technique is proposed. A depth camera connected to the mobile device acquires the color and depth data of a real object simultaneously, and an elemental image array is generated based on the original three-dimensional information for the object, with lens array specifications input into the mobile device. The three-dimensional visualization of the real object is reconstructed on the mobile display through optical or digital reconstruction methods. The proposed system is implemented successfully and the experimental results certify that the system is an effective and interesting method of displaying real three-dimensional content on a mobile device.

New method of control of tooth whitening

NASA Astrophysics Data System (ADS)

Angelov, I.; Mantareva, V.; Gisbrecht, A.; Valkanov, S.; Uzunov, Tz.

2010-10-01

New methods of control of tooth bleaching stages through simultaneous measurements of a reflected light and a fluorescence signal are proposed. It is shown that the bleaching process leads to significant changes in the intensity of a scattered signal and also in the shape and intensity of the fluorescence spectra. Experimental data illustrate that the bleaching process causes essential changes in the teeth discoloration in short time as 8-10 min from the beginning of the application procedure. The continuation of the treatment is not necessary moreover the probability of the enamel destroy increases considerably. The proposed optical back control of tooth surface is a base for development of a practical set up to control the duration of the bleaching procedure.

Efficient OCT Image Enhancement Based on Collaborative Shock Filtering

PubMed Central

2018-01-01

Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and then the denoised image is sharpened by a shock-type filtering for edge and detail enhancement. For dim OCT images, in order to improve image contrast for the detection of tiny lesions, a gamma transformation is first used to enhance the images within proper gray levels. The proposed method integrating image smoothing and sharpening simultaneously obtains better visual results in experiments. PMID:29599954

Efficient OCT Image Enhancement Based on Collaborative Shock Filtering.

PubMed

Liu, Guohua; Wang, Ziyu; Mu, Guoying; Li, Peijin

2018-01-01

Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and then the denoised image is sharpened by a shock-type filtering for edge and detail enhancement. For dim OCT images, in order to improve image contrast for the detection of tiny lesions, a gamma transformation is first used to enhance the images within proper gray levels. The proposed method integrating image smoothing and sharpening simultaneously obtains better visual results in experiments.

High-fidelity cluster state generation for ultracold atoms in an optical lattice.

PubMed

Inaba, Kensuke; Tokunaga, Yuuki; Tamaki, Kiyoshi; Igeta, Kazuhiro; Yamashita, Makoto

2014-03-21

We propose a method for generating high-fidelity multipartite spin entanglement of ultracold atoms in an optical lattice in a short operation time with a scalable manner, which is suitable for measurement-based quantum computation. To perform the desired operations based on the perturbative spin-spin interactions, we propose to actively utilize the extra degrees of freedom (DOFs) usually neglected in the perturbative treatment but included in the Hubbard Hamiltonian of atoms, such as, (pseudo-)charge and orbital DOFs. Our method simultaneously achieves high fidelity, short operation time, and scalability by overcoming the following fundamental problem: enhancing the interaction strength for shortening the operation time breaks the perturbative condition of the interaction and inevitably induces unwanted correlations among the spin and extra DOFs.

A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women.

PubMed

Levman, Jacob E D; Gallego-Ortiz, Cristina; Warner, Ellen; Causer, Petrina; Martel, Anne L

2016-02-01

Magnetic resonance imaging (MRI)-enabled cancer screening has been shown to be a highly sensitive method for the early detection of breast cancer. Computer-aided detection systems have the potential to improve the screening process by standardizing radiologists to a high level of diagnostic accuracy. This retrospective study was approved by the institutional review board of Sunnybrook Health Sciences Centre. This study compares the performance of a proposed method for computer-aided detection (based on the second-order spatial derivative of the relative signal intensity) with the signal enhancement ratio (SER) on MRI-based breast screening examinations. Comparison is performed using receiver operating characteristic (ROC) curve analysis as well as free-response receiver operating characteristic (FROC) curve analysis. A modified computer-aided detection system combining the proposed approach with the SER method is also presented. The proposed method provides improvements in the rates of false positive markings over the SER method in the detection of breast cancer (as assessed by FROC analysis). The modified computer-aided detection system that incorporates both the proposed method and the SER method yields ROC results equal to that produced by SER while simultaneously providing improvements over the SER method in terms of false positives per noncancerous exam. The proposed method for identifying malignancies outperforms the SER method in terms of false positives on a challenging dataset containing many small lesions and may play a useful role in breast cancer screening by MRI as part of a computer-aided detection system.

Information hiding based on double random-phase encoding and public-key cryptography.

PubMed

Sheng, Yuan; Xin, Zhou; Alam, Mohammed S; Xi, Lu; Xiao-Feng, Li

2009-03-02

A novel information hiding method based on double random-phase encoding (DRPE) and Rivest-Shamir-Adleman (RSA) public-key cryptosystem is proposed. In the proposed technique, the inherent diffusion property of DRPE is cleverly utilized to make up the diffusion insufficiency of RSA public-key cryptography, while the RSA cryptosystem is utilized for simultaneous transmission of the cipher text and the two phase-masks, which is not possible under the DRPE technique. This technique combines the complementary advantages of the DPRE and RSA encryption techniques and brings security and convenience for efficient information transmission. Extensive numerical simulation results are presented to verify the performance of the proposed technique.

Joint image encryption and compression scheme based on IWT and SPIHT

NASA Astrophysics Data System (ADS)

Zhang, Miao; Tong, Xiaojun

2017-03-01

A joint lossless image encryption and compression scheme based on integer wavelet transform (IWT) and set partitioning in hierarchical trees (SPIHT) is proposed to achieve lossless image encryption and compression simultaneously. Making use of the properties of IWT and SPIHT, encryption and compression are combined. Moreover, the proposed secure set partitioning in hierarchical trees (SSPIHT) via the addition of encryption in the SPIHT coding process has no effect on compression performance. A hyper-chaotic system, nonlinear inverse operation, Secure Hash Algorithm-256(SHA-256), and plaintext-based keystream are all used to enhance the security. The test results indicate that the proposed methods have high security and good lossless compression performance.

New clinical validation method for automated sphygmomanometer: a proposal by Japan ISO-WG for sphygmomanometer standard.

PubMed

Shirasaki, Osamu; Asou, Yosuke; Takahashi, Yukio

2007-12-01

Owing to fast or stepwise cuff deflation, or measuring at places other than the upper arm, the clinical accuracy of most recent automated sphygmomanometers (auto-BPMs) cannot be validated by one-arm simultaneous comparison, which would be the only accurate validation method based on auscultation. Two main alternative methods are provided by current standards, that is, two-arm simultaneous comparison (method 1) and one-arm sequential comparison (method 2); however, the accuracy of these validation methods might not be sufficient to compensate for the suspicious accuracy in lateral blood pressure (BP) differences (LD) and/or BP variations (BPV) between the device and reference readings. Thus, the Japan ISO-WG for sphygmomanometer standards has been studying a new method that might improve validation accuracy (method 3). The purpose of this study is to determine the appropriateness of method 3 by comparing immunity to LD and BPV with those of the current validation methods (methods 1 and 2). The validation accuracy of the above three methods was assessed in human participants [N=120, 45+/-15.3 years (mean+/-SD)]. An oscillometric automated monitor, Omron HEM-762, was used as the tested device. When compared with the others, methods 1 and 3 showed a smaller intra-individual standard deviation of device error (SD1), suggesting their higher reproducibility of validation. The SD1 by method 2 (P=0.004) significantly correlated with the participant's BP, supporting our hypothesis that the increased SD of device error by method 2 is at least partially caused by essential BPV. Method 3 showed a significantly (P=0.0044) smaller interparticipant SD of device error (SD2), suggesting its higher interparticipant consistency of validation. Among the methods of validation of the clinical accuracy of auto-BPMs, method 3, which showed the highest reproducibility and highest interparticipant consistency, can be proposed as being the most appropriate.

HPTLC Method for the Determination of Paracetamol, Pseudoephedrine and Loratidine in Tablets and Human Plasma

PubMed Central

Farid, Nehal Fayek; Abdelaleem, Eglal A.

2016-01-01

A sensitive, accurate and selective high performance thin layer chromatography (HPTLC) method was developed and validated for the simultaneous determination of paracetamol (PAR), its toxic impurity 4-aminophenol (4-AP), pseudoephedrine HCl (PSH) and loratidine (LOR). The proposed chromatographic method has been developed using HPTLC aluminum plates precoated with silica gel 60 F254 using acetone–hexane–ammonia (4:5:0.1, by volume) as a developing system followed by densitometric measurement at 254 nm for PAR, 4-AP and LOR, while PSH was scanned at 208 nm. System suitability testing parameters were calculated to ascertain the quality performance of the developed chromatographic method. The method was validated with respect to USP guidelines regarding accuracy, precision and specificity. The method was successfully applied for the determination of PAR, PSH and LOR in ATSHI® tablets. The three drugs were also determined in plasma by applying the proposed method in the ranges of 0.5–6 µg/band, 1.6–12 µg/band and 0.4–2 µg/band for PAR, PSH and LOR, respectively. The results obtained by the proposed method were compared with those obtained by a reported HPLC method, and there was no significance difference between both methods regarding accuracy and precision. PMID:26762956

Robust Point Set Matching for Partial Face Recognition.

PubMed

Weng, Renliang; Lu, Jiwen; Tan, Yap-Peng

2016-03-01

Over the past three decades, a number of face recognition methods have been proposed in computer vision, and most of them use holistic face images for person identification. In many real-world scenarios especially some unconstrained environments, human faces might be occluded by other objects, and it is difficult to obtain fully holistic face images for recognition. To address this, we propose a new partial face recognition approach to recognize persons of interest from their partial faces. Given a pair of gallery image and probe face patch, we first detect keypoints and extract their local textural features. Then, we propose a robust point set matching method to discriminatively match these two extracted local feature sets, where both the textural information and geometrical information of local features are explicitly used for matching simultaneously. Finally, the similarity of two faces is converted as the distance between these two aligned feature sets. Experimental results on four public face data sets show the effectiveness of the proposed approach.

A Novel Riemannian Metric Based on Riemannian Structure and Scaling Information for Fixed Low-Rank Matrix Completion.

PubMed

Mao, Shasha; Xiong, Lin; Jiao, Licheng; Feng, Tian; Yeung, Sai-Kit

2017-05-01

Riemannian optimization has been widely used to deal with the fixed low-rank matrix completion problem, and Riemannian metric is a crucial factor of obtaining the search direction in Riemannian optimization. This paper proposes a new Riemannian metric via simultaneously considering the Riemannian geometry structure and the scaling information, which is smoothly varying and invariant along the equivalence class. The proposed metric can make a tradeoff between the Riemannian geometry structure and the scaling information effectively. Essentially, it can be viewed as a generalization of some existing metrics. Based on the proposed Riemanian metric, we also design a Riemannian nonlinear conjugate gradient algorithm, which can efficiently solve the fixed low-rank matrix completion problem. By experimenting on the fixed low-rank matrix completion, collaborative filtering, and image and video recovery, it illustrates that the proposed method is superior to the state-of-the-art methods on the convergence efficiency and the numerical performance.

MRI intensity nonuniformity correction using simultaneously spatial and gray-level histogram information.

PubMed

Milles, Julien; Zhu, Yue Min; Gimenez, Gérard; Guttmann, Charles R G; Magnin, Isabelle E

2007-03-01

A novel approach for correcting intensity nonuniformity in magnetic resonance imaging (MRI) is presented. This approach is based on the simultaneous use of spatial and gray-level histogram information. Spatial information about intensity nonuniformity is obtained using cubic B-spline smoothing. Gray-level histogram information of the image corrupted by intensity nonuniformity is exploited from a frequential point of view. The proposed correction method is illustrated using both physical phantom and human brain images. The results are consistent with theoretical prediction, and demonstrate a new way of dealing with intensity nonuniformity problems. They are all the more significant as the ground truth on intensity nonuniformity is unknown in clinical images.

Monte Carlo based method for fluorescence tomographic imaging with lifetime multiplexing using time gates

PubMed Central

Chen, Jin; Venugopal, Vivek; Intes, Xavier

2011-01-01

Time-resolved fluorescence optical tomography allows 3-dimensional localization of multiple fluorophores based on lifetime contrast while providing a unique data set for improved resolution. However, to employ the full fluorescence time measurements, a light propagation model that accurately simulates weakly diffused and multiple scattered photons is required. In this article, we derive a computationally efficient Monte Carlo based method to compute time-gated fluorescence Jacobians for the simultaneous imaging of two fluorophores with lifetime contrast. The Monte Carlo based formulation is validated on a synthetic murine model simulating the uptake in the kidneys of two distinct fluorophores with lifetime contrast. Experimentally, the method is validated using capillaries filled with 2.5nmol of ICG and IRDye™800CW respectively embedded in a diffuse media mimicking the average optical properties of mice. Combining multiple time gates in one inverse problem allows the simultaneous reconstruction of multiple fluorophores with increased resolution and minimal crosstalk using the proposed formulation. PMID:21483610

Simultaneous determination of phenylephrine hydrochloride, guaifenesin, and chlorpheniramine maleate in cough syrup by gradient liquid chromatography.

PubMed

Amer, Sawsan M; Abbas, Samah S; Shehata, Mostafa A; Ali, Nahed M

2008-01-01

A simple and reliable high-performance liquid chromatographic method was developed for the simultaneous determination of mixture of phenylephrine hydrochloride (PHENYL), guaifenesin (GUAIF), and chlorpheniramine maleate (CHLO) either in pure form or in the presence of methylparaben and propylparaben in a commercial cough syrup dosage form. Separation was achieved on a C8 column using 0.005 M heptane sulfonic acid sodium salt (pH 3.4 +/- 0.1) and acetonitrile as a mobile phase by gradient elution at different flow rates, and detection was done spectrophotometrically at 210 nm. A linear relationship in the range of 30-180, 120-1800, and 10-60 microg/mL was obtained for PHENYL, GUAIF, and CHLO, respectively. The results were statistically analyzed and compared with those obtained by applying the British Pharmacopoeia (2002) method and showed that the proposed method is precise, accurate, and can be easily applied for the determination of the drugs under investigation in pure form and in cough syrup formulations.

Simultaneous determination of 20 pharmacologically active substances in cow's milk, goat's milk, and human breast milk by gas chromatography-mass spectrometry.

PubMed

Azzouz, Abdelmonaim; Jurado-Sánchez, Beatriz; Souhail, Badredine; Ballesteros, Evaristo

2011-05-11

This paper reports a systematic approach to the development of a method that combines continuous solid-phase extraction and gas chromatography-mass spectrometry for the simultaneous determination of 20 pharmacologically active substances including antibacterials (chloramphenicol, florfenicol, pyrimethamine, thiamphenicol), nonsteroideal anti-inflammatories (diclofenac, flunixin, ibuprofen, ketoprofen, naproxen, mefenamic acid, niflumic acid, phenylbutazone), antiseptic (triclosan), antiepileptic (carbamazepine), lipid regulator (clofibric acid), β-blockers (metoprolol, propranolol), and hormones (17α-ethinylestradiol, estrone, 17β-estradiol) in milk samples. The sample preparation procedure involves deproteination of the milk, followed by sample enrichment and cleanup by continuous solid-phase extraction. The proposed method provides a linear response over the range of 0.6-5000 ng/kg and features limits of detection from 0.2 to 1.2 ng/kg depending on the particular analyte. The method was successfully applied to the determination of pharmacologically active substance residues in food samples including whole, raw, half-skim, skim, and powdered milk from different sources (cow, goat, and human breast).

Simultaneous planning of the project scheduling and material procurement problem under the presence of multiple suppliers

NASA Astrophysics Data System (ADS)

Tabrizi, Babak H.; Ghaderi, Seyed Farid

2016-09-01

Simultaneous planning of project scheduling and material procurement can improve the project execution costs. Hence, the issue has been addressed here by a mixed-integer programming model. The proposed model facilitates the procurement decisions by accounting for a number of suppliers offering a distinctive discount formula from which to purchase the required materials. It is aimed at developing schedules with the best net present value regarding the obtained benefit and costs of the project execution. A genetic algorithm is applied to deal with the problem, in addition to a modified version equipped with a variable neighbourhood search. The underlying factors of the solution methods are calibrated by the Taguchi method to obtain robust solutions. The performance of the aforementioned methods is compared for different problem sizes, in which the utilized local search proved efficient. Finally, a sensitivity analysis is carried out to check the effect of inflation on the objective function value.

Simultaneous reconstruction of 3D refractive index, temperature, and intensity distribution of combustion flame by double computed tomography technologies based on spatial phase-shifting method

NASA Astrophysics Data System (ADS)

Guo, Zhenyan; Song, Yang; Yuan, Qun; Wulan, Tuya; Chen, Lei

2017-06-01

In this paper, a transient multi-parameter three-dimensional (3D) reconstruction method is proposed to diagnose and visualize a combustion flow field. Emission and transmission tomography based on spatial phase-shifted technology are combined to reconstruct, simultaneously, the various physical parameter distributions of a propane flame. Two cameras triggered by the internal trigger mode capture the projection information of the emission and moiré tomography, respectively. A two-step spatial phase-shifting method is applied to extract the phase distribution in the moiré fringes. By using the filtered back-projection algorithm, we reconstruct the 3D refractive-index distribution of the combustion flow field. Finally, the 3D temperature distribution of the flame is obtained from the refractive index distribution using the Gladstone-Dale equation. Meanwhile, the 3D intensity distribution is reconstructed based on the radiation projections from the emission tomography. Therefore, the structure and edge information of the propane flame are well visualized.

Simultaneous production and co-mixing of microparticles of nevirapine with excipients by supercritical antisolvent method for dissolution enhancement.

PubMed

Sanganwar, Ganesh P; Sathigari, Sateeshkumar; Babu, R Jayachandra; Gupta, Ram B

2010-01-31

Microparticles of a poorly water-soluble model drug, nevirapine (NEV) were prepared by supercritical antisolvent (SAS) method and simultaneously deposited on the surface of excipients such as lactose and microcrystalline cellulose in a single step to reduce drug-drug particle aggregation. In the proposed method, termed supercritical antisolvent-drug excipient mixing (SAS-DEM), drug particles were precipitated in supercritical CO(2) vessel containing excipient particles in suspended state. Drug/excipient mixtures were characterized for surface morphology, crystallinity, drug-excipient physico-chemical interactions, and molecular state of drug. In addition, the drug content uniformity and dissolution rate were determined. A highly ordered NEV-excipient mixture was produced. The SAS-DEM treatment was effective in overcoming drug-drug particle aggregation and did not affect the crystallinity or physico-chemical properties of NEV. The produced drug/excipient mixture has a significantly faster dissolution rate as compared to SAS drug microparticles alone or when physically mixed with the excipients. Copyright 2009 Elsevier B.V. All rights reserved.

Preparation of a novel sorptive stir bar based on vinylpyrrolidone-ethylene glycol dimethacrylate monolithic polymer for the simultaneous extraction of diazepam and nordazepam from human plasma.

PubMed

Torabizadeh, Mahsa; Talebpour, Zahra; Adib, Nuoshin; Aboul-Enein, Hassan Y

2016-04-01

A new monolithic coating based on vinylpyrrolidone-ethylene glycol dimethacrylate polymer was introduced for stir bar sorptive extraction. The polymerization step was performed using different contents of monomer, cross-linker and porogenic solvent, and the best formulation was selected. The quality of the prepared vinylpyrrolidone-ethylene glycol dimethacrylate stir bars was satisfactory, demonstrating good repeatability within batch (relative standard deviation < 3.5%) and acceptable reproducibility between batches (relative standard deviation < 6.0%). The prepared stir bar was utilized in combination with ultrasound-assisted liquid desorption, followed by high-performance liquid chromatography with ultraviolet detection for the simultaneous determination of diazepam and nordazepam in human plasma samples. To optimize the extraction step, a three-level, four-factor, three-block Box-Behnken design was applied. Under the optimum conditions, the analytical performance of the proposed method displayed excellent linear dynamic ranges for diazepam (36-1200 ng/mL) and nordazepam (25-1200 ng/mL), with correlation coefficients of 0.9986 and 0.9968 and detection limits of 12 and 10 ng/mL, respectively. The intra- and interday recovery ranged from 93 to 106%, and the relative standard deviations were less than 6%. Finally, the proposed method was successfully applied to the analysis of diazepam and nordazepam at their therapeutic levels in human plasma. The novelty of this study is the improved polarity of the stir bar coating and its application for the simultaneous extraction of diazepam and its active metabolite, nordazepam in human plasma sample. The method was more rapid than previously reported stir bar sorptive extraction techniques based on monolithic coatings, and exhibited lower detection limits in comparison with similar methods for the determination of diazepam and nordazepam in biological fluids. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multi-tasking arbitration and behaviour design for human-interactive robots

NASA Astrophysics Data System (ADS)

Kobayashi, Yuichi; Onishi, Masaki; Hosoe, Shigeyuki; Luo, Zhiwei

2013-05-01

Robots that interact with humans in household environments are required to handle multiple real-time tasks simultaneously, such as carrying objects, collision avoidance and conversation with human. This article presents a design framework for the control and recognition processes to meet these requirements taking into account stochastic human behaviour. The proposed design method first introduces a Petri net for synchronisation of multiple tasks. The Petri net formulation is converted to Markov decision processes and processed in an optimal control framework. Three tasks (safety confirmation, object conveyance and conversation) interact and are expressed by the Petri net. Using the proposed framework, tasks that normally tend to be designed by integrating many if-then rules can be designed in a systematic manner in a state estimation and optimisation framework from the viewpoint of the shortest time optimal control. The proposed arbitration method was verified by simulations and experiments using RI-MAN, which was developed for interactive tasks with humans.

Linear and nonlinear variable selection in competing risks data.

PubMed

Ren, Xiaowei; Li, Shanshan; Shen, Changyu; Yu, Zhangsheng

2018-06-15

Subdistribution hazard model for competing risks data has been applied extensively in clinical researches. Variable selection methods of linear effects for competing risks data have been studied in the past decade. There is no existing work on selection of potential nonlinear effects for subdistribution hazard model. We propose a two-stage procedure to select the linear and nonlinear covariate(s) simultaneously and estimate the selected covariate effect(s). We use spectral decomposition approach to distinguish the linear and nonlinear parts of each covariate and adaptive LASSO to select each of the 2 components. Extensive numerical studies are conducted to demonstrate that the proposed procedure can achieve good selection accuracy in the first stage and small estimation biases in the second stage. The proposed method is applied to analyze a cardiovascular disease data set with competing death causes. Copyright © 2018 John Wiley & Sons, Ltd.

A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network

PubMed Central

Qu, Jianfeng; Chai, Yi; Yang, Simon X.

2009-01-01

A wireless e-nose network system is developed for the special purpose of monitoring odorant gases and accurately estimating odor strength in and around livestock farms. This system is to simultaneously acquire accurate odor strength values remotely at various locations, where each node is an e-nose that includes four metal-oxide semiconductor (MOS) gas sensors. A modified Kalman filtering technique is proposed for collecting raw data and de-noising based on the output noise characteristics of those gas sensors. The measurement noise variance is obtained in real time by data analysis using the proposed slip windows average method. The optimal system noise variance of the filter is obtained by using the experiments data. The Kalman filter theory on how to acquire MOS gas sensors data is discussed. Simulation results demonstrate that the proposed method can adjust the Kalman filter parameters and significantly reduce the noise from the gas sensors. PMID:22399946

Depth detection in interactive projection system based on one-shot black-and-white stripe pattern.

PubMed

Zhou, Qian; Qiao, Xiaorui; Ni, Kai; Li, Xinghui; Wang, Xiaohao

2017-03-06

A novel method enabling estimation of not only the screen surface as the conventional one, but the depth information from two-dimensional coordinates in an interactive projection system was proposed in this research. In this method, a one-shot black-and-white stripe pattern from a projector is projected on a screen plane, where the deformed pattern is captured by a charge-coupled device camera. An algorithm based on object/shadow simultaneous detection is proposed for fulfillment of the correspondence. The depth information of the object is then calculated using the triangulation principle. This technology provides a more direct feeling of virtual interaction in three dimensions without using auxiliary equipment or a special screen as interaction proxies. Simulation and experiments are carried out and the results verified the effectiveness of this method in depth detection.

Uniformity Masks Design Method Based on the Shadow Matrix for Coating Materials with Different Condensation Characteristics

PubMed Central

2013-01-01

An intuitionistic method is proposed to design shadow masks to achieve thickness profile control for evaporation coating processes. The proposed method is based on the concept of the shadow matrix, which is a matrix that contains coefficients that build quantitive relations between shape parameters of masks and shadow quantities of substrate directly. By using the shadow matrix, shape parameters of shadow masks could be derived simply by solving a matrix equation. Verification experiments were performed on a special case where coating materials have different condensation characteristics. By using the designed mask pair with complementary shapes, thickness uniformities of better than 98% are demonstrated for MgF2 (m = 1) and LaF3 (m = 0.5) simultaneously on a 280 mm diameter spherical substrate with the radius curvature of 200 mm. PMID:24227996

Simultaneous determination of thirteen flavonoids from Xiaobuxin-Tang extract using high-performance liquid chromatography coupled with electrospray ionization mass spectrometry.

PubMed

Cen, Meifeng; Ruan, Jinxiu; Huang, Lihua; Zhang, Zhenqing; Yu, Nengjiang; Zhang, Youzhi; Cheng, Xuange; Xiong, Xiaohong; Wang, Guixiang; Zang, Linquan; Wang, Sujun

2015-11-10

A simple and reliable high performance liquid chromatography coupled with electrospray ionization mass spectrometry (HPLC-ESI-MS) analysis method was established to simultaneously determine thirteen flavonoids of Xiaobuxing-Tang in intestine perfusate, namely onpordin, 3'-O-methylorobol, glycitein, patuletin, genistein, luteolin, quercetin, nepitrin, quercimeritrin, daidzin, patulitrin, quercetagitrin and 3-glucosylisorhamnetin. Detection was performed on a quadrupole mass spectrometer equipped with an electrospray ionization (ESI) source operating in negative ionization mode. Negative ion ESI was used to form deprotonated molecules at m/z 315 for onpordin, m/z 299 for 3'-O-methylorobol, m/z 283 for glycitein, m/z 331 for patuletin, m/z 269 for genistein, m/z 285 for luteolin, m/z 301 for quercetin, m/z 477 for nepitrin, m/z 463 for quercimeritrin, m/z 461 for daidzin, m/z 493 for patulitrin, m/z 479 for quercetagitrin, m/z 477 for 3-glucosylisorhamnetin and m/z 609.2 for rutin. The linearity, sensitivity, selectivity, repeatability, accuracy, precision, recovery and matrix effect of the assay were evaluated. The proposed method was successfully applied to simultaneous determination of these thirteen flavonoids, and using this method, the intestinal absorption profiles of thirteen flavonoids were preliminarily predicted. Copyright © 2015 Elsevier B.V. All rights reserved.

Simultaneous reduction and nitrogen functionalization of graphene oxide using lemon for metal-free oxygen reduction reaction

NASA Astrophysics Data System (ADS)

Begum, Halima; Ahmed, Mohammad Shamsuddin; Cho, Sung; Jeon, Seungwon

2017-12-01

Inspire by the vision of finding a simple and green method for simultaneous reduction and nitrogen (N)-functionalization of graphene oxide (GO), a N-rich reduced graphene oxide (rGO) has been synthesized through a facile and ecofriendly hydrothermal strategy while most of the existing methods are involving with multiple steps and highly toxic reducing agents that are harmful to human health and environment. In this paper, the simultaneous reduction and N-functionalization of GO using as available lemon juice (denoted as Lem-rGO) for metal-free electrocatalysis towards oxygen reduction reaction (ORR) is described. The proposed method is based on the reduction of GO using of the reducing and the N-precursor capability of ascorbic acid and citric acid as well as the nitrogenous compounds, respectively, that containing in lemon juice. The resultant Lem-rGO has higher reduction degree, higher specific surface area and better crystalline nature with N-incorporation than that of well investigated ascorbic acid and citric acid treated rGO. As a result, it shows better ORR electrocatalytic activity in respect to the improved onset potential, electron transfer rate and kinetics than those typical rGO catalysts. Moreover, it shows a significant tolerance to the anodic fuels and durability than the Pt/C during ORR.

Sequential injection system for simultaneous determination of sucrose and phosphate in cola drinks using paired emitter-detector diode sensor.

PubMed

Saetear, Phoonthawee; Khamtau, Kittiwut; Ratanawimarnwong, Nuanlaor; Sereenonchai, Kamonthip; Nacapricha, Duangjai

2013-10-15

This work presents the simultaneous determination of sucrose and phosphate by using sequential injection (SI) system with a low cost paired emitter-detector diode (PEDD) light sensor. The PEDD uses two 890 nm LEDs. Measurement of sucrose in Brix unit was carried out based on the detection of light refraction occurring at the liquid interface (the schlieren effect) between the sucrose solution and water. Phosphate was measured from the formation of calcium phosphate with turbidimetric detection. With careful design of the loading sequence and volume (sample--precipitating reagent--sample), simultaneous detection of sucrose and phosphate was accomplished with the single PEDD detector. At the optimized condition, linear calibrations from 1 to 7 Brix sucrose and from 50 to 200mg PO4(3-)L(-1) were obtained. Good precision at lower than 2% RSD (n=10) for both analytes with satisfactory throughput of 21 injections h(-1) was achieved. The method was successfully applied for the determination of sucrose and phosphate in cola drinks. The proposed method is readily applicable for automation and is found to be an alternative method to conventional procedures for on-line quality control process in cola drink industry. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Development and validation of an HPLC method for simultaneous determination of trimethoprim and sulfamethoxazole in human plasma.

PubMed

Sayar, Esin; Sahin, Selma; Cevheroglu, Semsettin; Hincal, A Atilla

2010-09-01

The combination of trimethoprim (TMP) and sulfamethoxazole (SMX) is used in the treatment of many common infections such as urinary, respiratory and gastrointestinal tract infections. The aim of this study was to determine TMP and SMX simultaneously in human plasma samples by high performance liquid chromatography (HPLC) using antipyrine as the internal standard. Separation of the compounds was achieved on a reverse-phase C8 column packed with 5 microm dimethyl octadecylsilyl bonded amorphous silica (4.6 mm x 250 mm) column using a mobile phase consisted of potassium hydrogen phosphate, acetonitrile, methanol and water adjusted to pH 6.2. The mobile phase was delivered at a flow rate of 1 mL min- and the effluent was monitored using Max plot technique at 25 derees C. Retention times were 5 min for TMP, 7 min for antipyrine and 9 min for SMX. Quantitation limits were 10 ng mL(-1) for TMP and 50 ng mL(-1) for SMX. Our findings indicated that the developed HPLC method was precise, accurate, specific and sensitive for simultaneous determination of TMP and SMX. Proposed HPLC method was successfully applied for the analysis of TMP and SMX in human plasma after oral administration of a co-trimoxazole tablet to human volunteers.