Generalised Category Attack—Improving Histogram-Based Attack on JPEG LSB Embedding

NASA Astrophysics Data System (ADS)

Lee, Kwangsoo; Westfeld, Andreas; Lee, Sangjin

We present a generalised and improved version of the category attack on LSB steganography in JPEG images with straddled embedding path. It detects more reliably low embedding rates and is also less disturbed by double compressed images. The proposed methods are evaluated on several thousand images. The results are compared to both recent blind and specific attacks for JPEG embedding. The proposed attack permits a more reliable detection, although it is based on first order statistics only. Its simple structure makes it very fast.

Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding

PubMed Central

Tajima, Satohiro; Yanagawa, Toru; Fujii, Naotaka; Toyoizumi, Taro

2015-01-01

Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness. PMID:26584045

Embedding beyond electrostatics-The role of wave function confinement.

PubMed

Nåbo, Lina J; Olsen, Jógvan Magnus Haugaard; Holmgaard List, Nanna; Solanko, Lukasz M; Wüstner, Daniel; Kongsted, Jacob

2016-09-14

We study excited states of cholesterol in solution and show that, in this specific case, solute wave-function confinement is the main effect of the solvent. This is rationalized on the basis of the polarizable density embedding scheme, which in addition to polarizable embedding includes non-electrostatic repulsion that effectively confines the solute wave function to its cavity. We illustrate how the inclusion of non-electrostatic repulsion results in a successful identification of the intense π → π(∗) transition, which was not possible using an embedding method that only includes electrostatics. This underlines the importance of non-electrostatic repulsion in quantum-mechanical embedding-based methods.

A real-time spike sorting method based on the embedded GPU.

PubMed

Zelan Yang; Kedi Xu; Xiang Tian; Shaomin Zhang; Xiaoxiang Zheng

2017-07-01

Microelectrode arrays with hundreds of channels have been widely used to acquire neuron population signals in neuroscience studies. Online spike sorting is becoming one of the most important challenges for high-throughput neural signal acquisition systems. Graphic processing unit (GPU) with high parallel computing capability might provide an alternative solution for increasing real-time computational demands on spike sorting. This study reported a method of real-time spike sorting through computing unified device architecture (CUDA) which was implemented on an embedded GPU (NVIDIA JETSON Tegra K1, TK1). The sorting approach is based on the principal component analysis (PCA) and K-means. By analyzing the parallelism of each process, the method was further optimized in the thread memory model of GPU. Our results showed that the GPU-based classifier on TK1 is 37.92 times faster than the MATLAB-based classifier on PC while their accuracies were the same with each other. The high-performance computing features of embedded GPU demonstrated in our studies suggested that the embedded GPU provide a promising platform for the real-time neural signal processing.

Computational Efficiency of the Simplex Embedding Method in Convex Nondifferentiable Optimization

NASA Astrophysics Data System (ADS)

Kolosnitsyn, A. V.

2018-02-01

The simplex embedding method for solving convex nondifferentiable optimization problems is considered. A description of modifications of this method based on a shift of the cutting plane intended for cutting off the maximum number of simplex vertices is given. These modification speed up the problem solution. A numerical comparison of the efficiency of the proposed modifications based on the numerical solution of benchmark convex nondifferentiable optimization problems is presented.

Systematic Model-in-the-Loop Test of Embedded Control Systems

NASA Astrophysics Data System (ADS)

Krupp, Alexander; Müller, Wolfgang

Current model-based development processes offer new opportunities for verification automation, e.g., in automotive development. The duty of functional verification is the detection of design flaws. Current functional verification approaches exhibit a major gap between requirement definition and formal property definition, especially when analog signals are involved. Besides lack of methodical support for natural language formalization, there does not exist a standardized and accepted means for formal property definition as a target for verification planning. This article addresses several shortcomings of embedded system verification. An Enhanced Classification Tree Method is developed based on the established Classification Tree Method for Embeded Systems CTM/ES which applies a hardware verification language to define a verification environment.

Delay differential analysis of time series.

PubMed

Lainscsek, Claudia; Sejnowski, Terrence J

2015-03-01

Nonlinear dynamical system analysis based on embedding theory has been used for modeling and prediction, but it also has applications to signal detection and classification of time series. An embedding creates a multidimensional geometrical object from a single time series. Traditionally either delay or derivative embeddings have been used. The delay embedding is composed of delayed versions of the signal, and the derivative embedding is composed of successive derivatives of the signal. The delay embedding has been extended to nonuniform embeddings to take multiple timescales into account. Both embeddings provide information on the underlying dynamical system without having direct access to all the system variables. Delay differential analysis is based on functional embeddings, a combination of the derivative embedding with nonuniform delay embeddings. Small delay differential equation (DDE) models that best represent relevant dynamic features of time series data are selected from a pool of candidate models for detection or classification. We show that the properties of DDEs support spectral analysis in the time domain where nonlinear correlation functions are used to detect frequencies, frequency and phase couplings, and bispectra. These can be efficiently computed with short time windows and are robust to noise. For frequency analysis, this framework is a multivariate extension of discrete Fourier transform (DFT), and for higher-order spectra, it is a linear and multivariate alternative to multidimensional fast Fourier transform of multidimensional correlations. This method can be applied to short or sparse time series and can be extended to cross-trial and cross-channel spectra if multiple short data segments of the same experiment are available. Together, this time-domain toolbox provides higher temporal resolution, increased frequency and phase coupling information, and it allows an easy and straightforward implementation of higher-order spectra across time compared with frequency-based methods such as the DFT and cross-spectral analysis.

Privacy protection in surveillance systems based on JPEG DCT baseline compression and spectral domain watermarking

NASA Astrophysics Data System (ADS)

Sablik, Thomas; Velten, Jörg; Kummert, Anton

2015-03-01

An novel system for automatic privacy protection in digital media based on spectral domain watermarking and JPEG compression is described in the present paper. In a first step private areas are detected. Therefore a detection method is presented. The implemented method uses Haar cascades to detects faces. Integral images are used to speed up calculations and the detection. Multiple detections of one face are combined. Succeeding steps comprise embedding the data into the image as part of JPEG compression using spectral domain methods and protecting the area of privacy. The embedding process is integrated into and adapted to JPEG compression. A Spread Spectrum Watermarking method is used to embed the size and position of the private areas into the cover image. Different methods for embedding regarding their robustness are compared. Moreover the performance of the method concerning tampered images is presented.

Virtual network embedding in cross-domain network based on topology and resource attributes

NASA Astrophysics Data System (ADS)

Zhu, Lei; Zhang, Zhizhong; Feng, Linlin; Liu, Lilan

2018-03-01

Aiming at the network architecture ossification and the diversity of access technologies issues, this paper researches the cross-domain virtual network embedding algorithm. By analysing the topological attribute from the local and global perspective of nodes in the virtual network and the physical network, combined with the local network resource property, we rank the embedding priority of the nodes with PCA and TOPSIS methods. Besides, the link load distribution is considered. Above all, We proposed an cross-domain virtual network embedding algorithm based on topology and resource attributes. The simulation results depicts that our algorithm increases the acceptance rate of multi-domain virtual network requests, compared with the existing virtual network embedding algorithm.

Research on Generating Method of Embedded Software Test Document Based on Dynamic Model

NASA Astrophysics Data System (ADS)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

2018-03-01

This paper provides a dynamic model-based test document generation method for embedded software that provides automatic generation of two documents: test requirements specification documentation and configuration item test documentation. This method enables dynamic test requirements to be implemented in dynamic models, enabling dynamic test demand tracking to be easily generated; able to automatically generate standardized, standardized test requirements and test documentation, improved document-related content inconsistency and lack of integrity And other issues, improve the efficiency.

Time delayed Ensemble Nudging Method

NASA Astrophysics Data System (ADS)

An, Zhe; Abarbanel, Henry

Optimal nudging method based on time delayed embedding theory has shows potentials on analyzing and data assimilation in previous literatures. To extend the application and promote the practical implementation, new nudging assimilation method based on the time delayed embedding space is presented and the connection with other standard assimilation methods are studied. Results shows the incorporating information from the time series of data can reduce the sufficient observation needed to preserve the quality of numerical prediction, making it a potential alternative in the field of data assimilation of large geophysical models.

Nonschematic drawing recognition: a new approach based on attributed graph grammar with flexible embedding

NASA Astrophysics Data System (ADS)

Lee, Kyu J.; Kunii, T. L.; Noma, T.

1993-01-01

In this paper, we propose a syntactic pattern recognition method for non-schematic drawings, based on a new attributed graph grammar with flexible embedding. In our graph grammar, the embedding rule permits the nodes of a guest graph to be arbitrarily connected with the nodes of a host graph. The ambiguity caused by this flexible embedding is controlled with the evaluation of synthesized attributes and the check of context sensitivity. To integrate parsing with the synthesized attribute evaluation and the context sensitivity check, we also develop a bottom up parsing algorithm.

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

The data embedding method

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

Sandford, M.T. II; Bradley, J.N.; Handel, T.G.

Data embedding is a new steganographic method for combining digital information sets. This paper describes the data embedding method and gives examples of its application using software written in the C-programming language. Sandford and Handel produced a computer program (BMPEMBED, Ver. 1.51 written for IBM PC/AT or compatible, MS/DOS Ver. 3.3 or later) that implements data embedding in an application for digital imagery. Information is embedded into, and extracted from, Truecolor or color-pallet images in Microsoft{reg_sign} bitmap (.BMP) format. Hiding data in the noise component of a host, by means of an algorithm that modifies or replaces the noise bits,more » is termed {open_quote}steganography.{close_quote} Data embedding differs markedly from conventional steganography, because it uses the noise component of the host to insert information with few or no modifications to the host data values or their statistical properties. Consequently, the entropy of the host data is affected little by using data embedding to add information. The data embedding method applies to host data compressed with transform, or {open_quote}lossy{close_quote} compression algorithms, as for example ones based on discrete cosine transform and wavelet functions. Analysis of the host noise generates a key required for embedding and extracting the auxiliary data from the combined data. The key is stored easily in the combined data. Images without the key cannot be processed to extract the embedded information. To provide security for the embedded data, one can remove the key from the combined data and manage it separately. The image key can be encrypted and stored in the combined data or transmitted separately as a ciphertext much smaller in size than the embedded data. The key size is typically ten to one-hundred bytes, and it is in data an analysis algorithm.« less

Data embedding method

NASA Astrophysics Data System (ADS)

Sandford, Maxwell T., II; Bradley, Jonathan N.; Handel, Theodore G.

1996-01-01

Data embedding is a new steganographic method for combining digital information sets. This paper describes the data embedding method and gives examples of its application using software written in the C-programming language. Sandford and Handel produced a computer program (BMPEMBED, Ver. 1.51 written for IBM PC/AT or compatible, MS/DOS Ver. 3.3 or later) that implements data embedding in an application for digital imagery. Information is embedded into, and extracted from, Truecolor or color-pallet images in MicrosoftTM bitmap (BMP) format. Hiding data in the noise component of a host, by means of an algorithm that modifies or replaces the noise bits, is termed `steganography.' Data embedding differs markedly from conventional steganography, because it uses the noise component of the host to insert information with few or no modifications to the host data values or their statistical properties. Consequently, the entropy of the host data is affected little by using data embedding to add information. The data embedding method applies to host data compressed with transform, or `lossy' compression algorithms, as for example ones based on discrete cosine transform and wavelet functions. Analysis of the host noise generates a key required for embedding and extracting the auxiliary data from the combined data. The key is stored easily in the combined data. Images without the key cannot be processed to extract the embedded information. To provide security for the embedded data, one can remove the key from the combined data and manage it separately. The image key can be encrypted and stored in the combined data or transmitted separately as a ciphertext much smaller in size than the embedded data. The key size is typically ten to one-hundred bytes, and it is derived from the original host data by an analysis algorithm.

Streamflow Prediction based on Chaos Theory

NASA Astrophysics Data System (ADS)

Li, X.; Wang, X.; Babovic, V. M.

2015-12-01

Chaos theory is a popular method in hydrologic time series prediction. Local model (LM) based on this theory utilizes time-delay embedding to reconstruct the phase-space diagram. For this method, its efficacy is dependent on the embedding parameters, i.e. embedding dimension, time lag, and nearest neighbor number. The optimal estimation of these parameters is thus critical to the application of Local model. However, these embedding parameters are conventionally estimated using Average Mutual Information (AMI) and False Nearest Neighbors (FNN) separately. This may leads to local optimization and thus has limitation to its prediction accuracy. Considering about these limitation, this paper applies a local model combined with simulated annealing (SA) to find the global optimization of embedding parameters. It is also compared with another global optimization approach of Genetic Algorithm (GA). These proposed hybrid methods are applied in daily and monthly streamflow time series for examination. The results show that global optimization can contribute to the local model to provide more accurate prediction results compared with local optimization. The LM combined with SA shows more advantages in terms of its computational efficiency. The proposed scheme here can also be applied to other fields such as prediction of hydro-climatic time series, error correction, etc.

Study of Composite Plate Damages Using Embedded PZT Sensors with Various Center Frequency

NASA Astrophysics Data System (ADS)

Kang, Kyoung-Tak; Chun, Heoung-Jae; Son, Ju-Hyun; Byun, Joon-Hyung; Um, Moon-Kwang; Lee, Sang-Kwan

This study presents part of an experimental and analytical survey of candidate methods for damage detection of composite structural. Embedded piezoceramic (PZT) sensors were excited with the high power ultrasonic wave generator generating a propagation of stress wave along the composite plate. The same embedded piezoceramic (PZT) sensors are used as receivers for acquiring stress signals. The effects of center frequency of embedded sensor were evaluated for the damage identification capability with known localized defects. The study was carried out to assess damage in composite plate by fusing information from multiple sensing paths of the embedded network. It was based on the Hilbert transform, signal correlation and probabilistic searching. The obtained results show that satisfactory detection of defects could be achieved by proposed method.

Molecular properties via a subsystem density functional theory formulation: a common framework for electronic embedding.

PubMed

Höfener, Sebastian; Gomes, André Severo Pereira; Visscher, Lucas

2012-01-28

In this article, we present a consistent derivation of a density functional theory (DFT) based embedding method which encompasses wave-function theory-in-DFT (WFT-in-DFT) and the DFT-based subsystem formulation of response theory (DFT-in-DFT) by Neugebauer [J. Neugebauer, J. Chem. Phys. 131, 084104 (2009)] as special cases. This formulation, which is based on the time-averaged quasi-energy formalism, makes use of the variation Lagrangian techniques to allow the use of non-variational (in particular: coupled cluster) wave-function-based methods. We show how, in the time-independent limit, we naturally obtain expressions for the ground-state DFT-in-DFT and WFT-in-DFT embedding via a local potential. We furthermore provide working equations for the special case in which coupled cluster theory is used to obtain the density and excitation energies of the active subsystem. A sample application is given to demonstrate the method. © 2012 American Institute of Physics

Extracting similar terms from multiple EMR-based semantic embeddings to support chart reviews.

PubMed

Cheng Ye, M S; Fabbri, Daniel

2018-05-21

Word embeddings project semantically similar terms into nearby points in a vector space. When trained on clinical text, these embeddings can be leveraged to improve keyword search and text highlighting. In this paper, we present methods to refine the selection process of similar terms from multiple EMR-based word embeddings, and evaluate their performance quantitatively and qualitatively across multiple chart review tasks. Word embeddings were trained on each clinical note type in an EMR. These embeddings were then combined, weighted, and truncated to select a refined set of similar terms to be used in keyword search and text highlighting. To evaluate their quality, we measured the similar terms' information retrieval (IR) performance using precision-at-K (P@5, P@10). Additionally a user study evaluated users' search term preferences, while a timing study measured the time to answer a question from a clinical chart. The refined terms outperformed the baseline method's information retrieval performance (e.g., increasing the average P@5 from 0.48 to 0.60). Additionally, the refined terms were preferred by most users, and reduced the average time to answer a question. Clinical information can be more quickly retrieved and synthesized when using semantically similar term from multiple embeddings. Copyright © 2018. Published by Elsevier Inc.

A molecular method to assess bioburden embedded within silicon-based resins used on modern spacecraft materials

NASA Astrophysics Data System (ADS)

Stam, Christina N.; Bruckner, James; Spry, J. Andy; Venkateswaran, Kasthuri; La Duc, Myron T.

2012-07-01

Current assessments of bioburden embedded in spacecraft materials are based on work performed in the Viking era (1970s), and the ability to culture organisms extracted from such materials. To circumvent the limitations of such approaches, DNA-based techniques were evaluated alongside established culturing techniques to determine the recovery and survival of bacterial spores encapsulated in spacecraft-qualified polymer materials. Varying concentrations of Bacillus pumilus SAFR-032 spores were completely embedded in silicone epoxy. An organic dimethylacetamide-based solvent was used to digest the epoxy and spore recovery was evaluated via gyrB-targeted qPCR, direct agar plating, most probably number analysis, and microscopy. Although full-strength solvent was shown to inhibit the germination and/or outgrowth of spores, dilution in excess of 100-fold allowed recovery with no significant decrease in cultivability. Similarly, qPCR (quantitative PCR) detection sensitivities as low as ~103 CFU ml-1 were achieved upon removal of inhibitory substances associated with the epoxy and/or solvent. These detection and enumeration methods show promise for use in assessing the embedded bioburden of spacecraft hardware.

Developing a multimodal biometric authentication system using soft computing methods.

PubMed

Malcangi, Mario

2015-01-01

Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.

Extending density functional embedding theory for covalently bonded systems.

PubMed

Yu, Kuang; Carter, Emily A

2017-12-19

Quantum embedding theory aims to provide an efficient solution to obtain accurate electronic energies for systems too large for full-scale, high-level quantum calculations. It adopts a hierarchical approach that divides the total system into a small embedded region and a larger environment, using different levels of theory to describe each part. Previously, we developed a density-based quantum embedding theory called density functional embedding theory (DFET), which achieved considerable success in metals and semiconductors. In this work, we extend DFET into a density-matrix-based nonlocal form, enabling DFET to study the stronger quantum couplings between covalently bonded subsystems. We name this theory density-matrix functional embedding theory (DMFET), and we demonstrate its performance in several test examples that resemble various real applications in both chemistry and biochemistry. DMFET gives excellent results in all cases tested thus far, including predicting isomerization energies, proton transfer energies, and highest occupied molecular orbital-lowest unoccupied molecular orbital gaps for local chromophores. Here, we show that DMFET systematically improves the quality of the results compared with the widely used state-of-the-art methods, such as the simple capped cluster model or the widely used ONIOM method.

Integrated narrowband optical filter based on embedded subwavelength resonant grating structures

DOEpatents

Grann, Eric B.; Sitter, Jr., David N.

2000-01-01

A resonant grating structure in a waveguide and methods of tuning the performance of the grating structure are described. An apparatus includes a waveguide; and a subwavelength resonant grating structure embedded in the waveguide. The systems and methods provide advantages including narrowband filtering capabilities, minimal sideband reflections, spatial control, high packing density, and tunability.

Application of RT-PCR in formalin-fixed and paraffin-embedded lung cancer tissues.

PubMed

Zhang, Fan; Wang, Zhuo-min; Liu, Hong-yu; Bai, Yun; Wei, Sen; Li, Ying; Wang, Min; Chen, Jun; Zhou, Qing-hua

2010-01-01

To analyze gene expression in formalin-fixed, paraffin-embedded lung cancer tissues using modified method. Total RNA from frozen tissues was extracted using TRIZOL reagent. RNA was extracted from formalin-fixed, paraffin-embedded tissues by digestion with proteinase K before the acid-phenol:chloroform extraction and carrier precipitation. We modified this method by using a higher concentration of proteinase K and a longer digestion time, optimized to 16 hours. RT-PCR and real-time RT-PCR were used to check reproducibility and the concordance between frozen and paraffin-embedded samples. The results showed that the RNA extracted from the paraffin-embedded lung tissues had high quality with the most fragment length between 28S and 18S bands (about 1000 to 2000 bases). The housekeeping gene GUSB exhibited low variation of expression in frozen and paraffin-embedded lung tissues, whereas PGK1 had the lowest variation in lymphoma tissues. Furthermore, real-time PCR analysis of the expression of known prognostic genes in non-small cell lung carcinoma (NSCLC) demonstrated an extremely high correlation (r>0.880) between the paired frozen and formalin-fixed, paraffin-embedded specimens. This improved method of RNA extraction is suitable for real-time quantitative RT-PCR, and may be used for global gene expression profiling of paraffin-embedded tissues.

Non-integer expansion embedding techniques for reversible image watermarking

NASA Astrophysics Data System (ADS)

Xiang, Shijun; Wang, Yi

2015-12-01

This work aims at reducing the embedding distortion of prediction-error expansion (PE)-based reversible watermarking. In the classical PE embedding method proposed by Thodi and Rodriguez, the predicted value is rounded to integer number for integer prediction-error expansion (IPE) embedding. The rounding operation makes a constraint on a predictor's performance. In this paper, we propose a non-integer PE (NIPE) embedding approach, which can proceed non-integer prediction errors for embedding data into an audio or image file by only expanding integer element of a prediction error while keeping its fractional element unchanged. The advantage of the NIPE embedding technique is that the NIPE technique can really bring a predictor into full play by estimating a sample/pixel in a noncausal way in a single pass since there is no rounding operation. A new noncausal image prediction method to estimate a pixel with four immediate pixels in a single pass is included in the proposed scheme. The proposed noncausal image predictor can provide better performance than Sachnev et al.'s noncausal double-set prediction method (where data prediction in two passes brings a distortion problem due to the fact that half of the pixels were predicted with the watermarked pixels). In comparison with existing several state-of-the-art works, experimental results have shown that the NIPE technique with the new noncausal prediction strategy can reduce the embedding distortion for the same embedding payload.

Supervised linear dimensionality reduction with robust margins for object recognition

NASA Astrophysics Data System (ADS)

Dornaika, F.; Assoum, A.

2013-01-01

Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.

Embedded Professional Development and Classroom-Based Early Reading Intervention: Early Diagnostic Reading Intervention through Coaching

ERIC Educational Resources Information Center

Amendum, Steven J.

2014-01-01

The purpose of the current mixed-methods study was to investigate a model of professional development and classroom-based early reading intervention implemented by the 1st-grade teaching team in a large urban/suburban school district in the southeastern United States. The intervention provided teachers with ongoing embedded professional…

Self-consistent Green's function embedding for advanced electronic structure methods based on a dynamical mean-field concept

NASA Astrophysics Data System (ADS)

Chibani, Wael; Ren, Xinguo; Scheffler, Matthias; Rinke, Patrick

2016-04-01

We present an embedding scheme for periodic systems that facilitates the treatment of the physically important part (here a unit cell or a supercell) with advanced electronic structure methods, that are computationally too expensive for periodic systems. The rest of the periodic system is treated with computationally less demanding approaches, e.g., Kohn-Sham density-functional theory, in a self-consistent manner. Our scheme is based on the concept of dynamical mean-field theory formulated in terms of Green's functions. Our real-space dynamical mean-field embedding scheme features two nested Dyson equations, one for the embedded cluster and another for the periodic surrounding. The total energy is computed from the resulting Green's functions. The performance of our scheme is demonstrated by treating the embedded region with hybrid functionals and many-body perturbation theory in the GW approach for simple bulk systems. The total energy and the density of states converge rapidly with respect to the computational parameters and approach their bulk limit with increasing cluster (i.e., computational supercell) size.

Reliability Analysis and Optimal Release Problem Considering Maintenance Time of Software Components for an Embedded OSS Porting Phase

NASA Astrophysics Data System (ADS)

Tamura, Yoshinobu; Yamada, Shigeru

OSS (open source software) systems which serve as key components of critical infrastructures in our social life are still ever-expanding now. Especially, embedded OSS systems have been gaining a lot of attention in the embedded system area, i.e., Android, BusyBox, TRON, etc. However, the poor handling of quality problem and customer support prohibit the progress of embedded OSS. Also, it is difficult for developers to assess the reliability and portability of embedded OSS on a single-board computer. In this paper, we propose a method of software reliability assessment based on flexible hazard rates for the embedded OSS. Also, we analyze actual data of software failure-occurrence time-intervals to show numerical examples of software reliability assessment for the embedded OSS. Moreover, we compare the proposed hazard rate model for the embedded OSS with the typical conventional hazard rate models by using the comparison criteria of goodness-of-fit. Furthermore, we discuss the optimal software release problem for the porting-phase based on the total expected software maintenance cost.

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

PubMed

Tohka, Jussi; Moradi, Elaheh; Huttunen, Heikki

2016-07-01

We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons of the accuracy of various classification methods have been reported previously, the variability of the out-of-training sample classification accuracy and the set of selected features due to independent training and test sets have not been previously addressed in a brain imaging context. We studied two classification problems: 1) Alzheimer's disease (AD) vs. normal control (NC) and 2) mild cognitive impairment (MCI) vs. NC classification. In AD vs. NC classification, the variability in the test accuracy due to the subject sample did not vary between different methods and exceeded the variability due to different classifiers. In MCI vs. NC classification, particularly with a large training set, embedded feature selection methods outperformed SVM-based ones with the difference in the test accuracy exceeding the test accuracy variability due to the subject sample. The filter and embedded methods produced divergent feature patterns for MCI vs. NC classification that suggests the utility of the embedded feature selection for this problem when linked with the good generalization performance. The stability of the feature sets was strongly correlated with the number of features selected, weakly correlated with the stability of classification accuracy, and uncorrelated with the average classification accuracy.

Image segmentation-based robust feature extraction for color image watermarking

NASA Astrophysics Data System (ADS)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Word embeddings and recurrent neural networks based on Long-Short Term Memory nodes in supervised biomedical word sense disambiguation.

PubMed

Jimeno Yepes, Antonio

2017-09-01

Word sense disambiguation helps identifying the proper sense of ambiguous words in text. With large terminologies such as the UMLS Metathesaurus ambiguities appear and highly effective disambiguation methods are required. Supervised learning algorithm methods are used as one of the approaches to perform disambiguation. Features extracted from the context of an ambiguous word are used to identify the proper sense of such a word. The type of features have an impact on machine learning methods, thus affect disambiguation performance. In this work, we have evaluated several types of features derived from the context of the ambiguous word and we have explored as well more global features derived from MEDLINE using word embeddings. Results show that word embeddings improve the performance of more traditional features and allow as well using recurrent neural network classifiers based on Long-Short Term Memory (LSTM) nodes. The combination of unigrams and word embeddings with an SVM sets a new state of the art performance with a macro accuracy of 95.97 in the MSH WSD data set. Copyright © 2017 Elsevier Inc. All rights reserved.

Tailoring plasmonic properties of metal nanoparticle-embedded dielectric thin films: the sandwich method of preparation

NASA Astrophysics Data System (ADS)

Laha, Ranjit; Malar, P.; Osipowicz, Thomas; Kasiviswanathan, S.

2017-09-01

Tailoring of plasmonic properties of metal nanoparticle-embedded dielectric thin films are very crucial for many thin film-based applications. We, herein, investigate the various ways of tuning the plasmonic positions of gold nanoparticles (AuNPs)-embedded indium oxide thin films (Au:IO) through a sequence-specific sandwich method. The sandwich method is a four-step process involving deposition of In2O3 film by magnetron sputtering in first and fourth steps, thermal evaporation of Au on to In2O3 film in second and annealing of Au/In2O3 film in the third step. The Au:IO films were characterized by x-ray diffraction, spectrophotometry and transmission electron microscopy. The size and shape of the embedded nanoparticles were found from Rutherford back-scattering spectrometry. Based on dynamic Maxwell Garnett theory, the observed plasmon resonance position was ascribed to the oblate shape of AuNPs formed in sandwich method. Finally, through experimental data, it was shown that the plasmon resonance position of Au:IO thin films can be tuned by 125 nm. The method shown here can be used to tune the plasmon resonance position over the entire range of visible region for the thin films made from other combinations of metal-dielectric pair.

A novel edge based embedding in medical images based on unique key generated using sudoku puzzle design.

PubMed

Santhi, B; Dheeptha, B

2016-01-01

The field of telemedicine has gained immense momentum, owing to the need for transmitting patients' information securely. This paper puts forth a unique method for embedding data in medical images. It is based on edge based embedding and XOR coding. The algorithm proposes a novel key generation technique by utilizing the design of a sudoku puzzle to enhance the security of the transmitted message. The edge blocks of the cover image alone, are utilized to embed the payloads. The least significant bit of the pixel values are changed by XOR coding depending on the data to be embedded and the key generated. Hence the distortion in the stego image is minimized and the information is retrieved accurately. Data is embedded in the RGB planes of the cover image, thus increasing its embedding capacity. Several measures including peak signal noise ratio (PSNR), mean square error (MSE), universal image quality index (UIQI) and correlation coefficient (R) are the image quality measures that have been used to analyze the quality of the stego image. It is evident from the results that the proposed technique outperforms the former methodologies.

Properties of nanocrystalline Si layers embedded in structure of solar cell

NASA Astrophysics Data System (ADS)

Jurečka, Stanislav; Imamura, Kentaro; Matsumoto, Taketoshi; Kobayashi, Hikaru

2017-12-01

Suppression of spectral reflectance from the surface of solar cell is necessary for achieving a high energy conversion efficiency. We developed a simple method for forming nanocrystalline layers with ultralow reflectance in a broad range of wavelengths. The method is based on metal assisted etching of the silicon surface. In this work, we prepared Si solar cell structures with embedded nanocrystalline layers. The microstructure of embedded layer depends on the etching conditions. We examined the microstructure of the etched layers by a transmission electron microscope and analysed the experimental images by statistical and Fourier methods. The obtained results provide information on the applied treatment operations and can be used to optimize the solar cell forming procedure.

Parametric embedding for class visualization.

PubMed

Iwata, Tomoharu; Saito, Kazumi; Ueda, Naonori; Stromsten, Sean; Griffiths, Thomas L; Tenenbaum, Joshua B

2007-09-01

We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.

From nationwide standardized testing to school-based alternative embedded assessment in Israel: Students' performance in the matriculation 2000 project

NASA Astrophysics Data System (ADS)

Dori, Yehudit J.

2003-01-01

Matriculation 2000 was a 5-year project aimed at moving from the nationwide traditional examination system in Israel to a school-based alternative embedded assessment. Encompassing 22 high schools from various communities in the country, the Project aimed at fostering deep understanding, higher-order thinking skills, and students' engagement in learning through alternative teaching and embedded assessment methods. This article describes research conducted during the fifth year of the Project at 2 experimental and 2 control schools. The research objective was to investigate students' learning outcomes in chemistry and biology in the Matriculation 2000 Project. The assumption was that alternative embedded assessment has some effect on students' performance. The experimental students scored significantly higher than their control group peers on low-level assignments and more so on assignments that required higher-order thinking skills. The findings indicate that given adequate support and teachers' consent and collaboration, schools can transfer from nationwide or statewide standardized testing to school-based alter-native embedded assessment.

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

PubMed

Xu, Shanzhi; Hu, Hai; Ji, Linhong; Wang, Peng

2018-02-26

The recorded electroencephalography (EEG) signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA) is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC) and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA) EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding.

PubMed

Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

2017-07-15

Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k -mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k -mer co-occurrence information with recent advances in deep learning. We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k -mer embedding. We first split DNA sequences into k -mers and pre-train k -mer embedding vectors based on the co-occurrence matrix of k -mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k -mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm . tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn. Supplementary materials are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding

PubMed Central

Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

2017-01-01

Abstract Motivation: Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k-mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k-mer co-occurrence information with recent advances in deep learning. Results: We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k-mer embedding. We first split DNA sequences into k-mers and pre-train k-mer embedding vectors based on the co-occurrence matrix of k-mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k-mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. Availability and implementation: The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm. Contact: tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn Supplementary information: Supplementary materials are available at Bioinformatics online. PMID:28881969

Free vibration of an embedded single-walled carbon nanotube with various boundary conditions using the RMVT-based nonlocal Timoshenko beam theory and DQ method

NASA Astrophysics Data System (ADS)

Wu, Chih-Ping; Lai, Wei-Wen

2015-04-01

The nonlocal Timoshenko beam theories (TBTs), based on the Reissner mixed variation theory (RMVT) and principle of virtual displacement (PVD), are derived for the free vibration analysis of a single-walled carbon nanotube (SWCNT) embedded in an elastic medium and with various boundary conditions. The strong formulations of the nonlocal TBTs are derived using Hamilton's principle, in which Eringen's nonlocal constitutive relations are used to account for the small-scale effect. The interaction between the SWCNT and its surrounding elastic medium is simulated using the Winkler and Pasternak foundation models. The frequency parameters of the embedded SWCNT are obtained using the differential quadrature (DQ) method. In the cases of the SWCNT without foundations, the results of RMVT- and PVD-based nonlocal TBTs converge rapidly, and their convergent solutions closely agree with the exact ones available in the literature. Because the highest order with regard to the derivatives of the field variables used in the RMVT-based nonlocal TBT is lower than that used in its PVD-based counterpart, the former is more efficient than the latter with regard to the execution time. The former is thus both faster and obtains more accurate solutions than the latter for the numerical analysis of the embedded SWCNT.

Video Game Learning Dynamics: Actionable Measures of Multidimensional Learning Trajectories

ERIC Educational Resources Information Center

Reese, Debbie Denise; Tabachnick, Barbara G.; Kosko, Robert E.

2015-01-01

Valid, accessible, reusable methods for instructional video game design and embedded assessment can provide actionable information enhancing individual and collective achievement. Cyberlearning through game-based, metaphor-enhanced learning objects (CyGaMEs) design and embedded assessment quantify player behavior to study knowledge discovery and…

Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing.

PubMed

Li, Shuang; Liu, Bing; Zhang, Chen

2016-01-01

Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios.

Compression embedding

DOEpatents

Sandford, M.T. II; Handel, T.G.; Bradley, J.N.

1998-03-10

A method of embedding auxiliary information into the digital representation of host data created by a lossy compression technique is disclosed. The method applies to data compressed with lossy algorithms based on series expansion, quantization to a finite number of symbols, and entropy coding. Lossy compression methods represent the original data as integer indices having redundancy and uncertainty in value by one unit. Indices which are adjacent in value are manipulated to encode auxiliary data. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user. Lossy compression methods use loss-less compressions known also as entropy coding, to reduce to the final size the intermediate representation as indices. The efficiency of the compression entropy coding, known also as entropy coding is increased by manipulating the indices at the intermediate stage in the manner taught by the method. 11 figs.

Compression embedding

DOEpatents

Sandford, II, Maxwell T.; Handel, Theodore G.; Bradley, Jonathan N.

1998-01-01

A method of embedding auxiliary information into the digital representation of host data created by a lossy compression technique. The method applies to data compressed with lossy algorithms based on series expansion, quantization to a finite number of symbols, and entropy coding. Lossy compression methods represent the original data as integer indices having redundancy and uncertainty in value by one unit. Indices which are adjacent in value are manipulated to encode auxiliary data. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user. Lossy compression methods use loss-less compressions known also as entropy coding, to reduce to the final size the intermediate representation as indices. The efficiency of the compression entropy coding, known also as entropy coding is increased by manipulating the indices at the intermediate stage in the manner taught by the method.

Validation of the Lung Subtyping Panel in Multiple Fresh-Frozen and Formalin-Fixed, Paraffin-Embedded Lung Tumor Gene Expression Data Sets.

PubMed

Faruki, Hawazin; Mayhew, Gregory M; Fan, Cheng; Wilkerson, Matthew D; Parker, Scott; Kam-Morgan, Lauren; Eisenberg, Marcia; Horten, Bruce; Hayes, D Neil; Perou, Charles M; Lai-Goldman, Myla

2016-06-01

Context .- A histologic classification of lung cancer subtypes is essential in guiding therapeutic management. Objective .- To complement morphology-based classification of lung tumors, a previously developed lung subtyping panel (LSP) of 57 genes was tested using multiple public fresh-frozen gene-expression data sets and a prospectively collected set of formalin-fixed, paraffin-embedded lung tumor samples. Design .- The LSP gene-expression signature was evaluated in multiple lung cancer gene-expression data sets totaling 2177 patients collected from 4 platforms: Illumina RNAseq (San Diego, California), Agilent (Santa Clara, California) and Affymetrix (Santa Clara) microarrays, and quantitative reverse transcription-polymerase chain reaction. Gene centroids were calculated for each of 3 genomic-defined subtypes: adenocarcinoma, squamous cell carcinoma, and neuroendocrine, the latter of which encompassed both small cell carcinoma and carcinoid. Classification by LSP into 3 subtypes was evaluated in both fresh-frozen and formalin-fixed, paraffin-embedded tumor samples, and agreement with the original morphology-based diagnosis was determined. Results .- The LSP-based classifications demonstrated overall agreement with the original clinical diagnosis ranging from 78% (251 of 322) to 91% (492 of 538 and 869 of 951) in the fresh-frozen public data sets and 84% (65 of 77) in the formalin-fixed, paraffin-embedded data set. The LSP performance was independent of tissue-preservation method and gene-expression platform. Secondary, blinded pathology review of formalin-fixed, paraffin-embedded samples demonstrated concordance of 82% (63 of 77) with the original morphology diagnosis. Conclusions .- The LSP gene-expression signature is a reproducible and objective method for classifying lung tumors and demonstrates good concordance with morphology-based classification across multiple data sets. The LSP panel can supplement morphologic assessment of lung cancers, particularly when classification by standard methods is challenging.

Gear Fatigue Crack Diagnosis by Vibration Analysis Using Embedded Modeling

DTIC Science & Technology

2001-04-05

gave references on Wigner - Ville Distribution ( WVD ) and some statistical based methods including FM4, NA4 and NB4. There are limitations for vibration...Embedded Modeling DISTRIBUTION : Approved for public release, distribution unlimited This paper is part of the following report: TITLE: New Frontiers in

Using Embedded Visual Coding to Support Contextualization of Historical Texts

ERIC Educational Resources Information Center

Baron, Christine

2016-01-01

This mixed-method study examines the think-aloud protocols of 48 randomly assigned undergraduate students to understand what effect embedding a visual coding system, based on reliable visual cues for establishing historical time period, would have on novice history students' ability to contextualize historic documents. Results indicate that using…

Piezoresistive effect of the carbon nanotube yarn embedded axially into the 3D braided composite

NASA Astrophysics Data System (ADS)

Ma, Xin; Cao, Xiaona

2018-06-01

A new method for monitoring 3D braided composite structure health in real time by embedding the carbon nanotube yarn, based on its piezoresistivity, in the composite axially has been designed. The experimental system for piezoresistive effect detection of the carbon nanotube yarn in the 3D braided composite was built, and the sensing characteristics has been analyzed for further research. Compared with other structural health monitoring methods, the monitoring technique with carbon nanotubes yarns is more suitable for internal damage detection immediately, in addition the strength of the composite can be increased by embedding carbon nanotubes yarns. This method can also be used for strain sensing, the development of intelligent materials and structure systems.

Robust High-Capacity Audio Watermarking Based on FFT Amplitude Modification

NASA Astrophysics Data System (ADS)

Fallahpour, Mehdi; Megías, David

This paper proposes a novel robust audio watermarking algorithm to embed data and extract it in a bit-exact manner based on changing the magnitudes of the FFT spectrum. The key point is selecting a frequency band for embedding based on the comparison between the original and the MP3 compressed/decompressed signal and on a suitable scaling factor. The experimental results show that the method has a very high capacity (about 5kbps), without significant perceptual distortion (ODG about -0.25) and provides robustness against common audio signal processing such as added noise, filtering and MPEG compression (MP3). Furthermore, the proposed method has a larger capacity (number of embedded bits to number of host bits rate) than recent image data hiding methods.

A framework for optimal kernel-based manifold embedding of medical image data.

PubMed

Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

2015-04-01

Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nanofluidic Device with Embedded Nanopore

NASA Astrophysics Data System (ADS)

Zhang, Yuning; Reisner, Walter

2014-03-01

Nanofluidic based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with nanpore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a nanopore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We demonstrate that we can detect - using fluorescent microscopy - successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. We also show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore until a certain voltage bias is added.

Genetics algorithm optimization of DWT-DCT based image Watermarking

NASA Astrophysics Data System (ADS)

Budiman, Gelar; Novamizanti, Ledya; Iwut, Iwan

2017-01-01

Data hiding in an image content is mandatory for setting the ownership of the image. Two dimensions discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed as transform method in this paper. First, the host image in RGB color space is converted to selected color space. We also can select the layer where the watermark is embedded. Next, 2D-DWT transforms the selected layer obtaining 4 subband. We select only one subband. And then block-based 2D-DCT transforms the selected subband. Binary-based watermark is embedded on the AC coefficients of each block after zigzag movement and range based pixel selection. Delta parameter replacing pixels in each range represents embedded bit. +Delta represents bit “1” and -delta represents bit “0”. Several parameters to be optimized by Genetics Algorithm (GA) are selected color space, layer, selected subband of DWT decomposition, block size, embedding range, and delta. The result of simulation performs that GA is able to determine the exact parameters obtaining optimum imperceptibility and robustness, in any watermarked image condition, either it is not attacked or attacked. DWT process in DCT based image watermarking optimized by GA has improved the performance of image watermarking. By five attacks: JPEG 50%, resize 50%, histogram equalization, salt-pepper and additive noise with variance 0.01, robustness in the proposed method has reached perfect watermark quality with BER=0. And the watermarked image quality by PSNR parameter is also increased about 5 dB than the watermarked image quality from previous method.

Nanochannel Device with Embedded Nanopore: a New Approach for Single-Molecule DNA Analysis and Manipulation

NASA Astrophysics Data System (ADS)

Zhang, Yuning; Reisner, Walter

2012-02-01

Nanopore and nanochannel based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with nanpore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a nanopore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We will discuss our recent progress on device fabrication and characterization. In particular, we demonstrate that we can detect - using fluorescent microscopy - successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. In particular, we show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore, suggesting that the embedded pore could be used as a nanoscale window through which to interrogate a nanochannel extended DNA molecule.

Nanochannel Device with Embedded Nanopore: a New Approach for Single-Molecule DNA Analysis and Manipulation

NASA Astrophysics Data System (ADS)

Zhang, Yuning; Reisner, Walter

2013-03-01

Nanopore and nanochannel based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with embedded pore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a pore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We demonstrate that we can optically detect successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. In particular, we show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore, suggesting that the pore could be used as a nanoscale window through which to interrogate a nanochannel extended DNA molecule. Furthermore, electrical measurements through the nanopore are performed, indicating that DNA sensing is feasible using the nanochannel-nanopore device.

Neuro-symbolic representation learning on biological knowledge graphs.

PubMed

Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert

2017-09-01

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Gear fatigue crack prognosis using embedded model, gear dynamic model and fracture mechanics

NASA Astrophysics Data System (ADS)

Li, C. James; Lee, Hyungdae

2005-07-01

This paper presents a model-based method that predicts remaining useful life of a gear with a fatigue crack. The method consists of an embedded model to identify gear meshing stiffness from measured gear torsional vibration, an inverse method to estimate crack size from the estimated meshing stiffness; a gear dynamic model to simulate gear meshing dynamics and determine the dynamic load on the cracked tooth; and a fast crack propagation model to forecast the remaining useful life based on the estimated crack size and dynamic load. The fast crack propagation model was established to avoid repeated calculations of FEM and facilitate field deployment of the proposed method. Experimental studies were conducted to validate and demonstrate the feasibility of the proposed method for prognosis of a cracked gear.

Site-occupation embedding theory using Bethe ansatz local density approximations

NASA Astrophysics Data System (ADS)

Senjean, Bruno; Nakatani, Naoki; Tsuchiizu, Masahisa; Fromager, Emmanuel

2018-06-01

Site-occupation embedding theory (SOET) is an alternative formulation of density functional theory (DFT) for model Hamiltonians where the fully interacting Hubbard problem is mapped, in principle exactly, onto an impurity-interacting (rather than a noninteracting) one. It provides a rigorous framework for combining wave-function (or Green function)-based methods with DFT. In this work, exact expressions for the per-site energy and double occupation of the uniform Hubbard model are derived in the context of SOET. As readily seen from these derivations, the so-called bath contribution to the per-site correlation energy is, in addition to the latter, the key density functional quantity to model in SOET. Various approximations based on Bethe ansatz and perturbative solutions to the Hubbard and single-impurity Anderson models are constructed and tested on a one-dimensional ring. The self-consistent calculation of the embedded impurity wave function has been performed with the density-matrix renormalization group method. It has been shown that promising results are obtained in specific regimes of correlation and density. Possible further developments have been proposed in order to provide reliable embedding functionals and potentials.

Developing robust recurrence plot analysis techniques for investigating infant respiratory patterns.

PubMed

Terrill, Philip I; Wilson, Stephen; Suresh, Sadasivam; Cooper, David M

2007-01-01

Recurrence plot analysis is a useful non-linear analysis tool. There are still no well formalised procedures for carrying out this analysis on measured physiological data, and systemising analysis is often difficult. In this paper, the recurrence based embedding is compared to radius based embedding by studying a logistic attractor and measured breathing data collected from sleeping human infants. Recurrence based embedding appears to be a more robust method of carrying out a recurrence analysis when attractor size is likely to be different between datasets. In the infant breathing data, the radius measure calculated at a fixed recurrence, scaled by average respiratory period, allows the accurate discrimination of active sleep from quiet sleep states (AUC=0.975, Sn=098, Sp=0.94).

Embedding methods for the steady Euler equations

NASA Technical Reports Server (NTRS)

Chang, S. H.; Johnson, G. M.

1983-01-01

An approach to the numerical solution of the steady Euler equations is to embed the first-order Euler system in a second-order system and then to recapture the original solution by imposing additional boundary conditions. Initial development of this approach and computational experimentation with it were previously based on heuristic physical reasoning. This has led to the construction of a relaxation procedure for the solution of two-dimensional steady flow problems. The theoretical justification for the embedding approach is addressed. It is proven that, with the appropriate choice of embedding operator and additional boundary conditions, the solution to the embedded system is exactly the one to the original Euler equations. Hence, solving the embedded version of the Euler equations will not produce extraneous solutions.

Spherical hashing: binary code embedding with hyperspheres.

PubMed

Heo, Jae-Pil; Lee, Youngwoon; He, Junfeng; Chang, Shih-Fu; Yoon, Sung-Eui

2015-11-01

Many binary code embedding schemes have been actively studied recently, since they can provide efficient similarity search, and compact data representations suitable for handling large scale image databases. Existing binary code embedding techniques encode high-dimensional data by using hyperplane-based hashing functions. In this paper we propose a novel hypersphere-based hashing function, spherical hashing, to map more spatially coherent data points into a binary code compared to hyperplane-based hashing functions. We also propose a new binary code distance function, spherical Hamming distance, tailored for our hypersphere-based binary coding scheme, and design an efficient iterative optimization process to achieve both balanced partitioning for each hash function and independence between hashing functions. Furthermore, we generalize spherical hashing to support various similarity measures defined by kernel functions. Our extensive experiments show that our spherical hashing technique significantly outperforms state-of-the-art techniques based on hyperplanes across various benchmarks with sizes ranging from one to 75 million of GIST, BoW and VLAD descriptors. The performance gains are consistent and large, up to 100 percent improvements over the second best method among tested methods. These results confirm the unique merits of using hyperspheres to encode proximity regions in high-dimensional spaces. Finally, our method is intuitive and easy to implement.

Effect of using different cover image quality to obtain robust selective embedding in steganography

NASA Astrophysics Data System (ADS)

Abdullah, Karwan Asaad; Al-Jawad, Naseer; Abdulla, Alan Anwer

2014-05-01

One of the common types of steganography is to conceal an image as a secret message in another image which normally called a cover image; the resulting image is called a stego image. The aim of this paper is to investigate the effect of using different cover image quality, and also analyse the use of different bit-plane in term of robustness against well-known active attacks such as gamma, statistical filters, and linear spatial filters. The secret messages are embedded in higher bit-plane, i.e. in other than Least Significant Bit (LSB), in order to resist active attacks. The embedding process is performed in three major steps: First, the embedding algorithm is selectively identifying useful areas (blocks) for embedding based on its lighting condition. Second, is to nominate the most useful blocks for embedding based on their entropy and average. Third, is to select the right bit-plane for embedding. This kind of block selection made the embedding process scatters the secret message(s) randomly around the cover image. Different tests have been performed for selecting a proper block size and this is related to the nature of the used cover image. Our proposed method suggests a suitable embedding bit-plane as well as the right blocks for the embedding. Experimental results demonstrate that different image quality used for the cover images will have an effect when the stego image is attacked by different active attacks. Although the secret messages are embedded in higher bit-plane, but they cannot be recognised visually within the stegos image.

Detection of LSB+/-1 steganography based on co-occurrence matrix and bit plane clipping

NASA Astrophysics Data System (ADS)

Abolghasemi, Mojtaba; Aghaeinia, Hassan; Faez, Karim; Mehrabi, Mohammad Ali

2010-01-01

Spatial LSB+/-1 steganography changes smooth characteristics between adjoining pixels of the raw image. We present a novel steganalysis method for LSB+/-1 steganography based on feature vectors derived from the co-occurrence matrix in the spatial domain. We investigate how LSB+/-1 steganography affects the bit planes of an image and show that it changes more least significant bit (LSB) planes of it. The co-occurrence matrix is derived from an image in which some of its most significant bit planes are clipped. By this preprocessing, in addition to reducing the dimensions of the feature vector, the effects of embedding were also preserved. We compute the co-occurrence matrix in different directions and with different dependency and use the elements of the resulting co-occurrence matrix as features. This method is sensitive to the data embedding process. We use a Fisher linear discrimination (FLD) classifier and test our algorithm on different databases and embedding rates. We compare our scheme with the current LSB+/-1 steganalysis methods. It is shown that the proposed scheme outperforms the state-of-the-art methods in detecting the LSB+/-1 steganographic method for grayscale images.

Effect of Longitudinal Magnetic Field on Vibration Characteristics of Single-Walled Carbon Nanotubes in a Viscoelastic Medium

NASA Astrophysics Data System (ADS)

Zhang, D. P.; Lei, Y.; Shen, Z. B.

2017-12-01

The effect of longitudinal magnetic field on vibration response of a sing-walled carbon nanotube (SWCNT) embedded in viscoelastic medium is investigated. Based on nonlocal Euler-Bernoulli beam theory, Maxwell's relations, and Kelvin viscoelastic foundation model, the governing equations of motion for vibration analysis are established. The complex natural frequencies and corresponding mode shapes in closed form for the embedded SWCNT with arbitrary boundary conditions are obtained using transfer function method (TFM). The new analytical expressions for the complex natural frequencies are also derived for certain typical boundary conditions and Kelvin-Voigt model. Numerical results from the model are presented to show the effects of nonlocal parameter, viscoelastic parameter, boundary conditions, aspect ratio, and strength of the magnetic field on vibration characteristics for the embedded SWCNT in longitudinal magnetic field. The results demonstrate the efficiency of the proposed methods for vibration analysis of embedded SWCNTs under magnetic field.

A secure steganography for privacy protection in healthcare system.

PubMed

Liu, Jing; Tang, Guangming; Sun, Yifeng

2013-04-01

Private data in healthcare system require confidentiality protection while transmitting. Steganography is the art of concealing data into a cover media for conveying messages confidentially. In this paper, we propose a steganographic method which can provide private data in medical system with very secure protection. In our method, a cover image is first mapped into a 1D pixels sequence by Hilbert filling curve and then divided into non-overlapping embedding units with three consecutive pixels. We use adaptive pixel pair match (APPM) method to embed digits in the pixel value differences (PVD) of the three pixels and the base of embedded digits is dependent on the differences among the three pixels. By solving an optimization problem, minimal distortion of the pixel ternaries caused by data embedding can be obtained. The experimental results show our method is more suitable to privacy protection of healthcare system than prior steganographic works.

Embedding global and collective in a torus network with message class map based tree path selection

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

Chen, Dong; Coteus, Paul W.; Eisley, Noel A.

Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computermore » program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.« less

IMPROVEMENTS IN EPOXY RESIN EMBEDDING METHODS

PubMed Central

Luft, John H.

1961-01-01

Epoxy embedding methods of Glauert and Kushida have been modified so as to yield rapid, reproducible, and convenient embedding methods for electron microscopy. The sections are robust and tissue damage is less than with methacrylate embedding. PMID:13764136

D-Move: A Mobile Communication Based Delphi for Digital Natives to Support Embedded Research

ERIC Educational Resources Information Center

Petrovic, Otto

2017-01-01

Digital Natives are raised with computers and the Internet, which are a familiar part of their daily life. To gain insights into their attitude and behavior, methods and media for empirical research face new challenges like gamification, context oriented embedded research, integration of multiple data sources, and the increased importance of…

Embedded System Implementation of Sound Localization in Proximal Region

NASA Astrophysics Data System (ADS)

Iwanaga, Nobuyuki; Matsumura, Tomoya; Yoshida, Akihiro; Kobayashi, Wataru; Onoye, Takao

A sound localization method in the proximal region is proposed, which is based on a low-cost 3D sound localization algorithm with the use of head-related transfer functions (HRTFs). The auditory parallax model is applied to the current algorithm so that more accurate HRTFs can be used for sound localization in the proximal region. In addition, head-shadowing effects based on rigid-sphere model are reproduced in the proximal region by means of a second-order IIR filter. A subjective listening test demonstrates the effectiveness of the proposed method. Embedded system implementation of the proposed method is also described claiming that the proposed method improves sound effects in the proximal region only with 5.1% increase of memory capacity and 8.3% of computational costs.

Disease named entity recognition from biomedical literature using a novel convolutional neural network.

PubMed

Zhao, Zhehuan; Yang, Zhihao; Luo, Ling; Wang, Lei; Zhang, Yin; Lin, Hongfei; Wang, Jian

2017-12-28

Automatic disease named entity recognition (DNER) is of utmost importance for development of more sophisticated BioNLP tools. However, most conventional CRF based DNER systems rely on well-designed features whose selection is labor intensive and time-consuming. Though most deep learning methods can solve NER problems with little feature engineering, they employ additional CRF layer to capture the correlation information between labels in neighborhoods which makes them much complicated. In this paper, we propose a novel multiple label convolutional neural network (MCNN) based disease NER approach. In this approach, instead of the CRF layer, a multiple label strategy (MLS) first introduced by us, is employed. First, the character-level embedding, word-level embedding and lexicon feature embedding are concatenated. Then several convolutional layers are stacked over the concatenated embedding. Finally, MLS strategy is applied to the output layer to capture the correlation information between neighboring labels. As shown by the experimental results, MCNN can achieve the state-of-the-art performance on both NCBI and CDR corpora. The proposed MCNN based disease NER method achieves the state-of-the-art performance with little feature engineering. And the experimental results show the MLS strategy's effectiveness of capturing the correlation information between labels in the neighborhood.

DNA extraction from formalin-fixed, paraffin-embedded tissues: protein digestion as a limiting step for retrieval of high-quality DNA.

PubMed

Díaz-Cano, S J; Brady, S P

1997-12-01

Several DNA extraction methods have been used for formalin-fixed, paraffin-embedded tissues, with variable results being reported regarding the suitability of DNA obtained from such sources to serve as template in polymerase chain reaction (PCR)-based genetic analyses. We present a method routinely used for archival material in our laboratory that reliably yields DNA of sufficient quality for PCR studies. This method is based on extended proteinase K digestion (250 micrograms/ml in an EDTA-free calcium-containing buffer supplemented with mussel glycogen) followed by phenol-chloroform extraction. Agarose gel electrophoresis of both digestion buffer aliquots and PCR amplification of the beta-globin gene tested the suitability of the retrieved DNA for PCR amplification.

Fiber Optic Sensor Embedment Study for Multi-Parameter Strain Sensing

PubMed Central

Drissi-Habti, Monssef; Raman, Venkadesh; Khadour, Aghiad; Timorian, Safiullah

2017-01-01

The fiber optic sensors (FOSs) are commonly used for large-scale structure monitoring systems for their small size, noise free and low electrical risk characteristics. Embedded fiber optic sensors (FOSs) lead to micro-damage in composite structures. This damage generation threshold is based on the coating material of the FOSs and their diameter. In addition, embedded FOSs are aligned parallel to reinforcement fibers to avoid micro-damage creation. This linear positioning of distributed FOS fails to provide all strain parameters. We suggest novel sinusoidal sensor positioning to overcome this issue. This method tends to provide multi-parameter strains in a large surface area. The effectiveness of sinusoidal FOS positioning over linear FOS positioning is studied under both numerical and experimental methods. This study proves the advantages of the sinusoidal positioning method for FOS in composite material’s bonding. PMID:28333117

Realization of Chinese word segmentation based on deep learning method

NASA Astrophysics Data System (ADS)

Wang, Xuefei; Wang, Mingjiang; Zhang, Qiquan

2017-08-01

In recent years, with the rapid development of deep learning, it has been widely used in the field of natural language processing. In this paper, I use the method of deep learning to achieve Chinese word segmentation, with large-scale corpus, eliminating the need to construct additional manual characteristics. In the process of Chinese word segmentation, the first step is to deal with the corpus, use word2vec to get word embedding of the corpus, each character is 50. After the word is embedded, the word embedding feature is fed to the bidirectional LSTM, add a linear layer to the hidden layer of the output, and then add a CRF to get the model implemented in this paper. Experimental results show that the method used in the 2014 People's Daily corpus to achieve a satisfactory accuracy.

Non-uniform Continuum Model for Solvated Species Based on Frozen-Density Embedding Theory: The Study Case of Solvatochromism of Coumarin 153.

PubMed

Shedge, Sapana V; Zhou, Xiuwen; Wesolowski, Tomasz A

2014-09-01

Recent application of the Frozen-Density Embedding Theory based continuum model of the solvent, which is used for calculating solvatochromic shifts in the UV/Vis range, are reviewed. In this model, the solvent is represented as a non-uniform continuum taking into account both the statistical nature of the solvent and specific solute-solvent interactions. It offers, therefore, a computationally attractive alternative to methods in which the solvent is described at atomistic level. The evaluation of the solvatochromic shift involves only two calculations of excitation energy instead of at least hundreds needed to account for inhomogeneous broadening. The present review provides a detailed graphical analysis of the key quantities of this model: the average charge density of the solvent (<ρB>) and the corresponding Frozen-Density Embedding Theory derived embedding potential for coumarin 153.

A Predictive Model for Medical Events Based on Contextual Embedding of Temporal Sequences

PubMed Central

Wang, Zhimu; Huang, Yingxiang; Wang, Shuang; Wang, Fei; Jiang, Xiaoqian

2016-01-01

Background Medical concepts are inherently ambiguous and error-prone due to human fallibility, which makes it hard for them to be fully used by classical machine learning methods (eg, for tasks like early stage disease prediction). Objective Our work was to create a new machine-friendly representation that resembles the semantics of medical concepts. We then developed a sequential predictive model for medical events based on this new representation. Methods We developed novel contextual embedding techniques to combine different medical events (eg, diagnoses, prescriptions, and labs tests). Each medical event is converted into a numerical vector that resembles its “semantics,” via which the similarity between medical events can be easily measured. We developed simple and effective predictive models based on these vectors to predict novel diagnoses. Results We evaluated our sequential prediction model (and standard learning methods) in estimating the risk of potential diseases based on our contextual embedding representation. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.79 on chronic systolic heart failure and an average AUC of 0.67 (over the 80 most common diagnoses) using the Medical Information Mart for Intensive Care III (MIMIC-III) dataset. Conclusions We propose a general early prognosis predictor for 80 different diagnoses. Our method computes numeric representation for each medical event to uncover the potential meaning of those events. Our results demonstrate the efficiency of the proposed method, which will benefit patients and physicians by offering more accurate diagnosis. PMID:27888170

General rigid motion correction for computed tomography imaging based on locally linear embedding

NASA Astrophysics Data System (ADS)

Chen, Mianyi; He, Peng; Feng, Peng; Liu, Baodong; Yang, Qingsong; Wei, Biao; Wang, Ge

2018-02-01

The patient motion can damage the quality of computed tomography images, which are typically acquired in cone-beam geometry. The rigid patient motion is characterized by six geometric parameters and are more challenging to correct than in fan-beam geometry. We extend our previous rigid patient motion correction method based on the principle of locally linear embedding (LLE) from fan-beam to cone-beam geometry and accelerate the computational procedure with the graphics processing unit (GPU)-based all scale tomographic reconstruction Antwerp toolbox. The major merit of our method is that we need neither fiducial markers nor motion-tracking devices. The numerical and experimental studies show that the LLE-based patient motion correction is capable of calibrating the six parameters of the patient motion simultaneously, reducing patient motion artifacts significantly.

Embedded fiber optic ultrasonic sensors and generators

NASA Astrophysics Data System (ADS)

Dorighi, John F.; Krishnaswamy, Sridhar; Achenbach, Jan D.

1995-04-01

Ultrasonic sensors and generators based on fiber-optic systems are described. It is shown that intrinsic fiber optic Fabry-Perot ultrasound sensors that are embedded in a structure can be stabilized by actively tuning the laser frequency. The need for this method of stabilization is demonstrated by detecting piezoelectric transducer-generated ultrasonic pulses in the presence of low frequency dynamic strains that are intentionally induced to cause sensor drift. The actively stabilized embedded fiber optic Fabry-Perot sensor is also shown to have sufficient sensitivity to detect ultrasound that is generated in the interior of a structure by means of a high-power optical fiber that pipes energy from a pulsed laser to an embedded generator of ultrasound.

A FBG pulse wave demodulation method based on PCF modal interference filter

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Xu, Shan; Shen, Ziqi; Zhao, Junfa; Miao, Changyun; Bai, Hua

2016-10-01

Fiber optic sensor embedded in textiles has been a new direction of researching smart wearable technology. Pulse signal which is generated by heart beat contains vast amounts of physio-pathological information about the cardiovascular system. Therefore, the research for textile-based fiber optic sensor which can detect pulse wave has far-reaching effects on early discovery and timely treatment of cardiovascular diseases. A novel wavelength demodulation method based on photonic crystal fiber (PCF) modal interference filter is proposed for the purpose of developing FBG pulse wave sensing system embedded in smart clothing. The mechanism of the PCF modal interference and the principle of wavelength demodulation based on In-line Mach-Zehnder interferometer (In-line MZI) are analyzed in theory. The fabricated PCF modal interferometer has the advantages of good repeatability and low temperature sensitivity of 3.5pm/°C from 25°C to 60°C. The designed demodulation system can achieve linear demodulation in the range of 2nm, with the wavelength resolution of 2.2pm and the wavelength sensitivity of 0.055nm-1. The actual experiments' result indicates that the pulse wave can be well detected by this demodulation method, which is in accordance with the commercial demodulation instrument (SM130) and more sensitive than the traditional piezoelectric pulse sensor. This demodulation method provides important references for the research of smart clothing based on fiber grating sensor embedded in textiles and accelerates the developments of wearable fiber optic sensors technology.

Similarity-balanced discriminant neighbor embedding and its application to cancer classification based on gene expression data.

PubMed

Zhang, Li; Qian, Liqiang; Ding, Chuntao; Zhou, Weida; Li, Fanzhang

2015-09-01

The family of discriminant neighborhood embedding (DNE) methods is typical graph-based methods for dimension reduction, and has been successfully applied to face recognition. This paper proposes a new variant of DNE, called similarity-balanced discriminant neighborhood embedding (SBDNE) and applies it to cancer classification using gene expression data. By introducing a novel similarity function, SBDNE deals with two data points in the same class and the different classes with different ways. The homogeneous and heterogeneous neighbors are selected according to the new similarity function instead of the Euclidean distance. SBDNE constructs two adjacent graphs, or between-class adjacent graph and within-class adjacent graph, using the new similarity function. According to these two adjacent graphs, we can generate the local between-class scatter and the local within-class scatter, respectively. Thus, SBDNE can maximize the between-class scatter and simultaneously minimize the within-class scatter to find the optimal projection matrix. Experimental results on six microarray datasets show that SBDNE is a promising method for cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Embedded Piezoresistive Microcantilever Sensors for Chemical and Biological Sensing

NASA Astrophysics Data System (ADS)

Porter, Timothy; Eastman, Michael; Kooser, Ara; Manygoats, Kevin; Zhine, Rosalie

2003-03-01

Microcantilever sensors based on embedded piezoresisative technology offer a promising, low-cost method of sensing chemical and biological species. Here, we present data on the detection of various gaseous analytes, including volatile organic compounds (VOC's) and carbon monoxide. Also, we have used these sensors to detect the protein bovine serum albumin (BSA), a protein important in the study of human childhood diabetes.

An optical watermarking solution for color personal identification pictures

NASA Astrophysics Data System (ADS)

Tan, Yi-zhou; Liu, Hai-bo; Huang, Shui-hua; Sheng, Ben-jian; Pan, Zhong-ming

2009-11-01

This paper presents a new approach for embedding authentication information into image on printed materials based on optical projection technique. Our experimental setup consists of two parts, one is a common camera, and the other is a LCD projector, which project a pattern on personnel's body (especially on the face). The pattern, generated by a computer, act as the illumination light source with sinusoidal distribution and it is also the watermark signal. For a color image, the watermark is embedded into the blue channel. While we take pictures (256×256 and 512×512, 567×390 pixels, respectively), an invisible mark is embedded directly into magnitude coefficients of Discrete Fourier transform (DFT) at exposure moment. Both optical and digital correlation is suitable for detection of this type of watermark. The decoded watermark is a set of concentric circles or sectors in the DFT domain (middle frequencies region) which is robust to photographing, printing and scanning. The unlawful people modify or replace the original photograph, and make fake passport (drivers' license and so on). Experiments show, it is difficult to forge certificates in which a watermark was embedded by our projector-camera combination based on analogue watermark method rather than classical digital method.

Optical 3D watermark based digital image watermarking for telemedicine

NASA Astrophysics Data System (ADS)

Li, Xiao Wei; Kim, Seok Tae

2013-12-01

Region of interest (ROI) of a medical image is an area including important diagnostic information and must be stored without any distortion. This algorithm for application of watermarking technique for non-ROI of the medical image preserving ROI. The paper presents a 3D watermark based medical image watermarking scheme. In this paper, a 3D watermark object is first decomposed into 2D elemental image array (EIA) by a lenslet array, and then the 2D elemental image array data is embedded into the host image. The watermark extraction process is an inverse process of embedding. The extracted EIA through the computational integral imaging reconstruction (CIIR) technique, the 3D watermark can be reconstructed. Because the EIA is composed of a number of elemental images possesses their own perspectives of a 3D watermark object. Even though the embedded watermark data badly damaged, the 3D virtual watermark can be successfully reconstructed. Furthermore, using CAT with various rule number parameters, it is possible to get many channels for embedding. So our method can recover the weak point having only one transform plane in traditional watermarking methods. The effectiveness of the proposed watermarking scheme is demonstrated with the aid of experimental results.

Multilabel user classification using the community structure of online networks

PubMed Central

Papadopoulos, Symeon; Kompatsiaris, Yiannis

2017-01-01

We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user’s graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score. PMID:28278242

Multilabel user classification using the community structure of online networks.

PubMed

Rizos, Georgios; Papadopoulos, Symeon; Kompatsiaris, Yiannis

2017-01-01

We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user's graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score.

Modeling the mechanics of axonal fiber tracts using the embedded finite element method.

PubMed

Garimella, Harsha T; Kraft, Reuben H

2017-05-01

A subject-specific human head finite element model with embedded axonal fiber tractography obtained from diffusion tensor imaging was developed. The axonal fiber tractography finite element model was coupled with the volumetric elements in the head model using the embedded element method. This technique enables the calculation of axonal strains and real-time tracking of the mechanical response of the axonal fiber tracts. The coupled model was then verified using pressure and relative displacement-based (between skull and brain) experimental studies and was employed to analyze a head impact, demonstrating the applicability of this method in studying axonal injury. Following this, a comparison study of different injury criteria was performed. This model was used to determine the influence of impact direction on the extent of the axonal injury. The results suggested that the lateral impact loading is more dangerous compared to loading in the sagittal plane, a finding in agreement with previous studies. Through this analysis, we demonstrated the viability of the embedded element method as an alternative numerical approach for studying axonal injury in patient-specific human head models. Copyright © 2016 John Wiley & Sons, Ltd.

Oriented modulation for watermarking in direct binary search halftone images.

PubMed

Guo, Jing-Ming; Su, Chang-Cheng; Liu, Yun-Fu; Lee, Hua; Lee, Jiann-Der

2012-09-01

In this paper, a halftoning-based watermarking method is presented. This method enables high pixel-depth watermark embedding, while maintaining high image quality. This technique is capable of embedding watermarks with pixel depths up to 3 bits without causing prominent degradation to the image quality. To achieve high image quality, the parallel oriented high-efficient direct binary search (DBS) halftoning is selected to be integrated with the proposed orientation modulation (OM) method. The OM method utilizes different halftone texture orientations to carry different watermark data. In the decoder, the least-mean-square-trained filters are applied for feature extraction from watermarked images in the frequency domain, and the naïve Bayes classifier is used to analyze the extracted features and ultimately to decode the watermark data. Experimental results show that the DBS-based OM encoding method maintains a high degree of image quality and realizes the processing efficiency and robustness to be adapted in printing applications.

Embedded system of image storage based on fiber channel

NASA Astrophysics Data System (ADS)

Chen, Xiaodong; Su, Wanxin; Xing, Zhongbao; Wang, Hualong

2008-03-01

In domains of aerospace, aviation, aiming, and optic measure etc., the embedded system of imaging, processing and recording is absolutely necessary, which has small volume, high processing speed and high resolution. But the embedded storage technology becomes system bottleneck because of developing slowly. It is used to use RAID to promote storage speed, but it is unsuitable for the embedded system because of its big volume. Fiber channel (FC) technology offers a new method to develop the high-speed, portable storage system. In order to make storage subsystem meet the needs of high storage rate, make use of powerful Virtex-4 FPGA and high speed fiber channel, advance a project of embedded system of digital image storage based on Xilinx Fiber Channel Arbitrated Loop LogiCORE. This project utilizes Virtex- 4 RocketIO MGT transceivers to transmit the data serially, and connects many Fiber Channel hard drivers by using of Arbitrated Loop optionally. It can achieve 400MBps storage rate, breaks through the bottleneck of PCI interface, and has excellences of high-speed, real-time, portable and massive capacity.

Music score watermarking by clef modifications

NASA Astrophysics Data System (ADS)

Schmucker, Martin; Yan, Hongning

2003-06-01

In this paper we present a new method for hiding data in music scores. In contrast to previous published algorithms we investigate the possibilities of embedding information in clefs. Using the clef as information carrier has two advantages: First, a clef is present in each staff line which guarantees a fixed capacity. Second, the clef defines the reference system for musical symbols and music containing symbols, e.g. the notes and the rests, are not degraded by manipulations. Music scores must be robust against greyscale to binary conversion. As a consequence, the information is embedded by modifying the black and white distribution of pixels in certain areas. We evaluate simple image processing mechanisms based on erosion and dilation for embedding the information. For retrieving the watermark the b/w-distribution is extracted from the given clef. To solve the synchronization problem the watermarked clef is normalized in a pre-processing step. The normalization is based on moments. The areas used for watermarking are calculated by image segmentation techniques which consider the features of a clef. We analyze capacity and robustness of the proposed method using different parameters for our proposed method. This proposed method can be combined with other music score watermarking methods to increase the capacity of existing watermarking techniques.

Invariant domain watermarking using heaviside function of order alpha and fractional Gaussian field.

PubMed

Abbasi, Almas; Woo, Chaw Seng; Ibrahim, Rabha Waell; Islam, Saeed

2015-01-01

Digital image watermarking is an important technique for the authentication of multimedia content and copyright protection. Conventional digital image watermarking techniques are often vulnerable to geometric distortions such as Rotation, Scaling, and Translation (RST). These distortions desynchronize the watermark information embedded in an image and thus disable watermark detection. To solve this problem, we propose an RST invariant domain watermarking technique based on fractional calculus. We have constructed a domain using Heaviside function of order alpha (HFOA). The HFOA models the signal as a polynomial for watermark embedding. The watermark is embedded in all the coefficients of the image. We have also constructed a fractional variance formula using fractional Gaussian field. A cross correlation method based on the fractional Gaussian field is used for watermark detection. Furthermore the proposed method enables blind watermark detection where the original image is not required during the watermark detection thereby making it more practical than non-blind watermarking techniques. Experimental results confirmed that the proposed technique has a high level of robustness.

Invariant Domain Watermarking Using Heaviside Function of Order Alpha and Fractional Gaussian Field

PubMed Central

Abbasi, Almas; Woo, Chaw Seng; Ibrahim, Rabha Waell; Islam, Saeed

2015-01-01

Digital image watermarking is an important technique for the authentication of multimedia content and copyright protection. Conventional digital image watermarking techniques are often vulnerable to geometric distortions such as Rotation, Scaling, and Translation (RST). These distortions desynchronize the watermark information embedded in an image and thus disable watermark detection. To solve this problem, we propose an RST invariant domain watermarking technique based on fractional calculus. We have constructed a domain using Heaviside function of order alpha (HFOA). The HFOA models the signal as a polynomial for watermark embedding. The watermark is embedded in all the coefficients of the image. We have also constructed a fractional variance formula using fractional Gaussian field. A cross correlation method based on the fractional Gaussian field is used for watermark detection. Furthermore the proposed method enables blind watermark detection where the original image is not required during the watermark detection thereby making it more practical than non-blind watermarking techniques. Experimental results confirmed that the proposed technique has a high level of robustness. PMID:25884854

A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference.

PubMed

Hu, Shoubo; Chen, Zhitang; Chan, Laiwan

2018-05-01

Although nonstationary data are more common in the real world, most existing causal discovery methods do not take nonstationarity into consideration. In this letter, we propose a kernel embedding-based approach, ENCI, for nonstationary causal model inference where data are collected from multiple domains with varying distributions. In ENCI, we transform the complicated relation of a cause-effect pair into a linear model of variables of which observations correspond to the kernel embeddings of the cause-and-effect distributions in different domains. In this way, we are able to estimate the causal direction by exploiting the causal asymmetry of the transformed linear model. Furthermore, we extend ENCI to causal graph discovery for multiple variables by transforming the relations among them into a linear nongaussian acyclic model. We show that by exploiting the nonstationarity of distributions, both cause-effect pairs and two kinds of causal graphs are identifiable under mild conditions. Experiments on synthetic and real-world data are conducted to justify the efficacy of ENCI over major existing methods.

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

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

Akhbardeh, Alireza; Jacobs, Michael A.; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

2012-04-15

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), andmore » diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.« less

Enhancing Learning Outcomes in Computer-Based Training via Self-Generated Elaboration

ERIC Educational Resources Information Center

Cuevas, Haydee M.; Fiore, Stephen M.

2014-01-01

The present study investigated the utility of an instructional strategy known as the "query method" for enhancing learning outcomes in computer-based training. The query method involves an embedded guided, sentence generation task requiring elaboration of key concepts in the training material that encourages learners to "stop and…

H.264/AVC digital fingerprinting based on spatio-temporal just noticeable distortion

NASA Astrophysics Data System (ADS)

Ait Saadi, Karima; Bouridane, Ahmed; Guessoum, Abderrezak

2014-01-01

This paper presents a robust adaptive embedding scheme using a modified Spatio-Temporal noticeable distortion (JND) model that is designed for tracing the distribution of the H.264/AVC video content and protecting them from unauthorized redistribution. The Embedding process is performed during coding process in selected macroblocks type Intra 4x4 within I-Frame. The method uses spread-spectrum technique in order to obtain robustness against collusion attacks and the JND model to dynamically adjust the embedding strength and control the energy of the embedded fingerprints so as to ensure their imperceptibility. Linear and non linear collusion attacks are performed to show the robustness of the proposed technique against collusion attacks while maintaining visual quality unchanged.

Compression embedding

DOEpatents

Sandford, M.T. II; Handel, T.G.; Bradley, J.N.

1998-07-07

A method and apparatus for embedding auxiliary information into the digital representation of host data created by a lossy compression technique and a method and apparatus for constructing auxiliary data from the correspondence between values in a digital key-pair table with integer index values existing in a representation of host data created by a lossy compression technique are disclosed. The methods apply to data compressed with algorithms based on series expansion, quantization to a finite number of symbols, and entropy coding. Lossy compression methods represent the original data as ordered sequences of blocks containing integer indices having redundancy and uncertainty of value by one unit, allowing indices which are adjacent in value to be manipulated to encode auxiliary data. Also included is a method to improve the efficiency of lossy compression algorithms by embedding white noise into the integer indices. Lossy compression methods use loss-less compression to reduce to the final size the intermediate representation as indices. The efficiency of the loss-less compression, known also as entropy coding compression, is increased by manipulating the indices at the intermediate stage. Manipulation of the intermediate representation improves lossy compression performance by 1 to 10%. 21 figs.

Compression embedding

DOEpatents

Sandford, II, Maxwell T.; Handel, Theodore G.; Bradley, Jonathan N.

1998-01-01

A method and apparatus for embedding auxiliary information into the digital representation of host data created by a lossy compression technique and a method and apparatus for constructing auxiliary data from the correspondence between values in a digital key-pair table with integer index values existing in a representation of host data created by a lossy compression technique. The methods apply to data compressed with algorithms based on series expansion, quantization to a finite number of symbols, and entropy coding. Lossy compression methods represent the original data as ordered sequences of blocks containing integer indices having redundancy and uncertainty of value by one unit, allowing indices which are adjacent in value to be manipulated to encode auxiliary data. Also included is a method to improve the efficiency of lossy compression algorithms by embedding white noise into the integer indices. Lossy compression methods use loss-less compression to reduce to the final size the intermediate representation as indices. The efficiency of the loss-less compression, known also as entropy coding compression, is increased by manipulating the indices at the intermediate stage. Manipulation of the intermediate representation improves lossy compression performance by 1 to 10%.

Design of signal reception and processing system of embedded ultrasonic endoscope

NASA Astrophysics Data System (ADS)

Li, Ming; Yu, Feng; Zhang, Ruiqiang; Li, Yan; Chen, Xiaodong; Yu, Daoyin

2009-11-01

Embedded Ultrasonic Endoscope, based on embedded microprocessor and embedded real-time operating system, sends a micro ultrasonic probe into coelom through the biopsy channel of the Electronic Endoscope to get the fault histology features of digestive organs by rotary scanning, and acquires the pictures of the alimentary canal mucosal surface. At the same time, ultrasonic signals are processed by signal reception and processing system, forming images of the full histology of the digestive organs. Signal Reception and Processing System is an important component of Embedded Ultrasonic Endoscope. However, the traditional design, using multi-level amplifiers and special digital processing circuits to implement signal reception and processing, is no longer satisfying the standards of high-performance, miniaturization and low power requirements that embedded system requires, and as a result of the high noise that multi-level amplifier brought, the extraction of small signal becomes hard. Therefore, this paper presents a method of signal reception and processing based on double variable gain amplifier and FPGA, increasing the flexibility and dynamic range of the Signal Reception and Processing System, improving system noise level, and reducing power consumption. Finally, we set up the embedded experiment system, using a transducer with the center frequency of 8MHz to scan membrane samples, and display the image of ultrasonic echo reflected by each layer of membrane, with a frame rate of 5Hz, verifying the correctness of the system.

A novel attack method about double-random-phase-encoding-based image hiding method

NASA Astrophysics Data System (ADS)

Xu, Hongsheng; Xiao, Zhijun; Zhu, Xianchen

2018-03-01

By using optical image processing techniques, a novel text encryption and hiding method applied by double-random phase-encoding technique is proposed in the paper. The first step is that the secret message is transformed into a 2-dimension array. The higher bits of the elements in the array are used to fill with the bit stream of the secret text, while the lower bits are stored specific values. Then, the transformed array is encoded by double random phase encoding technique. Last, the encoded array is embedded on a public host image to obtain the image embedded with hidden text. The performance of the proposed technique is tested via analytical modeling and test data stream. Experimental results show that the secret text can be recovered either accurately or almost accurately, while maintaining the quality of the host image embedded with hidden data by properly selecting the method of transforming the secret text into an array and the superimposition coefficient.

Enhanced Microchip Electrophoresis Separations Combined with Electrochemical Detection Utilizing a Capillary Embedded in Polystyrene.

PubMed

Mehl, Benjamin T; Martin, R Scott

2018-01-07

The ability to use microchip-based electrophoresis for fast, high-throughput separations provides researchers with a tool for close-to real time analysis of biological systems. While PDMS-based electrophoresis devices are popular, the separation efficiency is often an issue due to the hydrophobic nature of PDMS. In this study, a hybrid microfluidic capillary device was fabricated to utilize the positive features of PDMS along with the electrophoretic performance of fused silica. A capillary loop was embedded in a polystyrene base that can be coupled with PDMS microchannels at minimal dead volume interconnects. A method for cleaning out the capillaries after a wet-polishing step was devised through the use of 3D printed syringe attachment. By comparing the separation efficiency of fluorescein and CBI-glycine with both a PDMS-based serpentine device and the embedded capillary loop device, it was shown that the embedded capillary loop device maintained higher theoretical plates for both analytes. A Pd decoupler with a carbon or Pt detection electrode were embedded along with the loop allowing integration of the electrophoretic separation with electrochemical detection. A series of catecholamines were separated to show the ability to resolve similar analytes and detect redox active species. The release of dopamine and norepinephrine from PC 12 cells was also analyzed showing the compatibility of these improved microchip separations with high ionic cell buffers associated with cell culture.

PDEs on moving surfaces via the closest point method and a modified grid based particle method

NASA Astrophysics Data System (ADS)

Petras, A.; Ruuth, S. J.

2016-05-01

Partial differential equations (PDEs) on surfaces arise in a wide range of applications. The closest point method (Ruuth and Merriman (2008) [20]) is a recent embedding method that has been used to solve a variety of PDEs on smooth surfaces using a closest point representation of the surface and standard Cartesian grid methods in the embedding space. The original closest point method (CPM) was designed for problems posed on static surfaces, however the solution of PDEs on moving surfaces is of considerable interest as well. Here we propose solving PDEs on moving surfaces using a combination of the CPM and a modification of the grid based particle method (Leung and Zhao (2009) [12]). The grid based particle method (GBPM) represents and tracks surfaces using meshless particles and an Eulerian reference grid. Our modification of the GBPM introduces a reconstruction step into the original method to ensure that all the grid points within a computational tube surrounding the surface are active. We present a number of examples to illustrate the numerical convergence properties of our combined method. Experiments for advection-diffusion equations that are strongly coupled to the velocity of the surface are also presented.

Multiview Locally Linear Embedding for Effective Medical Image Retrieval

PubMed Central

Shen, Hualei; Tao, Dacheng; Ma, Dianfu

2013-01-01

Content-based medical image retrieval continues to gain attention for its potential to assist radiological image interpretation and decision making. Many approaches have been proposed to improve the performance of medical image retrieval system, among which visual features such as SIFT, LBP, and intensity histogram play a critical role. Typically, these features are concatenated into a long vector to represent medical images, and thus traditional dimension reduction techniques such as locally linear embedding (LLE), principal component analysis (PCA), or laplacian eigenmaps (LE) can be employed to reduce the “curse of dimensionality”. Though these approaches show promising performance for medical image retrieval, the feature-concatenating method ignores the fact that different features have distinct physical meanings. In this paper, we propose a new method called multiview locally linear embedding (MLLE) for medical image retrieval. Following the patch alignment framework, MLLE preserves the geometric structure of the local patch in each feature space according to the LLE criterion. To explore complementary properties among a range of features, MLLE assigns different weights to local patches from different feature spaces. Finally, MLLE employs global coordinate alignment and alternating optimization techniques to learn a smooth low-dimensional embedding from different features. To justify the effectiveness of MLLE for medical image retrieval, we compare it with conventional spectral embedding methods. We conduct experiments on a subset of the IRMA medical image data set. Evaluation results show that MLLE outperforms state-of-the-art dimension reduction methods. PMID:24349277

Gravitational energy in the framework of embedding and splitting theories

NASA Astrophysics Data System (ADS)

Grad, D. A.; Ilin, R. V.; Paston, S. A.; Sheykin, A. A.

We study various definitions of the gravitational field energy based on the usage of isometric embeddings in the Regge-Teitelboim approach. For the embedding theory, we consider the coordinate translations on the surface as well as the coordinate translations in the flat bulk. In the latter case, the independent definition of gravitational energy-momentum tensor appears as a Noether current corresponding to global inner symmetry. In the field-theoretic form of this approach (splitting theory), we consider Noether procedure and the alternative method of energy-momentum tensor defining by varying the action of the theory with respect to flat bulk metric. As a result, we obtain energy definition in field-theoretic form of embedding theory which, among the other features, gives a nontrivial result for the solutions of embedding theory which are also solutions of Einstein equations. The question of energy localization is also discussed.

Improving End-of-Life Care: Palliative Care Embedded in an Oncology Clinic Specializing in Targeted and Immune-Based Therapies.

PubMed

Einstein, David J; DeSanto-Madeya, Susan; Gregas, Matthew; Lynch, Jessica; McDermott, David F; Buss, Mary K

2017-09-01

Patients with advanced cancer benefit from early involvement of palliative care. The ideal method of palliative care integration remains to be determined, as does its effectiveness for patients treated with targeted and immune-based therapies. We studied the impact of an embedded palliative care team that saw patients in an academic oncology clinic specializing in targeted and immune-based therapies. Patients seen on a specific day accessed the embedded model, on the basis of automatic criteria; patients seen other days could be referred to a separate palliative care clinic (usual care). We abstracted data from the medical records of 114 patients who died during the 3 years after this model's implementation. Compared with usual care (n = 88), patients with access to the embedded model (n = 26) encountered palliative care as outpatients more often ( P = .003) and earlier (mean, 231 v 109 days before death; P < .001). Hospice enrollment rates were similar ( P = .303), but duration was doubled (mean, 57 v 25 days; P = .006), and enrollment > 7 days before death-a core Quality Oncology Practice Initiative metric-was higher in the embedded model (odds ratio, 5.60; P = .034). Place of death ( P = .505) and end-of-life chemotherapy (odds ratio, 0.361; P = .204) did not differ between the two arms. A model of embedded and automatically triggered palliative care among patients treated exclusively with targeted and immune-based therapies was associated with significant improvements in use and timing of palliative care and hospice, compared with usual practice.

Reliability and performance evaluation of systems containing embedded rule-based expert systems

NASA Technical Reports Server (NTRS)

Beaton, Robert M.; Adams, Milton B.; Harrison, James V. A.

1989-01-01

A method for evaluating the reliability of real-time systems containing embedded rule-based expert systems is proposed and investigated. It is a three stage technique that addresses the impact of knowledge-base uncertainties on the performance of expert systems. In the first stage, a Markov reliability model of the system is developed which identifies the key performance parameters of the expert system. In the second stage, the evaluation method is used to determine the values of the expert system's key performance parameters. The performance parameters can be evaluated directly by using a probabilistic model of uncertainties in the knowledge-base or by using sensitivity analyses. In the third and final state, the performance parameters of the expert system are combined with performance parameters for other system components and subsystems to evaluate the reliability and performance of the complete system. The evaluation method is demonstrated in the context of a simple expert system used to supervise the performances of an FDI algorithm associated with an aircraft longitudinal flight-control system.

Staining Methods for Normal and Regenerative Myelin in the Nervous System.

PubMed

Carriel, Víctor; Campos, Antonio; Alaminos, Miguel; Raimondo, Stefania; Geuna, Stefano

2017-01-01

Histochemical techniques enable the specific identification of myelin by light microscopy. Here we describe three histochemical methods for the staining of myelin suitable for formalin-fixed and paraffin-embedded materials. The first method is conventional luxol fast blue (LFB) method which stains myelin in blue and Nissl bodies and mast cells in purple. The second method is a LBF-based method called MCOLL, which specifically stains the myelin as well the collagen fibers and cells, giving an integrated overview of the histology and myelin content of the tissue. Finally, we describe the osmium tetroxide method, which consist in the osmication of previously fixed tissues. Osmication is performed prior the embedding of tissues in paraffin giving a permanent positive reaction for myelin as well as other lipids present in the tissue.

Embedded arrays of vertically aligned carbon nanotube carpets and methods for making them

DOEpatents

Kim, Myung Jong; Nicholas, Nolan Walker; Kittrell, W. Carter; Schmidt, Howard K.

2015-06-30

According to some embodiments, the present invention provides a system and method for supporting a carbon nanotube array that involve an entangled carbon nanotube mat integral with the array, where the mat is embedded in an embedding material. The embedding material may be depositable on a carbon nanotube. A depositable material may be metallic or nonmetallic. The embedding material may be an adhesive material. The adhesive material may optionally be mixed with a metal powder. The embedding material may be supported by a substrate or self-supportive. The embedding material may be conductive or nonconductive. The system and method provide superior mechanical and, when applicable, electrical, contact between the carbon nanotubes in the array and the embedding material. The optional use of a conductive material for the embedding material provides a mechanism useful for integration of carbon nanotube arrays into electronic devices.

Development of an embedded thin-film strain-gauge-based SHM network into 3D-woven composite structure for wind turbine blades

NASA Astrophysics Data System (ADS)

Zhao, Dongning; Rasool, Shafqat; Forde, Micheal; Weafer, Bryan; Archer, Edward; McIlhagger, Alistair; McLaughlin, James

2017-04-01

Recently, there has been increasing demand in developing low-cost, effective structure health monitoring system to be embedded into 3D-woven composite wind turbine blades to determine structural integrity and presence of defects. With measuring the strain and temperature inside composites at both in-situ blade resin curing and in-service stages, we are developing a novel scheme to embed a resistive-strain-based thin-metal-film sensory into the blade spar-cap that is made of composite laminates to determine structural integrity and presence of defects. Thus, with fiberglass, epoxy, and a thinmetal- film sensing element, a three-part, low-cost, smart composite laminate is developed. Embedded strain sensory inside composite laminate prototype survived after laminate curing process. The internal strain reading from embedded strain sensor under three-point-bending test standard is comparable. It proves that our proposed method will provide another SHM alternative to reduce sensing costs during the renewable green energy generation.

Improving the durability of the optical fiber sensor based on strain transfer analysis

NASA Astrophysics Data System (ADS)

Wang, Huaping; Jiang, Lizhong; Xiang, Ping

2018-05-01

To realize the reliable and long-term strain detection, the durability of optical fiber sensors has attracted more and more attention. The packaging technique has been considered as an effective method, which can enhance the survival ratios of optical fiber sensors to resist the harsh construction and service environment in civil engineering. To monitor the internal strain of structures, the embedded installation is adopted. Due to the different material properties between host material and the protective layer, the monitored structure embedded with sensors can be regarded as a typical model containing inclusions. Interfacial characteristic between the sensor and host material exists obviously, and the contacted interface is prone to debonding failure induced by the large interfacial shear stress. To recognize the local interfacial debonding damage and extend the effective life cycle of the embedded sensor, strain transfer analysis of a general three-layered sensing model is conducted to investigate the failure mechanism. The perturbation of the embedded sensor on the local strain field of host material is discussed. Based on the theoretical analysis, the distribution of the interfacial shear stress along the sensing length is characterized and adopted for the diagnosis of local interfacial debonding, and the sensitive parameters influencing the interfacial shear stress are also investigated. The research in this paper explores the interfacial debonding failure mechanism of embedded sensors based on the strain transfer analysis and provides theoretical basis for enhancing the interfacial bonding properties and improving the durability of embedded optical fiber sensors.

Correlative Imaging of Fluorescent Proteins in Resin-Embedded Plant Material1

PubMed Central

Bell, Karen; Mitchell, Steve; Paultre, Danae; Posch, Markus; Oparka, Karl

2013-01-01

Fluorescent proteins (FPs) were developed for live-cell imaging and have revolutionized cell biology. However, not all plant tissues are accessible to live imaging using confocal microscopy, necessitating alternative approaches for protein localization. An example is the phloem, a tissue embedded deep within plant organs and sensitive to damage. To facilitate accurate localization of FPs within recalcitrant tissues, we developed a simple method for retaining FPs after resin embedding. This method is based on low-temperature fixation and dehydration, followed by embedding in London Resin White, and avoids the need for cryosections. We show that a palette of FPs can be localized in plant tissues while retaining good structural cell preservation, and that the polymerized block face can be counterstained with cell wall probes. Using this method we have been able to image green fluorescent protein-labeled plasmodesmata to a depth of more than 40 μm beneath the resin surface. Using correlative light and electron microscopy of the phloem, we were able to locate the same FP-labeled sieve elements in semithin and ultrathin sections. Sections were amenable to antibody labeling, and allowed a combination of confocal and superresolution imaging (three-dimensional-structured illumination microscopy) on the same cells. These correlative imaging methods should find several uses in plant cell biology. PMID:23457228

TopicLens: Efficient Multi-Level Visual Topic Exploration of Large-Scale Document Collections.

PubMed

Kim, Minjeong; Kang, Kyeongpil; Park, Deokgun; Choo, Jaegul; Elmqvist, Niklas

2017-01-01

Topic modeling, which reveals underlying topics of a document corpus, has been actively adopted in visual analytics for large-scale document collections. However, due to its significant processing time and non-interactive nature, topic modeling has so far not been tightly integrated into a visual analytics workflow. Instead, most such systems are limited to utilizing a fixed, initial set of topics. Motivated by this gap in the literature, we propose a novel interaction technique called TopicLens that allows a user to dynamically explore data through a lens interface where topic modeling and the corresponding 2D embedding are efficiently computed on the fly. To support this interaction in real time while maintaining view consistency, we propose a novel efficient topic modeling method and a semi-supervised 2D embedding algorithm. Our work is based on improving state-of-the-art methods such as nonnegative matrix factorization and t-distributed stochastic neighbor embedding. Furthermore, we have built a web-based visual analytics system integrated with TopicLens. We use this system to measure the performance and the visualization quality of our proposed methods. We provide several scenarios showcasing the capability of TopicLens using real-world datasets.

Application of neural based estimation algorithm for gait phases of above knee prosthesis.

PubMed

Tileylioğlu, E; Yilmaz, A

2015-01-01

In this study, two gait phase estimation methods which utilize a rule based quantization and an artificial neural network model respectively are developed and applied for the microcontroller based semi-active knee prosthesis in order to respond user demands and adapt environmental conditions. In this context, an experimental environment in which gait data collected synchronously from both inertial and image based measurement systems has been set up. The inertial measurement system that incorporates MEM accelerometers and gyroscopes is used to perform direct motion measurement through the microcontroller, while the image based measurement system is employed for producing the verification data and assessing the success of the prosthesis. Embedded algorithms dynamically normalize the input data prior to gait phase estimation. The real time analyses of two methods revealed that embedded ANN based approach performs slightly better in comparison with the rule based algorithm and has advantage of being easily-scalable, thus able to accommodate additional input parameters considering the microcontroller constraints.

Damage Detection in Rotorcraft Composite Structures Using Thermography and Laser-Based Ultrasound

NASA Technical Reports Server (NTRS)

Anastasi, Robert F.; Zalameda, Joseph N.; Madaras, Eric I.

2004-01-01

New rotorcraft structural composite designs incorporate lower structural weight, reduced manufacturing complexity, and improved threat protection. These new structural concepts require nondestructive evaluation inspection technologies that can potentially be field-portable and able to inspect complex geometries for damage or structural defects. Two candidate technologies were considered: Thermography and Laser-Based Ultrasound (Laser UT). Thermography and Laser UT have the advantage of being non-contact inspection methods, with Thermography being a full-field imaging method and Laser UT a point scanning technique. These techniques were used to inspect composite samples that contained both embedded flaws and impact damage of various size and shape. Results showed that the inspection techniques were able to detect both embedded and impact damage with varying degrees of success.

Comparison of the DNA extraction methods for polymerase chain reaction amplification from formalin-fixed and paraffin-embedded tissues.

PubMed

Sato, Y; Sugie, R; Tsuchiya, B; Kameya, T; Natori, M; Mukai, K

2001-12-01

To obtain an adequate quality and quantity of DNA from formalin-fixed and paraffin-embedded tissue, six different DNA extraction methods were compared. Four methods used deparaffinization by xylene followed by proteinase K digestion and phenol-chloroform extraction. The temperature of the different steps was changed to obtain higher yields and improved quality of extracted DNA. The remaining two methods used microwave heating for deparaffinization. The best DNA extraction method consisted of deparaffinization by microwave irradiation, protein digestion with proteinase K at 48 degrees C overnight, and no further purification steps. By this method, the highest DNA yield was obtained and the amplification of a 989-base pair beta-globin gene fragment was achieved. Furthermore, DNA extracted by means of this procedure from five gastric carcinomas was successfully used for single strand conformation polymorphism and direct sequencing assays of the beta-catenin gene. Because the microwave-based DNA extraction method presented here is simple, has a lower contamination risk, and results in a higher yield of DNA compared with the ordinary organic chemical reagent-based extraction method, it is considered applicable to various clinical and basic fields.

Biomedical analysis of formalin-fixed, paraffin-embedded tissue samples: The Holy Grail for molecular diagnostics.

PubMed

Donczo, Boglarka; Guttman, Andras

2018-06-05

More than a century ago in 1893, a revolutionary idea about fixing biological tissue specimens was introduced by Ferdinand Blum, a German physician. Since then, a plethora of fixation methods have been investigated and used. Formalin fixation with paraffin embedment became the most widely used types of fixation and preservation method, due to its proper architectural conservation of tissue structures and cellular shape. The huge collection of formalin-fixed, paraffin-embedded (FFPE) sample archives worldwide holds a large amount of unearthed information about diseases that could be the Holy Grail in contemporary biomarker research utilizing analytical omics based molecular diagnostics. The aim of this review is to critically evaluate the omics options for FFPE tissue sample analysis in the molecular diagnostics field. Copyright © 2018. Published by Elsevier B.V.

Seamless Tracing of Human Behavior Using Complementary Wearable and House-Embedded Sensors

PubMed Central

Augustyniak, Piotr; Smoleń, Magdalena; Mikrut, Zbigniew; Kańtoch, Eliasz

2014-01-01

This paper presents a multimodal system for seamless surveillance of elderly people in their living environment. The system uses simultaneously a wearable sensor network for each individual and premise-embedded sensors specific for each environment. The paper demonstrates the benefits of using complementary information from two types of mobility sensors: visual flow-based image analysis and an accelerometer-based wearable network. The paper provides results for indoor recognition of several elementary poses and outdoor recognition of complex movements. Instead of complete system description, particular attention was drawn to a polar histogram-based method of visual pose recognition, complementary use and synchronization of the data from wearable and premise-embedded networks and an automatic danger detection algorithm driven by two premise- and subject-related databases. The novelty of our approach also consists in feeding the databases with real-life recordings from the subject, and in using the dynamic time-warping algorithm for measurements of distance between actions represented as elementary poses in behavioral records. The main results of testing our method include: 95.5% accuracy of elementary pose recognition by the video system, 96.7% accuracy of elementary pose recognition by the accelerometer-based system, 98.9% accuracy of elementary pose recognition by the combined accelerometer and video-based system, and 80% accuracy of complex outdoor activity recognition by the accelerometer-based wearable system. PMID:24787640

Small Private Key PKS on an Embedded Microprocessor

PubMed Central

Seo, Hwajeong; Kim, Jihyun; Choi, Jongseok; Park, Taehwan; Liu, Zhe; Kim, Howon

2014-01-01

Multivariate quadratic ( ) cryptography requires the use of long public and private keys to ensure a sufficient security level, but this is not favorable to embedded systems, which have limited system resources. Recently, various approaches to cryptography using reduced public keys have been studied. As a result of this, at CHES2011 (Cryptographic Hardware and Embedded Systems, 2011), a small public key scheme, was proposed, and its feasible implementation on an embedded microprocessor was reported at CHES2012. However, the implementation of a small private key scheme was not reported. For efficient implementation, random number generators can contribute to reduce the key size, but the cost of using a random number generator is much more complex than computing on modern microprocessors. Therefore, no feasible results have been reported on embedded microprocessors. In this paper, we propose a feasible implementation on embedded microprocessors for a small private key scheme using a pseudo-random number generator and hash function based on a block-cipher exploiting a hardware Advanced Encryption Standard (AES) accelerator. To speed up the performance, we apply various implementation methods, including parallel computation, on-the-fly computation, optimized logarithm representation, vinegar monomials and assembly programming. The proposed method reduces the private key size by about 99.9% and boosts signature generation and verification by 5.78% and 12.19% than previous results in CHES2012. PMID:24651722

Small private key MQPKS on an embedded microprocessor.

PubMed

Seo, Hwajeong; Kim, Jihyun; Choi, Jongseok; Park, Taehwan; Liu, Zhe; Kim, Howon

2014-03-19

Multivariate quadratic (MQ) cryptography requires the use of long public and private keys to ensure a sufficient security level, but this is not favorable to embedded systems, which have limited system resources. Recently, various approaches to MQ cryptography using reduced public keys have been studied. As a result of this, at CHES2011 (Cryptographic Hardware and Embedded Systems, 2011), a small public key MQ scheme, was proposed, and its feasible implementation on an embedded microprocessor was reported at CHES2012. However, the implementation of a small private key MQ scheme was not reported. For efficient implementation, random number generators can contribute to reduce the key size, but the cost of using a random number generator is much more complex than computing MQ on modern microprocessors. Therefore, no feasible results have been reported on embedded microprocessors. In this paper, we propose a feasible implementation on embedded microprocessors for a small private key MQ scheme using a pseudo-random number generator and hash function based on a block-cipher exploiting a hardware Advanced Encryption Standard (AES) accelerator. To speed up the performance, we apply various implementation methods, including parallel computation, on-the-fly computation, optimized logarithm representation, vinegar monomials and assembly programming. The proposed method reduces the private key size by about 99.9% and boosts signature generation and verification by 5.78% and 12.19% than previous results in CHES2012.

A Secure and Robust Compressed Domain Video Steganography for Intra- and Inter-Frames Using Embedding-Based Byte Differencing (EBBD) Scheme

PubMed Central

Idbeaa, Tarik; Abdul Samad, Salina; Husain, Hafizah

2016-01-01

This paper presents a novel secure and robust steganographic technique in the compressed video domain namely embedding-based byte differencing (EBBD). Unlike most of the current video steganographic techniques which take into account only the intra frames for data embedding, the proposed EBBD technique aims to hide information in both intra and inter frames. The information is embedded into a compressed video by simultaneously manipulating the quantized AC coefficients (AC-QTCs) of luminance components of the frames during MPEG-2 encoding process. Later, during the decoding process, the embedded information can be detected and extracted completely. Furthermore, the EBBD basically deals with two security concepts: data encryption and data concealing. Hence, during the embedding process, secret data is encrypted using the simplified data encryption standard (S-DES) algorithm to provide better security to the implemented system. The security of the method lies in selecting candidate AC-QTCs within each non-overlapping 8 × 8 sub-block using a pseudo random key. Basic performance of this steganographic technique verified through experiments on various existing MPEG-2 encoded videos over a wide range of embedded payload rates. Overall, the experimental results verify the excellent performance of the proposed EBBD with a better trade-off in terms of imperceptibility and payload, as compared with previous techniques while at the same time ensuring minimal bitrate increase and negligible degradation of PSNR values. PMID:26963093

A Secure and Robust Compressed Domain Video Steganography for Intra- and Inter-Frames Using Embedding-Based Byte Differencing (EBBD) Scheme.

PubMed

Idbeaa, Tarik; Abdul Samad, Salina; Husain, Hafizah

2016-01-01

This paper presents a novel secure and robust steganographic technique in the compressed video domain namely embedding-based byte differencing (EBBD). Unlike most of the current video steganographic techniques which take into account only the intra frames for data embedding, the proposed EBBD technique aims to hide information in both intra and inter frames. The information is embedded into a compressed video by simultaneously manipulating the quantized AC coefficients (AC-QTCs) of luminance components of the frames during MPEG-2 encoding process. Later, during the decoding process, the embedded information can be detected and extracted completely. Furthermore, the EBBD basically deals with two security concepts: data encryption and data concealing. Hence, during the embedding process, secret data is encrypted using the simplified data encryption standard (S-DES) algorithm to provide better security to the implemented system. The security of the method lies in selecting candidate AC-QTCs within each non-overlapping 8 × 8 sub-block using a pseudo random key. Basic performance of this steganographic technique verified through experiments on various existing MPEG-2 encoded videos over a wide range of embedded payload rates. Overall, the experimental results verify the excellent performance of the proposed EBBD with a better trade-off in terms of imperceptibility and payload, as compared with previous techniques while at the same time ensuring minimal bitrate increase and negligible degradation of PSNR values.

Constructing Pairing-Friendly Elliptic Curves under Embedding Degree 1 for Securing Critical Infrastructures.

PubMed

Wang, Maocai; Dai, Guangming; Choo, Kim-Kwang Raymond; Jayaraman, Prem Prakash; Ranjan, Rajiv

2016-01-01

Information confidentiality is an essential requirement for cyber security in critical infrastructure. Identity-based cryptography, an increasingly popular branch of cryptography, is widely used to protect the information confidentiality in the critical infrastructure sector due to the ability to directly compute the user's public key based on the user's identity. However, computational requirements complicate the practical application of Identity-based cryptography. In order to improve the efficiency of identity-based cryptography, this paper presents an effective method to construct pairing-friendly elliptic curves with low hamming weight 4 under embedding degree 1. Based on the analysis of the Complex Multiplication(CM) method, the soundness of our method to calculate the characteristic of the finite field is proved. And then, three relative algorithms to construct pairing-friendly elliptic curve are put forward. 10 elliptic curves with low hamming weight 4 under 160 bits are presented to demonstrate the utility of our approach. Finally, the evaluation also indicates that it is more efficient to compute Tate pairing with our curves, than that of Bertoni et al.

Constructing Pairing-Friendly Elliptic Curves under Embedding Degree 1 for Securing Critical Infrastructures

PubMed Central

Dai, Guangming

2016-01-01

Information confidentiality is an essential requirement for cyber security in critical infrastructure. Identity-based cryptography, an increasingly popular branch of cryptography, is widely used to protect the information confidentiality in the critical infrastructure sector due to the ability to directly compute the user’s public key based on the user’s identity. However, computational requirements complicate the practical application of Identity-based cryptography. In order to improve the efficiency of identity-based cryptography, this paper presents an effective method to construct pairing-friendly elliptic curves with low hamming weight 4 under embedding degree 1. Based on the analysis of the Complex Multiplication(CM) method, the soundness of our method to calculate the characteristic of the finite field is proved. And then, three relative algorithms to construct pairing-friendly elliptic curve are put forward. 10 elliptic curves with low hamming weight 4 under 160 bits are presented to demonstrate the utility of our approach. Finally, the evaluation also indicates that it is more efficient to compute Tate pairing with our curves, than that of Bertoni et al. PMID:27564373

Optical colour image watermarking based on phase-truncated linear canonical transform and image decomposition

NASA Astrophysics Data System (ADS)

Su, Yonggang; Tang, Chen; Li, Biyuan; Lei, Zhenkun

2018-05-01

This paper presents a novel optical colour image watermarking scheme based on phase-truncated linear canonical transform (PT-LCT) and image decomposition (ID). In this proposed scheme, a PT-LCT-based asymmetric cryptography is designed to encode the colour watermark into a noise-like pattern, and an ID-based multilevel embedding method is constructed to embed the encoded colour watermark into a colour host image. The PT-LCT-based asymmetric cryptography, which can be optically implemented by double random phase encoding with a quadratic phase system, can provide a higher security to resist various common cryptographic attacks. And the ID-based multilevel embedding method, which can be digitally implemented by a computer, can make the information of the colour watermark disperse better in the colour host image. The proposed colour image watermarking scheme possesses high security and can achieve a higher robustness while preserving the watermark’s invisibility. The good performance of the proposed scheme has been demonstrated by extensive experiments and comparison with other relevant schemes.

Wave transmission approach based on modal analysis for embedded mechanical systems

NASA Astrophysics Data System (ADS)

Cretu, Nicolae; Nita, Gelu; Ioan Pop, Mihail

2013-09-01

An experimental method for determining the phase velocity in small solid samples is proposed. The method is based on measuring the resonant frequencies of a binary or ternary solid elastic system comprising the small sample of interest and a gauge material of manageable size. The wave transmission matrix of the combined system is derived and the theoretical values of its eigenvalues are used to determine the expected eigenfrequencies that, equated with the measured values, allow for the numerical estimation of the phase velocities in both materials. The known phase velocity of the gauge material is then used to asses the accuracy of the method. Using computer simulation and the experimental values for phase velocities, the theoretical values for the eigenfrequencies of the eigenmodes of the embedded elastic system are obtained, to validate the method. We conclude that the proposed experimental method may be reliably used to determine the elastic properties of small solid samples whose geometries do not allow a direct measurement of their resonant frequencies.

Fundamental Theory of Crystal Decomposition

DTIC Science & Technology

1991-05-01

rather than combine them as is often the case in a computation based on the density functional method.4 In the Case of a cluster embedded in a...classical lattice, special care needs to be taken to ensure that mathematical consistency is achieved between the cluster and the embedding lattice. This has...localizing potential or KKLP. Simulation of a large crystallite or an infinite lattice containing a point defect represented by a cluster and a

An Efficient and Reusable Embedded Ru Catalyst for the Hydrogenolysis of Levulinic Acid to γ-Valerolactone.

PubMed

Wei, Zuojun; Lou, Jiongtao; Su, Chuanmin; Guo, Dechao; Liu, Yingxin; Deng, Shuguang

2017-04-22

To achieve a higher activity and reusability of a Ru-based catalyst, Ru nanoparticles were embedded in N-doped mesoporous carbon through a hard-template method. The catalyst showed excellent catalytic performance (314 h -1 turnover frequency) and recyclability (reusable five times with 3 % activity loss) for the hydrogenolysis of levulinic acid to γ-valerolactone. Compared with the mesoporous carbon without N-doping and conventional activated carbon, the introduction of N-dopant effectively improved the dispersion of Ru nanoparticles, decreased the average size of Ru nanoparticles to as small as 1.32 nm, and improved the adsorption of levulinic acid, which contributed to the increase in the activity of the catalyst. Additionally, the embedding method increased the interaction between Ru nanoparticles and carbon support in contrast with the conventional impregnation method, thus preventing the Ru nanoparticles from migration, aggregation, and leaching from the carbon surface and therefore increasing the reusability of the catalyst. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the behavior of isolated and embedded carbon nano-tubes in a polymeric matrix

NASA Astrophysics Data System (ADS)

Rahimian-Koloor, Seyed Mostafa; Moshrefzadeh-Sani, Hadi; Mehrdad Shokrieh, Mahmood; Majid Hashemianzadeh, Seyed

2018-02-01

In the classical micro-mechanical method, the moduli of the reinforcement and the matrix are used to predict the stiffness of composites. However, using the classical micro-mechanical method to predict the stiffness of CNT/epoxy nanocomposites leads to overestimated results. One of the main reasons for this overestimation is using the stiffness of the isolated CNT and ignoring the CNT nanoscale effect by the method. In the present study the non-equilibrium molecular dynamics simulation was used to consider the influence of CNT length on the stiffness of the nanocomposites through the isothermal-isobaric ensemble. The results indicated that, due to the nanoscale effects, the reinforcing efficiency of the embedded CNT is not constant and decreases with decreasing its length. Based on the results, a relationship was derived, which predicts the effective stiffness of an embedded CNT in terms of its length. It was shown that using this relationship leads to predict more accurate elastic modulus of nanocomposite, which was validated by some experimental counterparts.

Design and control of an embedded vision guided robotic fish with multiple control surfaces.

PubMed

Yu, Junzhi; Wang, Kai; Tan, Min; Zhang, Jianwei

2014-01-01

This paper focuses on the development and control issues of a self-propelled robotic fish with multiple artificial control surfaces and an embedded vision system. By virtue of the hybrid propulsion capability in the body plus the caudal fin and the complementary maneuverability in accessory fins, a synthesized propulsion scheme including a caudal fin, a pair of pectoral fins, and a pelvic fin is proposed. To achieve flexible yet stable motions in aquatic environments, a central pattern generator- (CPG-) based control method is employed. Meanwhile, a monocular underwater vision serves as sensory feedback that modifies the control parameters. The integration of the CPG-based motion control and the visual processing in an embedded microcontroller allows the robotic fish to navigate online. Aquatic tests demonstrate the efficacy of the proposed mechatronic design and swimming control methods. Particularly, a pelvic fin actuated sideward swimming gait was first implemented. It is also found that the speeds and maneuverability of the robotic fish with coordinated control surfaces were largely superior to that of the swimming robot propelled by a single control surface.

Design and Control of an Embedded Vision Guided Robotic Fish with Multiple Control Surfaces

PubMed Central

Wang, Kai; Tan, Min; Zhang, Jianwei

2014-01-01

This paper focuses on the development and control issues of a self-propelled robotic fish with multiple artificial control surfaces and an embedded vision system. By virtue of the hybrid propulsion capability in the body plus the caudal fin and the complementary maneuverability in accessory fins, a synthesized propulsion scheme including a caudal fin, a pair of pectoral fins, and a pelvic fin is proposed. To achieve flexible yet stable motions in aquatic environments, a central pattern generator- (CPG-) based control method is employed. Meanwhile, a monocular underwater vision serves as sensory feedback that modifies the control parameters. The integration of the CPG-based motion control and the visual processing in an embedded microcontroller allows the robotic fish to navigate online. Aquatic tests demonstrate the efficacy of the proposed mechatronic design and swimming control methods. Particularly, a pelvic fin actuated sideward swimming gait was first implemented. It is also found that the speeds and maneuverability of the robotic fish with coordinated control surfaces were largely superior to that of the swimming robot propelled by a single control surface. PMID:24688413

Embedded Hyperchaotic Generators: A Comparative Analysis

NASA Astrophysics Data System (ADS)

Sadoudi, Said; Tanougast, Camel; Azzaz, Mohamad Salah; Dandache, Abbas

In this paper, we present a comparative analysis of FPGA implementation performances, in terms of throughput and resources cost, of five well known autonomous continuous hyperchaotic systems. The goal of this analysis is to identify the embedded hyperchaotic generator which leads to designs with small logic area cost, satisfactory throughput rates, low power consumption and low latency required for embedded applications such as secure digital communications between embedded systems. To implement the four-dimensional (4D) chaotic systems, we use a new structural hardware architecture based on direct VHDL description of the forth order Runge-Kutta method (RK-4). The comparative analysis shows that the hyperchaotic Lorenz generator provides attractive performances compared to that of others. In fact, its hardware implementation requires only 2067 CLB-slices, 36 multipliers and no block RAMs, and achieves a throughput rate of 101.6 Mbps, at the output of the FPGA circuit, at a clock frequency of 25.315 MHz with a low latency time of 316 ns. Consequently, these good implementation performances offer to the embedded hyperchaotic Lorenz generator the advantage of being the best candidate for embedded communications applications.

Dual-Level Security based Cyclic18 Steganographic Method and its Application for Secure Transmission of Keyframes during Wireless Capsule Endoscopy.

PubMed

Muhammad, Khan; Sajjad, Muhammad; Baik, Sung Wook

2016-05-01

In this paper, the problem of secure transmission of sensitive contents over the public network Internet is addressed by proposing a novel data hiding method in encrypted images with dual-level security. The secret information is divided into three blocks using a specific pattern, followed by an encryption mechanism based on the three-level encryption algorithm (TLEA). The input image is scrambled using a secret key, and the encrypted sub-message blocks are then embedded in the scrambled image by cyclic18 least significant bit (LSB) substitution method, utilizing LSBs and intermediate LSB planes. Furthermore, the cover image and its planes are rotated at different angles using a secret key prior to embedding, deceiving the attacker during data extraction. The usage of message blocks division, TLEA, image scrambling, and the cyclic18 LSB method results in an advanced security system, maintaining the visual transparency of resultant images and increasing the security of embedded data. In addition, employing various secret keys for image scrambling, data encryption, and data hiding using the cyclic18 LSB method makes the data recovery comparatively more challenging for attackers. Experimental results not only validate the effectiveness of the proposed framework in terms of visual quality and security compared to other state-of-the-art methods, but also suggest its feasibility for secure transmission of diagnostically important keyframes to healthcare centers and gastroenterologists during wireless capsule endoscopy.

Embedded 3D shape measurement system based on a novel spatio-temporal coding method

NASA Astrophysics Data System (ADS)

Xu, Bin; Tian, Jindong; Tian, Yong; Li, Dong

2016-11-01

Structured light measurement has been wildly used since 1970s in industrial component detection, reverse engineering, 3D molding, robot navigation, medical and many other fields. In order to satisfy the demand for high speed, high precision and high resolution 3-D measurement for embedded system, a new patterns combining binary and gray coding principle in space are designed and projected onto the object surface orderly. Each pixel corresponds to the designed sequence of gray values in time - domain, which is treated as a feature vector. The unique gray vector is then dimensionally reduced to a scalar which could be used as characteristic information for binocular matching. In this method, the number of projected structured light patterns is reduced, and the time-consuming phase unwrapping in traditional phase shift methods is avoided. This algorithm is eventually implemented on DM3730 embedded system for 3-D measuring, which consists of an ARM and a DSP core and has a strong capability of digital signal processing. Experimental results demonstrated the feasibility of the proposed method.

"You're just one of the group when you're embedded": report from a mixed-method investigation of the research-embedded health librarian experience.

PubMed

Greyson, Devon; Surette, Soleil; Dennett, Liz; Chatterley, Trish

2013-10-01

Embedded librarianship has received much attention in recent years. A model of embeddedness rarely discussed to date is that of research-embedded health librarians (REHLs). This study explores the characteristics of Canadian REHLs and the situations in which they are employed. The authors employed a sequential, mixed-method design. An online survey provided descriptive statistics about REHLs' positions and work experiences. This informed a series of focus group interviews that expanded upon the survey. Through constant comparison, we conducted qualitative descriptive analysis of the interviews. Based on twenty-nine survey responses and four group interviews, we created a portrait of a "typical" REHL and discovered themes relevant to REHL work. REHLs may identify more strongly as researchers than as librarians, with corresponding professional needs and rewards. REHLs value "belonging" to the research team, involvement in full project lifecycles, and in-depth relationships with nonlibrarian colleagues. Despite widely expressed job satisfaction, many REHLs struggle with isolation from library and information science peers and relative lack of job security. REHLs differ from non-embedded health librarians, as well as from other types of embedded librarians. REHLs' work also differs from just a decade or two ago, prior to widespread Internet access to digital resources. Given that research-embedded librarianship appears to be a distinct and growing subset of health librarianship, libraries, master's of library and information science programs, and professional associations will need to respond to the support and education needs of REHLs or risk losing them to the health research field.

Recovering an elastic obstacle containing embedded objects by the acoustic far-field measurements

NASA Astrophysics Data System (ADS)

Qu, Fenglong; Yang, Jiaqing; Zhang, Bo

2018-01-01

Consider the inverse scattering problem of time-harmonic acoustic waves by a 3D bounded elastic obstacle which may contain embedded impenetrable obstacles inside. We propose a novel and simple technique to show that the elastic obstacle can be uniquely recovered by the acoustic far-field pattern at a fixed frequency, disregarding its contents. Our method is based on constructing a well-posed modified interior transmission problem on a small domain and makes use of an a priori estimate for both the acoustic and elastic wave fields in the usual H 1-norm. In the case when there is no obstacle embedded inside the elastic body, our method gives a much simpler proof for the uniqueness result obtained previously in the literature (Natroshvili et al 2000 Rend. Mat. Serie VII 20 57-92 Monk and Selgas 2009 Inverse Problems Imaging 3 173-98).

Non-standard analysis and embedded software

NASA Technical Reports Server (NTRS)

Platek, Richard

1995-01-01

One model for computing in the future is ubiquitous, embedded computational devices analogous to embedded electrical motors. Many of these computers will control physical objects and processes. Such hidden computerized environments introduce new safety and correctness concerns whose treatment go beyond present Formal Methods. In particular, one has to begin to speak about Real Space software in analogy with Real Time software. By this we mean, computerized systems which have to meet requirements expressed in the real geometry of space. How to translate such requirements into ordinary software specifications and how to carry out proofs is a major challenge. In this talk we propose a research program based on the use of no-standard analysis. Much detail remains to be carried out. The purpose of the talk is to inform the Formal Methods community that Non-Standard Analysis provides a possible avenue to attack which we believe will be fruitful.

Image watermarking against lens flare effects

NASA Astrophysics Data System (ADS)

Chotikawanid, Piyanart; Amornraksa, Thumrongrat

2017-02-01

Lens flare effects in various photo and camera software nowadays can partially or fully damage the watermark information within the watermarked image. We propose in this paper a spatial domain based image watermarking against lens flare effects. The watermark embedding is based on the modification of the saturation color component in HSV color space of a host image. For watermark extraction, a homomorphic filter is used to predict the original embedding component from the watermarked component, and the watermark is blindly recovered by differentiating both components. The watermarked image's quality is evaluated by wPSNR, while the extracted watermark's accuracy is evaluated by NC. The experimental results against various types of lens flare effects from both computer software and mobile application showed that our proposed method outperformed the previous methods.

An RBF-based reparameterization method for constrained texture mapping.

PubMed

Yu, Hongchuan; Lee, Tong-Yee; Yeh, I-Cheng; Yang, Xiaosong; Li, Wenxi; Zhang, Jian J

2012-07-01

Texture mapping has long been used in computer graphics to enhance the realism of virtual scenes. However, to match the 3D model feature points with the corresponding pixels in a texture image, surface parameterization must satisfy specific positional constraints. However, despite numerous research efforts, the construction of a mathematically robust, foldover-free parameterization that is subject to positional constraints continues to be a challenge. In the present paper, this foldover problem is addressed by developing radial basis function (RBF)-based reparameterization. Given initial 2D embedding of a 3D surface, the proposed method can reparameterize 2D embedding into a foldover-free 2D mesh, satisfying a set of user-specified constraint points. In addition, this approach is mesh free. Therefore, generating smooth texture mapping results is possible without extra smoothing optimization.

An improved predictive functional control method with application to PMSM systems

NASA Astrophysics Data System (ADS)

Li, Shihua; Liu, Huixian; Fu, Wenshu

2017-01-01

In common design of prediction model-based control method, usually disturbances are not considered in the prediction model as well as the control design. For the control systems with large amplitude or strong disturbances, it is difficult to precisely predict the future outputs according to the conventional prediction model, and thus the desired optimal closed-loop performance will be degraded to some extent. To this end, an improved predictive functional control (PFC) method is developed in this paper by embedding disturbance information into the system model. Here, a composite prediction model is thus obtained by embedding the estimated value of disturbances, where disturbance observer (DOB) is employed to estimate the lumped disturbances. So the influence of disturbances on system is taken into account in optimisation procedure. Finally, considering the speed control problem for permanent magnet synchronous motor (PMSM) servo system, a control scheme based on the improved PFC method is designed to ensure an optimal closed-loop performance even in the presence of disturbances. Simulation and experimental results based on a hardware platform are provided to confirm the effectiveness of the proposed algorithm.

Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-07-01

This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

Embedding of multidimensional time-dependent observations.

PubMed

Barnard, J P; Aldrich, C; Gerber, M

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Embedding of multidimensional time-dependent observations

NASA Astrophysics Data System (ADS)

Barnard, Jakobus P.; Aldrich, Chris; Gerber, Marius

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Low-complexity object detection with deep convolutional neural network for embedded systems

NASA Astrophysics Data System (ADS)

Tripathi, Subarna; Kang, Byeongkeun; Dane, Gokce; Nguyen, Truong

2017-09-01

We investigate low-complexity convolutional neural networks (CNNs) for object detection for embedded vision applications. It is well-known that consolidation of an embedded system for CNN-based object detection is more challenging due to computation and memory requirement comparing with problems like image classification. To achieve these requirements, we design and develop an end-to-end TensorFlow (TF)-based fully-convolutional deep neural network for generic object detection task inspired by one of the fastest framework, YOLO.1 The proposed network predicts the localization of every object by regressing the coordinates of the corresponding bounding box as in YOLO. Hence, the network is able to detect any objects without any limitations in the size of the objects. However, unlike YOLO, all the layers in the proposed network is fully-convolutional. Thus, it is able to take input images of any size. We pick face detection as an use case. We evaluate the proposed model for face detection on FDDB dataset and Widerface dataset. As another use case of generic object detection, we evaluate its performance on PASCAL VOC dataset. The experimental results demonstrate that the proposed network can predict object instances of different sizes and poses in a single frame. Moreover, the results show that the proposed method achieves comparative accuracy comparing with the state-of-the-art CNN-based object detection methods while reducing the model size by 3× and memory-BW by 3 - 4× comparing with one of the best real-time CNN-based object detectors, YOLO. Our 8-bit fixed-point TF-model provides additional 4× memory reduction while keeping the accuracy nearly as good as the floating-point model. Moreover, the fixed- point model is capable of achieving 20× faster inference speed comparing with the floating-point model. Thus, the proposed method is promising for embedded implementations.

“You're just one of the group when you're embedded”: report from a mixed-method investigation of the research-embedded health librarian experience*

PubMed Central

Greyson, Devon; Surette, Soleil; Dennett, Liz; Chatterley, Trish

2013-01-01

Objective: Embedded librarianship has received much attention in recent years. A model of embeddedness rarely discussed to date is that of research-embedded health librarians (REHLs). This study explores the characteristics of Canadian REHLs and the situations in which they are employed. Methods: The authors employed a sequential, mixed-method design. An online survey provided descriptive statistics about REHLs' positions and work experiences. This informed a series of focus group interviews that expanded upon the survey. Through constant comparison, we conducted qualitative descriptive analysis of the interviews. Results: Based on twenty-nine survey responses and four group interviews, we created a portrait of a “typical” REHL and discovered themes relevant to REHL work. REHLs may identify more strongly as researchers than as librarians, with corresponding professional needs and rewards. REHLs value “belonging” to the research team, involvement in full project lifecycles, and in-depth relationships with nonlibrarian colleagues. Despite widely expressed job satisfaction, many REHLs struggle with isolation from library and information science peers and relative lack of job security. Conclusions: REHLs differ from non-embedded health librarians, as well as from other types of embedded librarians. REHLs' work also differs from just a decade or two ago, prior to widespread Internet access to digital resources. Implications: Given that research-embedded librarianship appears to be a distinct and growing subset of health librarianship, libraries, master's of library and information science programs, and professional associations will need to respond to the support and education needs of REHLs or risk losing them to the health research field. PMID:24163600

Feature-based component model for design of embedded systems

NASA Astrophysics Data System (ADS)

Zha, Xuan Fang; Sriram, Ram D.

2004-11-01

An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.

A Student Experiment Method for Learning the Basics of Embedded Software Technologies Including Hardware/Software Co-design

NASA Astrophysics Data System (ADS)

Kambe, Hidetoshi; Mitsui, Hiroyasu; Endo, Satoshi; Koizumi, Hisao

The applications of embedded system technologies have spread widely in various products, such as home appliances, cellular phones, automobiles, industrial machines and so on. Due to intensified competition, embedded software has expanded its role in realizing sophisticated functions, and new development methods like a hardware/software (HW/SW) co-design for uniting HW and SW development have been researched. The shortfall of embedded SW engineers was estimated to be approximately 99,000 in the year 2006, in Japan. Embedded SW engineers should understand HW technologies and system architecture design as well as SW technologies. However, a few universities offer this kind of education systematically. We propose a student experiment method for learning the basics of embedded system development, which includes a set of experiments for developing embedded SW, developing embedded HW and experiencing HW/SW co-design. The co-design experiment helps students learn about the basics of embedded system architecture design and the flow of designing actual HW and SW modules. We developed these experiments and evaluated them.

Implementing Assessment in an Outcome-Based Marketing Curriculum

ERIC Educational Resources Information Center

Borin, Norm; Metcalf, Lynn E.; Tietje, Brian C.

2008-01-01

This article describes the development and implementation of assessment in a new outcome-based marketing curriculum that was developed using a zero-based approach. Outcomes for the marketing curriculum were specified at the program, department, course, and lesson levels. Direct embedded assessments as well as indirect assessment methods were used…

Geminal embedding scheme for optimal atomic basis set construction in correlated calculations

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

Sorella, S., E-mail: sorella@sissa.it; Devaux, N.; Dagrada, M., E-mail: mario.dagrada@impmc.upmc.fr

2015-12-28

We introduce an efficient method to construct optimal and system adaptive basis sets for use in electronic structure and quantum Monte Carlo calculations. The method is based on an embedding scheme in which a reference atom is singled out from its environment, while the entire system (atom and environment) is described by a Slater determinant or its antisymmetrized geminal power (AGP) extension. The embedding procedure described here allows for the systematic and consistent contraction of the primitive basis set into geminal embedded orbitals (GEOs), with a dramatic reduction of the number of variational parameters necessary to represent the many-body wavemore » function, for a chosen target accuracy. Within the variational Monte Carlo method, the Slater or AGP part is determined by a variational minimization of the energy of the whole system in presence of a flexible and accurate Jastrow factor, representing most of the dynamical electronic correlation. The resulting GEO basis set opens the way for a fully controlled optimization of many-body wave functions in electronic structure calculation of bulk materials, namely, containing a large number of electrons and atoms. We present applications on the water molecule, the volume collapse transition in cerium, and the high-pressure liquid hydrogen.« less

Nonlinear dimensionality reduction of data lying on the multicluster manifold.

PubMed

Meng, Deyu; Leung, Yee; Fung, Tung; Xu, Zongben

2008-08-01

A new method, which is called decomposition-composition (D-C) method, is proposed for the nonlinear dimensionality reduction (NLDR) of data lying on the multicluster manifold. The main idea is first to decompose a given data set into clusters and independently calculate the low-dimensional embeddings of each cluster by the decomposition procedure. Based on the intercluster connections, the embeddings of all clusters are then composed into their proper positions and orientations by the composition procedure. Different from other NLDR methods for multicluster data, which consider associatively the intracluster and intercluster information, the D-C method capitalizes on the separate employment of the intracluster neighborhood structures and the intercluster topologies for effective dimensionality reduction. This, on one hand, isometrically preserves the rigid-body shapes of the clusters in the embedding process and, on the other hand, guarantees the proper locations and orientations of all clusters. The theoretical arguments are supported by a series of experiments performed on the synthetic and real-life data sets. In addition, the computational complexity of the proposed method is analyzed, and its efficiency is theoretically analyzed and experimentally demonstrated. Related strategies for automatic parameter selection are also examined.

Novel Concrete Temperature Monitoring Method Based on an Embedded Passive RFID Sensor Tag.

PubMed

Liu, Yongsheng; Deng, Fangming; He, Yigang; Li, Bing; Liang, Zhen; Zhou, Shuangxi

2017-06-22

This paper firstly introduces the importance of temperature control in concrete measurement, then a passive radio frequency identification (RFID) sensor tag embedded for concrete temperature monitoring is presented. In order to reduce the influences of concrete electromagnetic parameters during the drying process, a T-type antenna is proposed to measure the concrete temperature at the required depth. The proposed RFID sensor tag is based on the EPC generation-2 ultra-high frequency (UHF) communication protocol and operates in passive mode. The temperature sensor can convert the sensor signals to corresponding digital signals without an external reference clock due to the adoption of phase-locked loop (PLL)-based architecture. Laboratory experimentation and on-site testing demonstrate that our sensor tag embedded in concrete can provide reliable communication performance in passive mode. The maximum communicating distance between reader and tag is 7 m at the operating frequency of 915 MHz and the tested results show high consistency with the results tested by a thermocouple.

Novel Concrete Temperature Monitoring Method Based on an Embedded Passive RFID Sensor Tag

PubMed Central

Liu, Yongsheng; Deng, Fangming; He, Yigang; Li, Bing; Liang, Zhen; Zhou, Shuangxi

2017-01-01

This paper firstly introduces the importance of temperature control in concrete measurement, then a passive radio frequency identification (RFID) sensor tag embedded for concrete temperature monitoring is presented. In order to reduce the influences of concrete electromagnetic parameters during the drying process, a T-type antenna is proposed to measure the concrete temperature at the required depth. The proposed RFID sensor tag is based on the EPC generation-2 ultra-high frequency (UHF) communication protocol and operates in passive mode. The temperature sensor can convert the sensor signals to corresponding digital signals without an external reference clock due to the adoption of phase-locked loop (PLL)-based architecture. Laboratory experimentation and on-site testing demonstrate that our sensor tag embedded in concrete can provide reliable communication performance in passive mode. The maximum communicating distance between reader and tag is 7 m at the operating frequency of 915 MHz and the tested results show high consistency with the results tested by a thermocouple. PMID:28640188

Applying Human Factors Principles to Mitigate Usability Issues Related to Embedded Assumptions in Health Information Technology Design

PubMed Central

Lowry, Svetlana Z; Patterson, Emily S

2014-01-01

Background There is growing recognition that design flaws in health information technology (HIT) lead to increased cognitive work, impact workflows, and produce other undesirable user experiences that contribute to usability issues and, in some cases, patient harm. These usability issues may in turn contribute to HIT utilization disparities and patient safety concerns, particularly among “non-typical” HIT users and their health care providers. Health care disparities are associated with poor health outcomes, premature death, and increased health care costs. HIT has the potential to reduce these disparate outcomes. In the computer science field, it has long been recognized that embedded cultural assumptions can reduce the usability, usefulness, and safety of HIT systems for populations whose characteristics differ from “stereotypical” users. Among these non-typical users, inappropriate embedded design assumptions may contribute to health care disparities. It is unclear how to address potentially inappropriate embedded HIT design assumptions once detected. Objective The objective of this paper is to explain HIT universal design principles derived from the human factors engineering literature that can help to overcome potential usability and/or patient safety issues that are associated with unrecognized, embedded assumptions about cultural groups when designing HIT systems. Methods Existing best practices, guidance, and standards in software usability and accessibility were subjected to a 5-step expert review process to identify and summarize those best practices, guidance, and standards that could help identify and/or address embedded design assumptions in HIT that could negatively impact patient safety, particularly for non-majority HIT user populations. An iterative consensus-based process was then used to derive evidence-based design principles from the data to address potentially inappropriate embedded cultural assumptions. Results Design principles that may help identify and address embedded HIT design assumptions are available in the existing literature. Conclusions Evidence-based HIT design principles derived from existing human factors and informatics literature can help HIT developers identify and address embedded cultural assumptions that may underlie HIT-associated usability and patient safety concerns as well as health care disparities. PMID:27025349

Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Motivation: Most functions within the cell emerge thanks to protein–protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable. Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions. Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction. Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. Availability: https://sites.google.com/site/carlovittoriocannistraci/home Contact: kalokagathos.agon@gmail.com or timothy.ravasi@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23812985

Microfluidic networks embedded in a printed circuit board

NASA Astrophysics Data System (ADS)

Dong, Liangwei; Hu, Yueli

2017-07-01

In order to improve the robustness of microfluidic networks in printed circuit board (PCB)-based microfluidic platforms, a new method was presented. A pattern in a PCB was formed using hollowed-out technology. Polydimethylsiloxane was partly filled in the hollowed-out fields after mounting an adhesive tape on the bottom of the PCB, and solidified in an oven. Then, microfluidic networks were built using soft lithography technology. Microfluidic transportation and dilution operations were demonstrated using the fabricated microfluidic platform. Results show that this method can embed microfluidic networks into a PCB, and microfluidic operations can be implemented in the microfluidic networks embedded into the PCB.

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

PubMed

Aungkulanon, Pasura; Luangpaiboon, Pongchanun

2016-01-01

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

Development of a metal-based composite actuator

NASA Astrophysics Data System (ADS)

Asanuma, Hiroshi; Haga, Osamu; Ishii, Toshio; Kurihara, Haruki; Ohira, Junichiro; Hakoda, Genji

2000-06-01

This paper describes a basic concept and elemental developments to realize a metal based composite actuator to be used for smart structures. In this study, CFRP prepreg was laminated on aluminum plate to develop an actuator and this laminate could perform unidirectional actuation. SiC continuous fiber/Al composite thin plate could also be used for form a modified type of actuator instead of using CFRP. As sensors to be embedded in this actuator, the following ones wee developed. (1) A pre-notched optical fiber filament could be embedded in aluminum matrix without fracture by the interphase forming/bonding method with copper insert and could be fractured in it at the notch, which enabled forming of an optical interference type strain sensor. (2) Nickel wire could be uniformly oxidized and embedded in aluminum matrix without fracture, which could successfully work as a temperature sensor and a strain sensor.

Jointly learning word embeddings using a corpus and a knowledge base

PubMed Central

Bollegala, Danushka; Maehara, Takanori; Kawarabayashi, Ken-ichi

2018-01-01

Methods for representing the meaning of words in vector spaces purely using the information distributed in text corpora have proved to be very valuable in various text mining and natural language processing (NLP) tasks. However, these methods still disregard the valuable semantic relational structure between words in co-occurring contexts. These beneficial semantic relational structures are contained in manually-created knowledge bases (KBs) such as ontologies and semantic lexicons, where the meanings of words are represented by defining the various relationships that exist among those words. We combine the knowledge in both a corpus and a KB to learn better word embeddings. Specifically, we propose a joint word representation learning method that uses the knowledge in the KBs, and simultaneously predicts the co-occurrences of two words in a corpus context. In particular, we use the corpus to define our objective function subject to the relational constrains derived from the KB. We further utilise the corpus co-occurrence statistics to propose two novel approaches, Nearest Neighbour Expansion (NNE) and Hedged Nearest Neighbour Expansion (HNE), that dynamically expand the KB and therefore derive more constraints that guide the optimisation process. Our experimental results over a wide-range of benchmark tasks demonstrate that the proposed method statistically significantly improves the accuracy of the word embeddings learnt. It outperforms a corpus-only baseline and reports an improvement of a number of previously proposed methods that incorporate corpora and KBs in both semantic similarity prediction and word analogy detection tasks. PMID:29529052

Preliminary Development of Online Monitoring Acoustic Emission System for the Integrity of Research Reactor Components

NASA Astrophysics Data System (ADS)

Bakhri, S.; Sumarno, E.; Himawan, R.; Akbar, T. Y.; Subekti, M.; Sunaryo, G. R.

2018-02-01

Three research reactors owned by BATAN have been more than 25 years. Aging of (Structure, System and Component) SSC which is mainly related to mechanical causes become the most important issue for the sustainability and safety operation. Acoustic Emission (AE) is one of the appropriate and recommended methods by the IAEA for inspection as well as at the same time for the monitoring of mechanical SSC related. However, the advantages of AE method in detecting the acoustic emission both for the inspection and the online monitoring require a relatively complex measurement system including hardware software system for the signal detection and analysis purposes. Therefore, aim of this work was to develop an AE system based on an embedded system which capable for doing both the online monitoring and inspection of the research reactor’s integrity structure. An embedded system was selected due to the possibility to install the equipment on the field in extreme environmental condition with capability to store, analyses, and send the required information for further maintenance and operation. The research was done by designing the embedded system based on the Field Programmable Gate Array (FPGA) platform, because of their execution speed and system reconfigurable opportunities. The AE embedded system is then tested to identify the AE source location and AE characteristic under tensile material testing. The developed system successfully acquire the AE elastic waveform and determine the parameter-based analysis such as the amplitude, peak, duration, rise time, counts and the average frequency both for the source location test and the tensile test.

Content-based audio authentication using a hierarchical patchwork watermark embedding

NASA Astrophysics Data System (ADS)

Gulbis, Michael; Müller, Erika

2010-05-01

Content-based audio authentication watermarking techniques extract perceptual relevant audio features, which are robustly embedded into the audio file to protect. Manipulations of the audio file are detected on the basis of changes between the original embedded feature information and the anew extracted features during verification. The main challenges of content-based watermarking are on the one hand the identification of a suitable audio feature to distinguish between content preserving and malicious manipulations. On the other hand the development of a watermark, which is robust against content preserving modifications and able to carry the whole authentication information. The payload requirements are significantly higher compared to transaction watermarking or copyright protection. Finally, the watermark embedding should not influence the feature extraction to avoid false alarms. Current systems still lack a sufficient alignment of watermarking algorithm and feature extraction. In previous work we developed a content-based audio authentication watermarking approach. The feature is based on changes in DCT domain over time. A patchwork algorithm based watermark was used to embed multiple one bit watermarks. The embedding process uses the feature domain without inflicting distortions to the feature. The watermark payload is limited by the feature extraction, more precisely the critical bands. The payload is inverse proportional to segment duration of the audio file segmentation. Transparency behavior was analyzed in dependence of segment size and thus the watermark payload. At a segment duration of about 20 ms the transparency shows an optimum (measured in units of Objective Difference Grade). Transparency and/or robustness are fast decreased for working points beyond this area. Therefore, these working points are unsuitable to gain further payload, needed for the embedding of the whole authentication information. In this paper we present a hierarchical extension of the watermark method to overcome the limitations given by the feature extraction. The approach is a recursive application of the patchwork algorithm onto its own patches, with a modified patch selection to ensure a better signal to noise ratio for the watermark embedding. The robustness evaluation was done by compression (mp3, ogg, aac), normalization, and several attacks of the stirmark benchmark for audio suite. Compared on the base of same payload and transparency the hierarchical approach shows improved robustness.

Noncontact power/interrogation system for smart structures

NASA Astrophysics Data System (ADS)

Spillman, William B., Jr.; Durkee, S.

1994-05-01

The field of smart structures has been largely driven by the development of new high performance designed materials. Use of these materials has been generally limited due to the fact that they have not been in use long enough for statistical data bases to be developed on their failure modes. Real time health monitoring is therefore required for the benefits of structures using these materials to be realized. In this paper a non-contact method of powering and interrogating embedded electronic and opto-electronic systems is described. The technique utilizes inductive coupling between external and embedded coils etched on thin electronic circuit cards. The technique can be utilized to interrogate embedded sensors and to provide > 250 mW for embedded electronics. The system has been successfully demonstrated with a number of composite and plastic materials through material thicknesses up to 1 cm. An analytical description of the system is provided along with experimental results.

Time series analyses of breathing patterns of lung cancer patients using nonlinear dynamical system theory.

PubMed

Tewatia, D K; Tolakanahalli, R P; Paliwal, B R; Tomé, W A

2011-04-07

The underlying requirements for successful implementation of any efficient tumour motion management strategy are regularity and reproducibility of a patient's breathing pattern. The physiological act of breathing is controlled by multiple nonlinear feedback and feed-forward couplings. It would therefore be appropriate to analyse the breathing pattern of lung cancer patients in the light of nonlinear dynamical system theory. The purpose of this paper is to analyse the one-dimensional respiratory time series of lung cancer patients based on nonlinear dynamics and delay coordinate state space embedding. It is very important to select a suitable pair of embedding dimension 'm' and time delay 'τ' when performing a state space reconstruction. Appropriate time delay and embedding dimension were obtained using well-established methods, namely mutual information and the false nearest neighbour method, respectively. Establishing stationarity and determinism in a given scalar time series is a prerequisite to demonstrating that the nonlinear dynamical system that gave rise to the scalar time series exhibits a sensitive dependence on initial conditions, i.e. is chaotic. Hence, once an appropriate state space embedding of the dynamical system has been reconstructed, we show that the time series of the nonlinear dynamical systems under study are both stationary and deterministic in nature. Once both criteria are established, we proceed to calculate the largest Lyapunov exponent (LLE), which is an invariant quantity under time delay embedding. The LLE for all 16 patients is positive, which along with stationarity and determinism establishes the fact that the time series of a lung cancer patient's breathing pattern is not random or irregular, but rather it is deterministic in nature albeit chaotic. These results indicate that chaotic characteristics exist in the respiratory waveform and techniques based on state space dynamics should be employed for tumour motion management.

Exact vibration analysis of a double-nanobeam-systems embedded in an elastic medium by a Hamiltonian-based method

NASA Astrophysics Data System (ADS)

Zhou, Zhenhuan; Li, Yuejie; Fan, Junhai; Rong, Dalun; Sui, Guohao; Xu, Chenghui

2018-05-01

A new Hamiltonian-based approach is presented for finding exact solutions for transverse vibrations of double-nanobeam-systems embedded in an elastic medium. The continuum model is established within the frameworks of the symplectic methodology and the nonlocal Euler-Bernoulli and Timoshenko beam beams. The symplectic eigenfunctions are obtained after expressing the governing equations in a Hamiltonian form. Exact frequency equations, vibration modes and displacement amplitudes are obtained by using symplectic eigenfunctions and end conditions. Comparisons with previously published work are presented to illustrate the accuracy and reliability of the proposed method. The comprehensive results for arbitrary boundary conditions could serve as benchmark results for verifying numerically obtained solutions. In addition, a study on the difference between the nonlocal beam and the nonlocal plate is also included.

Quantum mechanical fragment methods based on partitioning atoms or partitioning coordinates.

PubMed

Wang, Bo; Yang, Ke R; Xu, Xuefei; Isegawa, Miho; Leverentz, Hannah R; Truhlar, Donald G

2014-09-16

Conspectus The development of more efficient and more accurate ways to represent reactive potential energy surfaces is a requirement for extending the simulation of large systems to more complex systems, longer-time dynamical processes, and more complete statistical mechanical sampling. One way to treat large systems is by direct dynamics fragment methods. Another way is by fitting system-specific analytic potential energy functions with methods adapted to large systems. Here we consider both approaches. First we consider three fragment methods that allow a given monomer to appear in more than one fragment. The first two approaches are the electrostatically embedded many-body (EE-MB) expansion and the electrostatically embedded many-body expansion of the correlation energy (EE-MB-CE), which we have shown to yield quite accurate results even when one restricts the calculations to include only electrostatically embedded dimers. The third fragment method is the electrostatically embedded molecular tailoring approach (EE-MTA), which is more flexible than EE-MB and EE-MB-CE. We show that electrostatic embedding greatly improves the accuracy of these approaches compared with the original unembedded approaches. Quantum mechanical fragment methods share with combined quantum mechanical/molecular mechanical (QM/MM) methods the need to treat a quantum mechanical fragment in the presence of the rest of the system, which is especially challenging for those parts of the rest of the system that are close to the boundary of the quantum mechanical fragment. This is a delicate matter even for fragments that are not covalently bonded to the rest of the system, but it becomes even more difficult when the boundary of the quantum mechanical fragment cuts a bond. We have developed a suite of methods for more realistically treating interactions across such boundaries. These methods include redistributing and balancing the external partial atomic charges and the use of tuned fluorine atoms for capping dangling bonds, and we have shown that they can greatly improve the accuracy. Finally we present a new approach that goes beyond QM/MM by combining the convenience of molecular mechanics with the accuracy of fitting a potential function to electronic structure calculations on a specific system. To make the latter practical for systems with a large number of degrees of freedom, we developed a method to interpolate between local internal-coordinate fits to the potential energy. A key issue for the application to large systems is that rather than assigning the atoms or monomers to fragments, we assign the internal coordinates to reaction, secondary, and tertiary sets. Thus, we make a partition in coordinate space rather than atom space. Fits to the local dependence of the potential energy on tertiary coordinates are arrayed along a preselected reaction coordinate at a sequence of geometries called anchor points; the potential energy function is called an anchor points reactive potential. Electrostatically embedded fragment methods and the anchor points reactive potential, because they are based on treating an entire system by quantum mechanical electronic structure methods but are affordable for large and complex systems, have the potential to open new areas for accurate simulations where combined QM/MM methods are inadequate.

Embedded optical interconnect technology in data storage systems

NASA Astrophysics Data System (ADS)

Pitwon, Richard C. A.; Hopkins, Ken; Milward, Dave; Muggeridge, Malcolm

2010-05-01

As both data storage interconnect speeds increase and form factors in hard disk drive technologies continue to shrink, the density of printed channels on the storage array midplane goes up. The dominant interconnect protocol on storage array midplanes is expected to increase to 12 Gb/s by 2012 thereby exacerbating the performance bottleneck in future digital data storage systems. The design challenges inherent to modern data storage systems are discussed and an embedded optical infrastructure proposed to mitigate this bottleneck. The proposed solution is based on the deployment of an electro-optical printed circuit board and active interconnect technology. The connection architecture adopted would allow for electronic line cards with active optical edge connectors to be plugged into and unplugged from a passive electro-optical midplane with embedded polymeric waveguides. A demonstration platform has been developed to assess the viability of embedded electro-optical midplane technology in dense data storage systems and successfully demonstrated at 10.3 Gb/s. Active connectors incorporate optical transceiver interfaces operating at 850 nm and are connected in an in-plane coupling configuration to the embedded waveguides in the midplane. In addition a novel method of passively aligning and assembling passive optical devices to embedded polymer waveguide arrays has also been demonstrated.

A telemetry system embedded in clothes for indoor localization and elderly health monitoring.

PubMed

Charlon, Yoann; Fourty, Nicolas; Campo, Eric

2013-09-04

This paper presents a telemetry system used in a combined trilateration method for the precise indoor localization of the elderly who need health monitoring. The system is based on the association of two wireless technologies: ultrasonic and 802.15.4. The use of the 802.15.4 RF signal gives the reference starting time of the ultrasonic emission (time difference of arrival method). A time of flight measurement of the ultrasonic pulses provides the distances between the mobile node and three anchor points. These distance measurements are then used to locate the mobile node using the trilateration method with an accuracy of a few centimetres. The originality of our work lies in embedding the mobile node in clothes. The system is embedded in clothes in two ways: on a shoe in order to form a "smart" shoe and in a hat in order to form a "smart" hat. Both accessories allow movements, gait speed and distance covered to be monitored for health applications. Experiments in a test room are presented to show the effectiveness of our system.

Immunohistochemical myofiber typing and high-resolution myofibrillar lesion detection in LR white embedded muscle

NASA Technical Reports Server (NTRS)

Thompson, J. L.; Vijayan, K.; Riley, D. A.

2000-01-01

We have developed a method of fixing, embedding, sectioning, and staining that allows high-resolution detection of myofibrillar structure and myosin immunocytochemical muscle fiber typing in serial semithin sections of LR White plastic embedded muscle at the light microscopic level. Traditional approaches, such as cryostat sections, permit fiber typing, but small myofibrillar lesions (1-3 sarcomeres) are difficult to detect because of section thickness. Semithin sections of hydrophobic resins do not stain well either histochemically or immunocytochemically. Electron microscopy can resolve lesions and discriminate fiber types based on morphology, but the sampling area is small. Our goal was to develop a rapid method for defining both fiber type and high-resolution primary myofibrillar lesion damage. Mild fixation (1-4% paraformaldehyde, 0. 05-0.1% glutaraldehyde) and embedment in a hydrophilic resin (LR White) were used. Myofibrillar structure was extremely well preserved at the light microscopic (LM) level, and lesions could be readily resolved in Toluidine blue stained 500-nm sections. Fiber type was defined by LM immunomyosin staining of serial plastic semithin sections, which demonstrated reciprocal staining patterns for "fast (Sigma M4276) and "total" (skeletal muscle) myosins (Sigma M7523). Copyright 2000 Wiley-Liss, Inc.

Correlation of live-cell imaging with volume scanning electron microscopy.

PubMed

Lucas, Miriam S; Günthert, Maja; Bittermann, Anne Greet; de Marco, Alex; Wepf, Roger

2017-01-01

Live-cell imaging is one of the most widely applied methods in live science. Here we describe two setups for live-cell imaging, which can easily be combined with volume SEM for correlative studies. The first procedure applies cell culture dishes with a gridded glass support, which can be used for any light microscopy modality. The second approach is a flow-chamber setup based on Ibidi μ-slides. Both live-cell imaging strategies can be followed up with serial blockface- or focused ion beam-scanning electron microscopy. Two types of resin embedding after heavy metal staining and dehydration are presented making best use of the particular advantages of each imaging modality: classical en-bloc embedding and thin-layer plastification. The latter can be used only for focused ion beam-scanning electron microscopy, but is advantageous for studying cell-interactions with specific substrates, or when the substrate cannot be removed. En-bloc embedding has diverse applications and can be applied for both described volume scanning electron microscopy techniques. Finally, strategies for relocating the cell of interest are discussed for both embedding approaches and in respect to the applied light and scanning electron microscopy methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Discriminative graph embedding for label propagation.

PubMed

Nguyen, Canh Hao; Mamitsuka, Hiroshi

2011-09-01

In many applications, the available information is encoded in graph structures. This is a common problem in biological networks, social networks, web communities and document citations. We investigate the problem of classifying nodes' labels on a similarity graph given only a graph structure on the nodes. Conventional machine learning methods usually require data to reside in some Euclidean spaces or to have a kernel representation. Applying these methods to nodes on graphs would require embedding the graphs into these spaces. By embedding and then learning the nodes on graphs, most methods are either flexible with different learning objectives or efficient enough for large scale applications. We propose a method to embed a graph into a feature space for a discriminative purpose. Our idea is to include label information into the embedding process, making the space representation tailored to the task. We design embedding objective functions that the following learning formulations become spectral transforms. We then reformulate these spectral transforms into multiple kernel learning problems. Our method, while being tailored to the discriminative tasks, is efficient and can scale to massive data sets. We show the need of discriminative embedding on some simulations. Applying to biological network problems, our method is shown to outperform baselines.

Distributed strain measurement and possible breakage detection of optical-fiber-embedded composite structure using slope-assisted Brillouin optical correlation-domain reflectometry

NASA Astrophysics Data System (ADS)

Lee, Heeyoung; Ochi, Yutaka; Matsui, Takahiro; Matsumoto, Yukihiro; Tanaka, Yosuke; Nakamura, Hitoshi; Mizuno, Yosuke; Nakamura, Kentaro

2018-07-01

Slope-assisted Brillouin optical correlation-domain reflectometry (SA-BOCDR) is a recently developed structural health monitoring technique for measurements of strain, temperature, and loss distributions along optical fibers. Although the basic operational principle of this method has been clarified, no measurements using optical fibers embedded in actual structures have been reported. As a first step towards such practical applications, in this study, we present an example of an SA-BOCDR-based diagnosis using a composite structure with carbon fiber-reinforced plastics. The system’s output agrees well with the actual strain distributions. We were also able to detect the breakage of the embedded fiber, thus demonstrating the promise of SA-BOCDR for practical applications.

Optimizing Aspect-Oriented Mechanisms for Embedded Applications

NASA Astrophysics Data System (ADS)

Hundt, Christine; Stöhr, Daniel; Glesner, Sabine

As applications for small embedded mobile devices are getting larger and more complex, it becomes inevitable to adopt more advanced software engineering methods from the field of desktop application development. Aspect-oriented programming (AOP) is a promising approach due to its advanced modularization capabilities. However, existing AOP languages tend to add a substantial overhead in both execution time and code size which restricts their practicality for small devices with limited resources. In this paper, we present optimizations for aspect-oriented mechanisms at the level of the virtual machine. Our experiments show that these optimizations yield a considerable performance gain along with a reduction of the code size. Thus, our optimizations establish the base for using advanced aspect-oriented modularization techniques for developing Java applications on small embedded devices.

Suggested Interactivity: Seeking Perceived Affordances for Information Visualization.

PubMed

Boy, Jeremy; Eveillard, Louis; Detienne, Françoise; Fekete, Jean-Daniel

2016-01-01

In this article, we investigate methods for suggesting the interactivity of online visualizations embedded with text. We first assess the need for such methods by conducting three initial experiments on Amazon's Mechanical Turk. We then present a design space for Suggested Interactivity (i. e., visual cues used as perceived affordances-SI), based on a survey of 382 HTML5 and visualization websites. Finally, we assess the effectiveness of three SI cues we designed for suggesting the interactivity of bar charts embedded with text. Our results show that only one cue (SI3) was successful in inciting participants to interact with the visualizations, and we hypothesize this is because this particular cue provided feedforward.

Transverse Vibration of Tapered Single-Walled Carbon Nanotubes Embedded in Viscoelastic Medium

NASA Astrophysics Data System (ADS)

Lei, Y. J.; Zhang, D. P.; Shen, Z. B.

2017-12-01

Based on the nonlocal theory, Euler-Bernoulli beam theory and Kelvin viscoelastic foundation model, free transverse vibration is studied for a tapered viscoelastic single-walled carbon nanotube (visco-SWCNT) embedded in a viscoelastic medium. Firstly, the governing equations for vibration analysis are established. And then, we derive the natural frequencies in closed form for SWCNTs with arbitrary boundary conditions by applying transfer function method and perturbation method. Numerical results are also presented to discuss the effects of nonlocal parameter, relaxation time and taper parameter of SWCNTs, and material property parameters of the medium. This study demonstrates that the proposed model is available for vibration analysis of the tapered SWCNTs-viscoelastic medium coupling system.

Fabrication and evaluation of a sustained-release chitosan-based scaffold embedded with PLGA microspheres.

PubMed

Song, Kedong; Liu, Yingchao; Macedo, Hugo M; Jiang, Lili; Li, Chao; Mei, Guanyu; Liu, Tianqing

2013-04-01

Nutrient depletion within three-dimensional (3D) scaffolds is one of the major hurdles in the use of this technology to grow cells for applications in tissue engineering. In order to help in addressing it, we herein propose to use the controlled release of encapsulated nutrients within polymer microspheres into chitosan-based 3D scaffolds, wherein the microspheres are embedded. This method has allowed maintaining a stable concentration of nutrients within the scaffolds over the long term. The polymer microspheres were prepared using multiple emulsions (w/o/w), in which bovine serum albumin (BSA) and poly (lactic-co-glycolic) acid (PLGA) were regarded as the protein pattern and the exoperidium material, respectively. These were then mixed with a chitosan solution in order to form the scaffolds by cryo-desiccation. The release of BSA, entrapped within the embedded microspheres, was monitored with time using a BCA kit. The morphology and structure of the PLGA microspheres containing BSA before and after embedding within the scaffold were observed under a scanning electron microscope (SEM). These had a round shape with diameters in the range of 27-55 μm, whereas the chitosan-based scaffolds had a uniform porous structure with the microspheres uniformly dispersed within their 3D structure and without any morphological change. In addition, the porosity, water absorption and degradation rate at 37 °C in an aqueous environment of 1% chitosan-based scaffolds were (92.99±2.51) %, (89.66±0.66) % and (73.77±3.21) %, respectively. The studies of BSA release from the embedded microspheres have shown a sustained and cumulative tendency with little initial burst, with (20.24±0.83) % of the initial amount released after 168 h (an average rate of 0.12%/h). The protein concentration within the chitosan-based scaffolds after 168 h was found to be (11.44±1.81)×10(-2) mg/mL. This novel chitosan-based scaffold embedded with PLGA microspheres has proven to be a promising technique for the development of new and improved tissue engineering scaffolds. Copyright © 2012 Elsevier B.V. All rights reserved.

Nuclear magnetic resonance technology in acupoint catgut embedding therapy for the treatment of menopausal panic disorder: its applications

NASA Astrophysics Data System (ADS)

Chen, Gui-zhen; Zhang, Sha-sha; Xu, Yun-xiang; Wang, Xiao-yun

2011-11-01

Nuclear Magnetic Resonance (NMR) is a diagnostic method which is non-invasive and non-ionizing irradiative to the human body. It not only suits structural, but also functional imaging. The NMR technique develops rapidly in its application in life science, which has become the hotspot in recent years. Menopausal panic disorder (MPD) is a typical psychosomatic disease during climacteric period, which may affect physical and mental health. Looking for a convenient, effective, and safe method, which is free of toxic-side effects to control the disease, is a modern medical issue. Based on reviewing the etiology and pathogenesis of MPD according to dual traditional Chinese medicine (TCM) and western medicine, further analyzed the advantages and principles for selecting acupoint prescription by tonifying kidney and benefiting marrow therapy for acupoint catgut-embedding to this disease. The application of Nuclear Magnetic Resonance Spectroscopy (NMRS) and Magnetic Resonance Imaging (MRI) technologies in mechanism research on acupoint catgut embedding for the treatment of MPD was discussed. It's pointed out that this intervention method is safe and effective to treat MPD. Breakthrough will be achieved from the research of the selection of acupoint prescription and therapeutic mechanism of acupoint catgut embedding for the treatment of menopausal panic disorder by utilizing the Functional Nuclear Magnetic Resonance Imaging (fMRI) and Metabonomics technologies.

Nuclear magnetic resonance technology in acupoint catgut embedding therapy for the treatment of menopausal panic disorder: its applications

NASA Astrophysics Data System (ADS)

Chen, Gui-zhen; Zhang, Sha-sha; Xu, Yun-xiang; Wang, Xiao-yun

2012-03-01

Nuclear Magnetic Resonance (NMR) is a diagnostic method which is non-invasive and non-ionizing irradiative to the human body. It not only suits structural, but also functional imaging. The NMR technique develops rapidly in its application in life science, which has become the hotspot in recent years. Menopausal panic disorder (MPD) is a typical psychosomatic disease during climacteric period, which may affect physical and mental health. Looking for a convenient, effective, and safe method, which is free of toxic-side effects to control the disease, is a modern medical issue. Based on reviewing the etiology and pathogenesis of MPD according to dual traditional Chinese medicine (TCM) and western medicine, further analyzed the advantages and principles for selecting acupoint prescription by tonifying kidney and benefiting marrow therapy for acupoint catgut-embedding to this disease. The application of Nuclear Magnetic Resonance Spectroscopy (NMRS) and Magnetic Resonance Imaging (MRI) technologies in mechanism research on acupoint catgut embedding for the treatment of MPD was discussed. It's pointed out that this intervention method is safe and effective to treat MPD. Breakthrough will be achieved from the research of the selection of acupoint prescription and therapeutic mechanism of acupoint catgut embedding for the treatment of menopausal panic disorder by utilizing the Functional Nuclear Magnetic Resonance Imaging (fMRI) and Metabonomics technologies.

A Robust Blind Quantum Copyright Protection Method for Colored Images Based on Owner's Signature

NASA Astrophysics Data System (ADS)

Heidari, Shahrokh; Gheibi, Reza; Houshmand, Monireh; Nagata, Koji

2017-08-01

Watermarking is the imperceptible embedding of watermark bits into multimedia data in order to use for different applications. Among all its applications, copyright protection is the most prominent usage which conceals information about the owner in the carrier, so as to prohibit others from assertion copyright. This application requires high level of robustness. In this paper, a new blind quantum copyright protection method based on owners's signature in RGB images is proposed. The method utilizes one of the RGB channels as indicator and two remained channels are used for embedding information about the owner. In our contribution the owner's signature is considered as a text. Therefore, in order to embed in colored image as watermark, a new quantum representation of text based on ASCII character set is offered. Experimental results which are analyzed in MATLAB environment, exhibit that the presented scheme shows good performance against attacks and can be used to find out who the real owner is. Finally, the discussed quantum copyright protection method is compared with a related work that our analysis confirm that the presented scheme is more secure and applicable than the previous ones currently found in the literature.

Developing and utilizing an Euler computational method for predicting the airframe/propulsion effects for an aft-mounted turboprop transport. Volume 2: User guide

NASA Technical Reports Server (NTRS)

Chen, H. C.; Neback, H. E.; Kao, T. J.; Yu, N. Y.; Kusunose, K.

1991-01-01

This manual explains how to use an Euler based computational method for predicting the airframe/propulsion integration effects for an aft-mounted turboprop transport. The propeller power effects are simulated by the actuator disk concept. This method consists of global flow field analysis and the embedded flow solution for predicting the detailed flow characteristics in the local vicinity of an aft-mounted propfan engine. The computational procedure includes the use of several computer programs performing four main functions: grid generation, Euler solution, grid embedding, and streamline tracing. This user's guide provides information for these programs, including input data preparations with sample input decks, output descriptions, and sample Unix scripts for program execution in the UNICOS environment.

Adjustment method for embedded metrology engine in an EM773 series microcontroller.

PubMed

Blazinšek, Iztok; Kotnik, Bojan; Chowdhury, Amor; Kačič, Zdravko

2015-09-01

This paper presents the problems of implementation and adjustment (calibration) of a metrology engine embedded in NXP's EM773 series microcontroller. The metrology engine is used in a smart metering application to collect data about energy utilization and is controlled with the use of metrology engine adjustment (calibration) parameters. The aim of this research is to develop a method which would enable the operators to find and verify the optimum parameters which would ensure the best possible accuracy. Properly adjusted (calibrated) metrology engines can then be used as a base for variety of products used in smart and intelligent environments. This paper focuses on the problems encountered in the development, partial automatisation, implementation and verification of this method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

MethylMeter(®): bisulfite-free quantitative and sensitive DNA methylation profiling and mutation detection in FFPE samples.

PubMed

McCarthy, David; Pulverer, Walter; Weinhaeusel, Andreas; Diago, Oscar R; Hogan, Daniel J; Ostertag, Derek; Hanna, Michelle M

2016-06-01

Development of a sensitive method for DNA methylation profiling and associated mutation detection in clinical samples. Formalin-fixed and paraffin-embedded tumors received by clinical laboratories often contain insufficient DNA for analysis with bisulfite or methylation sensitive restriction enzymes-based methods. To increase sensitivity, methyl-CpG DNA capture and Coupled Abscription PCR Signaling detection were combined in a new assay, MethylMeter(®). Gliomas were analyzed for MGMT methylation, glioma CpG island methylator phenotype and IDH1 R132H. MethylMeter had 100% assay success rate measuring all five biomarkers in formalin-fixed and paraffin-embedded tissue. MGMT methylation results were supported by survival and mRNA expression data. MethylMeter is a sensitive and quantitative method for multitarget DNA methylation profiling and associated mutation detection. The MethylMeter-based GliomaSTRAT assay measures methylation of four targets and one mutation to simultaneously grade gliomas and predict their response to temozolomide. This information is clinically valuable in management of gliomas.

Improving RF Transmit Power and Received Signal Strength in 2.4 GHz ZigBee Based Active RFID System with Embedded Method

NASA Astrophysics Data System (ADS)

Po'ad, F. A.; Ismail, W.; Jusoh, J. F.

2017-08-01

This paper describes the experiments and analysis conducted on 2.4 GHz embedded active Radio Frequency Identification (RFID) - Wireless Sensor Network (WSN) based system that has been developed for the purposes of location tracking and monitoring in indoor and outdoor environments. Several experiments are conducted to test the effectiveness and performance of the developed system and two of them is by measuring the Radio Frequency (RF) transmitting power and Received Signal Strength (RSS) to prove that the embedded active RFID tag is capable to generate higher transmit power during data transmission and able to provide better RSS reading compared to standalone RFID tag. Experiments are carried out on two RFID tags which are active RFID tag embedded with GPS and GSM (ER2G); and standalone RFID tag communicating with the same active RFID reader. The developed ER2G contributes 12.26 % transmit power and 6.47 % RSS reading higher than standalone RFID tag. The results conclude that the ER2G gives better performance compared to standalone RFID tag and can be used as guidelines for future design improvements.

Structural health monitoring for DOT using magnetic shape memory alloy cables in concrete

NASA Astrophysics Data System (ADS)

Davis, Allen; Mirsayar, Mirmilad; Sheahan, Emery; Hartl, Darren

2018-03-01

Embedding shape memory alloy (SMA) wires in concrete components offers the potential to monitor their structural health via external magnetic field sensing. Currently, structural health monitoring (SHM) is dominated by acoustic emission and vibration-based methods. Thus, it is attractive to pursue alternative damage sensing techniques that may lower the cost or increase the accuracy of SHM. In this work, SHM via magnetic field detection applied to embedded magnetic shape memory alloy (MSMA) is demonstrated both experimentally and using computational models. A concrete beam containing iron-based MSMA wire is subjected to a 3-point bend test where structural damage is induced, thereby resulting in a localized phase change of the MSMA wire. Magnetic field lines passing through the embedded MSMA domain are altered by this phase change and can thus be used to detect damage within the structure. A good correlation is observed between the computational and experimental results. Additionally, the implementation of stranded MSMA cables in place of the MSMA wire is assessed through similar computational models. The combination of these computational models and their subsequent experimental validation provide sufficient support for the feasibility of SHM using magnetic field sensing via MSMA embedded components.

Steganographic optical image encryption system based on reversible data hiding and double random phase encoding

NASA Astrophysics Data System (ADS)

Chuang, Cheng-Hung; Chen, Yen-Lin

2013-02-01

This study presents a steganographic optical image encryption system based on reversible data hiding and double random phase encoding (DRPE) techniques. Conventional optical image encryption systems can securely transmit valuable images using an encryption method for possible application in optical transmission systems. The steganographic optical image encryption system based on the DRPE technique has been investigated to hide secret data in encrypted images. However, the DRPE techniques vulnerable to attacks and many of the data hiding methods in the DRPE system can distort the decrypted images. The proposed system, based on reversible data hiding, uses a JBIG2 compression scheme to achieve lossless decrypted image quality and perform a prior encryption process. Thus, the DRPE technique enables a more secured optical encryption process. The proposed method extracts and compresses the bit planes of the original image using the lossless JBIG2 technique. The secret data are embedded in the remaining storage space. The RSA algorithm can cipher the compressed binary bits and secret data for advanced security. Experimental results show that the proposed system achieves a high data embedding capacity and lossless reconstruction of the original images.

Improved Secret Image Sharing Scheme in Embedding Capacity without Underflow and Overflow.

PubMed

Pang, Liaojun; Miao, Deyu; Li, Huixian; Wang, Qiong

2015-01-01

Computational secret image sharing (CSIS) is an effective way to protect a secret image during its transmission and storage, and thus it has attracted lots of attentions since its appearance. Nowadays, it has become a hot topic for researchers to improve the embedding capacity and eliminate the underflow and overflow situations, which is embarrassing and difficult to deal with. The scheme, which has the highest embedding capacity among the existing schemes, has the underflow and overflow problems. Although the underflow and overflow situations have been well dealt with by different methods, the embedding capacities of these methods are reduced more or less. Motivated by these concerns, we propose a novel scheme, in which we take the differential coding, Huffman coding, and data converting to compress the secret image before embedding it to further improve the embedding capacity, and the pixel mapping matrix embedding method with a newly designed matrix is used to embed secret image data into the cover image to avoid the underflow and overflow situations. Experiment results show that our scheme can improve the embedding capacity further and eliminate the underflow and overflow situations at the same time.

Improved Secret Image Sharing Scheme in Embedding Capacity without Underflow and Overflow

PubMed Central

Pang, Liaojun; Miao, Deyu; Li, Huixian; Wang, Qiong

2015-01-01

Computational secret image sharing (CSIS) is an effective way to protect a secret image during its transmission and storage, and thus it has attracted lots of attentions since its appearance. Nowadays, it has become a hot topic for researchers to improve the embedding capacity and eliminate the underflow and overflow situations, which is embarrassing and difficult to deal with. The scheme, which has the highest embedding capacity among the existing schemes, has the underflow and overflow problems. Although the underflow and overflow situations have been well dealt with by different methods, the embedding capacities of these methods are reduced more or less. Motivated by these concerns, we propose a novel scheme, in which we take the differential coding, Huffman coding, and data converting to compress the secret image before embedding it to further improve the embedding capacity, and the pixel mapping matrix embedding method with a newly designed matrix is used to embed secret image data into the cover image to avoid the underflow and overflow situations. Experiment results show that our scheme can improve the embedding capacity further and eliminate the underflow and overflow situations at the same time. PMID:26351657

Diversification of Processors Based on Redundancy in Instruction Set

NASA Astrophysics Data System (ADS)

Ichikawa, Shuichi; Sawada, Takashi; Hata, Hisashi

By diversifying processor architecture, computer software is expected to be more resistant to plagiarism, analysis, and attacks. This study presents a new method to diversify instruction set architecture (ISA) by utilizing the redundancy in the instruction set. Our method is particularly suited for embedded systems implemented with FPGA technology, and realizes a genuine instruction set randomization, which has not been provided by the preceding studies. The evaluation results on four typical ISAs indicate that our scheme can provide a far larger degree of freedom than the preceding studies. Diversified processors based on MIPS architecture were actually implemented and evaluated with Xilinx Spartan-3 FPGA. The increase of logic scale was modest: 5.1% in Specialized design and 3.6% in RAM-mapped design. The performance overhead was also modest: 3.4% in Specialized design and 11.6% in RAM-mapped design. From these results, our scheme is regarded as a practical and promising way to secure FPGA-based embedded systems.

New Developments in the Embedded Statistical Coupling Method: Atomistic/Continuum Crack Propagation

NASA Technical Reports Server (NTRS)

Saether, E.; Yamakov, V.; Glaessgen, E.

2008-01-01

A concurrent multiscale modeling methodology that embeds a molecular dynamics (MD) region within a finite element (FEM) domain has been enhanced. The concurrent MD-FEM coupling methodology uses statistical averaging of the deformation of the atomistic MD domain to provide interface displacement boundary conditions to the surrounding continuum FEM region, which, in turn, generates interface reaction forces that are applied as piecewise constant traction boundary conditions to the MD domain. The enhancement is based on the addition of molecular dynamics-based cohesive zone model (CZM) elements near the MD-FEM interface. The CZM elements are a continuum interpretation of the traction-displacement relationships taken from MD simulations using Cohesive Zone Volume Elements (CZVE). The addition of CZM elements to the concurrent MD-FEM analysis provides a consistent set of atomistically-based cohesive properties within the finite element region near the growing crack. Another set of CZVEs are then used to extract revised CZM relationships from the enhanced embedded statistical coupling method (ESCM) simulation of an edge crack under uniaxial loading.

Local density approximation in site-occupation embedding theory

NASA Astrophysics Data System (ADS)

Senjean, Bruno; Tsuchiizu, Masahisa; Robert, Vincent; Fromager, Emmanuel

2017-01-01

Site-occupation embedding theory (SOET) is a density functional theory (DFT)-based method which aims at modelling strongly correlated electrons. It is in principle exact and applicable to model and quantum chemical Hamiltonians. The theory is presented here for the Hubbard Hamiltonian. In contrast to conventional DFT approaches, the site (or orbital) occupations are deduced in SOET from a partially interacting system consisting of one (or more) impurity site(s) and non-interacting bath sites. The correlation energy of the bath is then treated implicitly by means of a site-occupation functional. In this work, we propose a simple impurity-occupation functional approximation based on the two-level (2L) Hubbard model which is referred to as two-level impurity local density approximation (2L-ILDA). Results obtained on a prototypical uniform eight-site Hubbard ring are promising. The extension of the method to larger systems and more sophisticated model Hamiltonians is currently in progress.

Bio-Inspired Networking — Self-Organizing Networked Embedded Systems

NASA Astrophysics Data System (ADS)

Dressler, Falko

The turn to nature has brought us many unforeseen great concepts and solutions. This course seems to hold on for many research domains. In this article, we study the applicability of biological mechanisms and techniques in the domain of communications. In particular, we study the behavior and the challenges in networked embedded systems that are meant to self-organize in large groups of nodes. Application examples include wireless sensor networks and sensor/actuator networks. Based on a review of the needs and requirements in such networks, we study selected bio-inspired networking approaches that claim to outperform other methods in specific domains. We study mechanisms in swarm intelligence, the artificial immune system, and approaches based on investigations on the cellular signaling pathways. As a major conclusion, we derive that bio-inspired networking techniques do have advantages compared to engineering methods. Nevertheless, selection and employment must be done carefully to achieve the desired performance gains.

Quality optimized medical image information hiding algorithm that employs edge detection and data coding.

PubMed

Al-Dmour, Hayat; Al-Ani, Ahmed

2016-04-01

The present work has the goal of developing a secure medical imaging information system based on a combined steganography and cryptography technique. It attempts to securely embed patient's confidential information into his/her medical images. The proposed information security scheme conceals coded Electronic Patient Records (EPRs) into medical images in order to protect the EPRs' confidentiality without affecting the image quality and particularly the Region of Interest (ROI), which is essential for diagnosis. The secret EPR data is converted into ciphertext using private symmetric encryption method. Since the Human Visual System (HVS) is less sensitive to alterations in sharp regions compared to uniform regions, a simple edge detection method has been introduced to identify and embed in edge pixels, which will lead to an improved stego image quality. In order to increase the embedding capacity, the algorithm embeds variable number of bits (up to 3) in edge pixels based on the strength of edges. Moreover, to increase the efficiency, two message coding mechanisms have been utilized to enhance the ±1 steganography. The first one, which is based on Hamming code, is simple and fast, while the other which is known as the Syndrome Trellis Code (STC), is more sophisticated as it attempts to find a stego image that is close to the cover image through minimizing the embedding impact. The proposed steganography algorithm embeds the secret data bits into the Region of Non Interest (RONI), where due to its importance; the ROI is preserved from modifications. The experimental results demonstrate that the proposed method can embed large amount of secret data without leaving a noticeable distortion in the output image. The effectiveness of the proposed algorithm is also proven using one of the efficient steganalysis techniques. The proposed medical imaging information system proved to be capable of concealing EPR data and producing imperceptible stego images with minimal embedding distortions compared to other existing methods. In order to refrain from introducing any modifications to the ROI, the proposed system only utilizes the Region of Non Interest (RONI) in embedding the EPR data. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

MethylMeter®: bisulfite-free quantitative and sensitive DNA methylation profiling and mutation detection in FFPE samples

PubMed Central

McCarthy, David; Pulverer, Walter; Weinhaeusel, Andreas; Diago, Oscar R; Hogan, Daniel J; Ostertag, Derek; Hanna, Michelle M

2016-01-01

Aim: Development of a sensitive method for DNA methylation profiling and associated mutation detection in clinical samples. Materials & methods: Formalin-fixed and paraffin-embedded tumors received by clinical laboratories often contain insufficient DNA for analysis with bisulfite or methylation sensitive restriction enzymes-based methods. To increase sensitivity, methyl-CpG DNA capture and Coupled Abscription PCR Signaling detection were combined in a new assay, MethylMeter®. Gliomas were analyzed for MGMT methylation, glioma CpG island methylator phenotype and IDH1 R132H. Results: MethylMeter had 100% assay success rate measuring all five biomarkers in formalin-fixed and paraffin-embedded tissue. MGMT methylation results were supported by survival and mRNA expression data. Conclusion: MethylMeter is a sensitive and quantitative method for multitarget DNA methylation profiling and associated mutation detection. The MethylMeter-based GliomaSTRAT assay measures methylation of four targets and one mutation to simultaneously grade gliomas and predict their response to temozolomide. This information is clinically valuable in management of gliomas. PMID:27337298

A Deep Learning-Based Method for Similar Patient Question Retrieval in Chinese.

PubMed

Tang, Guo Yu; Ni, Yuan; Xie, Guo Tong; Fan, Xin Li; Shi, Yan Ling

2017-01-01

The online patient question and answering (Q&A) system, either as a website or a mobile application, attracts an increasing number of users in China. Patients will post their questions and the registered doctors then provide the corresponding answers. A large amount of questions with answers from doctors are accumulated. Instead of awaiting the response from a doctor, the newly posted question could be quickly answered by finding a semantically equivalent question from the Q&A achive. In this study, we investigated a novel deep learning based method to retrieve the similar patient question in Chinese. An unsupervised learning algorithm using deep neural network is performed on the corpus to generate the word embedding. The word embedding was then used as the input to a supervised learning algorithm using a designed deep neural network, i.e. the supervised neural attention model (SNA), to predict the similarity between two questions. The experimental results showed that our SNA method achieved P@1 = 77% and P@5 = 84%, which outperformed all other compared methods.

Network embedding-based representation learning for single cell RNA-seq data.

PubMed

Li, Xiangyu; Chen, Weizheng; Chen, Yang; Zhang, Xuegong; Gu, Jin; Zhang, Michael Q

2017-11-02

Single cell RNA-seq (scRNA-seq) techniques can reveal valuable insights of cell-to-cell heterogeneities. Projection of high-dimensional data into a low-dimensional subspace is a powerful strategy in general for mining such big data. However, scRNA-seq suffers from higher noise and lower coverage than traditional bulk RNA-seq, hence bringing in new computational difficulties. One major challenge is how to deal with the frequent drop-out events. The events, usually caused by the stochastic burst effect in gene transcription and the technical failure of RNA transcript capture, often render traditional dimension reduction methods work inefficiently. To overcome this problem, we have developed a novel Single Cell Representation Learning (SCRL) method based on network embedding. This method can efficiently implement data-driven non-linear projection and incorporate prior biological knowledge (such as pathway information) to learn more meaningful low-dimensional representations for both cells and genes. Benchmark results show that SCRL outperforms other dimensional reduction methods on several recent scRNA-seq datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

FPGA-based multiprocessor system for injection molding control.

PubMed

Muñoz-Barron, Benigno; Morales-Velazquez, Luis; Romero-Troncoso, Rene J; Rodriguez-Donate, Carlos; Trejo-Hernandez, Miguel; Benitez-Rangel, Juan P; Osornio-Rios, Roque A

2012-10-18

The plastic industry is a very important manufacturing sector and injection molding is a widely used forming method in that industry. The contribution of this work is the development of a strategy to retrofit control of an injection molding machine based on an embedded system microprocessors sensor network on a field programmable gate array (FPGA) device. Six types of embedded processors are included in the system: a smart-sensor processor, a micro fuzzy logic controller, a programmable logic controller, a system manager, an IO processor and a communication processor. Temperature, pressure and position are controlled by the proposed system and experimentation results show its feasibility and robustness. As validation of the present work, a particular sample was successfully injected.

Shack-Hartmann wavefront sensor using a Raspberry Pi embedded system

NASA Astrophysics Data System (ADS)

Contreras-Martinez, Ramiro; Garduño-Mejía, Jesús; Rosete-Aguilar, Martha; Román-Moreno, Carlos J.

2017-05-01

In this work we present the design and manufacture of a compact Shack-Hartmann wavefront sensor using a Raspberry Pi and a microlens array. The main goal of this sensor is to recover the wavefront of a laser beam and to characterize its spatial phase using a simple and compact Raspberry Pi and the Raspberry Pi embedded camera. The recovery algorithm is based on a modified version of the Southwell method and was written in Python as well as its user interface. Experimental results and reconstructed wavefronts are presented.

Ab initio simulations of scanning-tunneling-microscope images with embedding techniques and application to C58-dimers on Au(111).

PubMed

Wilhelm, Jan; Walz, Michael; Stendel, Melanie; Bagrets, Alexei; Evers, Ferdinand

2013-05-14

We present a modification of the standard electron transport methodology based on the (non-equilibrium) Green's function formalism to efficiently simulate STM-images. The novel feature of this method is that it employs an effective embedding technique that allows us to extrapolate properties of metal substrates with adsorbed molecules from quantum-chemical cluster calculations. To illustrate the potential of this approach, we present an application to STM-images of C58-dimers immobilized on Au(111)-surfaces that is motivated by recent experiments.

NiCo2S4 nanorod embedded rGO sheets as electrodes for supercapacitor

NASA Astrophysics Data System (ADS)

Sarkar, Aatreyee; Bera, Supriya; Chakraborty, Amit Kumar

2018-04-01

We report the synthesis of a hybrid nanostructure based on NiCo2S4 and reduced graphene oxide (rGO) following a facile hydrothermal method. X-ray diffraction (XRD), and electron microscopy (FESEM and HRTEM) analyses showed rod-like NiCo2S4 nanostructures embedded in rGO sheets. The electrochemical analysis of the synthesized nanohybrid using cyclic voltammetry (CV) and galvanostatic charge discharge (GCD) revealed specific capacitance of 410 F/gm indicating its suitability as a good electrode material for supercapacitor.

Generation of Controlled Analog Emissions from Embedded Devices using Software Stress Methods

DTIC Science & Technology

2017-03-01

Generation of Controlled Analog Emissions from Embedded Devices using Software Stress Methods Oren Sternberg, Jonathan H. Nelson, Israel Perez...Abstract: In this paper, we present a new method that uses software diagnostic tools to study the generation of induced spurious physical emissions from...types of attacks warrants an understanding of unwanted signal generation. We examine this connection by observing the emission profile of an embedded

Lamb Wave Dispersion Ultrasound Vibrometry (LDUV) Method for Quantifying Mechanical Properties of Viscoelastic Solids

PubMed Central

Nenadic, Ivan Z.; Urban, Matthew W.; Mitchell, Scott A.; Greenleaf, James F.

2011-01-01

Diastolic dysfunction is the inability of the left ventricle to supply sufficient stroke volumes under normal physiological conditions and is often accompanied by stiffening of the left-ventricular myocardium. A noninvasive technique capable of quantifying viscoelasticity of the myocardium would be beneficial in clinical settings. Our group has been investigating the use of Shearwave Dispersion Ultrasound Vibrometry (SDUV), a noninvasive ultrasound based method for quantifying viscoelasticity of soft tissues. The primary motive of this study is the design and testing of viscoelastic materials suitable for validation of the Lamb wave Dispersion Ultrasound Vibrometry (LDUV), an SDUV-based technique for measuring viscoelasticity of tissues with plate-like geometry. We report the results of quantifying viscoelasticity of urethane rubber and gelatin samples using LDUV and an embedded sphere method. The LDUV method was used to excite antisymmetric Lamb waves and measure the dispersion in urethane rubber and gelatin plates. An antisymmetric Lamb wave model was fitted to the wave speed dispersion data to estimate elasticity and viscosity of the materials. A finite element model of a viscoelastic plate submerged in water was used to study the appropriateness of the Lamb wave dispersion equations. An embedded sphere method was used as an independent measurement of the viscoelasticity of the urethane rubber and gelatin. The FEM dispersion data were in excellent agreement with the theoretical predictions. Viscoelasticity of the urethane rubber and gelatin obtained using the LDUV and embedded sphere methods agreed within one standard deviation. LDUV studies on excised porcine myocardium sample were performed to investigate the feasibility of the approach in preparation for open-chest in vivo studies. The results suggest that the LDUV technique can be used to quantify mechanical properties of soft tissues with a plate-like geometry. PMID:21403186

Lamb wave dispersion ultrasound vibrometry (LDUV) method for quantifying mechanical properties of viscoelastic solids.

PubMed

Nenadic, Ivan Z; Urban, Matthew W; Mitchell, Scott A; Greenleaf, James F

2011-04-07

Diastolic dysfunction is the inability of the left ventricle to supply sufficient stroke volumes under normal physiological conditions and is often accompanied by stiffening of the left-ventricular myocardium. A noninvasive technique capable of quantifying viscoelasticity of the myocardium would be beneficial in clinical settings. Our group has been investigating the use of shear wave dispersion ultrasound vibrometry (SDUV), a noninvasive ultrasound-based method for quantifying viscoelasticity of soft tissues. The primary motive of this study is the design and testing of viscoelastic materials suitable for validation of the Lamb wave dispersion ultrasound vibrometry (LDUV), an SDUV-based technique for measuring viscoelasticity of tissues with plate-like geometry. We report the results of quantifying viscoelasticity of urethane rubber and gelatin samples using LDUV and an embedded sphere method. The LDUV method was used to excite antisymmetric Lamb waves and measure the dispersion in urethane rubber and gelatin plates. An antisymmetric Lamb wave model was fitted to the wave speed dispersion data to estimate elasticity and viscosity of the materials. A finite element model of a viscoelastic plate submerged in water was used to study the appropriateness of the Lamb wave dispersion equations. An embedded sphere method was used as an independent measurement of the viscoelasticity of the urethane rubber and gelatin. The FEM dispersion data were in excellent agreement with the theoretical predictions. Viscoelasticity of the urethane rubber and gelatin obtained using the LDUV and embedded sphere methods agreed within one standard deviation. LDUV studies on excised porcine myocardium sample were performed to investigate the feasibility of the approach in preparation for open-chest in vivo studies. The results suggest that the LDUV technique can be used to quantify the mechanical properties of soft tissues with a plate-like geometry.

Modular error embedding

DOEpatents

Sandford, II, Maxwell T.; Handel, Theodore G.; Ettinger, J. Mark

1999-01-01

A method of embedding auxiliary information into the digital representation of host data containing noise in the low-order bits. The method applies to digital data representing analog signals, for example digital images. The method reduces the error introduced by other methods that replace the low-order bits with auxiliary information. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user through use of a digital key. The modular error embedding method includes a process to permute the order in which the host data values are processed. The method doubles the amount of auxiliary information that can be added to host data values, in comparison with bit-replacement methods for high bit-rate coding. The invention preserves human perception of the meaning and content of the host data, permitting the addition of auxiliary data in the amount of 50% or greater of the original host data.

A Study on Watt-hour Meter Data Acquisition Method Based on RFID Technology

NASA Astrophysics Data System (ADS)

Chen, Xiangqun; Huang, Rui; Shen, Liman; Chen, Hao; Xiong, Dezhi; Xiao, Xiangqi; Liu, Mouhai; Xu, Renheng

2018-03-01

Considering that traditional watt-hour meter data acquisition was subjected to the influence of distance and occlusion, a watt-hour meter data acquisition method based on RFID technology was proposed in this paper. In detail, RFID electronic tag was embedded in the watt-hour meter to identify the meter and record electric energy information, which made RFID based wireless data acquisition for watt-hour meter come true. Eventually, overall lifecycle management of watt-hour meter is realized.

A Grassmann graph embedding framework for gait analysis

NASA Astrophysics Data System (ADS)

Connie, Tee; Goh, Michael Kah Ong; Teoh, Andrew Beng Jin

2014-12-01

Gait recognition is important in a wide range of monitoring and surveillance applications. Gait information has often been used as evidence when other biometrics is indiscernible in the surveillance footage. Building on recent advances of the subspace-based approaches, we consider the problem of gait recognition on the Grassmann manifold. We show that by embedding the manifold into reproducing kernel Hilbert space and applying the mechanics of graph embedding on such manifold, significant performance improvement can be obtained. In this work, the gait recognition problem is studied in a unified way applicable for both supervised and unsupervised configurations. Sparse representation is further incorporated in the learning mechanism to adaptively harness the local structure of the data. Experiments demonstrate that the proposed method can tolerate variations in appearance for gait identification effectively.

Liquid on Paper: Rapid Prototyping of Soft Functional Components for Paper Electronics.

PubMed

Han, Yu Long; Liu, Hao; Ouyang, Cheng; Lu, Tian Jian; Xu, Feng

2015-07-01

This paper describes a novel approach to fabricate paper-based electric circuits consisting of a paper matrix embedded with three-dimensional (3D) microchannels and liquid metal. Leveraging the high electric conductivity and good flowability of liquid metal, and metallophobic property of paper, it is possible to keep electric and mechanical functionality of the electric circuit even after a thousand cycles of deformation. Embedding liquid metal into paper matrix is a promising method to rapidly fabricate low-cost, disposable, and soft electric circuits for electronics. As a demonstration, we designed a programmable displacement transducer and applied it as variable resistors and pressure sensors. The unique metallophobic property, combined with softness, low cost and light weight, makes paper an attractive alternative to other materials in which liquid metal are currently embedded.

Audio Watermark Embedding Technique Applying Auditory Stream Segregation: "G-encoder Mark" Able to Be Extracted by Mobile Phone

NASA Astrophysics Data System (ADS)

Modegi, Toshio

We are developing audio watermarking techniques which enable extraction of embedded data by cell phones. For that we have to embed data onto frequency ranges, where our auditory response is prominent, therefore data embedding will cause much auditory noises. Previously we have proposed applying a two-channel stereo play-back feature, where noises generated by a data embedded left-channel signal will be reduced by the other right-channel signal. However, this proposal has practical problems of restricting extracting terminal location. In this paper, we propose synthesizing the noise reducing right-channel signal with the left-signal and reduces noises completely by generating an auditory stream segregation phenomenon to users. This newly proposed makes the noise reducing right-channel signal unnecessary and supports monaural play-back operations. Moreover, we propose a wide-band embedding method causing dual auditory stream segregation phenomena, which enables data embedding on whole public phone frequency ranges and stable extractions with 3-G mobile phones. From these proposals, extraction precisions become higher than those by the previously proposed method whereas the quality damages of embedded signals become smaller. In this paper we present an abstract of our newly proposed method and experimental results comparing with those by the previously proposed method.

Switching theory-based steganographic system for JPEG images

NASA Astrophysics Data System (ADS)

Cherukuri, Ravindranath C.; Agaian, Sos S.

2007-04-01

Cellular communications constitute a significant portion of the global telecommunications market. Therefore, the need for secured communication over a mobile platform has increased exponentially. Steganography is an art of hiding critical data into an innocuous signal, which provide answers to the above needs. The JPEG is one of commonly used format for storing and transmitting images on the web. In addition, the pictures captured using mobile cameras are in mostly in JPEG format. In this article, we introduce a switching theory based steganographic system for JPEG images which is applicable for mobile and computer platforms. The proposed algorithm uses the fact that energy distribution among the quantized AC coefficients varies from block to block and coefficient to coefficient. Existing approaches are effective with a part of these coefficients but when employed over all the coefficients they show there ineffectiveness. Therefore, we propose an approach that works each set of AC coefficients with different frame work thus enhancing the performance of the approach. The proposed system offers a high capacity and embedding efficiency simultaneously withstanding to simple statistical attacks. In addition, the embedded information could be retrieved without prior knowledge of the cover image. Based on simulation results, the proposed method demonstrates an improved embedding capacity over existing algorithms while maintaining a high embedding efficiency and preserving the statistics of the JPEG image after hiding information.

Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis

PubMed Central

Liu, Fang; Shen, Changqing; He, Qingbo; Zhang, Ao; Liu, Yongbin; Kong, Fanrang

2014-01-01

A fault diagnosis strategy based on the wayside acoustic monitoring technique is investigated for locomotive bearing fault diagnosis. Inspired by the transient modeling analysis method based on correlation filtering analysis, a so-called Parametric-Mother-Doppler-Wavelet (PMDW) is constructed with six parameters, including a center characteristic frequency and five kinematic model parameters. A Doppler effect eliminator containing a PMDW generator, a correlation filtering analysis module, and a signal resampler is invented to eliminate the Doppler effect embedded in the acoustic signal of the recorded bearing. Through the Doppler effect eliminator, the five kinematic model parameters can be identified based on the signal itself. Then, the signal resampler is applied to eliminate the Doppler effect using the identified parameters. With the ability to detect early bearing faults, the transient model analysis method is employed to detect localized bearing faults after the embedded Doppler effect is eliminated. The effectiveness of the proposed fault diagnosis strategy is verified via simulation studies and applications to diagnose locomotive roller bearing defects. PMID:24803197

Efficient embedding of complex networks to hyperbolic space via their Laplacian

PubMed Central

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-01-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction. PMID:27445157

Efficient embedding of complex networks to hyperbolic space via their Laplacian

NASA Astrophysics Data System (ADS)

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-07-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction.

Monitoring on internal temperature of composite insulator with embedding fiber Bragg grating for early diagnosis

NASA Astrophysics Data System (ADS)

Chen, Wen; Tang, Ming

2017-04-01

The abnormal temperature rise is the precursor of the defective composite insulator in power transmission line. However no consolidated techniques or methodologies can on line monitor its internal temperature now. Thus a new method using embedding fiber Bragg grating (FBG) in fiber reinforced polymer (FRP) rod is adopted to monitor its internal temperature. To correctly demodulate the internal temperature of FRP rod from the Bragg wavelength shift of FBG, the conversion coefficient between them is deduced theoretically based on comprehensive investigation on the thermal stresses of the metal-composite joint, as well as its material and structural properties. Theoretical model shows that the conversion coefficients of FBG embedded in different positions will be different because of non-uniform thermal stress distribution, which is verified by an experiment. This work lays the theoretical foundation of monitoring the internal temperature of composite insulator with embedding FBG, which is of great importance to its health structural monitoring, especially early diagnosis.

Lossless Data Embedding—New Paradigm in Digital Watermarking

NASA Astrophysics Data System (ADS)

Fridrich, Jessica; Goljan, Miroslav; Du, Rui

2002-12-01

One common drawback of virtually all current data embedding methods is the fact that the original image is inevitably distorted due to data embedding itself. This distortion typically cannot be removed completely due to quantization, bit-replacement, or truncation at the grayscales 0 and 255. Although the distortion is often quite small and perceptual models are used to minimize its visibility, the distortion may not be acceptable for medical imagery (for legal reasons) or for military images inspected under nonstandard viewing conditions (after enhancement or extreme zoom). In this paper, we introduce a new paradigm for data embedding in images (lossless data embedding) that has the property that the distortion due to embedding can be completely removed from the watermarked image after the embedded data has been extracted. We present lossless embedding methods for the uncompressed formats (BMP, TIFF) and for the JPEG format. We also show how the concept of lossless data embedding can be used as a powerful tool to achieve a variety of nontrivial tasks, including lossless authentication using fragile watermarks, steganalysis of LSB embedding, and distortion-free robust watermarking.

New technologies for supporting real-time on-board software development

NASA Astrophysics Data System (ADS)

Kerridge, D.

1995-03-01

The next generation of on-board data management systems will be significantly more complex than current designs, and will be required to perform more complex and demanding tasks in software. Improved hardware technology, in the form of the MA31750 radiation hard processor, is one key component in addressing the needs of future embedded systems. However, to complement these hardware advances, improved support for the design and implementation of real-time data management software is now needed. This will help to control the cost and risk assoicated with developing data management software development as it becomes an increasingly significant element within embedded systems. One particular problem with developing embedded software is managing the non-functional requirements in a systematic way. This paper identifies how Logica has exploited recent developments in hard real-time theory to address this problem through the use of new hard real-time analysis and design methods which can be supported by specialized tools. The first stage in transferring this technology from the research domain to industrial application has already been completed. The MA37150 Hard Real-Time Embedded Software Support Environment (HESSE) is a loosely integrated set of hardware and software tools which directly support the process of hard real-time analysis for software targeting the MA31750 processor. With further development, this HESSE promises to provide embedded system developers with software tools which can reduce the risks associated with developing complex hard real-time software. Supported in this way by more sophisticated software methods and tools, it is foreseen that MA31750 based embedded systems can meet the processing needs for the next generation of on-board data management systems.

Novel Variants of a Histogram Shift-Based Reversible Watermarking Technique for Medical Images to Improve Hiding Capacity

PubMed Central

Tuckley, Kushal

2017-01-01

In telemedicine systems, critical medical data is shared on a public communication channel. This increases the risk of unauthorised access to patient's information. This underlines the importance of secrecy and authentication for the medical data. This paper presents two innovative variations of classical histogram shift methods to increase the hiding capacity. The first technique divides the image into nonoverlapping blocks and embeds the watermark individually using the histogram method. The second method separates the region of interest and embeds the watermark only in the region of noninterest. This approach preserves the medical information intact. This method finds its use in critical medical cases. The high PSNR (above 45 dB) obtained for both techniques indicates imperceptibility of the approaches. Experimental results illustrate superiority of the proposed approaches when compared with other methods based on histogram shifting techniques. These techniques improve embedding capacity by 5–15% depending on the image type, without affecting the quality of the watermarked image. Both techniques also enable lossless reconstruction of the watermark and the host medical image. A higher embedding capacity makes the proposed approaches attractive for medical image watermarking applications without compromising the quality of the image. PMID:29104744

Applications and assessment of QM:QM electronic embedding using generalized asymmetric Mulliken atomic charges.

PubMed

Parandekar, Priya V; Hratchian, Hrant P; Raghavachari, Krishnan

2008-10-14

Hybrid QM:QM (quantum mechanics:quantum mechanics) and QM:MM (quantum mechanics:molecular mechanics) methods are widely used to calculate the electronic structure of large systems where a full quantum mechanical treatment at a desired high level of theory is computationally prohibitive. The ONIOM (our own N-layer integrated molecular orbital molecular mechanics) approximation is one of the more popular hybrid methods, where the total molecular system is divided into multiple layers, each treated at a different level of theory. In a previous publication, we developed a novel QM:QM electronic embedding scheme within the ONIOM framework, where the model system is embedded in the external Mulliken point charges of the surrounding low-level region to account for the polarization of the model system wave function. Therein, we derived and implemented a rigorous expression for the embedding energy as well as analytic gradients that depend on the derivatives of the external Mulliken point charges. In this work, we demonstrate the applicability of our QM:QM method with point charge embedding and assess its accuracy. We study two challenging systems--zinc metalloenzymes and silicon oxide cages--and demonstrate that electronic embedding shows significant improvement over mechanical embedding. We also develop a modified technique for the energy and analytic gradients using a generalized asymmetric Mulliken embedding method involving an unequal splitting of the Mulliken overlap populations to offer improvement in situations where the Mulliken charges may be deficient.

Monitoring Poisson's Ratio Degradation of FRP Composites under Fatigue Loading Using Biaxially Embedded FBG Sensors.

PubMed

Akay, Erdem; Yilmaz, Cagatay; Kocaman, Esat S; Turkmen, Halit S; Yildiz, Mehmet

2016-09-19

The significance of strain measurement is obvious for the analysis of Fiber-Reinforced Polymer (FRP) composites. Conventional strain measurement methods are sufficient for static testing in general. Nevertheless, if the requirements exceed the capabilities of these conventional methods, more sophisticated techniques are necessary to obtain strain data. Fiber Bragg Grating (FBG) sensors have many advantages for strain measurement over conventional ones. Thus, the present paper suggests a novel method for biaxial strain measurement using embedded FBG sensors during the fatigue testing of FRP composites. Poisson's ratio and its reduction were monitored for each cyclic loading by using embedded FBG sensors for a given specimen and correlated with the fatigue stages determined based on the variations of the applied fatigue loading and temperature due to the autogenous heating to predict an oncoming failure of the continuous fiber-reinforced epoxy matrix composite specimens under fatigue loading. The results show that FBG sensor technology has a remarkable potential for monitoring the evolution of Poisson's ratio on a cycle-by-cycle basis, which can reliably be used towards tracking the fatigue stages of composite for structural health monitoring purposes.

Efficient Text Encryption and Hiding with Double-Random Phase-Encoding

PubMed Central

Sang, Jun; Ling, Shenggui; Alam, Mohammad S.

2012-01-01

In this paper, a double-random phase-encoding technique-based text encryption and hiding method is proposed. First, the secret text is transformed into a 2-dimensional array and the higher bits of the elements in the transformed array are used to store the bit stream of the secret text, while the lower bits are filled with specific values. Then, the transformed array is encoded with double-random phase-encoding technique. Finally, the encoded array is superimposed on an expanded host image to obtain the image embedded with hidden data. The performance of the proposed technique, including the hiding capacity, the recovery accuracy of the secret text, and the quality of the image embedded with hidden data, is tested via analytical modeling and test data stream. Experimental results show that the secret text can be recovered either accurately or almost accurately, while maintaining the quality of the host image embedded with hidden data by properly selecting the method of transforming the secret text into an array and the superimposition coefficient. By using optical information processing techniques, the proposed method has been found to significantly improve the security of text information transmission, while ensuring hiding capacity at a prescribed level. PMID:23202003

Monitoring Poisson’s Ratio Degradation of FRP Composites under Fatigue Loading Using Biaxially Embedded FBG Sensors

PubMed Central

Akay, Erdem; Yilmaz, Cagatay; Kocaman, Esat S.; Turkmen, Halit S.; Yildiz, Mehmet

2016-01-01

The significance of strain measurement is obvious for the analysis of Fiber-Reinforced Polymer (FRP) composites. Conventional strain measurement methods are sufficient for static testing in general. Nevertheless, if the requirements exceed the capabilities of these conventional methods, more sophisticated techniques are necessary to obtain strain data. Fiber Bragg Grating (FBG) sensors have many advantages for strain measurement over conventional ones. Thus, the present paper suggests a novel method for biaxial strain measurement using embedded FBG sensors during the fatigue testing of FRP composites. Poisson’s ratio and its reduction were monitored for each cyclic loading by using embedded FBG sensors for a given specimen and correlated with the fatigue stages determined based on the variations of the applied fatigue loading and temperature due to the autogenous heating to predict an oncoming failure of the continuous fiber-reinforced epoxy matrix composite specimens under fatigue loading. The results show that FBG sensor technology has a remarkable potential for monitoring the evolution of Poisson’s ratio on a cycle-by-cycle basis, which can reliably be used towards tracking the fatigue stages of composite for structural health monitoring purposes. PMID:28773901

Adaptively synchronous scalable spread spectrum (A4S) data-hiding strategy for three-dimensional visualization

NASA Astrophysics Data System (ADS)

Hayat, Khizar; Puech, William; Gesquière, Gilles

2010-04-01

We propose an adaptively synchronous scalable spread spectrum (A4S) data-hiding strategy to integrate disparate data, needed for a typical 3-D visualization, into a single JPEG2000 format file. JPEG2000 encoding provides a standard format on one hand and the needed multiresolution for scalability on the other. The method has the potential of being imperceptible and robust at the same time. While the spread spectrum (SS) methods are known for the high robustness they offer, our data-hiding strategy is removable at the same time, which ensures highest possible visualization quality. The SS embedding of the discrete wavelet transform (DWT)-domain depth map is carried out in transform domain YCrCb components from the JPEG2000 coding stream just after the DWT stage. To maintain synchronization, the embedding is carried out while taking into account the correspondence of subbands. Since security is not the immediate concern, we are at liberty with the strength of embedding. This permits us to increase the robustness and bring the reversibility of our method. To estimate the maximum tolerable error in the depth map according to a given viewpoint, a human visual system (HVS)-based psychovisual analysis is also presented.

Vibration analysis of angle-ply laminated composite plates with an embedded piezoceramic layer.

PubMed

Lin, Hsien-Yang; Huang, Jin-Hung; Ma, Chien-Ching

2003-09-01

An optical full-field technique, called amplitude-fluctuation electronic speckle pattern interferometry (AF-ESPI), is used in this study to investigate the force-induced transverse vibration of an angle-ply laminated composite embedded with a piezoceramic layer (piezolaminated plates). The piezolaminated plates are excited by applying time-harmonic voltages to the embedded piezoceramic layer. Because clear fringe patterns will appear only at resonant frequencies, both the resonant frequencies and mode shapes of the vibrating piezolaminated plates with five different fiber orientation angles are obtained by the proposed AF-ESPI method. A laser Doppler vibrometer (LDV) system that has the advantage of high resolution and broad dynamic range also is applied to measure the frequency response of piezolaminated plates. In addition to the two proposed optical techniques, numerical computations based on a commercial finite element package are presented for comparison with the experimental results. Three different numerical formulations are used to evaluate the vibration characteristics of piezolaminated plates. Good agreements of the measured data by the optical method and the numerical results predicted by the finite element method (FEM) demonstrate that the proposed methodology in this study is a powerful tool for the vibration analysis of piezolaminated plates.

Stabilization of gold nanoparticle films on glass by thermal embedding.

PubMed

Karakouz, Tanya; Maoz, Ben M; Lando, Gilad; Vaskevich, Alexander; Rubinstein, Israel

2011-04-01

The poor adhesion of gold nanoparticles (NPs) to glass has been a known obstacle to studies and applications of NP-based systems, such as glass/Au-NP optical devices. Here we present a simple scheme for obtaining stable localized surface plasmon resonance (LSPR) transducers based on Au NP films immobilized on silanized glass and annealed. The procedure includes high-temperature annealing of the Au NP film, leading to partial embedding in the glass substrate and stabilization of the morphology and optical properties. The method is demonstrated using citrate-stabilized Au NPs, 20 and 63 nm mean diameter, immobilized electrostatically on glass microscope cover slides precoated with an aminosilane monolayer. Partial thermal embedding of the Au NPs in the glass occurs at temperatures in the vicinity of the glass transition temperature of the substrate. Upon annealing in air the Au NPs gradually settle into the glass and become encircled by a glass rim. In situ transmission UV-vis spectroscopy carried out during the annealing in a specially designed optical oven shows three regions: The most pronounced change of the surface plasmon (SP) band shape occurs in the first ca. 15 min of annealing; this is followed by a blue-shift of the SP band maximum (up to ca. 5 h), after which a steady red-shift of the SP band is observed (up to ca. 70 h, when the experiment was terminated). The development of the SP extinction spectrum was correlated to changes in the system structure, including thermal modification of the NP film morphology and embedding in the glass. The partially embedded Au NP films pass successfully the adhesive-tape test, while their morphology and optical response are stable toward immersion in solvents, drying, and thiol self-assembly. The enhanced adhesion is attributed to the metal NP embedding and rim formation. The stabilized NP films display a refractive index sensitivity (RIS) of 34-48 nm/RIU and 0.1-0.4 abs.u./RIU in SP band shift and extinction change, respectively. The RIS can be improved significantly by electroless deposition of Au on the embedded NPs, while the system stability is maintained. The method presented provides a simple route to obtaining stable Au NP film transducers. © 2011 American Chemical Society

Development and application of course-embedded assessment system for program outcome evaluation in the Korean nursing education: A pilot study.

PubMed

Park, Jee Won; Seo, Eun Ji; You, Mi-Ae; Song, Ju-Eun

2016-03-01

Program outcome evaluation is important because it is an indicator for good quality of education. Course-embedded assessment is one of the program outcome evaluation methods. However, it is rarely used in Korean nursing education. The study purpose was to develop and apply preliminarily a course-embedded assessment system to evaluate one program outcome and to share our experiences. This was a methodological study to develop and apply the course-embedded assessment system based on the theoretical framework in one nursing program in South Korea. Scores for 77 students generated from the three practicum courses were used. The course-embedded assessment system was developed following the six steps suggested by Han's model as follows. 1) One program outcome in the undergraduate program, "nursing process application ability", was selected and 2) the three clinical practicum courses related to the selected program outcome were identified. 3) Evaluation tools including rubric and items were selected for outcome measurement and 4) performance criterion, the educational goal level for the program, was established. 5) Program outcome was actually evaluated using the rubric and evaluation items in the three practicum courses and 6) the obtained scores were analyzed to identify the achievement rate, which was compared with the performance criterion. Achievement rates for the selected program outcome in adult, maternity, and pediatric nursing practicum were 98.7%, 100%, and 66.2% in the case report and 100% for all three in the clinical practice, and 100%, 100%, and 87% respectively for the conference. These are considered as satisfactory levels when compared with the performance criterion of "at least 60% or more". Course-embedded assessment can be used as an effective and economic method to evaluate the program outcome without running an integrative course additionally. Further studies to develop course-embedded assessment systems for other program outcomes in nursing education are needed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Categorizing biomedicine images using novel image features and sparse coding representation

PubMed Central

2013-01-01

Background Images embedded in biomedical publications carry rich information that often concisely summarize key hypotheses adopted, methods employed, or results obtained in a published study. Therefore, they offer valuable clues for understanding main content in a biomedical publication. Prior studies have pointed out the potential of mining images embedded in biomedical publications for automatically understanding and retrieving such images' associated source documents. Within the broad area of biomedical image processing, categorizing biomedical images is a fundamental step for building many advanced image analysis, retrieval, and mining applications. Similar to any automatic categorization effort, discriminative image features can provide the most crucial aid in the process. Method We observe that many images embedded in biomedical publications carry versatile annotation text. Based on the locations of and the spatial relationships between these text elements in an image, we thus propose some novel image features for image categorization purpose, which quantitatively characterize the spatial positions and distributions of text elements inside a biomedical image. We further adopt a sparse coding representation (SCR) based technique to categorize images embedded in biomedical publications by leveraging our newly proposed image features. Results we randomly selected 990 images of the JPG format for use in our experiments where 310 images were used as training samples and the rest were used as the testing cases. We first segmented 310 sample images following the our proposed procedure. This step produced a total of 1035 sub-images. We then manually labeled all these sub-images according to the two-level hierarchical image taxonomy proposed by [1]. Among our annotation results, 316 are microscopy images, 126 are gel electrophoresis images, 135 are line charts, 156 are bar charts, 52 are spot charts, 25 are tables, 70 are flow charts, and the remaining 155 images are of the type "others". A serial of experimental results are obtained. Firstly, each image categorizing results is presented, and next image categorizing performance indexes such as precision, recall, F-score, are all listed. Different features which include conventional image features and our proposed novel features indicate different categorizing performance, and the results are demonstrated. Thirdly, we conduct an accuracy comparison between support vector machine classification method and our proposed sparse representation classification method. At last, our proposed approach is compared with three peer classification method and experimental results verify our impressively improved performance. Conclusions Compared with conventional image features that do not exploit characteristics regarding text positions and distributions inside images embedded in biomedical publications, our proposed image features coupled with the SR based representation model exhibit superior performance for classifying biomedical images as demonstrated in our comparative benchmark study. PMID:24565470

Communication: Density functional theory embedding with the orthogonality constrained basis set expansion procedure

NASA Astrophysics Data System (ADS)

Culpitt, Tanner; Brorsen, Kurt R.; Hammes-Schiffer, Sharon

2017-06-01

Density functional theory (DFT) embedding approaches have generated considerable interest in the field of computational chemistry because they enable calculations on larger systems by treating subsystems at different levels of theory. To circumvent the calculation of the non-additive kinetic potential, various projector methods have been developed to ensure the orthogonality of molecular orbitals between subsystems. Herein the orthogonality constrained basis set expansion (OCBSE) procedure is implemented to enforce this subsystem orbital orthogonality without requiring a level shifting parameter. This scheme is a simple alternative to existing parameter-free projector-based schemes, such as the Huzinaga equation. The main advantage of the OCBSE procedure is that excellent convergence behavior is attained for DFT-in-DFT embedding without freezing any of the subsystem densities. For the three chemical systems studied, the level of accuracy is comparable to or higher than that obtained with the Huzinaga scheme with frozen subsystem densities. Allowing both the high-level and low-level DFT densities to respond to each other during DFT-in-DFT embedding calculations provides more flexibility and renders this approach more generally applicable to chemical systems. It could also be useful for future extensions to embedding approaches combining wavefunction theories and DFT.

Riemannian Metric Optimization on Surfaces (RMOS) for Intrinsic Brain Mapping in the Laplace-Beltrami Embedding Space

PubMed Central

Gahm, Jin Kyu; Shi, Yonggang

2018-01-01

Surface mapping methods play an important role in various brain imaging studies from tracking the maturation of adolescent brains to mapping gray matter atrophy patterns in Alzheimer’s disease. Popular surface mapping approaches based on spherical registration, however, have inherent numerical limitations when severe metric distortions are present during the spherical parameterization step. In this paper, we propose a novel computational framework for intrinsic surface mapping in the Laplace-Beltrami (LB) embedding space based on Riemannian metric optimization on surfaces (RMOS). Given a diffeomorphism between two surfaces, an isometry can be defined using the pullback metric, which in turn results in identical LB embeddings from the two surfaces. The proposed RMOS approach builds upon this mathematical foundation and achieves general feature-driven surface mapping in the LB embedding space by iteratively optimizing the Riemannian metric defined on the edges of triangular meshes. At the core of our framework is an optimization engine that converts an energy function for surface mapping into a distance measure in the LB embedding space, which can be effectively optimized using gradients of the LB eigen-system with respect to the Riemannian metrics. In the experimental results, we compare the RMOS algorithm with spherical registration using large-scale brain imaging data, and show that RMOS achieves superior performance in the prediction of hippocampal subfields and cortical gyral labels, and the holistic mapping of striatal surfaces for the construction of a striatal connectivity atlas from substantia nigra. PMID:29574399

A novel sample preparation method to avoid influence of embedding medium during nano-indentation

NASA Astrophysics Data System (ADS)

Meng, Yujie; Wang, Siqun; Cai, Zhiyong; Young, Timothy M.; Du, Guanben; Li, Yanjun

2013-02-01

The effect of the embedding medium on the nano-indentation measurements of lignocellulosic materials was investigated experimentally using nano-indentation. Both the reduced elastic modulus and the hardness of non-embedded cell walls were found to be lower than those of the embedded samples, proving that the embedding medium used for specimen preparation on cellulosic material during nano-indentation can modify cell-wall properties. This leads to structural and chemical changes in the cell-wall constituents, changes that may significantly alter the material properties. Further investigation was carried out to detect the influence of different vacuum times on the cell-wall mechanical properties during the embedding procedure. Interpretation of the statistical analysis revealed no linear relationships between vacuum time and the mechanical properties of cell walls. The quantitative measurements confirm that low-viscosity resin has a rapid penetration rate early in the curing process. Finally, a novel sample preparation method aimed at preventing resin diffusion into lignocellulosic cell walls was developed using a plastic film to wrap the sample before embedding. This method proved to be accessible and straightforward for many kinds of lignocellulosic material, but is especially suitable for small, soft samples.

A testbed for optimizing electrodes embedded in the skull or in artificial skull replacement pieces used after injury

PubMed Central

Jiang, JingLe; Marathe, Amar R.; Keene, Jennifer C.; Taylor, Dawn M.

2016-01-01

Background Custom-fitted skull replacement pieces are often used after a head injury or surgery to replace damaged bone. Chronic brain recordings are beneficial after injury/surgery for monitoring brain health and seizure development. Embedding electrodes directly in these artificial skull replacement pieces would be a novel, low-risk way to perform chronic brain monitoring in these patients. Similarly, embedding electrodes directly in healthy skull would be a viable minimally-invasive option for many other neuroscience and neurotechnology applications requiring chronic brain recordings. New Method We demonstrate a preclinical testbed that can be used for refining electrode designs embedded in artificial skull replacement pieces or for embedding directly into the skull itself. Options are explored to increase the surface area of the contacts without increasing recording contact diameter to maximize recording resolution. Results Embedding electrodes in real or artificial skull allows one to lower electrode impedance without increasing the recording contact diameter by making use of conductive channels that extend into the skull. The higher density of small contacts embedded in the artificial skull in this testbed enables one to optimize electrode spacing for use in real bone. Comparison with Existing Methods For brain monitoring applications, skull-embedded electrodes fill a gap between electroencephalograms recorded on the scalp surface and the more invasive epidural or subdural electrode sheets. Conclusions Embedding electrodes into the skull or in skull replacement pieces may provide a safe, convenient, minimally-invasive alternative for chronic brain monitoring. The manufacturing methods described here will facilitate further testing of skull-embedded electrodes in animal models. PMID:27979758

A sparse grid based method for generative dimensionality reduction of high-dimensional data

NASA Astrophysics Data System (ADS)

Bohn, Bastian; Garcke, Jochen; Griebel, Michael

2016-03-01

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.

A new smart traffic monitoring method using embedded cement-based piezoelectric sensors

NASA Astrophysics Data System (ADS)

Zhang, Jinrui; Lu, Youyuan; Lu, Zeyu; Liu, Chao; Sun, Guoxing; Li, Zongjin

2015-02-01

Cement-based piezoelectric composites are employed as the sensing elements of a new smart traffic monitoring system. The piezoelectricity of the cement-based piezoelectric sensors enables powerful and accurate real-time detection of the pressure induced by the traffic flow. To describe the mechanical-electrical conversion mechanism between traffic flow and the electrical output of the embedded piezoelectric sensors, a mathematical model is established based on Duhamel’s integral, the constitutive law and the charge-leakage characteristics of the piezoelectric composite. Laboratory tests show that the voltage magnitude of the sensor is linearly proportional to the applied pressure, which ensures the reliability of the cement-based piezoelectric sensors for traffic monitoring. A series of on-site road tests by a 10 tonne truck and a 6.8 tonne van show that vehicle weight-in-motion can be predicted based on the mechanical-electrical model by taking into account the vehicle speed and the charge-leakage property of the piezoelectric sensor. In the speed range from 20 km h-1 to 70 km h-1, the error of the repeated weigh-in-motion measurements of the 6.8 tonne van is less than 1 tonne. The results indicate that the embedded cement-based piezoelectric sensors and associated measurement setup have good capability of smart traffic monitoring, such as traffic flow detection, vehicle speed detection and weigh-in-motion measurement.

ADAPTIVE METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS VIA NATURAL EMBEDDINGS AND REJECTION SAMPLING WITH MEMORY.

PubMed

Rackauckas, Christopher; Nie, Qing

2017-01-01

Adaptive time-stepping with high-order embedded Runge-Kutta pairs and rejection sampling provides efficient approaches for solving differential equations. While many such methods exist for solving deterministic systems, little progress has been made for stochastic variants. One challenge in developing adaptive methods for stochastic differential equations (SDEs) is the construction of embedded schemes with direct error estimates. We present a new class of embedded stochastic Runge-Kutta (SRK) methods with strong order 1.5 which have a natural embedding of strong order 1.0 methods. This allows for the derivation of an error estimate which requires no additional function evaluations. Next we derive a general method to reject the time steps without losing information about the future Brownian path termed Rejection Sampling with Memory (RSwM). This method utilizes a stack data structure to do rejection sampling, costing only a few floating point calculations. We show numerically that the methods generate statistically-correct and tolerance-controlled solutions. Lastly, we show that this form of adaptivity can be applied to systems of equations, and demonstrate that it solves a stiff biological model 12.28x faster than common fixed timestep algorithms. Our approach only requires the solution to a bridging problem and thus lends itself to natural generalizations beyond SDEs.

ADAPTIVE METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS VIA NATURAL EMBEDDINGS AND REJECTION SAMPLING WITH MEMORY

PubMed Central

Rackauckas, Christopher

2017-01-01

Adaptive time-stepping with high-order embedded Runge-Kutta pairs and rejection sampling provides efficient approaches for solving differential equations. While many such methods exist for solving deterministic systems, little progress has been made for stochastic variants. One challenge in developing adaptive methods for stochastic differential equations (SDEs) is the construction of embedded schemes with direct error estimates. We present a new class of embedded stochastic Runge-Kutta (SRK) methods with strong order 1.5 which have a natural embedding of strong order 1.0 methods. This allows for the derivation of an error estimate which requires no additional function evaluations. Next we derive a general method to reject the time steps without losing information about the future Brownian path termed Rejection Sampling with Memory (RSwM). This method utilizes a stack data structure to do rejection sampling, costing only a few floating point calculations. We show numerically that the methods generate statistically-correct and tolerance-controlled solutions. Lastly, we show that this form of adaptivity can be applied to systems of equations, and demonstrate that it solves a stiff biological model 12.28x faster than common fixed timestep algorithms. Our approach only requires the solution to a bridging problem and thus lends itself to natural generalizations beyond SDEs. PMID:29527134

Steganographic embedding in containers-images

NASA Astrophysics Data System (ADS)

Nikishova, A. V.; Omelchenko, T. A.; Makedonskij, S. A.

2018-05-01

Steganography is one of the approaches to ensuring the protection of information transmitted over the network. But a steganographic method should vary depending on a used container. According to statistics, the most widely used containers are images and the most common image format is JPEG. Authors propose a method of data embedding into a frequency area of images in format JPEG 2000. It is proposed to use the method of Benham-Memon- Yeo-Yeung, in which instead of discrete cosine transform, discrete wavelet transform is used. Two requirements for images are formulated. Structure similarity is chosen to obtain quality assessment of data embedding. Experiments confirm that requirements satisfaction allows achieving high quality assessment of data embedding.

A Vision-Based Driver Nighttime Assistance and Surveillance System Based on Intelligent Image Sensing Techniques and a Heterogamous Dual-Core Embedded System Architecture

PubMed Central

Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

2012-01-01

This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system. PMID:22736956

A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture.

PubMed

Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

2012-01-01

This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

Method of assessing the state of a rolling bearing based on the relative compensation distance of multiple-domain features and locally linear embedding

NASA Astrophysics Data System (ADS)

Kang, Shouqiang; Ma, Danyang; Wang, Yujing; Lan, Chaofeng; Chen, Qingguo; Mikulovich, V. I.

2017-03-01

To effectively assess different fault locations and different degrees of performance degradation of a rolling bearing with a unified assessment index, a novel state assessment method based on the relative compensation distance of multiple-domain features and locally linear embedding is proposed. First, for a single-sample signal, time-domain and frequency-domain indexes can be calculated for the original vibration signal and each sensitive intrinsic mode function obtained by improved ensemble empirical mode decomposition, and the singular values of the sensitive intrinsic mode function matrix can be extracted by singular value decomposition to construct a high-dimensional hybrid-domain feature vector. Second, a feature matrix can be constructed by arranging each feature vector of multiple samples, the dimensions of each row vector of the feature matrix can be reduced by the locally linear embedding algorithm, and the compensation distance of each fault state of the rolling bearing can be calculated using the support vector machine. Finally, the relative distance between different fault locations and different degrees of performance degradation and the normal-state optimal classification surface can be compensated, and on the basis of the proposed relative compensation distance, the assessment model can be constructed and an assessment curve drawn. Experimental results show that the proposed method can effectively assess different fault locations and different degrees of performance degradation of the rolling bearing under certain conditions.

FPGA-Based Multiprocessor System for Injection Molding Control

PubMed Central

Muñoz-Barron, Benigno; Morales-Velazquez, Luis; Romero-Troncoso, Rene J.; Rodriguez-Donate, Carlos; Trejo-Hernandez, Miguel; Benitez-Rangel, Juan P.; Osornio-Rios, Roque A.

2012-01-01

The plastic industry is a very important manufacturing sector and injection molding is a widely used forming method in that industry. The contribution of this work is the development of a strategy to retrofit control of an injection molding machine based on an embedded system microprocessors sensor network on a field programmable gate array (FPGA) device. Six types of embedded processors are included in the system: a smart-sensor processor, a micro fuzzy logic controller, a programmable logic controller, a system manager, an IO processor and a communication processor. Temperature, pressure and position are controlled by the proposed system and experimentation results show its feasibility and robustness. As validation of the present work, a particular sample was successfully injected. PMID:23202036

A family of four stages embedded explicit six-step methods with eliminated phase-lag and its derivatives for the numerical solution of the second order problems

NASA Astrophysics Data System (ADS)

Simos, T. E.

2017-11-01

A family of four stages high algebraic order embedded explicit six-step methods, for the numerical solution of second order initial or boundary-value problems with periodical and/or oscillating solutions, are studied in this paper. The free parameters of the new proposed methods are calculated solving the linear system of equations which is produced by requesting the vanishing of the phase-lag of the methods and the vanishing of the phase-lag's derivatives of the schemes. For the new obtained methods we investigate: • Its local truncation error (LTE) of the methods.• The asymptotic form of the LTE obtained using as model problem the radial Schrödinger equation.• The comparison of the asymptotic forms of LTEs for several methods of the same family. This comparison leads to conclusions on the efficiency of each method of the family.• The stability and the interval of periodicity of the obtained methods of the new family of embedded finite difference pairs.• The applications of the new obtained family of embedded finite difference pairs to the numerical solution of several second order problems like the radial Schrödinger equation, astronomical problems etc. The above applications lead to conclusion on the efficiency of the methods of the new family of embedded finite difference pairs.

Flexible Regenerative Nanoelectronics for Advanced Peripheral Neural Interfaces

DTIC Science & Technology

2017-10-01

these materials will be developed based on 3D printing . Page 4 Task 3. Construct nerve guidance scaffolds comprising of embedded mesh electrodes with...Develop photo mask patterning methods. 1-9 In progress 50% Subtask 2.2.2. Develop 3D printing patterning methods. 9-18 9/1/2017 Milestone(s...research into patterning techniques, we found that 10% gelatin methacrylate (GelMA) base gel was the best for performing 3D printing of the gels

Treatment-Specific Changes in Decentering Following Mindfulness-Based Cognitive Therapy versus Antidepressant Medication or Placebo for Prevention of Depressive Relapse

ERIC Educational Resources Information Center

Bieling, Peter J.; Hawley, Lance L.; Bloch, Richard T.; Corcoran, Kathleen M.; Levitan, Robert D.; Young, L. Trevor; MacQueen, Glenda M.; Segal, Zindel V.

2012-01-01

Objective: To examine whether metacognitive psychological skills, acquired in mindfulness-based cognitive therapy (MBCT), are also present in patients receiving medication treatments for prevention of depressive relapse and whether these skills mediate MBCT's effectiveness. Method: This study, embedded within a randomized efficacy trial of MBCT,…

A pseudospectra-based approach to non-normal stability of embedded boundary methods

NASA Astrophysics Data System (ADS)

Rapaka, Narsimha; Samtaney, Ravi

2017-11-01

We present non-normal linear stability of embedded boundary (EB) methods employing pseudospectra and resolvent norms. Stability of the discrete linear wave equation is characterized in terms of the normalized distance of the EB to the nearest ghost node (α) in one and two dimensions. An important objective is that the CFL condition based on the Cartesian grid spacing remains unaffected by the EB. We consider various discretization methods including both central and upwind-biased schemes. Stability is guaranteed when α <=αmax ranges between 0.5 and 0.77 depending on the discretization scheme. Also, the stability characteristics remain the same in both one and two dimensions. Sharper limits on the sufficient conditions for stability are obtained based on the pseudospectral radius (the Kreiss constant) than the restrictive limits based on the usual singular value decomposition analysis. We present a simple and robust reclassification scheme for the ghost cells (``hybrid ghost cells'') to ensure Lax stability of the discrete systems. This has been tested successfully for both low and high order discretization schemes with transient growth of at most O (1). Moreover, we present a stable, fourth order EB reconstruction scheme. Supported by the KAUST Office of Competitive Research Funds under Award No. URF/1/1394-01.

Liquid on Paper: Rapid Prototyping of Soft Functional Components for Paper Electronics

PubMed Central

Long Han, Yu; Liu, Hao; Ouyang, Cheng; Jian Lu, Tian; Xu, Feng

2015-01-01

This paper describes a novel approach to fabricate paper-based electric circuits consisting of a paper matrix embedded with three-dimensional (3D) microchannels and liquid metal. Leveraging the high electric conductivity and good flowability of liquid metal, and metallophobic property of paper, it is possible to keep electric and mechanical functionality of the electric circuit even after a thousand cycles of deformation. Embedding liquid metal into paper matrix is a promising method to rapidly fabricate low-cost, disposable, and soft electric circuits for electronics. As a demonstration, we designed a programmable displacement transducer and applied it as variable resistors and pressure sensors. The unique metallophobic property, combined with softness, low cost and light weight, makes paper an attractive alternative to other materials in which liquid metal are currently embedded. PMID:26129723

Embedding and Chemical Reactivation of Green Fluorescent Protein in the Whole Mouse Brain for Optical Micro-Imaging

PubMed Central

Gang, Yadong; Zhou, Hongfu; Jia, Yao; Liu, Ling; Liu, Xiuli; Rao, Gong; Li, Longhui; Wang, Xiaojun; Lv, Xiaohua; Xiong, Hanqing; Yang, Zhongqin; Luo, Qingming; Gong, Hui; Zeng, Shaoqun

2017-01-01

Resin embedding has been widely applied to fixing biological tissues for sectioning and imaging, but has long been regarded as incompatible with green fluorescent protein (GFP) labeled sample because it reduces fluorescence. Recently, it has been reported that resin-embedded GFP-labeled brain tissue can be imaged with high resolution. In this protocol, we describe an optimized protocol for resin embedding and chemical reactivation of fluorescent protein labeled mouse brain, we have used mice as experiment model, but the protocol should be applied to other species. This method involves whole brain embedding and chemical reactivation of the fluorescent signal in resin-embedded tissue. The whole brain embedding process takes a total of 7 days. The duration of chemical reactivation is ~2 min for penetrating 4 μm below the surface in the resin-embedded brain. This protocol provides an efficient way to prepare fluorescent protein labeled sample for high-resolution optical imaging. This kind of sample was demonstrated to be imaged by various optical micro-imaging methods. Fine structures labeled with GFP across a whole brain can be detected. PMID:28352214

Design and implementation of embedded un-interruptible power supply system (EUPSS) for web-based mobile application

NASA Astrophysics Data System (ADS)

Zhang, De-gan; Zhang, Xiao-dan

2012-11-01

With the growth of the amount of information manipulated by embedded application systems, which are embedded into devices and offer access to the devices on the internet, the requirements of saving the information systemically is necessary so as to fulfil access from the client and the local processing more efficiently. For supporting mobile applications, a design and implementation solution of embedded un-interruptible power supply (UPS) system (in brief, EUPSS) is brought forward for long-distance monitoring and controlling of UPS based on Web. The implementation of system is based on ATmega161, RTL8019AS and Arm chips with TCP/IP protocol suite for communication. In the embedded UPS system, an embedded file system is designed and implemented which saves the data and index information on a serial EEPROM chip in a structured way and communicates with a microcontroller unit through I2C bus. By embedding the file system into UPS system or other information appliances, users can access and manipulate local data on the web client side. Embedded file system on chips will play a major role in the growth of IP networking. Based on our experiment tests, the mobile users can easily monitor and control UPS in different places of long-distance. The performance of EUPSS has satisfied the requirements of all kinds of Web-based mobile applications.

MEAM interatomic force calculation subroutine for LAMMPS

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

Stukowski, A.

2010-10-25

Interatomic force and energy calculation subroutine tobe used with the molecular dynamics simulation code LAMMPS (Ref a.). The code evaluates the total energy and atomic forces (energy gradient) according to cubic spine-based variant (Ref b.) of the Modified Embedded Atom Method (MEAM).

Secure steganography designed for mobile platforms

NASA Astrophysics Data System (ADS)

Agaian, Sos S.; Cherukuri, Ravindranath; Sifuentes, Ronnie R.

2006-05-01

Adaptive steganography, an intelligent approach to message hiding, integrated with matrix encoding and pn-sequences serves as a promising resolution to recent security assurance concerns. Incorporating the above data hiding concepts with established cryptographic protocols in wireless communication would greatly increase the security and privacy of transmitting sensitive information. We present an algorithm which will address the following problems: 1) low embedding capacity in mobile devices due to fixed image dimensions and memory constraints, 2) compatibility between mobile and land based desktop computers, and 3) detection of stego images by widely available steganalysis software [1-3]. Consistent with the smaller available memory, processor capabilities, and limited resolution associated with mobile devices, we propose a more magnified approach to steganography by focusing adaptive efforts at the pixel level. This deeper method, in comparison to the block processing techniques commonly found in existing adaptive methods, allows an increase in capacity while still offering a desired level of security. Based on computer simulations using high resolution, natural imagery and mobile device captured images, comparisons show that the proposed method securely allows an increased amount of embedding capacity but still avoids detection by varying steganalysis techniques.

Diverse Power Iteration Embeddings and Its Applications

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

Huang H.; Yoo S.; Yu, D.

2014-12-14

Abstract—Spectral Embedding is one of the most effective dimension reduction algorithms in data mining. However, its computation complexity has to be mitigated in order to apply it for real-world large scale data analysis. Many researches have been focusing on developing approximate spectral embeddings which are more efficient, but meanwhile far less effective. This paper proposes Diverse Power Iteration Embeddings (DPIE), which not only retains the similar efficiency of power iteration methods but also produces a series of diverse and more effective embedding vectors. We test this novel method by applying it to various data mining applications (e.g. clustering, anomaly detectionmore » and feature selection) and evaluating their performance improvements. The experimental results show our proposed DPIE is more effective than popular spectral approximation methods, and obtains the similar quality of classic spectral embedding derived from eigen-decompositions. Moreover it is extremely fast on big data applications. For example in terms of clustering result, DPIE achieves as good as 95% of classic spectral clustering on the complex datasets but 4000+ times faster in limited memory environment.« less

IGBT Switching Characteristic Curve Embedded Half-Bridge MMC Modelling and Real Time Simulation Realization

NASA Astrophysics Data System (ADS)

Zhengang, Lu; Hongyang, Yu; Xi, Yang

2017-05-01

The Modular Multilevel Converter (MMC) is one of the most attractive topologies in recent years for medium or high voltage industrial applications, such as high voltage dc transmission (HVDC) and medium voltage varying speed motor drive. The wide adoption of MMCs in industry is mainly due to its flexible expandability, transformer-less configuration, common dc bus, high reliability from redundancy, and so on. But, when the sub module number of MMC is more, the test of MMC controller will cost more time and effort. Hardware in the loop test based on real time simulator will save a lot of time and money caused by the MMC test. And due to the flexible of HIL, it becomes more and more popular in the industry area. The MMC modelling method remains an important issue for the MMC HIL test. Specifically, the VSC model should realistically reflect the nonlinear device switching characteristics, switching and conduction losses, tailing current, and diode reverse recovery behaviour of a realistic converter. In this paper, an IGBT switching characteristic curve embedded half-bridge MMC modelling method is proposed. This method is based on the switching curve referring and sample circuit calculation, and it is sample for implementation. Based on the proposed method, a FPGA real time simulation is carried out with 200ns sample time. The real time simulation results show the proposed method is correct.

Research on numerical control system based on S3C2410 and MCX314AL

NASA Astrophysics Data System (ADS)

Ren, Qiang; Jiang, Tingbiao

2008-10-01

With the rapid development of micro-computer technology, embedded system, CNC technology and integrated circuits, numerical control system with powerful functions can be realized by several high-speed CPU chips and RISC (Reduced Instruction Set Computing) chips which have small size and strong stability. In addition, the real-time operating system also makes the attainment of embedded system possible. Developing the NC system based on embedded technology can overcome some shortcomings of common PC-based CNC system, such as the waste of resources, low control precision, low frequency and low integration. This paper discusses a hardware platform of ENC (Embedded Numerical Control) system based on embedded processor chip ARM (Advanced RISC Machines)-S3C2410 and DSP (Digital Signal Processor)-MCX314AL and introduces the process of developing ENC system software. Finally write the MCX314AL's driver under the embedded Linux operating system. The embedded Linux operating system can deal with multitask well moreover satisfy the real-time and reliability of movement control. NC system has the advantages of best using resources and compact system with embedded technology. It provides a wealth of functions and superior performance with a lower cost. It can be sure that ENC is the direction of the future development.

Automatic Methods and Tools for the Verification of Real Time Systems

DTIC Science & Technology

1997-11-30

We developed formal methods and tools for the verification of real - time systems . This was accomplished by extending techniques, based on automata...embedded real - time systems , we introduced hybrid automata, which equip traditional discrete automata with real-numbered clock variables and continuous... real - time systems , and we identified the exact boundary between decidability and undecidability of real-time reasoning.

An analysis of the specificity of defects embedded into (1 0 0) and (1 1 1) faceted CVD diamond microcrystals grown on Si and Mo substrates by using E/H field discharge

NASA Astrophysics Data System (ADS)

Nasieka, Iurii; Strelchuk, Victor; Naseka, Victor; Stubrov, Yuriy; Dudnik, Stanislav; Gritsina, Vasiliy; Opalev, Oleg; Koshevoy, Konstantin; Strel'nitskij, Vladimir; Tkach, Vasyl; Boyko, Mykola; Antypov, Ievgen

2018-06-01

The PE CVD method with magnetic field discharge stabilization was applied for the growth of arrays of freestanding diamond grains (island films) as well as continuous films on Mo and Si substrates with (1 1 1) and (1 0 0) faceted microcrystals, respectively. Raman, SEM, XRD and PL methods were used for search of the specific features of defects embedded into (1 0 0) and (1 1 1) faceted grains. The main characteristic differences in the defect states of the diamond island films grown on Si and Mo substrates with (1 0 0) and (1 1 1) faceted diamond microcrystals were discussed on the base of the experimental data.

Experimental study on cross-sensitivity of temperature and vibration of embedded fiber Bragg grating sensors

NASA Astrophysics Data System (ADS)

Chen, Tao; Ye, Meng-li; Liu, Shu-liang; Deng, Yan

2018-03-01

In view of the principle for occurrence of cross-sensitivity, a series of calibration experiments are carried out to solve the cross-sensitivity problem of embedded fiber Bragg gratings (FBGs) using the reference grating method. Moreover, an ultrasonic-vibration-assisted grinding (UVAG) model is established, and finite element analysis (FEA) is carried out under the monitoring environment of embedded temperature measurement system. In addition, the related temperature acquisition tests are set in accordance with requirements of the reference grating method. Finally, comparative analyses of the simulation and experimental results are performed, and it may be concluded that the reference grating method may be utilized to effectively solve the cross-sensitivity of embedded FBGs.

Tensor manifold-based extreme learning machine for 2.5-D face recognition

NASA Astrophysics Data System (ADS)

Chong, Lee Ying; Ong, Thian Song; Teoh, Andrew Beng Jin

2018-01-01

We explore the use of the Gabor regional covariance matrix (GRCM), a flexible matrix-based descriptor that embeds the Gabor features in the covariance matrix, as a 2.5-D facial descriptor and an effective means of feature fusion for 2.5-D face recognition problems. Despite its promise, matching is not a trivial problem for GRCM since it is a special instance of a symmetric positive definite (SPD) matrix that resides in non-Euclidean space as a tensor manifold. This implies that GRCM is incompatible with the existing vector-based classifiers and distance matchers. Therefore, we bridge the gap of the GRCM and extreme learning machine (ELM), a vector-based classifier for the 2.5-D face recognition problem. We put forward a tensor manifold-compliant ELM and its two variants by embedding the SPD matrix randomly into reproducing kernel Hilbert space (RKHS) via tensor kernel functions. To preserve the pair-wise distance of the embedded data, we orthogonalize the random-embedded SPD matrix. Hence, classification can be done using a simple ridge regressor, an integrated component of ELM, on the random orthogonal RKHS. Experimental results show that our proposed method is able to improve the recognition performance and further enhance the computational efficiency.

Data embedding

DOEpatents

Sandford, II, Maxwell T.; Handel, Theodore G.

1997-01-01

A method of embedding auxiliary information into a set of host data, such as a photograph, television signal, facsimile transmission, or identification card. All such host data contain intrinsic noise, allowing pixels in the host data which are nearly identical and which have values differing by less than the noise value to be manipulated and replaced with auxiliary data. As the embedding method does not change the elemental values of the host data, the auxiliary data do not noticeably affect the appearance or interpretation of the host data. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user.

Data embedding

DOEpatents

Sandford, M.T. II; Handel, T.G.

1997-08-19

A method is disclosed for embedding auxiliary information into a set of host data, such as a photograph, television signal, facsimile transmission, or identification card. All such host data contain intrinsic noise, allowing pixels in the host data which are nearly identical and which have values differing by less than the noise value to be manipulated and replaced with auxiliary data. As the embedding method does not change the elemental values of the host data, the auxiliary data do not noticeably affect the appearance or interpretation of the host data. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user. 19 figs.

Evaluation of a Silver-Embedded Ceramic Tablet as a Primary and Secondary Point-of-Use Water Purification Technology in Limpopo Province, S. Africa

PubMed Central

Ehdaie, Beeta; Rento, Chloe T.; Son, Veronica; Turner, Sydney S.; Samie, Amidou; Dillingham, Rebecca A.

2017-01-01

The World Health Organization (WHO) recognizes point-of-use water treatment (PoUWT) technologies as effective means to improve water quality. This paper investigates long-term performance and social acceptance of a novel PoUWT technology, a silver-infused ceramic tablet, in Limpopo Province, South Africa. When placed in a water storage container, the silver-embedded ceramic tablet releases silver ions into water, thereby disinfecting microbial pathogens and leaving the water safe for human consumption. As a result of its simplicity and efficiency, the silver-embedded ceramic tablet can serve as a stand-alone PoUWT method and as a secondary PoUWT to improve exisitng PoUWT methods, such as ceramic water filters. In this paper, three PoUWT interventions were conducted to evaluate the silver-embedded ceramic tablet: (1) the silver-embedded ceramic tablet as a stand-alone PoUWT method, (2) ceramic water filters stand-alone, and (3) a filter-tablet combination. The filter-tablet combination evaluates the silver-embedded ceramic tablet as a secondary PoUWT method when placed in the lower reservoir of the ceramic water filter system to provide residual disinfection post-filtration. Samples were collected from 79 households over one year and analyzed for turbidity, total silver levels and coliform bacteria. Results show that the silver-embedded ceramic tablet effectively reduced total coliform bacteria (TC) and E. coli when used as a stand-alone PoUWT method and when used in combination with ceramic water filters. The silver-embedded ceramic tablet’s performance as a stand-alone PoUWT method was comparable to current inexpensive, single-use PoUWT methods, demonstrating 100% and 75% median reduction in E. coli and TC, respectively, after two months of use. Overall, the the filter-tablet combination performed the best of the three interventions, providing a 100% average percent reduction in E. coli over one year. User surveys were also conducted and indicated that the silver-embedded ceramic tablet was simple to use and culturally appropriate. Also, silver levels in all treated water samples remained below 20 μg/L, significantly lower than the drinking water standard of 100 μg/L, making it safe for consumption. Long-term data demonstrates that the silver-embedded ceramic tablet has beneficial effects even after one year of use. This study demonstrates that the silver-embedded ceramic tablet can effectively improve water quality when used alone, or with ceramic water filters, to reduce rates of recontamination. Therefore, the tablet has the potential to provide a low-cost means to purify water in resource-limited settings. PMID:28095435

Evaluation of a Silver-Embedded Ceramic Tablet as a Primary and Secondary Point-of-Use Water Purification Technology in Limpopo Province, S. Africa.

PubMed

Ehdaie, Beeta; Rento, Chloe T; Son, Veronica; Turner, Sydney S; Samie, Amidou; Dillingham, Rebecca A; Smith, James A

2017-01-01

The World Health Organization (WHO) recognizes point-of-use water treatment (PoUWT) technologies as effective means to improve water quality. This paper investigates long-term performance and social acceptance of a novel PoUWT technology, a silver-infused ceramic tablet, in Limpopo Province, South Africa. When placed in a water storage container, the silver-embedded ceramic tablet releases silver ions into water, thereby disinfecting microbial pathogens and leaving the water safe for human consumption. As a result of its simplicity and efficiency, the silver-embedded ceramic tablet can serve as a stand-alone PoUWT method and as a secondary PoUWT to improve exisitng PoUWT methods, such as ceramic water filters. In this paper, three PoUWT interventions were conducted to evaluate the silver-embedded ceramic tablet: (1) the silver-embedded ceramic tablet as a stand-alone PoUWT method, (2) ceramic water filters stand-alone, and (3) a filter-tablet combination. The filter-tablet combination evaluates the silver-embedded ceramic tablet as a secondary PoUWT method when placed in the lower reservoir of the ceramic water filter system to provide residual disinfection post-filtration. Samples were collected from 79 households over one year and analyzed for turbidity, total silver levels and coliform bacteria. Results show that the silver-embedded ceramic tablet effectively reduced total coliform bacteria (TC) and E. coli when used as a stand-alone PoUWT method and when used in combination with ceramic water filters. The silver-embedded ceramic tablet's performance as a stand-alone PoUWT method was comparable to current inexpensive, single-use PoUWT methods, demonstrating 100% and 75% median reduction in E. coli and TC, respectively, after two months of use. Overall, the the filter-tablet combination performed the best of the three interventions, providing a 100% average percent reduction in E. coli over one year. User surveys were also conducted and indicated that the silver-embedded ceramic tablet was simple to use and culturally appropriate. Also, silver levels in all treated water samples remained below 20 μg/L, significantly lower than the drinking water standard of 100 μg/L, making it safe for consumption. Long-term data demonstrates that the silver-embedded ceramic tablet has beneficial effects even after one year of use. This study demonstrates that the silver-embedded ceramic tablet can effectively improve water quality when used alone, or with ceramic water filters, to reduce rates of recontamination. Therefore, the tablet has the potential to provide a low-cost means to purify water in resource-limited settings.

The dynamic financial distress prediction method of EBW-VSTW-SVM

NASA Astrophysics Data System (ADS)

Sun, Jie; Li, Hui; Chang, Pei-Chann; He, Kai-Yu

2016-07-01

Financial distress prediction (FDP) takes important role in corporate financial risk management. Most of former researches in this field tried to construct effective static FDP (SFDP) models that are difficult to be embedded into enterprise information systems, because they are based on horizontal data-sets collected outside the modelling enterprise by defining the financial distress as the absolute conditions such as bankruptcy or insolvency. This paper attempts to propose an approach for dynamic evaluation and prediction of financial distress based on the entropy-based weighting (EBW), the support vector machine (SVM) and an enterprise's vertical sliding time window (VSTW). The dynamic FDP (DFDP) method is named EBW-VSTW-SVM, which keeps updating the FDP model dynamically with time goes on and only needs the historic financial data of the modelling enterprise itself and thus is easier to be embedded into enterprise information systems. The DFDP method of EBW-VSTW-SVM consists of four steps, namely evaluation of vertical relative financial distress (VRFD) based on EBW, construction of training data-set for DFDP modelling according to VSTW, training of DFDP model based on SVM and DFDP for the future time point. We carry out case studies for two listed pharmaceutical companies and experimental analysis for some other companies to simulate the sliding of enterprise vertical time window. The results indicated that the proposed approach was feasible and efficient to help managers improve corporate financial management.

Speech recognition for embedded automatic positioner for laparoscope

NASA Astrophysics Data System (ADS)

Chen, Xiaodong; Yin, Qingyun; Wang, Yi; Yu, Daoyin

2014-07-01

In this paper a novel speech recognition methodology based on Hidden Markov Model (HMM) is proposed for embedded Automatic Positioner for Laparoscope (APL), which includes a fixed point ARM processor as the core. The APL system is designed to assist the doctor in laparoscopic surgery, by implementing the specific doctor's vocal control to the laparoscope. Real-time respond to the voice commands asks for more efficient speech recognition algorithm for the APL. In order to reduce computation cost without significant loss in recognition accuracy, both arithmetic and algorithmic optimizations are applied in the method presented. First, depending on arithmetic optimizations most, a fixed point frontend for speech feature analysis is built according to the ARM processor's character. Then the fast likelihood computation algorithm is used to reduce computational complexity of the HMM-based recognition algorithm. The experimental results show that, the method shortens the recognition time within 0.5s, while the accuracy higher than 99%, demonstrating its ability to achieve real-time vocal control to the APL.

Using infrared HOG-based pedestrian detection for outdoor autonomous searching UAV with embedded system

NASA Astrophysics Data System (ADS)

Shao, Yanhua; Mei, Yanying; Chu, Hongyu; Chang, Zhiyuan; He, Yuxuan; Zhan, Huayi

2018-04-01

Pedestrian detection (PD) is an important application domain in computer vision and pattern recognition. Unmanned Aerial Vehicles (UAVs) have become a major field of research in recent years. In this paper, an algorithm for a robust pedestrian detection method based on the combination of the infrared HOG (IR-HOG) feature and SVM is proposed for highly complex outdoor scenarios on the basis of airborne IR image sequences from UAV. The basic flow of our application operation is as follows. Firstly, the thermal infrared imager (TAU2-336), which was installed on our Outdoor Autonomous Searching (OAS) UAV, is used for taking pictures of the designated outdoor area. Secondly, image sequences collecting and processing were accomplished by using high-performance embedded system with Samsung ODROID-XU4 and Ubuntu as the core and operating system respectively, and IR-HOG features were extracted. Finally, the SVM is used to train the pedestrian classifier. Experiment show that, our method shows promising results under complex conditions including strong noise corruption, partial occlusion etc.

Strain gauge using Si-based optical microring resonator.

PubMed

Lei, Longhai; Tang, Jun; Zhang, Tianen; Guo, Hao; Li, Yanna; Xie, Chengfeng; Shang, Chenglong; Bi, Yu; Zhang, Wendong; Xue, Chenyang; Liu, Jun

2014-12-20

This paper presents a strain gauge using the mechanical-optical coupling method. The Si-based optical microring resonator was employed as the sensing element, which was embedded on the microcantilevers. The experimental results show that applying external strain triggers a clear redshift of the output resonant spectrum of the structure. The sensitivity of 93.72  pm/MPa was achieved, which also was verified using theoretical simulations. This paper provides what we believe is a new method to develop micro-opto-electromechanical system (MOEMS) sensors.

Quantification of encapsulated bioburden in spacecraft polymer materials by cultivation-dependent and molecular methods.

PubMed

Bauermeister, Anja; Mahnert, Alexander; Auerbach, Anna; Böker, Alexander; Flier, Niwin; Weber, Christina; Probst, Alexander J; Moissl-Eichinger, Christine; Haberer, Klaus

2014-01-01

Bioburden encapsulated in spacecraft polymers (such as adhesives and coatings) poses a potential risk to jeopardize scientific exploration of other celestial bodies. This is particularly critical for spacecraft components intended for hard landing. So far, it remained unclear if polymers are indeed a source of microbial contamination. In addition, data with respect to survival of microbes during the embedding/polymerization process are sparse. In this study we developed testing strategies to quantitatively examine encapsulated bioburden in five different polymers used frequently and in large quantities on spaceflight hardware. As quantitative extraction of the bioburden from polymerized (solid) materials did not prove feasible, contaminants were extracted from uncured precursors. Cultivation-based analyses revealed <0.1-2.5 colony forming units (cfu) per cm3 polymer, whereas quantitative PCR-based detection of contaminants indicated considerably higher values, despite low DNA extraction efficiency. Results obtained from this approach reflect the most conservative proxy for encapsulated bioburden, as they give the maximum bioburden of the polymers irrespective of any additional physical and chemical stress occurring during polymerization. To address the latter issue, we deployed an embedding model to elucidate and monitor the physiological status of embedded Bacillus safensis spores in a cured polymer. Staining approaches using AlexaFluor succinimidyl ester 488 (AF488), propidium monoazide (PMA), CTC (5-cyano-2,3-diotolyl tetrazolium chloride) demonstrated that embedded spores retained integrity, germination and cultivation ability even after polymerization of the adhesive Scotch-Weld 2216 B/A. Using the methods presented here, we were able to estimate the worst case contribution of encapsulated bioburden in different polymers to the bioburden of spacecraft. We demonstrated that spores were not affected by polymerization processes. Besides Planetary Protection considerations, our results could prove useful for the manufacturing of food packaging, pharmacy industry and implant technology.

Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging.

PubMed

Ravi, Daniele; Fabelo, Himar; Callic, Gustavo Marrero; Yang, Guang-Zhong

2017-09-01

Recent advances in hyperspectral imaging have made it a promising solution for intra-operative tissue characterization, with the advantages of being non-contact, non-ionizing, and non-invasive. Working with hyperspectral images in vivo, however, is not straightforward as the high dimensionality of the data makes real-time processing challenging. In this paper, a novel dimensionality reduction scheme and a new processing pipeline are introduced to obtain a detailed tumor classification map for intra-operative margin definition during brain surgery. However, existing approaches to dimensionality reduction based on manifold embedding can be time consuming and may not guarantee a consistent result, thus hindering final tissue classification. The proposed framework aims to overcome these problems through a process divided into two steps: dimensionality reduction based on an extension of the T-distributed stochastic neighbor approach is first performed and then a semantic segmentation technique is applied to the embedded results by using a Semantic Texton Forest for tissue classification. Detailed in vivo validation of the proposed method has been performed to demonstrate the potential clinical value of the system.

Smart concrete slabs with embedded tubular PZT transducers for damage detection

NASA Astrophysics Data System (ADS)

Gao, Weihang; Huo, Linsheng; Li, Hongnan; Song, Gangbing

2018-02-01

The objective of this study is to develop a new concept and methodology of smart concrete slab (SCS) with embedded tubular lead zirconate titanate transducer array for image based damage detection. Stress waves, as the detecting signals, are generated by the embedded tubular piezoceramic transducers in the SCS. Tubular piezoceramic transducers are used due to their capacity of generating radially uniform stress waves in a two-dimensional concrete slab (such as bridge decks and walls), increasing the monitoring range. A circular type delay-and-sum (DAS) imaging algorithm is developed to image the active acoustic sources based on the direct response received by each sensor. After the scattering signals from the damage are obtained by subtracting the baseline response of the concrete structures from those of the defective ones, the elliptical type DAS imaging algorithm is employed to process the scattering signals and reconstruct the image of the damage. Finally, two experiments, including active acoustic source monitoring and damage imaging for concrete structures, are carried out to illustrate and demonstrate the effectiveness of the proposed method.

Semi-Supervised Tensor-Based Graph Embedding Learning and Its Application to Visual Discriminant Tracking.

PubMed

Hu, Weiming; Gao, Jin; Xing, Junliang; Zhang, Chao; Maybank, Stephen

2017-01-01

An appearance model adaptable to changes in object appearance is critical in visual object tracking. In this paper, we treat an image patch as a two-order tensor which preserves the original image structure. We design two graphs for characterizing the intrinsic local geometrical structure of the tensor samples of the object and the background. Graph embedding is used to reduce the dimensions of the tensors while preserving the structure of the graphs. Then, a discriminant embedding space is constructed. We prove two propositions for finding the transformation matrices which are used to map the original tensor samples to the tensor-based graph embedding space. In order to encode more discriminant information in the embedding space, we propose a transfer-learning- based semi-supervised strategy to iteratively adjust the embedding space into which discriminative information obtained from earlier times is transferred. We apply the proposed semi-supervised tensor-based graph embedding learning algorithm to visual tracking. The new tracking algorithm captures an object's appearance characteristics during tracking and uses a particle filter to estimate the optimal object state. Experimental results on the CVPR 2013 benchmark dataset demonstrate the effectiveness of the proposed tracking algorithm.

LSB-based Steganography Using Reflected Gray Code for Color Quantum Images

NASA Astrophysics Data System (ADS)

Li, Panchi; Lu, Aiping

2018-02-01

At present, the classical least-significant-bit (LSB) based image steganography has been extended to quantum image processing. For the existing LSB-based quantum image steganography schemes, the embedding capacity is no more than 3 bits per pixel. Therefore, it is meaningful to study how to improve the embedding capacity of quantum image steganography. This work presents a novel LSB-based steganography using reflected Gray code for colored quantum images, and the embedding capacity of this scheme is up to 4 bits per pixel. In proposed scheme, the secret qubit sequence is considered as a sequence of 4-bit segments. For the four bits in each segment, the first bit is embedded in the second LSB of B channel of the cover image, and and the remaining three bits are embedded in LSB of RGB channels of each color pixel simultaneously using reflected-Gray code to determine the embedded bit from secret information. Following the transforming rule, the LSB of stego-image are not always same as the secret bits and the differences are up to almost 50%. Experimental results confirm that the proposed scheme shows good performance and outperforms the previous ones currently found in the literature in terms of embedding capacity.

Embedded ensemble propagation for improving performance, portability, and scalability of uncertainty quantification on emerging computational architectures

DOE PAGES

Phipps, Eric T.; D'Elia, Marta; Edwards, Harold C.; ...

2017-04-18

In this study, quantifying simulation uncertainties is a critical component of rigorous predictive simulation. A key component of this is forward propagation of uncertainties in simulation input data to output quantities of interest. Typical approaches involve repeated sampling of the simulation over the uncertain input data, and can require numerous samples when accurately propagating uncertainties from large numbers of sources. Often simulation processes from sample to sample are similar and much of the data generated from each sample evaluation could be reused. We explore a new method for implementing sampling methods that simultaneously propagates groups of samples together in anmore » embedded fashion, which we call embedded ensemble propagation. We show how this approach takes advantage of properties of modern computer architectures to improve performance by enabling reuse between samples, reducing memory bandwidth requirements, improving memory access patterns, improving opportunities for fine-grained parallelization, and reducing communication costs. We describe a software technique for implementing embedded ensemble propagation based on the use of C++ templates and describe its integration with various scientific computing libraries within Trilinos. We demonstrate improved performance, portability and scalability for the approach applied to the simulation of partial differential equations on a variety of CPU, GPU, and accelerator architectures, including up to 131,072 cores on a Cray XK7 (Titan).« less

A robust embedded vision system feasible white balance algorithm

NASA Astrophysics Data System (ADS)

Wang, Yuan; Yu, Feihong

2018-01-01

White balance is a very important part of the color image processing pipeline. In order to meet the need of efficiency and accuracy in embedded machine vision processing system, an efficient and robust white balance algorithm combining several classical ones is proposed. The proposed algorithm mainly has three parts. Firstly, in order to guarantee higher efficiency, an initial parameter calculated from the statistics of R, G and B components from raw data is used to initialize the following iterative method. After that, the bilinear interpolation algorithm is utilized to implement demosaicing procedure. Finally, an adaptive step adjustable scheme is introduced to ensure the controllability and robustness of the algorithm. In order to verify the proposed algorithm's performance on embedded vision system, a smart camera based on IMX6 DualLite, IMX291 and XC6130 is designed. Extensive experiments on a large amount of images under different color temperatures and exposure conditions illustrate that the proposed white balance algorithm avoids color deviation problem effectively, achieves a good balance between efficiency and quality, and is suitable for embedded machine vision processing system.

An embedded fibre optic sensor for impact damage detection in composite materials

NASA Astrophysics Data System (ADS)

Glossop, Neil David William

1989-09-01

A structurally embedded fiber optic damage detection sensor for composite materials is described. The system is designed specifically for the detection of barely visible damage resulting from low velocity impacts in Kevlar-epoxy laminates. By monitoring the light transmission properties of optical fiber embedded in the composite, it was shown that the integrity of the material can be accurately determined. The effect of several parameters on the sensitivity of the system was investigated, including the effect of the optical fiber orientation and depth of embedding within the composite. A novel surface was also developed for the optical fibers to ensure they will fracture at the requisite damage level. The influence of the optical fiber sensors on the tensile and compressive material properties and on the impact resistance of the laminate was also studied. Extensive experimental results from impact tests are reported and a numerical model of the impact event is presented which is able to predict and model the damage mechanism and sensor system. A new and powerful method of nondestructive evaluation for translucent composite materials based on image enhanced backlighting is also described.

Using Structured Chemistry Examinations (SCHemEs) as an Assessment Method to Improve Undergraduate Students' Generic, Practical, and Laboratory-Based Skills

ERIC Educational Resources Information Center

Kirton, Stewart B.; Al-Ahmad, Abdullah; Fergus, Suzanne

2014-01-01

Increase in tuition fees means there will be renewed pressure on universities to provide "value for money" courses that provide extensive training in both subject-specific and generic skills. For graduates of chemistry this includes embedding the generic, practical, and laboratory-based skills associated with industrial research as an…

Challenges Experienced by District-Based Support Teams in the Execution of Their Functions in a Specific South African Province

ERIC Educational Resources Information Center

Makhalemele, Thabo; Nel, Mirna

2016-01-01

This article reports on the findings of an embedded mixed-method South African study that investigated the challenges experienced by District-Based Support Team (DBST) members in the sub-directorate of Inclusive Education of a South African province in the execution of their functions. A Likert-scale questionnaire and individual semi-structured…

Smart FBG-based FRP anchor

NASA Astrophysics Data System (ADS)

Zhou, Zhi; Zhang, Zhichun; Wang, Chuan; Ou, Jinping

2006-03-01

FRP ( Fiber Reinforced Polymer ) has become the popular material to alternate steel in civil engineering under harsh corrosion environment. But due to its low shear strength ability, the anchor for FRP is most important for its practical application. However, the strain state of the surface between FRP and anchor is not fully understood due to that there is no proper sensor to monitor the inner strain in the anchor by traditional method. In this paper, a new smart FBG-based FRP anchor is brought forward, and the inner strain distribution of FRP anchor has been monitored using FRP-OFBG sensors, a smart FBG-embedded FRP rebar, which is pre-embedded in the FRP rod and cast in the anchor. Based on the strain distribution information the bonding shear stress on the surface of FRP rod along the anchor can also be obtained. This method can supply important information for FRP anchor design and can also monitor the anchorage system, which is useful for the application of FRP in civil engineering. The experimental results also show that the smart FBG-based FRP anchor can give direct information of the load and damage of the FRP anchor.

Multilinear Graph Embedding: Representation and Regularization for Images.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting

2014-02-01

Given a set of images, finding a compact and discriminative representation is still a big challenge especially when multiple latent factors are hidden in the way of data generation. To represent multifactor images, although multilinear models are widely used to parameterize the data, most methods are based on high-order singular value decomposition (HOSVD), which preserves global statistics but interprets local variations inadequately. To this end, we propose a novel method, called multilinear graph embedding (MGE), as well as its kernelization MKGE to leverage the manifold learning techniques into multilinear models. Our method theoretically links the linear, nonlinear, and multilinear dimensionality reduction. We also show that the supervised MGE encodes informative image priors for image regularization, provided that an image is represented as a high-order tensor. From our experiments on face and gait recognition, the superior performance demonstrates that MGE better represents multifactor images than classic methods, including HOSVD and its variants. In addition, the significant improvement in image (or tensor) completion validates the potential of MGE for image regularization.

Spectral Regression Discriminant Analysis for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Pan, Y.; Wu, J.; Huang, H.; Liu, J.

2012-08-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learning methods are popular for dimensionality reduction, such as Locally Linear Embedding, Isomap, and Laplacian Eigenmap. However, a disadvantage of many manifold learning methods is that their computations usually involve eigen-decomposition of dense matrices which is expensive in both time and memory. In this paper, we introduce a new dimensionality reduction method, called Spectral Regression Discriminant Analysis (SRDA). SRDA casts the problem of learning an embedding function into a regression framework, which avoids eigen-decomposition of dense matrices. Also, with the regression based framework, different kinds of regularizes can be naturally incorporated into our algorithm which makes it more flexible. It can make efficient use of data points to discover the intrinsic discriminant structure in the data. Experimental results on Washington DC Mall and AVIRIS Indian Pines hyperspectral data sets demonstrate the effectiveness of the proposed method.

Analysis of shape memory alloy sensory particles for damage detection via substructure and continuum damage modeling

NASA Astrophysics Data System (ADS)

Bielefeldt, Brent R.; Benzerga, A. Amine; Hartl, Darren J.

2016-04-01

The ability to monitor and predict the structural health of an aircraft is of growing importance to the aerospace industry. Currently, structural inspections and maintenance are based upon experiences with similar aircraft operating in similar conditions. While effective, these methods are time-intensive and unnecessary if the aircraft is not in danger of structural failure. It is imagined that future aircraft will utilize non-destructive evaluation methods, allowing for the near real-time monitoring of structural health. A particularly interesting method involves utilizing the unique transformation response of shape memory alloy (SMA) particles embedded in an aircraft structure. By detecting changes in the mechanical and/or electromagnetic responses of embedded particles, operators could detect the formation or propagation of fatigue cracks in the vicinity of these particles. This work focuses on a finite element model of SMA particles embedded in an aircraft wing using a substructure modeling approach in which degrees of freedom are retained only at specified points of connection to other parts or the application of boundary conditions, greatly reducing computational cost. Previous work evaluated isolated particle response to a static crack to numerically demonstrate and validate this damage detection method. This paper presents the implementation of a damage model to account for crack propagation and examine for the first time the effect of particle configuration and/or relative placement with respect to the ability to detect damage.

Riemannian metric optimization on surfaces (RMOS) for intrinsic brain mapping in the Laplace-Beltrami embedding space.

PubMed

Gahm, Jin Kyu; Shi, Yonggang

2018-05-01

Surface mapping methods play an important role in various brain imaging studies from tracking the maturation of adolescent brains to mapping gray matter atrophy patterns in Alzheimer's disease. Popular surface mapping approaches based on spherical registration, however, have inherent numerical limitations when severe metric distortions are present during the spherical parameterization step. In this paper, we propose a novel computational framework for intrinsic surface mapping in the Laplace-Beltrami (LB) embedding space based on Riemannian metric optimization on surfaces (RMOS). Given a diffeomorphism between two surfaces, an isometry can be defined using the pullback metric, which in turn results in identical LB embeddings from the two surfaces. The proposed RMOS approach builds upon this mathematical foundation and achieves general feature-driven surface mapping in the LB embedding space by iteratively optimizing the Riemannian metric defined on the edges of triangular meshes. At the core of our framework is an optimization engine that converts an energy function for surface mapping into a distance measure in the LB embedding space, which can be effectively optimized using gradients of the LB eigen-system with respect to the Riemannian metrics. In the experimental results, we compare the RMOS algorithm with spherical registration using large-scale brain imaging data, and show that RMOS achieves superior performance in the prediction of hippocampal subfields and cortical gyral labels, and the holistic mapping of striatal surfaces for the construction of a striatal connectivity atlas from substantia nigra. Copyright © 2018 Elsevier B.V. All rights reserved.

A Freeze Substitution Fixation-Based Gold Enlarging Technique for EM Studies of Endocytosed Nanogold-Labeled Molecules

PubMed Central

He, Wanzhong; Kivork, Christine; Machinani, Suman; Morphew, Mary K.; Gail, Anna M.; Tesar, Devin B.; Tiangco, Noreen E.; McIntosh, J. Richard; Bjorkman, Pamela J.

2007-01-01

We have developed methods to locate individual ligands that can be used for electron microscopy studies of dynamic events during endocytosis and subsequent intracellular trafficking. The methods are based on enlargement of 1.4 nm Nanogold attached to an endocytosed ligand. Nanogold, a small label that does not induce misdirection of ligand-receptor complexes, is ideal for labeling ligands endocytosed by live cells, but is too small to be routinely located in cells by electron microscopy. Traditional pre-embedding enhancement protocols to enlarge Nanogold are not compatible with high pressure freezing/freeze substitution fixation (HPF/FSF), the most accurate method to preserve ultrastructure and dynamic events during trafficking. We have developed an improved enhancement procedure for chemically-fixed samples that reduced autonucleation, and a new pre-embedding gold-enlarging technique for HPF/FSF samples that preserved contrast and ultrastructure and can be used for high-resolution tomography. We evaluated our methods using labeled Fc as a ligand for the neonatal Fc receptor. Attachment of Nanogold to Fc did not interfere with receptor binding or uptake, and gold-labeled Fc could be specifically enlarged to allow identification in 2D projections and in tomograms. These methods should be broadly applicable to many endocytosis and transcytosis studies. PMID:17723309

A novel sample preparation method to avoid influence of embedding medium during nano-indentation

Treesearch

Yujie Meng; Siqun Wang; Zhiyong Cai; Timothy M. Young; Guanben Du; Yanjun Li

2012-01-01

The effect of the embedding medium on the nano-indentation measurements of lignocellulosic materials was investigated experimentally using nano-indentation. Both the reduced elastic modulus and the hardness of nonembedded cell walls were found to be lower than those of the embedded samples, proving that the embedding medium used for specimen preparation on cellulosic...

Phonon dispersion on Ag (100) surface: A modified analytic embedded atom method study

NASA Astrophysics Data System (ADS)

Xiao-Jun, Zhang; Chang-Le, Chen

2016-01-01

Within the harmonic approximation, the analytic expression of the dynamical matrix is derived based on the modified analytic embedded atom method (MAEAM) and the dynamics theory of surface lattice. The surface phonon dispersions along three major symmetry directions , and X¯M¯ are calculated for the clean Ag (100) surface by using our derived formulas. We then discuss the polarization and localization of surface modes at points X¯ and M¯ by plotting the squared polarization vectors as a function of the layer index. The phonon frequencies of the surface modes calculated by MAEAM are compared with the available experimental and other theoretical data. It is found that the present results are generally in agreement with the referenced experimental or theoretical results, with a maximum deviation of 10.4%. The agreement shows that the modified analytic embedded atom method is a reasonable many-body potential model to quickly describe the surface lattice vibration. It also lays a significant foundation for studying the surface lattice vibration in other metals. Project supported by the National Natural Science Foundation of China (Grant Nos. 61471301 and 61078057), the Scientific Research Program Funded by Shaanxi Provincial Education Department, China (Grant No. 14JK1301), and the Specialized Research Fund for the Doctoral Program of Higher Education, China (Grant No. 20126102110045).

A Steganographic Embedding Undetectable by JPEG Compatibility Steganalysis

DTIC Science & Technology

2002-01-01

itd.nrl.navy.mil Abstract. Steganography and steganalysis of digital images is a cat- and-mouse game. In recent work, Fridrich, Goljan and Du introduced a method...proposed embedding method. 1 Introduction Steganography and steganalysis of digital images is a cat-and-mouse game. Ever since Kurak and McHugh’s seminal...paper on LSB embeddings in images [10], various researchers have published work on either increasing the payload, im- proving the resistance to

A probabilistic method for determining the volume fraction of pre-embedded capsules in self-healing materials

NASA Astrophysics Data System (ADS)

Lv, Zhong; Chen, Huisu

2014-10-01

Autonomous healing of cracks using pre-embedded capsules containing healing agent is becoming a promising approach to restore the strength of damaged structures. In addition to the material properties, the size and volume fraction of capsules influence crack healing in the matrix. Understanding the crack and capsule interaction is critical in the development and design of structures made of self-healing materials. Assuming that the pre-embedded capsules are randomly dispersed we theoretically model flat ellipsoidal crack interaction with capsules and determine the probability of a crack intersecting the pre-embedded capsules i.e. the self-healing probability. We also develop a probabilistic model of a crack simultaneously meeting with capsules and catalyst carriers in two-component self-healing system matrix. Using a risk-based healing approach, we determine the volume fraction and size of the pre-embedded capsules that are required to achieve a certain self-healing probability. To understand the effect of the shape of the capsules on self-healing we theoretically modeled crack interaction with spherical and cylindrical capsules. We compared the results of our theoretical model with Monte-Carlo simulations of crack interaction with capsules. The formulae presented in this paper will provide guidelines for engineers working with self-healing structures in material selection and sustenance.

On Some Assumptions of the Null Hypothesis Statistical Testing

ERIC Educational Resources Information Center

Patriota, Alexandre Galvão

2017-01-01

Bayesian and classical statistical approaches are based on different types of logical principles. In order to avoid mistaken inferences and misguided interpretations, the practitioner must respect the inference rules embedded into each statistical method. Ignoring these principles leads to the paradoxical conclusions that the hypothesis…

Method for fabricating solar cells having integrated collector grids

NASA Technical Reports Server (NTRS)

Evans, J. C., Jr. (Inventor)

1979-01-01

A heterojunction or Schottky barrier photovoltaic device comprising a conductive base metal layer compatible with and coating predominately the exposed surface of the p-type substrate of the device such that a back surface field region is formed at the interface between the device and the base metal layer, a transparent, conductive mixed metal oxide layer in integral contact with the n-type layer of the heterojunction or Schottky barrier device having a metal alloy grid network of the same metal elements of the oxide constituents of the mixed metal oxide layer embedded in the mixed metal oxide layer, an insulating layer which prevents electrical contact between the conductive metal base layer and the transparent, conductive metal oxide layer, and a metal contact means covering the insulating layer and in intimate contact with the metal grid network embedded in the transparent, conductive oxide layer for conducting electrons generated by the photovoltaic process from the device.

Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes

DOE PAGES

Osborn, Sarah; Zulian, Patrick; Benson, Thomas; ...

2018-01-30

This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on anmore » embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.« less

Two-way coupling of magnetohydrodynamic simulations with embedded particle-in-cell simulations

NASA Astrophysics Data System (ADS)

Makwana, K. D.; Keppens, R.; Lapenta, G.

2017-12-01

We describe a method for coupling an embedded domain in a magnetohydrodynamic (MHD) simulation with a particle-in-cell (PIC) method. In this two-way coupling we follow the work of Daldorff et al. (2014) [19] in which the PIC domain receives its initial and boundary conditions from MHD variables (MHD to PIC coupling) while the MHD simulation is updated based on the PIC variables (PIC to MHD coupling). This method can be useful for simulating large plasma systems, where kinetic effects captured by particle-in-cell simulations are localized but affect global dynamics. We describe the numerical implementation of this coupling, its time-stepping algorithm, and its parallelization strategy, emphasizing the novel aspects of it. We test the stability and energy/momentum conservation of this method by simulating a steady-state plasma. We test the dynamics of this coupling by propagating plasma waves through the embedded PIC domain. Coupling with MHD shows satisfactory results for the fast magnetosonic wave, but significant distortion for the circularly polarized Alfvén wave. Coupling with Hall-MHD shows excellent coupling for the whistler wave. We also apply this methodology to simulate a Geospace Environmental Modeling (GEM) challenge type of reconnection with the diffusion region simulated by PIC coupled to larger scales with MHD and Hall-MHD. In both these cases we see the expected signatures of kinetic reconnection in the PIC domain, implying that this method can be used for reconnection studies.

Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes

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

Osborn, Sarah; Zulian, Patrick; Benson, Thomas

This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on anmore » embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.« less

Practicing Accounting Profession Criterial Skills in the Classroom: A Study of Collaborative Testing and the Impact on Final Exam Scores

ERIC Educational Resources Information Center

VanderLaan, Ski R.

2010-01-01

This mixed methods study (Creswell, 2008) was designed to test the influence of collaborative testing on learning using a quasi-experimental approach. This study used a modified embedded mixed method design in which the qualitative and quantitative data, associated with the secondary questions, provided a supportive role in a study based primarily…

Data embedding employing degenerate clusters of data having differences less than noise value

DOEpatents

Sanford, II, Maxwell T.; Handel, Theodore G.

1998-01-01

A method of embedding auxiliary information into a set of host data, such as a photograph, television signal, facsimile transmission, or identification card. All such host data contain intrinsic noise, allowing pixels in the host data which are nearly identical and which have values differing by less than the noise value to be manipulated and replaced with auxiliary data. As the embedding method does not change the elemental values of the host data, the auxiliary data do not noticeably affect the appearance or interpretation of the host data. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user.

Configurations of leadership practices in hospital units.

PubMed

Meier, Ninna

2015-01-01

The purpose of this paper is to explore how leadership is practiced across four different hospital units. The study is a comparative case study of four hospital units, based on detailed observations of the everyday work practices, interactions and interviews with ten interdisciplinary clinical managers. Comparing leadership as configurations of practices across four different clinical settings, the author shows how flexible and often shared leadership practices were embedded in and central to the core clinical work in all units studied here, especially in more unpredictable work settings. Practices of symbolic work and emotional support to staff were particularly important when patients were severely ill. Based on a study conducted with qualitative methods, these results cannot be expected to apply in all clinical settings. Future research is invited to extend the findings presented here by exploring leadership practices from a micro-level perspective in additional health care contexts: particularly the embedded and emergent nature of such practices. This paper shows leadership practices to be primarily embedded in the clinical work and often shared across organizational or professional boundaries. This paper demonstrated how leadership practices are embedded in the everyday work in hospital units. Moreover, the analysis shows how configurations of leadership practices varied in four different clinical settings, thus contributing with contextual accounts of leadership as practice, and suggested "configurations of practice" as a way to carve out similarities and differences in leadership practices across settings.

Authenticity preservation with histogram-based reversible data hiding and quadtree concepts.

PubMed

Huang, Hsiang-Cheh; Fang, Wai-Chi

2011-01-01

With the widespread use of identification systems, establishing authenticity with sensors has become an important research issue. Among the schemes for making authenticity verification based on information security possible, reversible data hiding has attracted much attention during the past few years. With its characteristics of reversibility, the scheme is required to fulfill the goals from two aspects. On the one hand, at the encoder, the secret information needs to be embedded into the original image by some algorithms, such that the output image will resemble the input one as much as possible. On the other hand, at the decoder, both the secret information and the original image must be correctly extracted and recovered, and they should be identical to their embedding counterparts. Under the requirement of reversibility, for evaluating the performance of the data hiding algorithm, the output image quality, named imperceptibility, and the number of bits for embedding, called capacity, are the two key factors to access the effectiveness of the algorithm. Besides, the size of side information for making decoding possible should also be evaluated. Here we consider using the characteristics of original images for developing our method with better performance. In this paper, we propose an algorithm that has the ability to provide more capacity than conventional algorithms, with similar output image quality after embedding, and comparable side information produced. Simulation results demonstrate the applicability and better performance of our algorithm.

Hiding Techniques for Dynamic Encryption Text based on Corner Point

NASA Astrophysics Data System (ADS)

Abdullatif, Firas A.; Abdullatif, Alaa A.; al-Saffar, Amna

2018-05-01

Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.

The nuclear size and mass effects on muonic hydrogen-like atoms embedded in Debye plasma

NASA Astrophysics Data System (ADS)

Poszwa, A.; Bahar, M. K.; Soylu, A.

2016-10-01

Effects of finite nuclear size and finite nuclear mass are investigated for muonic atoms and muonic ions embedded in the Debye plasma. Both nuclear charge radii and nuclear masses are taken into account with experimentally determined values. In particular, isotope shifts of bound state energies, radial probability densities, transition energies, and binding energies for several atoms are studied as functions of Debye length. The theoretical model based on semianalytical calculations, the Sturmian expansion method, and the perturbative approach has been constructed, in the nonrelativistic frame. For some limiting cases, the comparison with previous most accurate literature results has been made.

Micromagnetics on high-performance workstation and mobile computational platforms

NASA Astrophysics Data System (ADS)

Fu, S.; Chang, R.; Couture, S.; Menarini, M.; Escobar, M. A.; Kuteifan, M.; Lubarda, M.; Gabay, D.; Lomakin, V.

2015-05-01

The feasibility of using high-performance desktop and embedded mobile computational platforms is presented, including multi-core Intel central processing unit, Nvidia desktop graphics processing units, and Nvidia Jetson TK1 Platform. FastMag finite element method-based micromagnetic simulator is used as a testbed, showing high efficiency on all the platforms. Optimization aspects of improving the performance of the mobile systems are discussed. The high performance, low cost, low power consumption, and rapid performance increase of the embedded mobile systems make them a promising candidate for micromagnetic simulations. Such architectures can be used as standalone systems or can be built as low-power computing clusters.

Measurement of deformations of models in a wind tunnel

NASA Astrophysics Data System (ADS)

Charpin, F.; Armand, C.; Selvaggini, R.

Techniques used at the ONERA Modane Center to monitor geometric variations in scale-models in wind tunnel trials are described. The methods include: photography of reflections from mirrors embedded in the model surface; laser-based torsiometry with polarized mirrors embedded in the model surface; predictions of the deformations using numerical codes for the model surface mechanical characteristics and the measured surface stresses; and, use of an optical detector to monitor the position of luminous fiber optic sources emitting from the model surfaces. The data enhance the confidence that the wind tunnel aerodynamic data will correspond with the in-flight performance of full scale flight surfaces.

ESSAA: Embedded system safety analysis assistant

NASA Technical Reports Server (NTRS)

Wallace, Peter; Holzer, Joseph; Guarro, Sergio; Hyatt, Larry

1987-01-01

The Embedded System Safety Analysis Assistant (ESSAA) is a knowledge-based tool that can assist in identifying disaster scenarios. Imbedded software issues hazardous control commands to the surrounding hardware. ESSAA is intended to work from outputs to inputs, as a complement to simulation and verification methods. Rather than treating the software in isolation, it examines the context in which the software is to be deployed. Given a specified disasterous outcome, ESSAA works from a qualitative, abstract model of the complete system to infer sets of environmental conditions and/or failures that could cause a disasterous outcome. The scenarios can then be examined in depth for plausibility using existing techniques.

Quantum Fragment Based ab Initio Molecular Dynamics for Proteins.

PubMed

Liu, Jinfeng; Zhu, Tong; Wang, Xianwei; He, Xiao; Zhang, John Z H

2015-12-08

Developing ab initio molecular dynamics (AIMD) methods for practical application in protein dynamics is of significant interest. Due to the large size of biomolecules, applying standard quantum chemical methods to compute energies for dynamic simulation is computationally prohibitive. In this work, a fragment based ab initio molecular dynamics approach is presented for practical application in protein dynamics study. In this approach, the energy and forces of the protein are calculated by a recently developed electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method. For simulation in explicit solvent, mechanical embedding is introduced to treat protein interaction with explicit water molecules. This AIMD approach has been applied to MD simulations of a small benchmark protein Trpcage (with 20 residues and 304 atoms) in both the gas phase and in solution. Comparison to the simulation result using the AMBER force field shows that the AIMD gives a more stable protein structure in the simulation, indicating that quantum chemical energy is more reliable. Importantly, the present fragment-based AIMD simulation captures quantum effects including electrostatic polarization and charge transfer that are missing in standard classical MD simulations. The current approach is linear-scaling, trivially parallel, and applicable to performing the AIMD simulation of proteins with a large size.

Diagnosis of multiple sclerosis from EEG signals using nonlinear methods.

PubMed

Torabi, Ali; Daliri, Mohammad Reza; Sabzposhan, Seyyed Hojjat

2017-12-01

EEG signals have essential and important information about the brain and neural diseases. The main purpose of this study is classifying two groups of healthy volunteers and Multiple Sclerosis (MS) patients using nonlinear features of EEG signals while performing cognitive tasks. EEG signals were recorded when users were doing two different attentional tasks. One of the tasks was based on detecting a desired change in color luminance and the other task was based on detecting a desired change in direction of motion. EEG signals were analyzed in two ways: EEG signals analysis without rhythms decomposition and EEG sub-bands analysis. After recording and preprocessing, time delay embedding method was used for state space reconstruction; embedding parameters were determined for original signals and their sub-bands. Afterwards nonlinear methods were used in feature extraction phase. To reduce the feature dimension, scalar feature selections were done by using T-test and Bhattacharyya criteria. Then, the data were classified using linear support vector machines (SVM) and k-nearest neighbor (KNN) method. The best combination of the criteria and classifiers was determined for each task by comparing performances. For both tasks, the best results were achieved by using T-test criterion and SVM classifier. For the direction-based and the color-luminance-based tasks, maximum classification performances were 93.08 and 79.79% respectively which were reached by using optimal set of features. Our results show that the nonlinear dynamic features of EEG signals seem to be useful and effective in MS diseases diagnosis.

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

Cepstral domain modification of audio signals for data embedding: preliminary results

NASA Astrophysics Data System (ADS)

Gopalan, Kaliappan

2004-06-01

A method of embedding data in an audio signal using cepstral domain modification is described. Based on successful embedding in the spectral points of perceptually masked regions in each frame of speech, first the technique was extended to embedding in the log spectral domain. This extension resulted at approximately 62 bits /s of embedding with less than 2 percent of bit error rate (BER) for a clean cover speech (from the TIMIT database), and about 2.5 percent for a noisy speech (from an air traffic controller database), when all frames - including silence and transition between voiced and unvoiced segments - were used. Bit error rate increased significantly when the log spectrum in the vicinity of a formant was modified. In the next procedure, embedding by altering the mean cepstral values of two ranges of indices was studied. Tests on both a noisy utterance and a clean utterance indicated barely noticeable perceptual change in speech quality when lower range of cepstral indices - corresponding to vocal tract region - was modified in accordance with data. With an embedding capacity of approximately 62 bits/s - using one bit per each frame regardless of frame energy or type of speech - initial results showed a BER of less than 1.5 percent for a payload capacity of 208 embedded bits using the clean cover speech. BER of less than 1.3 percent resulted for the noisy host with a capacity was 316 bits. When the cepstrum was modified in the region of excitation, BER increased to over 10 percent. With quantization causing no significant problem, the technique warrants further studies with different cepstral ranges and sizes. Pitch-synchronous cepstrum modification, for example, may be more robust to attacks. In addition, cepstrum modification in regions of speech that are perceptually masked - analogous to embedding in frequency masked regions - may yield imperceptible stego audio with low BER.

A simple method for constructing the inhomogeneous quantum group IGLq(n) and its universal enveloping algebra Uq(igl(n))

NASA Astrophysics Data System (ADS)

Shariati, A.; Aghamohammadi, A.

1995-12-01

We propose a simple and concise method to construct the inhomogeneous quantum group IGLq(n) and its universal enveloping algebra Uq(igl(n)). Our technique is based on embedding an n-dimensional quantum space in an n+1-dimensional one as the set xn+1=1. This is possible only if one considers the multiparametric quantum space whose parameters are fixed in a specific way. The quantum group IGLq(n) is then the subset of GLq(n+1), which leaves the xn+1=1 subset invariant. For the deformed universal enveloping algebra Uq(igl(n)), we will show that it can also be embedded in Uq(gl(n+1)), provided one uses the multiparametric deformation of U(gl(n+1)) with a specific choice of its parameters.

Embedded algorithms within an FPGA-based system to process nonlinear time series data

NASA Astrophysics Data System (ADS)

Jones, Jonathan D.; Pei, Jin-Song; Tull, Monte P.

2008-03-01

This paper presents some preliminary results of an ongoing project. A pattern classification algorithm is being developed and embedded into a Field-Programmable Gate Array (FPGA) and microprocessor-based data processing core in this project. The goal is to enable and optimize the functionality of onboard data processing of nonlinear, nonstationary data for smart wireless sensing in structural health monitoring. Compared with traditional microprocessor-based systems, fast growing FPGA technology offers a more powerful, efficient, and flexible hardware platform including on-site (field-programmable) reconfiguration capability of hardware. An existing nonlinear identification algorithm is used as the baseline in this study. The implementation within a hardware-based system is presented in this paper, detailing the design requirements, validation, tradeoffs, optimization, and challenges in embedding this algorithm. An off-the-shelf high-level abstraction tool along with the Matlab/Simulink environment is utilized to program the FPGA, rather than coding the hardware description language (HDL) manually. The implementation is validated by comparing the simulation results with those from Matlab. In particular, the Hilbert Transform is embedded into the FPGA hardware and applied to the baseline algorithm as the centerpiece in processing nonlinear time histories and extracting instantaneous features of nonstationary dynamic data. The selection of proper numerical methods for the hardware execution of the selected identification algorithm and consideration of the fixed-point representation are elaborated. Other challenges include the issues of the timing in the hardware execution cycle of the design, resource consumption, approximation accuracy, and user flexibility of input data types limited by the simplicity of this preliminary design. Future work includes making an FPGA and microprocessor operate together to embed a further developed algorithm that yields better computational and power efficiency.

Calculation of nuclear spin-spin coupling constants using frozen density embedding

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

Götz, Andreas W., E-mail: agoetz@sdsc.edu; Autschbach, Jochen; Visscher, Lucas, E-mail: visscher@chem.vu.nl

2014-03-14

We present a method for a subsystem-based calculation of indirect nuclear spin-spin coupling tensors within the framework of current-spin-density-functional theory. Our approach is based on the frozen-density embedding scheme within density-functional theory and extends a previously reported subsystem-based approach for the calculation of nuclear magnetic resonance shielding tensors to magnetic fields which couple not only to orbital but also spin degrees of freedom. This leads to a formulation in which the electron density, the induced paramagnetic current, and the induced spin-magnetization density are calculated separately for the individual subsystems. This is particularly useful for the inclusion of environmental effects inmore » the calculation of nuclear spin-spin coupling constants. Neglecting the induced paramagnetic current and spin-magnetization density in the environment due to the magnetic moments of the coupled nuclei leads to a very efficient method in which the computationally expensive response calculation has to be performed only for the subsystem of interest. We show that this approach leads to very good results for the calculation of solvent-induced shifts of nuclear spin-spin coupling constants in hydrogen-bonded systems. Also for systems with stronger interactions, frozen-density embedding performs remarkably well, given the approximate nature of currently available functionals for the non-additive kinetic energy. As an example we show results for methylmercury halides which exhibit an exceptionally large shift of the one-bond coupling constants between {sup 199}Hg and {sup 13}C upon coordination of dimethylsulfoxide solvent molecules.« less

Integrating Science and Language Arts through Technology-based Macrocontexts.

ERIC Educational Resources Information Center

Kumar, David; Bristor, Valerie J.

1999-01-01

Videos, virtual reality, and the World Wide Web create effective macrocontexts for integrating science and language arts. Contexts must be readily available, appropriate for the level, and interesting to students. Teachers should be able to identify scientific concepts and language skills embedded in them. Alternative assessment methods are more…

Cobalt-embedded carbon nanofiber derived from a coordination polymer as a highly efficient heterogeneous catalyst for activating oxone in water.

PubMed

Lin, Kun-Yi Andrew; Tong, Wai-Chi; Du, Yunchen

2018-03-01

Carbon fiber (CF) supported cobalt nanoparticles (NPs) are promising catalysts for activating Oxone because carbon is non-metal and earth-abundant, and CF-based catalysts exhibit a high aspect ratio, which affords more accessible and dense catalytic sites. Nevertheless, most of CF-supported catalysts are fabricated by post-synthetic methods, which involve complicated preparations. More importantly, metallic NPs are attached to the outer surface of CF rather than embedded within CF. However, there is still a great demand for developing Co-bearing carbon fibers for Oxone activation via simple and effective methods. Thus, this study proposes to develop a cobalt NP-embedded carbon nanofiber (CCNF) by a simple hydrothermal reaction of Co and nitrilotriacetic acid (NA), followed by one-step carbonization. Owing to the coordinative structure of CoNA, the derivative CCNF exhibits a fibrous carbon matrix embedded with evenly distributed and densely packed Co 3 O 4 and magnetic Co 0 nanoparticles. The fibrous structure, magnetism and embedded Co NPs enable CCNF to be a promising catalyst for Oxone activation. As degradation of Rhodamine B (RhB) is selected as a model reaction, CCNF not only rapidly activates Oxone to fully degrade RhB but also shows a much higher catalytic activity than the most common Oxone activator, Co 3 O 4 . CCNF also exhibits the lowest activation energy than any reported catalysts for Oxone activation to degrade RhB. In addition, CCNF could be re-used to activate Oxone for RhB degradation. These results indicate that CCNF is a conveniently prepared and highly effective fibrous Co/C hybrid material for activating Oxone to oxidize contaminants in water. Copyright © 2017. Published by Elsevier Ltd.

Embedding Quantitative Methods by Stealth in Political Science: Developing a Pedagogy for Psephology

ERIC Educational Resources Information Center

Gunn, Andrew

2017-01-01

Student evaluations of quantitative methods courses in political science often reveal they are characterised by aversion, alienation and anxiety. As a solution to this problem, this paper describes a pedagogic research project with the aim of embedding quantitative methods by stealth into the first-year undergraduate curriculum. This paper…

Mixed methods research in mental health nursing.

PubMed

Kettles, A M; Creswell, J W; Zhang, W

2011-08-01

Mixed methods research is becoming more widely used in order to answer research questions and to investigate research problems in mental health and psychiatric nursing. However, two separate literature searches, one in Scotland and one in the USA, revealed that few mental health nursing studies identified mixed methods research in their titles. Many studies used the term 'embedded' but few studies identified in the literature were mixed methods embedded studies. The history, philosophical underpinnings, definition, types of mixed methods research and associated pragmatism are discussed, as well as the need for mixed methods research. Examples of mental health nursing mixed methods research are used to illustrate the different types of mixed methods: convergent parallel, embedded, explanatory and exploratory in their sequential and concurrent combinations. Implementing mixed methods research is also discussed briefly and the problem of identifying mixed methods research in mental and psychiatric nursing are discussed with some possible solutions to the problem proposed. © 2011 Blackwell Publishing.

Unsupervised nonlinear dimensionality reduction machine learning methods applied to multiparametric MRI in cerebral ischemia: preliminary results

NASA Astrophysics Data System (ADS)

Parekh, Vishwa S.; Jacobs, Jeremy R.; Jacobs, Michael A.

2014-03-01

The evaluation and treatment of acute cerebral ischemia requires a technique that can determine the total area of tissue at risk for infarction using diagnostic magnetic resonance imaging (MRI) sequences. Typical MRI data sets consist of T1- and T2-weighted imaging (T1WI, T2WI) along with advanced MRI parameters of diffusion-weighted imaging (DWI) and perfusion weighted imaging (PWI) methods. Each of these parameters has distinct radiological-pathological meaning. For example, DWI interrogates the movement of water in the tissue and PWI gives an estimate of the blood flow, both are critical measures during the evolution of stroke. In order to integrate these data and give an estimate of the tissue at risk or damaged; we have developed advanced machine learning methods based on unsupervised non-linear dimensionality reduction (NLDR) techniques. NLDR methods are a class of algorithms that uses mathematically defined manifolds for statistical sampling of multidimensional classes to generate a discrimination rule of guaranteed statistical accuracy and they can generate a two- or three-dimensional map, which represents the prominent structures of the data and provides an embedded image of meaningful low-dimensional structures hidden in their high-dimensional observations. In this manuscript, we develop NLDR methods on high dimensional MRI data sets of preclinical animals and clinical patients with stroke. On analyzing the performance of these methods, we observed that there was a high of similarity between multiparametric embedded images from NLDR methods and the ADC map and perfusion map. It was also observed that embedded scattergram of abnormal (infarcted or at risk) tissue can be visualized and provides a mechanism for automatic methods to delineate potential stroke volumes and early tissue at risk.

Optimization of the formation of embedded multicellular spheroids of MCF-7 cells: How to reliably produce a biomimetic 3D model.

PubMed

Zhang, Wenli; Li, Caibin; Baguley, Bruce C; Zhou, Fang; Zhou, Weisai; Shaw, John P; Wang, Zhen; Wu, Zimei; Liu, Jianping

2016-12-15

To obtain a multicellular MCF-7 spheroid model to mimic the three-dimensional (3D) of tumors, the microwell liquid overlay (A) and hanging-drop/agar (B) methods were first compared for their technical parameters. Then a method for embedding spheroids within collagen was optimized. For method A, centrifugation assisted cells form irregular aggregates but not spheroids. For method B, an extended sedimentation period of over 24 h for cell suspensions and increased viscosity of the culture medium using methylcellulose were necessary to harvest a dense and regular cell spheroid. When the number was less than 5000 cells/drop, embedded spheroids showed no tight cores and higher viability than the unembedded. However, above 5000 cells/drop, cellular viability of embedded spheroids was not significantly different from unembedded spheroids and cells invading through the collagen were in a sun-burst pattern with tight cores. Propidium Iodide staining indicated that spheroids had necrotic cores. The doxorubicin cytotoxicity demonstrated that spheroids were less susceptible to DOX than their monolayer cells. A reliable and reproducible method for embedding spheroids using the hanging-drop/agarose method within collagen is described herein. The cell culture model can be used to guide experimental manipulation of 3D cell cultures and to evaluate anticancer drug efficacy. Copyright © 2016 Elsevier Inc. All rights reserved.

Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape.

PubMed

Dai, Hanjun; Umarov, Ramzan; Kuwahara, Hiroyuki; Li, Yu; Song, Le; Gao, Xin

2017-11-15

An accurate characterization of transcription factor (TF)-DNA affinity landscape is crucial to a quantitative understanding of the molecular mechanisms underpinning endogenous gene regulation. While recent advances in biotechnology have brought the opportunity for building binding affinity prediction methods, the accurate characterization of TF-DNA binding affinity landscape still remains a challenging problem. Here we propose a novel sequence embedding approach for modeling the transcription factor binding affinity landscape. Our method represents DNA binding sequences as a hidden Markov model which captures both position specific information and long-range dependency in the sequence. A cornerstone of our method is a novel message passing-like embedding algorithm, called Sequence2Vec, which maps these hidden Markov models into a common nonlinear feature space and uses these embedded features to build a predictive model. Our method is a novel combination of the strength of probabilistic graphical models, feature space embedding and deep learning. We conducted comprehensive experiments on over 90 large-scale TF-DNA datasets which were measured by different high-throughput experimental technologies. Sequence2Vec outperforms alternative machine learning methods as well as the state-of-the-art binding affinity prediction methods. Our program is freely available at https://github.com/ramzan1990/sequence2vec. xin.gao@kaust.edu.sa or lsong@cc.gatech.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

A liquid metal-based structurally embedded vascular antenna: II. Multiobjective and parameterized design exploration

NASA Astrophysics Data System (ADS)

Hartl, D. J.; Frank, G. J.; Malak, R. J.; Baur, J. W.

2017-02-01

Research on the structurally embedded vascular antenna concept leverages past efforts on liquid metal (LM) reconfigurable electronics, microvascular composites, and structurally integrated and reconfigurable antennas. Such a concept has potential for reducing system weight or volume while simultaneously allowing in situ adjustment of resonant frequencies and/or changes in antenna directivity. This work considers a microvascular pattern embedded in a laminated composite and filled with LM. The conductive liquid provides radio frequency (RF) functionality while also allowing self-cooling. Models describing RF propagation and heat transfer, in addition to the structural effects of both the inclusion of channels and changes in temperature, were described in part 1 of this two-part work. In this part 2, the engineering models developed and demonstrated in part 1 toward the initial exploration of design trends are implemented into multiple optimization frameworks for more detailed design studies, one of which being novel and particularly applicable to this class of problem. The computational expense associated with the coupled multiphysical analysis of the structurally embedded LM transmitting antenna motivates the consideration of surrogate-based optimization methods. Both static and adaptive approaches are explored; it is shown that iteratively correcting the surrogate leads to more accurate optimized design predictions. The expected strong dependence of antenna performance on thermal environment motivates the consideration of a novel ‘parameterized’ optimization approach that simultaneously calculates whole families of optimal designs based on changes in design or operational variables generally beyond the control of the designer. The change in Pareto-optimal response with evolution in operating conditions is clearly demonstrated.

Can't Count or Won't Count? Embedding Quantitative Methods in Substantive Sociology Curricula: A Quasi-Experiment.

PubMed

Williams, Malcolm; Sloan, Luke; Cheung, Sin Yi; Sutton, Carole; Stevens, Sebastian; Runham, Libby

2016-06-01

This paper reports on a quasi-experiment in which quantitative methods (QM) are embedded within a substantive sociology module. Through measuring student attitudes before and after the intervention alongside control group comparisons, we illustrate the impact that embedding has on the student experience. Our findings are complex and even contradictory. Whilst the experimental group were less likely to be distrustful of statistics and appreciate how QM inform social research, they were also less confident about their statistical abilities, suggesting that through 'doing' quantitative sociology the experimental group are exposed to the intricacies of method and their optimism about their own abilities is challenged. We conclude that embedding QM in a single substantive module is not a 'magic bullet' and that a wider programme of content and assessment diversification across the curriculum is preferential.

A Project-Based Laboratory for Learning Embedded System Design with Industry Support

ERIC Educational Resources Information Center

Lee, Chyi-Shyong; Su, Juing-Huei; Lin, Kuo-En; Chang, Jia-Hao; Lin, Gu-Hong

2010-01-01

A project-based laboratory for learning embedded system design with support from industry is presented in this paper. The aim of this laboratory is to motivate students to learn the building blocks of embedded systems and practical control algorithms by constructing a line-following robot using the quadratic interpolation technique to predict the…

Development of an optimized protocol for the detection of classical swine fever virus in formalin-fixed, paraffin-embedded tissues by seminested reverse transcription-polymerase chain reaction and comparison with in situ hybridization.

PubMed

Ha, S-K; Choi, C; Chae, C

2004-10-01

An optimized protocol was developed for the detection of classical swine fever virus (CSFV) in formalin-fixed, paraffin-embedded tissues obtained from experimentally and naturally infected pigs by seminested reverse transcription-polymerase chain reaction (RT-PCR). The results for seminested RT-PCR were compared with those determined by in situ hybridization. The results obtained show that the use of deparaffinization with xylene, digestion with proteinase K, extraction with Trizol LS, followed by seminested RT-PCR is a reliable detection method. An increase in sensitivity was observed as amplicon size decreased. The highest sensitivity for RT-PCR on formalin-fixed, paraffin-embedded tissues RNA was obtained with amplicon sizes less than approximately 200 base pairs. An hybridization signal for CSFV was detected in lymph nodes from 12 experimentally and 12 naturally infected pigs. The sensitivity of seminested RT-PCR compared with in situ hybridization was 100% for CSFV. When only formalin-fixed tissues are available, seminested RT-PCR and in situ hybridization would be useful diagnostic methods for the detection of CSFV nucleic acid.

A new paradigm on battery powered embedded system design based on User-Experience-Oriented method

NASA Astrophysics Data System (ADS)

Wang, Zhuoran; Wu, Yue

2014-03-01

The battery sustainable time has been an active research topic recently for the development of battery powered embedded products such as tablets and smart phones, which are determined by the battery capacity and power consumption. Despite numerous efforts on the improvement of battery capacity in the field of material engineering, the power consumption also plays an important role and easier to ameliorate in delivering a desirable user-experience, especially considering the moderate advancement on batteries for decades. In this study, a new Top-Down modelling method, User-Experience-Oriented Battery Powered Embedded System Design Paradigm, is proposed to estimate the target average power consumption, to guide the hardware and software design, and eventually to approach the theoretical lowest power consumption that the application is still able to provide the full functionality. Starting from the 10-hour sustainable time standard, average working current is defined with battery design capacity and set as a target. Then an implementation is illustrated from both hardware perspective, which is summarized as Auto-Gating power management, and from software perspective, which introduces a new algorithm, SleepVote, to guide the system task design and scheduling.

Embedded Streaming Deep Neural Networks Accelerator With Applications.

PubMed

Dundar, Aysegul; Jin, Jonghoon; Martini, Berin; Culurciello, Eugenio

2017-07-01

Deep convolutional neural networks (DCNNs) have become a very powerful tool in visual perception. DCNNs have applications in autonomous robots, security systems, mobile phones, and automobiles, where high throughput of the feedforward evaluation phase and power efficiency are important. Because of this increased usage, many field-programmable gate array (FPGA)-based accelerators have been proposed. In this paper, we present an optimized streaming method for DCNNs' hardware accelerator on an embedded platform. The streaming method acts as a compiler, transforming a high-level representation of DCNNs into operation codes to execute applications in a hardware accelerator. The proposed method utilizes maximum computational resources available based on a novel-scheduled routing topology that combines data reuse and data concatenation. It is tested with a hardware accelerator implemented on the Xilinx Kintex-7 XC7K325T FPGA. The system fully explores weight-level and node-level parallelizations of DCNNs and achieves a peak performance of 247 G-ops while consuming less than 4 W of power. We test our system with applications on object classification and object detection in real-world scenarios. Our results indicate high-performance efficiency, outperforming all other presented platforms while running these applications.

Aircraft dual-shaft jet engine with indirect action fuel flow controller

NASA Astrophysics Data System (ADS)

Tudosie, Alexandru-Nicolae

2017-06-01

The paper deals with an aircraft single-jet engine's control system, based on a fuel flow controller. Considering the engine as controlled object and its thrust the most important operation effect, from the multitude of engine's parameters only its rotational speed n is measurable and proportional to its thrust, so engine's speed has become the most important controlled parameter. Engine's control system is based on fuel injection Qi dosage, while the output is engine's speed n. Based on embedded system's main parts' mathematical models, the author has described the system by its block diagram with transfer functions; furthermore, some Simulink-Matlab simulations are performed, concerning embedded system quality (its output parameters time behavior) and, meanwhile, some conclusions concerning engine's parameters mutual influences are revealed. Quantitative determinations are based on author's previous research results and contributions, as well as on existing models (taken from technical literature). The method can be extended for any multi-spool engine, single- or twin-jet.

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors.

PubMed

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-05-28

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms.

Data embedding employing degenerate clusters of data having differences less than noise value

DOEpatents

Sanford, M.T. II; Handel, T.G.

1998-10-06

A method of embedding auxiliary information into a set of host data, such as a photograph, television signal, facsimile transmission, or identification card. All such host data contain intrinsic noise, allowing pixels in the host data which are nearly identical and which have values differing by less than the noise value to be manipulated and replaced with auxiliary data. As the embedding method does not change the elemental values of the host data, the auxiliary data do not noticeably affect the appearance or interpretation of the host data. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user. 35 figs.

SPIP: A computer program implementing the Interaction Picture method for simulation of light-wave propagation in optical fibre

NASA Astrophysics Data System (ADS)

Balac, Stéphane; Fernandez, Arnaud

2016-02-01

The computer program SPIP is aimed at solving the Generalized Non-Linear Schrödinger equation (GNLSE), involved in optics e.g. in the modelling of light-wave propagation in an optical fibre, by the Interaction Picture method, a new efficient alternative method to the Symmetric Split-Step method. In the SPIP program a dedicated costless adaptive step-size control based on the use of a 4th order embedded Runge-Kutta method is implemented in order to speed up the resolution.

Aquatic Debris Detection Using Embedded Camera Sensors

PubMed Central

Wang, Yong; Wang, Dianhong; Lu, Qian; Luo, Dapeng; Fang, Wu

2015-01-01

Aquatic debris monitoring is of great importance to human health, aquatic habitats and water transport. In this paper, we first introduce the prototype of an aquatic sensor node equipped with an embedded camera sensor. Based on this sensing platform, we propose a fast and accurate debris detection algorithm. Our method is specifically designed based on compressive sensing theory to give full consideration to the unique challenges in aquatic environments, such as waves, swaying reflections, and tight energy budget. To upload debris images, we use an efficient sparse recovery algorithm in which only a few linear measurements need to be transmitted for image reconstruction. Besides, we implement the host software and test the debris detection algorithm on realistically deployed aquatic sensor nodes. The experimental results demonstrate that our approach is reliable and feasible for debris detection using camera sensors in aquatic environments. PMID:25647741

An effective convolutional neural network model for Chinese sentiment analysis

NASA Astrophysics Data System (ADS)

Zhang, Yu; Chen, Mengdong; Liu, Lianzhong; Wang, Yadong

2017-06-01

Nowadays microblog is getting more and more popular. People are increasingly accustomed to expressing their opinions on Twitter, Facebook and Sina Weibo. Sentiment analysis of microblog has received significant attention, both in academia and in industry. So far, Chinese microblog exploration still needs lots of further work. In recent years CNN has also been used to deal with NLP tasks, and already achieved good results. However, these methods ignore the effective use of a large number of existing sentimental resources. For this purpose, we propose a Lexicon-based Sentiment Convolutional Neural Networks (LSCNN) model focus on Weibo's sentiment analysis, which combines two CNNs, trained individually base on sentiment features and word embedding, at the fully connected hidden layer. The experimental results show that our model outperforms the CNN model only with word embedding features on microblog sentiment analysis task.

Optimal temperature control of tissue embedded with gold nanoparticles for enhanced thermal therapy based on two-energy equation model.

PubMed

Wang, Shen-Ling; Qi, Hong; Ren, Ya-Tao; Chen, Qin; Ruan, Li-Ming

2018-05-01

Thermal therapy is a very promising method for cancer treatment, which can be combined with chemotherapy, radiotherapy and other programs for enhanced cancer treatment. In order to get a better effect of thermal therapy in clinical applications, optimal internal temperature distribution of the tissue embedded with gold nanoparticles (GNPs) for enhanced thermal therapy was investigated in present research. The Monte Carlo method was applied to calculate the heat generation of the tissue embedded with GNPs irradiated by continuous laser. To have a better insight into the physical problem of heat transfer in tissues, the two-energy equation was employed to calculate the temperature distribution of the tissue in the process of GNPs enhanced therapy. The Arrhenius equation was applied to evaluate the degree of permanent thermal damage. A parametric study was performed to investigate the influence factors on the tissue internal temperature distribution, such as incident light intensity, the GNPs volume fraction, the periodic heating and cooling time, and the incident light position. It was found that period heating and cooling strategy can effectively avoid overheating of skin surface and heat damage of healthy tissue. Lower GNPs volume fraction will be better for the heat source distribution. Furthermore, the ring heating strategy is superior to the central heating strategy in the treatment effect. All the analysis provides theoretical guidance for optimal temperature control of tissue embedded with GNP for enhanced thermal therapy. Copyright © 2018 Elsevier Ltd. All rights reserved.

An Integrated In Silico Method to Discover Novel Rock1 Inhibitors: Multi- Complex-Based Pharmacophore, Molecular Dynamics Simulation and Hybrid Protocol Virtual Screening.

PubMed

Chen, Haining; Li, Sijia; Hu, Yajiao; Chen, Guo; Jiang, Qinglin; Tong, Rongsheng; Zang, Zhihe; Cai, Lulu

2016-01-01

Rho-associated, coiled-coil containing protein kinase 1 (ROCK1) is an important regulator of focal adhesion, actomyosin contraction and cell motility. In this manuscript, a combination of the multi-complex-based pharmacophore (MCBP), molecular dynamics simulation and a hybrid protocol of a virtual screening method, comprised of multipharmacophore- based virtual screening (PBVS) and ensemble docking-based virtual screening (DBVS) methods were used for retrieving novel ROCK1 inhibitors from the natural products database embedded in the ZINC database. Ten hit compounds were selected from the hit compounds, and five compounds were tested experimentally. Thus, these results may provide valuable information for further discovery of more novel ROCK1 inhibitors.

Rapid embedding methods into epoxy and LR White resins for morphological and immunological analysis of cryofixed biological specimens.

PubMed

McDonald, Kent L

2014-02-01

A variety of specimens including bacteria, ciliates, choanoflagellates (Salpingoeca rosetta), zebrafish (Danio rerio) embryos, nematode worms (Caenorhabditis elegans), and leaves of white clover (Trifolium repens) plants were high pressure frozen, freeze-substituted, infiltrated with either Epon, Epon-Araldite, or LR White resins, and polymerized. Total processing time from freezing to blocks ready to section was about 6 h. For epoxy embedding the specimens were freeze-substituted in 1% osmium tetroxide plus 0.1% uranyl acetate in acetone. For embedding in LR White the freeze-substitution medium was 0.2% uranyl acetate in acetone. Rapid infiltration was achieved by centrifugation through increasing concentrations of resin followed by polymerization at 100°C for 1.5-2 h. The preservation of ultrastructure was comparable to standard freeze substitution and resin embedding methods that take days to complete. On-section immunolabeling results for actin and tubulin molecules were positive with very low background labeling. The LR White methods offer a safer, quicker, and less-expensive alternative to Lowicryl embedding of specimens processed for on-section immunolabeling without traditional aldehyde fixatives.

GPU surface extraction using the closest point embedding

NASA Astrophysics Data System (ADS)

Kim, Mark; Hansen, Charles

2015-01-01

Isosurface extraction is a fundamental technique used for both surface reconstruction and mesh generation. One method to extract well-formed isosurfaces is a particle system; unfortunately, particle systems can be slow. In this paper, we introduce an enhanced parallel particle system that uses the closest point embedding as the surface representation to speedup the particle system for isosurface extraction. The closest point embedding is used in the Closest Point Method (CPM), a technique that uses a standard three dimensional numerical PDE solver on two dimensional embedded surfaces. To fully take advantage of the closest point embedding, it is coupled with a Barnes-Hut tree code on the GPU. This new technique produces well-formed, conformal unstructured triangular and tetrahedral meshes from labeled multi-material volume datasets. Further, this new parallel implementation of the particle system is faster than any known methods for conformal multi-material mesh extraction. The resulting speed-ups gained in this implementation can reduce the time from labeled data to mesh from hours to minutes and benefits users, such as bioengineers, who employ triangular and tetrahedral meshes

[Evaluation of 3 methods of DNA extraction from paraffin-embedded material for the amplification of genomic DNA using PCR].

PubMed

Mesquita, R A; Anzai, E K; Oliveira, R N; Nunes, F D

2001-01-01

There are several protocols reported in the literature for the extraction of genomic DNA from formalin-fixed paraffin-embedded samples. Genomic DNA is utilized in molecular analyses, including PCR. This study compares three different methods for the extraction of genomic DNA from formalin-fixed paraffin-embedded (inflammatory fibrous hyperplasia) and non-formalin-fixed (normal oral mucosa) samples: phenol with enzymatic digestion, and silica with and without enzymatic digestion. The amplification of DNA by means of the PCR technique was carried out with primers for the exon 7 of human keratin type 14. Amplicons were analyzed by means of electrophoresis in an 8% polyacrylamide gel with 5% glycerol, followed by silver-staining visualization. The phenol/enzymatic digestion and the silica/enzymatic digestion methods provided amplicons from both tissue samples. The method described is a potential aid in the establishment of the histopathologic diagnosis and in retrospective studies with archival paraffin-embedded samples.

Method for preparing hydrous zirconium oxide gels and spherules

DOEpatents

Collins, Jack L.

2003-08-05

Methods for preparing hydrous zirconium oxide spherules, hydrous zirconium oxide gels such as gel slabs, films, capillary and electrophoresis gels, zirconium monohydrogen phosphate spherules, hydrous zirconium oxide spherules having suspendable particles homogeneously embedded within to form a composite sorbent, zirconium monohydrogen phosphate spherules having suspendable particles of at least one different sorbent homogeneously embedded within to form a composite sorbent having a desired crystallinity, zirconium oxide spherules having suspendable particles homogeneously embedded within to form a composite, hydrous zirconium oxide fiber materials, zirconium oxide fiber materials, hydrous zirconium oxide fiber materials having suspendable particles homogeneously embedded within to form a composite, zirconium oxide fiber materials having suspendable particles homogeneously embedded within to form a composite and spherules of barium zirconate. The hydrous zirconium oxide spherules and gel forms prepared by the gel-sphere, internal gelation process are useful as inorganic ion exchangers, catalysts, getters and ceramics.

A low noise stenography method for medical images with QR encoding of patient information

NASA Astrophysics Data System (ADS)

Patiño-Vanegas, Alberto; Contreras-Ortiz, Sonia H.; Martinez-Santos, Juan C.

2017-03-01

This paper proposes an approach to facilitate the process of individualization of patients from their medical images, without compromising the inherent confidentiality of medical data. The identification of a patient from a medical image is not often the goal of security methods applied to image records. Usually, any identification data is removed from shared records, and security features are applied to determine ownership. We propose a method for embedding a QR-code containing information that can be used to individualize a patient. This is done so that the image to be shared does not differ significantly from the original image. The QR-code is distributed in the image by changing several pixels according to a threshold value based on the average value of adjacent pixels surrounding the point of interest. The results show that the code can be embedded and later fully recovered with minimal changes in the UIQI index - less than 0.1% of different.

Cross-entropy embedding of high-dimensional data using the neural gas model.

PubMed

Estévez, Pablo A; Figueroa, Cristián J; Saito, Kazumi

2005-01-01

A cross-entropy approach to mapping high-dimensional data into a low-dimensional space embedding is presented. The method allows to project simultaneously the input data and the codebook vectors, obtained with the Neural Gas (NG) quantizer algorithm, into a low-dimensional output space. The aim of this approach is to preserve the relationship defined by the NG neighborhood function for each pair of input and codebook vectors. A cost function based on the cross-entropy between input and output probabilities is minimized by using a Newton-Raphson method. The new approach is compared with Sammon's non-linear mapping (NLM) and the hierarchical approach of combining a vector quantizer such as the self-organizing feature map (SOM) or NG with the NLM recall algorithm. In comparison with these techniques, our method delivers a clear visualization of both data points and codebooks, and it achieves a better mapping quality in terms of the topology preservation measure q(m).

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

PubMed Central

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-01-01

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. PMID:28837096

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

PubMed

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-08-24

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

Can’t Count or Won’t Count? Embedding Quantitative Methods in Substantive Sociology Curricula: A Quasi-Experiment

PubMed Central

Williams, Malcolm; Sloan, Luke; Cheung, Sin Yi; Sutton, Carole; Stevens, Sebastian; Runham, Libby

2015-01-01

This paper reports on a quasi-experiment in which quantitative methods (QM) are embedded within a substantive sociology module. Through measuring student attitudes before and after the intervention alongside control group comparisons, we illustrate the impact that embedding has on the student experience. Our findings are complex and even contradictory. Whilst the experimental group were less likely to be distrustful of statistics and appreciate how QM inform social research, they were also less confident about their statistical abilities, suggesting that through ‘doing’ quantitative sociology the experimental group are exposed to the intricacies of method and their optimism about their own abilities is challenged. We conclude that embedding QM in a single substantive module is not a ‘magic bullet’ and that a wider programme of content and assessment diversification across the curriculum is preferential. PMID:27330225

Closed-form solution of temperature and heat flux in embedded cooling channels

NASA Astrophysics Data System (ADS)

Griggs, Steven Craig

1997-11-01

An analytical method is discussed for predicting temperature in a layered composite material with embedded cooling channels. The cooling channels are embedded in the material to maintain its temperature at acceptable levels. Problems of this type are encountered in the aerospace industry and include high-temperature or high-heat-flux protection for advanced composite-material skins of high-speed air vehicles; thermal boundary-layer flow control on supersonic transports; or infrared signature suppression on military vehicles. A Green's function solution of the diffusion equation is used to simultaneously predict the global and localized effects of temperature in the material and in the embedded cooling channels. The integral method is used to solve the energy equation with fluid flow to find the solution of temperature and heat flux in the cooling fluid and material simultaneously. This method of calculation preserves the three-dimensional nature of this problem.

Data Embedding for Covert Communications, Digital Watermarking, and Information Augmentation

DTIC Science & Technology

2000-03-01

proposed an image authentication algorithm based on the fragility of messages embedded in digital images using LSB encoding. In [Walt95], he proposes...Invertibility 2/ 3 SAMPLE DATA EMBEDDING TECHNIQUES 23 3.1 SPATIAL TECHNIQUES 23 LSB Encoding in Intensity Images 23 Data embedding...ATTACK 21 FIGURE 6. EFFECTS OF LSB ENCODING 25 FIGURE 7. ALGORITHM FOR EZSTEGO 28 FIGURE 8. DATA EMBEDDING IN THE FREQUENCY DOMAIN 30 FIGURE 9

Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding

PubMed Central

Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

2015-01-01

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches. PMID:26153771

Embedding piezoresistive pressure sensors to obtain online pressure profiles inside fiber composite laminates.

PubMed

Moghaddam, Maryam Kahali; Breede, Arne; Brauner, Christian; Lang, Walter

2015-03-27

The production of large and complex parts using fiber composite materials is costly due to the frequent formation of voids, porosity and waste products. By embedding different types of sensors and monitoring the process in real time, the amount of wastage can be significantly reduced. This work focuses on developing a knowledge-based method to improve and ensure complete impregnation of the fibers before initiation of the resin cure. Piezoresistive and capacitive pressure sensors were embedded in fiber composite laminates to measure the real-time the pressure values inside the laminate. A change of pressure indicates resin infusion. The sensors were placed in the laminate and the resin was infused by vacuum. The embedded piezoresistive pressure sensors were able to track the vacuum pressure in the fiber composite laminate setup, as well as the arrival of the resin at the sensor. The pressure increase due to closing the resin inlet was also measured. In contrast, the capacitive type of sensor was found to be inappropriate for measuring these quantities. The following study demonstrates real-time monitoring of pressure changes inside the fiber composite laminate, which validate the use of Darcy's law in porous media to control the resin flow during infusion.

Adsorption mechanism of SF6 decomposed species on pyridine-like PtN3 embedded CNT: A DFT study

NASA Astrophysics Data System (ADS)

Cui, Hao; Zhang, Xiaoxing; Chen, Dachang; Tang, Ju

2018-07-01

Metal-Nx embedded CNT have aroused considerable attention in the field of gas interaction due to their strong catalytic behavior, which provides prospective scopes for gas adsorption and sensing. Detecting SF6 decomposed species in certain devices is essential to guarantee their safe operation. In this work, we performed DFT method and simulated the adsorption of three SF6 decomposed gases (SO2, SOF2 and SO2F2) onto the PtN3 embedded CNT surface, in order to shed light on its adsorption ability and sensing mechanism. Results suggest that the CNT embedded with PtN3 center has strong interaction with these gas molecules, leading to high hybridization between Pt dopant and active atoms inner gas molecules. These interactions are assumed to be chemisorption due to the remarkable Ead and QT, thus resulting in dramatic deformations in electronic structure of PtN3-CNT near the Fermi level. Furthermore, the electronic redistribution cause the conductivity increase of proposed material in three systems, based on frontier molecular orbital theory. Our calculations attempt to suggest novel sensing material that are potentially employed in detection of SF6 decomposed components.

Embedded high-contrast distributed grating structures

DOEpatents

Zubrzycki, Walter J.; Vawter, Gregory A.; Allerman, Andrew A.

2002-01-01

A new class of fabrication methods for embedded distributed grating structures is claimed, together with optical devices which include such structures. These new methods are the only known approach to making defect-free high-dielectric contrast grating structures, which are smaller and more efficient than are conventional grating structures.

A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples.

PubMed

Boskamp, Tobias; Lachmund, Delf; Oetjen, Janina; Cordero Hernandez, Yovany; Trede, Dennis; Maass, Peter; Casadonte, Rita; Kriegsmann, Jörg; Warth, Arne; Dienemann, Hendrik; Weichert, Wilko; Kriegsmann, Mark

2017-07-01

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) shows a high potential for applications in histopathological diagnosis, and in particular for supporting tumor typing and subtyping. The development of such applications requires the extraction of spectral fingerprints that are relevant for the given tissue and the identification of biomarkers associated with these spectral patterns. We propose a novel data analysis method based on the extraction of characteristic spectral patterns (CSPs) that allow automated generation of classification models for spectral data. Formalin-fixed paraffin embedded (FFPE) tissue samples from N=445 patients assembled on 12 tissue microarrays were analyzed. The method was applied to discriminate primary lung and pancreatic cancer, as well as adenocarcinoma and squamous cell carcinoma of the lung. A classification accuracy of 100% and 82.8%, resp., could be achieved on core level, assessed by cross-validation. The method outperformed the more conventional classification method based on the extraction of individual m/z values in the first application, while achieving a comparable accuracy in the second. LC-MS/MS peptide identification demonstrated that the spectral features present in selected CSPs correspond to peptides relevant for the respective classification. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2016 Elsevier B.V. All rights reserved.

Developing a Psychology Undergraduate Research Community in a New University

ERIC Educational Resources Information Center

Roberts, Patricia; Ertubey, Candan; McMurray, Isabella; Robertson, Ian

2012-01-01

Psychology is a science-based discipline in which research is inextricably embedded in teaching and learning activities. Educators use different methods to help students in their learning of the nature of research and the practical skills required to conduct research, with students playing either a passive or more active role in the learning…

Demonstrable Competence: An Assessment Method for Competency Domains in Learning and Leadership Doctoral Program

ERIC Educational Resources Information Center

Rausch, David W.; Crawford, Elizabeth K.

2013-01-01

Through this paper, we describe how a doctoral program in Learning and Leadership combines the best of both worlds from theory based programs and applied programs. Participants work from their embedded professional practice underpinned with the theoretical constructs of the program's seven foundational competency domains. Competencies are…

Image-Based Participatory Pedagogies: Reimagining Social Justice

ERIC Educational Resources Information Center

Powell, Kimberly; Serriere, Stephanie

2013-01-01

As educators and scholars in social studies and art education respectively, we describe two visual methods from our own research and teaching in pre-K to university settings that are embedded in visual practices. We underscore their transformative potential by using Maxine Greene's (1995) ideas of the education of perception as a critical means…

Using Students' Knowledge to Generate Individual Feedback: Concept for an Intelligent Educational System on Logistics.

ERIC Educational Resources Information Center

Ziems, Dietrich; Neumann, Gaby

1997-01-01

Discusses a methods kit for interactive problem-solving exercises in engineering education as well as a methodology for intelligent evaluation of solutions. The quality of a system teaching logistics thinking can be improved using artificial intelligence. Embedding a rule-based diagnosis module that evaluates the student's knowledge actively…

Methodological Reflections: Supervisory Discourses and Practice-Based Learning

ERIC Educational Resources Information Center

Sarja, Anneli; Janhonen, Sirpa

2009-01-01

The concept of dialogue is often examined apart from the social and historical context in which it is embedded. This paper identifies how dialogue between a superior and a subordinate generates a reorganisation of situated knowledge in the education and training of nurse teachers. We created an analytic method of supervisory discourse founded on…

Embedded correlated wavefunction schemes: theory and applications.

PubMed

Libisch, Florian; Huang, Chen; Carter, Emily A

2014-09-16

Conspectus Ab initio modeling of matter has become a pillar of chemical research: with ever-increasing computational power, simulations can be used to accurately predict, for example, chemical reaction rates, electronic and mechanical properties of materials, and dynamical properties of liquids. Many competing quantum mechanical methods have been developed over the years that vary in computational cost, accuracy, and scalability: density functional theory (DFT), the workhorse of solid-state electronic structure calculations, features a good compromise between accuracy and speed. However, approximate exchange-correlation functionals limit DFT's ability to treat certain phenomena or states of matter, such as charge-transfer processes or strongly correlated materials. Furthermore, conventional DFT is purely a ground-state theory: electronic excitations are beyond its scope. Excitations in molecules are routinely calculated using time-dependent DFT linear response; however applications to condensed matter are still limited. By contrast, many-electron wavefunction methods aim for a very accurate treatment of electronic exchange and correlation. Unfortunately, the associated computational cost renders treatment of more than a handful of heavy atoms challenging. On the other side of the accuracy spectrum, parametrized approaches like tight-binding can treat millions of atoms. In view of the different (dis-)advantages of each method, the simulation of complex systems seems to force a compromise: one is limited to the most accurate method that can still handle the problem size. For many interesting problems, however, compromise proves insufficient. A possible solution is to break up the system into manageable subsystems that may be treated by different computational methods. The interaction between subsystems may be handled by an embedding formalism. In this Account, we review embedded correlated wavefunction (CW) approaches and some applications. We first discuss our density functional embedding theory, which is formally exact. We show how to determine the embedding potential, which replaces the interaction between subsystems, at the DFT level. CW calculations are performed using a fixed embedding potential, that is, a non-self-consistent embedding scheme. We demonstrate this embedding theory for two challenging electron transfer phenomena: (1) initial oxidation of an aluminum surface and (2) hot-electron-mediated dissociation of hydrogen molecules on a gold surface. In both cases, the interaction between gas molecules and metal surfaces were treated by sophisticated CW techniques, with the remainder of the extended metal surface being treated by DFT. Our embedding approach overcomes the limitations of conventional Kohn-Sham DFT in describing charge transfer, multiconfigurational character, and excited states. From these embedding simulations, we gained important insights into fundamental processes that are crucial aspects of fuel cell catalysis (i.e., O2 reduction at metal surfaces) and plasmon-mediated photocatalysis by metal nanoparticles. Moreover, our findings agree very well with experimental observations, while offering new views into the chemistry. We finally discuss our recently formulated potential-functional embedding theory that provides a seamless, first-principles way to include back-action onto the environment from the embedded region.

Research and embedded implementation of Layer 3 switch

NASA Astrophysics Data System (ADS)

Song, Jin; Cheng, Zijing

2009-12-01

In the internetworking world, switches and routers have been deployed for workgroup and enterprise connectivity. In the past, switches mainly operated at Layer 2 (they were extensions of bridges), while routers were clearly Layer3 devices. Recently, the line has blurred and switches operating at Layer 3 are becoming more popular. This paper explains the Linux Bridge, Layer 2 Switches, Virtual LAN (VLAN) and Layer 3 Switches. The flow chart of Layer 3 switches and working routine related to Layer 3 switch technology were investigated in detail. This paper presents a new method to implement layer 3 switching that is entirely accomplished in software and is embedded implemented by code transplanting based on PowerPC 460GT platform.

Functional DNA quantification guides accurate next-generation sequencing mutation detection in formalin-fixed, paraffin-embedded tumor biopsies

PubMed Central

2013-01-01

The formalin-fixed, paraffin-embedded (FFPE) biopsy is a challenging sample for molecular assays such as targeted next-generation sequencing (NGS). We compared three methods for FFPE DNA quantification, including a novel PCR assay (‘QFI-PCR’) that measures the absolute copy number of amplifiable DNA, across 165 residual clinical specimens. The results reveal the limitations of commonly used approaches, and demonstrate the value of an integrated workflow using QFI-PCR to improve the accuracy of NGS mutation detection and guide changes in input that can rescue low quality FFPE DNA. These findings address a growing need for improved quality measures in NGS-based patient testing. PMID:24001039

A Weight-Adaptive Laplacian Embedding for Graph-Based Clustering.

PubMed

Cheng, De; Nie, Feiping; Sun, Jiande; Gong, Yihong

2017-07-01

Graph-based clustering methods perform clustering on a fixed input data graph. Thus such clustering results are sensitive to the particular graph construction. If this initial construction is of low quality, the resulting clustering may also be of low quality. We address this drawback by allowing the data graph itself to be adaptively adjusted in the clustering procedure. In particular, our proposed weight adaptive Laplacian (WAL) method learns a new data similarity matrix that can adaptively adjust the initial graph according to the similarity weight in the input data graph. We develop three versions of these methods based on the L2-norm, fuzzy entropy regularizer, and another exponential-based weight strategy, that yield three new graph-based clustering objectives. We derive optimization algorithms to solve these objectives. Experimental results on synthetic data sets and real-world benchmark data sets exhibit the effectiveness of these new graph-based clustering methods.

SPAMCART: a code for smoothed particle Monte Carlo radiative transfer

NASA Astrophysics Data System (ADS)

Lomax, O.; Whitworth, A. P.

2016-10-01

We present a code for generating synthetic spectral energy distributions and intensity maps from smoothed particle hydrodynamics simulation snapshots. The code is based on the Lucy Monte Carlo radiative transfer method, I.e. it follows discrete luminosity packets as they propagate through a density field, and then uses their trajectories to compute the radiative equilibrium temperature of the ambient dust. The sources can be extended and/or embedded, and discrete and/or diffuse. The density is not mapped on to a grid, and therefore the calculation is performed at exactly the same resolution as the hydrodynamics. We present two example calculations using this method. First, we demonstrate that the code strictly adheres to Kirchhoff's law of radiation. Secondly, we present synthetic intensity maps and spectra of an embedded protostellar multiple system. The algorithm uses data structures that are already constructed for other purposes in modern particle codes. It is therefore relatively simple to implement.

Electrochemical removal of metallic implants from Technovit 9100 New embedded hard and soft tissues prior to histological sectioning.

PubMed

Willbold, Elmar; Reebmann, Mattias; Jeffries, Richard; Witte, Frank

2013-11-01

Solid metallic implants in soft or hard tissues are serious challenges for histological processing. However, metallic implants are more frequently used in e.g. cardiovascular or orthopaedic therapies. Before clinical use, these devices need to be tested thoroughly in a biological environment and histological analysis of their biocompatibility is a major requirement. To allow the histological analysis of metallic implants in tissues especially in calcified hard tissues, we describe a method for embedding these tissues in the resin Technovit 9100 New and removing the metallic implants by electrochemical dissolution. With the combination of these two processes, we are able to achieve 5 μm thick sections from soft or hard tissues with a superior preservation of tissue architecture and especially the implant-tissue interface. These sections can be stained by classical stainings, immunohistochemical and enzymehistochemical as well as DNA-based staining methods.

Soft-error tolerance and energy consumption evaluation of embedded computer with magnetic random access memory in practical systems using computer simulations

NASA Astrophysics Data System (ADS)

Nebashi, Ryusuke; Sakimura, Noboru; Sugibayashi, Tadahiko

2017-08-01

We evaluated the soft-error tolerance and energy consumption of an embedded computer with magnetic random access memory (MRAM) using two computer simulators. One is a central processing unit (CPU) simulator of a typical embedded computer system. We simulated the radiation-induced single-event-upset (SEU) probability in a spin-transfer-torque MRAM cell and also the failure rate of a typical embedded computer due to its main memory SEU error. The other is a delay tolerant network (DTN) system simulator. It simulates the power dissipation of wireless sensor network nodes of the system using a revised CPU simulator and a network simulator. We demonstrated that the SEU effect on the embedded computer with 1 Gbit MRAM-based working memory is less than 1 failure in time (FIT). We also demonstrated that the energy consumption of the DTN sensor node with MRAM-based working memory can be reduced to 1/11. These results indicate that MRAM-based working memory enhances the disaster tolerance of embedded computers.

Method for preparing hydrous iron oxide gels and spherules

DOEpatents

Collins, Jack L.; Lauf, Robert J.; Anderson, Kimberly K.

2003-07-29

The present invention is directed to methods for preparing hydrous iron oxide spherules, hydrous iron oxide gels such as gel slabs, films, capillary and electrophoresis gels, iron monohydrogen phosphate spherules, hydrous iron oxide spherules having suspendable particles homogeneously embedded within to form composite sorbents and catalysts, iron monohydrogen phosphate spherules having suspendable particles of at least one different sorbent homogeneously embedded within to form a composite sorbent, iron oxide spherules having suspendable particles homogeneously embedded within to form a composite of hydrous iron oxide fiber materials, iron oxide fiber materials, hydrous iron oxide fiber materials having suspendable particles homogeneously embedded within to form a composite, iron oxide fiber materials having suspendable particles homogeneously embedded within to form a composite, dielectric spherules of barium, strontium, and lead ferrites and mixtures thereof, and composite catalytic spherules of barium or strontium ferrite embedded with oxides of Mg, Zn, Pb, Ce and mixtures thereof. These variations of hydrous iron oxide spherules and gel forms prepared by the gel-sphere, internal gelation process offer more useful forms of inorganic ion exchangers, catalysts, getters, dielectrics, and ceramics.

Connector For Embedded Optical Fiber

NASA Technical Reports Server (NTRS)

Wilkerson, Charles; Hiles, Steven; Houghton, J. Richard; Holland, Brent W.

1994-01-01

Partly embedded fixture is simpler and sturdier than other types of outlets for optical fibers embedded in solid structures. No need to align coupling prism and lenses. Fixture includes base, tube bent at 45 degree angle, and ceramic ferrule.

Java Source Code Analysis for API Migration to Embedded Systems

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

Winter, Victor; McCoy, James A.; Guerrero, Jonathan

Embedded systems form an integral part of our technological infrastructure and oftentimes play a complex and critical role within larger systems. From the perspective of reliability, security, and safety, strong arguments can be made favoring the use of Java over C in such systems. In part, this argument is based on the assumption that suitable subsets of Java’s APIs and extension libraries are available to embedded software developers. In practice, a number of Java-based embedded processors do not support the full features of the JVM. For such processors, source code migration is a mechanism by which key abstractions offered bymore » APIs and extension libraries can made available to embedded software developers. The analysis required for Java source code-level library migration is based on the ability to correctly resolve element references to their corresponding element declarations. A key challenge in this setting is how to perform analysis for incomplete source-code bases (e.g., subsets of libraries) from which types and packages have been omitted. This article formalizes an approach that can be used to extend code bases targeted for migration in such a manner that the threats associated the analysis of incomplete code bases are eliminated.« less

A new method to unveil embedded stellar clusters

NASA Astrophysics Data System (ADS)

Lombardi, Marco; Lada, Charles J.; Alves, João

2017-11-01

In this paper we present a novel method to identify and characterize stellar clusters deeply embedded in a dark molecular cloud. The method is based on measuring stellar surface density in wide-field infrared images using star counting techniques. It takes advantage of the differing H-band luminosity functions (HLFs) of field stars and young stellar populations and is able to statistically associate each star in an image as a member of either the background stellar population or a young stellar population projected on or near the cloud. Moreover, the technique corrects for the effects of differential extinction toward each individual star. We have tested this method against simulations as well as observations. In particular, we have applied the method to 2MASS point sources observed in the Orion A and B complexes, and the results obtained compare very well with those obtained from deep Spitzer and Chandra observations where presence of infrared excess or X-ray emission directly determines membership status for every star. Additionally, our method also identifies unobscured clusters and a low resolution version of the Orion stellar surface density map shows clearly the relatively unobscured and diffuse OB 1a and 1b sub-groups and provides useful insights on their spatial distribution.

Metric Optimization for Surface Analysis in the Laplace-Beltrami Embedding Space

PubMed Central

Lai, Rongjie; Wang, Danny J.J.; Pelletier, Daniel; Mohr, David; Sicotte, Nancy; Toga, Arthur W.

2014-01-01

In this paper we present a novel approach for the intrinsic mapping of anatomical surfaces and its application in brain mapping research. Using the Laplace-Beltrami eigen-system, we represent each surface with an isometry invariant embedding in a high dimensional space. The key idea in our system is that we realize surface deformation in the embedding space via the iterative optimization of a conformal metric without explicitly perturbing the surface or its embedding. By minimizing a distance measure in the embedding space with metric optimization, our method generates a conformal map directly between surfaces with highly uniform metric distortion and the ability of aligning salient geometric features. Besides pairwise surface maps, we also extend the metric optimization approach for group-wise atlas construction and multi-atlas cortical label fusion. In experimental results, we demonstrate the robustness and generality of our method by applying it to map both cortical and hippocampal surfaces in population studies. For cortical labeling, our method achieves excellent performance in a cross-validation experiment with 40 manually labeled surfaces, and successfully models localized brain development in a pediatric study of 80 subjects. For hippocampal mapping, our method produces much more significant results than two popular tools on a multiple sclerosis study of 109 subjects. PMID:24686245

Near infrared photometric and optical spectroscopic study of 22 low mass star clusters embedded in nebulae

NASA Astrophysics Data System (ADS)

Soares, J. B.; Bica, E.; Ahumada, A. V.; Clariá, J. J.

2008-02-01

Aims:Among the star clusters in the Galaxy, those embedded in nebulae represent the youngest group, which has only recently been explored. The analysis of a sample of 22 candidate embedded stellar systems in reflection nebulae and/or HII environments is presented. Methods: We employed optical spectroscopic observations of stars in the directions of the clusters carried out at CASLEO (Argentina) together with near infrared photometry from the 2MASS catalogue. Our analysis is based on source surface density, colour-colour diagrams and on theoretical pre-main sequence isochrones. We take into account the field star contamination by carrying out a statistical subtraction. Results: The studied objects have the characteristics of low mass systems. We derive their fundamental parameters. Most of the cluster ages are younger than 2 Myr. The studied embedded stellar systems in reflection nebulae and/or HII region complexes do not have stars of spectral types earlier than B. The total stellar masses locked in the clusters are in the range 20-220 M⊙. They are found to be gravitationally unstable and are expected to dissolve in a timescale of a few Myr. Based on observations made at Complejo Astronómico El Leoncito, which is operated under agreement between the Consejo Nacional de Investigaciones Científicas y Técnicas de la República Argentina and the National Universities of La Plata, Córdoba and San Juan, Argentina.

LC Circuits for Diagnosing Embedded Piezoelectric Devices

NASA Technical Reports Server (NTRS)

Chattin, Richard L.; Fox, Robert Lee; Moses, Robert W.; Shams, Qamar A.

2005-01-01

A recently invented method of nonintrusively detecting faults in piezoelectric devices involves measurement of the resonance frequencies of inductor capacitor (LC) resonant circuits. The method is intended especially to enable diagnosis of piezoelectric sensors, actuators, and sensor/actuators that are embedded in structures and/or are components of multilayer composite material structures.

Effectiveness of xenogenous-based bovine-derived platelet gel embedded within a three-dimensional collagen implant on the healing and regeneration of the Achilles tendon defect in rabbits

PubMed Central

Moshiri, Ali; Oryan, Ahmad; Meimandi-Parizi, Abdolhamid; Koohi-Hosseinabadi, Omid

2014-01-01

Background and objective: Tissue engineering is an option in reconstructing large tendon defects and managing their healing and regeneration. We designed and produced a novel xenogeneic-based bovine platelet, embedded it within a tissue-engineered collagen implant (CI) and applied it in an experimentally induced large tendon defect model in rabbits to test whether bovine platelets could stimulate tendon healing and regeneration in vivo. Methods: One hundred twenty rabbits were randomly divided into two experimental and pilot groups. In all the animals, the left Achilles tendon was surgically excised and the tendon edges were aligned by Kessler suture. Each group was then divided into three groups of control (no implant), treated with CI and treated with collagen-platelet implant. The pilot groups were euthanized at 10, 15, 30 and 40 days post-injury (DPI), and their gross and histologic characteristics were evaluated to study host–graft interaction mechanism. To study the tendon healing and its outcome, the experimental animals were tested during the experiment using hematologic, ultrasonographic and various methods of clinical examinations and then euthanized at 60 DPI and their tendons were evaluated by gross pathologic, histopathologic, scanning electron microscopic, biophysical and biochemical methods. Results: Bovine platelets embedded within a CI increased inflammation at short term while it increased the rate of implant absorption and matrix replacement compared with the controls and CI alone. Treatment also significantly increased diameter, density, amount, alignment and differentiation of the collagen fibrils and fibers and approximated the water uptake and delivery behavior of the healing tendons to normal contralaterals (p < 0.05). Treatment also improved echogenicity and homogenicity of the tendons and reduced peritendinous adhesion, muscle fibrosis and atrophy, and therefore, it improved the clinical scores and physical activity related to the injured limb when compared with the controls (p < 0.05). Conclusion: The bovine platelet gel embedded within the tissue-engineered CI was effective in healing, modeling and remodeling of the Achilles tendon in rabbit. This strategy may be a valuable option in the clinical setting. PMID:24840092

Dimension from covariance matrices.

PubMed

Carroll, T L; Byers, J M

2017-02-01

We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.

High-speed event detector for embedded nanopore bio-systems.

PubMed

Huang, Yiyun; Magierowski, Sebastian; Ghafar-Zadeh, Ebrahim; Wang, Chengjie

2015-08-01

Biological measurements of microscopic phenomena often deal with discrete-event signals. The ability to automatically carry out such measurements at high-speed in a miniature embedded system is desirable but compromised by high-frequency noise along with practical constraints on filter quality and sampler resolution. This paper presents a real-time event-detection method in the context of nanopore sensing that helps to mitigate these drawbacks and allows accurate signal processing in an embedded system. Simulations show at least a 10× improvement over existing on-line detection methods.

A New Method of Facial Expression Recognition Based on SPE Plus SVM

NASA Astrophysics Data System (ADS)

Ying, Zilu; Huang, Mingwei; Wang, Zhen; Wang, Zhewei

A novel method of facial expression recognition (FER) is presented, which uses stochastic proximity embedding (SPE) for data dimension reduction, and support vector machine (SVM) for expression classification. The proposed algorithm is applied to Japanese Female Facial Expression (JAFFE) database for FER, better performance is obtained compared with some traditional algorithms, such as PCA and LDA etc.. The result have further proved the effectiveness of the proposed algorithm.

Reverse-micelle-induced porous pressure-sensitive rubber for wearable human-machine interfaces.

PubMed

Jung, Sungmook; Kim, Ji Hoon; Kim, Jaemin; Choi, Suji; Lee, Jongsu; Park, Inhyuk; Hyeon, Taeghwan; Kim, Dae-Hyeong

2014-07-23

A novel method to produce porous pressure-sensitive rubber is developed. For the controlled size distribution of embedded micropores, solution-based procedures using reverse micelles are adopted. The piezosensitivity of the pressure sensitive rubber is significantly increased by introducing micropores. Using this method, wearable human-machine interfaces are fabricated, which can be applied to the remote control of a robot. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Activating articulation skills through theraplay.

PubMed

Kupperman, P; Bligh, S; Goodban, M

1980-11-01

Speech Theraplay, a method of remediation for children with articulation disorders, is described. The approach is based on parent-child interactions that are postulated to activate articulation acquisition. These interactions between parent and child were duplicated and intensified in the clinical setting. Target phonemes were embedded into spontaneous interactive play, both in isolation and in meaningful exchange. The results of a six-week study indicate improvement in the articulation abilities of six children with this method.

Cell Kinetic and Histomorphometric Analysis of Microgravitational Osteopenia: PARE.03B

NASA Technical Reports Server (NTRS)

Roberts, W. Eugene; Garetto, Lawrence P.

1998-01-01

Previous methods of identifying cells undergoing DNA synthesis (S-phase) utilized H-3 thymidine (3HT) autoradiography. 5-Bromo-2'-deoxyuridine (BrdU) immunohistochemistry is a nonradioactive alternative method. This experiment compared the two methods using the nuclear volume model for osteoblast histogenesis in two different embedding media. Twenty Sprague-Dawley rats were used, with half receiving 3HT (1 micro Ci/g) and the other half BrdU (50 microgram/g). Condyies were embedded (one side in paraffin, the other in plastic) and S-phase nuclei were identified using either autoradiography or immunohistochemistry. The fractional distribution of preosteoblast cell types and the percentage of labeled cells (within each cell fraction and label index) were calculated and expressed as mean q standard error. Chi-Square analysis showed only a minor difference in the fractional distribution of cell types. However, there were significant differences (p less than 0.05) by ANOVA, in the nuclear labeling of specific cell types. With the exception of the less-differentiated A+A'cells, more BrdU label was consistently detected in paraffin than in plastic-embedded sections. In general, more nuclei were labeled with 3H-thymidine than with BrdU in both types of embedding media. Labeling index data (labeled cells/total cells sampled x 100) indicated that BrdU in paraffin, but not plastic gave the same results as 3HT in either embedding method. Thus, we conclude that the two labeling methods do not yield the same results for the nuclear volume model and that embedding media is an important factor whenusing BrdU. As a result of this work, 3HT was chosen for used in the PARE.03 flight experiments.

Application of the FICTION technique for the simultaneous detection of immunophenotype and chromosomal abnormalities in routinely fixed, paraffin wax embedded bone marrow trephines

PubMed Central

Korać, P; Jones, M; Dominis, M; Kušec, R; Mason, D Y; Banham, A H; Ventura, R A

2005-01-01

The use of interphase fluorescence in situ hybridisation (FISH) to study cytogenetic abnormalities in routinely fixed paraffin wax embedded tissue has become commonplace over the past decade. However, very few studies have applied FISH to routinely fixed bone marrow trephines (BMTs). This may be because of the acid based decalcification methods that are commonly used during the processing of BMTs, which may adversely affect the suitability of the sample for FISH analysis. For the first time, this report describes the simultaneous application of FISH and immunofluorescent staining (the FICTION technique) to formalin fixed, EDTA decalcified and paraffin wax embedded BMTs. This technique allows the direct correlation of genetic abnormalities to immunophenotype, and therefore will be particularly useful for the identification of genetic abnormalities in specific tumour cells present in BMTs. The application of this to routine clinical practice will assist diagnosis and the detection of minimal residual disease. PMID:16311361

Antimicrobial polycaprolactone/polyethylene glycol embedded lysozyme coatings of Ti implants for osteoblast functional properties in tissue engineering

NASA Astrophysics Data System (ADS)

Visan, A.; Cristescu, R.; Stefan, N.; Miroiu, M.; Nita, C.; Socol, M.; Florica, C.; Rasoga, O.; Zgura, I.; Sima, L. E.; Chiritoiu, M.; Chifiriuc, M. C.; Holban, A. M.; Mihailescu, I. N.; Socol, G.

2017-09-01

In this study, coatings based on lysozyme embedded into a matrix of polyethylene glycol (PEG) and polycaprolactone (PCL) were fabricated by two different methods (Matrix Assisted Pulsed Laser Evaporation - MAPLE and Dip Coating) for obtaining antimicrobial coatings envisaged for long term medical applications. Coatings with different PEG:PCL compositions (3:1; 1:1; 1:3) were synthesized in order to evaluate the antimicrobial activity of lysozyme embedded into the polymeric matrix. The main surface features, such as roughness and wettability, with impact on the microbial adhesion as well as on the eukaryote cell function were measured. The obtained composite coatings exhibited a significant antibacterial activity against Escherichia coli, Bacillus subtilis, Enterococcus faecalis and Staphylococcus aureus strains. As well, specific blended coatings showed appropriate viability, good spreading and normal cell morphology of SaOs2 human osteoblasts and mesenchymal stem cells (MSCs). These investigations highlight the suitability of biodegradable composites as implant coatings for decreasing the risk of bacterial contamination associated with prosthetic procedures.

Nonlinear Prediction As A Tool For Determining Parameters For Phase Space Reconstruction In Meteorology

NASA Astrophysics Data System (ADS)

Miksovsky, J.; Raidl, A.

Time delays phase space reconstruction represents one of useful tools of nonlinear time series analysis, enabling number of applications. Its utilization requires the value of time delay to be known, as well as the value of embedding dimension. There are sev- eral methods how to estimate both these parameters. Typically, time delay is computed first, followed by embedding dimension. Our presented approach is slightly different - we reconstructed phase space for various combinations of mentioned parameters and used it for prediction by means of the nearest neighbours in the phase space. Then some measure of prediction's success was computed (correlation or RMSE, e.g.). The position of its global maximum (minimum) should indicate the suitable combination of time delay and embedding dimension. Several meteorological (particularly clima- tological) time series were used for the computations. We have also created a MS- Windows based program in order to implement this approach - its basic features will be presented as well.

Siblings of Children with Autism: the Siblings Embedded Systems Framework.

PubMed

Kovshoff, Hanna; Cebula, Katie; Tsai, Hsiao-Wei Joy; Hastings, Richard P

2017-01-01

A range of interacting factors/mechanisms at the individual, family, and wider systems levels influences siblings living in families where one sibling has autism. We introduce the Sibling Embedded Systems Framework which aims to contextualise siblings' experience and characterise the multiple and interacting factors influencing family and, in particular, sibling outcomes. Findings from studies that have reported outcomes for siblings of children with autism are equivocal, ranging from negative impact, no difference, to positive experience. This is likely due to the complex nature of understanding the sibling experience. We focus on particular elements of the framework and review recent novel literature to help guide future directions for research and practice including the influence of culture, methodological considerations, and wider participatory methods. The Siblings Embedded System Framework can be used to understand interactive factors that affect sibling adjustment and to develop clinically, educationally and empirically based work that aims to enhance and support sibling adjustment, relationships, and well-being in families of children with autism.

Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera

NASA Astrophysics Data System (ADS)

Dziri, Aziz; Duranton, Marc; Chapuis, Roland

2016-07-01

Multiple-object tracking constitutes a major step in several computer vision applications, such as surveillance, advanced driver assistance systems, and automatic traffic monitoring. Because of the number of cameras used to cover a large area, these applications are constrained by the cost of each node, the power consumption, the robustness of the tracking, the processing time, and the ease of deployment of the system. To meet these challenges, the use of low-power and low-cost embedded vision platforms to achieve reliable tracking becomes essential in networks of cameras. We propose a tracking pipeline that is designed for fixed smart cameras and which can handle occlusions between objects. We show that the proposed pipeline reaches real-time processing on a low-cost embedded smart camera composed of a Raspberry-Pi board and a RaspiCam camera. The tracking quality and the processing speed obtained with the proposed pipeline are evaluated on publicly available datasets and compared to the state-of-the-art methods.

Steganography based on pixel intensity value decomposition

NASA Astrophysics Data System (ADS)

Abdulla, Alan Anwar; Sellahewa, Harin; Jassim, Sabah A.

2014-05-01

This paper focuses on steganography based on pixel intensity value decomposition. A number of existing schemes such as binary, Fibonacci, Prime, Natural, Lucas, and Catalan-Fibonacci (CF) are evaluated in terms of payload capacity and stego quality. A new technique based on a specific representation is proposed to decompose pixel intensity values into 16 (virtual) bit-planes suitable for embedding purposes. The proposed decomposition has a desirable property whereby the sum of all bit-planes does not exceed the maximum pixel intensity value, i.e. 255. Experimental results demonstrate that the proposed technique offers an effective compromise between payload capacity and stego quality of existing embedding techniques based on pixel intensity value decomposition. Its capacity is equal to that of binary and Lucas, while it offers a higher capacity than Fibonacci, Prime, Natural, and CF when the secret bits are embedded in 1st Least Significant Bit (LSB). When the secret bits are embedded in higher bit-planes, i.e., 2nd LSB to 8th Most Significant Bit (MSB), the proposed scheme has more capacity than Natural numbers based embedding. However, from the 6th bit-plane onwards, the proposed scheme offers better stego quality. In general, the proposed decomposition scheme has less effect in terms of quality on pixel value when compared to most existing pixel intensity value decomposition techniques when embedding messages in higher bit-planes.

Rule based design of conceptual models for formative evaluation

NASA Technical Reports Server (NTRS)

Moore, Loretta A.; Chang, Kai; Hale, Joseph P.; Bester, Terri; Rix, Thomas; Wang, Yaowen

1994-01-01

A Human-Computer Interface (HCI) Prototyping Environment with embedded evaluation capability has been investigated. This environment will be valuable in developing and refining HCI standards and evaluating program/project interface development, especially Space Station Freedom on-board displays for payload operations. This environment, which allows for rapid prototyping and evaluation of graphical interfaces, includes the following four components: (1) a HCI development tool; (2) a low fidelity simulator development tool; (3) a dynamic, interactive interface between the HCI and the simulator; and (4) an embedded evaluator that evaluates the adequacy of a HCI based on a user's performance. The embedded evaluation tool collects data while the user is interacting with the system and evaluates the adequacy of an interface based on a user's performance. This paper describes the design of conceptual models for the embedded evaluation system using a rule-based approach.

Rule based design of conceptual models for formative evaluation

NASA Technical Reports Server (NTRS)

Moore, Loretta A.; Chang, Kai; Hale, Joseph P.; Bester, Terri; Rix, Thomas; Wang, Yaowen

1994-01-01

A Human-Computer Interface (HCI) Prototyping Environment with embedded evaluation capability has been investigated. This environment will be valuable in developing and refining HCI standards and evaluating program/project interface development, especially Space Station Freedom on-board displays for payload operations. This environment, which allows for rapid prototyping and evaluation of graphical interfaces, includes the following four components: (1) a HCI development tool, (2) a low fidelity simulator development tool, (3) a dynamic, interactive interface between the HCI and the simulator, and (4) an embedded evaluator that evaluates the adequacy of a HCI based on a user's performance. The embedded evaluation tool collects data while the user is interacting with the system and evaluates the adequacy of an interface based on a user's performance. This paper describes the design of conceptual models for the embedded evaluation system using a rule-based approach.

A telepresence robot system realized by embedded object concept

NASA Astrophysics Data System (ADS)

Vallius, Tero; Röning, Juha

2006-10-01

This paper presents the Embedded Object Concept (EOC) and a telepresence robot system which is a test case for the EOC. The EOC utilizes common object-oriented methods used in software by applying them to combined Lego-like software-hardware entities. These entities represent objects in object-oriented design methods, and they are the building blocks of embedded systems. The goal of the EOC is to make the designing embedded systems faster and easier. This concept enables people without comprehensive knowledge in electronics design to create new embedded systems, and for experts it shortens the design time of new embedded systems. We present the current status of a telepresence robot created with second-generation Atomi-objects, which is the name for our implementation of the embedded objects. The telepresence robot is a relatively complex test case for the EOC. The robot has been constructed using incremental device development, which is made possible by the architecture of the EOC. The robot contains video and audio exchange capability and a controlling system for driving with two wheels. The robot is built in two versions, the first consisting of a PC device and Atomi-objects, and the second consisting of only Atomi-objects. The robot is currently incomplete, but most of it has been successfully tested.

A hardware-in-the-loop simulation program for ground-based radar

NASA Astrophysics Data System (ADS)

Lam, Eric P.; Black, Dennis W.; Ebisu, Jason S.; Magallon, Julianna

2011-06-01

A radar system created using an embedded computer system needs testing. The way to test an embedded computer system is different from the debugging approaches used on desktop computers. One way to test a radar system is to feed it artificial inputs and analyze the outputs of the radar. More often, not all of the building blocks of the radar system are available to test. This will require the engineer to test parts of the radar system using a "black box" approach. A common way to test software code on a desktop simulation is to use breakpoints so that is pauses after each cycle through its calculations. The outputs are compared against the values that are expected. This requires the engineer to use valid test scenarios. We will present a hardware-in-the-loop simulator that allows the embedded system to think it is operating with real-world inputs and outputs. From the embedded system's point of view, it is operating in real-time. The hardware in the loop simulation is based on our Desktop PC Simulation (PCS) testbed. In the past, PCS was used for ground-based radars. This embedded simulation, called Embedded PCS, allows a rapid simulated evaluation of ground-based radar performance in a laboratory environment.

Light Weight MP3 Watermarking Method for Mobile Terminals

NASA Astrophysics Data System (ADS)

Takagi, Koichi; Sakazawa, Shigeyuki; Takishima, Yasuhiro

This paper proposes a novel MP3 watermarking method which is applicable to a mobile terminal with limited computational resources. Considering that in most cases the embedded information is copyright information or metadata, which should be extracted before playing back audio contents, the watermark detection process should be executed at high speed. However, when conventional methods are used with a mobile terminal, it takes a considerable amount of time to detect a digital watermark. This paper focuses on scalefactor manipulation to enable high speed watermark embedding/detection for MP3 audio and also proposes the manipulation method which minimizes audio quality degradation adaptively. Evaluation tests showed that the proposed method is capable of embedding 3 bits/frame information without degrading audio quality and detecting it at very high speed. Finally, this paper describes application examples for authentication with a digital signature.

Tensor Train Neighborhood Preserving Embedding

NASA Astrophysics Data System (ADS)

Wang, Wenqi; Aggarwal, Vaneet; Aeron, Shuchin

2018-05-01

In this paper, we propose a Tensor Train Neighborhood Preserving Embedding (TTNPE) to embed multi-dimensional tensor data into low dimensional tensor subspace. Novel approaches to solve the optimization problem in TTNPE are proposed. For this embedding, we evaluate novel trade-off gain among classification, computation, and dimensionality reduction (storage) for supervised learning. It is shown that compared to the state-of-the-arts tensor embedding methods, TTNPE achieves superior trade-off in classification, computation, and dimensionality reduction in MNIST handwritten digits and Weizmann face datasets.

Multispectral embedding-based deep neural network for three-dimensional human pose recovery

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng

2018-01-01

Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

Locating damage using integrated global-local approach with wireless sensing system and single-chip impedance measurement device.

PubMed

Lin, Tzu-Hsuan; Lu, Yung-Chi; Hung, Shih-Lin

2014-01-01

This study developed an integrated global-local approach for locating damage on building structures. A damage detection approach with a novel embedded frequency response function damage index (NEFDI) was proposed and embedded in the Imote2.NET-based wireless structural health monitoring (SHM) system to locate global damage. Local damage is then identified using an electromechanical impedance- (EMI-) based damage detection method. The electromechanical impedance was measured using a single-chip impedance measurement device which has the advantages of small size, low cost, and portability. The feasibility of the proposed damage detection scheme was studied with reference to a numerical example of a six-storey shear plane frame structure and a small-scale experimental steel frame. Numerical and experimental analysis using the integrated global-local SHM approach reveals that, after NEFDI indicates the approximate location of a damaged area, the EMI-based damage detection approach can then identify the detailed damage location in the structure of the building.

Initial Noise Assessment of an Embedded-wing-propulsion Concept Vehicle

NASA Technical Reports Server (NTRS)

Stone, James R.; Krejsa, Eugene A.

2008-01-01

Vehicle acoustic requirements are considered for a Cruise-Efficient Short Take-Off and Landing (CESTOL) vehicle concept using an Embedded-Wing-Propulsion (EWP) system based on a review of the literature. Successful development of such vehicles would enable more efficient use of existing airports in accommodating the anticipated growth in air traffic while at the same time reducing the noise impact on the community around the airport. A noise prediction capability for CESTOL-EWP aircraft is developed, based largely on NASA's FOOTPR code and other published methods, with new relations for high aspect ratio slot nozzles and wing shielding. The predictive model is applied to a preliminary concept developed by Boeing for NASA GRC. Significant noise reduction for such an aircraft relative to the current state-of-the-art is predicted, and technology issues are identified which should be addressed to assure that the potential of this design concept is fully achieved with minimum technical risk.

A blind dual color images watermarking based on IWT and state coding

NASA Astrophysics Data System (ADS)

Su, Qingtang; Niu, Yugang; Liu, Xianxi; Zhu, Yu

2012-04-01

In this paper, a state-coding based blind watermarking algorithm is proposed to embed color image watermark to color host image. The technique of state coding, which makes the state code of data set be equal to the hiding watermark information, is introduced in this paper. When embedding watermark, using Integer Wavelet Transform (IWT) and the rules of state coding, these components, R, G and B, of color image watermark are embedded to these components, Y, Cr and Cb, of color host image. Moreover, the rules of state coding are also used to extract watermark from the watermarked image without resorting to the original watermark or original host image. Experimental results show that the proposed watermarking algorithm cannot only meet the demand on invisibility and robustness of the watermark, but also have well performance compared with other proposed methods considered in this work.

Hardware/software codesign for embedded RISC core

NASA Astrophysics Data System (ADS)

Liu, Peng

2001-12-01

This paper describes hardware/software codesign method of the extendible embedded RISC core VIRGO, which based on MIPS-I instruction set architecture. VIRGO is described by Verilog hardware description language that has five-stage pipeline with shared 32-bit cache/memory interface, and it is controlled by distributed control scheme. Every pipeline stage has one small controller, which controls the pipeline stage status and cooperation among the pipeline phase. Since description use high level language and structure is distributed, VIRGO core has highly extension that can meet the requirements of application. We take look at the high-definition television MPEG2 MPHL decoder chip, constructed the hardware/software codesign virtual prototyping machine that can research on VIRGO core instruction set architecture, and system on chip memory size requirements, and system on chip software, etc. We also can evaluate the system on chip design and RISC instruction set based on the virtual prototyping machine platform.

Coupled binary embedding for large-scale image retrieval.

PubMed

Zheng, Liang; Wang, Shengjin; Tian, Qi

2014-08-01

Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts.

Histological methods to determine blood flow distribution with fluorescent microspheres.

PubMed

Luchtel, D L; Boykin, J C; Bernard, S L; Glenny, R W

1998-11-01

We evaluated several histological methods and determined their advantages and disadvantages for histological studies of tissues and organs perfused with fluorescent microspheres. Microspheres retained their fluorescence in 7-10 microm serial sections with a change in the antimedium from toluene when samples were fixed in formalin and embedded in paraffin. Several antimedia allowed both wax infiltration of tissue and preservation of microsphere fluorescence. Histoclear II was the best substitute for toluene. When samples were fixed in formalin and embedded in glycol methacrylate, thinner (3-5 microm) sections provided greater histological detail but had fewer microspheres per section. Air dried lung tissue followed by Vibratome sectioning provided thick sections (100 microm) that facilitated rapid survey of large volumes of tissue for microspheres but limited histological detail, and the air drying procedure was restricted to lung tissue. Samples fixed in formalin followed by Vibratome sectioning of unembedded tissue provided better histological detail of lung tissue and was also useful for other organs. These sections were more difficult to handle and to mount on slides compared to air dried tissue, whereas fixed tissue embedded in gelatin provided better tissue support for Vibratome sectioning. Rapid freezing followed by cryo-microtome sectioning resulted in frozen sections that were relatively difficult to handle compared to embedded or unembedded tissue; they also deteriorated relatively rapidly with time. Paraffin sections were stained with hematoxylin and eosin or with aqueous methyl green, although tissue autofluorescence by itself was usually sufficient to identify histological features. Methacrylate sections quenched tissue autofluorescence, and Lee's stain or Richardson's stain were used for staining sections. Toluene based mountants such as Cytoseal quenched fluorescence, particularly the red fluorescent microspheres. Aqueous based mountants such as Aquamount, Crystal/Mount, Fluoromount-G were substituted, although such preparations were not as permanent as Cytoseal mounted coverglasses and tended to cause fading of stained sections.

Effect of Age on Complexity and Causality of the Cardiovascular Control: Comparison between Model-Based and Model-Free Approaches

PubMed Central

Porta, Alberto; Faes, Luca; Bari, Vlasta; Marchi, Andrea; Bassani, Tito; Nollo, Giandomenico; Perseguini, Natália Maria; Milan, Juliana; Minatel, Vinícius; Borghi-Silva, Audrey; Takahashi, Anielle C. M.; Catai, Aparecida M.

2014-01-01

The proposed approach evaluates complexity of the cardiovascular control and causality among cardiovascular regulatory mechanisms from spontaneous variability of heart period (HP), systolic arterial pressure (SAP) and respiration (RESP). It relies on construction of a multivariate embedding space, optimization of the embedding dimension and a procedure allowing the selection of the components most suitable to form the multivariate embedding space. Moreover, it allows the comparison between linear model-based (MB) and nonlinear model-free (MF) techniques and between MF approaches exploiting local predictability (LP) and conditional entropy (CE). The framework was applied to study age-related modifications of complexity and causality in healthy humans in supine resting (REST) and during standing (STAND). We found that: 1) MF approaches are more efficient than the MB method when nonlinear components are present, while the reverse situation holds in presence of high dimensional embedding spaces; 2) the CE method is the least powerful in detecting age-related trends; 3) the association of HP complexity on age suggests an impairment of cardiac regulation and response to STAND; 4) the relation of SAP complexity on age indicates a gradual increase of sympathetic activity and a reduced responsiveness of vasomotor control to STAND; 5) the association from SAP to HP on age during STAND reveals a progressive inefficiency of baroreflex; 6) the reduced connection from HP to SAP with age might be linked to the progressive exploitation of Frank-Starling mechanism at REST and to the progressive increase of peripheral resistances during STAND; 7) at REST the diminished association from RESP to HP with age suggests a vagal withdrawal and a gradual uncoupling between respiratory activity and heart; 8) the weakened connection from RESP to SAP with age might be related to the progressive increase of left ventricular thickness and vascular stiffness and to the gradual decrease of respiratory sinus arrhythmia. PMID:24586796

An embedded laser marking controller based on ARM and FPGA processors.

PubMed

Dongyun, Wang; Xinpiao, Ye

2014-01-01

Laser marking is an important branch of the laser information processing technology. The existing laser marking machine based on PC and WINDOWS operating system, are large and inconvenient to move. Still, it cannot work outdoors or in other harsh environments. In order to compensate for the above mentioned disadvantages, this paper proposed an embedded laser marking controller based on ARM and FPGA processors. Based on the principle of laser galvanometer scanning marking, the hardware and software were designed for the application. Experiments showed that this new embedded laser marking controller controls the galvanometers synchronously and could achieve precise marking.

A self-consistent density based embedding scheme applied to the adsorption of CO on Pd(111)

NASA Astrophysics Data System (ADS)

Lahav, D.; Klüner, T.

2007-06-01

We derive a variant of a density based embedded cluster approach as an improvement to a recently proposed embedding theory for metallic substrates (Govind et al 1999 J. Chem. Phys. 110 7677; Klüner et al 2001 Phys. Rev. Lett. 86 5954). In this scheme, a local region in space is represented by a small cluster which is treated by accurate quantum chemical methodology. The interaction of the cluster with the infinite solid is taken into account by an effective one-electron embedding operator representing the surrounding region. We propose a self-consistent embedding scheme which resolves intrinsic problems of the former theory, in particular a violation of strict density conservation. The proposed scheme is applied to the well-known benchmark system CO/Pd(111).

An embedded stress sensor for concrete SHM based on amorphous ferromagnetic microwires.

PubMed

Olivera, Jesús; González, Margarita; Fuente, José Vicente; Varga, Rastislav; Zhukov, Arkady; Anaya, José Javier

2014-10-24

A new smart concrete aggregate design as a candidate for applications in structural health monitoring (SHM) of critical elements in civil infrastructure is proposed. The cement-based stress/strain sensor was developed by utilizing the stress/strain sensing properties of a magnetic microwire embedded in cement-based composite (MMCC). This is a contact-less type sensor that measures variations of magnetic properties resulting from stress variations. Sensors made of these materials can be designed to satisfy the specific demand for an economic way to monitor concrete infrastructure health. For this purpose, we embedded a thin magnetic microwire in the core of a cement-based cylinder, which was inserted into the concrete specimen under study as an extra aggregate. The experimental results show that the embedded MMCC sensor is capable of measuring internal compressive stress around the range of 1-30 MPa. Two stress sensing properties of the embedded sensor under uniaxial compression were studied: the peak amplitude and peak position of magnetic switching field. The sensitivity values for the amplitude and position within the measured range were 5 mV/MPa and 2.5 µs/MPa, respectively.

Biological Embedding: Evaluation and Analysis of an Emerging Concept for Nursing Scholarship

PubMed Central

Nist, Marliese Dion

2016-01-01

Aim The purpose of this paper is to report the analysis of the concept of biological embedding. Background Research that incorporates a life course perspective is becoming increasingly prominent in the health sciences. Biological embedding is a central concept in life course theory and may be important for nursing theories to enhance our understanding of health states in individuals and populations. Before the concept of biological embedding can be used in nursing theory and research, an analysis of the concept is required to advance it toward full maturity. Design Concept analysis. Data Sources PubMed, CINAHL and PsycINFO were searched for publications using the term ‘biological embedding’ or ‘biological programming’ and published through 2015. Methods An evaluation of the concept was first conducted to determine the concept’s level of maturity and was followed by a concept comparison, using the methods for concept evaluation and comparison described by Morse. Results A consistent definition of biological embedding – the process by which early life experience alters biological processes to affect adult health outcomes – was found throughout the literature. The concept has been used in several theories that describe the mechanisms through which biological embedding might occur and highlight its role in the development of health trajectories. Biological embedding is a partially mature concept, requiring concept comparison with an overlapping concept – biological programming – to more clearly establish the boundaries of biological embedding. Conclusions Biological embedding has significant potential for theory development and application in multiple academic disciplines, including nursing. PMID:27682606

Numerical computation of diffusion on a surface.

PubMed

Schwartz, Peter; Adalsteinsson, David; Colella, Phillip; Arkin, Adam Paul; Onsum, Matthew

2005-08-09

We present a numerical method for computing diffusive transport on a surface derived from image data. Our underlying discretization method uses a Cartesian grid embedded boundary method for computing the volume transport in a region consisting of all points a small distance from the surface. We obtain a representation of this region from image data by using a front propagation computation based on level set methods for solving the Hamilton-Jacobi and eikonal equations. We demonstrate that the method is second-order accurate in space and time and is capable of computing solutions on complex surface geometries obtained from image data of cells.

Glycogen in the Nervous System. I; Methods for Light and Electron Microscopy

NASA Technical Reports Server (NTRS)

Estable, Rosita F. De; Estable-Puig, J. F.; Miquel, J.

1964-01-01

'l'he relative value of different methods for combined light and electron microscopical studies of glycogen in the nervous tissue was investigated. Picroalcoholic fixatives preserve glycogen in a considerable amount but give an inadequate morphological image of glycogen distribution and are unsuitable for ultrastructural studies. Fixation by perfusion, with Dalton's chromeosmic fluid seems adequate for ultrastructural cytochemistry of glycogen. Furthermore it permits routine paraffin embedding of brain slices adjacent to those used for electron microscopy. Dimedone blocking is a necessary step for a selective staining of glycogen with PAS after osmic fixation. Enzymatic removal of glycogen in osmic fixed nervous tissue can be done In paraffin-embedded tissue. It can also be performed in glycolmethacrylate-embedded tissue without removal of the embedding medium. Paraphenylenediamine stains glycogen following periodic acid oxidation.

A Comparative Study of Sample Preparation for Staining and Immunodetection of Plant Cell Walls by Light Microscopy

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

Verhertbruggen, Yves; Walker, Jesse L.; Guillon, Fabienne

Staining and immunodetection by light microscopy are methods widely used to investigate plant cell walls. The two techniques have been crucial to study the cell wall architecture in planta, its deconstruction by chemicals or cell wall-degrading enzymes. They have been instrumental in detecting the presence of cell types, in deciphering plant cell wall evolution and in characterizing plant mutants and transformants. The success of immunolabeling relies on how plant materials are embedded and sectioned. Agarose coating, wax and resin embedding are, respectively, associated with vibratome, microtome and ultramicrotome sectioning. Here, we have systematically carried out a comparative analysis of thesemore » three methods of sample preparation when they are applied for cell wall staining and cell wall immunomicroscopy. In order to help the plant community in understanding and selecting adequate methods of embedding and sectioning for cell wall immunodetection, we review in this article the advantages and limitations of these three methods. Moreover, we offer detailed protocols of embedding for studying plant materials through microscopy.« less

A Comparative Study of Sample Preparation for Staining and Immunodetection of Plant Cell Walls by Light Microscopy

DOE PAGES

Verhertbruggen, Yves; Walker, Jesse L.; Guillon, Fabienne; ...

2017-08-29

Staining and immunodetection by light microscopy are methods widely used to investigate plant cell walls. The two techniques have been crucial to study the cell wall architecture in planta, its deconstruction by chemicals or cell wall-degrading enzymes. They have been instrumental in detecting the presence of cell types, in deciphering plant cell wall evolution and in characterizing plant mutants and transformants. The success of immunolabeling relies on how plant materials are embedded and sectioned. Agarose coating, wax and resin embedding are, respectively, associated with vibratome, microtome and ultramicrotome sectioning. Here, we have systematically carried out a comparative analysis of thesemore » three methods of sample preparation when they are applied for cell wall staining and cell wall immunomicroscopy. In order to help the plant community in understanding and selecting adequate methods of embedding and sectioning for cell wall immunodetection, we review in this article the advantages and limitations of these three methods. Moreover, we offer detailed protocols of embedding for studying plant materials through microscopy.« less

A Comparative Study of Sample Preparation for Staining and Immunodetection of Plant Cell Walls by Light Microscopy

PubMed Central

Verhertbruggen, Yves; Walker, Jesse L.; Guillon, Fabienne; Scheller, Henrik V.

2017-01-01

Staining and immunodetection by light microscopy are methods widely used to investigate plant cell walls. The two techniques have been crucial to study the cell wall architecture in planta, its deconstruction by chemicals or cell wall-degrading enzymes. They have been instrumental in detecting the presence of cell types, in deciphering plant cell wall evolution and in characterizing plant mutants and transformants. The success of immunolabeling relies on how plant materials are embedded and sectioned. Agarose coating, wax and resin embedding are, respectively, associated with vibratome, microtome and ultramicrotome sectioning. Here, we have systematically carried out a comparative analysis of these three methods of sample preparation when they are applied for cell wall staining and cell wall immunomicroscopy. In order to help the plant community in understanding and selecting adequate methods of embedding and sectioning for cell wall immunodetection, we review in this article the advantages and limitations of these three methods. Moreover, we offer detailed protocols of embedding for studying plant materials through microscopy. PMID:28900439

Fracture Mechanics Method for Word Embedding Generation of Neural Probabilistic Linguistic Model.

PubMed

Bi, Size; Liang, Xiao; Huang, Ting-Lei

2016-01-01

Word embedding, a lexical vector representation generated via the neural linguistic model (NLM), is empirically demonstrated to be appropriate for improvement of the performance of traditional language model. However, the supreme dimensionality that is inherent in NLM contributes to the problems of hyperparameters and long-time training in modeling. Here, we propose a force-directed method to improve such problems for simplifying the generation of word embedding. In this framework, each word is assumed as a point in the real world; thus it can approximately simulate the physical movement following certain mechanics. To simulate the variation of meaning in phrases, we use the fracture mechanics to do the formation and breakdown of meaning combined by a 2-gram word group. With the experiments on the natural linguistic tasks of part-of-speech tagging, named entity recognition and semantic role labeling, the result demonstrated that the 2-dimensional word embedding can rival the word embeddings generated by classic NLMs, in terms of accuracy, recall, and text visualization.

Method for preparing hydrous titanium oxide spherules and other gel forms thereof

DOEpatents

Collins, J.L.

1998-10-13

The present invention are methods for preparing hydrous titanium oxide spherules, hydrous titanium oxide gels such as gel slabs, films, capillary and electrophoresis gels, titanium monohydrogen phosphate spherules, hydrous titanium oxide spherules having suspendible particles homogeneously embedded within to form a composite sorbent, titanium monohydrogen phosphate spherules having suspendible particles of at least one different sorbent homogeneously embedded within to form a composite sorbent having a desired crystallinity, titanium oxide spherules in the form of anatase, brookite or rutile, titanium oxide spherules having suspendible particles homogeneously embedded within to form a composite, hydrous titanium oxide fiber materials, titanium oxide fiber materials, hydrous titanium oxide fiber materials having suspendible particles homogeneously embedded within to form a composite, titanium oxide fiber materials having suspendible particles homogeneously embedded within to form a composite and spherules of barium titanate. These variations of hydrous titanium oxide spherules and gel forms prepared by the gel-sphere, internal gelation process offer more useful forms of inorganic ion exchangers, catalysts, getters and ceramics. 6 figs.

The Quality of the Embedding Potential Is Decisive for Minimal Quantum Region Size in Embedding Calculations: The Case of the Green Fluorescent Protein.

PubMed

Nåbo, Lina J; Olsen, Jógvan Magnus Haugaard; Martínez, Todd J; Kongsted, Jacob

2017-12-12

The calculation of spectral properties for photoactive proteins is challenging because of the large cost of electronic structure calculations on large systems. Mixed quantum mechanical (QM) and molecular mechanical (MM) methods are typically employed to make such calculations computationally tractable. This study addresses the connection between the minimal QM region size and the method used to model the MM region in the calculation of absorption properties-here exemplified for calculations on the green fluorescent protein. We find that polarizable embedding is necessary for a qualitatively correct description of the MM region, and that this enables the use of much smaller QM regions compared to fixed charge electrostatic embedding. Furthermore, absorption intensities converge very slowly with system size and inclusion of effective external field effects in the MM region through polarizabilities is therefore very important. Thus, this embedding scheme enables accurate prediction of intensities for systems that are too large to be treated fully quantum mechanically.

Method for preparing hydrous titanium oxide spherules and other gel forms thereof

DOEpatents

Collins, Jack L.

1998-01-01

The present invention are methods for preparing hydrous titanium oxide spherules, hydrous titanium oxide gels such as gel slabs, films, capillary and electrophoresis gels, titanium monohydrogen phosphate spherules, hydrous titanium oxide spherules having suspendible particles homogeneously embedded within to form a composite sorbent, titanium monohydrogen phosphate spherules having suspendible particles of at least one different sorbent homogeneously embedded within to form a composite sorbent having a desired crystallinity, titanium oxide spherules in the form of anatase, brookite or rutile, titanium oxide spherules having suspendible particles homogeneously embedded within to form a composite, hydrous titanium oxide fiber materials, titanium oxide fiber materials, hydrous titanium oxide fiber materials having suspendible particles homogeneously embedded within to form a composite, titanium oxide fiber materials having suspendible particles homogeneously embedded within to form a composite and spherules of barium titanate. These variations of hydrous titanium oxide spherules and gel forms prepared by the gel-sphere, internal gelation process offer more useful forms of inorganic ion exchangers, catalysts, getters and ceramics.

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

Millis, Andrew

Understanding the behavior of interacting electrons in molecules and solids so that one can predict new superconductors, catalysts, light harvesters, energy and battery materials and optimize existing ones is the ``quantum many-body problem’’. This is one of the scientific grand challenges of the 21 st century. A complete solution to the problem has been proven to be exponentially hard, meaning that straightforward numerical approaches fail. New insights and new methods are needed to provide accurate yet feasible approximate solutions. This CMSCN project brought together chemists and physicists to combine insights from the two disciplines to develop innovative new approaches. Outcomesmore » included the Density Matrix Embedding method, a new, computationally inexpensive and extremely accurate approach that may enable first principles treatment of superconducting and magnetic properties of strongly correlated materials, new techniques for existing methods including an Adaptively Truncated Hilbert Space approach that will vastly expand the capabilities of the dynamical mean field method, a self-energy embedding theory and a new memory-function based approach to the calculations of the behavior of driven systems. The methods developed under this project are now being applied to improve our understanding of superconductivity, to calculate novel topological properties of materials and to characterize and improve the properties of nanoscale devices.« less

Improved LSB matching steganography with histogram characters reserved

NASA Astrophysics Data System (ADS)

Chen, Zhihong; Liu, Wenyao

2008-03-01

This letter bases on the researches of LSB (least significant bit, i.e. the last bit of a binary pixel value) matching steganographic method and the steganalytic method which aims at histograms of cover images, and proposes a modification to LSB matching. In the LSB matching, if the LSB of the next cover pixel matches the next bit of secret data, do nothing; otherwise, choose to add or subtract one from the cover pixel value at random. In our improved method, a steganographic information table is defined and records the changes which embedded secrete bits introduce in. Through the table, the next LSB which has the same pixel value will be judged to add or subtract one dynamically in order to ensure the histogram's change of cover image is minimized. Therefore, the modified method allows embedding the same payload as the LSB matching but with improved steganographic security and less vulnerability to attacks compared with LSB matching. The experimental results of the new method show that the histograms maintain their attributes, such as peak values and alternative trends, in an acceptable degree and have better performance than LSB matching in the respects of histogram distortion and resistance against existing steganalysis.

Scheduling of network access for feedback-based embedded systems

NASA Astrophysics Data System (ADS)

Liberatore, Vincenzo

2002-07-01

nd communication capabilities. Examples range from smart dust embedded in building materials to networks of appliances in the home. Embedded devices will be deployed in unprecedented numbers, will enable pervasive distributed computing, and will radically change the way people interact with the surrounding environment [EGH00a]. The paper targets embedded systems and their real-time (RT) communication requirements. RT requirements arise from the

Aligning Teaching to Learning: A 3-Year Study Examining the Embedding of Language and Argumentation into Elementary Science Classrooms

ERIC Educational Resources Information Center

Hand, Brian; Norton-Meier, Lori A.; Gunel, Murat; Akkus, Recai

2016-01-01

How can classrooms become communities of inquiry that connect intellectually challenging science content with language-based activities (opportunities to talk, listen, read, and write) especially in settings with diverse populations? This question guided a 3-year mixed-methods research study using the Science Writing Heuristic (SWH) approach in…

Motor Impairment Evaluation for Upper Limb in Stroke Patients on the Basis of a Microsensor

ERIC Educational Resources Information Center

Huang, Shuai; Luo, Chun; Ye, Shiwei; Liu, Fei; Xie, Bin; Wang, Caifeng; Yang, Li; Huang, Zhen; Wu, Jiankang

2012-01-01

There has been an urgent need for an effective and efficient upper limb rehabilitation method for poststroke patients. We present a Micro-Sensor-based Upper Limb rehabilitation System for poststroke patients. The wearable motion capture units are attached to upper limb segments embedded in the fabric of garments. The body segment orientation…

Application of binomial and multinomial probability statistics to the sampling design process of a global grain tracing and recall system

USDA-ARS?s Scientific Manuscript database

Small, coded, pill-sized tracers embedded in grain are proposed as a method for grain traceability. A sampling process for a grain traceability system was designed and investigated by applying probability statistics using a science-based sampling approach to collect an adequate number of tracers fo...

The Effectiveness of Web-Based Multimedia Applications Simulation in Teaching and Learning

ERIC Educational Resources Information Center

Ziden, Azidah Abu; Rahman, Muhammad Faizal Abdul

2013-01-01

This study focuses on the effectiveness of using multimedia virtual simulation in Islamic Studies in Malaysia. Virtual simulation methods embedded in Microsoft PowerPoint was used in this study to determine the effectiveness of these modes to motivate students on the topic of pilgrimage in the Islamic Studies subject. Pilgrimage topic has been…

Cell Kinetic and Histomorphometric Analysis of Microgravitational Osteopenia: PARE.03B

NASA Technical Reports Server (NTRS)

Roberts, W. Eugene; Garetto, Lawrence P.

1998-01-01

Previous methods of identifying cells undergoing DNA synthesis (S-phase) utilized 3H-thymidine (3HT) autoradiography. 5-Bromo-2'-deoxyuridine (BrdU) immunohistochemistry is a nonradioactive alternative method. This experiment compared the two methods using the nuclear volume model for osteoblast histogenesis in two different embedding media. Twenty Sprague-Dawley rats were used, with half receiving 3HT (1 micro-Ci/g) and the other half BrdU (50 micro-g/g). Condyles were embedded (one side in paraffin, the other in plastic) and S-phase nuclei were identified using either autoradiography or immunohistochemistry. The fractional distribution of preosteoblast cell types and the percentage of labeled cells (within each cell fraction and label index) were calculated and expressed as mean +/- standard error. Chi-Square analysis showed only a minor difference in the fractional distribution of cell types. However, there were,significant differences (p less than 0.05) by ANOVA, in the nuclear labeling of specific cell types. With the exception of the less-differentiated A+A' cells, more BrdU label was consistently detected in paraffin than in plastic-embedded sections. In general, more nuclei were labeled with 3H-thymidine than with BrdU in both types of embedding media (Fig 2.). Labeling index data (labeled cells/total cells sampled x 100) indicated that BrdU in paraffin, but not plastic gave the same results as 3HT in either embedding method. Thus, we conclude that the two labeling methods do not yield the same results.

Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment

PubMed Central

Guevara, Rainer Dane; Rantz, Marilyn

2015-01-01

We present an example of unobtrusive, continuous monitoring in the home for the purpose of assessing early health changes. Sensors embedded in the environment capture behavior and activity patterns. Changes in patterns are detected as potential signs of changing health. We first present results of a preliminary study investigating 22 features extracted from in-home sensor data. A 1-D alert algorithm was then implemented to generate health alerts to clinicians in a senior housing facility. Clinicians analyze each alert and provide a rating on the clinical relevance. These ratings are then used as ground truth for training and testing classifiers. Here, we present the methodology for four classification approaches that fuse multisensor data. Results are shown using embedded sensor data and health alert ratings collected on 21 seniors over nine months. The best results show similar performance for two techniques, where one approach uses only domain knowledge and the second uses supervised learning for training. Finally, we propose a health change detection model based on these results and clinical expertise. The system of in-home sensors and algorithms for automated health alerts provides a method for detecting health problems very early so that early treatment is possible. This method of passive in-home sensing alleviates compliance issues. PMID:27170900

In situ hybridisation for the detection of Leishmania species in paraffin wax-embedded canine tissues using a digoxigenin-labelled oligonucleotide probe

PubMed Central

Dinhopl, N.; Mostegl, M. M.; Richter, B.; Nedorost, N.; Maderner, A.; Fragner, K.; Weissenböck, H.

2011-01-01

The diagnosis of canine leishmaniosis (CanL) is currently predominantly achieved by cytological or histological identification of amastigotes in biopsy samples, demonstration of specific anti-Leishmania antibodies and PCR-based approaches. All these methods have the advantage of being sensitive and more or less specific; nevertheless, most of them also have disadvantages. A chromogenic in situ hybridisation (ISH) procedure with a digoxigenin-labelled probe, targeting a fragment of the 5.8S rRNA was developed for the detection of all species of Leishmania parasites in routinely paraffin wax-embedded canine tissues. This method was validated in comparison with traditional techniques (histology, PCR), on various tissues from three dogs with histological changes consistent with a florid leishmaniosis. Amastigote forms of Leishmania gave clear signals and were easily identified using ISH. Various tissues from 10 additional dogs with clinical suspicion or/and a positive serological test but without histological presence of amastigotes did not show any ISH signals. Potential cross-reactivity of the probe was ruled out by negative outcome of the ISH against selected protozoa (including the related Trypanosoma cruzi) and fungi. Thus, ISH proved to be a powerful tool for unambiguous detection of Leishmania parasites in paraffin wax-embedded tissues. PMID:21921059

Heartbeat-based error diagnosis framework for distributed embedded systems

NASA Astrophysics Data System (ADS)

Mishra, Swagat; Khilar, Pabitra Mohan

2012-01-01

Distributed Embedded Systems have significant applications in automobile industry as steer-by-wire, fly-by-wire and brake-by-wire systems. In this paper, we provide a general framework for fault detection in a distributed embedded real time system. We use heartbeat monitoring, check pointing and model based redundancy to design a scalable framework that takes care of task scheduling, temperature control and diagnosis of faulty nodes in a distributed embedded system. This helps in diagnosis and shutting down of faulty actuators before the system becomes unsafe. The framework is designed and tested using a new simulation model consisting of virtual nodes working on a message passing system.

Heartbeat-based error diagnosis framework for distributed embedded systems

NASA Astrophysics Data System (ADS)

Mishra, Swagat; Khilar, Pabitra Mohan

2011-12-01

Distributed Embedded Systems have significant applications in automobile industry as steer-by-wire, fly-by-wire and brake-by-wire systems. In this paper, we provide a general framework for fault detection in a distributed embedded real time system. We use heartbeat monitoring, check pointing and model based redundancy to design a scalable framework that takes care of task scheduling, temperature control and diagnosis of faulty nodes in a distributed embedded system. This helps in diagnosis and shutting down of faulty actuators before the system becomes unsafe. The framework is designed and tested using a new simulation model consisting of virtual nodes working on a message passing system.

An embedded real-time red peach detection system based on an OV7670 camera, ARM cortex-M4 processor and 3D look-up tables.

PubMed

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-10-22

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second.

An Embedded Real-Time Red Peach Detection System Based on an OV7670 Camera, ARM Cortex-M4 Processor and 3D Look-Up Tables

PubMed Central

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-01-01

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second. PMID:23202040

Effective scheme for partitioning covalent bonds in density-functional embedding theory: From molecules to extended covalent systems.

PubMed

Huang, Chen; Muñoz-García, Ana Belén; Pavone, Michele

2016-12-28

Density-functional embedding theory provides a general way to perform multi-physics quantum mechanics simulations of large-scale materials by dividing the total system's electron density into a cluster's density and its environment's density. It is then possible to compute the accurate local electronic structures and energetics of the embedded cluster with high-level methods, meanwhile retaining a low-level description of the environment. The prerequisite step in the density-functional embedding theory is the cluster definition. In covalent systems, cutting across the covalent bonds that connect the cluster and its environment leads to dangling bonds (unpaired electrons). These represent a major obstacle for the application of density-functional embedding theory to study extended covalent systems. In this work, we developed a simple scheme to define the cluster in covalent systems. Instead of cutting covalent bonds, we directly split the boundary atoms for maintaining the valency of the cluster. With this new covalent embedding scheme, we compute the dehydrogenation energies of several different molecules, as well as the binding energy of a cobalt atom on graphene. Well localized cluster densities are observed, which can facilitate the use of localized basis sets in high-level calculations. The results are found to converge faster with the embedding method than the other multi-physics approach ONIOM. This work paves the way to perform the density-functional embedding simulations of heterogeneous systems in which different types of chemical bonds are present.

Solid-phase extraction method for the isolation of plant thionins from European mistletoe, wheat and barley using zirconium silicate embedded in poly(styrene-co-divinylbenzene) hollow-monoliths.

PubMed

Hussain, Shah; Güzel, Yüksel; Schönbichler, Stefan A; Rainer, Matthias; Huck, Christian W; Bonn, Günther K

2013-09-01

Thionins are cysteine-rich, biologically active small (∼5 kDa) and basic proteins occurring ubiquitously in the plant kingdom. This study describes an efficient solid-phase extraction (SPE) method for the selective isolation of these pharmacologically active proteins. Hollow-monolithic extraction tips based on poly(styrene-co-divinylbenzene) with embedded zirconium silicate nano-powder were designed, which showed an excellent selectivity for sulphur-rich proteins owing to strong co-ordination between zirconium and the sulphur atoms from the thiol-group of cysteine. The sorbent provides a combination of strong hydrophobic and electrostatic interactions which may help in targeted separation of certain classes of proteins in a complex mixture based upon the binding strength of different proteins. European mistletoe, wheat and barley samples were used for selective isolation of viscotoxins, purothionins and hordothionins, respectively. The enriched fractions were subjected to analysis by matrix-assisted laser desorption/ionisation-time-of-flight mass spectrometer to prove the selectivity of the SPE method towards thionins. For peptide mass-fingerprint analysis, tryptic digests of SPE eluates were examined. Reversed-phase high-performance liquid chromatography hyphenated to diode-array detection was employed for the purification of individual isoforms. The developed method was found to be highly specific for the isolation and purification of thionins.

Nanodiamond embedded ta-C composite film by pulsed filtered vacuum arc deposition from a single target

NASA Astrophysics Data System (ADS)

Iyer, Ajai; Etula, Jarkko; Ge, Yanling; Liu, Xuwen; Koskinen, Jari

2016-11-01

Detonation Nanodiamonds (DNDs) are known to have sp3 core, sp2 shell, small size (few nm) and are gaining importance as multi-functional nanoparticles. Diverse methods have been used to form composites, containing detonation nanodiamonds (DNDs) embedded in conductive and dielectric matrices for various applications. Here we show a method, wherein DND-ta-C composite film, consisting of DNDs embedded in ta-C matrix have been co-deposited from the same cathode by pulsed filtered cathodic vacuum arc method. Transmission Electron Microscope analysis of these films revel the presence of DNDs embedded in the matrix of amorphous carbon. Raman spectroscopy indicates that the presence of DNDs does not adversely affect the sp3 content of DND-ta-C composite film compared to ta-C film of same thickness. Nanoindentation and nanowear tests indicate that DND-ta-C composite films possess improved mechanical properties in comparison to ta-C films of similar thickness.

A study on the performance of piezoelectric composite materials for designing embedded transducers for concrete assessment

NASA Astrophysics Data System (ADS)

Dumoulin, Cédric; Deraemaeker, Arnaud

2018-03-01

Ultrasonic measurements of concrete can provide crucial information about its state of health. The most common practice in the construction industry consists in using external probes which strongly limits the use of the method since large parts of the in-service structures are difficult to access. It is also possible to assess in real time the setting process of the concrete using ultrasonic measurements. In practice, the field measurement of the concrete hardening is limited by the formworks. As an alternative, some research teams have studied the possibility to directly embed the transducers into the concrete structures. The current embedded ultrasonic transducers are of two categories: bulk piezoelectric elements surrounded by several coating and matching layers and composites piezoelectric elements. Both technologies aim at optimizing the wave energy transmitted to the tested medium. The performances of the transducers of the first kind have been studied in a previous study. A fair amount of recent research has been focused on the development of novel cement-based piezoelectric composites. In this study, we first compare the effective properties of such cement-based materials with more widespread composites made with matrices of epoxy resins or polyurethane. The study only concerns the 1-3 fiber arrangement composites. The effective properties are computed using both an analytical mixing rule method and a finite element based homogenization method using representative volume elements (RVEs) which allows for considering more realistic fiber arrangements, leading yet to very similar results. The effective piezoelectric properties of cement-based composites appear to be very low compared to composites made of epoxy or polyurethane. This result is underlined by looking at the acoustic response and the electric input impedance of different piezoelectric disks where we compare performances of such transducers with a low-cost bulk piezoelectric disc element. The first radial mode of the latter is responsible for an acoustic response of the same order of magnitude as those for the piezo-composites. This result confirms that the design of efficient low-cost embedded ultrasonic transducers can be done with such piezoceramic disks.

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors

PubMed Central

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-01-01

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms. PMID:27240382

A Transfer Hamiltonian Model for Devices Based on Quantum Dot Arrays

PubMed Central

Illera, S.; Prades, J. D.; Cirera, A.; Cornet, A.

2015-01-01

We present a model of electron transport through a random distribution of interacting quantum dots embedded in a dielectric matrix to simulate realistic devices. The method underlying the model depends only on fundamental parameters of the system and it is based on the Transfer Hamiltonian approach. A set of noncoherent rate equations can be written and the interaction between the quantum dots and between the quantum dots and the electrodes is introduced by transition rates and capacitive couplings. A realistic modelization of the capacitive couplings, the transmission coefficients, the electron/hole tunneling currents, and the density of states of each quantum dot have been taken into account. The effects of the local potential are computed within the self-consistent field regime. While the description of the theoretical framework is kept as general as possible, two specific prototypical devices, an arbitrary array of quantum dots embedded in a matrix insulator and a transistor device based on quantum dots, are used to illustrate the kind of unique insight that numerical simulations based on the theory are able to provide. PMID:25879055

A transfer hamiltonian model for devices based on quantum dot arrays.

PubMed

Illera, S; Prades, J D; Cirera, A; Cornet, A

2015-01-01

We present a model of electron transport through a random distribution of interacting quantum dots embedded in a dielectric matrix to simulate realistic devices. The method underlying the model depends only on fundamental parameters of the system and it is based on the Transfer Hamiltonian approach. A set of noncoherent rate equations can be written and the interaction between the quantum dots and between the quantum dots and the electrodes is introduced by transition rates and capacitive couplings. A realistic modelization of the capacitive couplings, the transmission coefficients, the electron/hole tunneling currents, and the density of states of each quantum dot have been taken into account. The effects of the local potential are computed within the self-consistent field regime. While the description of the theoretical framework is kept as general as possible, two specific prototypical devices, an arbitrary array of quantum dots embedded in a matrix insulator and a transistor device based on quantum dots, are used to illustrate the kind of unique insight that numerical simulations based on the theory are able to provide.

Thermomechanical response of NiTi shape-memory nanoprecipitates in TiV alloys

NASA Astrophysics Data System (ADS)

Maisel, S. B.; Ko, W.-S.; Zhang, J.-L.; Grabowski, B.; Neugebauer, J.

2017-08-01

We study the properties of NiTi shape-memory nanoparticles coherently embedded in TiV matrices using three-dimensional atomistic simulations based on the modified embedded-atom method. To this end, we develop and present a suitable NiTiV potential for our simulations. Employing this potential, we identify the conditions under which the martensitic phase transformation of such a nanoparticle is triggered—specifically, how these conditions can be tuned by modifying the size of the particle, the composition of the surrounding matrix, or the temperature and strain state of the system. Using these insights, we establish how the transformation temperature of such particles can be influenced and discuss the practical implications in the context of shape-memory strengthened alloys.

Investigation of protein adsorption performance of Ni2+-attached diatomite particles embedded in composite monolithic cryogels.

PubMed

Ünlü, Nuri; Ceylan, Şeyda; Erzengin, Mahmut; Odabaşı, Mehmet

2011-08-01

As a low-cost natural adsorbent, diatomite (DA) (2 μm) has several advantages including high surface area, chemical reactivity, hydrophilicity and lack of toxicity. In this study, the protein adsorption performance of supermacroporous composite cryogels embedded with Ni(2+)-attached DA particles (Ni(2+)-ADAPs) was investigated. Supermacroporous poly(2-hydroxyethyl methacrylate) (PHEMA)-based monolithic composite cryogel column embedded with Ni(2+)-ADAPs was prepared by radical cryo-copolymerization of 2-hydroxyethyl methacrylate (HEMA) with N,N'-methylene-bis-acrylamide (MBAAm) as cross-linker directly in a plastic syringe for affinity purification of human serum albumin (HSA) both from aqueous solutions and human serum. The chemical composition and surface area of DA was determined by XRF and BET method, respectively. The characterization of composite cryogel was investigated by SEM. The effect of pH, and embedded Ni(2+)-ADAPs amount, initial HSA concentration, temperature and flow rate on adsorption were studied. The maximum amount of HSA adsorption from aqueous solution at pH 8.0 phosphate buffer was very high (485.15 mg/g DA). It was observed that HSA could be repeatedly adsorbed and desorbed to the embedded Ni(2+)-ADAPs in poly(2-hydroxyethyl methacrylate) composite cryogel without significant loss of adsorption capacity. The efficiency of albumin adsorption from human serum before and after albumin adsorption was also investigated with SDS-PAGE analyses. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Polyester Wax: A New Embedding Medium for the Histopathologic Study of Human Temporal Bones

PubMed Central

Merchant, Saumil N.; Burgess, Barbara; O'Malley, Jennifer; Jones, Diane; Adams, Joe C.

2007-01-01

Background Celloidin and paraffin are the two common embedding mediums used for histopathologic study of the human temporal bone by light microscopy. Although celloidin embedding permits excellent morphologic assessment, celloidin is difficult to remove, and there are significant restrictions on success with immunostaining. Embedding in paraffin allows immunostaining to be performed, but preservation of cellular detail within the membranous labyrinth is relatively poor. Objectives/Hypothesis Polyester wax is an embedding medium that has a low melting point (37°C), is soluble in most organic solvents, is water tolerant, and sections easily. We hypothesized that embedding in polyester wax would permit good preservation of the morphology of the membranous labyrinth and, at the same time, allow the study of proteins by immunostaining. Methods Nine temporal bones from individuals aged 1 to 94 years removed 2 to 31 hours postmortem, from subjects who had no history of otologic disease, were used. The bones were fixed using 10% formalin, decal-cified using EDTA, embedded in polyester wax, and serially sectioned at a thickness of 8 to 12 μm on a rotary microtome. The block and knife were cooled with frozen CO2 (dry ice) held in a funnel above the block. Sections were placed on glass slides coated with a solution of 1% fish gelatin and 1% bovine albumin, followed by staining of selected sections with hematoxylin and eosin (H&E). Immunostaining was also performed on selected sections using antibodies to 200 kD neurofilament and Na-K-ATPase. Results Polyester wax–embedded sections demonstrated good preservation of cellular detail of the organ of Corti and other structures of the membranous labyrinth, as well as the surrounding otic capsule. The protocol described in this paper was reliable and consistently yielded sections of good quality. Immuno-staining was successful with both antibodies. Conclusion The use of polyester wax as an embedding medium for human temporal bones offers the advantage of good preservation of morphology and ease of immunostaining. We anticipate that in the future, polyester wax embedding will also permit other molecular biologic assays on temporal bone sections such as the retrieval of nucleic acids and the study of proteins using mass spectrometry–based proteomic analysis. PMID:16467713

Endoluminal dilatation for embedded hemodialysis catheters: A case-control study of factors associated with embedding and clinical outcomes

PubMed Central

Talreja, Hari; Ryan, Stephen Edward; Graham, Janet; Sood, Manish M.; Hadziomerovic, Adnan; Clark, Edward

2017-01-01

Background With the increasing frequency of tunneled hemodialysis catheter use there is a parallel increase in the need for removal and/or exchange. A small but significant minority of catheters become embedded or ‘stuck’ and cannot be removed by traditional means. Management of embedded catheters involves cutting the catheter, burying the retained fragment with a subsequent increased risk of infections and thrombosis. Endoluminal dilatation may provide a potential safe and effective technique for removing embedded catheters, however, to date, there is a paucity of data. Objectives 1) To determine factors associated with catheters becoming embedded and 2) to determine outcomes associated with endoluminal dilatation Methods All patients with endoluminal dilatation for embedded catheters at our institution since Jan. 2010 were included. Patients who had an embedded catheter were matched 1:3 with patients with uncomplicated catheter removal. Baseline patient and catheter characteristics were compared. Outcomes included procedural success and procedure-related infection. Logistic regression models were used to determine factors associated with embedded catheters. Results We matched 15 cases of embedded tunneled catheters with 45 controls. Among patients with embedded catheters, there were no complications with endoluminal dilatation. Factors independently associated with embedded catheters included catheter dwell time (> 2 years) and history of central venous stenosis. Conclusion Embedded catheters can be successfully managed by endoluminal dilatation with minimal complications and factors associated with embedding include dwell times > 2 years and/or with a history of central venous stenosis. PMID:28346468

Research and application of embedded real-time operating system

NASA Astrophysics Data System (ADS)

Zhang, Bo

2013-03-01

In this paper, based on the analysis of existing embedded real-time operating system, the architecture of an operating system is designed and implemented. The experimental results show that the design fully complies with the requirements of embedded real-time operating system, can achieve the purposes of reducing the complexity of embedded software design and improving the maintainability, reliability, flexibility. Therefore, this design program has high practical value.

Securing resource constraints embedded devices using elliptic curve cryptography

NASA Astrophysics Data System (ADS)

Tam, Tony; Alfasi, Mohamed; Mozumdar, Mohammad

2014-06-01

The use of smart embedded device has been growing rapidly in recent time because of miniaturization of sensors and platforms. Securing data from these embedded devices is now become one of the core challenges both in industry and research community. Being embedded, these devices have tight constraints on resources such as power, computation, memory, etc. Hence it is very difficult to implement traditional Public Key Cryptography (PKC) into these resource constrained embedded devices. Moreover, most of the public key security protocols requires both public and private key to be generated together. In contrast with this, Identity Based Encryption (IBE), a public key cryptography protocol, allows a public key to be generated from an arbitrary string and the corresponding private key to be generated later on demand. While IBE has been actively studied and widely applied in cryptography research, conventional IBE primitives are also computationally demanding and cannot be efficiently implemented on embedded system. Simplified version of the identity based encryption has proven its competence in being robust and also satisfies tight budget of the embedded platform. In this paper, we describe the choice of several parameters for implementing lightweight IBE in resource constrained embedded sensor nodes. Our implementation of IBE is built using elliptic curve cryptography (ECC).

Construction of Optimally Reduced Empirical Model by Spatially Distributed Climate Data

NASA Astrophysics Data System (ADS)

Gavrilov, A.; Mukhin, D.; Loskutov, E.; Feigin, A.

2016-12-01

We present an approach to empirical reconstruction of the evolution operator in stochastic form by space-distributed time series. The main problem in empirical modeling consists in choosing appropriate phase variables which can efficiently reduce the dimension of the model at minimal loss of information about system's dynamics which consequently leads to more robust model and better quality of the reconstruction. For this purpose we incorporate in the model two key steps. The first step is standard preliminary reduction of observed time series dimension by decomposition via certain empirical basis (e. g. empirical orthogonal function basis or its nonlinear or spatio-temporal generalizations). The second step is construction of an evolution operator by principal components (PCs) - the time series obtained by the decomposition. In this step we introduce a new way of reducing the dimension of the embedding in which the evolution operator is constructed. It is based on choosing proper combinations of delayed PCs to take into account the most significant spatio-temporal couplings. The evolution operator is sought as nonlinear random mapping parameterized using artificial neural networks (ANN). Bayesian approach is used to learn the model and to find optimal hyperparameters: the number of PCs, the dimension of the embedding, the degree of the nonlinearity of ANN. The results of application of the method to climate data (sea surface temperature, sea level pressure) and their comparing with the same method based on non-reduced embedding are presented. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS).

Patron perception and utilization of an embedded librarian program.

PubMed

Blake, Lindsay; Ballance, Darra; Davies, Kathy; Gaines, Julie K; Mears, Kim; Shipman, Peter; Connolly-Brown, Maryska; Burchfield, Vicki

2016-07-01

The study measured the perceived value of an academic library's embedded librarian service model. The study took place at the health sciences campuses of a research institution. A web-based survey was distributed that asked respondents a series of questions about their utilization of and satisfaction with embedded librarians and services. Over 58% of respondents reported being aware of their embedded librarians, and 95% of these were satisfied with provided services. The overall satisfaction with services was encouraging, but awareness of the embedded program was low, suggesting an overall need for marketing of services.

Image steganography based on 2k correction and coherent bit length

NASA Astrophysics Data System (ADS)

Sun, Shuliang; Guo, Yongning

2014-10-01

In this paper, a novel algorithm is proposed. Firstly, the edge of cover image is detected with Canny operator and secret data is embedded in edge pixels. Sorting method is used to randomize the edge pixels in order to enhance security. Coherent bit length L is determined by relevant edge pixels. Finally, the method of 2k correction is applied to achieve better imperceptibility in stego image. The experiment shows that the proposed method is better than LSB-3 and Jae-Gil Yu's in PSNR and capacity.

Orthogonality of embedded wave functions for different states in frozen-density embedding theory

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

Zech, Alexander; Wesolowski, Tomasz A.; Aquilante, Francesco

2015-10-28

Other than lowest-energy stationary embedded wave functions obtained in Frozen-Density Embedding Theory (FDET) [T. A. Wesolowski, Phys. Rev. A 77, 012504 (2008)] can be associated with electronic excited states but they can be mutually non-orthogonal. Although this does not violate any physical principles — embedded wave functions are only auxiliary objects used to obtain stationary densities — working with orthogonal functions has many practical advantages. In the present work, we show numerically that excitation energies obtained using conventional FDET calculations (allowing for non-orthogonality) can be obtained using embedded wave functions which are strictly orthogonal. The used method preserves the mathematicalmore » structure of FDET and self-consistency between energy, embedded wave function, and the embedding potential (they are connected through the Euler-Lagrange equations). The orthogonality is built-in through the linearization in the embedded density of the relevant components of the total energy functional. Moreover, we show formally that the differences between the expectation values of the embedded Hamiltonian are equal to the excitation energies, which is the exact result within linearized FDET. Linearized FDET is shown to be a robust approximation for a large class of reference densities.« less

Nonenzymatic glucose sensor based on renewable electrospun Ni nanoparticle-loaded carbon nanofiber paste electrode.

PubMed

Liu, Yang; Teng, Hong; Hou, Haoqing; You, Tianyan

2009-07-15

A novel nonenzymatic glucose sensor was developed based on the renewable Ni nanoparticle-loaded carbon nanofiber paste (NiCFP) electrode. The NiCF nanocomposite was prepared by combination of electrospinning technique with thermal treatment method. The scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images showed that large amounts of spherical nanoparticles were well dispersed on the surface or embedded in the carbon nanofibers. And the nanoparticles were composed of Ni and NiO, as revealed by energy dispersive X-ray spectroscopy (EDX) and X-ray powder diffraction (XRD). In application to nonenzymatic glucose determination, the renewable NiCFP electrodes, which were constructed by simply mixing the electrospun nanocomposite with mineral oil, exhibited strong and fast amperometric response without being poisoned by chloride ions. Low detection limit of 1 microM with wide linear range from 2 microM to 2.5 mM (R=0.9997) could be obtained. The current response of the proposed glucose sensor was highly sensitive and stable, attributing to the electrocatalytic performance of the firmly embedded Ni nanoparticles as well as the chemical inertness of the carbon-based electrode. The good analytical performance, low cost and straightforward preparation method made this novel electrode material promising for the development of effective glucose sensor.

Density-Difference-Driven Optimized Embedding Potential Method To Study the Spectroscopy of Br₂ in Water Clusters.

PubMed

Roncero, Octavio; Aguado, Alfredo; Batista-Romero, Fidel A; Bernal-Uruchurtu, Margarita I; Hernández-Lamoneda, Ramón

2015-03-10

A variant of the density difference driven optimized embedding potential (DDD-OEP) method, proposed by Roncero et al. (J. Chem. Phys. 2009, 131, 234110), has been applied to the calculation of excited states of Br2 within small water clusters. It is found that the strong interaction of Br2 with the lone electronic pair of the water molecules makes necessary to optimize specific embedding potentials for ground and excited electronic states, separately and using the corresponding densities. Diagnosis and convergence studies are presented with the aim of providing methods to be applied for the study of chromophores in solution. Also, some preliminary results obtained for the study of electronic states of Br2 in clathrate cages are presented.

Autofocus method for automated microscopy using embedded GPUs.

PubMed

Castillo-Secilla, J M; Saval-Calvo, M; Medina-Valdès, L; Cuenca-Asensi, S; Martínez-Álvarez, A; Sánchez, C; Cristóbal, G

2017-03-01

In this paper we present a method for autofocusing images of sputum smears taken from a microscope which combines the finding of the optimal focus distance with an algorithm for extending the depth of field (EDoF). Our multifocus fusion method produces an unique image where all the relevant objects of the analyzed scene are well focused, independently to their distance to the sensor. This process is computationally expensive which makes unfeasible its automation using traditional embedded processors. For this purpose a low-cost optimized implementation is proposed using limited resources embedded GPU integrated on cutting-edge NVIDIA system on chip. The extensive tests performed on different sputum smear image sets show the real-time capabilities of our implementation maintaining the quality of the output image.

An Embedded Laser Marking Controller Based on ARM and FPGA Processors

PubMed Central

Dongyun, Wang; Xinpiao, Ye

2014-01-01

Laser marking is an important branch of the laser information processing technology. The existing laser marking machine based on PC and WINDOWS operating system, are large and inconvenient to move. Still, it cannot work outdoors or in other harsh environments. In order to compensate for the above mentioned disadvantages, this paper proposed an embedded laser marking controller based on ARM and FPGA processors. Based on the principle of laser galvanometer scanning marking, the hardware and software were designed for the application. Experiments showed that this new embedded laser marking controller controls the galvanometers synchronously and could achieve precise marking. PMID:24772028

Carbon-embedded Ni nanocatalysts derived from MOFs by a sacrificial template method for efficient hydrogenation of furfural to tetrahydrofurfuryl alcohol.

PubMed

Su, Yanping; Chen, Chun; Zhu, Xiaoguang; Zhang, Yong; Gong, Wanbing; Zhang, Haimin; Zhao, Huijun; Wang, Guozhong

2017-05-16

We report a fast and simple method for the synthesis of Ni-based metal-organic-frameworks (Ni-MOFs). Due to the existence of nickel ions and an organic ligand, the MOFs are employed as a sacrificial template for the facile preparation of carbon-embedded Ni (Ni/C) catalysts by a direct thermal decomposition method. The obtained Ni/C catalysts exhibit excellent catalytic activity for selectively transforming furfural (FAL) to tetrahydrofurfuryl alcohol (THFOL) due to the Ni nanoparticles (NPs) embedded uniformly in the ligand-derived carbon. The exemplified results illustrate that the catalytic performance of the Ni/C catalyst is greatly affected by the calcination conditions (temperature and time), composition of the Ni-MOF precursor and the catalysis conditions. The conversion of FAL and selectivity of THFOL both reached 100% under the conditions of 120 °C, 1 MPa H 2 pressure and 120 min of hydrogenation over the Ni/C-500 catalyst, derived from the pyrolysis of Ni-MOFs (Ni : BTC mole ratio of 1.0) at 500 °C for 120 min, which exhibits an average nanoparticle size of ∼14 nm and uniform dispersion, and the highest BET surface area (∼92 m 2 g -1 ) among all investigated Ni/C catalysts. This facilely prepared heterogeneous catalyst would be very promising for the replacement of noble metal catalysts for the efficient catalytic conversion of biomass-derived feedstocks into value-added chemicals.

Polarizable embedding with a multiconfiguration short-range density functional theory linear response method

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

Hedegård, Erik Donovan, E-mail: erik.hedegard@phys.chem.ethz.ch; Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Campusvej 55, DK-5230 Odense; Olsen, Jógvan Magnus Haugaard

2015-03-21

We present here the coupling of a polarizable embedding (PE) model to the recently developed multiconfiguration short-range density functional theory method (MC-srDFT), which can treat multiconfigurational systems with a simultaneous account for dynamical and static correlation effects. PE-MC-srDFT is designed to combine efficient treatment of complicated electronic structures with inclusion of effects from the surrounding environment. The environmental effects encompass classical electrostatic interactions as well as polarization of both the quantum region and the environment. Using response theory, molecular properties such as excitation energies and oscillator strengths can be obtained. The PE-MC-srDFT method and the additional terms required for linearmore » response have been implemented in a development version of DALTON. To benchmark the PE-MC-srDFT approach against the literature data, we have investigated the low-lying electronic excitations of acetone and uracil, both immersed in water solution. The PE-MC-srDFT results are consistent and accurate, both in terms of the calculated solvent shift and, unlike regular PE-MCSCF, also with respect to the individual absolute excitation energies. To demonstrate the capabilities of PE-MC-srDFT, we also investigated the retinylidene Schiff base chromophore embedded in the channelrhodopsin protein. While using a much more compact reference wave function in terms of active space, our PE-MC-srDFT approach yields excitation energies comparable in quality to CASSCF/CASPT2 benchmarks.« less

Sorption of DNA by diatomite-Zn(II) embedded supermacroporous monolithic p(HEMA) cryogels.

PubMed

Tozak, Kabil Özcan; Erzengin, Mahmut; Sargin, Idris; Ünlü, Nuri

2013-01-01

In this study, the DNA sorption performance of diatomite-Zn(II) embedded supermacroporous monolithic p(HEMA) cryogels were investigated for the purpose of designing a novel adsorbent that can be utilized for DNA purification, separation and immunoadsorption studies such as removal of anti-dsDNA antibodies from systemic lupus erythematosus (SLE) patient plasma. Poly(2-hydroxyethyl methacrylate) [p(HEMA)]-based monolithic cryogel column embedded with Zn(2+)-diatomite particles was prepared by free radical cryo-copolymerization of 2-hydroxyethyl methacrylate (HEMA) with N,N'-methylene-bis-acrylamide (MBAAm). The polymerization reaction was initiated by N,N,N',N'-tetramethylene diamine (TEMED) and ammonium persulfate (APS) pair in an ice bath. After thawing, the monolithic composite cryogels were used for affinity sorption and then subsequent desorption of DNA molecules from aqueous solutions. Diatomite (DA) particles were characterized by XRF and BET method. The characterization of composite cryogel was done through SEM imaging. The effects of pH of the solution, initial DNA concentration, ionic strength, temperature and flow rates on adsorption were investigated to determine the optimum conditions for adsorption/desorption experiments. The particle embedding procedure was shown to yield significantly enhanced adsorption of DNA on the adsorbent. Furthermore, considering its excellent bio-compatibility, p(HEMA) cryogels are promising a candidate for further DNA sorption studies.

Embedding Piezoresistive Pressure Sensors to Obtain Online Pressure Profiles Inside Fiber Composite Laminates

PubMed Central

Kahali Moghaddam, Maryam; Breede, Arne; Brauner, Christian; Lang, Walter

2015-01-01

The production of large and complex parts using fiber composite materials is costly due to the frequent formation of voids, porosity and waste products. By embedding different types of sensors and monitoring the process in real time, the amount of wastage can be significantly reduced. This work focuses on developing a knowledge-based method to improve and ensure complete impregnation of the fibers before initiation of the resin cure. Piezoresistive and capacitive pressure sensors were embedded in fiber composite laminates to measure the real-time the pressure values inside the laminate. A change of pressure indicates resin infusion. The sensors were placed in the laminate and the resin was infused by vacuum. The embedded piezoresistive pressure sensors were able to track the vacuum pressure in the fiber composite laminate setup, as well as the arrival of the resin at the sensor. The pressure increase due to closing the resin inlet was also measured. In contrast, the capacitive type of sensor was found to be inappropriate for measuring these quantities. The following study demonstrates real-time monitoring of pressure changes inside the fiber composite laminate, which validate the use of Darcy’s law in porous media to control the resin flow during infusion. PMID:25825973

Sorption of DNA by diatomite-Zn(II) embedded supermacroporous monolithic p(HEMA) cryogels

PubMed Central

Tozak, Kabil Özcan; Erzengin, Mahmut; Sargin, Idris; Ünlü, Nuri

2013-01-01

In this study, the DNA sorption performance of diatomite-Zn(II) embedded supermacroporous monolithic p(HEMA) cryogels were investigated for the purpose of designing a novel adsorbent that can be utilized for DNA purification, separation and immunoadsorption studies such as removal of anti-dsDNA antibodies from systemic lupus erythematosus (SLE) patient plasma. Poly(2-hydroxyethyl methacrylate) [p(HEMA)]-based monolithic cryogel column embedded with Zn2+-diatomite particles was prepared by free radical cryo-copolymerization of 2-hydroxyethyl methacrylate (HEMA) with N,N'-methylene-bis-acrylamide (MBAAm). The polymerization reaction was initiated by N,N,N',N'-tetramethylene diamine (TEMED) and ammonium persulfate (APS) pair in an ice bath. After thawing, the monolithic composite cryogels were used for affinity sorption and then subsequent desorption of DNA molecules from aqueous solutions. Diatomite (DA) particles were characterized by XRF and BET method. The characterization of composite cryogel was done through SEM imaging. The effects of pH of the solution, initial DNA concentration, ionic strength, temperature and flow rates on adsorption were investigated to determine the optimum conditions for adsorption/desorption experiments. The particle embedding procedure was shown to yield significantly enhanced adsorption of DNA on the adsorbent. Furthermore, considering its excellent bio-compatibility, p(HEMA) cryogels are promising a candidate for further DNA sorption studies. PMID:26600734

Enhanced thermal conductance of polymer composites through embedding aligned carbon nanofibers

DOE PAGES

Nicholas, Roberts; Hensley, Dale K.; Wood, David

2016-07-08

The focus of this work is to find a more efficient method of enhancing the thermal conductance of polymer thin films. This work compares polymer thin films embedded with randomly oriented carbon nanotubes to those with vertically aligned carbon nanofibers. Thin films embedded with carbon nanofibers demonstrated a similar thermal conductance between 40–60 μm and a higher thermal conductance between 25–40 μm than films embedded with carbon nanotubes with similar volume fractions even though carbon nanotubes have a higher thermal conductivity than carbon nanofibers

Enhanced thermal conductance of polymer composites through embedding aligned carbon nanofibers

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

Nicholas, Roberts; Hensley, Dale K.; Wood, David

The focus of this work is to find a more efficient method of enhancing the thermal conductance of polymer thin films. This work compares polymer thin films embedded with randomly oriented carbon nanotubes to those with vertically aligned carbon nanofibers. Thin films embedded with carbon nanofibers demonstrated a similar thermal conductance between 40–60 μm and a higher thermal conductance between 25–40 μm than films embedded with carbon nanotubes with similar volume fractions even though carbon nanotubes have a higher thermal conductivity than carbon nanofibers

Fabrication of Sb₂S₃ Hybrid Solar Cells Based on Embedded Photoelectrodes of Ag Nanowires-Au Nanoparticles Composite.

PubMed

Kim, Kang-Pil; Hwang, Dae-Kue; Woo, Sung-Ho; Kim, Dae-Hwan

2018-09-01

The Ag nanowire (NW) + Au nanoparticle (NP)-embedded TiO2 photoelectrodes were adopted for conventional planar TiO2-based Sb2S3 hybrid solar cells to improve the cell efficiency. Compared to conventional planar TiO2-based Sb2S3 hybrid solar cells, the Ag NW + Au NP/TiO2-based Sb2S3 hybrid solar cells exhibited an improvement of approximately 40% in the cell efficiency due to the significant increase in both Jsc and Voc. These enhanced Jsc and Voc were attributed to the increased surface area, charge-collection efficiency, and light absorption by embedding the Ag NWs + Au NPs composite. The Ag NW + Au NP/TiO2-based Sb2S3 hybrid solar cells showed the highest efficiency of 2.17%, demonstrating that the Ag NW + Au NP-embedded TiO2 photoelectrode was a suitable photoelectrode structure to improve the power conversion efficiency in the Sb2S3 hybrid solar cells.

Codestream-Based Identification of JPEG 2000 Images with Different Coding Parameters

NASA Astrophysics Data System (ADS)

Watanabe, Osamu; Fukuhara, Takahiro; Kiya, Hitoshi

A method of identifying JPEG 2000 images with different coding parameters, such as code-block sizes, quantization-step sizes, and resolution levels, is presented. It does not produce false-negative matches regardless of different coding parameters (compression rate, code-block size, and discrete wavelet transform (DWT) resolutions levels) or quantization step sizes. This feature is not provided by conventional methods. Moreover, the proposed approach is fast because it uses the number of zero-bit-planes that can be extracted from the JPEG 2000 codestream by only parsing the header information without embedded block coding with optimized truncation (EBCOT) decoding. The experimental results revealed the effectiveness of image identification based on the new method.

Embedded object concept: case balancing two-wheeled robot

NASA Astrophysics Data System (ADS)

Vallius, Tero; Röning, Juha

2007-09-01

This paper presents the Embedded Object Concept (EOC) and a telepresence robot system which is a test case for the EOC. The EOC utilizes common object-oriented methods used in software by applying them to combined Lego-like software-hardware entities. These entities represent objects in object-oriented design methods, and they are the building blocks of embedded systems. The goal of the EOC is to make the designing of embedded systems faster and easier. This concept enables people without comprehensive knowledge in electronics design to create new embedded systems, and for experts it shortens the design time of new embedded systems. We present the current status of a telepresence robot created with Atomi-objects, which is the name for our implementation of the embedded objects. The telepresence robot is a relatively complex test case for the EOC. The robot has been constructed using incremental device development, which is made possible by the architecture of the EOC. The robot contains video and audio exchange capability and a controlling system for driving with two wheels. The robot consists of Atomi-objects, demonstrating the suitability of the EOC for prototyping and easy modifications, and proving the capabilities of the EOC by realizing a function that normally requires a computer. The computer counterpart is a regular PC with audio and video capabilities running with a robot control application. The robot is functional and successfully tested.

Epoxy Resins in Electron Microscopy

PubMed Central

Finck, Henry

1960-01-01

A method of embedding biological specimens in araldite 502 (Ciba) has been developed for materials available in the United States. Araldite-embedded tissues are suitable for electron microscopy, but the cutting qualities of the resin necessitates more than routine attention during microtomy. The rather high viscosity of araldite 502 also seems to be an unnecessary handicap. The less viscous epoxy epon 812 (Shell) produces specimens with improved cutting qualities, and has several features—low shrinkage and absence of specimen damage during cure, minimal compression of sections, relative absence of electron beam-induced section damage, etc.—which recommends it as a routine embedding material. The hardness of the cured resin can be easily adjusted by several methods to suit the materials embedded in it. Several problems and advantages of working with sections of epoxy resins are also discussed. PMID:13822825

Development and application of remote video monitoring system for combine harvester based on embedded Linux

NASA Astrophysics Data System (ADS)

Chen, Jin; Wang, Yifan; Wang, Xuelei; Wang, Yuehong; Hu, Rui

2017-01-01

Combine harvester usually works in sparsely populated areas with harsh environment. In order to achieve the remote real-time video monitoring of the working state of combine harvester. A remote video monitoring system based on ARM11 and embedded Linux is developed. The system uses USB camera for capturing working state video data of the main parts of combine harvester, including the granary, threshing drum, cab and cut table. Using JPEG image compression standard to compress video data then transferring monitoring screen to remote monitoring center over the network for long-range monitoring and management. At the beginning of this paper it describes the necessity of the design of the system. Then it introduces realization methods of hardware and software briefly. And then it describes detailedly the configuration and compilation of embedded Linux operating system and the compiling and transplanting of video server program are elaborated. At the end of the paper, we carried out equipment installation and commissioning on combine harvester and then tested the system and showed the test results. In the experiment testing, the remote video monitoring system for combine harvester can achieve 30fps with the resolution of 800x600, and the response delay in the public network is about 40ms.

An Embedded Sensory System for Worker Safety: Prototype Development and Evaluation

PubMed Central

Cho, Chunhee; Park, JeeWoong

2018-01-01

At a construction site, workers mainly rely on two senses, which are sight and sound, in order to perceive their physical surroundings. However, they are often hindered by the nature of most construction sites, which are usually dynamic, loud, and complicated. To overcome these challenges, this research explored a method using an embedded sensory system that might offer construction workers an artificial sensing ability to better perceive their surroundings. This study identified three parameters (i.e., intensity, signal length, and delay between consecutive pulses) needed for tactile-based signals for the construction workers to communicate quickly. We developed a prototype system based on these parameters, conducted experimental studies to quantify and validate the sensitivity of the parameters for quick communication, and analyzed test data to reveal what was added by this method in order to perceive information from the tactile signals. The findings disclosed that the parameters of tactile-based signals and their distinguishable ranges could be perceived in a short amount of time (i.e., a fraction of a second). Further experimentation demonstrated the capability of the identified unit signals combined with a signal mapping technique to effectively deliver simple information to individuals and offer an additional sense of awareness to the surroundings. The findings of this study could serve as a basis for future research in exploring advanced tactile-based messages to overcome challenges in environments for which communication is a struggle. PMID:29662008

An Embedded Sensory System for Worker Safety: Prototype Development and Evaluation.

PubMed

Cho, Chunhee; Park, JeeWoong

2018-04-14

At a construction site, workers mainly rely on two senses, which are sight and sound, in order to perceive their physical surroundings. However, they are often hindered by the nature of most construction sites, which are usually dynamic, loud, and complicated. To overcome these challenges, this research explored a method using an embedded sensory system that might offer construction workers an artificial sensing ability to better perceive their surroundings. This study identified three parameters (i.e., intensity, signal length, and delay between consecutive pulses) needed for tactile-based signals for the construction workers to communicate quickly. We developed a prototype system based on these parameters, conducted experimental studies to quantify and validate the sensitivity of the parameters for quick communication, and analyzed test data to reveal what was added by this method in order to perceive information from the tactile signals. The findings disclosed that the parameters of tactile-based signals and their distinguishable ranges could be perceived in a short amount of time (i.e., a fraction of a second). Further experimentation demonstrated the capability of the identified unit signals combined with a signal mapping technique to effectively deliver simple information to individuals and offer an additional sense of awareness to the surroundings. The findings of this study could serve as a basis for future research in exploring advanced tactile-based messages to overcome challenges in environments for which communication is a struggle.

PPP1R12A Copy Number Is Associated with Clinical Outcomes of Stage III CRC Receiving Oxaliplatin-Based Chemotherapy

PubMed Central

Zhang, Chenbo; Li, Ajian; Li, Huaguang; Peng, Kangsheng; Wei, Qing; Lin, Moubin; Liu, Zhanju; Yin, Lu; Li, Jianwen

2015-01-01

Aim. To investigate the correlation between PPP1R12A gene copy number and clinical outcomes of oxaliplatin-based regimen in stage III colorectal cancer (CRC). Methods. A total of 139 paraffin-embedded tissue samples of stage III CRC patients who received oxaliplatin-based treatment after radical surgery were recruited. Genomic DNA was extracted and purified from paraffin-embedded sections. Quantitative PCR methods were used to detect the relative copy number (RCN) of PPP1R12A. Results. Statistical analysis demonstrated that low PPP1R12A RCN was associated with poor RFS (HR = 2.186, 95% CI: 1.293–3.696; P = 0.003) and OS (HR = 2.782, 95% CI: 1.531–5.052; P < 0.001). Additionally, when patients were stratified according to subgroups of stage III and tumor location, poor RFS and OS were also observed in the low PPP1R12A RCN group with significance (RFS: IIIB HR = 2.870, P < 0.001; colon HR = 1.910, P = 0.037; OS: IIIB HR = 3.527, P < 0.001; IIIC HR = 2.662, P = 0.049; rectum HR = 4.229, P = 0.002). Conclusion. Our findings suggest the copy number of PPP1R12A can independently predict recurrence and overall survival of stage III colorectal cancer patients receiving oxaliplatin-based chemotherapy. PMID:26113782

Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data

PubMed Central

2012-01-01

Background Dimensionality reduction (DR) enables the construction of a lower dimensional space (embedding) from a higher dimensional feature space while preserving object-class discriminability. However several popular DR approaches suffer from sensitivity to choice of parameters and/or presence of noise in the data. In this paper, we present a novel DR technique known as consensus embedding that aims to overcome these problems by generating and combining multiple low-dimensional embeddings, hence exploiting the variance among them in a manner similar to ensemble classifier schemes such as Bagging. We demonstrate theoretical properties of consensus embedding which show that it will result in a single stable embedding solution that preserves information more accurately as compared to any individual embedding (generated via DR schemes such as Principal Component Analysis, Graph Embedding, or Locally Linear Embedding). Intelligent sub-sampling (via mean-shift) and code parallelization are utilized to provide for an efficient implementation of the scheme. Results Applications of consensus embedding are shown in the context of classification and clustering as applied to: (1) image partitioning of white matter and gray matter on 10 different synthetic brain MRI images corrupted with 18 different combinations of noise and bias field inhomogeneity, (2) classification of 4 high-dimensional gene-expression datasets, (3) cancer detection (at a pixel-level) on 16 image slices obtained from 2 different high-resolution prostate MRI datasets. In over 200 different experiments concerning classification and segmentation of biomedical data, consensus embedding was found to consistently outperform both linear and non-linear DR methods within all applications considered. Conclusions We have presented a novel framework termed consensus embedding which leverages ensemble classification theory within dimensionality reduction, allowing for application to a wide range of high-dimensional biomedical data classification and segmentation problems. Our generalizable framework allows for improved representation and classification in the context of both imaging and non-imaging data. The algorithm offers a promising solution to problems that currently plague DR methods, and may allow for extension to other areas of biomedical data analysis. PMID:22316103

Damage sensing and mechanical characteristics of CFRP strengthened steel plate

NASA Astrophysics Data System (ADS)

Mieda, Genki; Nakano, Daiki; Fuji, Yuya; Nakamura, Hitoshi; Mizuno, Yosuke; Nakamura, Kentaro; Matsui, Takahiro; Ochi, Yutaka; Matsumoto, Yukihiro

2017-10-01

In recent years, a large number of structures that were built during the period of high economic growth in Japan is beginning to show signs of aging. For example, the structural performance of steel structures has degraded due to corrosion. One measure that has been proposed and studied to address this issue is the adhesive bonding method, which can be used to repair and reinforce these structures. However, this method produces brittle fracture in the adhesive layer and is difficult to maintain after bonding. To solve the problem faced by this method, a clarification of the mechanical properties inside the adhesive is necessary. Then this background, a fiber Bragg grating (FBG) sensor has been used in this study. This sensor can be embedded within the building material that needs repairing and reinforcing because an FBG sensor is extremely small. Eventually based on this, a three-point bending test of a carbon fiber reinforced plastic (CFRP) strengthened steel plate that was embedded with an FBG sensor was conducted. This paper demonstrates that an FBG sensor is effectively applicable for sensing when damage occurs.

Fault diagnosis and fault-tolerant finite control set-model predictive control of a multiphase voltage-source inverter supplying BLDC motor.

PubMed

Salehifar, Mehdi; Moreno-Equilaz, Manuel

2016-01-01

Due to its fault tolerance, a multiphase brushless direct current (BLDC) motor can meet high reliability demand for application in electric vehicles. The voltage-source inverter (VSI) supplying the motor is subjected to open circuit faults. Therefore, it is necessary to design a fault-tolerant (FT) control algorithm with an embedded fault diagnosis (FD) block. In this paper, finite control set-model predictive control (FCS-MPC) is developed to implement the fault-tolerant control algorithm of a five-phase BLDC motor. The developed control method is fast, simple, and flexible. A FD method based on available information from the control block is proposed; this method is simple, robust to common transients in motor and able to localize multiple open circuit faults. The proposed FD and FT control algorithm are embedded in a five-phase BLDC motor drive. In order to validate the theory presented, simulation and experimental results are conducted on a five-phase two-level VSI supplying a five-phase BLDC motor. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Evaluating the accuracy of the Wechsler Memory Scale-Fourth Edition (WMS-IV) logical memory embedded validity index for detecting invalid test performance.

PubMed

Soble, Jason R; Bain, Kathleen M; Bailey, K Chase; Kirton, Joshua W; Marceaux, Janice C; Critchfield, Edan A; McCoy, Karin J M; O'Rourke, Justin J F

2018-01-08

Embedded performance validity tests (PVTs) allow for continuous assessment of invalid performance throughout neuropsychological test batteries. This study evaluated the utility of the Wechsler Memory Scale-Fourth Edition (WMS-IV) Logical Memory (LM) Recognition score as an embedded PVT using the Advanced Clinical Solutions (ACS) for WAIS-IV/WMS-IV Effort System. This mixed clinical sample was comprised of 97 total participants, 71 of whom were classified as valid and 26 as invalid based on three well-validated, freestanding criterion PVTs. Overall, the LM embedded PVT demonstrated poor concordance with the criterion PVTs and unacceptable psychometric properties using ACS validity base rates (42% sensitivity/79% specificity). Moreover, 15-39% of participants obtained an invalid ACS base rate despite having a normatively-intact age-corrected LM Recognition total score. Receiving operating characteristic curve analysis revealed a Recognition total score cutoff of < 61% correct improved specificity (92%) while sensitivity remained weak (31%). Thus, results indicated the LM Recognition embedded PVT is not appropriate for use from an evidence-based perspective, and that clinicians may be faced with reconciling how a normatively intact cognitive performance on the Recognition subtest could simultaneously reflect invalid performance validity.

An Embedded Stress Sensor for Concrete SHM Based on Amorphous Ferromagnetic Microwires

PubMed Central

Olivera, Jesús; González, Margarita; Fuente, José Vicente; Varga, Rastislav; Zhukov, Arkady; Anaya, José Javier

2014-01-01

A new smart concrete aggregate design as a candidate for applications in structural health monitoring (SHM) of critical elements in civil infrastructure is proposed. The cement-based stress/strain sensor was developed by utilizing the stress/strain sensing properties of a magnetic microwire embedded in cement-based composite (MMCC). This is a contact-less type sensor that measures variations of magnetic properties resulting from stress variations. Sensors made of these materials can be designed to satisfy the specific demand for an economic way to monitor concrete infrastructure health. For this purpose, we embedded a thin magnetic microwire in the core of a cement-based cylinder, which was inserted into the concrete specimen under study as an extra aggregate. The experimental results show that the embedded MMCC sensor is capable of measuring internal compressive stress around the range of 1–30 MPa. Two stress sensing properties of the embedded sensor under uniaxial compression were studied: the peak amplitude and peak position of magnetic switching field. The sensitivity values for the amplitude and position within the measured range were 5 mV/MPa and 2.5 μs/MPa, respectively. PMID:25347582

A Novel Method for Block Size Forensics Based on Morphological Operations

NASA Astrophysics Data System (ADS)

Luo, Weiqi; Huang, Jiwu; Qiu, Guoping

Passive forensics analysis aims to find out how multimedia data is acquired and processed without relying on pre-embedded or pre-registered information. Since most existing compression schemes for digital images are based on block processing, one of the fundamental steps for subsequent forensics analysis is to detect the presence of block artifacts and estimate the block size for a given image. In this paper, we propose a novel method for blind block size estimation. A 2×2 cross-differential filter is first applied to detect all possible block artifact boundaries, morphological operations are then used to remove the boundary effects caused by the edges of the actual image contents, and finally maximum-likelihood estimation (MLE) is employed to estimate the block size. The experimental results evaluated on over 1300 nature images show the effectiveness of our proposed method. Compared with existing gradient-based detection method, our method achieves over 39% accuracy improvement on average.

Embedded Spherical Localization for Micro Underwater Vehicles Based on Attenuation of Electro-Magnetic Carrier Signals

PubMed Central

Duecker, Daniel-André; Geist, A. René; Hengeler, Michael; Kreuzer, Edwin; Pick, Marc-André; Rausch, Viktor; Solowjow, Eugen

2017-01-01

Self-localization is one of the most challenging problems for deploying micro autonomous underwater vehicles (μAUV) in confined underwater environments. This paper extends a recently-developed self-localization method that is based on the attenuation of electro-magnetic waves, to the μAUV domain. We demonstrate a compact, low-cost architecture that is able to perform all signal processing steps present in the original method. The system is passive with one-way signal transmission and scales to possibly large μAUV fleets. It is based on the spherical localization concept. We present results from static and dynamic position estimation experiments and discuss the tradeoffs of the system. PMID:28445419

Embedded Spherical Localization for Micro Underwater Vehicles Based on Attenuation of Electro-Magnetic Carrier Signals.

PubMed

Duecker, Daniel-André; Geist, A René; Hengeler, Michael; Kreuzer, Edwin; Pick, Marc-André; Rausch, Viktor; Solowjow, Eugen

2017-04-26

Self-localization is one of the most challenging problems for deploying micro autonomous underwater vehicles ( μ AUV) in confined underwater environments. This paper extends a recently-developed self-localization method that is based on the attenuation of electro-magnetic waves, to the μ AUV domain. We demonstrate a compact, low-cost architecture that is able to perform all signal processing steps present in the original method. The system is passive with one-way signal transmission and scales to possibly large μ AUV fleets. It is based on the spherical localization concept. We present results from static and dynamic position estimation experiments and discuss the tradeoffs of the system.

Dimensionality reduction of collective motion by principal manifolds

NASA Astrophysics Data System (ADS)

Gajamannage, Kelum; Butail, Sachit; Porfiri, Maurizio; Bollt, Erik M.

2015-01-01

While the existence of low-dimensional embedding manifolds has been shown in patterns of collective motion, the current battery of nonlinear dimensionality reduction methods is not amenable to the analysis of such manifolds. This is mainly due to the necessary spectral decomposition step, which limits control over the mapping from the original high-dimensional space to the embedding space. Here, we propose an alternative approach that demands a two-dimensional embedding which topologically summarizes the high-dimensional data. In this sense, our approach is closely related to the construction of one-dimensional principal curves that minimize orthogonal error to data points subject to smoothness constraints. Specifically, we construct a two-dimensional principal manifold directly in the high-dimensional space using cubic smoothing splines, and define the embedding coordinates in terms of geodesic distances. Thus, the mapping from the high-dimensional data to the manifold is defined in terms of local coordinates. Through representative examples, we show that compared to existing nonlinear dimensionality reduction methods, the principal manifold retains the original structure even in noisy and sparse datasets. The principal manifold finding algorithm is applied to configurations obtained from a dynamical system of multiple agents simulating a complex maneuver called predator mobbing, and the resulting two-dimensional embedding is compared with that of a well-established nonlinear dimensionality reduction method.

Development and optimisation of an HPLC-DAD-ESI-Q-ToF method for the determination of phenolic acids and derivatives.

PubMed

Restivo, Annalaura; Degano, Ilaria; Ribechini, Erika; Colombini, Maria Perla

2014-01-01

A method for the HPLC-MS/MS analysis of phenols, including phenolic acids and naphtoquinones, using an amide-embedded phase column was developed and compared to the literature methods based on classical C18 stationary phase columns. RP-Amide is a recently developed polar embedded stationary phase, whose wetting properties mean that up to 100% water can be used as an eluent. The increased retention and selectivity for polar compounds and the possibility of working in 100% water conditions make this column particularly interesting for the HPLC analysis of phenolic acids and derivatives. In this study, the chromatographic separation was optimised on an HPLC-DAD, and was used to separate 13 standard phenolic acids and derivatives. The method was validated on an HPLC-ESI-Q-ToF. The acquisition was performed in negative polarity and MS/MS target mode. Ionisation conditions and acquisition parameters for the Q-ToF detector were investigated by working on collision energies and fragmentor potentials. The performance of the method was fully evaluated on standards. Moreover, several raw materials containing phenols were analysed: walnut, gall, wine, malbec grape, French oak, red henna and propolis. Our method allowed us to characterize the phenolic composition in a wide range of matrices and to highlight possible matrix effects.

Seamless Assessment in Science: A Guide for Elementary & Middle School. Grades: K - 8

ERIC Educational Resources Information Center

National Science Teachers Association (NJ3), 2006

2006-01-01

When a classroom is opened to inquiry-based learning, teachers can no longer rely solely on traditional end-of-unit tests. "Seamless Assessment" is a one-stop guide to strategies that mirror the investigatory spirit. Working with the popular 5E model as an instructional framework, the authors have designed methods for embedding formative and…

Integrated, Project-Based Learning and Knowledge Retention: A Mixed Methods Study Comparing High School Students in Two Geometry Courses

ERIC Educational Resources Information Center

Canuteson, Ashley Dyanne

2017-01-01

The developing synergy of legislation and research throughout recent history points to the current momentum behind college and career readiness for every student. Researchers have found that embedding academic content into career education improves student learning. Integrated learning can vary in approach and style and can be adjusted to fit into…

A Communications Modeling System for Swarm-Based Sensors

DTIC Science & Technology

2003-09-01

6-10 6.6. Digital and Swarm System Performance Measures . . . . . . . . . . 6-21 7.1. Simulation computing hardware...detection and monitoring, and advances in computational capabilities have provided for embedded data analysis and the generation of information from raw... computing and manufacturing technology have made such systems possible. In order to harness this potential for Air Force applica- tions, a method of

Electrochromic nanocomposite films

DOEpatents

Milliron, Delia; Llordes, Anna; Buonsanti, Raffaella; Garcia, Guillermo

2018-04-10

The present invention provides an electrochromic nanocomposite film. In an exemplary embodiment, the electrochromic nanocomposite film, includes (1) a solid matrix of oxide based material and (2) transparent conducting oxide (TCO) nanostructures embedded in the matrix. In a further embodiment, the electrochromic nanocomposite film farther includes a substrate upon which the matrix is deposited. The present invention also provides a method of preparing an electrochromic nanocomposite film.

A novel image watermarking method based on singular value decomposition and digital holography

NASA Astrophysics Data System (ADS)

Cai, Zhishan

2016-10-01

According to the information optics theory, a novel watermarking method based on Fourier-transformed digital holography and singular value decomposition (SVD) is proposed in this paper. First of all, a watermark image is converted to a digital hologram using the Fourier transform. After that, the original image is divided into many non-overlapping blocks. All the blocks and the hologram are decomposed using SVD. The singular value components of the hologram are then embedded into the singular value components of each block using an addition principle. Finally, SVD inverse transformation is carried out on the blocks and hologram to generate the watermarked image. The watermark information embedded in each block is extracted at first when the watermark is extracted. After that, an averaging operation is carried out on the extracted information to generate the final watermark information. Finally, the algorithm is simulated. Furthermore, to test the encrypted image's resistance performance against attacks, various attack tests are carried out. The results show that the proposed algorithm has very good robustness against noise interference, image cut, compression, brightness stretching, etc. In particular, when the image is rotated by a large angle, the watermark information can still be extracted correctly.

Field Measurements and Numerical Simulations of Temperature and Moisture in Highway Engineering Using a Frequency Domain Reflectometry Sensor.

PubMed

Yao, Yong-Sheng; Zheng, Jian-Long; Chen, Zeng-Shun; Zhang, Jun-Hui; Li, Yong

2016-06-10

This paper presents a systematic pioneering study on the use of agricultural-purpose frequency domain reflectometry (FDR) sensors to monitor temperature and moisture of a subgrade in highway extension and reconstruction engineering. The principle of agricultural-purpose FDR sensors and the process for embedding this kind of sensors for subgrade engineering purposes are introduced. Based on field measured weather data, a numerical analysis model for temperature and moisture content in the subgrade's soil is built. Comparisons of the temperature and moisture data obtained from numerical simulation and FDR-based measurements are conducted. The results show that: (1) the embedding method and process, data acquisition, and remote transmission presented are reasonable; (2) the temperature and moisture changes are coordinated with the atmospheric environment and they are also in close agreement with numerical calculations; (3) the change laws of both are consistent at positions where the subgrade is compacted uniformly. These results suggest that the data measured by the agricultural-purpose FDR sensors are reliable. The findings of this paper enable a new and effective real-time monitoring method for a subgrade's temperature and moisture changes, and thus broaden the application of agricultural-purpose FDR sensors.

Quantized phase coding and connected region labeling for absolute phase retrieval.

PubMed

Chen, Xiangcheng; Wang, Yuwei; Wang, Yajun; Ma, Mengchao; Zeng, Chunnian

2016-12-12

This paper proposes an absolute phase retrieval method for complex object measurement based on quantized phase-coding and connected region labeling. A specific code sequence is embedded into quantized phase of three coded fringes. Connected regions of different codes are labeled and assigned with 3-digit-codes combining the current period and its neighbors. Wrapped phase, more than 36 periods, can be restored with reference to the code sequence. Experimental results verify the capability of the proposed method to measure multiple isolated objects.

Delivering spacecraft control centers with embedded knowledge-based systems: The methodology issue

NASA Technical Reports Server (NTRS)

Ayache, S.; Haziza, M.; Cayrac, D.

1994-01-01

Matra Marconi Space (MMS) occupies a leading place in Europe in the domain of satellite and space data processing systems. The maturity of the knowledge-based systems (KBS) technology, the theoretical and practical experience acquired in the development of prototype, pre-operational and operational applications, make it possible today to consider the wide operational deployment of KBS's in space applications. In this perspective, MMS has to prepare the introduction of the new methods and support tools that will form the basis of the development of such systems. This paper introduces elements of the MMS methodology initiatives in the domain and the main rationale that motivated the approach. These initiatives develop along two main axes: knowledge engineering methods and tools, and a hybrid method approach for coexisting knowledge-based and conventional developments.

Supervised embedding of textual predictors with applications in clinical diagnostics for pediatric cardiology.

PubMed

Perry, Thomas Ernest; Zha, Hongyuan; Zhou, Ke; Frias, Patricio; Zeng, Dadan; Braunstein, Mark

2014-02-01

Electronic health records possess critical predictive information for machine-learning-based diagnostic aids. However, many traditional machine learning methods fail to simultaneously integrate textual data into the prediction process because of its high dimensionality. In this paper, we present a supervised method using Laplacian Eigenmaps to enable existing machine learning methods to estimate both low-dimensional representations of textual data and accurate predictors based on these low-dimensional representations at the same time. We present a supervised Laplacian Eigenmap method to enhance predictive models by embedding textual predictors into a low-dimensional latent space, which preserves the local similarities among textual data in high-dimensional space. The proposed implementation performs alternating optimization using gradient descent. For the evaluation, we applied our method to over 2000 patient records from a large single-center pediatric cardiology practice to predict if patients were diagnosed with cardiac disease. In our experiments, we consider relatively short textual descriptions because of data availability. We compared our method with latent semantic indexing, latent Dirichlet allocation, and local Fisher discriminant analysis. The results were assessed using four metrics: the area under the receiver operating characteristic curve (AUC), Matthews correlation coefficient (MCC), specificity, and sensitivity. The results indicate that supervised Laplacian Eigenmaps was the highest performing method in our study, achieving 0.782 and 0.374 for AUC and MCC, respectively. Supervised Laplacian Eigenmaps showed an increase of 8.16% in AUC and 20.6% in MCC over the baseline that excluded textual data and a 2.69% and 5.35% increase in AUC and MCC, respectively, over unsupervised Laplacian Eigenmaps. As a solution, we present a supervised Laplacian Eigenmap method to embed textual predictors into a low-dimensional Euclidean space. This method allows many existing machine learning predictors to effectively and efficiently capture the potential of textual predictors, especially those based on short texts.

The impact of embedded support for underprepared students in a college chemistry course

NASA Astrophysics Data System (ADS)

Hesser, Tiffany L.

This quasi-experimental study examined the impact of embedded support on academic success for students requiring remediation in college chemistry. Additional support for underprepared students incorporated within a course is recommended by Connecticut's Public Act 12-40, An Act Concerning College Readiness and Completion. For this study, embedded support consisted of weekly instructional support sessions and introduced the concepts of metacognitive awareness and motivation in learning. Students' progression through the course was measured using a series of standardized questions. Metacognitive awareness and motivation levels were measure at the start and completion of the semester using the Metacognitive Awareness Inventory (MAI) and Motivated Student Learning Questionnaire (MSLQ). It was found that with embedded support, underprepared students performed academically at a level equivalent to that of their college-ready peers. Based on these results, this embedded support model as an evidence-based practice should be considered in class development or policies surrounding students identified as underprepared.

Quantum Watermarking Scheme Based on INEQR

NASA Astrophysics Data System (ADS)

Zhou, Ri-Gui; Zhou, Yang; Zhu, Changming; Wei, Lai; Zhang, Xiafen; Ian, Hou

2018-04-01

Quantum watermarking technology protects copyright by embedding invisible quantum signal in quantum multimedia data. In this paper, a watermarking scheme based on INEQR was presented. Firstly, the watermark image is extended to achieve the requirement of embedding carrier image. Secondly, the swap and XOR operation is used on the processed pixels. Since there is only one bit per pixel, XOR operation can achieve the effect of simple encryption. Thirdly, both the watermark image extraction and embedding operations are described, where the key image, swap operation and LSB algorithm are used. When the embedding is made, the binary image key is changed. It means that the watermark has been embedded. Of course, if the watermark image is extracted, the key's state need detected. When key's state is |1>, this extraction operation is carried out. Finally, for validation of the proposed scheme, both the Signal-to-noise ratio (PSNR) and the security of the scheme are analyzed.

Robust and Blind 3D Mesh Watermarking in Spatial Domain Based on Faces Categorization and Sorting

NASA Astrophysics Data System (ADS)

Molaei, Amir Masoud; Ebrahimnezhad, Hossein; Sedaaghi, Mohammad Hossein

2016-06-01

In this paper, a 3D watermarking algorithm in spatial domain is presented with blind detection. In the proposed method, a negligible visual distortion is observed in host model. Initially, a preprocessing is applied on the 3D model to make it robust against geometric transformation attacks. Then, a number of triangle faces are determined as mark triangles using a novel systematic approach in which faces are categorized and sorted robustly. In order to enhance the capability of information retrieval by attacks, block watermarks are encoded using Reed-Solomon block error-correcting code before embedding into the mark triangles. Next, the encoded watermarks are embedded in spherical coordinates. The proposed method is robust against additive noise, mesh smoothing and quantization attacks. Also, it is stout next to geometric transformation, vertices and faces reordering attacks. Moreover, the proposed algorithm is designed so that it is robust against the cropping attack. Simulation results confirm that the watermarked models confront very low distortion if the control parameters are selected properly. Comparison with other methods demonstrates that the proposed method has good performance against the mesh smoothing attacks.

Persistent topological features of dynamical systems

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

Maletić, Slobodan, E-mail: slobodan@hitsz.edu.cn; Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade; Zhao, Yi, E-mail: zhao.yi@hitsz.edu.cn

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

The Preparation of Gelatine-Embedded Soil and Litter Sections and Their Application to Some Soil Ecological Studies.

ERIC Educational Resources Information Center

Anderson, J. M.

1978-01-01

A method is described for preparing large gelatine-embedded soil sections for ecological studies. Sampling methods reduce structural disturbance of the samples to a minimum and include freezing the samples in the field to kill soil invertebrates in their natural microhabitats. Projects are suggested for upper secondary school students. (Author/BB)

Reliability Validation and Improvement Framework

DTIC Science & Technology

2012-11-01

systems . Steps in that direction include the use of the Architec- ture Tradeoff Analysis Method ® (ATAM®) developed at the Carnegie Mellon...embedded software • cyber - physical systems (CPSs) to indicate that the embedded software interacts with, manag - es, and controls a physical system [Lee...the use of formal static analysis methods to increase our confidence in system operation beyond testing. However, analysis results

Incremental isometric embedding of high-dimensional data using connected neighborhood graphs.

PubMed

Zhao, Dongfang; Yang, Li

2009-01-01

Most nonlinear data embedding methods use bottom-up approaches for capturing the underlying structure of data distributed on a manifold in high dimensional space. These methods often share the first step which defines neighbor points of every data point by building a connected neighborhood graph so that all data points can be embedded to a single coordinate system. These methods are required to work incrementally for dimensionality reduction in many applications. Because input data stream may be under-sampled or skewed from time to time, building connected neighborhood graph is crucial to the success of incremental data embedding using these methods. This paper presents algorithms for updating $k$-edge-connected and $k$-connected neighborhood graphs after a new data point is added or an old data point is deleted. It further utilizes a simple algorithm for updating all-pair shortest distances on the neighborhood graph. Together with incremental classical multidimensional scaling using iterative subspace approximation, this paper devises an incremental version of Isomap with enhancements to deal with under-sampled or unevenly distributed data. Experiments on both synthetic and real-world data sets show that the algorithm is efficient and maintains low dimensional configurations of high dimensional data under various data distributions.

Accelerating wavefunction in density-functional-theory embedding by truncating the active basis set

NASA Astrophysics Data System (ADS)

Bennie, Simon J.; Stella, Martina; Miller, Thomas F.; Manby, Frederick R.

2015-07-01

Methods where an accurate wavefunction is embedded in a density-functional description of the surrounding environment have recently been simplified through the use of a projection operator to ensure orthogonality of orbital subspaces. Projector embedding already offers significant performance gains over conventional post-Hartree-Fock methods by reducing the number of correlated occupied orbitals. However, in our first applications of the method, we used the atomic-orbital basis for the full system, even for the correlated wavefunction calculation in a small, active subsystem. Here, we further develop our method for truncating the atomic-orbital basis to include only functions within or close to the active subsystem. The number of atomic orbitals in a calculation on a fixed active subsystem becomes asymptotically independent of the size of the environment, producing the required O ( N 0 ) scaling of cost of the calculation in the active subsystem, and accuracy is controlled by a single parameter. The applicability of this approach is demonstrated for the embedded many-body expansion of binding energies of water hexamers and calculation of reaction barriers of SN2 substitution of fluorine by chlorine in α-fluoroalkanes.

Measurement of longitudinal strain and estimation of peel stress in adhesive-bonded single-lap joint of CFRP adherend using embedded FBG sensor

NASA Astrophysics Data System (ADS)

Ning, X.; Murayama, H.; Kageyama, K.; Uzawa, K.; Wada, D.

2012-04-01

In this research, longitudinal strain and peel stress in adhesive-bonded single-lap joint of carbon fiber reinforced plastics (CFRP) were measured and estimated by embedded fiber Bragg grating (FBG) sensor. Two unidirectional CFRP substrates were bonded by epoxy to form a single-lap configuration. The distributed strain measurement system is used. It is based on optical frequency domain reflectometry (OFDR), which can provide measurement at an arbitrary position along FBG sensors with the high spatial resolution. The longitudinal strain was measured based on Bragg grating effect and the peel stress was estimated based on birefringence effect. Special manufacturing procedure was developed to ensure the embedded location of FBG sensor. A portion of the FBG sensor was embedded into one of CFRP adherends along fiber direction and another portion was kept free for temperature compensation. Photomicrograph of cross-section of specimen was taken to verify the sensor was embedded into proper location after adherend curing. The residual strain was monitored during specimen curing and adhesive joint bonding process. Tensile tests were carried out and longitudinal strain and peel stress of the bondline are measured and estimated by the embedded FBG sensor. A two-dimensional geometrically nonlinear finite element analysis was performed by ANSYS to evaluate the measurement precision.

ETHERNET BASED EMBEDDED SYSTEM FOR FEL DIAGNOSTICS AND CONTROLS

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

Jianxun Yan; Daniel Sexton; Steven Moore

2006-10-24

An Ethernet based embedded system has been developed to upgrade the Beam Viewer and Beam Position Monitor (BPM) systems within the free-electron laser (FEL) project at Jefferson Lab. The embedded microcontroller was mounted on the front-end I/O cards with software packages such as Experimental Physics and Industrial Control System (EPICS) and Real Time Executive for Multiprocessor System (RTEMS) running as an Input/Output Controller (IOC). By cross compiling with the EPICS, the RTEMS kernel, IOC device supports, and databases all of these can be downloaded into the microcontroller. The first version of the BPM electronics based on the embedded controller wasmore » built and is currently running in our FEL system. The new version of BPM that will use a Single Board IOC (SBIOC), which integrates with an Field Programming Gate Array (FPGA) and a ColdFire embedded microcontroller, is presently under development. The new system has the features of a low cost IOC, an open source real-time operating system, plug&play-like ease of installation and flexibility, and provides a much more localized solution.« less

The application of polyethylene glycol (PEG) to electron microscopy

PubMed Central

1980-01-01

The cytoplasm of cells from a variety of tissues has been viewed in sections (0.25-1 micrometers) devoid of any embedding resin. Glutaraldehyde- and osmium tetroxide-fixed tissues were infiltrated and embedded in a water-miscible wax, polyethylene glycol (PEG), and subsequently sectioned on dry glass or diamond knives. The PEG matrix was removed and the sections were placed on Formvarcarbon-polylysine- coated grids, dehydrated, dried by the critical-point method, and observed in either the high- or low-voltage electron microscope. Stereoscopic views of cells devoid of embedding resin present an image of cell utrastructure unobscured by electron-scattering resins similar to the image of whole, unembedded critical-point-dried or freeze-dried cultured cells observed by transmission electron microscopy. All organelles, including the cytoskeletal structures, are identified and appear not to have been damaged during processing, although membrane components appear somewhat less distinct. The absence of an embedding matrix eliminates the need for additional staining to increase contrast, unlike the situation with specimens embedded in standard electron-scattering resins. The PEG technique thus appears to be a valuable adjunct to conventional methods for ultrastructural analysis. PMID:7400222

The application of polyethylene glycol (PEG) to electron microscopy.

PubMed

Wolosewick, J J

1980-08-01

The cytoplasm of cells from a variety of tissues has been viewed in sections (0.25-1 micrometers) devoid of any embedding resin. Glutaraldehyde- and osmium tetroxide-fixed tissues were infiltrated and embedded in a water-miscible wax, polyethylene glycol (PEG), and subsequently sectioned on dry glass or diamond knives. The PEG matrix was removed and the sections were placed on Formvarcarbon-polylysine-coated grids, dehydrated, dried by the critical-point method, and observed in either the high- or low-voltage electron microscope. Stereoscopic views of cells devoid of embedding resin present an image of cell utrastructure unobscured by electron-scattering resins similar to the image of whole, unembedded critical-point-dried or freeze-dried cultured cells observed by transmission electron microscopy. All organelles, including the cytoskeletal structures, are identified and appear not to have been damaged during processing, although membrane components appear somewhat less distinct. The absence of an embedding matrix eliminates the need for additional staining to increase contrast, unlike the situation with specimens embedded in standard electron-scattering resins. The PEG technique thus appears to be a valuable adjunct to conventional methods for ultrastructural analysis.

Research on self-calibration biaxial autocollimator based on ZYNQ

NASA Astrophysics Data System (ADS)

Guo, Pan; Liu, Bingguo; Liu, Guodong; Zhong, Yao; Lu, Binghui

2018-01-01

Autocollimators are mainly based on computers or the electronic devices that can be connected to the internet, and its precision, measurement range and resolution are all defective, and external displays are needed to display images in real time. What's more, there is no real-time calibration for autocollimator in the market. In this paper, we propose a biaxial autocollimator based on the ZYNQ embedded platform to solve the above problems. Firstly, the traditional optical system is improved and a light path is added for real-time calibration. Then, in order to improve measurement speed, the embedded platform based on ZYNQ that combines Linux operating system with autocollimator is designed. In this part, image acquisition, image processing, image display and the man-machine interaction interface based on Qt are achieved. Finally, the system realizes two-dimensional small angle measurement. Experimental results showed that the proposed method can improve the angle measurement accuracy. The standard deviation of the close distance (1.5m) is 0.15" in horizontal direction of image and 0.24"in vertical direction, the repeatability of measurement of the long distance (10m) is improved by 0.12 in horizontal direction of image and 0.3 in vertical direction.

Advanced microprocessor based power protection system using artificial neural network techniques

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

Chen, Z.; Kalam, A.; Zayegh, A.

This paper describes an intelligent embedded microprocessor based system for fault classification in power system protection system using advanced 32-bit microprocessor technology. The paper demonstrates the development of protective relay to provide overcurrent protection schemes for fault detection. It also describes a method for power fault classification in three-phase system based on the use of neural network technology. The proposed design is implemented and tested on a single line three phase power system in power laboratory. Both the hardware and software development are described in detail.

Low-dimensional approximation searching strategy for transfer entropy from non-uniform embedding

PubMed Central

2018-01-01

Transfer entropy from non-uniform embedding is a popular tool for the inference of causal relationships among dynamical subsystems. In this study we present an approach that makes use of low-dimensional conditional mutual information quantities to decompose the original high-dimensional conditional mutual information in the searching procedure of non-uniform embedding for significant variables at different lags. We perform a series of simulation experiments to assess the sensitivity and specificity of our proposed method to demonstrate its advantage compared to previous algorithms. The results provide concrete evidence that low-dimensional approximations can help to improve the statistical accuracy of transfer entropy in multivariate causality analysis and yield a better performance over other methods. The proposed method is especially efficient as the data length grows. PMID:29547669

Excitons in Potassium Bromide: A Study using Embedded Time-dependent Density Functional Theory and Equation-of-Motion Coupled Cluster Methods

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

Govind, Niranjan; Sushko, Petr V.; Hess, Wayne P.

2009-03-05

We present a study of the electronic excitations in insulating materials using an embedded- cluster method. The excited states of the embedded cluster are studied systematically using time-dependent density functional theory (TDDFT) and high-level equation-of-motion coupled cluster (EOMCC) methods. In particular, we have used EOMCC models with singles and doubles (EOMCCSD) and two approaches which account for the e®ect of triply excited con¯gurations in non-iterative and iterative fashions. We present calculations of the lowest surface excitations of the well-studied potassium bromide (KBr) system and compare our results with experiment. The bulk-surface exciton shift is also calculated at the TDDFT levelmore » and compared with experiment.« less

Embedded Palmprint Recognition System Using OMAP 3530

PubMed Central

Shen, Linlin; Wu, Shipei; Zheng, Songhao; Ji, Zhen

2012-01-01

We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the ccentral pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance. PMID:22438721