Volume 39, Issue 9, Pages 763-864(30 July 2002)
Research Article
Embedded turbulence model in numerical methods for hyperbolic conservation laws
NASA Astrophysics Data System (ADS)
Drikakis, D.
2002-07-01
The paper describes the use of numerical methods for hyperbolic conservation laws as an embedded turbulence modelling approach. Different Godunov-type schemes are utilized in computations of Burgers' turbulence and a two-dimensional mixing layer. The schemes include a total variation diminishing, characteristic-based scheme which is developed in this paper using the flux limiter approach. The embedded turbulence modelling property of the above methods is demonstrated through coarsely resolved large eddy simulations with and without subgrid scale models. Copyright
Gait Characteristic Analysis and Identification Based on the iPhone's Accelerometer and Gyrometer
Sun, Bing; Wang, Yang; Banda, Jacob
2014-01-01
Gait identification is a valuable approach to identify humans at a distance. In this paper, gait characteristics are analyzed based on an iPhone's accelerometer and gyrometer, and a new approach is proposed for gait identification. Specifically, gait datasets are collected by the triaxial accelerometer and gyrometer embedded in an iPhone. Then, the datasets are processed to extract gait characteristic parameters which include gait frequency, symmetry coefficient, dynamic range and similarity coefficient of characteristic curves. Finally, a weighted voting scheme dependent upon the gait characteristic parameters is proposed for gait identification. Four experiments are implemented to validate the proposed scheme. The attitude and acceleration solutions are verified by simulation. Then the gait characteristics are analyzed by comparing two sets of actual data, and the performance of the weighted voting identification scheme is verified by 40 datasets of 10 subjects. PMID:25222034
Small Private Key PKS on an Embedded Microprocessor
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.
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.
Simplifying the representation of complex free-energy landscapes using sketch-map
Ceriotti, Michele; Tribello, Gareth A.; Parrinello, Michele
2011-01-01
A new scheme, sketch-map, for obtaining a low-dimensional representation of the region of phase space explored during an enhanced dynamics simulation is proposed. We show evidence, from an examination of the distribution of pairwise distances between frames, that some features of the free-energy surface are inherently high-dimensional. This makes dimensionality reduction problematic because the data does not satisfy the assumptions made in conventional manifold learning algorithms We therefore propose that when dimensionality reduction is performed on trajectory data one should think of the resultant embedding as a quickly sketched set of directions rather than a road map. In other words, the embedding tells one about the connectivity between states but does not provide the vectors that correspond to the slow degrees of freedom. This realization informs the development of sketch-map, which endeavors to reproduce the proximity information from the high-dimensionality description in a space of lower dimensionality even when a faithful embedding is not possible. PMID:21730167
Watermarking scheme for authentication of compressed image
NASA Astrophysics Data System (ADS)
Hsieh, Tsung-Han; Li, Chang-Tsun; Wang, Shuo
2003-11-01
As images are commonly transmitted or stored in compressed form such as JPEG, to extend the applicability of our previous work, a new scheme for embedding watermark in compressed domain without resorting to cryptography is proposed. In this work, a target image is first DCT transformed and quantised. Then, all the coefficients are implicitly watermarked in order to minimize the risk of being attacked on the unwatermarked coefficients. The watermarking is done through registering/blending the zero-valued coefficients with a binary sequence to create the watermark and involving the unembedded coefficients during the process of embedding the selected coefficients. The second-order neighbors and the block itself are considered in the process of the watermark embedding in order to thwart different attacks such as cover-up, vector quantisation, and transplantation. The experiments demonstrate the capability of the proposed scheme in thwarting local tampering, geometric transformation such as cropping, and common signal operations such as lowpass filtering.
Quantum decimation in Hilbert space: Coarse graining without structure
NASA Astrophysics Data System (ADS)
Singh, Ashmeet; Carroll, Sean M.
2018-03-01
We present a technique to coarse grain quantum states in a finite-dimensional Hilbert space. Our method is distinguished from other approaches by not relying on structures such as a preferred factorization of Hilbert space or a preferred set of operators (local or otherwise) in an associated algebra. Rather, we use the data corresponding to a given set of states, either specified independently or constructed from a single state evolving in time. Our technique is based on principle component analysis (PCA), and the resulting coarse-grained quantum states live in a lower-dimensional Hilbert space whose basis is defined using the underlying (isometric embedding) transformation of the set of fine-grained states we wish to coarse grain. Physically, the transformation can be interpreted to be an "entanglement coarse-graining" scheme that retains most of the global, useful entanglement structure of each state, while needing fewer degrees of freedom for its reconstruction. This scheme could be useful for efficiently describing collections of states whose number is much smaller than the dimension of Hilbert space, or a single state evolving over time.
Etch Profile Simulation Using Level Set Methods
NASA Technical Reports Server (NTRS)
Hwang, Helen H.; Meyyappan, Meyya; Arnold, James O. (Technical Monitor)
1997-01-01
Etching and deposition of materials are critical steps in semiconductor processing for device manufacturing. Both etching and deposition may have isotropic and anisotropic components, due to directional sputtering and redeposition of materials, for example. Previous attempts at modeling profile evolution have used so-called "string theory" to simulate the moving solid-gas interface between the semiconductor and the plasma. One complication of this method is that extensive de-looping schemes are required at the profile corners. We will present a 2D profile evolution simulation using level set theory to model the surface. (1) By embedding the location of the interface in a field variable, the need for de-looping schemes is eliminated and profile corners are more accurately modeled. This level set profile evolution model will calculate both isotropic and anisotropic etch and deposition rates of a substrate in low pressure (10s mTorr) plasmas, considering the incident ion energy angular distribution functions and neutral fluxes. We will present etching profiles of Si substrates in Ar/Cl2 discharges for various incident ion energies and trench geometries.
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.
Force Field for Water Based on Neural Network.
Wang, Hao; Yang, Weitao
2018-05-18
We developed a novel neural network based force field for water based on training with high level ab initio theory. The force field was built based on electrostatically embedded many-body expansion method truncated at binary interactions. Many-body expansion method is a common strategy to partition the total Hamiltonian of large systems into a hierarchy of few-body terms. Neural networks were trained to represent electrostatically embedded one-body and two-body interactions, which require as input only one and two water molecule calculations at the level of ab initio electronic structure method CCSD/aug-cc-pVDZ embedded in the molecular mechanics water environment, making it efficient as a general force field construction approach. Structural and dynamic properties of liquid water calculated with our force field show good agreement with experimental results. We constructed two sets of neural network based force fields: non-polarizable and polarizable force fields. Simulation results show that the non-polarizable force field using fixed TIP3P charges has already behaved well, since polarization effects and many-body effects are implicitly included due to the electrostatic embedding scheme. Our results demonstrate that the electrostatically embedded many-body expansion combined with neural network provides a promising and systematic way to build the next generation force fields at high accuracy and low computational costs, especially for large systems.
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
NASA Astrophysics Data System (ADS)
Viswanath, Satish; Tiwari, Pallavi; Rosen, Mark; Madabhushi, Anant
2008-03-01
Recently, in vivo Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) have emerged as promising new modalities to aid in prostate cancer (CaP) detection. MRI provides anatomic and structural information of the prostate while MRS provides functional data pertaining to biochemical concentrations of metabolites such as creatine, choline and citrate. We have previously presented a hierarchical clustering scheme for CaP detection on in vivo prostate MRS and have recently developed a computer-aided method for CaP detection on in vivo prostate MRI. In this paper we present a novel scheme to develop a meta-classifier to detect CaP in vivo via quantitative integration of multimodal prostate MRS and MRI by use of non-linear dimensionality reduction (NLDR) methods including spectral clustering and locally linear embedding (LLE). Quantitative integration of multimodal image data (MRI and PET) involves the concatenation of image intensities following image registration. However multimodal data integration is non-trivial when the individual modalities include spectral and image intensity data. We propose a data combination solution wherein we project the feature spaces (image intensities and spectral data) associated with each of the modalities into a lower dimensional embedding space via NLDR. NLDR methods preserve the relationships between the objects in the original high dimensional space when projecting them into the reduced low dimensional space. Since the original spectral and image intensity data are divorced from their original physical meaning in the reduced dimensional space, data at the same spatial location can be integrated by concatenating the respective embedding vectors. Unsupervised consensus clustering is then used to partition objects into different classes in the combined MRS and MRI embedding space. Quantitative results of our multimodal computer-aided diagnosis scheme on 16 sets of patient data obtained from the ACRIN trial, for which corresponding histological ground truth for spatial extent of CaP is known, show a marginally higher sensitivity, specificity, and positive predictive value compared to corresponding CAD results with the individual modalities.
NASA Astrophysics Data System (ADS)
Alapaty, K.; Zhang, G. J.; Song, X.; Kain, J. S.; Herwehe, J. A.
2012-12-01
Short lived pollutants such as aerosols play an important role in modulating not only the radiative balance but also cloud microphysical properties and precipitation rates. In the past, to understand the interactions of aerosols with clouds, several cloud-resolving modeling studies were conducted. These studies indicated that in the presence of anthropogenic aerosols, single-phase deep convection precipitation is reduced or suppressed. On the other hand, anthropogenic aerosol pollution led to enhanced precipitation for mixed-phase deep convective clouds. To date, there have not been many efforts to incorporate such aerosol indirect effects (AIE) in mesoscale models or global models that use parameterization schemes for deep convection. Thus, the objective of this work is to implement a diagnostic cloud microphysical scheme directly into a deep convection parameterization facilitating aerosol indirect effects in the WRF-CMAQ integrated modeling systems. Major research issues addressed in this study are: What is the sensitivity of a deep convection scheme to cloud microphysical processes represented by a bulk double-moment scheme? How close are the simulated cloud water paths as compared to observations? Does increased aerosol pollution lead to increased precipitation for mixed-phase clouds? These research questions are addressed by performing several WRF simulations using the Kain-Fritsch convection parameterization and a diagnostic cloud microphysical scheme. In the first set of simulations (control simulations) the WRF model is used to simulate two scenarios of deep convection over the continental U.S. during two summer periods at 36 km grid resolution. In the second set, these simulations are repeated after incorporating a diagnostic cloud microphysical scheme to study the impacts of inclusion of cloud microphysical processes. Finally, in the third set, aerosol concentrations simulated by the CMAQ modeling system are supplied to the embedded cloud microphysical scheme to study impacts of aerosol concentrations on precipitation and radiation fields. Observations available from the ARM microbase data, the SURFRAD network, GOES imagery, and other reanalysis and measurements will be used to analyze the impacts of a cloud microphysical scheme and aerosol concentrations on parameterized convection.
Watermarking protocols for authentication and ownership protection based on timestamps and holograms
NASA Astrophysics Data System (ADS)
Dittmann, Jana; Steinebach, Martin; Croce Ferri, Lucilla
2002-04-01
Digital watermarking has become an accepted technology for enabling multimedia protection schemes. One problem here is the security of these schemes. Without a suitable framework, watermarks can be replaced and manipulated. We discuss different protocols providing security against rightful ownership attacks and other fraud attempts. We compare the characteristics of existing protocols for different media like direct embedding or seed based and required attributes of the watermarking technology like robustness or payload. We introduce two new media independent protocol schemes for rightful ownership authentication. With the first scheme we ensure security of digital watermarks used for ownership protection with a combination of two watermarks: first watermark of the copyright holder and a second watermark from a Trusted Third Party (TTP). It is based on hologram embedding and the watermark consists of e.g. a company logo. As an example we use digital images and specify the properties of the embedded additional security information. We identify components necessary for the security protocol like timestamp, PKI and cryptographic algorithms. The second scheme is used for authentication. It is designed for invertible watermarking applications which require high data integrity. We combine digital signature schemes and digital watermarking to provide a public verifiable integrity. The original data can only be reproduced with a secret key. Both approaches provide solutions for copyright and authentication watermarking and are introduced for image data but can be easily adopted for video and audio data as well.
Principled design for an integrated computational environment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Disessa, A.A.
Boxer is a computer language designed to be the base of an integrated computational environment providing a broad array of functionality -- from text editing to programming -- for naive and novice users. It stands in the line of Lisp inspired languages (Lisp, Logo, Scheme), but differs from these in achieving much of its understandability from pervasive use of a spatial metaphor reinforced through suitable graphics. This paper describes a set of learnability and understandability issues first and then uses them to motivate design decisions made concerning Boxer and the environment in which it is embedded.
Tokuda, T; Yamada, H; Sasagawa, K; Ohta, J
2009-10-01
This paper proposes and demonstrates a polarization-analyzing CMOS sensor based on image sensor architecture. The sensor was designed targeting applications for chiral analysis in a microchemistry system. The sensor features a monolithically embedded polarizer. Embedded polarizers with different angles were implemented to realize a real-time absolute measurement of the incident polarization angle. Although the pixel-level performance was confirmed to be limited, estimation schemes based on the variation of the polarizer angle provided a promising performance for real-time polarization measurements. An estimation scheme using 180 pixels in a 1deg step provided an estimation accuracy of 0.04deg. Polarimetric measurements of chiral solutions were also successfully performed to demonstrate the applicability of the sensor to optical chiral analysis.
Spatial-frequency composite watermarking for digital image copyright protection
NASA Astrophysics Data System (ADS)
Su, Po-Chyi; Kuo, C.-C. Jay
2000-05-01
Digital watermarks can be classified into two categories according to the embedding and retrieval domain, i.e. spatial- and frequency-domain watermarks. Because the two watermarks have different characteristics and limitations, combination of them can have various interesting properties when applied to different applications. In this research, we examine two spatial-frequency composite watermarking schemes. In both cases, a frequency-domain watermarking technique is applied as a baseline structure in the system. The embedded frequency- domain watermark is robust against filtering and compression. A spatial-domain watermarking scheme is then built to compensate some deficiency of the frequency-domain scheme. The first composite scheme is to embed a robust watermark in images to convey copyright or author information. The frequency-domain watermark contains owner's identification number while the spatial-domain watermark is embedded for image registration to resist cropping attack. The second composite scheme is to embed fragile watermark for image authentication. The spatial-domain watermark helps in locating the tampered part of the image while the frequency-domain watermark indicates the source of the image and prevents double watermarking attack. Experimental results show that the two watermarks do not interfere with each other and different functionalities can be achieved. Watermarks in both domains are detected without resorting to the original image. Furthermore, the resulting watermarked image can still preserve high fidelity without serious visual degradation.
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.
Schlorhaufer, C; Behrends, M; Diekhaus, G; Keberle, M; Weidemann, J
2012-12-01
Due to the time factor in polytraumatized patients all relevant pathologies in a polytrauma computed tomography (CT) scan have to be read and communicated very quickly. During radiology residency acquisition of effective reading schemes based on typical polytrauma pathologies is very important. Thus, an online tutorial for the structured diagnosis of polytrauma CT was developed. Based on current multimedia theories like the cognitive load theory a didactic concept was developed. As a web-environment the learning management system ILIAS was chosen. CT data sets were converted into online scrollable QuickTime movies. Audiovisual tutorial movies with guided image analyses by a consultant radiologist were recorded. The polytrauma tutorial consists of chapterized text content and embedded interactive scrollable CT data sets. Selected trauma pathologies are demonstrated to the user by guiding tutor movies. Basic reading schemes are communicated with the help of detailed commented movies of normal data sets. Common and important pathologies could be explored in a self-directed manner. Ambitious didactic concepts can be supported by a web based application on the basis of cognitive load theory and currently available software tools. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
