Adaptive noise canceling of electrocardiogram artifacts in single channel electroencephalogram.

PubMed

Cho, Sung Pil; Song, Mi Hye; Park, Young Cheol; Choi, Ho Seon; Lee, Kyoung Joung

2007-01-01

A new method for estimating and eliminating electrocardiogram (ECG) artifacts from single channel scalp electroencephalogram (EEG) is proposed. The proposed method consists of emphasis of QRS complex from EEG using least squares acceleration (LSA) filter, generation of synchronized pulse with R-peak and ECG artifacts estimation and elimination using adaptive filter. The performance of the proposed method was evaluated using simulated and real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, which are independent component analysis (ICA) and ensemble average (EA) method. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifacts from single channel EEG and simple to use for ambulatory/portable EEG monitoring system.

Identification of Successive ``Unobservable'' Cyber Data Attacks in Power Systems Through Matrix Decomposition

NASA Astrophysics Data System (ADS)

Gao, Pengzhi; Wang, Meng; Chow, Joe H.; Ghiocel, Scott G.; Fardanesh, Bruce; Stefopoulos, George; Razanousky, Michael P.

2016-11-01

This paper presents a new framework of identifying a series of cyber data attacks on power system synchrophasor measurements. We focus on detecting "unobservable" cyber data attacks that cannot be detected by any existing method that purely relies on measurements received at one time instant. Leveraging the approximate low-rank property of phasor measurement unit (PMU) data, we formulate the identification problem of successive unobservable cyber attacks as a matrix decomposition problem of a low-rank matrix plus a transformed column-sparse matrix. We propose a convex-optimization-based method and provide its theoretical guarantee in the data identification. Numerical experiments on actual PMU data from the Central New York power system and synthetic data are conducted to verify the effectiveness of the proposed method.

Simulation tests of the optimization method of Hopfield and Tank using neural networks

NASA Technical Reports Server (NTRS)

Paielli, Russell A.

1988-01-01

The method proposed by Hopfield and Tank for using the Hopfield neural network with continuous valued neurons to solve the traveling salesman problem is tested by simulation. Several researchers have apparently been unable to successfully repeat the numerical simulation documented by Hopfield and Tank. However, as suggested to the author by Adams, it appears that the reason for those difficulties is that a key parameter value is reported erroneously (by four orders of magnitude) in the original paper. When a reasonable value is used for that parameter, the network performs generally as claimed. Additionally, a new method of using feedback to control the input bias currents to the amplifiers is proposed and successfully tested. This eliminates the need to set the input currents by trial and error.

Mechanism of bonding and debonding using surface activated bonding method with Si intermediate layer

NASA Astrophysics Data System (ADS)

Takeuchi, Kai; Fujino, Masahisa; Matsumoto, Yoshiie; Suga, Tadatomo

2018-04-01

Techniques of handling thin and fragile substrates in a high-temperature process are highly required for the fabrication of semiconductor devices including thin film transistors (TFTs). In our previous study, we proposed applying the surface activated bonding (SAB) method using Si intermediate layers to the bonding and debonding of glass substrates. The SAB method has successfully bonded glass substrates at room temperature, and the substrates have been debonded after heating at 450 °C, in which TFTs are fabricated on thin glass substrates for LC display devices. In this study, we conducted the bonding and debonding of Si and glass in order to understand the mechanism in the proposed process. Si substrates are also successfully bonded to glass substrates at room temperature and debonded after heating at 450 °C using the proposed bonding process. By the composition analysis of bonding interfaces, it is clarified that the absorbed water on the glass forms interfacial voids and cause the decrease in bond strength.

Hybrid ARQ Scheme with Autonomous Retransmission for Multicasting in Wireless Sensor Networks.

PubMed

Jung, Young-Ho; Choi, Jihoon

2017-02-25

A new hybrid automatic repeat request (HARQ) scheme for multicast service for wireless sensor networks is proposed in this study. In the proposed algorithm, the HARQ operation is combined with an autonomous retransmission method that ensure a data packet is transmitted irrespective of whether or not the packet is successfully decoded at the receivers. The optimal number of autonomous retransmissions is determined to ensure maximum spectral efficiency, and a practical method that adjusts the number of autonomous retransmissions for realistic conditions is developed. Simulation results show that the proposed method achieves higher spectral efficiency than existing HARQ techniques.

Modified slanted-edge method for camera modulation transfer function measurement using nonuniform fast Fourier transform technique

NASA Astrophysics Data System (ADS)

Duan, Yaxuan; Xu, Songbo; Yuan, Suochao; Chen, Yongquan; Li, Hongguang; Da, Zhengshang; Gao, Limin

2018-01-01

ISO 12233 slanted-edge method experiences errors using fast Fourier transform (FFT) in the camera modulation transfer function (MTF) measurement due to tilt angle errors in the knife-edge resulting in nonuniform sampling of the edge spread function (ESF). In order to resolve this problem, a modified slanted-edge method using nonuniform fast Fourier transform (NUFFT) for camera MTF measurement is proposed. Theoretical simulations for images with noise at a different nonuniform sampling rate of ESF are performed using the proposed modified slanted-edge method. It is shown that the proposed method successfully eliminates the error due to the nonuniform sampling of the ESF. An experimental setup for camera MTF measurement is established to verify the accuracy of the proposed method. The experiment results show that under different nonuniform sampling rates of ESF, the proposed modified slanted-edge method has improved accuracy for the camera MTF measurement compared to the ISO 12233 slanted-edge method.

Equivalent orthotropic elastic moduli identification method for laminated electrical steel sheets

NASA Astrophysics Data System (ADS)

Saito, Akira; Nishikawa, Yasunari; Yamasaki, Shintaro; Fujita, Kikuo; Kawamoto, Atsushi; Kuroishi, Masakatsu; Nakai, Hideo

2016-05-01

In this paper, a combined numerical-experimental methodology for the identification of elastic moduli of orthotropic media is presented. Special attention is given to the laminated electrical steel sheets, which are modeled as orthotropic media with nine independent engineering elastic moduli. The elastic moduli are determined specifically for use with finite element vibration analyses. We propose a three-step methodology based on a conventional nonlinear least squares fit between measured and computed natural frequencies. The methodology consists of: (1) successive augmentations of the objective function by increasing the number of modes, (2) initial condition updates, and (3) appropriate selection of the natural frequencies based on their sensitivities on the elastic moduli. Using the results of numerical experiments, it is shown that the proposed method achieves more accurate converged solution than a conventional approach. Finally, the proposed method is applied to measured natural frequencies and mode shapes of the laminated electrical steel sheets. It is shown that the method can successfully identify the orthotropic elastic moduli that can reproduce the measured natural frequencies and frequency response functions by using finite element analyses with a reasonable accuracy.

Learning to Rapidly Re-Contact the Lost Plume in Chemical Plume Tracing

PubMed Central

Cao, Meng-Li; Meng, Qing-Hao; Wang, Jia-Ying; Luo, Bing; Jing, Ya-Qi; Ma, Shu-Gen

2015-01-01

Maintaining contact between the robot and plume is significant in chemical plume tracing (CPT). In the time immediately following the loss of chemical detection during the process of CPT, Track-Out activities bias the robot heading relative to the upwind direction, expecting to rapidly re-contact the plume. To determine the bias angle used in the Track-Out activity, we propose an online instance-based reinforcement learning method, namely virtual trail following (VTF). In VTF, action-value is generalized from recently stored instances of successful Track-Out activities. We also propose a collaborative VTF (cVTF) method, in which multiple robots store their own instances, and learn from the stored instances, in the same database. The proposed VTF and cVTF methods are compared with biased upwind surge (BUS) method, in which all Track-Out activities utilize an offline optimized universal bias angle, in an indoor environment with three different airflow fields. With respect to our experimental conditions, VTF and cVTF show stronger adaptability to different airflow environments than BUS, and furthermore, cVTF yields higher success rates and time-efficiencies than VTF. PMID:25825974

An hp symplectic pseudospectral method for nonlinear optimal control

NASA Astrophysics Data System (ADS)

Peng, Haijun; Wang, Xinwei; Li, Mingwu; Chen, Biaosong

2017-01-01

An adaptive symplectic pseudospectral method based on the dual variational principle is proposed and is successfully applied to solving nonlinear optimal control problems in this paper. The proposed method satisfies the first order necessary conditions of continuous optimal control problems, also the symplectic property of the original continuous Hamiltonian system is preserved. The original optimal control problem is transferred into a set of nonlinear equations which can be solved easily by Newton-Raphson iterations, and the Jacobian matrix is found to be sparse and symmetric. The proposed method, on one hand, exhibits exponent convergence rates when the number of collocation points are increasing with the fixed number of sub-intervals; on the other hand, exhibits linear convergence rates when the number of sub-intervals is increasing with the fixed number of collocation points. Furthermore, combining with the hp method based on the residual error of dynamic constraints, the proposed method can achieve given precisions in a few iterations. Five examples highlight the high precision and high computational efficiency of the proposed method.

Successful aging as a multidimensional concept: An integrative review

PubMed Central

Zanjari, Nasibeh; Sharifian Sani, Maryam; Chavoshi, Meimanat Hosseini; Rafiey, Hassan; Mohammadi Shahboulaghi, Farahnaz

2017-01-01

Background: Successful aging as an umbrella term with a large amount of literature has emerged with a variety of meanings and dimensions in different studies. This article aims at determining what dimensions contribute to constructing the concept of successful aging. Methods: The method used in this study is an integrative review of published literature related to successful aging. This method includes both qualitative and quantitative studies. Data searching was conducted during November and December 2014 and was then updated in October 2015. First, 2543 articles were identified, and after the screening phase, 76 articles were eligible for inclusion in the integrative review. Results: The results specified 14 subcategories and 5 main categories of successful aging: social well-being, psychological wellbeing, physical health, spirituality and transcendence, and environment and economic security. Conclusion: The present study provides a thorough understanding of successful aging dimensions and proposes the importance of the multidimensional concept of successful aging at the individual, interpersonal, and environmental levels for future studies and policymaking on population aging.

Pile-up correction algorithm based on successive integration for high count rate medical imaging and radiation spectroscopy

NASA Astrophysics Data System (ADS)

Mohammadian-Behbahani, Mohammad-Reza; Saramad, Shahyar

2018-07-01

In high count rate radiation spectroscopy and imaging, detector output pulses tend to pile up due to high interaction rate of the particles with the detector. Pile-up effects can lead to a severe distortion of the energy and timing information. Pile-up events are conventionally prevented or rejected by both analog and digital electronics. However, for decreasing the exposure times in medical imaging applications, it is important to maintain the pulses and extract their true information by pile-up correction methods. The single-event reconstruction method is a relatively new model-based approach for recovering the pulses one-by-one using a fitting procedure, for which a fast fitting algorithm is a prerequisite. This article proposes a fast non-iterative algorithm based on successive integration which fits the bi-exponential model to experimental data. After optimizing the method, the energy spectra, energy resolution and peak-to-peak count ratios are calculated for different counting rates using the proposed algorithm as well as the rejection method for comparison. The obtained results prove the effectiveness of the proposed method as a pile-up processing scheme designed for spectroscopic and medical radiation detection applications.

An efficient spectrofluorimetric method adopts doxazosin, terazosin and alfuzosin coupling with orthophthalaldehyde: Application in human plasma

NASA Astrophysics Data System (ADS)

Omar, Mahmoud A.; Mohamed, Abdel-Maaboud I.; Derayea, Sayed M.; Hammad, Mohamed A.; Mohamed, Abobakr A.

2018-04-01

A new, selective and sensitive spectrofluorimetric method was designed for the quantitation of doxazosin (DOX), terazosin (TER) and alfuzosin (ALF) in their dosage forms and human plasma. The method adopts efficient derivatization of the studied drugs with ortho-phthalaldehyde (OPA), in the presence of 2-mercaptoethanol in borate buffer (pH 9.7) to generate a highly fluorescent isoindole derivatives, which can strongly enhance the fluorescence intensities of the studied drugs, allowing their sensitive determination at 430 nm after excitation at 337 nm. The fluorescence-concentration plots were rectilinear over the ranges (10.0-400.0) ng/mL. Detection and quantification limits were found to be (0.52-3.88) and (1.59-11.76) ng/mL, respectively. The proposed method was validated according to ICH guidelines, and successfully applied for the determination of pharmaceutical preparations of the studied drugs. Moreover, the high sensitivity of the proposed method permits its successful application to the analysis of the studied drugs in spiked human plasma with % recovery (96.12 ± 1.34-100.66 ± 0.57, n = 3). A proposal for the reaction mechanism was presented.

Electrohydrodynamic assisted droplet alignment for lens fabrication by droplet evaporation

NASA Astrophysics Data System (ADS)

Wang, Guangxu; Deng, Jia; Guo, Xing

2018-04-01

Lens fabrication by droplet evaporation has attracted a lot of attention since the fabrication approach is simple and moldless. Droplet position accuracy is a critical parameter in this approach, and thus it is of great importance to use accurate methods to realize the droplet position alignment. In this paper, we propose an electrohydrodynamic (EHD) assisted droplet alignment method. An electrostatic force was induced at the interface between materials to overcome the surface tension and gravity. The deviation of droplet position from the center region was eliminated and alignment was successfully realized. We demonstrated the capability of the proposed method theoretically and experimentally. First, we built a simulation model coupled with the three-phase flow formulations and the EHD equations to study the three-phase flowing process in an electric field. Results show that it is the uneven electric field distribution that leads to the relative movement of the droplet. Then, we conducted experiments to verify the method. Experimental results are consistent with the numerical simulation results. Moreover, we successfully fabricated a crater lens after applying the proposed method. A light emitting diode module packaging with the fabricated crater lens shows a significant light intensity distribution adjustment compared with a spherical cap lens.

Prompt identification of tsunamigenic earthquakes from 3-component seismic data

NASA Astrophysics Data System (ADS)

Kundu, Ajit; Bhadauria, Y. S.; Basu, S.; Mukhopadhyay, S.

2016-10-01

An Artificial Neural Network (ANN) based algorithm for prompt identification of shallow focus (depth < 70 km) tsunamigenic earthquakes at a regional distance is proposed in the paper. The promptness here refers to decision making as fast as 5 min after the arrival of LR phase in the seismogram. The root mean square amplitudes of seismic phases recorded by a single 3-component station have been considered as inputs besides location and magnitude. The trained ANN has been found to categorize 100% of the new earthquakes successfully as tsunamigenic or non-tsunamigenic. The proposed method has been corroborated by an alternate mapping technique of earthquake category estimation. The second method involves computation of focal parameters, estimation of water volume displaced at the source and eventually deciding category of the earthquake. The method has been found to identify 95% of the new earthquakes successfully. Both the methods have been tested using three component broad band seismic data recorded at PALK (Pallekele, Sri Lanka) station provided by IRIS for earthquakes originating from Sumatra region of magnitude 6 and above. The fair agreement between the methods ensures that a prompt alert system could be developed based on proposed method. The method would prove to be extremely useful for the regions that are not adequately instrumented for azimuthal coverage.

Automated feature extraction in color retinal images by a model based approach.

PubMed

Li, Huiqi; Chutatape, Opas

2004-02-01

Color retinal photography is an important tool to detect the evidence of various eye diseases. Novel methods to extract the main features in color retinal images have been developed in this paper. Principal component analysis is employed to locate optic disk; A modified active shape model is proposed in the shape detection of optic disk; A fundus coordinate system is established to provide a better description of the features in the retinal images; An approach to detect exudates by the combined region growing and edge detection is proposed. The success rates of disk localization, disk boundary detection, and fovea localization are 99%, 94%, and 100%, respectively. The sensitivity and specificity of exudate detection are 100% and 71%, correspondingly. The success of the proposed algorithms can be attributed to the utilization of the model-based methods. The detection and analysis could be applied to automatic mass screening and diagnosis of the retinal diseases.

Multiresolution persistent homology for excessively large biomolecular datasets

NASA Astrophysics Data System (ADS)

Xia, Kelin; Zhao, Zhixiong; Wei, Guo-Wei

2015-10-01

Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topological analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs.

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

Xia, Kelin; Zhao, Zhixiong; Wei, Guo-Wei, E-mail: wei@math.msu.edu

Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topologicalmore » analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs.« less

A new in vitro method for testing plant metabolism in mutagenicity studies.

PubMed

Benigni, R; Bignami, M; Camoni, I; Carere, A; Conti, G; Iachetta, R; Morpurgo, G; Ortali, V A

1979-09-01

A rapid method was proposed to detect whether a harmless agricultural chemical can be converted into a mutagenic one by plant metabolism. The method is based on the use of Nicotiana alata cell cultures. Results obtained with five pesticides (atrazine, dichlorvos, tetrachlorvinphos, Kelevan, and maleic hydrazide) suggest that the proposed method simulates the metabolism of the whole plant. This procedure was also successfully applied to the genetic system of Aspergillus nidulans. One pesticide, atrazine, induced mutations and somatic segregation only after metabolism during cocultivation with N. alata cells.

An improved transmutation method for quantitative determination of the components in multicomponent overlapping chromatograms.

PubMed

Shao, Xueguang; Yu, Zhengliang; Ma, Chaoxiong

2004-06-01

An improved method is proposed for the quantitative determination of multicomponent overlapping chromatograms based on a known transmutation method. To overcome the main limitation of the transmutation method caused by the oscillation generated in the transmutation process, two techniques--wavelet transform smoothing and the cubic spline interpolation for reducing data points--were adopted, and a new criterion was also developed. By using the proposed algorithm, the oscillation can be suppressed effectively, and quantitative determination of the components in both the simulated and experimental overlapping chromatograms is successfully obtained.

Analytical investigation of different mathematical approaches utilizing manipulation of ratio spectra

NASA Astrophysics Data System (ADS)

Osman, Essam Eldin A.

2018-01-01

This work represents a comparative study of different approaches of manipulating ratio spectra, applied on a binary mixture of ciprofloxacin HCl and dexamethasone sodium phosphate co-formulated as ear drops. The proposed new spectrophotometric methods are: ratio difference spectrophotometric method (RDSM), amplitude center method (ACM), first derivative of the ratio spectra (1DD) and mean centering of ratio spectra (MCR). The proposed methods were checked using laboratory-prepared mixtures and were successfully applied for the analysis of pharmaceutical formulation containing the cited drugs. The proposed methods were validated according to the ICH guidelines. A comparative study was conducted between those methods regarding simplicity, limitations and sensitivity. The obtained results were statistically compared with those obtained from the reported HPLC method, showing no significant difference with respect to accuracy and precision.

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

A hybrid technique for speech segregation and classification using a sophisticated deep neural network

PubMed Central

Nawaz, Tabassam; Mehmood, Zahid; Rashid, Muhammad; Habib, Hafiz Adnan

2018-01-01

Recent research on speech segregation and music fingerprinting has led to improvements in speech segregation and music identification algorithms. Speech and music segregation generally involves the identification of music followed by speech segregation. However, music segregation becomes a challenging task in the presence of noise. This paper proposes a novel method of speech segregation for unlabelled stationary noisy audio signals using the deep belief network (DBN) model. The proposed method successfully segregates a music signal from noisy audio streams. A recurrent neural network (RNN)-based hidden layer segregation model is applied to remove stationary noise. Dictionary-based fisher algorithms are employed for speech classification. The proposed method is tested on three datasets (TIMIT, MIR-1K, and MusicBrainz), and the results indicate the robustness of proposed method for speech segregation. The qualitative and quantitative analysis carried out on three datasets demonstrate the efficiency of the proposed method compared to the state-of-the-art speech segregation and classification-based methods. PMID:29558485

Analysis on critical success factors for agile manufacturing evaluation in original equipment manufacturing industry-an AHP approach

NASA Astrophysics Data System (ADS)

Ajay Guru Dev, C.; Senthil Kumar, V. S.

2016-09-01

Manufacturing industries are facing challenges in the implementation of agile manufacturing in their products and processes. Agility is widely accepted as a new competitive concept in the manufacturing sector in fulfilling varying customer demand. Thus, evaluation of agile manufacturing in industries has become a necessity. The success of an organisation depends on its ability to manage finding the critical success factors and give them special and continued attention in order to bring about high performance. This paper proposes a set of critical success factors (CSFs) for evaluating agile manufacturing considered appropriate for the manufacturing sector. The analytical hierarchy process (AHP) method is applied for prioritizing the success factors, by summarizing the opinions of experts. It is believed that the proposed CSFs enable and assist manufacturing industries to achieve a higher performance in agile manufacturing so as to increase competitiveness.

New Spectrofluorimetric Method with Enhanced Sensitivity for Determination of Paroxetine in Dosage Forms and Plasma

PubMed Central

Darwish, Ibrahim A.; Amer, Sawsan M.; Abdine, Heba H.; Al-Rayes, Lama I.

2008-01-01

New simple spectrofluorimetric method with enhanced sensitivity has been developed and validated for the determination of the antidepressant paroxetine (PXT) in its dosage forms and plasma. The method was based on nucleophilic substitution reaction of PXT with 4-chloro-7-nitrobenzo-2-oxa-1,3-diazole in an alkaline medium (pH 8) to form a highly fluorescent derivative that was measured at 545 nm after excitation at 490 nm. The factors affecting the reaction was carefully studied and optimized. The kinetics of the reaction was investigated, and the reaction mechanism was presented. Under the optimized conditions, linear relationship with good correlation coefficient (0.9993) was found between the fluorescence intensity and PXT concentration in the range of 80–800 ng ml−1. The limits of detection and quantitation for the method were 25 and 77 ng ml−1, respectively. The precision of the method was satisfactory; the values of relative standard deviations did not exceed 3%. The proposed method was successfully applied to the determination of PXT in its pharmaceutical tablets with good accuracy; the recovery values were 100.2 ± 1.61%. The results obtained by the proposed method were comparable with those obtained by the official method. The proposed method is superior to the previously reported spectrofluorimetric method for determination of PXT in terms of its higher sensitivity and wider linear range. The high sensitivity of the method allowed its successful application to the analysis of PXT in spiked human plasma. The proposed method is practical and valuable for its routine application in quality control and clinical laboratories for analysis of PXT. PMID:19609398

Robust and fast-converging level set method for side-scan sonar image segmentation

NASA Astrophysics Data System (ADS)

Liu, Yan; Li, Qingwu; Huo, Guanying

2017-11-01

A robust and fast-converging level set method is proposed for side-scan sonar (SSS) image segmentation. First, the noise in each sonar image is removed using the adaptive nonlinear complex diffusion filter. Second, k-means clustering is used to obtain the initial presegmentation image from the denoised image, and then the distance maps of the initial contours are reinitialized to guarantee the accuracy of the numerical calculation used in the level set evolution. Finally, the satisfactory segmentation is achieved using a robust variational level set model, where the evolution control parameters are generated by the presegmentation. The proposed method is successfully applied to both synthetic image with speckle noise and real SSS images. Experimental results show that the proposed method needs much less iteration and therefore is much faster than the fuzzy local information c-means clustering method, the level set method using a gamma observation model, and the enhanced region-scalable fitting method. Moreover, the proposed method can usually obtain more accurate segmentation results compared with other methods.

A new method for species identification via protein-coding and non-coding DNA barcodes by combining machine learning with bioinformatic methods.

PubMed

Zhang, Ai-bing; Feng, Jie; Ward, Robert D; Wan, Ping; Gao, Qiang; Wu, Jun; Zhao, Wei-zhong

2012-01-01

Species identification via DNA barcodes is contributing greatly to current bioinventory efforts. The initial, and widely accepted, proposal was to use the protein-coding cytochrome c oxidase subunit I (COI) region as the standard barcode for animals, but recently non-coding internal transcribed spacer (ITS) genes have been proposed as candidate barcodes for both animals and plants. However, achieving a robust alignment for non-coding regions can be problematic. Here we propose two new methods (DV-RBF and FJ-RBF) to address this issue for species assignment by both coding and non-coding sequences that take advantage of the power of machine learning and bioinformatics. We demonstrate the value of the new methods with four empirical datasets, two representing typical protein-coding COI barcode datasets (neotropical bats and marine fish) and two representing non-coding ITS barcodes (rust fungi and brown algae). Using two random sub-sampling approaches, we demonstrate that the new methods significantly outperformed existing Neighbor-joining (NJ) and Maximum likelihood (ML) methods for both coding and non-coding barcodes when there was complete species coverage in the reference dataset. The new methods also out-performed NJ and ML methods for non-coding sequences in circumstances of potentially incomplete species coverage, although then the NJ and ML methods performed slightly better than the new methods for protein-coding barcodes. A 100% success rate of species identification was achieved with the two new methods for 4,122 bat queries and 5,134 fish queries using COI barcodes, with 95% confidence intervals (CI) of 99.75-100%. The new methods also obtained a 96.29% success rate (95%CI: 91.62-98.40%) for 484 rust fungi queries and a 98.50% success rate (95%CI: 96.60-99.37%) for 1094 brown algae queries, both using ITS barcodes.

Online damage detection using recursive principal component analysis and recursive condition indicators

NASA Astrophysics Data System (ADS)

Krishnan, M.; Bhowmik, B.; Tiwari, A. K.; Hazra, B.

2017-08-01

In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using recursive principal component analysis (RPCA) in conjunction with online damage indicators is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal modes in online using the rank-one perturbation method, and subsequently utilized to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/nonlinear-states that indicate damage. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. An online condition indicator (CI) based on the L2 norm of the error between actual response and the response projected using recursive eigenvector matrix updates over successive iterations is proposed. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data. The proposed CI, named recursive residual error, is also adopted for simultaneous spatio-temporal damage detection. Numerical simulations performed on five-degree of freedom nonlinear system under white noise and El Centro excitations, with different levels of nonlinearity simulating the damage scenarios, demonstrate the robustness of the proposed algorithm. Successful results obtained from practical case studies involving experiments performed on a cantilever beam subjected to earthquake excitation, for full sensors and underdetermined cases; and data from recorded responses of the UCLA Factor building (full data and its subset) demonstrate the efficacy of the proposed methodology as an ideal candidate for real-time, reference free structural health monitoring.

An individual and dynamic Body Segment Inertial Parameter validation method using ground reaction forces.

PubMed

Hansen, Clint; Venture, Gentiane; Rezzoug, Nasser; Gorce, Philippe; Isableu, Brice

2014-05-07

Over the last decades a variety of research has been conducted with the goal to improve the Body Segment Inertial Parameters (BSIP) estimations but to our knowledge a real validation has never been completely successful, because no ground truth is available. The aim of this paper is to propose a validation method for a BSIP identification method (IM) and to confirm the results by comparing them with recalculated contact forces using inverse dynamics to those obtained by a force plate. Furthermore, the results are compared with the recently proposed estimation method by Dumas et al. (2007). Additionally, the results are cross validated with a high velocity overarm throwing movement. Throughout conditions higher correlations, smaller metrics and smaller RMSE can be found for the proposed BSIP estimation (IM) which shows its advantage compared to recently proposed methods as of Dumas et al. (2007). The purpose of the paper is to validate an already proposed method and to show that this method can be of significant advantage compared to conventional methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Derivative free Davidon-Fletcher-Powell (DFP) for solving symmetric systems of nonlinear equations

NASA Astrophysics Data System (ADS)

Mamat, M.; Dauda, M. K.; Mohamed, M. A. bin; Waziri, M. Y.; Mohamad, F. S.; Abdullah, H.

2018-03-01

Research from the work of engineers, economist, modelling, industry, computing, and scientist are mostly nonlinear equations in nature. Numerical solution to such systems is widely applied in those areas of mathematics. Over the years, there has been significant theoretical study to develop methods for solving such systems, despite these efforts, unfortunately the methods developed do have deficiency. In a contribution to solve systems of the form F(x) = 0, x ∈ Rn , a derivative free method via the classical Davidon-Fletcher-Powell (DFP) update is presented. This is achieved by simply approximating the inverse Hessian matrix with {Q}k+1-1 to θkI. The modified method satisfied the descent condition and possess local superlinear convergence properties. Interestingly, without computing any derivative, the proposed method never fail to converge throughout the numerical experiments. The output is based on number of iterations and CPU time, different initial starting points were used on a solve 40 benchmark test problems. With the aid of the squared norm merit function and derivative-free line search technique, the approach yield a method of solving symmetric systems of nonlinear equations that is capable of significantly reducing the CPU time and number of iteration, as compared to its counterparts. A comparison between the proposed method and classical DFP update were made and found that the proposed methodis the top performer and outperformed the existing method in almost all the cases. In terms of number of iterations, out of the 40 problems solved, the proposed method solved 38 successfully, (95%) while classical DFP solved 2 problems (i.e. 05%). In terms of CPU time, the proposed method solved 29 out of the 40 problems given, (i.e.72.5%) successfully whereas classical DFP solves 11 (27.5%). The method is valid in terms of derivation, reliable in terms of number of iterations and accurate in terms of CPU time. Thus, suitable and achived the objective.

A baseline lunar mine

NASA Technical Reports Server (NTRS)

Gertsch, Richard E.

1992-01-01

A models lunar mining method is proposed that illustrates the problems to be expected in lunar mining and how they might be solved. While the method is quite feasible, it is, more importantly, a useful baseline system against which to test other, possible better, methods. Our study group proposed the slusher to stimulate discussion of how a lunar mining operation might be successfully accomplished. Critics of the slusher system were invited to propose better methods. The group noted that while nonterrestrial mining has been a vital part of past space manufacturing proposals, no one has proposed a lunar mining system in any real detail. The group considered it essential that the design of actual, workable, and specific lunar mining methods begin immediately. Based on an earlier proposal, the method is a three-drum slusher, also known as a cable-operated drag scraper. Its terrestrial application is quite limited, as it is relatively inefficient and inflexible. The method usually finds use in underwater mining from the shore and in moving small amounts of ore underground. When lunar mining scales up, the lunarized slusher will be replaced by more efficient, high-volume methods. Other aspects of lunar mining are discussed.

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.

Credit Risk Evaluation of Power Market Players with Random Forest

NASA Astrophysics Data System (ADS)

Umezawa, Yasushi; Mori, Hiroyuki

A new method is proposed for credit risk evaluation in a power market. The credit risk evaluation is to measure the bankruptcy risk of the company. The power system liberalization results in new environment that puts emphasis on the profit maximization and the risk minimization. There is a high probability that the electricity transaction causes a risk between companies. So, power market players are concerned with the risk minimization. As a management strategy, a risk index is requested to evaluate the worth of the business partner. This paper proposes a new method for evaluating the credit risk with Random Forest (RF) that makes ensemble learning for the decision tree. RF is one of efficient data mining technique in clustering data and extracting relationship between input and output data. In addition, the method of generating pseudo-measurements is proposed to improve the performance of RF. The proposed method is successfully applied to real financial data of energy utilities in the power market. A comparison is made between the proposed and the conventional methods.

2004 Strategic Master Plan for Higher Education. Update on Implementation

ERIC Educational Resources Information Center

Washington Higher Education Coordinating Board, 2005

2005-01-01

The 2004 Strategic Master Plan for Higher Education identified clear and measurable goals that focused on outcomes rather than inputs alone. To reinforce this outcomes-based approach, the plan proposed that the state develop a new funding method to reward public colleges and universities for student success. Specifically, it proposed that the…

Proposing a sequential comparative analysis for assessing multilateral health agency transformation and sustainable capacity: exploring the advantages of institutional theory

PubMed Central

2014-01-01

Background This article proposes an approach to comparing and assessing the adaptive capacity of multilateral health agencies in meeting country and individual healthcare needs. Most studies comparing multilateral health agencies have failed to clearly propose a method for conducting agency comparisons. Methods This study conducted a qualitative case study methodological approach, such that secondary and primary case study literature was used to conduct case study comparisons of multilateral health agencies. Results Through the proposed Sequential Comparative Analysis (SCA), the author found a more effective way to justify the selection of cases, compare and assess organizational transformative capacity, and to learn from agency success in policy sustainability processes. Conclusions To more affectively understand and explain why some multilateral health agencies are more capable of adapting to country and individual healthcare needs, SCA provides a methodological approach that may help to better understand why these agencies are so different and what we can learn from successful reform processes. As funding challenges continue to hamper these agencies' adaptive capacity, learning from each other will become increasingly important. PMID:24886283

The Pixon Method for Data Compression Image Classification, and Image Reconstruction

NASA Technical Reports Server (NTRS)

Puetter, Richard; Yahil, Amos

2002-01-01

As initially proposed, this program had three goals: (1) continue to develop the highly successful Pixon method for image reconstruction and support other scientist in implementing this technique for their applications; (2) develop image compression techniques based on the Pixon method; and (3) develop artificial intelligence algorithms for image classification based on the Pixon approach for simplifying neural networks. Subsequent to proposal review the scope of the program was greatly reduced and it was decided to investigate the ability of the Pixon method to provide superior restorations of images compressed with standard image compression schemes, specifically JPEG-compressed images.

Machine learning methods for locating re-entrant drivers from electrograms in a model of atrial fibrillation

NASA Astrophysics Data System (ADS)

McGillivray, Max Falkenberg; Cheng, William; Peters, Nicholas S.; Christensen, Kim

2018-04-01

Mapping resolution has recently been identified as a key limitation in successfully locating the drivers of atrial fibrillation (AF). Using a simple cellular automata model of AF, we demonstrate a method by which re-entrant drivers can be located quickly and accurately using a collection of indirect electrogram measurements. The method proposed employs simple, out-of-the-box machine learning algorithms to correlate characteristic electrogram gradients with the displacement of an electrogram recording from a re-entrant driver. Such a method is less sensitive to local fluctuations in electrical activity. As a result, the method successfully locates 95.4% of drivers in tissues containing a single driver, and 95.1% (92.6%) for the first (second) driver in tissues containing two drivers of AF. Additionally, we demonstrate how the technique can be applied to tissues with an arbitrary number of drivers. In its current form, the techniques presented are not refined enough for a clinical setting. However, the methods proposed offer a promising path for future investigations aimed at improving targeted ablation for AF.

Deep imitation learning for 3D navigation tasks.

PubMed

Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina

2018-01-01

Deep learning techniques have shown success in learning from raw high-dimensional data in various applications. While deep reinforcement learning is recently gaining popularity as a method to train intelligent agents, utilizing deep learning in imitation learning has been scarcely explored. Imitation learning can be an efficient method to teach intelligent agents by providing a set of demonstrations to learn from. However, generalizing to situations that are not represented in the demonstrations can be challenging, especially in 3D environments. In this paper, we propose a deep imitation learning method to learn navigation tasks from demonstrations in a 3D environment. The supervised policy is refined using active learning in order to generalize to unseen situations. This approach is compared to two popular deep reinforcement learning techniques: deep-Q-networks and Asynchronous actor-critic (A3C). The proposed method as well as the reinforcement learning methods employ deep convolutional neural networks and learn directly from raw visual input. Methods for combining learning from demonstrations and experience are also investigated. This combination aims to join the generalization ability of learning by experience with the efficiency of learning by imitation. The proposed methods are evaluated on 4 navigation tasks in a 3D simulated environment. Navigation tasks are a typical problem that is relevant to many real applications. They pose the challenge of requiring demonstrations of long trajectories to reach the target and only providing delayed rewards (usually terminal) to the agent. The experiments show that the proposed method can successfully learn navigation tasks from raw visual input while learning from experience methods fail to learn an effective policy. Moreover, it is shown that active learning can significantly improve the performance of the initially learned policy using a small number of active samples.

A spatial scan statistic for multiple clusters.

PubMed

Li, Xiao-Zhou; Wang, Jin-Feng; Yang, Wei-Zhong; Li, Zhong-Jie; Lai, Sheng-Jie

2011-10-01

Spatial scan statistics are commonly used for geographical disease surveillance and cluster detection. While there are multiple clusters coexisting in the study area, they become difficult to detect because of clusters' shadowing effect to each other. The recently proposed sequential method showed its better power for detecting the second weaker cluster, but did not improve the ability of detecting the first stronger cluster which is more important than the second one. We propose a new extension of the spatial scan statistic which could be used to detect multiple clusters. Through constructing two or more clusters in the alternative hypothesis, our proposed method accounts for other coexisting clusters in the detecting and evaluating process. The performance of the proposed method is compared to the sequential method through an intensive simulation study, in which our proposed method shows better power in terms of both rejecting the null hypothesis and accurately detecting the coexisting clusters. In the real study of hand-foot-mouth disease data in Pingdu city, a true cluster town is successfully detected by our proposed method, which cannot be evaluated to be statistically significant by the standard method due to another cluster's shadowing effect. Copyright © 2011 Elsevier Inc. All rights reserved.

Adaptive target binarization method based on a dual-camera system

NASA Astrophysics Data System (ADS)

Lei, Jing; Zhang, Ping; Xu, Jiangtao; Gao, Zhiyuan; Gao, Jing

2018-01-01

An adaptive target binarization method based on a dual-camera system that contains two dynamic vision sensors was proposed. First, a preprocessing procedure of denoising is introduced to remove the noise events generated by the sensors. Then, the complete edge of the target is retrieved and represented by events based on an event mosaicking method. Third, the region of the target is confirmed by an event-to-event method. Finally, a postprocessing procedure of image open and close operations of morphology methods is adopted to remove the artifacts caused by event-to-event mismatching. The proposed binarization method has been extensively tested on numerous degraded images with nonuniform illumination, low contrast, noise, or light spots and successfully compared with other well-known binarization methods. The experimental results, which are based on visual and misclassification error criteria, show that the proposed method performs well and has better robustness on the binarization of degraded images.

Development and validation of multivariate calibration methods for simultaneous estimation of Paracetamol, Enalapril maleate and hydrochlorothiazide in pharmaceutical dosage form

NASA Astrophysics Data System (ADS)

Singh, Veena D.; Daharwal, Sanjay J.

2017-01-01

Three multivariate calibration spectrophotometric methods were developed for simultaneous estimation of Paracetamol (PARA), Enalapril maleate (ENM) and Hydrochlorothiazide (HCTZ) in tablet dosage form; namely multi-linear regression calibration (MLRC), trilinear regression calibration method (TLRC) and classical least square (CLS) method. The selectivity of the proposed methods were studied by analyzing the laboratory prepared ternary mixture and successfully applied in their combined dosage form. The proposed methods were validated as per ICH guidelines and good accuracy; precision and specificity were confirmed within the concentration range of 5-35 μg mL- 1, 5-40 μg mL- 1 and 5-40 μg mL- 1of PARA, HCTZ and ENM, respectively. The results were statistically compared with reported HPLC method. Thus, the proposed methods can be effectively useful for the routine quality control analysis of these drugs in commercial tablet dosage form.

Dynamic deformation image de-blurring and image processing for digital imaging correlation measurement

NASA Astrophysics Data System (ADS)

Guo, X.; Li, Y.; Suo, T.; Liu, H.; Zhang, C.

2017-11-01

This paper proposes a method for de-blurring of images captured in the dynamic deformation of materials. De-blurring is achieved based on the dynamic-based approach, which is used to estimate the Point Spread Function (PSF) during the camera exposure window. The deconvolution process involving iterative matrix calculations of pixels, is then performed on the GPU to decrease the time cost. Compared to the Gauss method and the Lucy-Richardson method, it has the best result of the image restoration. The proposed method has been evaluated by using the Hopkinson bar loading system. In comparison to the blurry image, the proposed method has successfully restored the image. It is also demonstrated from image processing applications that the de-blurring method can improve the accuracy and the stability of the digital imaging correlation measurement.

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

NASA Astrophysics Data System (ADS)

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.

Elements for successful sensor-based process control {Integrated Metrology}

NASA Astrophysics Data System (ADS)

Butler, Stephanie Watts

1998-11-01

Current productivity needs have stimulated development of alternative metrology, control, and equipment maintenance methods. Specifically, sensor applications provide the opportunity to increase productivity, tighten control, reduce scrap, and improve maintenance schedules and procedures. Past experience indicates a complete integrated solution must be provided for sensor-based control to be used successfully in production. In this paper, Integrated Metrology is proposed as the term for an integrated solution that will result in a successful application of sensors for process control. This paper defines and explores the perceived four elements of successful sensor applications: business needs, integration, components, and form. Based upon analysis of existing successful commercially available controllers, the necessary business factors have been determined to be strong, measurable industry-wide business needs whose solution is profitable and feasible. This paper examines why the key aspect of integration is the decision making process. A detailed discussion is provided of the components of most importance to sensor based control: decision-making methods, the 3R's of sensors, and connectivity. A metric for one of the R's (resolution) is proposed to allow focus on this important aspect of measurement. A form for these integrated components which synergistically partitions various aspects of control at the equipment and MES levels to efficiently achieve desired benefits is recommended.

[Treatment of metaphyseal fractures of shin bones by the method of blocking osteosynthesis].

PubMed

Neverov, V A; Khromov, A A; Cherniaev, S N; Egorov, K S; Shebarshov, A L

2008-01-01

The proposed method of reposition and polyaxial stabilization of fragments for intramedullary meallosynthesis of fractures of long tubular bones allows blocking osteosynthesis to be successfully used in treatment of complex metaphyseal fractures of shin bones. It results in strong fixation of the fragments, makes it possible to successfully eliminate residual deformities after introduction of the nail and to avoid the development of them in future under the influence of loading. The method provides early functioning of the interfacing joints, early axial loading, shorter period of disability, the absence of external immobilization.

A New Multiconstraint Method for Determining the Optimal Cable Stresses in Cable-Stayed Bridges

PubMed Central

Asgari, B.; Osman, S. A.; Adnan, A.

2014-01-01

Cable-stayed bridges are one of the most popular types of long-span bridges. The structural behaviour of cable-stayed bridges is sensitive to the load distribution between the girder, pylons, and cables. The determination of pretensioning cable stresses is critical in the cable-stayed bridge design procedure. By finding the optimum stresses in cables, the load and moment distribution of the bridge can be improved. In recent years, different research works have studied iterative and modern methods to find optimum stresses of cables. However, most of the proposed methods have limitations in optimising the structural performance of cable-stayed bridges. This paper presents a multiconstraint optimisation method to specify the optimum cable forces in cable-stayed bridges. The proposed optimisation method produces less bending moments and stresses in the bridge members and requires shorter simulation time than other proposed methods. The results of comparative study show that the proposed method is more successful in restricting the deck and pylon displacements and providing uniform deck moment distribution than unit load method (ULM). The final design of cable-stayed bridges can be optimised considerably through proposed multiconstraint optimisation method. PMID:25050400

A new multiconstraint method for determining the optimal cable stresses in cable-stayed bridges.

PubMed

Asgari, B; Osman, S A; Adnan, A

2014-01-01

Cable-stayed bridges are one of the most popular types of long-span bridges. The structural behaviour of cable-stayed bridges is sensitive to the load distribution between the girder, pylons, and cables. The determination of pretensioning cable stresses is critical in the cable-stayed bridge design procedure. By finding the optimum stresses in cables, the load and moment distribution of the bridge can be improved. In recent years, different research works have studied iterative and modern methods to find optimum stresses of cables. However, most of the proposed methods have limitations in optimising the structural performance of cable-stayed bridges. This paper presents a multiconstraint optimisation method to specify the optimum cable forces in cable-stayed bridges. The proposed optimisation method produces less bending moments and stresses in the bridge members and requires shorter simulation time than other proposed methods. The results of comparative study show that the proposed method is more successful in restricting the deck and pylon displacements and providing uniform deck moment distribution than unit load method (ULM). The final design of cable-stayed bridges can be optimised considerably through proposed multiconstraint optimisation method.

A Kinect based sign language recognition system using spatio-temporal features

NASA Astrophysics Data System (ADS)

Memiş, Abbas; Albayrak, Songül

2013-12-01

This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System.

PubMed

Turksoy, Kamuran; Samadi, Sediqeh; Feng, Jianyuan; Littlejohn, Elizabeth; Quinn, Laurie; Cinar, Ali

2016-01-01

A novel meal-detection algorithm is developed based on continuous glucose measurements. Bergman's minimal model is modified and used in an unscented Kalman filter for state estimations. The estimated rate of appearance of glucose is used for meal detection. Data from nine subjects are used to assess the performance of the algorithm. The results indicate that the proposed algorithm works successfully with high accuracy. The average change in glucose levels between the meals and the detection points is 16(±9.42) [mg/dl] for 61 successfully detected meals and snacks. The algorithm is developed as a new module of an integrated multivariable adaptive artificial pancreas control system. Meal detection with the proposed method is used to administer insulin boluses and prevent most of postprandial hyperglycemia without any manual meal announcements. A novel meal bolus calculation method is proposed and tested with the UVA/Padova simulator. The results indicate significant reduction in hyperglycemia.

Analysis of carbon-oxygen reactions by use of a square-input response technique and {sup 18}O isotope

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

Miura, Kouichi; Nakagawa, Hiroyuki

1996-12-31

Carbon gasification reaction has been investigated for decades including the pioneering works of Walker and his co-workers, but its mechanism has not been completely elucidated. The concept of the active surface area (ASA) was proposed by them, and its importance has been recognized. However, since ASA was measured by O{sub 2} chemisorption at below 300{degrees}C where carbon loss through gasification is negligible, it does not reflect the actual gasification situation. To overcome this weak point, measurements of ASA in a batch reactor and the so-called transient kinetic (TK) method were proposed. Ahmed and Back successfully measured the chemisorbed oxygen duringmore » the gasification using a batch reactor, and proposed a new mechanistic sequence for carbon-oxygen reaction which stresses the importance of the reaction between the gaseous oxygen and the chemisorbed oxygen. Radovic et al. proposed the concept of the reactive surface area (RSA), and reported excellent proportionality between the CO{sub 2} gasification rate and the RSA estimated by the TK and the TPD methods. Kapteijn et al. showed that the TK method with labeled molecules is more powerful to examine the mechanism. They found the presence of two types of surface oxygen complexes which desorb at different rates. A Square-input response (SIR) method is applied to the carbon-oxygen reaction. This method allows the observation of transient changes on two step changes. This method has been successfully applied to the analysis of a coal char gasification.« less

Algorithm Summary and Evaluation: Automatic Implementation of Ringdown Analysis for Electromechanical Mode Identification from Phasor Measurements

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

Zhou, Ning; Huang, Zhenyu; Tuffner, Francis K.

2010-02-28

Small signal stability problems are one of the major threats to grid stability and reliability. Prony analysis has been successfully applied on ringdown data to monitor electromechanical modes of a power system using phasor measurement unit (PMU) data. To facilitate an on-line application of mode estimation, this paper develops a recursive algorithm for implementing Prony analysis and proposed an oscillation detection method to detect ringdown data in real time. By automatically detecting ringdown data, the proposed method helps guarantee that Prony analysis is applied properly and timely on the ringdown data. Thus, the mode estimation results can be performed reliablymore » and timely. The proposed method is tested using Monte Carlo simulations based on a 17-machine model and is shown to be able to properly identify the oscillation data for on-line application of Prony analysis. In addition, the proposed method is applied to field measurement data from WECC to show the performance of the proposed algorithm.« less

Sorting protein decoys by machine-learning-to-rank

PubMed Central

Jing, Xiaoyang; Wang, Kai; Lu, Ruqian; Dong, Qiwen

2016-01-01

Much progress has been made in Protein structure prediction during the last few decades. As the predicted models can span a broad range of accuracy spectrum, the accuracy of quality estimation becomes one of the key elements of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, and these methods could be roughly divided into three categories: the single-model methods, clustering-based methods and quasi single-model methods. In this study, we develop a single-model method MQAPRank based on the learning-to-rank algorithm firstly, and then implement a quasi single-model method Quasi-MQAPRank. The proposed methods are benchmarked on the 3DRobot and CASP11 dataset. The five-fold cross-validation on the 3DRobot dataset shows the proposed single model method outperforms other methods whose outputs are taken as features of the proposed method, and the quasi single-model method can further enhance the performance. On the CASP11 dataset, the proposed methods also perform well compared with other leading methods in corresponding categories. In particular, the Quasi-MQAPRank method achieves a considerable performance on the CASP11 Best150 dataset. PMID:27530967

Sorting protein decoys by machine-learning-to-rank.

PubMed

Jing, Xiaoyang; Wang, Kai; Lu, Ruqian; Dong, Qiwen

2016-08-17

Much progress has been made in Protein structure prediction during the last few decades. As the predicted models can span a broad range of accuracy spectrum, the accuracy of quality estimation becomes one of the key elements of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, and these methods could be roughly divided into three categories: the single-model methods, clustering-based methods and quasi single-model methods. In this study, we develop a single-model method MQAPRank based on the learning-to-rank algorithm firstly, and then implement a quasi single-model method Quasi-MQAPRank. The proposed methods are benchmarked on the 3DRobot and CASP11 dataset. The five-fold cross-validation on the 3DRobot dataset shows the proposed single model method outperforms other methods whose outputs are taken as features of the proposed method, and the quasi single-model method can further enhance the performance. On the CASP11 dataset, the proposed methods also perform well compared with other leading methods in corresponding categories. In particular, the Quasi-MQAPRank method achieves a considerable performance on the CASP11 Best150 dataset.

Surface EMG decomposition based on K-means clustering and convolution kernel compensation.

PubMed

Ning, Yong; Zhu, Xiangjun; Zhu, Shanan; Zhang, Yingchun

2015-03-01

A new approach has been developed by combining the K-mean clustering (KMC) method and a modified convolution kernel compensation (CKC) method for multichannel surface electromyogram (EMG) decomposition. The KMC method was first utilized to cluster vectors of observations at different time instants and then estimate the initial innervation pulse train (IPT). The CKC method, modified with a novel multistep iterative process, was conducted to update the estimated IPT. The performance of the proposed K-means clustering-Modified CKC (KmCKC) approach was evaluated by reconstructing IPTs from both simulated and experimental surface EMG signals. The KmCKC approach successfully reconstructed all 10 IPTs from the simulated surface EMG signals with true positive rates (TPR) of over 90% with a low signal-to-noise ratio (SNR) of -10 dB. More than 10 motor units were also successfully extracted from the 64-channel experimental surface EMG signals of the first dorsal interosseous (FDI) muscles when a contraction force was held at 8 N by using the KmCKC approach. A "two-source" test was further conducted with 64-channel surface EMG signals. The high percentage of common MUs and common pulses (over 92% at all force levels) between the IPTs reconstructed from the two independent groups of surface EMG signals demonstrates the reliability and capability of the proposed KmCKC approach in multichannel surface EMG decomposition. Results from both simulated and experimental data are consistent and confirm that the proposed KmCKC approach can successfully reconstruct IPTs with high accuracy at different levels of contraction.

Anatomical image-guided fluorescence molecular tomography reconstruction using kernel method

NASA Astrophysics Data System (ADS)

Baikejiang, Reheman; Zhao, Yue; Fite, Brett Z.; Ferrara, Katherine W.; Li, Changqing

2017-05-01

Fluorescence molecular tomography (FMT) is an important in vivo imaging modality to visualize physiological and pathological processes in small animals. However, FMT reconstruction is ill-posed and ill-conditioned due to strong optical scattering in deep tissues, which results in poor spatial resolution. It is well known that FMT image quality can be improved substantially by applying the structural guidance in the FMT reconstruction. An approach to introducing anatomical information into the FMT reconstruction is presented using the kernel method. In contrast to conventional methods that incorporate anatomical information with a Laplacian-type regularization matrix, the proposed method introduces the anatomical guidance into the projection model of FMT. The primary advantage of the proposed method is that it does not require segmentation of targets in the anatomical images. Numerical simulations and phantom experiments have been performed to demonstrate the proposed approach's feasibility. Numerical simulation results indicate that the proposed kernel method can separate two FMT targets with an edge-to-edge distance of 1 mm and is robust to false-positive guidance and inhomogeneity in the anatomical image. For the phantom experiments with two FMT targets, the kernel method has reconstructed both targets successfully, which further validates the proposed kernel method.

Information loss method to measure node similarity in networks

NASA Astrophysics Data System (ADS)

Li, Yongli; Luo, Peng; Wu, Chong

2014-09-01

Similarity measurement for the network node has been paid increasing attention in the field of statistical physics. In this paper, we propose an entropy-based information loss method to measure the node similarity. The whole model is established based on this idea that less information loss is caused by seeing two more similar nodes as the same. The proposed new method has relatively low algorithm complexity, making it less time-consuming and more efficient to deal with the large scale real-world network. In order to clarify its availability and accuracy, this new approach was compared with some other selected approaches on two artificial examples and synthetic networks. Furthermore, the proposed method is also successfully applied to predict the network evolution and predict the unknown nodes' attributions in the two application examples.

Portable system of programmable syringe pump with potentiometer for determination of promethazine in pharmaceutical applications.

PubMed

Saleh, Tawfik A; Abulkibash, A M; Ibrahim, Atta E

2012-04-01

A simple and fast-automated method was developed and validated for the assay of promethazine hydrochloride in pharmaceutical formulations, based on the oxidation of promethazine by cerium in an acidic medium. A portable system, consisting of a programmable syringe pump connected to a potentiometer, was constructed. The developed change in potential during promethazine oxidation was monitored. The related optimum working conditions, such as supporting electrolyte concentration, cerium(IV) concentration and flow rate were optimized. The proposed method was successfully applied to pharmaceutical samples as well as synthetic ones. The obtained results were realized by the official British pharmacopoeia (BP) method and comparable results were obtained. The obtained t-value indicates no significant differences between the results of the proposed and BP methods, with the advantages of the proposed method being simple, sensitive and cost effective.

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 novel shape from focus method based on 3D steerable filters for improved performance on treating textureless region

NASA Astrophysics Data System (ADS)

Fan, Tiantian; Yu, Hongbin

2018-03-01

A novel shape from focus method combining 3D steerable filter for improved performance on treating textureless region was proposed in this paper. Different from conventional spatial methods focusing on the search of maximum edges' response to estimate the depth map, the currently proposed method took both of the edges' response and the axial imaging blur degree into consideration during treatment. As a result, more robust and accurate identification for the focused location can be achieved, especially when treating textureless objects. Improved performance in depth measurement has been successfully demonstrated from both of the simulation and experiment results.

An Evidence Theoretic Approach to Design of Reliable Low-Cost UAVs

DTIC Science & Technology

2009-07-28

given period. For complex systems with various stages of missions, “ success ” becomes hard to define. For a UAV, for example, is success defined as...For this reason, the proposed methods in this thesis investigate probability of failure (PoF ) rather than probability of success . Further, failure will...reduction in system PoF . Figure 25 illustrates this; a single component 43 (A) from the original system (Figure 25a) is modified to act in a subsystem with

An improved graph cut segmentation method for cervical lymph nodes on sonograms and its relationship with node's shape assessment.

PubMed

Zhang, Junhua; Wang, Yuanyuan; Shi, Xinling

2009-12-01

A modified graph cut was proposed under the elliptical shape constraint to segment cervical lymph nodes on sonograms, and its effect on the measurement of short axis to long axis ratio (S/L) was investigated by using the relative ultimate measurement accuracy (RUMA). Under the same user inputs, the proposed algorithm successfully segmented all 60 sonograms tested, while the traditional graph cut failed. The mean RUMA resulted from the developed method was comparable to that resulted from the manual segmentation. Results indicated that utilizing the elliptical shape prior could appreciably improve the graph cut for nodes segmentation, and the proposed method satisfied the accuracy requirement of S/L measurement.

New charging strategy for lithium-ion batteries based on the integration of Taguchi method and state of charge estimation

NASA Astrophysics Data System (ADS)

Vo, Thanh Tu; Chen, Xiaopeng; Shen, Weixiang; Kapoor, Ajay

2015-01-01

In this paper, a new charging strategy of lithium-polymer batteries (LiPBs) has been proposed based on the integration of Taguchi method (TM) and state of charge estimation. The TM is applied to search an optimal charging current pattern. An adaptive switching gain sliding mode observer (ASGSMO) is adopted to estimate the SOC which controls and terminates the charging process. The experimental results demonstrate that the proposed charging strategy can successfully charge the same types of LiPBs with different capacities and cycle life. The proposed charging strategy also provides much shorter charging time, narrower temperature variation and slightly higher energy efficiency than the equivalent constant current constant voltage charging method.

Gas Classification Using Deep Convolutional Neural Networks.

PubMed

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-08

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP).

Gas Classification Using Deep Convolutional Neural Networks

PubMed Central

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-01

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP). PMID:29316723

Microaneurysm detection using fully convolutional neural networks.

PubMed

Chudzik, Piotr; Majumdar, Somshubra; Calivá, Francesco; Al-Diri, Bashir; Hunter, Andrew

2018-05-01

Diabetic retinopathy is a microvascular complication of diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper presents an automatic method for detecting microaneurysms in fundus photographies. A novel patch-based fully convolutional neural network with batch normalization layers and Dice loss function is proposed. Compared to other methods that require up to five processing stages, it requires only three. Furthermore, to the best of the authors' knowledge, this is the first paper that shows how to successfully transfer knowledge between datasets in the microaneurysm detection domain. The proposed method was evaluated using three publicly available and widely used datasets: E-Ophtha, DIARETDB1, and ROC. It achieved better results than state-of-the-art methods using the FROC metric. The proposed algorithm accomplished highest sensitivities for low false positive rates, which is particularly important for screening purposes. Performance, simplicity, and robustness of the proposed method demonstrates its suitability for diabetic retinopathy screening applications. Copyright © 2018 Elsevier B.V. All rights reserved.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

A Doppler Transient Model Based on the Laplace Wavelet and Spectrum Correlation Assessment for Locomotive Bearing Fault Diagnosis

PubMed Central

Shen, Changqing; Liu, Fang; Wang, Dong; Zhang, Ao; Kong, Fanrang; Tse, Peter W.

2013-01-01

The condition of locomotive bearings, which are essential components in trains, is crucial to train safety. The Doppler effect significantly distorts acoustic signals during high movement speeds, substantially increasing the difficulty of monitoring locomotive bearings online. In this study, a new Doppler transient model based on the acoustic theory and the Laplace wavelet is presented for the identification of fault-related impact intervals embedded in acoustic signals. An envelope spectrum correlation assessment is conducted between the transient model and the real fault signal in the frequency domain to optimize the model parameters. The proposed method can identify the parameters used for simulated transients (periods in simulated transients) from acoustic signals. Thus, localized bearing faults can be detected successfully based on identified parameters, particularly period intervals. The performance of the proposed method is tested on a simulated signal suffering from the Doppler effect. Besides, the proposed method is used to analyze real acoustic signals of locomotive bearings with inner race and outer race faults, respectively. The results confirm that the periods between the transients, which represent locomotive bearing fault characteristics, can be detected successfully. PMID:24253191

A Doppler transient model based on the laplace wavelet and spectrum correlation assessment for locomotive bearing fault diagnosis.

PubMed

Shen, Changqing; Liu, Fang; Wang, Dong; Zhang, Ao; Kong, Fanrang; Tse, Peter W

2013-11-18

The condition of locomotive bearings, which are essential components in trains, is crucial to train safety. The Doppler effect significantly distorts acoustic signals during high movement speeds, substantially increasing the difficulty of monitoring locomotive bearings online. In this study, a new Doppler transient model based on the acoustic theory and the Laplace wavelet is presented for the identification of fault-related impact intervals embedded in acoustic signals. An envelope spectrum correlation assessment is conducted between the transient model and the real fault signal in the frequency domain to optimize the model parameters. The proposed method can identify the parameters used for simulated transients (periods in simulated transients) from acoustic signals. Thus, localized bearing faults can be detected successfully based on identified parameters, particularly period intervals. The performance of the proposed method is tested on a simulated signal suffering from the Doppler effect. Besides, the proposed method is used to analyze real acoustic signals of locomotive bearings with inner race and outer race faults, respectively. The results confirm that the periods between the transients, which represent locomotive bearing fault characteristics, can be detected successfully.

Computation of geometric representation of novel spectrophotometric methods used for the analysis of minor components in pharmaceutical preparations.

PubMed

Lotfy, Hayam M; Saleh, Sarah S; Hassan, Nagiba Y; Salem, Hesham

2015-01-01

Novel spectrophotometric methods were applied for the determination of the minor component tetryzoline HCl (TZH) in its ternary mixture with ofloxacin (OFX) and prednisolone acetate (PA) in the ratio of (1:5:7.5), and in its binary mixture with sodium cromoglicate (SCG) in the ratio of (1:80). The novel spectrophotometric methods determined the minor component (TZH) successfully in the two selected mixtures by computing the geometrical relationship of either standard addition or subtraction. The novel spectrophotometric methods are: geometrical amplitude modulation (GAM), geometrical induced amplitude modulation (GIAM), ratio H-point standard addition method (RHPSAM) and compensated area under the curve (CAUC). The proposed methods were successfully applied for the determination of the minor component TZH below its concentration range. The methods were validated as per ICH guidelines where accuracy, repeatability, inter-day precision and robustness were found to be within the acceptable limits. The results obtained from the proposed methods were statistically compared with official ones where no significant difference was observed. No difference was observed between the obtained results when compared to the reported HPLC method, which proved that the developed methods could be alternative to HPLC techniques in quality control laboratories. Copyright © 2015 Elsevier B.V. All rights reserved.

Depth-enhanced integral imaging display system with electrically variable image planes using polymer-dispersed liquid-crystal layers.

PubMed

Kim, Yunhee; Choi, Heejin; Kim, Joohwan; Cho, Seong-Woo; Kim, Youngmin; Park, Gilbae; Lee, Byoungho

2007-06-20

A depth-enhanced three-dimensional integral imaging system with electrically variable image planes is proposed. For implementing the variable image planes, polymer-dispersed liquid-crystal (PDLC) films and a projector are adopted as a new display system in the integral imaging. Since the transparencies of PDLC films are electrically controllable, we can make each film diffuse the projected light successively with a different depth from the lens array. As a result, the proposed method enables control of the location of image planes electrically and enhances the depth. The principle of the proposed method is described, and experimental results are also presented.

Wireless and real-time structural damage detection: A novel decentralized method for wireless sensor networks

NASA Astrophysics Data System (ADS)

Avci, Onur; Abdeljaber, Osama; Kiranyaz, Serkan; Hussein, Mohammed; Inman, Daniel J.

2018-06-01

Being an alternative to conventional wired sensors, wireless sensor networks (WSNs) are extensively used in Structural Health Monitoring (SHM) applications. Most of the Structural Damage Detection (SDD) approaches available in the SHM literature are centralized as they require transferring data from all sensors within the network to a single processing unit to evaluate the structural condition. These methods are found predominantly feasible for wired SHM systems; however, transmission and synchronization of huge data sets in WSNs has been found to be arduous. As such, the application of centralized methods with WSNs has been a challenge for engineers. In this paper, the authors are presenting a novel application of 1D Convolutional Neural Networks (1D CNNs) on WSNs for SDD purposes. The SDD is successfully performed completely wireless and real-time under ambient conditions. As a result of this, a decentralized damage detection method suitable for wireless SHM systems is proposed. The proposed method is based on 1D CNNs and it involves training an individual 1D CNN for each wireless sensor in the network in a format where each CNN is assigned to process the locally-available data only, eliminating the need for data transmission and synchronization. The proposed damage detection method operates directly on the raw ambient vibration condition signals without any filtering or preprocessing. Moreover, the proposed approach requires minimal computational time and power since 1D CNNs merge both feature extraction and classification tasks into a single learning block. This ability is prevailingly cost-effective and evidently practical in WSNs considering the hardware systems have been occasionally reported to suffer from limited power supply in these networks. To display the capability and verify the success of the proposed method, large-scale experiments conducted on a laboratory structure equipped with a state-of-the-art WSN are reported.

A comparative study between three stability indicating spectrophotometric methods for the determination of diatrizoate sodium in presence of its cytotoxic degradation product based on two-wavelength selection

NASA Astrophysics Data System (ADS)

Riad, Safaa M.; El-Rahman, Mohamed K. Abd; Fawaz, Esraa M.; Shehata, Mostafa A.

2015-06-01

Three sensitive, selective, and precise stability indicating spectrophotometric methods for the determination of the X-ray contrast agent, diatrizoate sodium (DTA) in the presence of its acidic degradation product (highly cytotoxic 3,5-diamino metabolite) and in pharmaceutical formulation, were developed and validated. The first method is ratio difference, the second one is the bivariate method, and the third one is the dual wavelength method. The calibration curves for the three proposed methods are linear over a concentration range of 2-24 μg/mL. The selectivity of the proposed methods was tested using laboratory prepared mixtures. The proposed methods have been successfully applied to the analysis of DTA in pharmaceutical dosage forms without interference from other dosage form additives. The results were statistically compared with the official US pharmacopeial method. No significant difference for either accuracy or precision was observed.

A comparative study between three stability indicating spectrophotometric methods for the determination of diatrizoate sodium in presence of its cytotoxic degradation product based on two-wavelength selection.

PubMed

Riad, Safaa M; El-Rahman, Mohamed K Abd; Fawaz, Esraa M; Shehata, Mostafa A

2015-06-15

Three sensitive, selective, and precise stability indicating spectrophotometric methods for the determination of the X-ray contrast agent, diatrizoate sodium (DTA) in the presence of its acidic degradation product (highly cytotoxic 3,5-diamino metabolite) and in pharmaceutical formulation, were developed and validated. The first method is ratio difference, the second one is the bivariate method, and the third one is the dual wavelength method. The calibration curves for the three proposed methods are linear over a concentration range of 2-24 μg/mL. The selectivity of the proposed methods was tested using laboratory prepared mixtures. The proposed methods have been successfully applied to the analysis of DTA in pharmaceutical dosage forms without interference from other dosage form additives. The results were statistically compared with the official US pharmacopeial method. No significant difference for either accuracy or precision was observed. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Design of a dual-mode electrochemical measurement and analysis system.

PubMed

Yang, Jr-Fu; Wei, Chia-Ling; Wu, Jian-Fu; Liu, Bin-Da

2013-01-01

A dual-mode electrochemical measurement and analysis system is proposed. This system includes a dual-mode chip, which was designed and fabricated by using TSMC 0.35 µm 3.3 V/5 V 2P4M mixed-signal CMOS process. Two electrochemical measurement and analysis methods, chronopotentiometry and voltammetry, can be performed by using the proposed chip and system. The proposed chip and system are verified successfully by performing voltammetry and chronopotentiometry on solutions.

Different applications of isosbestic points, normalized spectra and dual wavelength as powerful tools for resolution of multicomponent mixtures with severely overlapping spectra.

PubMed

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

2017-05-25

Analysis of complex mixture containing three or more components represented a challenge for analysts. New smart spectrophotometric methods have been recently evolved with no limitation. A study of different novel and smart spectrophotometric techniques for resolution of severely overlapping spectra were presented in this work utilizing isosbestic points present in different absorption spectra, normalized spectra as a divisor and dual wavelengths. A quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PCT) and para-aminophenol (PAP) was taken as an example for application of the proposed techniques without any separation steps. The adopted techniques adopted of successive and progressive steps manipulating zero /or ratio /or derivative spectra. The proposed techniques includes eight novel and simple methods namely direct spectrophotometry after applying derivative transformation (DT) via multiplying by a decoding spectrum, spectrum subtraction (SS), advanced absorbance subtraction (AAS), advanced amplitude modulation (AAM), simultaneous derivative ratio (S 1 DD), advanced ratio difference (ARD), induced ratio difference (IRD) and finally double divisor-ratio difference-dual wavelength (DD-RD-DW) methods. The proposed methods were assessed by analyzing synthetic mixtures of the studied drugs. They were also successfully applied to commercial pharmaceutical formulations without interference from other dosage form additives. The methods were validated according to the ICH guidelines, accuracy, precision, repeatability, were found to be within the acceptable limits. The proposed procedures are accurate, simple and reproducible and yet economic. They are also sensitive and selective and could be used for routine analysis of complex most of the binary, ternary and quaternary mixtures and even more complex mixtures.

Method of evaluating the impact of ERP implementation critical success factors - a case study in oil and gas industries

NASA Astrophysics Data System (ADS)

Gajic, Gordana; Stankovski, Stevan; Ostojic, Gordana; Tesic, Zdravko; Miladinovic, Ljubomir

2014-01-01

The so far implemented enterprise resource planning (ERP) systems have in many cases failed to meet the requirements regarding the business process control, decrease of business costs and increase of company profit margin. Therefore, there is a real need for an evaluation of the influence of ERP on the company's performance indicators. Proposed in this article is an advanced model for the evaluation of the success of ERP implementation on organisational and operational performance indicators in oil-gas companies. The recommended method establishes a correlation between a process-based method, a scorecard model and ERP critical success factors. The method was verified and tested on two case studies in oil-gas companies using the following procedure: the model was developed, tested and implemented in a pilot gas-oil company, while the results were implemented and verified in another gas-oil company.

Development of a direct patterning method for functional oxide thin films using ultraviolet irradiation and hybrid-cluster gels and its application to thin-film transistor fabrication

NASA Astrophysics Data System (ADS)

Yoshimoto, Yuuki; Li, Jinwang; Shimoda, Tatsuya

2018-04-01

A gel state exists in the solution-solid conversion process. We found that solidification can be promoted by irradiating the gel with ultraviolet (UV) light. In this study, a patterning method without using a vacuum system or employing photoresist materials has been proposed wherein solidification was applied to a gel by UV irradiation. Indium oxide gel, indium gallium oxide gel, lanthanum zirconium oxide gel, and lanthanum ruthenium oxide gels were successfully patterned by using our technique. Moreover, an oxide thin-film transistor was fabricated by our novel patterning method and was successfully operated.

Development of spectrofluorimetric method for determination of certain aminoglycoside drugs in dosage forms and human plasma through condensation with ninhydrin and phenyl acetaldehyde.

PubMed

Omar, Mahmoud A; Hammad, Mohamed A; Nagy, Dalia M; Aly, Alshymaa A

2015-02-05

A simple and sensitive spectrofluorimetric method has been developed and validated for determination of amikacin sulfate, neomycin sulfate and tobramycin in pure forms, pharmaceutical formulations and human plasma. The method was based on condensation reaction of cited drugs with ninhydrin and phenylacetaldehyde in buffered medium (pH 6) resulting in formation of fluorescent products which exhibit excitation and emission maxima at 395 and 470nm, respectively. The different experimental parameters affecting the development and stability of the reaction products were carefully studied and optimized. The calibration plots were constructed with good correlation coefficients (0.9993 for tobramycin and 0.9996 for both neomycin and amikacin). The proposed method was successfully applied for the analysis of cited drugs in dosage forms with high accuracy (98.33-101.7)±(0.80-1.26)%. The results show an excellent agreement with the reference method, indicating no significant difference in accuracy and precision. Due to its high sensitivity, the proposed method was applied successfully for determination of amikacin in real human plasma. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel 3D deformation measurement method under optical microscope for micro-scale bulge-test

NASA Astrophysics Data System (ADS)

Wu, Dan; Xie, Huimin

2017-11-01

A micro-scale 3D deformation measurement method combined with optical microscope is proposed in this paper. The method is based on gratings and phase shifting algorithm. By recording the grating images before and after deformation from two symmetrical angles and calculating the phases of the grating patterns, the 3D deformation field of the specimen can be extracted from the phases of the grating patterns. The proposed method was applied to the micro-scale bulge test. A micro-scale thermal/mechanical coupling bulge-test apparatus matched with the super-depth microscope was exploited. With the gratings fabricated onto the film, the deformed morphology of the bulged film was measured reliably. The experimental results show that the proposed method and the exploited bulge-test apparatus can be used to characterize the thermal/mechanical properties of the films at micro-scale successfully.

Portable system of programmable syringe pump with potentiometer for determination of promethazine in pharmaceutical applications

PubMed Central

Saleh, Tawfik A.; Abulkibash, A.M.; Ibrahim, Atta E.

2011-01-01

A simple and fast-automated method was developed and validated for the assay of promethazine hydrochloride in pharmaceutical formulations, based on the oxidation of promethazine by cerium in an acidic medium. A portable system, consisting of a programmable syringe pump connected to a potentiometer, was constructed. The developed change in potential during promethazine oxidation was monitored. The related optimum working conditions, such as supporting electrolyte concentration, cerium(IV) concentration and flow rate were optimized. The proposed method was successfully applied to pharmaceutical samples as well as synthetic ones. The obtained results were realized by the official British pharmacopoeia (BP) method and comparable results were obtained. The obtained t-value indicates no significant differences between the results of the proposed and BP methods, with the advantages of the proposed method being simple, sensitive and cost effective. PMID:23960787

Successive approximation-like 4-bit full-optical analog-to-digital converter based on Kerr-like nonlinear photonic crystal ring resonators

NASA Astrophysics Data System (ADS)

Tavousi, Alireza; Mansouri-Birjandi, Mohammad Ali; Saffari, Mehdi

2016-09-01

Implementing of photonic sampling and quantizing analog-to-digital converters (ADCs) enable us to extract a single binary word from optical signals without need for extra electronic assisting parts. This would enormously increase the sampling and quantizing time as well as decreasing the consumed power. To this end, based on the concept of successive approximation method, a 4-bit full-optical ADC that operates using the intensity-dependent Kerr-like nonlinearity in a two dimensional photonic crystal (2DPhC) platform is proposed. The Silicon (Si) nanocrystal is chosen because of the suitable nonlinear material characteristic. An optical limiter is used for the clamping and quantization of each successive levels that represent the ADC bits. In the proposal, an energy efficient optical ADC circuit is implemented by controlling the system parameters such as ring-to-waveguide coupling coefficients, the ring's nonlinear refractive index, and the ring's length. The performance of the ADC structure is verified by the simulation using finite difference time domain (FDTD) method.

Derivative spectrophotometric method for simultaneous determination of clindamycin phosphate and tretinoin in pharmaceutical dosage forms.

PubMed

Barazandeh Tehrani, Maliheh; Namadchian, Melika; Fadaye Vatan, Sedigheh; Souri, Effat

2013-04-10

A derivative spectrophotometric method was proposed for the simultaneous determination of clindamycin and tretinoin in pharmaceutical dosage forms. The measurement was achieved using the first and second derivative signals of clindamycin at (1D) 251 nm and (2D) 239 nm and tretinoin at (1D) 364 nm and (2D) 387 nm.The proposed method showed excellent linearity at both first and second derivative order in the range of 60-1200 and 1.25-25 μg/ml for clindamycin phosphate and tretinoin respectively. The within-day and between-day precision and accuracy was in acceptable range (CV<3.81%, error<3.20%). Good agreement between the found andadded concentrations indicates successful application of the proposed method for simultaneous determination of clindamycin and tretinoin in synthetic mixtures and pharmaceutical dosage form.

Predicting missing values in a home care database using an adaptive uncertainty rule method.

PubMed

Konias, S; Gogou, G; Bamidis, P D; Vlahavas, I; Maglaveras, N

2005-01-01

Contemporary literature illustrates an abundance of adaptive algorithms for mining association rules. However, most literature is unable to deal with the peculiarities, such as missing values and dynamic data creation, that are frequently encountered in fields like medicine. This paper proposes an uncertainty rule method that uses an adaptive threshold for filling missing values in newly added records. A new approach for mining uncertainty rules and filling missing values is proposed, which is in turn particularly suitable for dynamic databases, like the ones used in home care systems. In this study, a new data mining method named FiMV (Filling Missing Values) is illustrated based on the mined uncertainty rules. Uncertainty rules have quite a similar structure to association rules and are extracted by an algorithm proposed in previous work, namely AURG (Adaptive Uncertainty Rule Generation). The main target was to implement an appropriate method for recovering missing values in a dynamic database, where new records are continuously added, without needing to specify any kind of thresholds beforehand. The method was applied to a home care monitoring system database. Randomly, multiple missing values for each record's attributes (rate 5-20% by 5% increments) were introduced in the initial dataset. FiMV demonstrated 100% completion rates with over 90% success in each case, while usual approaches, where all records with missing values are ignored or thresholds are required, experienced significantly reduced completion and success rates. It is concluded that the proposed method is appropriate for the data-cleaning step of the Knowledge Discovery process in databases. The latter, containing much significance for the output efficiency of any data mining technique, can improve the quality of the mined information.

Solving rational matrix equations in the state space with applications to computer-aided control-system design

NASA Technical Reports Server (NTRS)

Packard, A. K.; Sastry, S. S.

1986-01-01

A method of solving a class of linear matrix equations over various rings is proposed, using results from linear geometric control theory. An algorithm, successfully implemented, is presented, along with non-trivial numerical examples. Applications of the method to the algebraic control system design methodology are discussed.

Rolling bearing fault diagnosis and health assessment using EEMD and the adjustment Mahalanobis-Taguchi system

NASA Astrophysics Data System (ADS)

Chen, Junxun; Cheng, Longsheng; Yu, Hui; Hu, Shaolin

2018-01-01