Quantization of Electromagnetic Fields in Cavities

NASA Technical Reports Server (NTRS)

Kakazu, Kiyotaka; Oshiro, Kazunori

1996-01-01

A quantization procedure for the electromagnetic field in a rectangular cavity with perfect conductor walls is presented, where a decomposition formula of the field plays an essential role. All vector mode functions are obtained by using the decomposition. After expanding the field in terms of the vector mode functions, we get the quantized electromagnetic Hamiltonian.

Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

PubMed Central

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality. PMID:23049544

Medical image compression based on vector quantization with variable block sizes in wavelet domain.

PubMed

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.

Detecting double compressed MPEG videos with the same quantization matrix and synchronized group of pictures structure

NASA Astrophysics Data System (ADS)

Aghamaleki, Javad Abbasi; Behrad, Alireza

2018-01-01

Double compression detection is a crucial stage in digital image and video forensics. However, the detection of double compressed videos is challenging when the video forger uses the same quantization matrix and synchronized group of pictures (GOP) structure during the recompression history to conceal tampering effects. A passive approach is proposed for detecting double compressed MPEG videos with the same quantization matrix and synchronized GOP structure. To devise the proposed algorithm, the effects of recompression on P frames are mathematically studied. Then, based on the obtained guidelines, a feature vector is proposed to detect double compressed frames on the GOP level. Subsequently, sparse representations of the feature vectors are used for dimensionality reduction and enrich the traces of recompression. Finally, a support vector machine classifier is employed to detect and localize double compression in temporal domain. The experimental results show that the proposed algorithm achieves the accuracy of more than 95%. In addition, the comparisons of the results of the proposed method with those of other methods reveal the efficiency of the proposed algorithm.

A Heisenberg Algebra Bundle of a Vector Field in Three-Space and its Weyl Quantization

NASA Astrophysics Data System (ADS)

Binz, Ernst; Pods, Sonja

2006-01-01

In these notes we associate a natural Heisenberg group bundle Ha with a singularity free smooth vector field X = (id,a) on a submanifold M in a Euclidean three-space. This bundle yields naturally an infinite dimensional Heisenberg group HX∞. A representation of the C*-group algebra of HX∞ is a quantization. It causes a natural Weyl-deformation quantization of X. The influence of the topological structure of M on this quantization is encoded in the Chern class of a canonical complex line bundle inside Ha.

Global synchronization of complex dynamical networks through digital communication with limited data rate.

PubMed

Wang, Yan-Wu; Bian, Tao; Xiao, Jiang-Wen; Wen, Changyun

2015-10-01

This paper studies the global synchronization of complex dynamical network (CDN) under digital communication with limited bandwidth. To realize the digital communication, the so-called uniform-quantizer-sets are introduced to quantize the states of nodes, which are then encoded and decoded by newly designed encoders and decoders. To meet the requirement of the bandwidth constraint, a scaling function is utilized to guarantee the quantizers having bounded inputs and thus achieving bounded real-time quantization levels. Moreover, a new type of vector norm is introduced to simplify the expression of the bandwidth limit. Through mathematical induction, a sufficient condition is derived to ensure global synchronization of the CDNs. The lower bound on the sum of the real-time quantization levels is analyzed for different cases. Optimization method is employed to relax the requirements on the network topology and to determine the minimum of such lower bound for each case, respectively. Simulation examples are also presented to illustrate the established results.

Vector quantizer designs for joint compression and terrain categorization of multispectral imagery

NASA Technical Reports Server (NTRS)

Gorman, John D.; Lyons, Daniel F.

1994-01-01

Two vector quantizer designs for compression of multispectral imagery and their impact on terrain categorization performance are evaluated. The mean-squared error (MSE) and classification performance of the two quantizers are compared, and it is shown that a simple two-stage design minimizing MSE subject to a constraint on classification performance has a significantly better classification performance than a standard MSE-based tree-structured vector quantizer followed by maximum likelihood classification. This improvement in classification performance is obtained with minimal loss in MSE performance. The results show that it is advantageous to tailor compression algorithm designs to the required data exploitation tasks. Applications of joint compression/classification include compression for the archival or transmission of Landsat imagery that is later used for land utility surveys and/or radiometric analysis.

Combining Vector Quantization and Histogram Equalization.

ERIC Educational Resources Information Center

Cosman, Pamela C.; And Others

1992-01-01

Discussion of contrast enhancement techniques focuses on the use of histogram equalization with a data compression technique, i.e., tree-structured vector quantization. The enhancement technique of intensity windowing is described, and the use of enhancement techniques for medical images is explained, including adaptive histogram equalization.…

Application of a VLSI vector quantization processor to real-time speech coding

NASA Technical Reports Server (NTRS)

Davidson, G.; Gersho, A.

1986-01-01

Attention is given to a working vector quantization processor for speech coding that is based on a first-generation VLSI chip which efficiently performs the pattern-matching operation needed for the codebook search process (CPS). Using this chip, the CPS architecture has been successfully incorporated into a compact, single-board Vector PCM implementation operating at 7-18 kbits/sec. A real time Adaptive Vector Predictive Coder system using the CPS has also been implemented.

Perceptual compression of magnitude-detected synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

Gorman, John D.; Werness, Susan A.

1994-01-01

A perceptually-based approach for compressing synthetic aperture radar (SAR) imagery is presented. Key components of the approach are a multiresolution wavelet transform, a bit allocation mask based on an empirical human visual system (HVS) model, and hybrid scalar/vector quantization. Specifically, wavelet shrinkage techniques are used to segregate wavelet transform coefficients into three components: local means, edges, and texture. Each of these three components is then quantized separately according to a perceptually-based bit allocation scheme. Wavelet coefficients associated with local means and edges are quantized using high-rate scalar quantization while texture information is quantized using low-rate vector quantization. The impact of the perceptually-based multiresolution compression algorithm on visual image quality, impulse response, and texture properties is assessed for fine-resolution magnitude-detected SAR imagery; excellent image quality is found at bit rates at or above 1 bpp along with graceful performance degradation at rates below 1 bpp.

Necessary conditions for the optimality of variable rate residual vector quantizers

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Barnes, Christopher F.

1993-01-01

Residual vector quantization (RVQ), or multistage VQ, as it is also called, has recently been shown to be a competitive technique for data compression. The competitive performance of RVQ reported in results from the joint optimization of variable rate encoding and RVQ direct-sum code books. In this paper, necessary conditions for the optimality of variable rate RVQ's are derived, and an iterative descent algorithm based on a Lagrangian formulation is introduced for designing RVQ's having minimum average distortion subject to an entropy constraint. Simulation results for these entropy-constrained RVQ's (EC-RVQ's) are presented for memory less Gaussian, Laplacian, and uniform sources. A Gauss-Markov source is also considered. The performance is superior to that of entropy-constrained scalar quantizers (EC-SQ's) and practical entropy-constrained vector quantizers (EC-VQ's), and is competitive with that of some of the best source coding techniques that have appeared in the literature.

Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design

PubMed Central

Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco

2016-01-01

The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms. PMID:27886061

Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design.

PubMed

Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco

2016-11-23

The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms.

Quantized Vector Potential and the Photon Wave-function

NASA Astrophysics Data System (ADS)

Meis, C.; Dahoo, P. R.

2017-12-01

The vector potential function {\\overrightarrow{α }}kλ (\\overrightarrow{r},t) for a k-mode and λ-polarization photon, with the quantized amplitude α 0k (ω k ) = ξω k , satisfies the classical wave propagation equation as well as the Schrodinger’s equation with the relativistic massless Hamiltonian \\mathop{H}\\limits∼ =-i\\hslash c\\overrightarrow{\

Reduced Order Podolsky Model

NASA Astrophysics Data System (ADS)

Thibes, Ronaldo

2017-02-01

We perform the canonical and path integral quantizations of a lower-order derivatives model describing Podolsky's generalized electrodynamics. The physical content of the model shows an auxiliary massive vector field coupled to the usual electromagnetic field. The equivalence with Podolsky's original model is studied at classical and quantum levels. Concerning the dynamical time evolution, we obtain a theory with two first-class and two second-class constraints in phase space. We calculate explicitly the corresponding Dirac brackets involving both vector fields. We use the Senjanovic procedure to implement the second-class constraints and the Batalin-Fradkin-Vilkovisky path integral quantization scheme to deal with the symmetries generated by the first-class constraints. The physical interpretation of the results turns out to be simpler due to the reduced derivatives order permeating the equations of motion, Dirac brackets and effective action.

Vector Quantization Algorithm Based on Associative Memories

NASA Astrophysics Data System (ADS)

Guzmán, Enrique; Pogrebnyak, Oleksiy; Yáñez, Cornelio; Manrique, Pablo

This paper presents a vector quantization algorithm for image compression based on extended associative memories. The proposed algorithm is divided in two stages. First, an associative network is generated applying the learning phase of the extended associative memories between a codebook generated by the LBG algorithm and a training set. This associative network is named EAM-codebook and represents a new codebook which is used in the next stage. The EAM-codebook establishes a relation between training set and the LBG codebook. Second, the vector quantization process is performed by means of the recalling stage of EAM using as associative memory the EAM-codebook. This process generates a set of the class indices to which each input vector belongs. With respect to the LBG algorithm, the main advantages offered by the proposed algorithm is high processing speed and low demand of resources (system memory); results of image compression and quality are presented.

Conditional Entropy-Constrained Residual VQ with Application to Image Coding

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1996-01-01

This paper introduces an extension of entropy-constrained residual vector quantization (VQ) where intervector dependencies are exploited. The method, which we call conditional entropy-constrained residual VQ, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. When applied to coding images, the proposed method is shown to achieve better rate-distortion performance than that of entropy-constrained residual vector quantization with less computational complexity and lower memory requirements. Moreover, it can be designed to support progressive transmission in a natural way. It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature. This is due partly to the joint optimization between the residual vector quantizer and a high-order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the prediction.

A VLSI chip set for real time vector quantization of image sequences

NASA Technical Reports Server (NTRS)

Baker, Richard L.

1989-01-01

The architecture and implementation of a VLSI chip set that vector quantizes (VQ) image sequences in real time is described. The chip set forms a programmable Single-Instruction, Multiple-Data (SIMD) machine which can implement various vector quantization encoding structures. Its VQ codebook may contain unlimited number of codevectors, N, having dimension up to K = 64. Under a weighted least squared error criterion, the engine locates at video rates the best code vector in full-searched or large tree searched VQ codebooks. The ability to manipulate tree structured codebooks, coupled with parallelism and pipelining, permits searches in as short as O (log N) cycles. A full codebook search results in O(N) performance, compared to O(KN) for a Single-Instruction, Single-Data (SISD) machine. With this VLSI chip set, an entire video code can be built on a single board that permits realtime experimentation with very large codebooks.

Covariant open bosonic string field theory on multiple D-branes in the proper-time gauge

NASA Astrophysics Data System (ADS)

Lee, Taejin

2017-12-01

We construct a covariant open bosonic string field theory on multiple D-branes, which reduces to a non-Abelian group Yang-Mills gauge theory in the zero-slope limit. Making use of the first quantized open bosonic string in the proper time gauge, we convert the string amplitudes given by the Polyakov path integrals on string world sheets into those of the second quantized theory. The world sheet diagrams generated by the constructed open string field theory are planar in contrast to those of the Witten's cubic string field theory. However, the constructed string field theory is yet equivalent to the Witten's cubic string field theory. Having obtained planar diagrams, we may adopt the light-cone string field theory technique to calculate the multi-string scattering amplitudes with an arbitrary number of external strings. We examine in detail the three-string vertex diagram and the effective four-string vertex diagrams generated perturbatively by the three-string vertex at tree level. In the zero-slope limit, the string scattering amplitudes are identified precisely as those of non-Abelian Yang-Mills gauge theory if the external states are chosen to be massless vector particles.

High Order Entropy-Constrained Residual VQ for Lossless Compression of Images

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Scales, Allen

1995-01-01

High order entropy coding is a powerful technique for exploiting high order statistical dependencies. However, the exponentially high complexity associated with such a method often discourages its use. In this paper, an entropy-constrained residual vector quantization method is proposed for lossless compression of images. The method consists of first quantizing the input image using a high order entropy-constrained residual vector quantizer and then coding the residual image using a first order entropy coder. The distortion measure used in the entropy-constrained optimization is essentially the first order entropy of the residual image. Experimental results show very competitive performance.

BSIFT: toward data-independent codebook for large scale image search.

PubMed

Zhou, Wengang; Li, Houqiang; Hong, Richang; Lu, Yijuan; Tian, Qi

2015-03-01

Bag-of-Words (BoWs) model based on Scale Invariant Feature Transform (SIFT) has been widely used in large-scale image retrieval applications. Feature quantization by vector quantization plays a crucial role in BoW model, which generates visual words from the high- dimensional SIFT features, so as to adapt to the inverted file structure for the scalable retrieval. Traditional feature quantization approaches suffer several issues, such as necessity of visual codebook training, limited reliability, and update inefficiency. To avoid the above problems, in this paper, a novel feature quantization scheme is proposed to efficiently quantize each SIFT descriptor to a descriptive and discriminative bit-vector, which is called binary SIFT (BSIFT). Our quantizer is independent of image collections. In addition, by taking the first 32 bits out from BSIFT as code word, the generated BSIFT naturally lends itself to adapt to the classic inverted file structure for image indexing. Moreover, the quantization error is reduced by feature filtering, code word expansion, and query sensitive mask shielding. Without any explicit codebook for quantization, our approach can be readily applied in image search in some resource-limited scenarios. We evaluate the proposed algorithm for large scale image search on two public image data sets. Experimental results demonstrate the index efficiency and retrieval accuracy of our approach.

Density-Dependent Quantized Least Squares Support Vector Machine for Large Data Sets.

PubMed

Nan, Shengyu; Sun, Lei; Chen, Badong; Lin, Zhiping; Toh, Kar-Ann

2017-01-01

Based on the knowledge that input data distribution is important for learning, a data density-dependent quantization scheme (DQS) is proposed for sparse input data representation. The usefulness of the representation scheme is demonstrated by using it as a data preprocessing unit attached to the well-known least squares support vector machine (LS-SVM) for application on big data sets. Essentially, the proposed DQS adopts a single shrinkage threshold to obtain a simple quantization scheme, which adapts its outputs to input data density. With this quantization scheme, a large data set is quantized to a small subset where considerable sample size reduction is generally obtained. In particular, the sample size reduction can save significant computational cost when using the quantized subset for feature approximation via the Nyström method. Based on the quantized subset, the approximated features are incorporated into LS-SVM to develop a data density-dependent quantized LS-SVM (DQLS-SVM), where an analytic solution is obtained in the primal solution space. The developed DQLS-SVM is evaluated on synthetic and benchmark data with particular emphasis on large data sets. Extensive experimental results show that the learning machine incorporating DQS attains not only high computational efficiency but also good generalization performance.

Enhancing speech recognition using improved particle swarm optimization based hidden Markov model.

PubMed

Selvaraj, Lokesh; Ganesan, Balakrishnan

2014-01-01

Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages, namely, (i) denoising, (ii) feature mining (iii), vector quantization, and (iv) IPSO based hidden Markov model (HMM) technique (IP-HMM). At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC), mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.

Magnetic resonance image compression using scalar-vector quantization

NASA Astrophysics Data System (ADS)

Mohsenian, Nader; Shahri, Homayoun

1995-12-01

A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. SVQ is a fixed-rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity issues of using variable-length scalar quantizers. When transmission of images over noisy channels is considered, our coding scheme does not suffer from error propagation which is typical of coding schemes which use variable-length codes. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit-rates are indistinguishable. Furthermore, our encoded images are perceptually indistinguishable from the original, when displayed on a monitor. This makes our SVQ based coder an attractive compression scheme for picture archiving and communication systems (PACS), currently under consideration for an all digital radiology environment in hospitals, where reliable transmission, storage, and high fidelity reconstruction of images are desired.

Fast large-scale object retrieval with binary quantization

NASA Astrophysics Data System (ADS)

Zhou, Shifu; Zeng, Dan; Shen, Wei; Zhang, Zhijiang; Tian, Qi

2015-11-01

The objective of large-scale object retrieval systems is to search for images that contain the target object in an image database. Where state-of-the-art approaches rely on global image representations to conduct searches, we consider many boxes per image as candidates to search locally in a picture. In this paper, a feature quantization algorithm called binary quantization is proposed. In binary quantization, a scale-invariant feature transform (SIFT) feature is quantized into a descriptive and discriminative bit-vector, which allows itself to adapt to the classic inverted file structure for box indexing. The inverted file, which stores the bit-vector and box ID where the SIFT feature is located inside, is compact and can be loaded into the main memory for efficient box indexing. We evaluate our approach on available object retrieval datasets. Experimental results demonstrate that the proposed approach is fast and achieves excellent search quality. Therefore, the proposed approach is an improvement over state-of-the-art approaches for object retrieval.

Quantized Spectral Compressed Sensing: Cramer–Rao Bounds and Recovery Algorithms

NASA Astrophysics Data System (ADS)

Fu, Haoyu; Chi, Yuejie

2018-06-01

Efficient estimation of wideband spectrum is of great importance for applications such as cognitive radio. Recently, sub-Nyquist sampling schemes based on compressed sensing have been proposed to greatly reduce the sampling rate. However, the important issue of quantization has not been fully addressed, particularly for high-resolution spectrum and parameter estimation. In this paper, we aim to recover spectrally-sparse signals and the corresponding parameters, such as frequency and amplitudes, from heavy quantizations of their noisy complex-valued random linear measurements, e.g. only the quadrant information. We first characterize the Cramer-Rao bound under Gaussian noise, which highlights the trade-off between sample complexity and bit depth under different signal-to-noise ratios for a fixed budget of bits. Next, we propose a new algorithm based on atomic norm soft thresholding for signal recovery, which is equivalent to proximal mapping of properly designed surrogate signals with respect to the atomic norm that motivates spectral sparsity. The proposed algorithm can be applied to both the single measurement vector case, as well as the multiple measurement vector case. It is shown that under the Gaussian measurement model, the spectral signals can be reconstructed accurately with high probability, as soon as the number of quantized measurements exceeds the order of K log n, where K is the level of spectral sparsity and $n$ is the signal dimension. Finally, numerical simulations are provided to validate the proposed approaches.

Symplectic Quantization of a Vector-Tensor Gauge Theory with Topological Coupling

NASA Astrophysics Data System (ADS)

Barcelos-Neto, J.; Silva, M. B. D.

We use the symplectic formalism to quantize a gauge theory where vectors and tensors fields are coupled in a topological way. This is an example of reducible theory and a procedure like of ghosts-of-ghosts of the BFV method is applied but in terms of Lagrange multipliers. Our final results are in agreement with the ones found in the literature by using the Dirac method.

On the Problem of Bandwidth Partitioning in FDD Block-Fading Single-User MISO/SIMO Systems

NASA Astrophysics Data System (ADS)

Ivrlač, Michel T.; Nossek, Josef A.

2008-12-01

We report on our research activity on the problem of how to optimally partition the available bandwidth of frequency division duplex, multi-input single-output communication systems, into subbands for the uplink, the downlink, and the feedback. In the downlink, the transmitter applies coherent beamforming based on quantized channel information which is obtained by feedback from the receiver. As feedback takes away resources from the uplink, which could otherwise be used to transfer payload data, it is highly desirable to reserve the "right" amount of uplink resources for the feedback. Under the assumption of random vector quantization, and a frequency flat, independent and identically distributed block-fading channel, we derive closed-form expressions for both the feedback quantization and bandwidth partitioning which jointly maximize the sum of the average payload data rates of the downlink and the uplink. While we do introduce some approximations to facilitate mathematical tractability, the analytical solution is asymptotically exact as the number of antennas approaches infinity, while for systems with few antennas, it turns out to be a fairly accurate approximation. In this way, the obtained results are meaningful for practical communication systems, which usually can only employ a few antennas.

Locally adaptive vector quantization: Data compression with feature preservation

NASA Technical Reports Server (NTRS)

Cheung, K. M.; Sayano, M.

1992-01-01

A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modifications to improve performance are discussed. These modifications are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ's performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv-based algorithms, but LAVQ uses far less memory during the coding process.

Observation of Landau levels in potassium-intercalated graphite under a zero magnetic field

PubMed Central

Guo, Donghui; Kondo, Takahiro; Machida, Takahiro; Iwatake, Keigo; Okada, Susumu; Nakamura, Junji

2012-01-01

The charge carriers in graphene are massless Dirac fermions and exhibit a relativistic Landau-level quantization in a magnetic field. Recently, it has been reported that, without any external magnetic field, quantized energy levels have been also observed from strained graphene nanobubbles on a platinum surface, which were attributed to the Landau levels of massless Dirac fermions in graphene formed by a strain-induced pseudomagnetic field. Here we show the generation of the Landau levels of massless Dirac fermions on a partially potassium-intercalated graphite surface without applying external magnetic field. Landau levels of massless Dirac fermions indicate the graphene character in partially potassium-intercalated graphite. The generation of the Landau levels is ascribed to a vector potential induced by the perturbation of nearest-neighbour hopping, which may originate from a strain or a gradient of on-site potentials at the perimeters of potassium-free domains. PMID:22990864

A constrained joint source/channel coder design and vector quantization of nonstationary sources

NASA Technical Reports Server (NTRS)

Sayood, Khalid; Chen, Y. C.; Nori, S.; Araj, A.

1993-01-01

The emergence of broadband ISDN as the network for the future brings with it the promise of integration of all proposed services in a flexible environment. In order to achieve this flexibility, asynchronous transfer mode (ATM) has been proposed as the transfer technique. During this period a study was conducted on the bridging of network transmission performance and video coding. The successful transmission of variable bit rate video over ATM networks relies on the interaction between the video coding algorithm and the ATM networks. Two aspects of networks that determine the efficiency of video transmission are the resource allocation algorithm and the congestion control algorithm. These are explained in this report. Vector quantization (VQ) is one of the more popular compression techniques to appear in the last twenty years. Numerous compression techniques, which incorporate VQ, have been proposed. While the LBG VQ provides excellent compression, there are also several drawbacks to the use of the LBG quantizers including search complexity and memory requirements, and a mismatch between the codebook and the inputs. The latter mainly stems from the fact that the VQ is generally designed for a specific rate and a specific class of inputs. In this work, an adaptive technique is proposed for vector quantization of images and video sequences. This technique is an extension of the recursively indexed scalar quantization (RISQ) algorithm.

Radial quantization of the 3d CFT and the higher spin/vector model duality

NASA Astrophysics Data System (ADS)

Hu, Shan; Li, Tianjun

2014-10-01

We study the radial quantization of the 3dO(N) vector model. We calculate the higher spin charges whose commutation relations give the higher spin algebra. The Fock states of higher spin gravity in AdS4 are realized as the states in the 3d CFT. The dynamical information is encoded in their inner products. This serves as the simplest explicit demonstration of the CFT definition for the quantum gravity.

Wavelet subband coding of computer simulation output using the A++ array class library

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

Bradley, J.N.; Brislawn, C.M.; Quinlan, D.J.

1995-07-01

The goal of the project is to produce utility software for off-line compression of existing data and library code that can be called from a simulation program for on-line compression of data dumps as the simulation proceeds. Naturally, we would like the amount of CPU time required by the compression algorithm to be small in comparison to the requirements of typical simulation codes. We also want the algorithm to accomodate a wide variety of smooth, multidimensional data types. For these reasons, the subband vector quantization (VQ) approach employed in has been replaced by a scalar quantization (SQ) strategy using amore » bank of almost-uniform scalar subband quantizers in a scheme similar to that used in the FBI fingerprint image compression standard. This eliminates the considerable computational burdens of training VQ codebooks for each new type of data and performing nearest-vector searches to encode the data. The comparison of subband VQ and SQ algorithms in indicated that, in practice, there is relatively little additional gain from using vector as opposed to scalar quantization on DWT subbands, even when the source imagery is from a very homogeneous population, and our subjective experience with synthetic computer-generated data supports this stance. It appears that a careful study is needed of the tradeoffs involved in selecting scalar vs. vector subband quantization, but such an analysis is beyond the scope of this paper. Our present work is focused on the problem of generating wavelet transform/scalar quantization (WSQ) implementations that can be ported easily between different hardware environments. This is an extremely important consideration given the great profusion of different high-performance computing architectures available, the high cost associated with learning how to map algorithms effectively onto a new architecture, and the rapid rate of evolution in the world of high-performance computing.« less

Speech coding at low to medium bit rates

NASA Astrophysics Data System (ADS)

Leblanc, Wilfred Paul

1992-09-01

Improved search techniques coupled with improved codebook design methodologies are proposed to improve the performance of conventional code-excited linear predictive coders for speech. Improved methods for quantizing the short term filter are developed by employing a tree search algorithm and joint codebook design to multistage vector quantization. Joint codebook design procedures are developed to design locally optimal multistage codebooks. Weighting during centroid computation is introduced to improve the outlier performance of the multistage vector quantizer. Multistage vector quantization is shown to be both robust against input characteristics and in the presence of channel errors. Spectral distortions of about 1 dB are obtained at rates of 22-28 bits/frame. Structured codebook design procedures for excitation in code-excited linear predictive coders are compared to general codebook design procedures. Little is lost using significant structure in the excitation codebooks while greatly reducing the search complexity. Sparse multistage configurations are proposed for reducing computational complexity and memory size. Improved search procedures are applied to code-excited linear prediction which attempt joint optimization of the short term filter, the adaptive codebook, and the excitation. Improvements in signal to noise ratio of 1-2 dB are realized in practice.

Image coding using entropy-constrained residual vector quantization

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Barnes, Christopher F.

1993-01-01

The residual vector quantization (RVQ) structure is exploited to produce a variable length codeword RVQ. Necessary conditions for the optimality of this RVQ are presented, and a new entropy-constrained RVQ (ECRVQ) design algorithm is shown to be very effective in designing RVQ codebooks over a wide range of bit rates and vector sizes. The new EC-RVQ has several important advantages. It can outperform entropy-constrained VQ (ECVQ) in terms of peak signal-to-noise ratio (PSNR), memory, and computation requirements. It can also be used to design high rate codebooks and codebooks with relatively large vector sizes. Experimental results indicate that when the new EC-RVQ is applied to image coding, very high quality is achieved at relatively low bit rates.

Real-time data compression of broadcast video signals

NASA Technical Reports Server (NTRS)

Shalkauser, Mary Jo W. (Inventor); Whyte, Wayne A., Jr. (Inventor); Barnes, Scott P. (Inventor)

1991-01-01

A non-adaptive predictor, a nonuniform quantizer, and a multi-level Huffman coder are incorporated into a differential pulse code modulation system for coding and decoding broadcast video signals in real time.

Quantized impedance dealing with the damping behavior of the one-dimensional oscillator

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

Zhu, Jinghao; Zhang, Jing; Li, Yuan

2015-11-15

A quantized impedance is proposed to theoretically establish the relationship between the atomic eigenfrequency and the intrinsic frequency of the one-dimensional oscillator in this paper. The classical oscillator is modified by the idea that the electron transition is treated as a charge-discharge process of a suggested capacitor with the capacitive energy equal to the energy level difference of the jumping electron. The quantized capacitance of the impedance interacting with the jumping electron can lead the resonant frequency of the oscillator to the same as the atomic eigenfrequency. The quantized resistance reflects that the damping coefficient of the oscillator is themore » mean collision frequency of the transition electron. In addition, the first and third order electric susceptibilities based on the oscillator are accordingly quantized. Our simulation of the hydrogen atom emission spectrum based on the proposed method agrees well with the experimental one. Our results exhibits that the one-dimensional oscillator with the quantized impedance may become useful in the estimations of the refractive index and one- or multi-photon absorption coefficients of some nonmagnetic media composed of hydrogen-like atoms.« less

Quantized impedance dealing with the damping behavior of the one-dimensional oscillator

NASA Astrophysics Data System (ADS)

Zhu, Jinghao; Zhang, Jing; Li, Yuan; Zhang, Yong; Fang, Zhengji; Zhao, Peide; Li, Erping

2015-11-01

A quantized impedance is proposed to theoretically establish the relationship between the atomic eigenfrequency and the intrinsic frequency of the one-dimensional oscillator in this paper. The classical oscillator is modified by the idea that the electron transition is treated as a charge-discharge process of a suggested capacitor with the capacitive energy equal to the energy level difference of the jumping electron. The quantized capacitance of the impedance interacting with the jumping electron can lead the resonant frequency of the oscillator to the same as the atomic eigenfrequency. The quantized resistance reflects that the damping coefficient of the oscillator is the mean collision frequency of the transition electron. In addition, the first and third order electric susceptibilities based on the oscillator are accordingly quantized. Our simulation of the hydrogen atom emission spectrum based on the proposed method agrees well with the experimental one. Our results exhibits that the one-dimensional oscillator with the quantized impedance may become useful in the estimations of the refractive index and one- or multi-photon absorption coefficients of some nonmagnetic media composed of hydrogen-like atoms.

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

PubMed

Zhang, Yu; Wu, Jianxin; Cai, Jianfei

2016-05-01

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

Spectrally efficient digitized radio-over-fiber system with k-means clustering-based multidimensional quantization.

PubMed

Zhang, Lu; Pang, Xiaodan; Ozolins, Oskars; Udalcovs, Aleksejs; Popov, Sergei; Xiao, Shilin; Hu, Weisheng; Chen, Jiajia

2018-04-01

We propose a spectrally efficient digitized radio-over-fiber (D-RoF) system by grouping highly correlated neighboring samples of the analog signals into multidimensional vectors, where the k-means clustering algorithm is adopted for adaptive quantization. A 30  Gbit/s D-RoF system is experimentally demonstrated to validate the proposed scheme, reporting a carrier aggregation of up to 40 100 MHz orthogonal frequency division multiplexing (OFDM) channels with quadrate amplitude modulation (QAM) order of 4 and an aggregation of 10 100 MHz OFDM channels with a QAM order of 16384. The equivalent common public radio interface rates from 37 to 150  Gbit/s are supported. Besides, the error vector magnitude (EVM) of 8% is achieved with the number of quantization bits of 4, and the EVM can be further reduced to 1% by increasing the number of quantization bits to 7. Compared with conventional pulse coding modulation-based D-RoF systems, the proposed D-RoF system improves the signal-to-noise-ratio up to ∼9  dB and greatly reduces the EVM, given the same number of quantization bits.

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

Vector quantizer based on brightness maps for image compression with the polynomial transform

NASA Astrophysics Data System (ADS)

Escalante-Ramirez, Boris; Moreno-Gutierrez, Mauricio; Silvan-Cardenas, Jose L.

2002-11-01

We present a vector quantization scheme acting on brightness fields based on distance/distortion criteria correspondent with psycho-visual aspects. These criteria quantify sensorial distortion between vectors that represent either portions of a digital image or alternatively, coefficients of a transform-based coding system. In the latter case, we use an image representation model, namely the Hermite transform, that is based on some of the main perceptual characteristics of the human vision system (HVS) and in their response to light stimulus. Energy coding in the brightness domain, determination of local structure, code-book training and local orientation analysis are all obtained by means of the Hermite transform. This paper, for thematic reasons, is divided in four sections. The first one will shortly highlight the importance of having newer and better compression algorithms. This section will also serve to explain briefly the most relevant characteristics of the HVS, advantages and disadvantages related with the behavior of our vision in front of ocular stimulus. The second section shall go through a quick review of vector quantization techniques, focusing their performance on image treatment, as a preview for the image vector quantizer compressor actually constructed in section 5. Third chapter was chosen to concentrate the most important data gathered on brightness models. The building of this so-called brightness maps (quantification of the human perception on the visible objects reflectance), in a bi-dimensional model, will be addressed here. The Hermite transform, a special case of polynomial transforms, and its usefulness, will be treated, in an applicable discrete form, in the fourth chapter. As we have learned from previous works 1, Hermite transform has showed to be a useful and practical solution to efficiently code the energy within an image block, deciding which kind of quantization is to be used upon them (whether scalar or vector). It will also be a unique tool to structurally classify the image block within a given lattice. This particular operation intends to be one of the main contributions of this work. The fifth section will fuse the proposals derived from the study of the three main topics- addressed in the last sections- in order to propose an image compression model that takes advantage of vector quantizers inside the brightness transformed domain to determine the most important structures, finding the energy distribution inside the Hermite domain. Sixth and last section will show some results obtained while testing the coding-decoding model. The guidelines to evaluate the image compressing performance were the compression ratio, SNR and psycho-visual quality. Some conclusions derived from the research and possible unexplored paths will be shown on this section as well.

Consciousness of Unification: The Mind-Matter Phallacy Bites the Dust

NASA Astrophysics Data System (ADS)

Beichler, James E.

A complete theoretical model of how consciousness arises in neural nets can be developed based on a mixed quantum/classical basis. Both mind and consciousness are multi-leveled scalar and vector electromagnetic complexity patterns, respectively, which emerge within all living organisms through the process of evolution. Like life, the mind and consciousness patterns extend throughout living organisms (bodies), but the neural nets and higher level groupings that distinguish higher levels of consciousness only exist in the brain so mind and consciousness have been traditionally associated with the brain alone. A close study of neurons and neural nets in the brain shows that the microtubules within axons are classical bio-magnetic inductors that emit and absorb electromagnetic pulses from each other. These pulses establish interference patterns that influence the quantized vector potential patterns of interstitial water molecules within the neurons as well as create the coherence within neurons and neural nets that scientists normally associate with more complex memories, thought processes and streams of thought. Memory storage and recall are guided by the microtubules and the actual memory patterns are stored as magnetic vector potential complexity patterns in the points of space at the quantum level occupied by the water molecules. This model also accounts for the plasticity of the brain and implies that mind and consciousness, like life itself, are the result of evolutionary processes. However, consciousness can evolve independent of an organism's birth genetics once it has evolved by normal bottom-up genetic processes and thus force a new type of top-down evolution on living organisms and species as a whole that can be explained by expanding the laws of thermodynamics to include orderly systems.

Visual data mining for quantized spatial data

NASA Technical Reports Server (NTRS)

Braverman, Amy; Kahn, Brian

2004-01-01

In previous papers we've shown how a well known data compression algorithm called Entropy-constrained Vector Quantization ( can be modified to reduce the size and complexity of very large, satellite data sets. In this paper, we descuss how to visualize and understand the content of such reduced data sets.

Topological charge quantization via path integration: An application of the Kustaanheimo-Stiefel transformation

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

Inomata, A.; Junker, G.; Wilson, R.

1993-08-01

The unified treatment of the Dirac monopole, the Schwinger monopole, and the Aharonov-Bahn problem by Barut and Wilson is revisited via a path integral approach. The Kustaanheimo-Stiefel transformation of space and time is utilized to calculate the path integral for a charged particle in the singular vector potential. In the process of dimensional reduction, a topological charge quantization rule is derived, which contains Dirac's quantization condition as a special case. 32 refs.

Multi-rate, real time image compression for images dominated by point sources

NASA Technical Reports Server (NTRS)

Huber, A. Kris; Budge, Scott E.; Harris, Richard W.

1993-01-01

An image compression system recently developed for compression of digital images dominated by point sources is presented. Encoding consists of minimum-mean removal, vector quantization, adaptive threshold truncation, and modified Huffman encoding. Simulations are presented showing that the peaks corresponding to point sources can be transmitted losslessly for low signal-to-noise ratios (SNR) and high point source densities while maintaining a reduced output bit rate. Encoding and decoding hardware has been built and tested which processes 552,960 12-bit pixels per second at compression rates of 10:1 and 4:1. Simulation results are presented for the 10:1 case only.

Medical Image Retrieval Using Multi-Texton Assignment.

PubMed

Tang, Qiling; Yang, Jirong; Xia, Xianfu

2018-02-01

In this paper, we present a multi-texton representation method for medical image retrieval, which utilizes the locality constraint to encode each filter bank response within its local-coordinate system consisting of the k nearest neighbors in texton dictionary and subsequently employs spatial pyramid matching technique to implement feature vector representation. Comparison with the traditional nearest neighbor assignment followed by texton histogram statistics method, our strategies reduce the quantization errors in mapping process and add information about the spatial layout of texton distributions and, thus, increase the descriptive power of the image representation. We investigate the effects of different parameters on system performance in order to choose the appropriate ones for our datasets and carry out experiments on the IRMA-2009 medical collection and the mammographic patch dataset. The extensive experimental results demonstrate that the proposed method has superior performance.

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

NASA Technical Reports Server (NTRS)

Jaggi, S.

1993-01-01

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

On Fock-space representations of quantized enveloping algebras related to noncommutative differential geometry

NASA Astrophysics Data System (ADS)

Jurčo, B.; Schlieker, M.

1995-07-01

In this paper explicitly natural (from the geometrical point of view) Fock-space representations (contragradient Verma modules) of the quantized enveloping algebras are constructed. In order to do so, one starts from the Gauss decomposition of the quantum group and introduces the differential operators on the corresponding q-deformed flag manifold (assumed as a left comodule for the quantum group) by a projection to it of the right action of the quantized enveloping algebra on the quantum group. Finally, the representatives of the elements of the quantized enveloping algebra corresponding to the left-invariant vector fields on the quantum group are expressed as first-order differential operators on the q-deformed flag manifold.

Optimal source coding, removable noise elimination, and natural coordinate system construction for general vector sources using replicator neural networks

NASA Astrophysics Data System (ADS)

Hecht-Nielsen, Robert

1997-04-01

A new universal one-chart smooth manifold model for vector information sources is introduced. Natural coordinates (a particular type of chart) for such data manifolds are then defined. Uniformly quantized natural coordinates form an optimal vector quantization code for a general vector source. Replicator neural networks (a specialized type of multilayer perceptron with three hidden layers) are the introduced. As properly configured examples of replicator networks approach minimum mean squared error (e.g., via training and architecture adjustment using randomly chosen vectors from the source), these networks automatically develop a mapping which, in the limit, produces natural coordinates for arbitrary source vectors. The new concept of removable noise (a noise model applicable to a wide variety of real-world noise processes) is then discussed. Replicator neural networks, when configured to approach minimum mean squared reconstruction error (e.g., via training and architecture adjustment on randomly chosen examples from a vector source, each with randomly chosen additive removable noise contamination), in the limit eliminate removable noise and produce natural coordinates for the data vector portions of the noise-corrupted source vectors. Consideration regarding selection of the dimension of a data manifold source model and the training/configuration of replicator neural networks are discussed.

Curvilinear component analysis: a self-organizing neural network for nonlinear mapping of data sets.

PubMed

Demartines, P; Herault, J

1997-01-01

We present a new strategy called "curvilinear component analysis" (CCA) for dimensionality reduction and representation of multidimensional data sets. The principle of CCA is a self-organized neural network performing two tasks: vector quantization (VQ) of the submanifold in the data set (input space); and nonlinear projection (P) of these quantizing vectors toward an output space, providing a revealing unfolding of the submanifold. After learning, the network has the ability to continuously map any new point from one space into another: forward mapping of new points in the input space, or backward mapping of an arbitrary position in the output space.

Multipurpose image watermarking algorithm based on multistage vector quantization.

PubMed

Lu, Zhe-Ming; Xu, Dian-Guo; Sun, Sheng-He

2005-06-01

The rapid growth of digital multimedia and Internet technologies has made copyright protection, copy protection, and integrity verification three important issues in the digital world. To solve these problems, the digital watermarking technique has been presented and widely researched. Traditional watermarking algorithms are mostly based on discrete transform domains, such as the discrete cosine transform, discrete Fourier transform (DFT), and discrete wavelet transform (DWT). Most of these algorithms are good for only one purpose. Recently, some multipurpose digital watermarking methods have been presented, which can achieve the goal of content authentication and copyright protection simultaneously. However, they are based on DWT or DFT. Lately, several robust watermarking schemes based on vector quantization (VQ) have been presented, but they can only be used for copyright protection. In this paper, we present a novel multipurpose digital image watermarking method based on the multistage vector quantizer structure, which can be applied to image authentication and copyright protection. In the proposed method, the semi-fragile watermark and the robust watermark are embedded in different VQ stages using different techniques, and both of them can be extracted without the original image. Simulation results demonstrate the effectiveness of our algorithm in terms of robustness and fragility.

Distance learning in discriminative vector quantization.

PubMed

Schneider, Petra; Biehl, Michael; Hammer, Barbara

2009-10-01

Discriminative vector quantization schemes such as learning vector quantization (LVQ) and extensions thereof offer efficient and intuitive classifiers based on the representation of classes by prototypes. The original methods, however, rely on the Euclidean distance corresponding to the assumption that the data can be represented by isotropic clusters. For this reason, extensions of the methods to more general metric structures have been proposed, such as relevance adaptation in generalized LVQ (GLVQ) and matrix learning in GLVQ. In these approaches, metric parameters are learned based on the given classification task such that a data-driven distance measure is found. In this letter, we consider full matrix adaptation in advanced LVQ schemes. In particular, we introduce matrix learning to a recent statistical formalization of LVQ, robust soft LVQ, and we compare the results on several artificial and real-life data sets to matrix learning in GLVQ, a derivation of LVQ-like learning based on a (heuristic) cost function. In all cases, matrix adaptation allows a significant improvement of the classification accuracy. Interestingly, however, the principled behavior of the models with respect to prototype locations and extracted matrix dimensions shows several characteristic differences depending on the data sets.

Hadron Spectra, Decays and Scattering Properties Within Basis Light Front Quantization

NASA Astrophysics Data System (ADS)

Vary, James P.; Adhikari, Lekha; Chen, Guangyao; Jia, Shaoyang; Li, Meijian; Li, Yang; Maris, Pieter; Qian, Wenyang; Spence, John R.; Tang, Shuo; Tuchin, Kirill; Yu, Anji; Zhao, Xingbo

2018-07-01

We survey recent progress in calculating properties of the electron and hadrons within the basis light front quantization (BLFQ) approach. We include applications to electromagnetic and strong scattering processes in relativistic heavy ion collisions. We present an initial investigation into the glueball states by applying BLFQ with multigluon sectors, introducing future research possibilities on multi-quark and multi-gluon systems.

Vector nature of multi-soliton patterns in a passively mode-locked figure-eight fiber laser.

PubMed

Ning, Qiu-Yi; Liu, Hao; Zheng, Xu-Wu; Yu, Wei; Luo, Ai-Ping; Huang, Xu-Guang; Luo, Zhi-Chao; Xu, Wen-Cheng; Xu, Shan-Hui; Yang, Zhong-Min

2014-05-19

The vector nature of multi-soliton dynamic patterns was investigated in a passively mode-locked figure-eight fiber laser based on the nonlinear amplifying loop mirror (NALM). By properly adjusting the cavity parameters such as the pump power level and intra-cavity polarization controllers (PCs), in addition to the fundamental vector soliton, various vector multi-soliton regimes were observed, such as the random static distribution of vector multiple solitons, vector soliton cluster, vector soliton flow, and the state of vector multiple solitons occupying the whole cavity. Both the polarization-locked vector solitons (PLVSs) and the polarization-rotating vector solitons (PRVSs) were observed for fundamental soliton and each type of multi-soliton patterns. The obtained results further reveal the fundamental physics of multi-soliton patterns and demonstrate that the figure-eight fiber lasers are indeed a good platform for investigating the vector nature of different soliton types.

Quantized kernel least mean square algorithm.

PubMed

Chen, Badong; Zhao, Songlin; Zhu, Pingping; Príncipe, José C

2012-01-01

In this paper, we propose a quantization approach, as an alternative of sparsification, to curb the growth of the radial basis function structure in kernel adaptive filtering. The basic idea behind this method is to quantize and hence compress the input (or feature) space. Different from sparsification, the new approach uses the "redundant" data to update the coefficient of the closest center. In particular, a quantized kernel least mean square (QKLMS) algorithm is developed, which is based on a simple online vector quantization method. The analytical study of the mean square convergence has been carried out. The energy conservation relation for QKLMS is established, and on this basis we arrive at a sufficient condition for mean square convergence, and a lower and upper bound on the theoretical value of the steady-state excess mean square error. Static function estimation and short-term chaotic time-series prediction examples are presented to demonstrate the excellent performance.

Low bit rate coding of Earth science images

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1993-01-01

In this paper, the authors discuss compression based on some new ideas in vector quantization and their incorporation in a sub-band coding framework. Several variations are considered, which collectively address many of the individual compression needs within the earth science community. The approach taken in this work is based on some recent advances in the area of variable rate residual vector quantization (RVQ). This new RVQ method is considered separately and in conjunction with sub-band image decomposition. Very good results are achieved in coding a variety of earth science images. The last section of the paper provides some comparisons that illustrate the improvement in performance attributable to this approach relative the the JPEG coding standard.

Pipeline synthetic aperture radar data compression utilizing systolic binary tree-searched architecture for vector quantization

NASA Technical Reports Server (NTRS)

Chang, Chi-Yung (Inventor); Fang, Wai-Chi (Inventor); Curlander, John C. (Inventor)

1995-01-01

A system for data compression utilizing systolic array architecture for Vector Quantization (VQ) is disclosed for both full-searched and tree-searched. For a tree-searched VQ, the special case of a Binary Tree-Search VQ (BTSVQ) is disclosed with identical Processing Elements (PE) in the array for both a Raw-Codebook VQ (RCVQ) and a Difference-Codebook VQ (DCVQ) algorithm. A fault tolerant system is disclosed which allows a PE that has developed a fault to be bypassed in the array and replaced by a spare at the end of the array, with codebook memory assignment shifted one PE past the faulty PE of the array.

A fingerprint key binding algorithm based on vector quantization and error correction

NASA Astrophysics Data System (ADS)

Li, Liang; Wang, Qian; Lv, Ke; He, Ning

2012-04-01

In recent years, researches on seamless combination cryptosystem with biometric technologies, e.g. fingerprint recognition, are conducted by many researchers. In this paper, we propose a binding algorithm of fingerprint template and cryptographic key to protect and access the key by fingerprint verification. In order to avoid the intrinsic fuzziness of variant fingerprints, vector quantization and error correction technique are introduced to transform fingerprint template and then bind with key, after a process of fingerprint registration and extracting global ridge pattern of fingerprint. The key itself is secure because only hash value is stored and it is released only when fingerprint verification succeeds. Experimental results demonstrate the effectiveness of our ideas.

Application of Classification Models to Pharyngeal High-Resolution Manometry

ERIC Educational Resources Information Center

Mielens, Jason D.; Hoffman, Matthew R.; Ciucci, Michelle R.; McCulloch, Timothy M.; Jiang, Jack J.

2012-01-01

Purpose: The authors present 3 methods of performing pattern recognition on spatiotemporal plots produced by pharyngeal high-resolution manometry (HRM). Method: Classification models, including the artificial neural networks (ANNs) multilayer perceptron (MLP) and learning vector quantization (LVQ), as well as support vector machines (SVM), were…

An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

NASA Technical Reports Server (NTRS)

Lin, Paul P.; Jules, Kenol

2002-01-01

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen's self-organizing feature map, learning vector quantization, and back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system.

Automatic detection of voice impairments by means of short-term cepstral parameters and neural network based detectors.

PubMed

Godino-Llorente, J I; Gómez-Vilda, P

2004-02-01

It is well known that vocal and voice diseases do not necessarily cause perceptible changes in the acoustic voice signal. Acoustic analysis is a useful tool to diagnose voice diseases being a complementary technique to other methods based on direct observation of the vocal folds by laryngoscopy. Through the present paper two neural-network based classification approaches applied to the automatic detection of voice disorders will be studied. Structures studied are multilayer perceptron and learning vector quantization fed using short-term vectors calculated accordingly to the well-known Mel Frequency Coefficient cepstral parameterization. The paper shows that these architectures allow the detection of voice disorders--including glottic cancer--under highly reliable conditions. Within this context, the Learning Vector quantization methodology demonstrated to be more reliable than the multilayer perceptron architecture yielding 96% frame accuracy under similar working conditions.

Accelerating simulation for the multiple-point statistics algorithm using vector quantization

NASA Astrophysics Data System (ADS)

Zuo, Chen; Pan, Zhibin; Liang, Hao

2018-03-01

Multiple-point statistics (MPS) is a prominent algorithm to simulate categorical variables based on a sequential simulation procedure. Assuming training images (TIs) as prior conceptual models, MPS extracts patterns from TIs using a template and records their occurrences in a database. However, complex patterns increase the size of the database and require considerable time to retrieve the desired elements. In order to speed up simulation and improve simulation quality over state-of-the-art MPS methods, we propose an accelerating simulation for MPS using vector quantization (VQ), called VQ-MPS. First, a variable representation is presented to make categorical variables applicable for vector quantization. Second, we adopt a tree-structured VQ to compress the database so that stationary simulations are realized. Finally, a transformed template and classified VQ are used to address nonstationarity. A two-dimensional (2D) stationary channelized reservoir image is used to validate the proposed VQ-MPS. In comparison with several existing MPS programs, our method exhibits significantly better performance in terms of computational time, pattern reproductions, and spatial uncertainty. Further demonstrations consist of a 2D four facies simulation, two 2D nonstationary channel simulations, and a three-dimensional (3D) rock simulation. The results reveal that our proposed method is also capable of solving multifacies, nonstationarity, and 3D simulations based on 2D TIs.

Vector coding of wavelet-transformed images

NASA Astrophysics Data System (ADS)

Zhou, Jun; Zhi, Cheng; Zhou, Yuanhua

1998-09-01

Wavelet, as a brand new tool in signal processing, has got broad recognition. Using wavelet transform, we can get octave divided frequency band with specific orientation which combines well with the properties of Human Visual System. In this paper, we discuss the classified vector quantization method for multiresolution represented image.

Permutation modulation for quantization and information reconciliation in CV-QKD systems

NASA Astrophysics Data System (ADS)

Daneshgaran, Fred; Mondin, Marina; Olia, Khashayar

2017-08-01

This paper is focused on the problem of Information Reconciliation (IR) for continuous variable Quantum Key Distribution (QKD). The main problem is quantization and assignment of labels to the samples of the Gaussian variables observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective Signal to Noise Ratio (SNR) exasperating the problem. Here we propose to use Permutation Modulation (PM) as a means of quantization of Gaussian vectors at Alice and Bob over a d-dimensional space with d ≫ 1. The goal is to achieve the necessary coding efficiency to extend the achievable range of continuous variable QKD by quantizing over larger and larger dimensions. Fractional bit rate per sample is easily achieved using PM at very reasonable computational cost. Ordered statistics is used extensively throughout the development from generation of the seed vector in PM to analysis of error rates associated with the signs of the Gaussian samples at Alice and Bob as a function of the magnitude of the observed samples at Bob.

Robust fault tolerant control based on sliding mode method for uncertain linear systems with quantization.

PubMed

Hao, Li-Ying; Yang, Guang-Hong

2013-09-01

This paper is concerned with the problem of robust fault-tolerant compensation control problem for uncertain linear systems subject to both state and input signal quantization. By incorporating novel matrix full-rank factorization technique with sliding surface design successfully, the total failure of certain actuators can be coped with, under a special actuator redundancy assumption. In order to compensate for quantization errors, an adjustment range of quantization sensitivity for a dynamic uniform quantizer is given through the flexible choices of design parameters. Comparing with the existing results, the derived inequality condition leads to the fault tolerance ability stronger and much wider scope of applicability. With a static adjustment policy of quantization sensitivity, an adaptive sliding mode controller is then designed to maintain the sliding mode, where the gain of the nonlinear unit vector term is updated automatically to compensate for the effects of actuator faults, quantization errors, exogenous disturbances and parameter uncertainties without the need for a fault detection and isolation (FDI) mechanism. Finally, the effectiveness of the proposed design method is illustrated via a model of a rocket fairing structural-acoustic. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Face recognition algorithm using extended vector quantization histogram features.

PubMed

Yan, Yan; Lee, Feifei; Wu, Xueqian; Chen, Qiu

2018-01-01

In this paper, we propose a face recognition algorithm based on a combination of vector quantization (VQ) and Markov stationary features (MSF). The VQ algorithm has been shown to be an effective method for generating features; it extracts a codevector histogram as a facial feature representation for face recognition. Still, the VQ histogram features are unable to convey spatial structural information, which to some extent limits their usefulness in discrimination. To alleviate this limitation of VQ histograms, we utilize Markov stationary features (MSF) to extend the VQ histogram-based features so as to add spatial structural information. We demonstrate the effectiveness of our proposed algorithm by achieving recognition results superior to those of several state-of-the-art methods on publicly available face databases.

Soft learning vector quantization and clustering algorithms based on ordered weighted aggregation operators.

PubMed

Karayiannis, N B

2000-01-01

This paper presents the development and investigates the properties of ordered weighted learning vector quantization (LVQ) and clustering algorithms. These algorithms are developed by using gradient descent to minimize reformulation functions based on aggregation operators. An axiomatic approach provides conditions for selecting aggregation operators that lead to admissible reformulation functions. Minimization of admissible reformulation functions based on ordered weighted aggregation operators produces a family of soft LVQ and clustering algorithms, which includes fuzzy LVQ and clustering algorithms as special cases. The proposed LVQ and clustering algorithms are used to perform segmentation of magnetic resonance (MR) images of the brain. The diagnostic value of the segmented MR images provides the basis for evaluating a variety of ordered weighted LVQ and clustering algorithms.

Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors

DTIC Science & Technology

2011-04-15

funded by Mitsubishi Electric Research Laboratories. †ICTEAM Institute, ELEN Department, Université catholique de Louvain (UCL), B-1348 Louvain-la-Neuve...reduced to a simple comparator that tests for values above or below zero, enabling extremely simple, efficient, and fast quantization. A 1-bit quantizer is...these two terms appears to be significantly different, according to the previously discussed experiments. To test the hypothesis that this term is the key

Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences.

PubMed

An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Fang, Yu-Hong; Zhao, Yu-Jun; Zhang, Ming

2016-01-01

We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM) model and Local Phase Quantization (LPQ) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.

VLSI realization of learning vector quantization with hardware/software co-design for different applications

NASA Astrophysics Data System (ADS)

An, Fengwei; Akazawa, Toshinobu; Yamasaki, Shogo; Chen, Lei; Jürgen Mattausch, Hans

2015-04-01

This paper reports a VLSI realization of learning vector quantization (LVQ) with high flexibility for different applications. It is based on a hardware/software (HW/SW) co-design concept for on-chip learning and recognition and designed as a SoC in 180 nm CMOS. The time consuming nearest Euclidean distance search in the LVQ algorithm’s competition layer is efficiently implemented as a pipeline with parallel p-word input. Since neuron number in the competition layer, weight values, input and output number are scalable, the requirements of many different applications can be satisfied without hardware changes. Classification of a d-dimensional input vector is completed in n × \\lceil d/p \\rceil + R clock cycles, where R is the pipeline depth, and n is the number of reference feature vectors (FVs). Adjustment of stored reference FVs during learning is done by the embedded 32-bit RISC CPU, because this operation is not time critical. The high flexibility is verified by the application of human detection with different numbers for the dimensionality of the FVs.

Vector quantization for efficient coding of upper subbands

NASA Technical Reports Server (NTRS)

Zeng, W. J.; Huang, Y. F.

1994-01-01

This paper examines the application of vector quantization (VQ) to exploit both intra-band and inter-band redundancy in subband coding. The focus here is on the exploitation of inter-band dependency. It is shown that VQ is particularly suitable and effective for coding the upper subbands. Three subband decomposition-based VQ coding schemes are proposed here to exploit the inter-band dependency by making full use of the extra flexibility of VQ approach over scalar quantization. A quadtree-based variable rate VQ (VRVQ) scheme which takes full advantage of the intra-band and inter-band redundancy is first proposed. Then, a more easily implementable alternative based on an efficient block-based edge estimation technique is employed to overcome the implementational barriers of the first scheme. Finally, a predictive VQ scheme formulated in the context of finite state VQ is proposed to further exploit the dependency among different subbands. A VRVQ scheme proposed elsewhere is extended to provide an efficient bit allocation procedure. Simulation results show that these three hybrid techniques have advantages, in terms of peak signal-to-noise ratio (PSNR) and complexity, over other existing subband-VQ approaches.

Efficient boundary hunting via vector quantization

NASA Astrophysics Data System (ADS)

Diamantini, Claudia; Panti, Maurizio

2001-03-01

A great amount of information about a classification problem is contained in those instances falling near the decision boundary. This intuition dates back to the earliest studies in pattern recognition, and in the more recent adaptive approaches to the so called boundary hunting, such as the work of Aha et alii on Instance Based Learning and the work of Vapnik et alii on Support Vector Machines. The last work is of particular interest, since theoretical and experimental results ensure the accuracy of boundary reconstruction. However, its optimization approach has heavy computational and memory requirements, which limits its application on huge amounts of data. In the paper we describe an alternative approach to boundary hunting based on adaptive labeled quantization architectures. The adaptation is performed by a stochastic gradient algorithm for the minimization of the error probability. Error probability minimization guarantees the accurate approximation of the optimal decision boundary, while the use of a stochastic gradient algorithm defines an efficient method to reach such approximation. In the paper comparisons to Support Vector Machines are considered.

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).

Evaluation of Raman spectra of human brain tumor tissue using the learning vector quantization neural network

NASA Astrophysics Data System (ADS)

Liu, Tuo; Chen, Changshui; Shi, Xingzhe; Liu, Chengyong

2016-05-01

The Raman spectra of tissue of 20 brain tumor patients was recorded using a confocal microlaser Raman spectroscope with 785 nm excitation in vitro. A total of 133 spectra were investigated. Spectra peaks from normal white matter tissue and tumor tissue were analyzed. Algorithms, such as principal component analysis, linear discriminant analysis, and the support vector machine, are commonly used to analyze spectral data. However, in this study, we employed the learning vector quantization (LVQ) neural network, which is typically used for pattern recognition. By applying the proposed method, a normal diagnosis accuracy of 85.7% and a glioma diagnosis accuracy of 89.5% were achieved. The LVQ neural network is a recent approach to excavating Raman spectra information. Moreover, it is fast and convenient, does not require the spectra peak counterpart, and achieves a relatively high accuracy. It can be used in brain tumor prognostics and in helping to optimize the cutting margins of gliomas.

Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology.

PubMed

Hipp, Jason D; Cheng, Jerome Y; Toner, Mehmet; Tompkins, Ronald G; Balis, Ulysses J

2011-02-26

HISTORICALLY, EFFECTIVE CLINICAL UTILIZATION OF IMAGE ANALYSIS AND PATTERN RECOGNITION ALGORITHMS IN PATHOLOGY HAS BEEN HAMPERED BY TWO CRITICAL LIMITATIONS: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. With the advent of the recent and rapid adoption of whole slide imaging solutions, the former limitation has been largely resolved. However, with the expectation that it is unlikely for the general cohort of contemporary pathologists to gain advanced image analysis skills in the short term, the latter problem remains, thus underscoring the need for a class of algorithm that has the concurrent properties of image domain (or organ system) independence and extreme ease of use, without the need for specialized training or expertise. In this report, we present a novel, general case pattern recognition algorithm, Spatially Invariant Vector Quantization (SIVQ), that overcomes the aforementioned knowledge deficit. Fundamentally based on conventional Vector Quantization (VQ) pattern recognition approaches, SIVQ gains its superior performance and essentially zero-training workflow model from its use of ring vectors, which exhibit continuous symmetry, as opposed to square or rectangular vectors, which do not. By use of the stochastic matching properties inherent in continuous symmetry, a single ring vector can exhibit as much as a millionfold improvement in matching possibilities, as opposed to conventional VQ vectors. SIVQ was utilized to demonstrate rapid and highly precise pattern recognition capability in a broad range of gross and microscopic use-case settings. With the performance of SIVQ observed thus far, we find evidence that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a turnkey solution. We anticipate that SIVQ, and other related class-independent pattern recognition algorithms, will become part of the overall armamentarium of digital image analysis approaches that are immediately available to practicing pathologists, without the need for the immediate availability of an image analysis expert.

Digital television system design study

NASA Technical Reports Server (NTRS)

Huth, G. K.

1976-01-01

The use of digital techniques for transmission of pictorial data is discussed for multi-frame images (television). Video signals are processed in a manner which includes quantization and coding such that they are separable from the noise introduced into the channel. The performance of digital television systems is determined by the nature of the processing techniques (i.e., whether the video signal itself or, instead, something related to the video signal is quantized and coded) and to the quantization and coding schemes employed.

Image Classification of Ribbed Smoked Sheet using Learning Vector Quantization

NASA Astrophysics Data System (ADS)

Rahmat, R. F.; Pulungan, A. F.; Faza, S.; Budiarto, R.

2017-01-01

Natural rubber is an important export commodity in Indonesia, which can be a major contributor to national economic development. One type of rubber used as rubber material exports is Ribbed Smoked Sheet (RSS). The quantity of RSS exports depends on the quality of RSS. RSS rubber quality has been assigned in SNI 06-001-1987 and the International Standards of Quality and Packing for Natural Rubber Grades (The Green Book). The determination of RSS quality is also known as the sorting process. In the rubber factones, the sorting process is still done manually by looking and detecting at the levels of air bubbles on the surface of the rubber sheet by naked eyes so that the result is subjective and not so good. Therefore, a method is required to classify RSS rubber automatically and precisely. We propose some image processing techniques for the pre-processing, zoning method for feature extraction and Learning Vector Quantization (LVQ) method for classifying RSS rubber into two grades, namely RSS1 and RSS3. We used 120 RSS images as training dataset and 60 RSS images as testing dataset. The result shows that our proposed method can give 89% of accuracy and the best perform epoch is in the fifteenth epoch.

Progressive low-bitrate digital color/monochrome image coding by neuro-fuzzy clustering

NASA Astrophysics Data System (ADS)

Mitra, Sunanda; Meadows, Steven

1997-10-01

Color image coding at low bit rates is an area of research that is just being addressed in recent literature since the problems of storage and transmission of color images are becoming more prominent in many applications. Current trends in image coding exploit the advantage of subband/wavelet decompositions in reducing the complexity in optimal scalar/vector quantizer (SQ/VQ) design. Compression ratios (CRs) of the order of 10:1 to 20:1 with high visual quality have been achieved by using vector quantization of subband decomposed color images in perceptually weighted color spaces. We report the performance of a recently developed adaptive vector quantizer, namely, AFLC-VQ for effective reduction in bit rates while maintaining high visual quality of reconstructed color as well as monochrome images. For 24 bit color images, excellent visual quality is maintained upto a bit rate reduction to approximately 0.48 bpp (for each color plane or monochrome 0.16 bpp, CR 50:1) by using the RGB color space. Further tuning of the AFLC-VQ, and addition of an entropy coder module after the VQ stage results in extremely low bit rates (CR 80:1) for good quality, reconstructed images. Our recent study also reveals that for similar visual quality, RGB color space requires less bits/pixel than either the YIQ, or HIS color space for storing the same information when entropy coding is applied. AFLC-VQ outperforms other standard VQ and adaptive SQ techniques in retaining visual fidelity at similar bit rate reduction.

GENERAL: Scattering Phase Correction for Semiclassical Quantization Rules in Multi-Dimensional Quantum Systems

NASA Astrophysics Data System (ADS)

Huang, Wen-Min; Mou, Chung-Yu; Chang, Cheng-Hung

2010-02-01

While the scattering phase for several one-dimensional potentials can be exactly derived, less is known in multi-dimensional quantum systems. This work provides a method to extend the one-dimensional phase knowledge to multi-dimensional quantization rules. The extension is illustrated in the example of Bogomolny's transfer operator method applied in two quantum wells bounded by step potentials of different heights. This generalized semiclassical method accurately determines the energy spectrum of the systems, which indicates the substantial role of the proposed phase correction. Theoretically, the result can be extended to other semiclassical methods, such as Gutzwiller trace formula, dynamical zeta functions, and semiclassical Landauer-Büttiker formula. In practice, this recipe enhances the applicability of semiclassical methods to multi-dimensional quantum systems bounded by general soft potentials.

Coherent states for the relativistic harmonic oscillator

NASA Technical Reports Server (NTRS)

Aldaya, Victor; Guerrero, J.

1995-01-01

Recently we have obtained, on the basis of a group approach to quantization, a Bargmann-Fock-like realization of the Relativistic Harmonic Oscillator as well as a generalized Bargmann transform relating fock wave functions and a set of relativistic Hermite polynomials. Nevertheless, the relativistic creation and annihilation operators satisfy typical relativistic commutation relations of the Lie product (vector-z, vector-z(sup dagger)) approximately equals Energy (an SL(2,R) algebra). Here we find higher-order polarization operators on the SL(2,R) group, providing canonical creation and annihilation operators satisfying the Lie product (vector-a, vector-a(sup dagger)) = identity vector 1, the eigenstates of which are 'true' coherent states.

On families of differential equations on two-torus with all phase-lock areas

NASA Astrophysics Data System (ADS)

Glutsyuk, Alexey; Rybnikov, Leonid

2017-01-01

We consider two-parametric families of non-autonomous ordinary differential equations on the two-torus with coordinates (x, t) of the type \\overset{\\centerdot}{{x}} =v(x)+A+Bf(t) . We study its rotation number as a function of the parameters (A, B). The phase-lock areas are those level sets of the rotation number function ρ =ρ (A,B) that have non-empty interiors. Buchstaber, Karpov and Tertychnyi studied the case when v(x)=\\sin x in their joint paper. They observed the quantization effect: for every smooth periodic function f(t) the family of equations may have phase-lock areas only for integer rotation numbers. Another proof of this quantization statement was later obtained in a joint paper by Ilyashenko, Filimonov and Ryzhov. This implies a similar quantization effect for every v(x)=a\\sin (mx)+b\\cos (mx)+c and rotation numbers that are multiples of \\frac{1}{m} . We show that for every other analytic vector field v(x) (i.e. having at least two Fourier harmonics with non-zero non-opposite degrees and nonzero coefficients) there exists an analytic periodic function f(t) such that the corresponding family of equations has phase-lock areas for all the rational values of the rotation number.

Recursive optimal pruning with applications to tree structured vector quantizers

NASA Technical Reports Server (NTRS)

Kiang, Shei-Zein; Baker, Richard L.; Sullivan, Gary J.; Chiu, Chung-Yen

1992-01-01

A pruning algorithm of Chou et al. (1989) for designing optimal tree structures identifies only those codebooks which lie on the convex hull of the original codebook's operational distortion rate function. The authors introduce a modified version of the original algorithm, which identifies a large number of codebooks having minimum average distortion, under the constraint that, in each step, only modes having no descendents are removed from the tree. All codebooks generated by the original algorithm are also generated by this algorithm. The new algorithm generates a much larger number of codebooks in the middle- and low-rate regions. The additional codebooks permit operation near the codebook's operational distortion rate function without time sharing by choosing from the increased number of available bit rates. Despite the statistical mismatch which occurs when coding data outside the training sequence, these pruned codebooks retain their performance advantage over full search vector quantizers (VQs) for a large range of rates.

Quantized Overcomplete Expansions: Analysis, Synthesis and Algorithms

DTIC Science & Technology

1995-07-01

would be in the spirit of the Lempel - Ziv algorithm . The decoder would have to be aware of changes in the dictionary, but depending on the nature of the...37 3.4 A General Vector Compression Algorithm Based on Frames : : : : : : : : : : 40 ii 3.4.1 Design Considerations...x3.3. Along with exploring general properties of matching pursuit, we are interested in its application to compressing data vectors in RN. A general

Dynamics of entropy and nonclassical properties of the state of a Λ-type three-level atom interacting with a single-mode cavity field with intensity-dependent coupling in a Kerr medium

NASA Astrophysics Data System (ADS)

Faghihi, M. J.; Tavassoly, M. K.

2012-02-01

In this paper, we study the interaction between a three-level atom and a quantized single-mode field with ‘intensity-dependent coupling’ in a ‘Kerr medium’. The three-level atom is considered to be in a Λ-type configuration. Under particular initial conditions, which may be prepared for the atom and the field, the dynamical state vector of the entire system will be explicitly obtained, for the arbitrary nonlinearity function f(n) associated with any physical system. Then, after evaluating the variation of the field entropy against time, we will investigate the quantum statistics as well as some of the nonclassical properties of the introduced state. During our calculations we investigate the effects of intensity-dependent coupling, Kerr medium and detuning parameters on the depth and domain of the nonclassicality features of the atom-field state vector. Finally, we compare our obtained results with those of V-type three-level atoms.

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

Quantum theory of structured monochromatic light

NASA Astrophysics Data System (ADS)

Punnoose, Alexander; Tu, J. J.

2017-08-01

Applications that envisage utilizing the orbital angular momentum (OAM) at the single photon level assume that the OAM degrees of freedom of the photons are orthogonal. To test this critical assumption, we quantize the beam-like solutions of the vector Helmholtz equation from first principles. We show that although the photon operators of a diffracting monochromatic beam do not in general satisfy the canonical commutation relations, implying that the photon states in Fock space are not orthogonal, the states are bona fide eigenstates of the number and Hamiltonian operators. As a result, the representation for the photon operators presented in this work form a natural basis to study structured monochromatic light at the single photon level.

A new local-global approach for classification.

PubMed

Peres, R T; Pedreira, C E

2010-09-01

In this paper, we propose a new local-global pattern classification scheme that combines supervised and unsupervised approaches, taking advantage of both, local and global environments. We understand as global methods the ones concerned with the aim of constructing a model for the whole problem space using the totality of the available observations. Local methods focus into sub regions of the space, possibly using an appropriately selected subset of the sample. In the proposed method, the sample is first divided in local cells by using a Vector Quantization unsupervised algorithm, the LBG (Linde-Buzo-Gray). In a second stage, the generated assemblage of much easier problems is locally solved with a scheme inspired by Bayes' rule. Four classification methods were implemented for comparison purposes with the proposed scheme: Learning Vector Quantization (LVQ); Feedforward Neural Networks; Support Vector Machine (SVM) and k-Nearest Neighbors. These four methods and the proposed scheme were implemented in eleven datasets, two controlled experiments, plus nine public available datasets from the UCI repository. The proposed method has shown a quite competitive performance when compared to these classical and largely used classifiers. Our method is simple concerning understanding and implementation and is based on very intuitive concepts. Copyright 2010 Elsevier Ltd. All rights reserved.

Quantization of high dimensional Gaussian vector using permutation modulation with application to information reconciliation in continuous variable QKD

NASA Astrophysics Data System (ADS)

Daneshgaran, Fred; Mondin, Marina; Olia, Khashayar

This paper is focused on the problem of Information Reconciliation (IR) for continuous variable Quantum Key Distribution (QKD). The main problem is quantization and assignment of labels to the samples of the Gaussian variables observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective Signal-to-Noise Ratio (SNR) exasperating the problem. Quantization over higher dimensions is advantageous since it allows for fractional bit per sample accuracy which may be needed at very low SNR conditions whereby the achievable secret key rate is significantly less than one bit per sample. In this paper, we propose to use Permutation Modulation (PM) for quantization of Gaussian vectors potentially containing thousands of samples. PM is applied to the magnitudes of the Gaussian samples and we explore the dependence of the sign error probability on the magnitude of the samples. At very low SNR, we may transmit the entire label of the PM code from Bob to Alice in Reverse Reconciliation (RR) over public channel. The side information extracted from this label can then be used by Alice to characterize the sign error probability of her individual samples. Forward Error Correction (FEC) coding can be used by Bob on each subset of samples with similar sign error probability to aid Alice in error correction. This can be done for different subsets of samples with similar sign error probabilities leading to an Unequal Error Protection (UEP) coding paradigm.

An efficient system for reliably transmitting image and video data over low bit rate noisy channels

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.; Huang, Y. F.; Stevenson, Robert L.

1994-01-01

This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices.

Studies on image compression and image reconstruction

NASA Technical Reports Server (NTRS)

Sayood, Khalid; Nori, Sekhar; Araj, A.

1994-01-01

During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.

Optical systolic array processor using residue arithmetic

NASA Technical Reports Server (NTRS)

Jackson, J.; Casasent, D.

1983-01-01

The use of residue arithmetic to increase the accuracy and reduce the dynamic range requirements of optical matrix-vector processors is evaluated. It is determined that matrix-vector operations and iterative algorithms can be performed totally in residue notation. A new parallel residue quantizer circuit is developed which significantly improves the performance of the systolic array feedback processor. Results are presented of a computer simulation of this system used to solve a set of three simultaneous equations.

Measuring and Modeling Shared Visual Attention

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.; Gontar, Patrick

2016-01-01

Multi-person teams are sometimes responsible for critical tasks, such as flying an airliner. Here we present a method using gaze tracking data to assess shared visual attention, a term we use to describe the situation where team members are attending to a common set of elements in the environment. Gaze data are quantized with respect to a set of N areas of interest (AOIs); these are then used to construct a time series of N dimensional vectors, with each vector component representing one of the AOIs, all set to 0 except for the component corresponding to the currently fixated AOI, which is set to 1. The resulting sequence of vectors can be averaged in time, with the result that each vector component represents the proportion of time that the corresponding AOI was fixated within the given time interval. We present two methods for comparing sequences of this sort, one based on computing the time-varying correlation of the averaged vectors, and another based on a chi-square test testing the hypothesis that the observed gaze proportions are drawn from identical probability distributions. We have evaluated the method using synthetic data sets, in which the behavior was modeled as a series of "activities," each of which was modeled as a first-order Markov process. By tabulating distributions for pairs of identical and disparate activities, we are able to perform a receiver operating characteristic (ROC) analysis, allowing us to choose appropriate criteria and estimate error rates. We have applied the methods to data from airline crews, collected in a high-fidelity flight simulator (Haslbeck, Gontar & Schubert, 2014). We conclude by considering the problem of automatic (blind) discovery of activities, using methods developed for text analysis.

Measuring and Modeling Shared Visual Attention

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.

2016-01-01

Multi-person teams are sometimes responsible for critical tasks, such as flying an airliner. Here we present a method using gaze tracking data to assess shared visual attention, a term we use to describe the situation where team members are attending to a common set of elements in the environment. Gaze data are quantized with respect to a set of N areas of interest (AOIs); these are then used to construct a time series of N dimensional vectors, with each vector component representing one of the AOIs, all set to 0 except for the component corresponding to the currently fixated AOI, which is set to 1. The resulting sequence of vectors can be averaged in time, with the result that each vector component represents the proportion of time that the corresponding AOI was fixated within the given time interval. We present two methods for comparing sequences of this sort, one based on computing the time-varying correlation of the averaged vectors, and another based on a chi-square test testing the hypothesis that the observed gaze proportions are drawn from identical probability distributions.We have evaluated the method using synthetic data sets, in which the behavior was modeled as a series of activities, each of which was modeled as a first-order Markov process. By tabulating distributions for pairs of identical and disparate activities, we are able to perform a receiver operating characteristic (ROC) analysis, allowing us to choose appropriate criteria and estimate error rates.We have applied the methods to data from airline crews, collected in a high-fidelity flight simulator (Haslbeck, Gontar Schubert, 2014). We conclude by considering the problem of automatic (blind) discovery of activities, using methods developed for text analysis.

Image segmentation using hidden Markov Gauss mixture models.

PubMed

Pyun, Kyungsuk; Lim, Johan; Won, Chee Sun; Gray, Robert M

2007-07-01

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

FIVQ algorithm for interference hyper-spectral image compression

NASA Astrophysics Data System (ADS)

Wen, Jia; Ma, Caiwen; Zhao, Junsuo

2014-07-01

Based on the improved vector quantization (IVQ) algorithm [1] which was proposed in 2012, this paper proposes a further improved vector quantization (FIVQ) algorithm for LASIS (Large Aperture Static Imaging Spectrometer) interference hyper-spectral image compression. To get better image quality, IVQ algorithm takes both the mean values and the VQ indices as the encoding rules. Although IVQ algorithm can improve both the bit rate and the image quality, it still can be further improved in order to get much lower bit rate for the LASIS interference pattern with the special optical characteristics based on the pushing and sweeping in LASIS imaging principle. In the proposed algorithm FIVQ, the neighborhood of the encoding blocks of the interference pattern image, which are using the mean value rules, will be checked whether they have the same mean value as the current processing block. Experiments show the proposed algorithm FIVQ can get lower bit rate compared to that of the IVQ algorithm for the LASIS interference hyper-spectral sequences.

Quantization, Frobenius and Bi algebras from the Categorical Framework of Quantum Mechanics to Natural Language Semantics

NASA Astrophysics Data System (ADS)

Sadrzadeh, Mehrnoosh

2017-07-01

Compact Closed categories and Frobenius and Bi algebras have been applied to model and reason about Quantum protocols. The same constructions have also been applied to reason about natural language semantics under the name: ``categorical distributional compositional'' semantics, or in short, the ``DisCoCat'' model. This model combines the statistical vector models of word meaning with the compositional models of grammatical structure. It has been applied to natural language tasks such as disambiguation, paraphrasing and entailment of phrases and sentences. The passage from the grammatical structure to vectors is provided by a functor, similar to the Quantization functor of Quantum Field Theory. The original DisCoCat model only used compact closed categories. Later, Frobenius algebras were added to it to model long distance dependancies such as relative pronouns. Recently, bialgebras have been added to the pack to reason about quantifiers. This paper reviews these constructions and their application to natural language semantics. We go over the theory and present some of the core experimental results.

Learning vector quantization neural networks improve accuracy of transcranial color-coded duplex sonography in detection of middle cerebral artery spasm--preliminary report.

PubMed

Swiercz, Miroslaw; Kochanowicz, Jan; Weigele, John; Hurst, Robert; Liebeskind, David S; Mariak, Zenon; Melhem, Elias R; Krejza, Jaroslaw

2008-01-01

To determine the performance of an artificial neural network in transcranial color-coded duplex sonography (TCCS) diagnosis of middle cerebral artery (MCA) spasm. TCCS was prospectively acquired within 2 h prior to routine cerebral angiography in 100 consecutive patients (54M:46F, median age 50 years). Angiographic MCA vasospasm was classified as mild (<25% of vessel caliber reduction), moderate (25-50%), or severe (>50%). A Learning Vector Quantization neural network classified MCA spasm based on TCCS peak-systolic, mean, and end-diastolic velocity data. During a four-class discrimination task, accurate classification by the network ranged from 64.9% to 72.3%, depending on the number of neurons in the Kohonen layer. Accurate classification of vasospasm ranged from 79.6% to 87.6%, with an accuracy of 84.7% to 92.1% for the detection of moderate-to-severe vasospasm. An artificial neural network may increase the accuracy of TCCS in diagnosis of MCA spasm.

Joint Machine Learning and Game Theory for Rate Control in High Efficiency Video Coding.

PubMed

Gao, Wei; Kwong, Sam; Jia, Yuheng

2017-08-25

In this paper, a joint machine learning and game theory modeling (MLGT) framework is proposed for inter frame coding tree unit (CTU) level bit allocation and rate control (RC) optimization in High Efficiency Video Coding (HEVC). First, a support vector machine (SVM) based multi-classification scheme is proposed to improve the prediction accuracy of CTU-level Rate-Distortion (R-D) model. The legacy "chicken-and-egg" dilemma in video coding is proposed to be overcome by the learning-based R-D model. Second, a mixed R-D model based cooperative bargaining game theory is proposed for bit allocation optimization, where the convexity of the mixed R-D model based utility function is proved, and Nash bargaining solution (NBS) is achieved by the proposed iterative solution search method. The minimum utility is adjusted by the reference coding distortion and frame-level Quantization parameter (QP) change. Lastly, intra frame QP and inter frame adaptive bit ratios are adjusted to make inter frames have more bit resources to maintain smooth quality and bit consumption in the bargaining game optimization. Experimental results demonstrate that the proposed MLGT based RC method can achieve much better R-D performances, quality smoothness, bit rate accuracy, buffer control results and subjective visual quality than the other state-of-the-art one-pass RC methods, and the achieved R-D performances are very close to the performance limits from the FixedQP method.

Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic

NASA Astrophysics Data System (ADS)

Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; Breivik, L.-A.

2010-10-01

The retrieval of sea ice motion with the Maximum Cross-Correlation (MCC) method from low-resolution (10-15 km) spaceborne imaging sensors is challenged by a dominating quantization noise as the time span of displacement vectors is shortened. To allow investigating shorter displacements from these instruments, we introduce an alternative sea ice motion tracking algorithm that builds on the MCC method but relies on a continuous optimization step for computing the motion vector. The prime effect of this method is to effectively dampen the quantization noise, an artifact of the MCC. It allows for retrieving spatially smooth 48 h sea ice motion vector fields in the Arctic. Strategies to detect and correct erroneous vectors as well as to optimally merge several polarization channels of a given instrument are also described. A test processing chain is implemented and run with several active and passive microwave imagers (Advanced Microwave Scanning Radiometer-EOS (AMSR-E), Special Sensor Microwave Imager, and Advanced Scatterometer) during three Arctic autumn, winter, and spring seasons. Ice motion vectors are collocated to and compared with GPS positions of in situ drifters. Error statistics are shown to be ranging from 2.5 to 4.5 km (standard deviation for components of the vectors) depending on the sensor, without significant bias. We discuss the relative contribution of measurement and representativeness errors by analyzing monthly validation statistics. The 37 GHz channels of the AMSR-E instrument allow for the best validation statistics. The operational low-resolution sea ice drift product of the EUMETSAT OSI SAF (European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility) is based on the algorithms presented in this paper.

Particle on a torus knot: Constrained dynamics and semi-classical quantization in a magnetic field

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

Das, Praloy, E-mail: praloydasdurgapur@gmail.com; Pramanik, Souvik, E-mail: souvick.in@gmail.com; Ghosh, Subir, E-mail: subirghosh20@gmail.com

2016-11-15

Kinematics and dynamics of a particle moving on a torus knot poses an interesting problem as a constrained system. In the first part of the paper we have derived the modified symplectic structure or Dirac brackets of the above model in Dirac’s Hamiltonian framework, both in toroidal and Cartesian coordinate systems. This algebra has been used to study the dynamics, in particular small fluctuations in motion around a specific torus. The spatial symmetries of the system have also been studied. In the second part of the paper we have considered the quantum theory of a charge moving in a torusmore » knot in the presence of a uniform magnetic field along the axis of the torus in a semiclassical quantization framework. We exploit the Einstein–Brillouin–Keller (EBK) scheme of quantization that is appropriate for multidimensional systems. Embedding of the knot on a specific torus is inherently two dimensional that gives rise to two quantization conditions. This shows that although the system, after imposing the knot condition reduces to a one dimensional system, even then it has manifested non-planar features which shows up again in the study of fractional angular momentum. Finally we compare the results obtained from EBK (multi-dimensional) and Bohr–Sommerfeld (single dimensional) schemes. The energy levels and fractional spin depend on the torus knot parameters that specifies its non-planar features. Interestingly, we show that there can be non-planar corrections to the planar anyon-like fractional spin.« less

Vector adaptive predictive coder for speech and audio

NASA Technical Reports Server (NTRS)

Chen, Juin-Hwey (Inventor); Gersho, Allen (Inventor)

1990-01-01

A real-time vector adaptive predictive coder which approximates each vector of K speech samples by using each of M fixed vectors in a first codebook to excite a time-varying synthesis filter and picking the vector that minimizes distortion. Predictive analysis for each frame determines parameters used for computing from vectors in the first codebook zero-state response vectors that are stored at the same address (index) in a second codebook. Encoding of input speech vectors s.sub.n is then carried out using the second codebook. When the vector that minimizes distortion is found, its index is transmitted to a decoder which has a codebook identical to the first codebook of the decoder. There the index is used to read out a vector that is used to synthesize an output speech vector s.sub.n. The parameters used in the encoder are quantized, for example by using a table, and the indices are transmitted to the decoder where they are decoded to specify transfer characteristics of filters used in producing the vector s.sub.n from the receiver codebook vector selected by the vector index transmitted.

Prior-Based Quantization Bin Matching for Cloud Storage of JPEG Images.

PubMed

Liu, Xianming; Cheung, Gene; Lin, Chia-Wen; Zhao, Debin; Gao, Wen

2018-07-01

Millions of user-generated images are uploaded to social media sites like Facebook daily, which translate to a large storage cost. However, there exists an asymmetry in upload and download data: only a fraction of the uploaded images are subsequently retrieved for viewing. In this paper, we propose a cloud storage system that reduces the storage cost of all uploaded JPEG photos, at the expense of a controlled increase in computation mainly during download of requested image subset. Specifically, the system first selectively re-encodes code blocks of uploaded JPEG images using coarser quantization parameters for smaller storage sizes. Then during download, the system exploits known signal priors-sparsity prior and graph-signal smoothness prior-for reverse mapping to recover original fine quantization bin indices, with either deterministic guarantee (lossless mode) or statistical guarantee (near-lossless mode). For fast reverse mapping, we use small dictionaries and sparse graphs that are tailored for specific clusters of similar blocks, which are classified via tree-structured vector quantizer. During image upload, cluster indices identifying the appropriate dictionaries and graphs for the re-quantized blocks are encoded as side information using a differential distributed source coding scheme to facilitate reverse mapping during image download. Experimental results show that our system can reap significant storage savings (up to 12.05%) at roughly the same image PSNR (within 0.18 dB).

Quantization noise in digital speech. M.S. Thesis- Houston Univ.

NASA Technical Reports Server (NTRS)

Schmidt, O. L.

1972-01-01

The amount of quantization noise generated in a digital-to-analog converter is dependent on the number of bits or quantization levels used to digitize the analog signal in the analog-to-digital converter. The minimum number of quantization levels and the minimum sample rate were derived for a digital voice channel. A sample rate of 6000 samples per second and lowpass filters with a 3 db cutoff of 2400 Hz are required for 100 percent sentence intelligibility. Consonant sounds are the first speech components to be degraded by quantization noise. A compression amplifier can be used to increase the weighting of the consonant sound amplitudes in the analog-to-digital converter. An expansion network must be installed at the output of the digital-to-analog converter to restore the original weighting of the consonant sounds. This technique results in 100 percent sentence intelligibility for a sample rate of 5000 samples per second, eight quantization levels, and lowpass filters with a 3 db cutoff of 2000 Hz.

Physics-based Detection of Subpixel Targets in Hyperspectral Imagery

DTIC Science & Technology

2007-01-01

Learning Vector Quantization LWIR ...Wave Infrared ( LWIR ) from 7.0 to 15.0 microns regions as well. At these wavelengths, emissivity dominates the spectral signature. Emissivity is...object emits instead of reflects. Initial work has already been finished applying the hybrid detectors to LWIR sensors [13]. However, target

Multipath search coding of stationary signals with applications to speech

NASA Astrophysics Data System (ADS)

Fehn, H. G.; Noll, P.

1982-04-01

This paper deals with the application of multipath search coding (MSC) concepts to the coding of stationary memoryless and correlated sources, and of speech signals, at a rate of one bit per sample. Use is made of three MSC classes: (1) codebook coding, or vector quantization, (2) tree coding, and (3) trellis coding. This paper explains the performances of these coders and compares them both with those of conventional coders and with rate-distortion bounds. The potentials of MSC coding strategies are demonstrated by illustrations. The paper reports also on results of MSC coding of speech, where both the strategy of adaptive quantization and of adaptive prediction were included in coder design.

Vacuum polarization of the quantized massive fields in Friedman-Robertson-Walker spacetime

NASA Astrophysics Data System (ADS)

Matyjasek, Jerzy; Sadurski, Paweł; Telecka, Małgorzata

2014-04-01

The stress-energy tensor of the quantized massive fields in a spatially open, flat, and closed Friedman-Robertson-Walker universe is constructed using the adiabatic regularization (for the scalar field) and the Schwinger-DeWitt approach (for the scalar, spinor, and vector fields). It is shown that the stress-energy tensor calculated in the sixth adiabatic order coincides with the result obtained from the regularized effective action, constructed from the heat kernel coefficient a3. The behavior of the tensor is examined in the power-law cosmological models, and the semiclassical Einstein field equations are solved exactly in a few physically interesting cases, such as the generalized Starobinsky models.

Comparison of Radio Frequency Distinct Native Attribute and Matched Filtering Techniques for Device Discrimination and Operation Identification

DTIC Science & Technology

identification. URE from ten MSP430F5529 16-bit microcontrollers were analyzed using: 1) RF distinct native attributes (RF-DNA) fingerprints paired with multiple...discriminant analysis/maximum likelihood (MDA/ML) classification, 2) RF-DNA fingerprints paired with generalized relevance learning vector quantized

Image segmentation using fuzzy LVQ clustering networks

NASA Technical Reports Server (NTRS)

Tsao, Eric Chen-Kuo; Bezdek, James C.; Pal, Nikhil R.

1992-01-01

In this note we formulate image segmentation as a clustering problem. Feature vectors extracted from a raw image are clustered into subregions, thereby segmenting the image. A fuzzy generalization of a Kohonen learning vector quantization (LVQ) which integrates the Fuzzy c-Means (FCM) model with the learning rate and updating strategies of the LVQ is used for this task. This network, which segments images in an unsupervised manner, is thus related to the FCM optimization problem. Numerical examples on photographic and magnetic resonance images are given to illustrate this approach to image segmentation.

Theory of the Quantized Hall Conductance in Periodic Systems: a Topological Analysis.

NASA Astrophysics Data System (ADS)

Czerwinski, Michael Joseph

The integral quantization of the Hall conductance in two-dimensional periodic systems is investigated from a topological point of view. Attention is focused on the contributions from the electronic sub-bands which arise from perturbed Landau levels. After reviewing the theoretical work leading to the identification of the Hall conductance as a topological quantum number, both a determination and interpretation of these quantized values for the sub-band conductances is made. It is shown that the Hall conductance of each sub-band can be regarded as the sum of two terms which will be referred to as classical and nonclassical. Although each of these contributions individually leads to a fractional conductance, the sum of these two contributions does indeed yield an integer. These integral conductances are found to be given by the solution of a simple Diophantine equation which depends on the periodic perturbation. A connection between the quantized value of the Hall conductance and the covering of real space by the zeroes of the sub-band wavefunctions allows for a determination of these conductances under more general potentials. A method is described for obtaining the conductance values from only those states bordering the Brillouin zone, and not the states in its interior. This method is demonstrated to give Hall conductances in agreement with those obtained from the Diophantine equation for the sinusoidal potential case explored earlier. Generalizing a simple gauge invariance argument from real space to k-space, a k-space 'vector potential' is introduced. This allows for a explicit identification of the Hall conductance with the phase winding number of the sub-band wavefunction around the Brillouin zone. The previously described division of the Hall conductance into classical and nonclassical contributions is in this way made more rigorous; based on periodicity considerations alone, these terms are identified as the winding numbers associated with (i) the basis states and (ii) the coefficients of these basis states, respectively. In this way a general Diophantine equation, independent of the periodic potential, is obtained. Finally, the use of the 'parallel transport' of state vectors in the determination of an overall phase convention for these states is described. This is seen to lead to a simple and straightforward method for determining the Hall conductance. This method is based on the states directly, without reference to the particular component wavefunctions of these states. Mention is made of the generality of calculations of this type, within the context of the geometric (or Berry) phases acquired by systems under an adiabatic modification of their environment.

Supporting Dynamic Quantization for High-Dimensional Data Analytics.

PubMed

Guzun, Gheorghi; Canahuate, Guadalupe

2017-05-01

Similarity searches are at the heart of exploratory data analysis tasks. Distance metrics are typically used to characterize the similarity between data objects represented as feature vectors. However, when the dimensionality of the data increases and the number of features is large, traditional distance metrics fail to distinguish between the closest and furthest data points. Localized distance functions have been proposed as an alternative to traditional distance metrics. These functions only consider dimensions close to query to compute the distance/similarity. Furthermore, in order to enable interactive explorations of high-dimensional data, indexing support for ad-hoc queries is needed. In this work we set up to investigate whether bit-sliced indices can be used for exploratory analytics such as similarity searches and data clustering for high-dimensional big-data. We also propose a novel dynamic quantization called Query dependent Equi-Depth (QED) quantization and show its effectiveness on characterizing high-dimensional similarity. When applying QED we observe improvements in kNN classification accuracy over traditional distance functions. Gheorghi Guzun and Guadalupe Canahuate. 2017. Supporting Dynamic Quantization for High-Dimensional Data Analytics. In Proceedings of Ex-ploreDB'17, Chicago, IL, USA, May 14-19, 2017, 6 pages. https://doi.org/http://dx.doi.org/10.1145/3077331.3077336.

Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

PubMed

Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

2017-06-22

In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

Spin dynamics of paramagnetic centers with anisotropic g tensor and spin of ½

PubMed Central

Maryasov, Alexander G.

2012-01-01

The influence of g tensor anisotropy on spin dynamics of paramagnetic centers having real or effective spin of 1/2 is studied. The g anisotropy affects both the excitation and the detection of EPR signals, producing noticeable differences between conventional continuous-wave (cw) EPR and pulsed EPR spectra. The magnitudes and directions of the spin and magnetic moment vectors are generally not proportional to each other, but are related to each other through the g tensor. The equilibrium magnetic moment direction is generally parallel to neither the magnetic field nor the spin quantization axis due to the g anisotropy. After excitation with short microwave pulses, the spin vector precesses around its quantization axis, in a plane that is generally not perpendicular to the applied magnetic field. Paradoxically, the magnetic moment vector precesses around its equilibrium direction in a plane exactly perpendicular to the external magnetic field. In the general case, the oscillating part of the magnetic moment is elliptically polarized and the direction of precession is determined by the sign of the g tensor determinant (g tensor signature). Conventional pulsed and cw EPR spectrometers do not allow determination of the g tensor signature or the ellipticity of the magnetic moment trajectory. It is generally impossible to set a uniform spin turning angle for simple pulses in an unoriented or ‘powder’ sample when g tensor anisotropy is significant. PMID:22743542

Spin dynamics of paramagnetic centers with anisotropic g tensor and spin of 1/2

NASA Astrophysics Data System (ADS)

Maryasov, Alexander G.; Bowman, Michael K.

2012-08-01

The influence of g tensor anisotropy on spin dynamics of paramagnetic centers having real or effective spin of 1/2 is studied. The g anisotropy affects both the excitation and the detection of EPR signals, producing noticeable differences between conventional continuous-wave (cw) EPR and pulsed EPR spectra. The magnitudes and directions of the spin and magnetic moment vectors are generally not proportional to each other, but are related to each other through the g tensor. The equilibrium magnetic moment direction is generally parallel to neither the magnetic field nor the spin quantization axis due to the g anisotropy. After excitation with short microwave pulses, the spin vector precesses around its quantization axis, in a plane that is generally not perpendicular to the applied magnetic field. Paradoxically, the magnetic moment vector precesses around its equilibrium direction in a plane exactly perpendicular to the external magnetic field. In the general case, the oscillating part of the magnetic moment is elliptically polarized and the direction of precession is determined by the sign of the g tensor determinant (g tensor signature). Conventional pulsed and cw EPR spectrometers do not allow determination of the g tensor signature or the ellipticity of the magnetic moment trajectory. It is generally impossible to set a uniform spin turning angle for simple pulses in an unoriented or 'powder' sample when g tensor anisotropy is significant.

Classical Field Theory and the Stress-Energy Tensor

NASA Astrophysics Data System (ADS)

Swanson, Mark S.

2015-09-01

This book is a concise introduction to the key concepts of classical field theory for beginning graduate students and advanced undergraduate students who wish to study the unifying structures and physical insights provided by classical field theory without dealing with the additional complication of quantization. In that regard, there are many important aspects of field theory that can be understood without quantizing the fields. These include the action formulation, Galilean and relativistic invariance, traveling and standing waves, spin angular momentum, gauge invariance, subsidiary conditions, fluctuations, spinor and vector fields, conservation laws and symmetries, and the Higgs mechanism, all of which are often treated briefly in a course on quantum field theory. The variational form of classical mechanics and continuum field theory are both developed in the time-honored graduate level text by Goldstein et al (2001). An introduction to classical field theory from a somewhat different perspective is available in Soper (2008). Basic classical field theory is often treated in books on quantum field theory. Two excellent texts where this is done are Greiner and Reinhardt (1996) and Peskin and Schroeder (1995). Green's function techniques are presented in Arfken et al (2013).

Path integral solution for a Klein-Gordon particle in vector and scalar deformed radial Rosen-Morse-type potentials

NASA Astrophysics Data System (ADS)

Khodja, A.; Kadja, A.; Benamira, F.; Guechi, L.

2017-12-01

The problem of a Klein-Gordon particle moving in equal vector and scalar Rosen-Morse-type potentials is solved in the framework of Feynman's path integral approach. Explicit path integration leads to a closed form for the radial Green's function associated with different shapes of the potentials. For q≤-1, and 1/2α ln | q|0, it is shown that the quantization conditions for the bound state energy levels E_{nr} are transcendental equations which can be solved numerically. Three special cases such as the standard radial Manning-Rosen potential (| q| =1), the standard radial Rosen-Morse potential (V2→ -V2,q=1) and the radial Eckart potential (V1→ -V1,q=1) are also briefly discussed.

Wavelet Transforms in Parallel Image Processing

DTIC Science & Technology

1994-01-27

NUMBER OF PAGES Object Segmentation, Texture Segmentation, Image Compression, Image 137 Halftoning , Neural Network, Parallel Algorithms, 2D and 3D...Vector Quantization of Wavelet Transform Coefficients ........ ............................. 57 B.1.f Adaptive Image Halftoning based on Wavelet...application has been directed to the adaptive image halftoning . The gray information at a pixel, including its gray value and gradient, is represented by

Light-cone quantization of two dimensional field theory in the path integral approach

NASA Astrophysics Data System (ADS)

Cortés, J. L.; Gamboa, J.

1999-05-01

A quantization condition due to the boundary conditions and the compatification of the light cone space-time coordinate x- is identified at the level of the classical equations for the right-handed fermionic field in two dimensions. A detailed analysis of the implications of the implementation of this quantization condition at the quantum level is presented. In the case of the Thirring model one has selection rules on the excitations as a function of the coupling and in the case of the Schwinger model a double integer structure of the vacuum is derived in the light-cone frame. Two different quantized chiral Schwinger models are found, one of them without a θ-vacuum structure. A generalization of the quantization condition to theories with several fermionic fields and to higher dimensions is presented.

Consensus Control of Complex and Multi-scale Networks with Network Uncertainty and Adversary

DTIC Science & Technology

2015-09-02

Mu 0.80 Yang Wang 0.50 1.60 3 PERCENT_SUPPORTEDNAME FTE Equivalent: Total Number: National Academy Member George Yin 0.11 Le Yi Wang 0.11 0.22 2...0) Nicholas Baran (0) Lijian Xu (0.3) Zhixin Yang (0) 4 PERCENT_SUPPORTEDNAME FTE Equivalent: Total Number: Project Report... Jifeng  Zhang, Asymptotically efficient identification of FIR systems with  quantized observations and general quantized inputs, Automatica, Vol. 57, pp

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

PubMed Central

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

PubMed

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

The simulation on diode-clamped five-level converters common-mode voltage suppression with zero-vector PWM strategy

NASA Astrophysics Data System (ADS)

Zhang, Yonggao; Gao, Yanli; Long, Lizhong

2012-04-01

More and more researchers have great concern on the issue of Common-mode voltage (CMV) in high voltage large power converter. A novel common-mode voltage suppression scheme based on zero-vector PWM strategy (ZVPWM) is present in this paper. Taking a diode-clamped five-level converter as example, the principle of zero vector PWM common-mode voltage (ZCMVPWM) suppression method is studied in detail. ZCMVPWM suppression strategy is including four important parts, which are locating the sector of reference voltage vector, locating the small triangular sub-sector of reference voltage vector, reference vector synthesis, and calculating the operating time of vector. The principles of four important pars are illustrated in detail and the corresponding MATLAB models are established. System simulation and experimental results are provided. It gives some consultation value for the development and research of multi-level converters.

Visibility of wavelet quantization noise

NASA Technical Reports Server (NTRS)

Watson, A. B.; Yang, G. Y.; Solomon, J. A.; Villasenor, J.

1997-01-01

The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.

Strapdown system performance optimization test evaluations (SPOT), volume 1

NASA Technical Reports Server (NTRS)

Blaha, R. J.; Gilmore, J. P.

1973-01-01

A three axis inertial system was packaged in an Apollo gimbal fixture for fine grain evaluation of strapdown system performance in dynamic environments. These evaluations have provided information to assess the effectiveness of real-time compensation techniques and to study system performance tradeoffs to factors such as quantization and iteration rate. The strapdown performance and tradeoff studies conducted include: (1) Compensation models and techniques for the inertial instrument first-order error terms were developed and compensation effectivity was demonstrated in four basic environments; single and multi-axis slew, and single and multi-axis oscillatory. (2) The theoretical coning bandwidth for the first-order quaternion algorithm expansion was verified. (3) Gyro loop quantization was identified to affect proportionally the system attitude uncertainty. (4) Land navigation evaluations identified the requirement for accurate initialization alignment in order to pursue fine grain navigation evaluations.

Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances

DOE PAGES

Zhang, Yan; Inouye, Hideyo; Crowley, Michael; ...

2016-10-14

Intensity simulation of X-ray scattering from large twisted cellulose molecular fibrils is important in understanding the impact of chemical or physical treatments on structural properties such as twisting or coiling. This paper describes a highly efficient method for the simulation of X-ray diffraction patterns from complex fibrils using atom-type-specific pair-distance quantization. Pair distances are sorted into arrays which are labelled by atom type. Histograms of pair distances in each array are computed and binned and the resulting population distributions are used to represent the whole pair-distance data set. These quantized pair-distance arrays are used with a modified and vectorized Debyemore » formula to simulate diffraction patterns. This approach utilizes fewer pair distances in each iteration, and atomic scattering factors are moved outside the iteration since the arrays are labelled by atom type. As a result, this algorithm significantly reduces the computation time while maintaining the accuracy of diffraction pattern simulation, making possible the simulation of diffraction patterns from large twisted fibrils in a relatively short period of time, as is required for model testing and refinement.« less

Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances

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

Zhang, Yan; Inouye, Hideyo; Crowley, Michael

Intensity simulation of X-ray scattering from large twisted cellulose molecular fibrils is important in understanding the impact of chemical or physical treatments on structural properties such as twisting or coiling. This paper describes a highly efficient method for the simulation of X-ray diffraction patterns from complex fibrils using atom-type-specific pair-distance quantization. Pair distances are sorted into arrays which are labelled by atom type. Histograms of pair distances in each array are computed and binned and the resulting population distributions are used to represent the whole pair-distance data set. These quantized pair-distance arrays are used with a modified and vectorized Debyemore » formula to simulate diffraction patterns. This approach utilizes fewer pair distances in each iteration, and atomic scattering factors are moved outside the iteration since the arrays are labelled by atom type. This algorithm significantly reduces the computation time while maintaining the accuracy of diffraction pattern simulation, making possible the simulation of diffraction patterns from large twisted fibrils in a relatively short period of time, as is required for model testing and refinement.« less

Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances

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

Zhang, Yan; Inouye, Hideyo; Crowley, Michael

Intensity simulation of X-ray scattering from large twisted cellulose molecular fibrils is important in understanding the impact of chemical or physical treatments on structural properties such as twisting or coiling. This paper describes a highly efficient method for the simulation of X-ray diffraction patterns from complex fibrils using atom-type-specific pair-distance quantization. Pair distances are sorted into arrays which are labelled by atom type. Histograms of pair distances in each array are computed and binned and the resulting population distributions are used to represent the whole pair-distance data set. These quantized pair-distance arrays are used with a modified and vectorized Debyemore » formula to simulate diffraction patterns. This approach utilizes fewer pair distances in each iteration, and atomic scattering factors are moved outside the iteration since the arrays are labelled by atom type. As a result, this algorithm significantly reduces the computation time while maintaining the accuracy of diffraction pattern simulation, making possible the simulation of diffraction patterns from large twisted fibrils in a relatively short period of time, as is required for model testing and refinement.« less

Quaternionic Kähler Detour Complexes and {mathcal{N} = 2} Supersymmetric Black Holes

NASA Astrophysics Data System (ADS)

Cherney, D.; Latini, E.; Waldron, A.

2011-03-01

We study a class of supersymmetric spinning particle models derived from the radial quantization of stationary, spherically symmetric black holes of four dimensional {{mathcal N} = 2} supergravities. By virtue of the c-map, these spinning particles move in quaternionic Kähler manifolds. Their spinning degrees of freedom describe mini-superspace-reduced supergravity fermions. We quantize these models using BRST detour complex technology. The construction of a nilpotent BRST charge is achieved by using local (worldline) supersymmetry ghosts to generate special holonomy transformations. (An interesting byproduct of the construction is a novel Dirac operator on the superghost extended Hilbert space.) The resulting quantized models are gauge invariant field theories with fields equaling sections of special quaternionic vector bundles. They underly and generalize the quaternionic version of Dolbeault cohomology discovered by Baston. In fact, Baston’s complex is related to the BPS sector of the models we write down. Our results rely on a calculus of operators on quaternionic Kähler manifolds that follows from BRST machinery, and although directly motivated by black hole physics, can be broadly applied to any model relying on quaternionic geometry.

Modeling and analysis of energy quantization effects on single electron inverter performance

NASA Astrophysics Data System (ADS)

Dan, Surya Shankar; Mahapatra, Santanu

2009-08-01

In this paper, for the first time, the effects of energy quantization on single electron transistor (SET) inverter performance are analyzed through analytical modeling and Monte Carlo simulations. It is shown that energy quantization mainly changes the Coulomb blockade region and drain current of SET devices and thus affects the noise margin, power dissipation, and the propagation delay of SET inverter. A new analytical model for the noise margin of SET inverter is proposed which includes the energy quantization effects. Using the noise margin as a metric, the robustness of SET inverter is studied against the effects of energy quantization. A compact expression is developed for a novel parameter quantization threshold which is introduced for the first time in this paper. Quantization threshold explicitly defines the maximum energy quantization that an SET inverter logic circuit can withstand before its noise margin falls below a specified tolerance level. It is found that SET inverter designed with CT:CG=1/3 (where CT and CG are tunnel junction and gate capacitances, respectively) offers maximum robustness against energy quantization.

Master equation for open two-band systems and its applications to Hall conductance

NASA Astrophysics Data System (ADS)

Shen, H. Z.; Zhang, S. S.; Dai, C. M.; Yi, X. X.

2018-02-01

Hall conductivity in the presence of a dephasing environment has recently been investigated with a dissipative term introduced phenomenologically. In this paper, we study the dissipative topological insulator (TI) and its topological transition in the presence of quantized electromagnetic environments. A Lindblad-type equation is derived to determine the dynamics of a two-band system. When the two-band model describes TIs, the environment may be the fluctuations of radiation that surround the TIs. We find the dependence of decay rates in the master equation on Bloch vectors in the two-band system, which leads to a mixing of the band occupations. Hence the environment-induced current is in general not perfectly topological in the presence of coupling to the environment, although deviations are small in the weak limit. As an illustration, we apply the Bloch-vector-dependent master equation to TIs and calculate the Hall conductance of tight-binding electrons in a two-dimensional lattice. The influence of environments on the Hall conductance is presented and discussed. The calculations show that the phase transition points of the TIs are robust against the quantized electromagnetic environment. The results might bridge the gap between quantum optics and topological photonic materials.

Musical sound analysis/synthesis using vector-quantized time-varying spectra

NASA Astrophysics Data System (ADS)

Ehmann, Andreas F.; Beauchamp, James W.

2002-11-01

A fundamental goal of computer music sound synthesis is accurate, yet efficient resynthesis of musical sounds, with the possibility of extending the synthesis into new territories using control of perceptually intuitive parameters. A data clustering technique known as vector quantization (VQ) is used to extract a globally optimum set of representative spectra from phase vocoder analyses of instrument tones. This set of spectra, called a Codebook, is used for sinusoidal additive synthesis or, more efficiently, for wavetable synthesis. Instantaneous spectra are synthesized by first determining the Codebook indices corresponding to the best least-squares matches to the original time-varying spectrum. Spectral index versus time functions are then smoothed, and interpolation is employed to provide smooth transitions between Codebook spectra. Furthermore, spectral frames are pre-flattened and their slope, or tilt, extracted before clustering is applied. This allows spectral tilt, closely related to the perceptual parameter ''brightness,'' to be independently controlled during synthesis. The result is a highly compressed format consisting of the Codebook spectra and time-varying tilt, amplitude, and Codebook index parameters. This technique has been applied to a variety of harmonic musical instrument sounds with the resulting resynthesized tones providing good matches to the originals.

The edge-preservation multi-classifier relearning framework for the classification of high-resolution remotely sensed imagery

NASA Astrophysics Data System (ADS)

Han, Xiaopeng; Huang, Xin; Li, Jiayi; Li, Yansheng; Yang, Michael Ying; Gong, Jianya

2018-04-01

In recent years, the availability of high-resolution imagery has enabled more detailed observation of the Earth. However, it is imperative to simultaneously achieve accurate interpretation and preserve the spatial details for the classification of such high-resolution data. To this aim, we propose the edge-preservation multi-classifier relearning framework (EMRF). This multi-classifier framework is made up of support vector machine (SVM), random forest (RF), and sparse multinomial logistic regression via variable splitting and augmented Lagrangian (LORSAL) classifiers, considering their complementary characteristics. To better characterize complex scenes of remote sensing images, relearning based on landscape metrics is proposed, which iteratively quantizes both the landscape composition and spatial configuration by the use of the initial classification results. In addition, a novel tri-training strategy is proposed to solve the over-smoothing effect of relearning by means of automatic selection of training samples with low classification certainties, which always distribute in or near the edge areas. Finally, EMRF flexibly combines the strengths of relearning and tri-training via the classification certainties calculated by the probabilistic output of the respective classifiers. It should be noted that, in order to achieve an unbiased evaluation, we assessed the classification accuracy of the proposed framework using both edge and non-edge test samples. The experimental results obtained with four multispectral high-resolution images confirm the efficacy of the proposed framework, in terms of both edge and non-edge accuracy.

A visual detection model for DCT coefficient quantization

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Peterson, Heidi A.

1993-01-01

The discrete cosine transform (DCT) is widely used in image compression, and is part of the JPEG and MPEG compression standards. The degree of compression, and the amount of distortion in the decompressed image are determined by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. Our approach is to set the quantization level for each coefficient so that the quantization error is at the threshold of visibility. Here we combine results from our previous work to form our current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color.

Electron-electron interaction and spin-orbit coupling in InAs/AlSb heterostructures with a two-dimensional electron gas

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

Gavrilenko, V. I.; Krishtopenko, S. S., E-mail: ds_a-teens@mail.ru; Goiran, M.

2011-01-15

The effect of electron-electron interaction on the spectrum of two-dimensional electron states in InAs/AlSb (001) heterostructures with a GaSb cap layer with one filled size-quantization subband. The energy spectrum of two-dimensional electrons is calculated in the Hartree and Hartree-Fock approximations. It is shown that the exchange interaction decreasing the electron energy in subbands increases the energy gap between subbands and the spin-orbit splitting of the spectrum in the entire region of electron concentrations, at which only the lower size-quantization band is filled. The nonlinear dependence of the Rashba splitting constant at the Fermi wave vector on the concentration of two-dimensionalmore » electrons is demonstrated.« less

Feature Vector Construction Method for IRIS Recognition

NASA Astrophysics Data System (ADS)

Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

Vectorization for Molecular Dynamics on Intel Xeon Phi Corpocessors

NASA Astrophysics Data System (ADS)

Yi, Hongsuk

2014-03-01

Many modern processors are capable of exploiting data-level parallelism through the use of single instruction multiple data (SIMD) execution. The new Intel Xeon Phi coprocessor supports 512 bit vector registers for the high performance computing. In this paper, we have developed a hierarchical parallelization scheme for accelerated molecular dynamics simulations with the Terfoff potentials for covalent bond solid crystals on Intel Xeon Phi coprocessor systems. The scheme exploits multi-level parallelism computing. We combine thread-level parallelism using a tightly coupled thread-level and task-level parallelism with 512-bit vector register. The simulation results show that the parallel performance of SIMD implementations on Xeon Phi is apparently superior to their x86 CPU architecture.

Comparison of SOM point densities based on different criteria.

PubMed

Kohonen, T

1999-11-15

Point densities of model (codebook) vectors in self-organizing maps (SOMs) are evaluated in this article. For a few one-dimensional SOMs with finite grid lengths and a given probability density function of the input, the numerically exact point densities have been computed. The point density derived from the SOM algorithm turned out to be different from that minimizing the SOM distortion measure, showing that the model vectors produced by the basic SOM algorithm in general do not exactly coincide with the optimum of the distortion measure. A new computing technique based on the calculus of variations has been introduced. It was applied to the computation of point densities derived from the distortion measure for both the classical vector quantization and the SOM with general but equal dimensionality of the input vectors and the grid, respectively. The power laws in the continuum limit obtained in these cases were found to be identical.

The Coulomb problem on a 3-sphere and Heun polynomials

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

Bellucci, Stefano; Yeghikyan, Vahagn; Yerevan State University, Alex-Manoogian st. 1, 00025 Yerevan

2013-08-15

The paper studies the quantum mechanical Coulomb problem on a 3-sphere. We present a special parametrization of the ellipto-spheroidal coordinate system suitable for the separation of variables. After quantization we get the explicit form of the spectrum and present an algebraic equation for the eigenvalues of the Runge-Lentz vector. We also present the wave functions expressed via Heun polynomials.

Deformation quantization with separation of variables of an endomorphism bundle

NASA Astrophysics Data System (ADS)

Karabegov, Alexander

2014-01-01

Given a holomorphic Hermitian vector bundle E and a star-product with separation of variables on a pseudo-Kähler manifold, we construct a star product on the sections of the endomorphism bundle of the dual bundle E∗ which also has the appropriately generalized property of separation of variables. For this star product we prove a generalization of Gammelgaard's graph-theoretic formula.

Quantum entanglement and position-momentum entropic squeezing of a moving Lambda-type three-level atom interacting with a single-mode quantized field with intensity-dependent coupling

NASA Astrophysics Data System (ADS)

Faghihi, M. J.; Tavassoly, M. K.

2013-07-01

In this paper, we study the interaction between a moving Λ-type three-level atom and a single-mode cavity field in the presence of intensity-dependent atom-field coupling. After obtaining the state vector of the entire system explicitly, we study the nonclassical features of the system such as quantum entanglement, position-momentum entropic squeezing, quadrature squeezing and sub-Poissonian statistics. According to the obtained numerical results we illustrate that the squeezed period, the duration of entropy squeezing and the maximal squeezing can be controlled by choosing the appropriate nonlinearity function together with entering the atomic motion effect by the suitable selection of the field-mode structure parameter. Also, the atomic motion, as well as the nonlinearity function, leads to the oscillatory behaviour of the degree of entanglement between the atom and field.

Entanglement Dynamics of Linear and Nonlinear Interaction of Two Two-Level Atoms with a Quantized Phase-Damped Field in the Dispersive Regime

NASA Astrophysics Data System (ADS)

Tavassoly, M. K.; Daneshmand, R.; Rustaee, N.

2018-06-01

In this paper we study the linear and nonlinear (intensity-dependent) interactions of two two-level atoms with a single-mode quantized field far from resonance, while the phase-damping effect is also taken into account. To find the analytical solution of the atom-field state vector corresponding to the considered model, after deducing the effective Hamiltonian we evaluate the time-dependent elements of the density operator using the master equation approach and superoperator method. Consequently, we are able to study the influences of the special nonlinearity function f (n) = √ {n}, the intensity of the initial coherent state field and the phase-damping parameter on the degree of entanglement of the whole system as well as the field and atom. It is shown that in the presence of damping, by passing time, the amount of entanglement of each subsystem with the rest of system, asymptotically reaches to its stationary and maximum value. Also, the nonlinear interaction does not have any effect on the entanglement of one of the atoms with the rest of system, but it changes the amplitude and time period of entanglement oscillations of the field and the other atom. Moreover, this may cause that, the degree of entanglement which may be low (high) at some moments of time becomes high (low) by entering the intensity-dependent function in the atom-field coupling.

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

Lindstrom, P; Cohen, J D

We present a streaming geometry compression codec for multiresolution, uniformly-gridded, triangular terrain patches that supports very fast decompression. Our method is based on linear prediction and residual coding for lossless compression of the full-resolution data. As simplified patches on coarser levels in the hierarchy already incur some data loss, we optionally allow further quantization for more lossy compression. The quantization levels are adaptive on a per-patch basis, while still permitting seamless, adaptive tessellations of the terrain. Our geometry compression on such a hierarchy achieves compression ratios of 3:1 to 12:1. Our scheme is not only suitable for fast decompression onmore » the CPU, but also for parallel decoding on the GPU with peak throughput over 2 billion triangles per second. Each terrain patch is independently decompressed on the fly from a variable-rate bitstream by a GPU geometry program with no branches or conditionals. Thus we can store the geometry compressed on the GPU, reducing storage and bandwidth requirements throughout the system. In our rendering approach, only compressed bitstreams and the decoded height values in the view-dependent 'cut' are explicitly stored on the GPU. Normal vectors are computed in a streaming fashion, and remaining geometry and texture coordinates, as well as mesh connectivity, are shared and re-used for all patches. We demonstrate and evaluate our algorithms on a small prototype system in which all compressed geometry fits in the GPU memory and decompression occurs on the fly every rendering frame without any cache maintenance.« less

Detection of potential mosquito breeding sites based on community sourced geotagged images

NASA Astrophysics Data System (ADS)

Agarwal, Ankit; Chaudhuri, Usashi; Chaudhuri, Subhasis; Seetharaman, Guna

2014-06-01

Various initiatives have been taken all over the world to involve the citizens in the collection and reporting of data to make better and informed data-driven decisions. Our work shows how the geotagged images collected through the general population can be used to combat Malaria and Dengue by identifying and visualizing localities that contain potential mosquito breeding sites. Our method first employs image quality assessment on the client side to reject the images with distortions like blur and artifacts. Each geotagged image received on the server is converted into a feature vector using the bag of visual words model. We train an SVM classifier on a histogram-based feature vector obtained after the vector quantization of SIFT features to discriminate images containing either a small stagnant water body like puddle, or open containers and tires, bushes etc. from those that contain flowing water, manicured lawns, tires attached to a vehicle etc. A geographical heat map is generated by assigning a specific location a probability value of it being a potential mosquito breeding ground of mosquito using feature level fusion or the max approach presented in the paper. The heat map thus generated can be used by concerned health authorities to take appropriate action and to promote civic awareness.

Velocity-tunable slow beams of cold O2 in a single spin-rovibronic state with full angular-momentum orientation by multistage Zeeman deceleration

NASA Astrophysics Data System (ADS)

Wiederkehr, A. W.; Schmutz, H.; Motsch, M.; Merkt, F.

2012-08-01

Cold samples of oxygen molecules in supersonic beams have been decelerated from initial velocities of 390 and 450 m s-1 to final velocities in the range between 150 and 280 m s-1 using a 90-stage Zeeman decelerator. (2 + 1) resonance-enhanced-multiphoton-ionization (REMPI) spectra of the 3sσ g 3Π g (C) ? two-photon transition of O2 have been recorded to characterize the state selectivity of the deceleration process. The decelerated molecular sample was found to consist exclusively of molecules in the J ‧‧ = 2 spin-rotational component of the X ? ground state of O2. Measurements of the REMPI spectra using linearly polarized laser radiation with polarization vector parallel to the decelerator axis, and thus to the magnetic-field vector of the deceleration solenoids, further showed that only the ? magnetic sublevel of the N‧‧ = 1, J ‧‧ = 2 spin-rotational level is populated in the decelerated sample, which therefore is characterized by a fully oriented total-angular-momentum vector. By maintaining a weak quantization magnetic field beyond the decelerator, the polarization of the sample could be maintained over the 5 cm distance separating the last deceleration solenoid and the detection region.

Radiation and matter: Electrodynamics postulates and Lorenz gauge

NASA Astrophysics Data System (ADS)

Bobrov, V. B.; Trigger, S. A.; van Heijst, G. J.; Schram, P. P.

2016-11-01

In general terms, we have considered matter as the system of charged particles and quantized electromagnetic field. For consistent description of the thermodynamic properties of matter, especially in an extreme state, the problem of quantization of the longitudinal and scalar potentials should be solved. In this connection, we pay attention that the traditional postulates of electrodynamics, which claim that only electric and magnetic fields are observable, is resolved by denial of the statement about validity of the Maxwell equations for microscopic fields. The Maxwell equations, as the generalization of experimental data, are valid only for averaged values. We show that microscopic electrodynamics may be based on postulation of the d'Alembert equations for four-vector of the electromagnetic field potential. The Lorenz gauge is valid for the averages potentials (and provides the implementation of the Maxwell equations for averages). The suggested concept overcomes difficulties under the electromagnetic field quantization procedure being in accordance with the results of quantum electrodynamics. As a result, longitudinal and scalar photons become real rather than virtual and may be observed in principle. The longitudinal and scalar photons provide not only the Coulomb interaction of charged particles, but also allow the electrical Aharonov-Bohm effect.

Applications of wavelet-based compression to multidimensional Earth science data

NASA Technical Reports Server (NTRS)

Bradley, Jonathan N.; Brislawn, Christopher M.

1993-01-01

A data compression algorithm involving vector quantization (VQ) and the discrete wavelet transform (DWT) is applied to two different types of multidimensional digital earth-science data. The algorithms (WVQ) is optimized for each particular application through an optimization procedure that assigns VQ parameters to the wavelet transform subbands subject to constraints on compression ratio and encoding complexity. Preliminary results of compressing global ocean model data generated on a Thinking Machines CM-200 supercomputer are presented. The WVQ scheme is used in both a predictive and nonpredictive mode. Parameters generated by the optimization algorithm are reported, as are signal-to-noise (SNR) measurements of actual quantized data. The problem of extrapolating hydrodynamic variables across the continental landmasses in order to compute the DWT on a rectangular grid is discussed. Results are also presented for compressing Landsat TM 7-band data using the WVQ scheme. The formulation of the optimization problem is presented along with SNR measurements of actual quantized data. Postprocessing applications are considered in which the seven spectral bands are clustered into 256 clusters using a k-means algorithm and analyzed using the Los Alamos multispectral data analysis program, SPECTRUM, both before and after being compressed using the WVQ program.

Evaluation of NASA speech encoder

NASA Technical Reports Server (NTRS)

1976-01-01

Techniques developed by NASA for spaceflight instrumentation were used in the design of a quantizer for speech-decoding. Computer simulation of the actions of the quantizer was tested with synthesized and real speech signals. Results were evaluated by a phometician. Topics discussed include the relationship between the number of quantizer levels and the required sampling rate; reconstruction of signals; digital filtering; speech recording, sampling, and storage, and processing results.

Quantized Rabi oscillations and circular dichroism in quantum Hall systems

NASA Astrophysics Data System (ADS)

Tran, D. T.; Cooper, N. R.; Goldman, N.

2018-06-01

The dissipative response of a quantum system upon periodic driving can be exploited as a probe of its topological properties. Here we explore the implications of such phenomena in two-dimensional gases subjected to a uniform magnetic field. It is shown that a filled Landau level exhibits a quantized circular dichroism, which can be traced back to its underlying nontrivial topology. Based on selection rules, we find that this quantized effect can be suitably described in terms of Rabi oscillations, whose frequencies satisfy simple quantization laws. We discuss how quantized dissipative responses can be probed locally, both in the bulk and at the boundaries of the system. This work suggests alternative forms of topological probes based on circular dichroism.

Direct Images, Fields of Hilbert Spaces, and Geometric Quantization

NASA Astrophysics Data System (ADS)

Lempert, László; Szőke, Róbert

2014-04-01

Geometric quantization often produces not one Hilbert space to represent the quantum states of a classical system but a whole family H s of Hilbert spaces, and the question arises if the spaces H s are canonically isomorphic. Axelrod et al. (J. Diff. Geo. 33:787-902, 1991) and Hitchin (Commun. Math. Phys. 131:347-380, 1990) suggest viewing H s as fibers of a Hilbert bundle H, introduce a connection on H, and use parallel transport to identify different fibers. Here we explore to what extent this can be done. First we introduce the notion of smooth and analytic fields of Hilbert spaces, and prove that if an analytic field over a simply connected base is flat, then it corresponds to a Hermitian Hilbert bundle with a flat connection and path independent parallel transport. Second we address a general direct image problem in complex geometry: pushing forward a Hermitian holomorphic vector bundle along a non-proper map . We give criteria for the direct image to be a smooth field of Hilbert spaces. Third we consider quantizing an analytic Riemannian manifold M by endowing TM with the family of adapted Kähler structures from Lempert and Szőke (Bull. Lond. Math. Soc. 44:367-374, 2012). This leads to a direct image problem. When M is homogeneous, we prove the direct image is an analytic field of Hilbert spaces. For certain such M—but not all—the direct image is even flat; which means that in those cases quantization is unique.

Understanding Local Structure Globally in Earth Science Remote Sensing Data Sets

NASA Technical Reports Server (NTRS)

Braverman, Amy; Fetzer, Eric

2007-01-01

Empirical probability distributions derived from the data are the signatures of physical processes generating the data. Distributions defined on different space-time windows can be compared and differences or changes can be attributed to physical processes. This presentation discusses on ways to reduce remote sensing data in a way that preserves information, focusing on the rate-distortion theory and using the entropy-constrained vector quantization algorithm.

Direct Volume Rendering with Shading via Three-Dimensional Textures

NASA Technical Reports Server (NTRS)

VanGelder, Allen; Kim, Kwansik

1996-01-01

A new and easy-to-implement method for direct volume rendering that uses 3D texture maps for acceleration, and incorporates directional lighting, is described. The implementation, called Voltx, produces high-quality images at nearly interactive speeds on workstations with hardware support for three-dimensional texture maps. Previously reported methods did not incorporate a light model, and did not address issues of multiple texture maps for large volumes. Our research shows that these extensions impact performance by about a factor of ten. Voltx supports orthographic, perspective, and stereo views. This paper describes the theory and implementation of this technique, and compares it to the shear-warp factorization approach. A rectilinear data set is converted into a three-dimensional texture map containing color and opacity information. Quantized normal vectors and a lookup table provide efficiency. A new tesselation of the sphere is described, which serves as the basis for normal-vector quantization. A new gradient-based shading criterion is described, in which the gradient magnitude is interpreted in the context of the field-data value and the material classification parameters, and not in isolation. In the rendering phase, the texture map is applied to a stack of parallel planes, which effectively cut the texture into many slabs. The slabs are composited to form an image.

Single-user MIMO versus multi-user MIMO in distributed antenna systems with limited feedback

NASA Astrophysics Data System (ADS)

Schwarz, Stefan; Heath, Robert W.; Rupp, Markus

2013-12-01

This article investigates the performance of cellular networks employing distributed antennas in addition to the central antennas of the base station. Distributed antennas are likely to be implemented using remote radio units, which is enabled by a low latency and high bandwidth dedicated link to the base station. This facilitates coherent transmission from potentially all available antennas at the same time. Such distributed antenna system (DAS) is an effective way to deal with path loss and large-scale fading in cellular systems. DAS can apply precoding across multiple transmission points to implement single-user MIMO (SU-MIMO) and multi-user MIMO (MU-MIMO) transmission. The throughput performance of various SU-MIMO and MU-MIMO transmission strategies is investigated in this article, employing a Long-Term evolution (LTE) standard compliant simulation framework. The previously theoretically established cell-capacity improvement of MU-MIMO in comparison to SU-MIMO in DASs is confirmed under the practical constraints imposed by the LTE standard, even under the assumption of imperfect channel state information (CSI) at the base station. Because practical systems will use quantized feedback, the performance of different CSI feedback algorithms for DASs is investigated. It is shown that significant gains in the CSI quantization accuracy and in the throughput of especially MU-MIMO systems can be achieved with relatively simple quantization codebook constructions that exploit the available temporal correlation and channel gain differences.

Information extraction from multivariate images

NASA Technical Reports Server (NTRS)

Park, S. K.; Kegley, K. A.; Schiess, J. R.

1986-01-01

An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

A visual detection model for DCT coefficient quantization

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Watson, Andrew B.

1994-01-01

The discrete cosine transform (DCT) is widely used in image compression and is part of the JPEG and MPEG compression standards. The degree of compression and the amount of distortion in the decompressed image are controlled by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. One approach is to set the quantization level for each coefficient so that the quantization error is near the threshold of visibility. Results from previous work are combined to form the current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color. A model-based method of optimizing the quantization matrix for an individual image was developed. The model described above provides visual thresholds for each DCT frequency. These thresholds are adjusted within each block for visual light adaptation and contrast masking. For given quantization matrix, the DCT quantization errors are scaled by the adjusted thresholds to yield perceptual errors. These errors are pooled nonlinearly over the image to yield total perceptual error. With this model one may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over image-independent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.

Thyra Abstract Interface Package

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

Bartlett, Roscoe A.

2005-09-01

Thrya primarily defines a set of abstract C++ class interfaces needed for the development of abstract numerical atgorithms (ANAs) such as iterative linear solvers, transient solvers all the way up to optimization. At the foundation of these interfaces are abstract C++ classes for vectors, vector spaces, linear operators and multi-vectors. Also included in the Thyra package is C++ code for creating concrete vector, vector space, linear operator, and multi-vector subclasses as well as other utilities to aid in the development of ANAs. Currently, very general and efficient concrete subclass implementations exist for serial and SPMD in-core vectors and multi-vectors. Codemore » also currently exists for testing objects and providing composite objects such as product vectors.« less

Wigner functions on non-standard symplectic vector spaces

NASA Astrophysics Data System (ADS)

Dias, Nuno Costa; Prata, João Nuno

2018-01-01

We consider the Weyl quantization on a flat non-standard symplectic vector space. We focus mainly on the properties of the Wigner functions defined therein. In particular we show that the sets of Wigner functions on distinct symplectic spaces are different but have non-empty intersections. This extends previous results to arbitrary dimension and arbitrary (constant) symplectic structure. As a by-product we introduce and prove several concepts and results on non-standard symplectic spaces which generalize those on the standard symplectic space, namely, the symplectic spectrum, Williamson's theorem, and Narcowich-Wigner spectra. We also show how Wigner functions on non-standard symplectic spaces behave under the action of an arbitrary linear coordinate transformation.

Fault detection of helicopter gearboxes using the multi-valued influence matrix method

NASA Technical Reports Server (NTRS)

Chin, Hsinyung; Danai, Kourosh; Lewicki, David G.

1993-01-01

In this paper we investigate the effectiveness of a pattern classifying fault detection system that is designed to cope with the variability of fault signatures inherent in helicopter gearboxes. For detection, the measurements are monitored on-line and flagged upon the detection of abnormalities, so that they can be attributed to a faulty or normal case. As such, the detection system is composed of two components, a quantization matrix to flag the measurements, and a multi-valued influence matrix (MVIM) that represents the behavior of measurements during normal operation and at fault instances. Both the quantization matrix and influence matrix are tuned during a training session so as to minimize the error in detection. To demonstrate the effectiveness of this detection system, it was applied to vibration measurements collected from a helicopter gearbox during normal operation and at various fault instances. The results indicate that the MVIM method provides excellent results when the full range of faults effects on the measurements are included in the training set.

Advance in multi-hit detection and quantization in atom probe tomography.

PubMed

Da Costa, G; Wang, H; Duguay, S; Bostel, A; Blavette, D; Deconihout, B

2012-12-01

The preferential retention of high evaporation field chemical species at the sample surface in atom-probe tomography (e.g., boron in silicon or in metallic alloys) leads to correlated field evaporation and pronounced pile-up effects on the detector. The latter severely affects the reliability of concentration measurements of current 3D atom probes leading to an under-estimation of the concentrations of the high-field species. The multi-hit capabilities of the position-sensitive time-resolved detector is shown to play a key role. An innovative method based on Fourier space signal processing of signals supplied by an advance delay-line position-sensitive detector is shown to drastically improve the time resolving power of the detector and consequently its capability to detect multiple events. Results show that up to 30 ions on the same evaporation pulse can be detected and properly positioned. The major impact of this new method on the quantization of chemical composition in materials, particularly in highly-doped Si(B) samples is highlighted.

The BRST complex of homological Poisson reduction

NASA Astrophysics Data System (ADS)

Müller-Lennert, Martin

2017-02-01

BRST complexes are differential graded Poisson algebras. They are associated with a coisotropic ideal J of a Poisson algebra P and provide a description of the Poisson algebra (P/J)^J as their cohomology in degree zero. Using the notion of stable equivalence introduced in Felder and Kazhdan (Contemporary Mathematics 610, Perspectives in representation theory, 2014), we prove that any two BRST complexes associated with the same coisotropic ideal are quasi-isomorphic in the case P = R[V] where V is a finite-dimensional symplectic vector space and the bracket on P is induced by the symplectic structure on V. As a corollary, the cohomology of the BRST complexes is canonically associated with the coisotropic ideal J in the symplectic case. We do not require any regularity assumptions on the constraints generating the ideal J. We finally quantize the BRST complex rigorously in the presence of infinitely many ghost variables and discuss the uniqueness of the quantization procedure.

Diffractive charmonium spectrum in high energy collisions in the basis light-front quantization approach

DOE PAGES

Chen, Guangyao; Li, Yang; Maris, Pieter; ...

2017-04-14

Using the charmonium light-front wavefunctions obtained by diagonalizing an effective Hamiltonian with the one-gluon exchange interaction and a confining potential inspired by light-front holography in the basis light-front quantization formalism, we compute production of charmonium states in diffractive deep inelastic scattering and ultra-peripheral heavy ion collisions within the dipole picture. Our method allows us to predict yields of all vector charmonium states below the open flavor thresholds in high-energy deep inelastic scattering, proton-nucleus and ultra-peripheral heavy ion collisions, without introducing any new parameters in the light-front wavefunctions. The obtained charmonium cross section is in reasonable agreement with experimental data atmore » HERA, RHIC and LHC. We observe that the cross-section ratio σΨ(2s)/σJ/Ψ reveals significant independence of model parameters« less

Theory of quantized systems: formal basis for DEVS/HLA distributed simulation environment

NASA Astrophysics Data System (ADS)

Zeigler, Bernard P.; Lee, J. S.

1998-08-01

In the context of a DARPA ASTT project, we are developing an HLA-compliant distributed simulation environment based on the DEVS formalism. This environment will provide a user- friendly, high-level tool-set for developing interoperable discrete and continuous simulation models. One application is the study of contract-based predictive filtering. This paper presents a new approach to predictive filtering based on a process called 'quantization' to reduce state update transmission. Quantization, which generates state updates only at quantum level crossings, abstracts a sender model into a DEVS representation. This affords an alternative, efficient approach to embedding continuous models within distributed discrete event simulations. Applications of quantization to message traffic reduction are discussed. The theory has been validated by DEVSJAVA simulations of test cases. It will be subject to further test in actual distributed simulations using the DEVS/HLA modeling and simulation environment.

Landau quantization of Dirac fermions in graphene and its multilayers

NASA Astrophysics Data System (ADS)

Yin, Long-Jing; Bai, Ke-Ke; Wang, Wen-Xiao; Li, Si-Yu; Zhang, Yu; He, Lin

2017-08-01

When electrons are confined in a two-dimensional (2D) system, typical quantum-mechanical phenomena such as Landau quantization can be detected. Graphene systems, including the single atomic layer and few-layer stacked crystals, are ideal 2D materials for studying a variety of quantum-mechanical problems. In this article, we review the experimental progress in the unusual Landau quantized behaviors of Dirac fermions in monolayer and multilayer graphene by using scanning tunneling microscopy (STM) and scanning tunneling spectroscopy (STS). Through STS measurement of the strong magnetic fields, distinct Landau-level spectra and rich level-splitting phenomena are observed in different graphene layers. These unique properties provide an effective method for identifying the number of layers, as well as the stacking orders, and investigating the fundamentally physical phenomena of graphene. Moreover, in the presence of a strain and charged defects, the Landau quantization of graphene can be significantly modified, leading to unusual spectroscopic and electronic properties.

Multi-level damage identification with response reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Chao-Dong; Xu, You-Lin

2017-10-01

Damage identification through finite element (FE) model updating usually forms an inverse problem. Solving the inverse identification problem for complex civil structures is very challenging since the dimension of potential damage parameters in a complex civil structure is often very large. Aside from enormous computation efforts needed in iterative updating, the ill-condition and non-global identifiability features of the inverse problem probably hinder the realization of model updating based damage identification for large civil structures. Following a divide-and-conquer strategy, a multi-level damage identification method is proposed in this paper. The entire structure is decomposed into several manageable substructures and each substructure is further condensed as a macro element using the component mode synthesis (CMS) technique. The damage identification is performed at two levels: the first is at macro element level to locate the potentially damaged region and the second is over the suspicious substructures to further locate as well as quantify the damage severity. In each level's identification, the damage searching space over which model updating is performed is notably narrowed down, not only reducing the computation amount but also increasing the damage identifiability. Besides, the Kalman filter-based response reconstruction is performed at the second level to reconstruct the response of the suspicious substructure for exact damage quantification. Numerical studies and laboratory tests are both conducted on a simply supported overhanging steel beam for conceptual verification. The results demonstrate that the proposed multi-level damage identification via response reconstruction does improve the identification accuracy of damage localization and quantization considerably.

Direct comparison of fractional and integer quantized Hall resistance

NASA Astrophysics Data System (ADS)

Ahlers, Franz J.; Götz, Martin; Pierz, Klaus

2017-08-01

We present precision measurements of the fractional quantized Hall effect, where the quantized resistance {{R}≤ft[ 1/3 \\right]} in the fractional quantum Hall state at filling factor 1/3 was compared with a quantized resistance {{R}[2]} , represented by an integer quantum Hall state at filling factor 2. A cryogenic current comparator bridge capable of currents down to the nanoampere range was used to directly compare two resistance values of two GaAs-based devices located in two cryostats. A value of 1-(5.3  ±  6.3) 10-8 (95% confidence level) was obtained for the ratio ({{R}≤ft[ 1/3 \\right]}/6{{R}[2]} ). This constitutes the most precise comparison of integer resistance quantization (in terms of h/e 2) in single-particle systems and of fractional quantization in fractionally charged quasi-particle systems. While not relevant for practical metrology, such a test of the validity of the underlying physics is of significance in the context of the upcoming revision of the SI.

Parallel image compression

NASA Technical Reports Server (NTRS)

Reif, John H.

1987-01-01

A parallel compression algorithm for the 16,384 processor MPP machine was developed. The serial version of the algorithm can be viewed as a combination of on-line dynamic lossless test compression techniques (which employ simple learning strategies) and vector quantization. These concepts are described. How these concepts are combined to form a new strategy for performing dynamic on-line lossy compression is discussed. Finally, the implementation of this algorithm in a massively parallel fashion on the MPP is discussed.

Course 4: Anyons

NASA Astrophysics Data System (ADS)

Myrheim, J.

Contents 1 Introduction 1.1 The concept of particle statistics 1.2 Statistical mechanics and the many-body problem 1.3 Experimental physics in two dimensions 1.4 The algebraic approach: Heisenberg quantization 1.5 More general quantizations 2 The configuration space 2.1 The Euclidean relative space for two particles 2.2 Dimensions d=1,2,3 2.3 Homotopy 2.4 The braid group 3 Schroedinger quantization in one dimension 4 Heisenberg quantization in one dimension 4.1 The coordinate representation 5 Schroedinger quantization in dimension d ≥ 2 5.1 Scalar wave functions 5.2 Homotopy 5.3 Interchange phases 5.4 The statistics vector potential 5.5 The N-particle case 5.6 Chern-Simons theory 6 The Feynman path integral for anyons 6.1 Eigenstates for position and momentum 6.2 The path integral 6.3 Conjugation classes in SN 6.4 The non-interacting case 6.5 Duality of Feynman and Schroedinger quantization 7 The harmonic oscillator 7.1 The two-dimensional harmonic oscillator 7.2 Two anyons in a harmonic oscillator potential 7.3 More than two anyons 7.4 The three-anyon problem 8 The anyon gas 8.1 The cluster and virial expansions 8.2 First and second order perturbative results 8.3 Regularization by periodic boundary conditions 8.4 Regularization by a harmonic oscillator potential 8.5 Bosons and fermions 8.6 Two anyons 8.7 Three anyons 8.8 The Monte Carlo method 8.9 The path integral representation of the coefficients GP 8.10 Exact and approximate polynomials 8.11 The fourth virial coefficient of anyons 8.12 Two polynomial theorems 9 Charged particles in a constant magnetic field 9.1 One particle in a magnetic field 9.2 Two anyons in a magnetic field 9.3 The anyon gas in a magnetic field 10 Interchange phases and geometric phases 10.1 Introduction to geometric phases 10.2 One particle in a magnetic field 10.3 Two particles in a magnetic field 10.4 Interchange of two anyons in potential wells 10.5 Laughlin's theory of the fractional quantum Hall effect

A consistent covariant quantization of the Brink-Schwarz superparticle

NASA Astrophysics Data System (ADS)

Eisenberg, Yeshayahu

1992-02-01

We perform the covariant quantization of the ten-dimensional Brink-Schwarz superparticle by reducing it to a system whose constraints are all first class, covariant and have only two levels of reducibility. Research supported by the Rothschild Fellowship.

Light-hole quantization in the optical response of ultra-wide GaAs/Al(x)Ga(1-x)As quantum wells.

PubMed

Solovyev, V V; Bunakov, V A; Schmult, S; Kukushkin, I V

2013-01-16

Temperature-dependent reflectivity and photoluminescence spectra are studied for undoped ultra-wide 150 and 250 nm GaAs quantum wells. It is shown that spectral features previously attributed to a size quantization of the exciton motion in the z-direction coincide well with energies of quantized levels for light holes. Furthermore, optical spectra reveal very similar properties at temperatures above the exciton dissociation point.

Thin noble metal films on Si (111) investigated by optical second-harmonic generation and photoemission

NASA Astrophysics Data System (ADS)

Pedersen, K.; Kristensen, T. B.; Pedersen, T. G.; Morgen, P.; Li, Z.; Hoffmann, S. V.

2002-05-01

Thin noble metal films (Ag, Au and Cu) on Si (111) have been investigated by optical second-harmonic generation (SHG) in combination with synchrotron radiation photoemission spectroscopy. The valence band spectra of Ag films show a quantization of the sp-band in the 4-eV energy range from the Fermi level down to the onset of the d-bands. For Cu and Au the corresponding energy range is much narrower and quantization effects are less visible. Quantization effects in SHG are observed as oscillations in the signal as a function of film thickness. The oscillations are strongest for Ag and less pronounced for Cu, in agreement with valence band photoemission spectra. In the case of Au, a reacted layer floating on top of the Au film masks the observation of quantum well levels by photoemission. However, SHG shows a well-developed quantization of levels in the Au film below the reacted layer. For Ag films, the relation between film thickness and photon energy of the SHG resonances indicates different types of resonances, some of which involve both quantum well and substrate states.

Single Vector Calibration System for Multi-Axis Load Cells and Method for Calibrating a Multi-Axis Load Cell

NASA Technical Reports Server (NTRS)

Parker, Peter A. (Inventor)

2003-01-01

A single vector calibration system is provided which facilitates the calibration of multi-axis load cells, including wind tunnel force balances. The single vector system provides the capability to calibrate a multi-axis load cell using a single directional load, for example loading solely in the gravitational direction. The system manipulates the load cell in three-dimensional space, while keeping the uni-directional calibration load aligned. The use of a single vector calibration load reduces the set-up time for the multi-axis load combinations needed to generate a complete calibration mathematical model. The system also reduces load application inaccuracies caused by the conventional requirement to generate multiple force vectors. The simplicity of the system reduces calibration time and cost, while simultaneously increasing calibration accuracy.

Rotating effects on the Landau quantization for an atom with a magnetic quadrupole moment

NASA Astrophysics Data System (ADS)

Fonseca, I. C.; Bakke, K.

2016-01-01

Based on the single particle approximation [Dmitriev et al., Phys. Rev. C 50, 2358 (1994) and C.-C. Chen, Phys. Rev. A 51, 2611 (1995)], the Landau quantization associated with an atom with a magnetic quadrupole moment is introduced, and then, rotating effects on this analogue of the Landau quantization is investigated. It is shown that rotating effects can modify the cyclotron frequency and breaks the degeneracy of the analogue of the Landau levels.

Rotating effects on the Landau quantization for an atom with a magnetic quadrupole moment

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

Fonseca, I. C.; Bakke, K., E-mail: kbakke@fisica.ufpb.br

2016-01-07

Based on the single particle approximation [Dmitriev et al., Phys. Rev. C 50, 2358 (1994) and C.-C. Chen, Phys. Rev. A 51, 2611 (1995)], the Landau quantization associated with an atom with a magnetic quadrupole moment is introduced, and then, rotating effects on this analogue of the Landau quantization is investigated. It is shown that rotating effects can modify the cyclotron frequency and breaks the degeneracy of the analogue of the Landau levels.

Broad Absorption Line Quasar catalogues with Supervised Neural Networks

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

Scaringi, Simone; Knigge, Christian; Cottis, Christopher E.

2008-12-05

We have applied a Learning Vector Quantization (LVQ) algorithm to SDSS DR5 quasar spectra in order to create a large catalogue of broad absorption line quasars (BALQSOs). We first discuss the problems with BALQSO catalogues constructed using the conventional balnicity and/or absorption indices (BI and AI), and then describe the supervised LVQ network we have trained to recognise BALQSOs. The resulting BALQSO catalogue should be substantially more robust and complete than BI-or AI-based ones.

Quantization of Motor Activity into Primitives and Time-Frequency Atoms Using Independent Component Analysis and Matching Pursuit Algorithms

DTIC Science & Technology

2001-10-25

form: (1) A is a scaling factor, t is time and r a coordinate vector describing the limb configuration. We...combination of limb state and EMG. In our early examination of EMG we detected underlying groups of muscles and phases of activity by inspection and...representations of EEG or other biological signals has been thoroughly explored. Such components might be used as a basis for neuroprosthetic control

The electronic structure of Au25 clusters: between discrete and continuous

NASA Astrophysics Data System (ADS)

Katsiev, Khabiboulakh; Lozova, Nataliya; Wang, Lu; Sai Krishna, Katla; Li, Ruipeng; Mei, Wai-Ning; Skrabalak, Sara E.; Kumar, Challa S. S. R.; Losovyj, Yaroslav

2016-08-01

Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies.Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies. Electronic supplementary information (ESI) available: Experimental details including chemicals, sample preparation, and characterization methods. Computation techniques, SV-AUC, GIWAXS, XPS, UPS, MALDI-TOF, ESI data of Au25 clusters. See DOI: 10.1039/c6nr02374f

Digital Correlation Microwave Polarimetry: Analysis and Demonstration

NASA Technical Reports Server (NTRS)

Piepmeier, J. R.; Gasiewski, A. J.; Krebs, Carolyn A. (Technical Monitor)

2000-01-01

The design, analysis, and demonstration of a digital-correlation microwave polarimeter for use in earth remote sensing is presented. We begin with an analysis of three-level digital correlation and develop the correlator transfer function and radiometric sensitivity. A fifth-order polynomial regression is derived for inverting the digital correlation coefficient into the analog statistic. In addition, the effects of quantizer threshold asymmetry and hysteresis are discussed. A two-look unpolarized calibration scheme is developed for identifying correlation offsets. The developed theory and calibration method are verified using a 10.7 GHz and a 37.0 GHz polarimeter. The polarimeters are based upon 1-GS/s three-level digital correlators and measure the first three Stokes parameters. Through experiment, the radiometric sensitivity is shown to approach the theoretical as derived earlier in the paper and the two-look unpolarized calibration method is successfully compared with results using a polarimetric scheme. Finally, sample data from an aircraft experiment demonstrates that the polarimeter is highly-useful for ocean wind-vector measurement.

Constraints in distortion-invariant target recognition system simulation

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Razzaque, Md A.

2000-11-01

Automatic target recognition (ATR) is a mature but active research area. In an earlier paper, we proposed a novel ATR approach for recognition of targets varying in fine details, rotation, and translation using a Learning Vector Quantization (LVQ) Neural Network (NN). The proposed approach performed segmentation of multiple objects and the identification of the objects using LVQNN. In this current paper, we extend the previous approach for recognition of targets varying in rotation, translation, scale, and combination of all three distortions. We obtain the analytical results of the system level design to show that the approach performs well with some constraints. The first constraint determines the size of the input images and input filters. The second constraint shows the limits on amount of rotation, translation, and scale of input objects. We present the simulation verification of the constraints using DARPA's Moving and Stationary Target Recognition (MSTAR) images with different depression and pose angles. The simulation results using MSTAR images verify the analytical constraints of the system level design.

Quantization error of CCD cameras and their influence on phase calculation in fringe pattern analysis.

PubMed

Skydan, Oleksandr A; Lilley, Francis; Lalor, Michael J; Burton, David R

2003-09-10

We present an investigation into the phase errors that occur in fringe pattern analysis that are caused by quantization effects. When acquisition devices with a limited value of camera bit depth are used, there are a limited number of quantization levels available to record the signal. This may adversely affect the recorded signal and adds a potential source of instrumental error to the measurement system. Quantization effects also determine the accuracy that may be achieved by acquisition devices in a measurement system. We used the Fourier fringe analysis measurement technique. However, the principles can be applied equally well for other phase measuring techniques to yield a phase error distribution that is caused by the camera bit depth.

Image-adaptive and robust digital wavelet-domain watermarking for images

NASA Astrophysics Data System (ADS)

Zhao, Yi; Zhang, Liping

2018-03-01

We propose a new frequency domain wavelet based watermarking technique. The key idea of our scheme is twofold: multi-tier solution representation of image and odd-even quantization embedding/extracting watermark. Because many complementary watermarks need to be hidden, the watermark image designed is image-adaptive. The meaningful and complementary watermark images was embedded into the original image (host image) by odd-even quantization modifying coefficients, which was selected from the detail wavelet coefficients of the original image, if their magnitudes are larger than their corresponding Just Noticeable Difference thresholds. The tests show good robustness against best-known attacks such as noise addition, image compression, median filtering, clipping as well as geometric transforms. Further research may improve the performance by refining JND thresholds.

Modular Multi-Sensor Display System Design Study. Volume 1. Requirements Analysis and Design Studies

DTIC Science & Technology

1974-08-01

1 0.00001 0.00001 0.00003 Residual 1x2x3 1 0.01002 0.01002 0.0348 Total 11 0.28822 Gray Shade Quantization. The main effect of gray shade...Quantization 3 Tararets 1 x 2 1 x 3 Z x i 1x2x3 RppTiratjnns Totals Degrees Freedom 1 2 5 10 10 3j6 71 Sum Squares 0.6463 0.5985 1.2009...x 3 2x3 1x2x3 Replications Totals DF 1 2 5 2 5 10 10 36 71 5S 1708.8 1413.2 2355.5 39.6 1342.2 1563.9 1568.8 2583.8 12576.1

Pseudoclassical Foldy-Wouthuysen transformation and canonical quantization of (D-2n)-dimensional relativistic particle with spin in an external electromagnetic field

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

Grigoryan, G.V.; Grigoryan, R.P.

1995-09-01

The canonical quantization of a (D=2n)-dimensional Dirac particle with spin in an arbitrary external electromagnetic field is performed in a gauge that makes it possible to describe simultaneously particles and antiparticles (both massive and massless) already at the classical level. A pseudoclassical Foldy-Wouthuysen transformation is used to find the canonical (Newton-Wigner) coordinates. The connection between this quantization scheme and Blount`s picture describing the behavior of a Dirac particle in an external electromagnetic field is discussed.

Techniques for decoding speech phonemes and sounds: A concept

NASA Technical Reports Server (NTRS)

Lokerson, D. C.; Holby, H. G.

1975-01-01

Techniques studied involve conversion of speech sounds into machine-compatible pulse trains. (1) Voltage-level quantizer produces number of output pulses proportional to amplitude characteristics of vowel-type phoneme waveforms. (2) Pulses produced by quantizer of first speech formants are compared with pulses produced by second formants.

Methods of Contemporary Gauge Theory

NASA Astrophysics Data System (ADS)

Makeenko, Yuri

2002-08-01

Preface; Part I. Path Integrals: 1. Operator calculus; 2. Second quantization; 3. Quantum anomalies from path integral; 4. Instantons in quantum mechanics; Part II. Lattice Gauge Theories: 5. Observables in gauge theories; 6. Gauge fields on a lattice; 7. Lattice methods; 8. Fermions on a lattice; 9. Finite temperatures; Part III. 1/N Expansion: 10. O(N) vector models; 11. Multicolor QCD; 12. QCD in loop space; 13. Matrix models; Part IV. Reduced Models: 14. Eguchi-Kawai model; 15. Twisted reduced models; 16. Non-commutative gauge theories.

Methods of Contemporary Gauge Theory

NASA Astrophysics Data System (ADS)

Makeenko, Yuri

2005-11-01

Preface; Part I. Path Integrals: 1. Operator calculus; 2. Second quantization; 3. Quantum anomalies from path integral; 4. Instantons in quantum mechanics; Part II. Lattice Gauge Theories: 5. Observables in gauge theories; 6. Gauge fields on a lattice; 7. Lattice methods; 8. Fermions on a lattice; 9. Finite temperatures; Part III. 1/N Expansion: 10. O(N) vector models; 11. Multicolor QCD; 12. QCD in loop space; 13. Matrix models; Part IV. Reduced Models: 14. Eguchi-Kawai model; 15. Twisted reduced models; 16. Non-commutative gauge theories.

Vector/Matrix Quantization for Narrow-Bandwidth Digital Speech Compression.

DTIC Science & Technology

1982-09-01

8217o 0 -X -u -vc "oi ’" o 0 00i MN nM I -r -: I I Ir , I C 64 ut c 4c -C ;6 19I *~I C’ I I I 1 Kall 9 I I V4 S.0 M r4) ** al Iw* 0 0 10* 0 f 65 signal...Prediction of the Speech Wave, JASA Vol. 50, pp. 637-655, April 1971 . - 2. I. Itakura and S. Saito, Analysis Synthesis Telephony Based Upon the Maximum

Image and Video Compression with VLSI Neural Networks

NASA Technical Reports Server (NTRS)

Fang, W.; Sheu, B.

1993-01-01

An advanced motion-compensated predictive video compression system based on artificial neural networks has been developed to effectively eliminate the temporal and spatial redundancy of video image sequences and thus reduce the bandwidth and storage required for the transmission and recording of the video signal. The VLSI neuroprocessor for high-speed high-ratio image compression based upon a self-organization network and the conventional algorithm for vector quantization are compared. The proposed method is quite efficient and can achieve near-optimal results.

Modulated error diffusion CGHs for neural nets

NASA Astrophysics Data System (ADS)

Vermeulen, Pieter J. E.; Casasent, David P.

1990-05-01

New modulated error diffusion CGHs (computer generated holograms) for optical computing are considered. Specific attention is given to their use in optical matrix-vector, associative processor, neural net and optical interconnection architectures. We consider lensless CGH systems (many CGHs use an external Fourier transform (FT) lens), the Fresnel sampling requirements, the effects of finite CGH apertures (sample and hold inputs), dot size correction (for laser recorders), and new applications for this novel encoding method (that devotes attention to quantization noise effects).

Quantum angular momentum diffusion of rigid bodies

NASA Astrophysics Data System (ADS)

Papendell, Birthe; Stickler, Benjamin A.; Hornberger, Klaus

2017-12-01

We show how to describe the diffusion of the quantized angular momentum vector of an arbitrarily shaped rigid rotor as induced by its collisional interaction with an environment. We present the general form of the Lindblad-type master equation and relate it to the orientational decoherence of an asymmetric nanoparticle in the limit of small anisotropies. The corresponding diffusion coefficients are derived for gas particles scattering off large molecules and for ambient photons scattering off dielectric particles, using the elastic scattering amplitudes.

Effect of lead-aircraft ground-speed on self-spacing performance using a cockpit display of traffic information

NASA Technical Reports Server (NTRS)

Kelly, J. R.

1983-01-01

A simulator investigation was conducted to determine the effect of the lead-aircraft ground-speed quantization level on self-spacing performance using a Cockpit Display of Traffic Information (CDTI). The study utilized a simulator employing cathode-ray tubes for the primary flight and navigation displays and highly augmented flight control modes. The pilot's task was to follow, and self-space on, a lead aircraft which was performing an idle-thrust profile descent to an instrument landing system (ILS) approach and landing. The spacing requirement was specified in terms of both a minimum distance and a time interval. The results indicate that the ground-speed quantization level, lead-aircraft scenario, and pilot technique had a significant effect on self-spacing performance. However, the ground-speed quantization level only had a significant effect on the performance when the lead aircraft flew a fast final approach.

Becchi-Rouet-Stora-Tyutin formalism and zero locus reduction

NASA Astrophysics Data System (ADS)

Grigoriev, M. A.; Semikhatov, A. M.; Tipunin, I. Yu.

2001-08-01

In the Becchi-Rouet-Stora-Tyutin (BRST) quantization of gauge theories, the zero locus ZQ of the BRST differential Q carries an (anti)bracket whose parity is opposite to that of the fundamental bracket. Observables of the BRST theory are in a 1:1 correspondence with Casimir functions of the bracket on ZQ. For any constrained dynamical system with the phase space N0 and the constraint surface Σ, we prove its equivalence to the constrained system on the BFV-extended phase space with the constraint surface given by ZQ. Reduction to the zero locus of the differential gives rise to relations between bracket operations and differentials arising in different complexes (the Gerstenhaber, Schouten, Berezin-Kirillov, and Sklyanin brackets); the equation ensuring the existence of a nilpotent vector field on the reduced manifold can be the classical Yang-Baxter equation. We also generalize our constructions to the bi-QP manifolds which from the BRST theory viewpoint correspond to the BRST-anti-BRST-symmetric quantization.

Fast and efficient search for MPEG-4 video using adjacent pixel intensity difference quantization histogram feature

NASA Astrophysics Data System (ADS)

Lee, Feifei; Kotani, Koji; Chen, Qiu; Ohmi, Tadahiro

2010-02-01

In this paper, a fast search algorithm for MPEG-4 video clips from video database is proposed. An adjacent pixel intensity difference quantization (APIDQ) histogram is utilized as the feature vector of VOP (video object plane), which had been reliably applied to human face recognition previously. Instead of fully decompressed video sequence, partially decoded data, namely DC sequence of the video object are extracted from the video sequence. Combined with active search, a temporal pruning algorithm, fast and robust video search can be realized. The proposed search algorithm has been evaluated by total 15 hours of video contained of TV programs such as drama, talk, news, etc. to search for given 200 MPEG-4 video clips which each length is 15 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 80ms, and Equal Error Rate (ERR) of 2 % in drama and news categories are achieved, which are more accurately and robust than conventional fast video search algorithm.

Application of heterogeneous pulse coupled neural network in image quantization

NASA Astrophysics Data System (ADS)

Huang, Yi; Ma, Yide; Li, Shouliang; Zhan, Kun

2016-11-01

On the basis of the different strengths of synaptic connections between actual neurons, this paper proposes a heterogeneous pulse coupled neural network (HPCNN) algorithm to perform quantization on images. HPCNNs are developed from traditional pulse coupled neural network (PCNN) models, which have different parameters corresponding to different image regions. This allows pixels of different gray levels to be classified broadly into two categories: background regional and object regional. Moreover, an HPCNN also satisfies human visual characteristics. The parameters of the HPCNN model are calculated automatically according to these categories, and quantized results will be optimal and more suitable for humans to observe. At the same time, the experimental results of natural images from the standard image library show the validity and efficiency of our proposed quantization method.

Optimal Compression of Floating-Point Astronomical Images Without Significant Loss of Information

NASA Technical Reports Server (NTRS)

Pence, William D.; White, R. L.; Seaman, R.

2010-01-01

We describe a compression method for floating-point astronomical images that gives compression ratios of 6 - 10 while still preserving the scientifically important information in the image. The pixel values are first preprocessed by quantizing them into scaled integer intensity levels, which removes some of the uncompressible noise in the image. The integers are then losslessly compressed using the fast and efficient Rice algorithm and stored in a portable FITS format file. Quantizing an image more coarsely gives greater image compression, but it also increases the noise and degrades the precision of the photometric and astrometric measurements in the quantized image. Dithering the pixel values during the quantization process greatly improves the precision of measurements in the more coarsely quantized images. We perform a series of experiments on both synthetic and real astronomical CCD images to quantitatively demonstrate that the magnitudes and positions of stars in the quantized images can be measured with the predicted amount of precision. In order to encourage wider use of these image compression methods, we have made available a pair of general-purpose image compression programs, called fpack and funpack, which can be used to compress any FITS format image.

Joint Source-Channel Coding by Means of an Oversampled Filter Bank Code

NASA Astrophysics Data System (ADS)

Marinkovic, Slavica; Guillemot, Christine

2006-12-01

Quantized frame expansions based on block transforms and oversampled filter banks (OFBs) have been considered recently as joint source-channel codes (JSCCs) for erasure and error-resilient signal transmission over noisy channels. In this paper, we consider a coding chain involving an OFB-based signal decomposition followed by scalar quantization and a variable-length code (VLC) or a fixed-length code (FLC). This paper first examines the problem of channel error localization and correction in quantized OFB signal expansions. The error localization problem is treated as an[InlineEquation not available: see fulltext.]-ary hypothesis testing problem. The likelihood values are derived from the joint pdf of the syndrome vectors under various hypotheses of impulse noise positions, and in a number of consecutive windows of the received samples. The error amplitudes are then estimated by solving the syndrome equations in the least-square sense. The message signal is reconstructed from the corrected received signal by a pseudoinverse receiver. We then improve the error localization procedure by introducing a per-symbol reliability information in the hypothesis testing procedure of the OFB syndrome decoder. The per-symbol reliability information is produced by the soft-input soft-output (SISO) VLC/FLC decoders. This leads to the design of an iterative algorithm for joint decoding of an FLC and an OFB code. The performance of the algorithms developed is evaluated in a wavelet-based image coding system.

Passive forensics for copy-move image forgery using a method based on DCT and SVD.

PubMed

Zhao, Jie; Guo, Jichang

2013-12-10

As powerful image editing tools are widely used, the demand for identifying the authenticity of an image is much increased. Copy-move forgery is one of the tampering techniques which are frequently used. Most existing techniques to expose this forgery need to improve the robustness for common post-processing operations and fail to precisely locate the tampering region especially when there are large similar or flat regions in the image. In this paper, a robust method based on DCT and SVD is proposed to detect this specific artifact. Firstly, the suspicious image is divided into fixed-size overlapping blocks and 2D-DCT is applied to each block, then the DCT coefficients are quantized by a quantization matrix to obtain a more robust representation of each block. Secondly, each quantized block is divided non-overlapping sub-blocks and SVD is applied to each sub-block, then features are extracted to reduce the dimension of each block using its largest singular value. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks will be matched by predefined shift frequency threshold. Experiment results demonstrate that our proposed method can effectively detect multiple copy-move forgery and precisely locate the duplicated regions, even when an image was distorted by Gaussian blurring, AWGN, JPEG compression and their mixed operations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Resolution-Adaptive Hybrid MIMO Architectures for Millimeter Wave Communications

NASA Astrophysics Data System (ADS)

Choi, Jinseok; Evans, Brian L.; Gatherer, Alan

2017-12-01

In this paper, we propose a hybrid analog-digital beamforming architecture with resolution-adaptive ADCs for millimeter wave (mmWave) receivers with large antenna arrays. We adopt array response vectors for the analog combiners and derive ADC bit-allocation (BA) solutions in closed form. The BA solutions reveal that the optimal number of ADC bits is logarithmically proportional to the RF chain's signal-to-noise ratio raised to the 1/3 power. Using the solutions, two proposed BA algorithms minimize the mean square quantization error of received analog signals under a total ADC power constraint. Contributions of this paper include 1) ADC bit-allocation algorithms to improve communication performance of a hybrid MIMO receiver, 2) approximation of the capacity with the BA algorithm as a function of channels, and 3) a worst-case analysis of the ergodic rate of the proposed MIMO receiver that quantifies system tradeoffs and serves as the lower bound. Simulation results demonstrate that the BA algorithms outperform a fixed-ADC approach in both spectral and energy efficiency, and validate the capacity and ergodic rate formula. For a power constraint equivalent to that of fixed 4-bit ADCs, the revised BA algorithm makes the quantization error negligible while achieving 22% better energy efficiency. Having negligible quantization error allows existing state-of-the-art digital beamformers to be readily applied to the proposed system.

Synthesis of a combined system for precise stabilization of the Spektr-UF observatory: II

NASA Astrophysics Data System (ADS)

Bychkov, I. V.; Voronov, V. A.; Druzhinin, E. I.; Kozlov, R. I.; Ul'yanov, S. A.; Belyaev, B. B.; Telepnev, P. P.; Ul'yashin, A. I.

2014-03-01

The paper presents the second part of the results of search studies for the development of a combined system of high-precision stabilization of the optical telescope for the designed Spectr-UF international observatory [1]. A new modification of the strict method of the synthesis of nonlinear discrete-continuous stabilization systems with uncertainties is described, which is based on the minimization of the guaranteed accuracy estimate calculated using vector Lyapunov functions. Using this method, the synthesis of the feedback parameters in the mode of precise inertial stabilization of the optical telescope axis is performed taking the design nonrigidity, quantization of signals over time and level, and errors of orientation meters, as well as the errors and limitation of control moments of executive engine-flywheels into account. The results of numerical experiments that demonstrate the quality of the synthesized system are presented.

Magnetofermionic condensate in two dimensions

PubMed Central

Kulik, L. V.; Zhuravlev, A. S.; Dickmann, S.; Gorbunov, A. V.; Timofeev, V. B.; Kukushkin, I. V.; Schmult, S.

2016-01-01

Coherent condensate states of particles obeying either Bose or Fermi statistics are in the focus of interest in modern physics. Here we report on condensation of collective excitations with Bose statistics, cyclotron magnetoexcitons, in a high-mobility two-dimensional electron system in a magnetic field. At low temperatures, the dense non-equilibrium ensemble of long-lived triplet magnetoexcitons exhibits both a drastic reduction in the viscosity and a steep enhancement in the response to the external electromagnetic field. The observed effects are related to formation of a super-absorbing state interacting coherently with the electromagnetic field. Simultaneously, the electrons below the Fermi level form a super-emitting state. The effects are explicable from the viewpoint of a coherent condensate phase in a non-equilibrium system of two-dimensional fermions with a fully quantized energy spectrum. The condensation occurs in the space of vectors of magnetic translations, a property providing a completely new landscape for future physical investigations. PMID:27848969

A robust H.264/AVC video watermarking scheme with drift compensation.

PubMed

Jiang, Xinghao; Sun, Tanfeng; Zhou, Yue; Wang, Wan; Shi, Yun-Qing

2014-01-01

A robust H.264/AVC video watermarking scheme for copyright protection with self-adaptive drift compensation is proposed. In our scheme, motion vector residuals of macroblocks with the smallest partition size are selected to hide copyright information in order to hold visual impact and distortion drift to a minimum. Drift compensation is also implemented to reduce the influence of watermark to the most extent. Besides, discrete cosine transform (DCT) with energy compact property is applied to the motion vector residual group, which can ensure robustness against intentional attacks. According to the experimental results, this scheme gains excellent imperceptibility and low bit-rate increase. Malicious attacks with different quantization parameters (QPs) or motion estimation algorithms can be resisted efficiently, with 80% accuracy on average after lossy compression.

A Robust H.264/AVC Video Watermarking Scheme with Drift Compensation

PubMed Central

Sun, Tanfeng; Zhou, Yue; Shi, Yun-Qing

2014-01-01

A robust H.264/AVC video watermarking scheme for copyright protection with self-adaptive drift compensation is proposed. In our scheme, motion vector residuals of macroblocks with the smallest partition size are selected to hide copyright information in order to hold visual impact and distortion drift to a minimum. Drift compensation is also implemented to reduce the influence of watermark to the most extent. Besides, discrete cosine transform (DCT) with energy compact property is applied to the motion vector residual group, which can ensure robustness against intentional attacks. According to the experimental results, this scheme gains excellent imperceptibility and low bit-rate increase. Malicious attacks with different quantization parameters (QPs) or motion estimation algorithms can be resisted efficiently, with 80% accuracy on average after lossy compression. PMID:24672376

Identifying images of handwritten digits using deep learning in H2O

NASA Astrophysics Data System (ADS)

Sadhasivam, Jayakumar; Charanya, R.; Kumar, S. Harish; Srinivasan, A.

2017-11-01

Automatic digit recognition is of popular interest today. Deep learning techniques make it possible for object recognition in image data. Perceiving the digit has turned into a fundamental part as far as certifiable applications. Since, digits are composed in various styles in this way to distinguish the digit it is important to perceive and arrange it with the assistance of machine learning methods. This exploration depends on supervised learning vector quantization neural system arranged under counterfeit artificial neural network. The pictures of digits are perceived, prepared and tried. After the system is made digits are prepared utilizing preparing dataset vectors and testing is connected to the pictures of digits which are separated to each other by fragmenting the picture and resizing the digit picture as needs be for better precision.

Multi-label classification of chronically ill patients with bag of words and supervised dimensionality reduction algorithms.

PubMed

Bromuri, Stefano; Zufferey, Damien; Hennebert, Jean; Schumacher, Michael

2014-10-01

This research is motivated by the issue of classifying illnesses of chronically ill patients for decision support in clinical settings. Our main objective is to propose multi-label classification of multivariate time series contained in medical records of chronically ill patients, by means of quantization methods, such as bag of words (BoW), and multi-label classification algorithms. Our second objective is to compare supervised dimensionality reduction techniques to state-of-the-art multi-label classification algorithms. The hypothesis is that kernel methods and locality preserving projections make such algorithms good candidates to study multi-label medical time series. We combine BoW and supervised dimensionality reduction algorithms to perform multi-label classification on health records of chronically ill patients. The considered algorithms are compared with state-of-the-art multi-label classifiers in two real world datasets. Portavita dataset contains 525 diabetes type 2 (DT2) patients, with co-morbidities of DT2 such as hypertension, dyslipidemia, and microvascular or macrovascular issues. MIMIC II dataset contains 2635 patients affected by thyroid disease, diabetes mellitus, lipoid metabolism disease, fluid electrolyte disease, hypertensive disease, thrombosis, hypotension, chronic obstructive pulmonary disease (COPD), liver disease and kidney disease. The algorithms are evaluated using multi-label evaluation metrics such as hamming loss, one error, coverage, ranking loss, and average precision. Non-linear dimensionality reduction approaches behave well on medical time series quantized using the BoW algorithm, with results comparable to state-of-the-art multi-label classification algorithms. Chaining the projected features has a positive impact on the performance of the algorithm with respect to pure binary relevance approaches. The evaluation highlights the feasibility of representing medical health records using the BoW for multi-label classification tasks. The study also highlights that dimensionality reduction algorithms based on kernel methods, locality preserving projections or both are good candidates to deal with multi-label classification tasks in medical time series with many missing values and high label density. Copyright © 2014 Elsevier Inc. All rights reserved.

Design of a Two-level Adaptive Multi-Agent System for Malaria Vectors driven by an ontology

PubMed Central

Koum, Guillaume; Yekel, Augustin; Ndifon, Bengyella; Etang, Josiane; Simard, Frédéric

2007-01-01

Background The understanding of heterogeneities in disease transmission dynamics as far as malaria vectors are concerned is a big challenge. Many studies while tackling this problem don't find exact models to explain the malaria vectors propagation. Methods To solve the problem we define an Adaptive Multi-Agent System (AMAS) which has the property to be elastic and is a two-level system as well. This AMAS is a dynamic system where the two levels are linked by an Ontology which allows it to function as a reduced system and as an extended system. In a primary level, the AMAS comprises organization agents and in a secondary level, it is constituted of analysis agents. Its entry point, a User Interface Agent, can reproduce itself because it is given a minimum of background knowledge and it learns appropriate "behavior" from the user in the presence of ambiguous queries and from other agents of the AMAS in other situations. Results Some of the outputs of our system present a series of tables, diagrams showing some factors like Entomological parameters of malaria transmission, Percentages of malaria transmission per malaria vectors, Entomological inoculation rate. Many others parameters can be produced by the system depending on the inputted data. Conclusion Our approach is an intelligent one which differs from statistical approaches that are sometimes used in the field. This intelligent approach aligns itself with the distributed artificial intelligence. In terms of fight against malaria disease our system offers opportunities of reducing efforts of human resources who are not obliged to cover the entire territory while conducting surveys. Secondly the AMAS can determine the presence or the absence of malaria vectors even when specific data have not been collected in the geographical area. In the difference of a statistical technique, in our case the projection of the results in the field can sometimes appeared to be more general. PMID:17605778

Quantization of Gaussian samples at very low SNR regime in continuous variable QKD applications

NASA Astrophysics Data System (ADS)

Daneshgaran, Fred; Mondin, Marina

2016-09-01

The main problem for information reconciliation in continuous variable Quantum Key Distribution (QKD) at low Signal to Noise Ratio (SNR) is quantization and assignment of labels to the samples of the Gaussian Random Variables (RVs) observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective SNR exasperating the problem. This paper looks at the quantization problem of the Gaussian samples at very low SNR regime from an information theoretic point of view. We look at the problem of two bit per sample quantization of the Gaussian RVs at Alice and Bob and derive expressions for the mutual information between the bit strings as a result of this quantization. The quantization threshold for the Most Significant Bit (MSB) should be chosen based on the maximization of the mutual information between the quantized bit strings. Furthermore, while the LSB string at Alice and Bob are balanced in a sense that their entropy is close to maximum, this is not the case for the second most significant bit even under optimal threshold. We show that with two bit quantization at SNR of -3 dB we achieve 75.8% of maximal achievable mutual information between Alice and Bob, hence, as the number of quantization bits increases beyond 2-bits, the number of additional useful bits that can be extracted for secret key generation decreases rapidly. Furthermore, the error rates between the bit strings at Alice and Bob at the same significant bit level are rather high demanding very powerful error correcting codes. While our calculations and simulation shows that the mutual information between the LSB at Alice and Bob is 0.1044 bits, that at the MSB level is only 0.035 bits. Hence, it is only by looking at the bits jointly that we are able to achieve a mutual information of 0.2217 bits which is 75.8% of maximum achievable. The implication is that only by coding both MSB and LSB jointly can we hope to get close to this 75.8% limit. Hence, non-binary codes are essential to achieve acceptable performance.

Radiation dose-rate meter using an energy-sensitive counter

DOEpatents

Kopp, Manfred K.

1988-01-01

A radiation dose-rate meter is provided which uses an energy-sensitive detector and combines charge quantization and pulse-rate measurement to monitor radiation dose rates. The charge from each detected photon is quantized by level-sensitive comparators so that the resulting total output pulse rate is proportional to the dose-rate.

Perturbative Yang-Mills theory without Faddeev-Popov ghost fields

NASA Astrophysics Data System (ADS)

Huffel, Helmuth; Markovic, Danijel

2018-05-01

A modified Faddeev-Popov path integral density for the quantization of Yang-Mills theory in the Feynman gauge is discussed, where contributions of the Faddeev-Popov ghost fields are replaced by multi-point gauge field interactions. An explicit calculation to O (g2) shows the equivalence of the usual Faddeev-Popov scheme and its modified version.

Finite-time H∞ control for a class of discrete-time switched time-delay systems with quantized feedback

NASA Astrophysics Data System (ADS)

Song, Haiyu; Yu, Li; Zhang, Dan; Zhang, Wen-An

2012-12-01

This paper is concerned with the finite-time quantized H∞ control problem for a class of discrete-time switched time-delay systems with time-varying exogenous disturbances. By using the sector bound approach and the average dwell time method, sufficient conditions are derived for the switched system to be finite-time bounded and ensure a prescribed H∞ disturbance attenuation level, and a mode-dependent quantized state feedback controller is designed by solving an optimization problem. Two illustrative examples are provided to demonstrate the effectiveness of the proposed theoretical results.

Classification of postural profiles among mouth-breathing children by learning vector quantization.

PubMed

Mancini, F; Sousa, F S; Hummel, A D; Falcão, A E J; Yi, L C; Ortolani, C F; Sigulem, D; Pisa, I T

2011-01-01

Mouth breathing is a chronic syndrome that may bring about postural changes. Finding characteristic patterns of changes occurring in the complex musculoskeletal system of mouth-breathing children has been a challenge. Learning vector quantization (LVQ) is an artificial neural network model that can be applied for this purpose. The aim of the present study was to apply LVQ to determine the characteristic postural profiles shown by mouth-breathing children, in order to further understand abnormal posture among mouth breathers. Postural training data on 52 children (30 mouth breathers and 22 nose breathers) and postural validation data on 32 children (22 mouth breathers and 10 nose breathers) were used. The performance of LVQ and other classification models was compared in relation to self-organizing maps, back-propagation applied to multilayer perceptrons, Bayesian networks, naive Bayes, J48 decision trees, k, and k-nearest-neighbor classifiers. Classifier accuracy was assessed by means of leave-one-out cross-validation, area under ROC curve (AUC), and inter-rater agreement (Kappa statistics). By using the LVQ model, five postural profiles for mouth-breathing children could be determined. LVQ showed satisfactory results for mouth-breathing and nose-breathing classification: sensitivity and specificity rates of 0.90 and 0.95, respectively, when using the training dataset, and 0.95 and 0.90, respectively, when using the validation dataset. The five postural profiles for mouth-breathing children suggested by LVQ were incorporated into application software for classifying the severity of mouth breathers' abnormal posture.

Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search.

PubMed

Liu, Xianglong; Huang, Lei; Deng, Cheng; Lang, Bo; Tao, Dacheng

2016-10-01

Hash-based nearest neighbor search has become attractive in many applications. However, the quantization in hashing usually degenerates the discriminative power when using Hamming distance ranking. Besides, for large-scale visual search, existing hashing methods cannot directly support the efficient search over the data with multiple sources, and while the literature has shown that adaptively incorporating complementary information from diverse sources or views can significantly boost the search performance. To address the problems, this paper proposes a novel and generic approach to building multiple hash tables with multiple views and generating fine-grained ranking results at bitwise and tablewise levels. For each hash table, a query-adaptive bitwise weighting is introduced to alleviate the quantization loss by simultaneously exploiting the quality of hash functions and their complement for nearest neighbor search. From the tablewise aspect, multiple hash tables are built for different data views as a joint index, over which a query-specific rank fusion is proposed to rerank all results from the bitwise ranking by diffusing in a graph. Comprehensive experiments on image search over three well-known benchmarks show that the proposed method achieves up to 17.11% and 20.28% performance gains on single and multiple table search over the state-of-the-art methods.

Approaching the Planck scale from a generally relativistic point of view: A philosophical appraisal of loop quantum gravity

NASA Astrophysics Data System (ADS)

Wuthrich, Christian

My dissertation studies the foundations of loop quantum gravity (LQG), a candidate for a quantum theory of gravity based on classical general relativity. At the outset, I discuss two---and I claim separate---questions: first, do we need a quantum theory of gravity at all; and second, if we do, does it follow that gravity should or even must be quantized? My evaluation of different arguments either way suggests that while no argument can be considered conclusive, there are strong indications that gravity should be quantized. LQG attempts a canonical quantization of general relativity and thereby provokes a foundational interest as it must take a stance on many technical issues tightly linked to the interpretation of general relativity. Most importantly, it codifies general relativity's main innovation, the so-called background independence, in a formalism suitable for quantization. This codification pulls asunder what has been joined together in general relativity: space and time. It is thus a central issue whether or not general relativity's four-dimensional structure can be retrieved in the alternative formalism and how it fares through the quantization process. I argue that the rightful four-dimensional spacetime structure can only be partially retrieved at the classical level. What happens at the quantum level is an entirely open issue. Known examples of classically singular behaviour which gets regularized by quantization evoke an admittedly pious hope that the singularities which notoriously plague the classical theory may be washed away by quantization. This work scrutinizes pronouncements claiming that the initial singularity of classical cosmological models vanishes in quantum cosmology based on LQG and concludes that these claims must be severely qualified. In particular, I explicate why casting the quantum cosmological models in terms of a deterministic temporal evolution fails to capture the concepts at work adequately. Finally, a scheme is developed of how the re-emergence of the smooth spacetime from the underlying discrete quantum structure could be understood.

Topological Frequency Conversion in Strongly Driven Quantum Systems

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

Martin, Ivar; Refael, Gil; Halperin, Bertrand

When a physical system is subjected to a strong external multi-frequency drive, its dynamics can be conveniently represented in the multi-dimensional Floquet lattice. The number of the Floquet lattice dimensions equals the number of irrationally-related drive frequencies, and the evolution occurs in response to a built-in effective \\electric" field, whose components are proportional to the corresponding drive frequencies. The mapping allows to engineer and study temporal analogs of many real-space phenomena. Here we focus on the specifc example of a two-level system under two-frequency drive that induces topologically nontrivial band structure in the 2D Floquet space. The observable consequence ofmore » such construction is quantized pumping of energy between the sources with frequencies w 1 and w 2. Finally, when the system is initialized into a Floquet band with the Chern number C, the pumping occurs at the rate P 12 = – P 21 = ( C/2π)hw 1w 2, an exact counterpart of the transverse current in a conventional topological insulator.« less

Topological Frequency Conversion in Strongly Driven Quantum Systems

DOE PAGES

Martin, Ivar; Refael, Gil; Halperin, Bertrand

2017-10-16

When a physical system is subjected to a strong external multi-frequency drive, its dynamics can be conveniently represented in the multi-dimensional Floquet lattice. The number of the Floquet lattice dimensions equals the number of irrationally-related drive frequencies, and the evolution occurs in response to a built-in effective \\electric" field, whose components are proportional to the corresponding drive frequencies. The mapping allows to engineer and study temporal analogs of many real-space phenomena. Here we focus on the specifc example of a two-level system under two-frequency drive that induces topologically nontrivial band structure in the 2D Floquet space. The observable consequence ofmore » such construction is quantized pumping of energy between the sources with frequencies w 1 and w 2. Finally, when the system is initialized into a Floquet band with the Chern number C, the pumping occurs at the rate P 12 = – P 21 = ( C/2π)hw 1w 2, an exact counterpart of the transverse current in a conventional topological insulator.« less

High-level rapid production of full-size monoclonal antibodies in plants by a single-vector DNA replicon system

PubMed Central

Huang, Zhong; Phoolcharoen, Waranyoo; Lai, Huafang; Piensook, Khanrat; Cardineau, Guy; Zeitlin, Larry; Whaley, Kevin J.; Arntzen, Charles J.

2010-01-01

Plant viral vectors have great potential in rapid production of important pharmaceutical proteins. However, high-yield production of heterooligomeric proteins that require the expression and assembly of two or more protein subunits often suffers problems due to the “competing” nature of viral vectors derived from the same virus. Previously we reported that a bean yellow dwarf virus (BeYDV)-derived, three-component DNA replicon system allows rapid production of single recombinant proteins in plants (Huang et al. 2009). In this article, we report further development of this expression system for its application in high-yield production of oligomeric protein complexes including monoclonal antibodies (mAbs) in plants. We showed that the BeYDV replicon system permits simultaneous efficient replication of two DNA replicons and thus, high-level accumulation of two recombinant proteins in the same plant cell. We also demonstrated that a single vector that contains multiple replicon cassettes was as efficient as the three-component system in driving the expression of two distinct proteins. Using either the non-competing, three-vector system or the multi-replicon single vector, we produced both the heavy and light chain subunits of a protective IgG mAb 6D8 against Ebola virus GP1 (Wilson et al. 2000) at 0.5 mg of mAb per gram leaf fresh weight within 4 days post infiltration of Nicotiana benthamiana leaves. We further demonstrated that full-size tetrameric IgG complex containing two heavy and two light chains was efficiently assembled and readily purified, and retained its functionality in specific binding to inactivated Ebola virus. Thus, our single-vector replicon system provides high-yield production capacity for heterooligomeric proteins, yet eliminates the difficult task of identifying non-competing virus and the need for co-infection of multiple expression modules. The multi-replicon vector represents a significant advance in transient expression technology for antibody production in plants. PMID:20047189

The canonical quantization of chaotic maps on the torus

NASA Astrophysics Data System (ADS)

Rubin, Ron Shai

In this thesis, a quantization method for classical maps on the torus is presented. The quantum algebra of observables is defined as the quantization of measurable functions on the torus with generators exp (2/pi ix) and exp (2/pi ip). The Hilbert space we use remains the infinite-dimensional L2/ (/IR, dx). The dynamics is given by a unitary quantum propagator such that as /hbar /to 0, the classical dynamics is returned. We construct such a quantization for the Kronecker map, the cat map, the baker's map, the kick map, and the Harper map. For the cat map, we find the same for the propagator on the plane the same integral kernel conjectured in (HB) using semiclassical methods. We also define a quantum 'integral over phase space' as a trace over the quantum algebra. Using this definition, we proceed to define quantum ergodicity and mixing for maps on the torus. We prove that the quantum cat map and Kronecker map are both ergodic, but only the cat map is mixing, true to its classical origins. For Planck's constant satisfying the integrality condition h = 1/N, with N/in doubz+, we construct an explicit isomorphism between L2/ (/IR, dx) and the Hilbert space of sections of an N-dimensional vector bundle over a θ-torus T2 of boundary conditions. The basis functions are distributions in L2/ (/IR, dx), given by an infinite comb of Dirac δ-functions. In Bargmann space these distributions take on the form of Jacobi ϑ-functions. Transformations from position to momentum representation can be implemented via a finite N-dimensional discrete Fourier transform. With the θ-torus, we provide a connection between the finite-dimensional quantum maps given in the physics literature and the canonical quantization presented here and found in the language of pseudo-differential operators elsewhere in mathematics circles. Specifically, at a fixed point of the dynamics on the θ-torus, we return a finite-dimensional matrix propagator. We present this connection explicitly for several examples.

A multi-dimensional Smolyak collocation method in curvilinear coordinates for computing vibrational spectra

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

Avila, Gustavo, E-mail: Gustavo-Avila@telefonica.net; Carrington, Tucker, E-mail: Tucker.Carrington@queensu.ca

In this paper, we improve the collocation method for computing vibrational spectra that was presented in Avila and Carrington, Jr. [J. Chem. Phys. 139, 134114 (2013)]. Using an iterative eigensolver, energy levels and wavefunctions are determined from values of the potential on a Smolyak grid. The kinetic energy matrix-vector product is evaluated by transforming a vector labelled with (nondirect product) grid indices to a vector labelled by (nondirect product) basis indices. Both the transformation and application of the kinetic energy operator (KEO) scale favorably. Collocation facilitates dealing with complicated KEOs because it obviates the need to calculate integrals of coordinatemore » dependent coefficients of differential operators. The ideas are tested by computing energy levels of HONO using a KEO in bond coordinates.« less

Minimal-post-processing 320-Gbps true random bit generation using physical white chaos.

PubMed

Wang, Anbang; Wang, Longsheng; Li, Pu; Wang, Yuncai

2017-02-20

Chaotic external-cavity semiconductor laser (ECL) is a promising entropy source for generation of high-speed physical random bits or digital keys. The rate and randomness is unfortunately limited by laser relaxation oscillation and external-cavity resonance, and is usually improved by complicated post processing. Here, we propose using a physical broadband white chaos generated by optical heterodyning of two ECLs as entropy source to construct high-speed random bit generation (RBG) with minimal post processing. The optical heterodyne chaos not only has a white spectrum without signature of relaxation oscillation and external-cavity resonance but also has a symmetric amplitude distribution. Thus, after quantization with a multi-bit analog-digital-convertor (ADC), random bits can be obtained by extracting several least significant bits (LSBs) without any other processing. In experiments, a white chaos with a 3-dB bandwidth of 16.7 GHz is generated. Its entropy rate is estimated as 16 Gbps by single-bit quantization which means a spectrum efficiency of 96%. With quantization using an 8-bit ADC, 320-Gbps physical RBG is achieved by directly extracting 4 LSBs at 80-GHz sampling rate.

Model-based VQ for image data archival, retrieval and distribution

NASA Technical Reports Server (NTRS)

Manohar, Mareboyana; Tilton, James C.

1995-01-01

An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

The research of "blind" spot in the LVQ network

NASA Astrophysics Data System (ADS)

Guo, Zhanjie; Nan, Shupo; Wang, Xiaoli

2017-04-01

Nowadays competitive neural network has been widely used in the pattern recognition, classification and other aspects, and show the great advantages compared with the traditional clustering methods. But the competitive neural networks still has inadequate in many aspects, and it needs to be further improved. Based on the learning Vector Quantization Network proposed by Learning Kohonen [1], this paper resolve the issue of the large training error, when there are "blind" spots in a network through the introduction of threshold value learning rules and finally programs the realization with Matlab.

Research on conceptual/innovative design for the life cycle

NASA Technical Reports Server (NTRS)

Cagan, Jonathan; Agogino, Alice M.

1990-01-01

The goal of this research is developing and integrating qualitative and quantitative methods for life cycle design. The definition of the problem includes formal computer-based methods limited to final detailing stages of design; CAD data bases do not capture design intent or design history; and life cycle issues were ignored during early stages of design. Viewgraphs outline research in conceptual design; the SYMON (SYmbolic MONotonicity analyzer) algorithm; multistart vector quantization optimization algorithm; intelligent manufacturing: IDES - Influence Diagram Architecture; and 1st PRINCE (FIRST PRINciple Computational Evaluator).

A neural net based architecture for the segmentation of mixed gray-level and binary pictures

NASA Technical Reports Server (NTRS)

Tabatabai, Ali; Troudet, Terry P.

1991-01-01

A neural-net-based architecture is proposed to perform segmentation in real time for mixed gray-level and binary pictures. In this approach, the composite picture is divided into 16 x 16 pixel blocks, which are identified as character blocks or image blocks on the basis of a dichotomy measure computed by an adaptive 16 x 16 neural net. For compression purposes, each image block is further divided into 4 x 4 subblocks; a one-bit nonparametric quantizer is used to encode 16 x 16 character and 4 x 4 image blocks; and the binary map and quantizer levels are obtained through a neural net segmentor over each block. The efficiency of the neural segmentation in terms of computational speed, data compression, and quality of the compressed picture is demonstrated. The effect of weight quantization is also discussed. VLSI implementations of such adaptive neural nets in CMOS technology are described and simulated in real time for a maximum block size of 256 pixels.

Enhanced secure 4-D modulation space optical multi-carrier system based on joint constellation and Stokes vector scrambling.

PubMed

Liu, Bo; Zhang, Lijia; Xin, Xiangjun

2018-03-19

This paper proposes and demonstrates an enhanced secure 4-D modulation optical generalized filter bank multi-carrier (GFBMC) system based on joint constellation and Stokes vector scrambling. The constellation and Stokes vectors are scrambled by using different scrambling parameters. A multi-scroll Chua's circuit map is adopted as the chaotic model. Large secure key space can be obtained due to the multi-scroll attractors and independent operability of subcarriers. A 40.32Gb/s encrypted optical GFBMC signal with 128 parallel subcarriers is successfully demonstrated in the experiment. The results show good resistance against the illegal receiver and indicate a potential way for the future optical multi-carrier system.

Linear time relational prototype based learning.

PubMed

Gisbrecht, Andrej; Mokbel, Bassam; Schleif, Frank-Michael; Zhu, Xibin; Hammer, Barbara

2012-10-01

Prototype based learning offers an intuitive interface to inspect large quantities of electronic data in supervised or unsupervised settings. Recently, many techniques have been extended to data described by general dissimilarities rather than Euclidean vectors, so-called relational data settings. Unlike the Euclidean counterparts, the techniques have quadratic time complexity due to the underlying quadratic dissimilarity matrix. Thus, they are infeasible already for medium sized data sets. The contribution of this article is twofold: On the one hand we propose a novel supervised prototype based classification technique for dissimilarity data based on popular learning vector quantization (LVQ), on the other hand we transfer a linear time approximation technique, the Nyström approximation, to this algorithm and an unsupervised counterpart, the relational generative topographic mapping (GTM). This way, linear time and space methods result. We evaluate the techniques on three examples from the biomedical domain.

Vector Sum Excited Linear Prediction (VSELP) speech coding at 4.8 kbps

NASA Technical Reports Server (NTRS)

Gerson, Ira A.; Jasiuk, Mark A.

1990-01-01

Code Excited Linear Prediction (CELP) speech coders exhibit good performance at data rates as low as 4800 bps. The major drawback to CELP type coders is their larger computational requirements. The Vector Sum Excited Linear Prediction (VSELP) speech coder utilizes a codebook with a structure which allows for a very efficient search procedure. Other advantages of the VSELP codebook structure is discussed and a detailed description of a 4.8 kbps VSELP coder is given. This coder is an improved version of the VSELP algorithm, which finished first in the NSA's evaluation of the 4.8 kbps speech coders. The coder uses a subsample resolution single tap long term predictor, a single VSELP excitation codebook, a novel gain quantizer which is robust to channel errors, and a new adaptive pre/postfilter arrangement.

Bit Grooming: statistically accurate precision-preserving quantization with compression, evaluated in the netCDF Operators (NCO, v4.4.8+)

NASA Astrophysics Data System (ADS)

Zender, Charles S.

2016-09-01

Geoscientific models and measurements generate false precision (scientifically meaningless data bits) that wastes storage space. False precision can mislead (by implying noise is signal) and be scientifically pointless, especially for measurements. By contrast, lossy compression can be both economical (save space) and heuristic (clarify data limitations) without compromising the scientific integrity of data. Data quantization can thus be appropriate regardless of whether space limitations are a concern. We introduce, implement, and characterize a new lossy compression scheme suitable for IEEE floating-point data. Our new Bit Grooming algorithm alternately shaves (to zero) and sets (to one) the least significant bits of consecutive values to preserve a desired precision. This is a symmetric, two-sided variant of an algorithm sometimes called Bit Shaving that quantizes values solely by zeroing bits. Our variation eliminates the artificial low bias produced by always zeroing bits, and makes Bit Grooming more suitable for arrays and multi-dimensional fields whose mean statistics are important. Bit Grooming relies on standard lossless compression to achieve the actual reduction in storage space, so we tested Bit Grooming by applying the DEFLATE compression algorithm to bit-groomed and full-precision climate data stored in netCDF3, netCDF4, HDF4, and HDF5 formats. Bit Grooming reduces the storage space required by initially uncompressed and compressed climate data by 25-80 and 5-65 %, respectively, for single-precision values (the most common case for climate data) quantized to retain 1-5 decimal digits of precision. The potential reduction is greater for double-precision datasets. When used aggressively (i.e., preserving only 1-2 digits), Bit Grooming produces storage reductions comparable to other quantization techniques such as Linear Packing. Unlike Linear Packing, whose guaranteed precision rapidly degrades within the relatively narrow dynamic range of values that it can compress, Bit Grooming guarantees the specified precision throughout the full floating-point range. Data quantization by Bit Grooming is irreversible (i.e., lossy) yet transparent, meaning that no extra processing is required by data users/readers. Hence Bit Grooming can easily reduce data storage volume without sacrificing scientific precision or imposing extra burdens on users.

Event-triggered H∞ state estimation for semi-Markov jumping discrete-time neural networks with quantization.

PubMed

Rakkiyappan, R; Maheswari, K; Velmurugan, G; Park, Ju H

2018-05-17

This paper investigates H ∞ state estimation problem for a class of semi-Markovian jumping discrete-time neural networks model with event-triggered scheme and quantization. First, a new event-triggered communication scheme is introduced to determine whether or not the current sampled sensor data should be broad-casted and transmitted to the quantizer, which can save the limited communication resource. Second, a novel communication framework is employed by the logarithmic quantizer that quantifies and reduces the data transmission rate in the network, which apparently improves the communication efficiency of networks. Third, a stabilization criterion is derived based on the sufficient condition which guarantees a prescribed H ∞ performance level in the estimation error system in terms of the linear matrix inequalities. Finally, numerical simulations are given to illustrate the correctness of the proposed scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

Regional autonomy changes in resting-state functional MRI in patients with HIV associated neurocognitive disorder

NASA Astrophysics Data System (ADS)

DSouza, Adora M.; Abidin, Anas Z.; Chockanathan, Udaysankar; Wismüller, Axel

2018-03-01

In this study, we investigate whether there are discernable changes in influence that brain regions have on themselves once patients show symptoms of HIV Associated Neurocognitive Disorder (HAND) using functional MRI (fMRI). Simple functional connectivity measures, such as correlation cannot reveal such information. To this end, we use mutual connectivity analysis (MCA) with Local Models (LM), which reveals a measure of influence in terms of predictability. Once such measures of interaction are obtained, we train two classifiers to characterize difference in patterns of regional self-influence between healthy subjects and subjects presenting with HAND symptoms. The two classifiers we use are Support Vector Machines (SVM) and Localized Generalized Matrix Learning Vector Quantization (LGMLVQ). Performing machine learning on fMRI connectivity measures is popularly known as multi-voxel pattern analysis (MVPA). By performing such an analysis, we are interested in studying the impact HIV infection has on an individual's brain. The high area under receiver operating curve (AUC) and accuracy values for 100 different train/test separations using MCA-LM self-influence measures (SVM: mean AUC=0.86, LGMLVQ: mean AUC=0.88, SVM and LGMLVQ: mean accuracy=0.78) compared with standard MVPA analysis using cross-correlation between fMRI time-series (SVM: mean AUC=0.58, LGMLVQ: mean AUC=0.57), demonstrates that self-influence features can be more discriminative than measures of interaction between time-series pairs. Furthermore, our results suggest that incorporating measures of self-influence in MVPA analysis used commonly in fMRI analysis has the potential to provide a performance boost and indicate important changes in dynamics of regions in the brain as a consequence of HIV infection.

Mission Capability Gains from Multi-Mode Propulsion Thrust Profile Variations for a Plane Change Maneuver

DTIC Science & Technology

2010-12-29

propellant mass [kg] msc = mass of the spacecraft [kg] MMP = multi-mode propulsion   = position in the Geocentric Equatorial Reference...thrust burn time [s] Tsc = thrust of the spacecraft [N] = vector between current and final velocity vector   = velocity vector in the Geocentric ...Equatorial Reference Frame of spacecraft in intended orbit [km/s]   = velocity vector in the Geocentric Equatorial Reference Frame of spacecraft in

Entanglement Criteria of Two Two-Level Atoms Interacting with Two Coupled Modes

NASA Astrophysics Data System (ADS)

Baghshahi, Hamid Reza; Tavassoly, Mohammad Kazem; Faghihi, Mohammad Javad

2015-08-01

In this paper, we study the interaction between two two-level atoms and two coupled modes of a quantized radiation field in the form of parametric frequency converter injecting within an optical cavity enclosed by a medium with Kerr nonlinearity. It is demonstrated that, by applying the Bogoliubov-Valatin canonical transformation, the introduced model is reduced to a well-known form of the generalized Jaynes-Cummings model. Then, under particular initial conditions for the atoms (in a coherent superposition of its ground and upper states) and the fields (in a standard coherent state) which may be prepared, the time evolution of state vector of the entire system is analytically evaluated. In order to understand the degree of entanglement between subsystems (atom-field and atom-atom), the dynamics of entanglement through different measures, namely, von Neumann reduced entropy, concurrence and negativity is evaluated. In each case, the effects of Kerr nonlinearity and detuning parameter on the above measures are numerically analyzed, in detail. It is illustrated that the amount of entanglement can be tuned by choosing the evolved parameters, appropriately.

Quantization and superselection sectors III: Multiply connected spaces and indistinguishable particles

NASA Astrophysics Data System (ADS)

Landsman, N. P. Klaas

2016-09-01

We reconsider the (non-relativistic) quantum theory of indistinguishable particles on the basis of Rieffel’s notion of C∗-algebraic (“strict”) deformation quantization. Using this formalism, we relate the operator approach of Messiah and Greenberg (1964) to the configuration space approach pioneered by Souriau (1967), Laidlaw and DeWitt-Morette (1971), Leinaas and Myrheim (1977), and others. In dimension d > 2, the former yields bosons, fermions, and paraparticles, whereas the latter seems to leave room for bosons and fermions only, apparently contradicting the operator approach as far as the admissibility of parastatistics is concerned. To resolve this, we first prove that in d > 2 the topologically non-trivial configuration spaces of the second approach are quantized by the algebras of observables of the first. Secondly, we show that the irreducible representations of the latter may be realized by vector bundle constructions, among which the line bundles recover the results of the second approach. Mathematically speaking, representations on higher-dimensional bundles (which define parastatistics) cannot be excluded, which render the configuration space approach incomplete. Physically, however, we show that the corresponding particle states may always be realized in terms of bosons and/or fermions with an unobserved internal degree of freedom (although based on non-relativistic quantum mechanics, this conclusion is analogous to the rigorous results of the Doplicher-Haag-Roberts analysis in algebraic quantum field theory, as well as to the heuristic arguments which led Gell-Mann and others to QCD (i.e. Quantum Chromodynamics)).

Methods, systems and apparatus for controlling third harmonic voltage when operating a multi-space machine in an overmodulation region

DOEpatents

Perisic, Milun; Kinoshita, Michael H; Ranson, Ray M; Gallegos-Lopez, Gabriel

2014-06-03

Methods, system and apparatus are provided for controlling third harmonic voltages when operating a multi-phase machine in an overmodulation region. The multi-phase machine can be, for example, a five-phase machine in a vector controlled motor drive system that includes a five-phase PWM controlled inverter module that drives the five-phase machine. Techniques for overmodulating a reference voltage vector are provided. For example, when the reference voltage vector is determined to be within the overmodulation region, an angle of the reference voltage vector can be modified to generate a reference voltage overmodulation control angle, and a magnitude of the reference voltage vector can be modified, based on the reference voltage overmodulation control angle, to generate a modified magnitude of the reference voltage vector. By modifying the reference voltage vector, voltage command signals that control a five-phase inverter module can be optimized to increase output voltages generated by the five-phase inverter module.

Magnetic quantization in monolayer bismuthene

NASA Astrophysics Data System (ADS)

Chen, Szu-Chao; Chiu, Chih-Wei; Lin, Hui-Chi; Lin, Ming-Fa

The magnetic quantization in monolayer bismuthene is investigated by the generalized tight-binding model. The quite large Hamiltonian matrix is built from the tight-binding functions of the various sublattices, atomic orbitals and spin states. Due to the strong spin orbital coupling and sp3 bonding, monolayer bismuthene has the diverse low-lying energy bands such as the parabolic, linear and oscillating energy bands. The main features of band structures are further reflected in the rich magnetic quantization. Under a uniform perpendicular magnetic field (Bz) , three groups of Landau levels (LLs) with distinct features are revealed near the Fermi level. Their Bz-dependent energy spectra display the linear, square-root and non-monotonous dependences, respectively. These LLs are dominated by the combinations of the 6pz orbital and (6px,6py) orbitals as a result of strong sp3 bonding. Specifically, the LL anti-crossings only occur between LLs originating from the oscillating energy band.

Electrically pumped graphene-based Landau-level laser

NASA Astrophysics Data System (ADS)

Brem, Samuel; Wendler, Florian; Winnerl, Stephan; Malic, Ermin

2018-03-01

Graphene exhibits a nonequidistant Landau quantization with tunable Landau-level (LL) transitions in the technologically desired terahertz spectral range. Here, we present a strategy for an electrically driven terahertz laser based on Landau-quantized graphene as the gain medium. Performing microscopic modeling of the coupled electron, phonon, and photon dynamics in such a laser, we reveal that an inter-LL population inversion can be achieved resulting in the emission of coherent terahertz radiation. The presented paper provides a concrete recipe for the experimental realization of tunable graphene-based terahertz laser systems.

The electronic structure of Au25 clusters: between discrete and continuous.

PubMed

Katsiev, Khabiboulakh; Lozova, Nataliya; Wang, Lu; Sai Krishna, Katla; Li, Ruipeng; Mei, Wai-Ning; Skrabalak, Sara E; Kumar, Challa S S R; Losovyj, Yaroslav

2016-08-21

Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies.

A robust hidden Markov Gauss mixture vector quantizer for a noisy source.

PubMed

Pyun, Kyungsuk Peter; Lim, Johan; Gray, Robert M

2009-07-01

Noise is ubiquitous in real life and changes image acquisition, communication, and processing characteristics in an uncontrolled manner. Gaussian noise and Salt and Pepper noise, in particular, are prevalent in noisy communication channels, camera and scanner sensors, and medical MRI images. It is not unusual for highly sophisticated image processing algorithms developed for clean images to malfunction when used on noisy images. For example, hidden Markov Gauss mixture models (HMGMM) have been shown to perform well in image segmentation applications, but they are quite sensitive to image noise. We propose a modified HMGMM procedure specifically designed to improve performance in the presence of noise. The key feature of the proposed procedure is the adjustment of covariance matrices in Gauss mixture vector quantizer codebooks to minimize an overall minimum discrimination information distortion (MDI). In adjusting covariance matrices, we expand or shrink their elements based on the noisy image. While most results reported in the literature assume a particular noise type, we propose a framework without assuming particular noise characteristics. Without denoising the corrupted source, we apply our method directly to the segmentation of noisy sources. We apply the proposed procedure to the segmentation of aerial images with Salt and Pepper noise and with independent Gaussian noise, and we compare our results with those of the median filter restoration method and the blind deconvolution-based method, respectively. We show that our procedure has better performance than image restoration-based techniques and closely matches to the performance of HMGMM for clean images in terms of both visual segmentation results and error rate.

Poisson traces, D-modules, and symplectic resolutions

NASA Astrophysics Data System (ADS)

Etingof, Pavel; Schedler, Travis

2018-03-01

We survey the theory of Poisson traces (or zeroth Poisson homology) developed by the authors in a series of recent papers. The goal is to understand this subtle invariant of (singular) Poisson varieties, conditions for it to be finite-dimensional, its relationship to the geometry and topology of symplectic resolutions, and its applications to quantizations. The main technique is the study of a canonical D-module on the variety. In the case the variety has finitely many symplectic leaves (such as for symplectic singularities and Hamiltonian reductions of symplectic vector spaces by reductive groups), the D-module is holonomic, and hence, the space of Poisson traces is finite-dimensional. As an application, there are finitely many irreducible finite-dimensional representations of every quantization of the variety. Conjecturally, the D-module is the pushforward of the canonical D-module under every symplectic resolution of singularities, which implies that the space of Poisson traces is dual to the top cohomology of the resolution. We explain many examples where the conjecture is proved, such as symmetric powers of du Val singularities and symplectic surfaces and Slodowy slices in the nilpotent cone of a semisimple Lie algebra. We compute the D-module in the case of surfaces with isolated singularities and show it is not always semisimple. We also explain generalizations to arbitrary Lie algebras of vector fields, connections to the Bernstein-Sato polynomial, relations to two-variable special polynomials such as Kostka polynomials and Tutte polynomials, and a conjectural relationship with deformations of symplectic resolutions. In the appendix we give a brief recollection of the theory of D-modules on singular varieties that we require.

Poisson traces, D-modules, and symplectic resolutions.

PubMed

Etingof, Pavel; Schedler, Travis

2018-01-01

We survey the theory of Poisson traces (or zeroth Poisson homology) developed by the authors in a series of recent papers. The goal is to understand this subtle invariant of (singular) Poisson varieties, conditions for it to be finite-dimensional, its relationship to the geometry and topology of symplectic resolutions, and its applications to quantizations. The main technique is the study of a canonical D-module on the variety. In the case the variety has finitely many symplectic leaves (such as for symplectic singularities and Hamiltonian reductions of symplectic vector spaces by reductive groups), the D-module is holonomic, and hence, the space of Poisson traces is finite-dimensional. As an application, there are finitely many irreducible finite-dimensional representations of every quantization of the variety. Conjecturally, the D-module is the pushforward of the canonical D-module under every symplectic resolution of singularities, which implies that the space of Poisson traces is dual to the top cohomology of the resolution. We explain many examples where the conjecture is proved, such as symmetric powers of du Val singularities and symplectic surfaces and Slodowy slices in the nilpotent cone of a semisimple Lie algebra. We compute the D-module in the case of surfaces with isolated singularities and show it is not always semisimple. We also explain generalizations to arbitrary Lie algebras of vector fields, connections to the Bernstein-Sato polynomial, relations to two-variable special polynomials such as Kostka polynomials and Tutte polynomials, and a conjectural relationship with deformations of symplectic resolutions. In the appendix we give a brief recollection of the theory of D-modules on singular varieties that we require.

Vector critical points and generalized quasi-efficient solutions in nonsmooth multi-objective programming.

PubMed

Wang, Zhen; Li, Ru; Yu, Guolin

2017-01-01

In this work, several extended approximately invex vector-valued functions of higher order involving a generalized Jacobian are introduced, and some examples are presented to illustrate their existences. The notions of higher-order (weak) quasi-efficiency with respect to a function are proposed for a multi-objective programming. Under the introduced generalization of higher-order approximate invexities assumptions, we prove that the solutions of generalized vector variational-like inequalities in terms of the generalized Jacobian are the generalized quasi-efficient solutions of nonsmooth multi-objective programming problems. Moreover, the equivalent conditions are presented, namely, a vector critical point is a weakly quasi-efficient solution of higher order with respect to a function.

Toward semantic-based retrieval of visual information: a model-based approach

NASA Astrophysics Data System (ADS)

Park, Youngchoon; Golshani, Forouzan; Panchanathan, Sethuraman

2002-07-01

This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.

Vaccine strategies against Babesia bovis based on prime-boost immunizations in mice with modified vaccinia Ankara vector and recombinant proteins.

PubMed

Jaramillo Ortiz, José Manuel; Del Médico Zajac, María Paula; Zanetti, Flavia Adriana; Molinari, María Paula; Gravisaco, María José; Calamante, Gabriela; Wilkowsky, Silvina Elizabeth

2014-08-06

In this study, a recombinant modified vaccinia virus Ankara vector expressing a chimeric multi-antigen was obtained and evaluated as a candidate vaccine in homologous and heterologous prime-boost immunizations with a recombinant protein cocktail. The chimeric multi-antigen comprises immunodominant B and T cell regions of three Babesia bovis proteins. Humoral and cellular immune responses were evaluated in mice to compare the immunogenicity induced by different immunization schemes. The best vaccination scheme was achieved with a prime of protein cocktail and a boost with the recombinant virus. This scheme induced high level of specific IgG antibodies and secreted IFN and a high degree of activation of IFNγ(+) CD4(+) and CD8(+) specific T cells. This is the first report in which a novel vaccine candidate was constructed based on a rationally designed multi-antigen and evaluated in a prime-boost regime, optimizing the immune response necessary for protection against bovine babesiosis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Three-Level De-Multiplexed Dual-Branch Complex Delta-Sigma Transmitter.

PubMed

Arfi, Anis Ben; Elsayed, Fahmi; Aflaki, Pouya M; Morris, Brad; Ghannouchi, Fadhel M

2018-02-20

In this paper, a dual-branch topology driven by a Delta-Sigma Modulator (DSM) with a complex quantizer, also known as the Complex Delta Sigma Modulator (CxDSM), with a 3-level quantized output signal is proposed. By de-multiplexing the 3-level Delta-Sigma-quantized signal into two bi-level streams, an efficiency enhancement over the operational frequency range is achieved. The de-multiplexed signals drive a dual-branch amplification block composed of two switch-mode back-to-back power amplifiers working at peak power. A signal processing technique known as quantization noise reduction with In-band Filtering (QNRIF) is applied to each of the de-multiplexed streams to boost the overall performances; particularly the Adjacent Channel Leakage Ratio (ACLR). After amplification, the two branches are combined using a non-isolated combiner, preserving the efficiency of the transmitter. A comprehensive study on the operation of this topology and signal characteristics used to drive the dual-branch Switch-Mode Power Amplifiers (SMPAs) was established. Moreover, this work proposes a highly efficient design of the amplification block based on a back-to-back power topology performing a dynamic load modulation exploiting the non-overlapping properties of the de-multiplexed Complex DSM signal. For experimental validation, the proposed de-multiplexed 3-level Delta-Sigma topology was implemented on the BEEcube™ platform followed by the back-to-back Class-E switch-mode power amplification block. The full transceiver is assessed using a 4th-Generation mobile communications standard LTE (Long Term Evolution) standard 1.4 MHz signal with a peak to average power ratio (PAPR) of 8 dB. The dual-branch topology exhibited a good linearity and a coding efficiency of the transmitter chain higher than 72% across the band of frequency from 1.8 GHz to 2.7 GHz.

Face biometrics with renewable templates

NASA Astrophysics Data System (ADS)

van der Veen, Michiel; Kevenaar, Tom; Schrijen, Geert-Jan; Akkermans, Ton H.; Zuo, Fei

2006-02-01

In recent literature, privacy protection technologies for biometric templates were proposed. Among these is the so-called helper-data system (HDS) based on reliable component selection. In this paper we integrate this approach with face biometrics such that we achieve a system in which the templates are privacy protected, and multiple templates can be derived from the same facial image for the purpose of template renewability. Extracting binary feature vectors forms an essential step in this process. Using the FERET and Caltech databases, we show that this quantization step does not significantly degrade the classification performance compared to, for example, traditional correlation-based classifiers. The binary feature vectors are integrated in the HDS leading to a privacy protected facial recognition algorithm with acceptable FAR and FRR, provided that the intra-class variation is sufficiently small. This suggests that a controlled enrollment procedure with a sufficient number of enrollment measurements is required.

Detecting double compression of audio signal

NASA Astrophysics Data System (ADS)

Yang, Rui; Shi, Yun Q.; Huang, Jiwu

2010-01-01

MP3 is the most popular audio format nowadays in our daily life, for example music downloaded from the Internet and file saved in the digital recorder are often in MP3 format. However, low bitrate MP3s are often transcoded to high bitrate since high bitrate ones are of high commercial value. Also audio recording in digital recorder can be doctored easily by pervasive audio editing software. This paper presents two methods for the detection of double MP3 compression. The methods are essential for finding out fake-quality MP3 and audio forensics. The proposed methods use support vector machine classifiers with feature vectors formed by the distributions of the first digits of the quantized MDCT (modified discrete cosine transform) coefficients. Extensive experiments demonstrate the effectiveness of the proposed methods. To the best of our knowledge, this piece of work is the first one to detect double compression of audio signal.

Information preserving coding for multispectral data

NASA Technical Reports Server (NTRS)

Duan, J. R.; Wintz, P. A.

1973-01-01

A general formulation of the data compression system is presented. A method of instantaneous expansion of quantization levels by reserving two codewords in the codebook to perform a folding over in quantization is implemented for error free coding of data with incomplete knowledge of the probability density function. Results for simple DPCM with folding and an adaptive transform coding technique followed by a DPCM technique are compared using ERTS-1 data.

Three learning phases for radial-basis-function networks.

PubMed

Schwenker, F; Kestler, H A; Palm, G

2001-05-01

In this paper, learning algorithms for radial basis function (RBF) networks are discussed. Whereas multilayer perceptrons (MLP) are typically trained with backpropagation algorithms, starting the training procedure with a random initialization of the MLP's parameters, an RBF network may be trained in many different ways. We categorize these RBF training methods into one-, two-, and three-phase learning schemes. Two-phase RBF learning is a very common learning scheme. The two layers of an RBF network are learnt separately; first the RBF layer is trained, including the adaptation of centers and scaling parameters, and then the weights of the output layer are adapted. RBF centers may be trained by clustering, vector quantization and classification tree algorithms, and the output layer by supervised learning (through gradient descent or pseudo inverse solution). Results from numerical experiments of RBF classifiers trained by two-phase learning are presented in three completely different pattern recognition applications: (a) the classification of 3D visual objects; (b) the recognition hand-written digits (2D objects); and (c) the categorization of high-resolution electrocardiograms given as a time series (ID objects) and as a set of features extracted from these time series. In these applications, it can be observed that the performance of RBF classifiers trained with two-phase learning can be improved through a third backpropagation-like training phase of the RBF network, adapting the whole set of parameters (RBF centers, scaling parameters, and output layer weights) simultaneously. This, we call three-phase learning in RBF networks. A practical advantage of two- and three-phase learning in RBF networks is the possibility to use unlabeled training data for the first training phase. Support vector (SV) learning in RBF networks is a different learning approach. SV learning can be considered, in this context of learning, as a special type of one-phase learning, where only the output layer weights of the RBF network are calculated, and the RBF centers are restricted to be a subset of the training data. Numerical experiments with several classifier schemes including k-nearest-neighbor, learning vector quantization and RBF classifiers trained through two-phase, three-phase and support vector learning are given. The performance of the RBF classifiers trained through SV learning and three-phase learning are superior to the results of two-phase learning, but SV learning often leads to complex network structures, since the number of support vectors is not a small fraction of the total number of data points.

On a canonical quantization of 3D Anti de Sitter pure gravity

NASA Astrophysics Data System (ADS)

Kim, Jihun; Porrati, Massimo

2015-10-01

We perform a canonical quantization of pure gravity on AdS 3 using as a technical tool its equivalence at the classical level with a Chern-Simons theory with gauge group SL(2,{R})× SL(2,{R}) . We first quantize the theory canonically on an asymptotically AdS space -which is topologically the real line times a Riemann surface with one connected boundary. Using the "constrain first" approach we reduce canonical quantization to quantization of orbits of the Virasoro group and Kähler quantization of Teichmüller space. After explicitly computing the Kähler form for the torus with one boundary component and after extending that result to higher genus, we recover known results, such as that wave functions of SL(2,{R}) Chern-Simons theory are conformal blocks. We find new restrictions on the Hilbert space of pure gravity by imposing invariance under large diffeomorphisms and normalizability of the wave function. The Hilbert space of pure gravity is shown to be the target space of Conformal Field Theories with continuous spectrum and a lower bound on operator dimensions. A projection defined by topology changing amplitudes in Euclidean gravity is proposed. It defines an invariant subspace that allows for a dual interpretation in terms of a Liouville CFT. Problems and features of the CFT dual are assessed and a new definition of the Hilbert space, exempt from those problems, is proposed in the case of highly-curved AdS 3.

Multi-view L2-SVM and its multi-view core vector machine.

PubMed

Huang, Chengquan; Chung, Fu-lai; Wang, Shitong

2016-03-01

In this paper, a novel L2-SVM based classifier Multi-view L2-SVM is proposed to address multi-view classification tasks. The proposed Multi-view L2-SVM classifier does not have any bias in its objective function and hence has the flexibility like μ-SVC in the sense that the number of the yielded support vectors can be controlled by a pre-specified parameter. The proposed Multi-view L2-SVM classifier can make full use of the coherence and the difference of different views through imposing the consensus among multiple views to improve the overall classification performance. Besides, based on the generalized core vector machine GCVM, the proposed Multi-view L2-SVM classifier is extended into its GCVM version MvCVM which can realize its fast training on large scale multi-view datasets, with its asymptotic linear time complexity with the sample size and its space complexity independent of the sample size. Our experimental results demonstrated the effectiveness of the proposed Multi-view L2-SVM classifier for small scale multi-view datasets and the proposed MvCVM classifier for large scale multi-view datasets. Copyright © 2015 Elsevier Ltd. All rights reserved.

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Multi-Baker Map as a Model of Digital PD Control

NASA Astrophysics Data System (ADS)

Csernák, Gábor; Gyebrószki, Gergely; Stépán, Gábor

Digital stabilization of unstable equilibria of linear systems may lead to small amplitude stochastic-like oscillations. We show that these vibrations can be related to a deterministic chaotic dynamics induced by sampling and quantization. A detailed analytical proof of chaos is presented for the case of a PD controlled oscillator: it is shown that there exists a finite attracting domain in the phase-space, the largest Lyapunov exponent is positive and the existence of a Smale horseshoe is also pointed out. The corresponding two-dimensional micro-chaos map is a multi-baker map, i.e. it consists of a finite series of baker’s maps.

The Population Inversion and the Entropy of a Moving Two-Level Atom in Interaction with a Quantized Field

NASA Astrophysics Data System (ADS)

Abo-Kahla, D. A. M.; Abdel-Aty, M.; Farouk, A.

2018-05-01

An atom with only two energy eigenvalues is described by a two-dimensional state space spanned by the two energy eigenstates is called a two-level atom. We consider the interaction between a two-level atom system with a constant velocity. An analytic solution of the systems which interacts with a quantized field is provided. Furthermore, the significant effect of the temperature on the atomic inversion, the purity and the information entropy are discussed in case of the initial state either an exited state or a maximally mixed state. Additionally, the effect of the half wavelengths number of the field-mode is investigated.

Bit Grooming: Statistically accurate precision-preserving quantization with compression, evaluated in the netCDF operators (NCO, v4.4.8+)

DOE PAGES

Zender, Charles S.

2016-09-19

Geoscientific models and measurements generate false precision (scientifically meaningless data bits) that wastes storage space. False precision can mislead (by implying noise is signal) and be scientifically pointless, especially for measurements. By contrast, lossy compression can be both economical (save space) and heuristic (clarify data limitations) without compromising the scientific integrity of data. Data quantization can thus be appropriate regardless of whether space limitations are a concern. We introduce, implement, and characterize a new lossy compression scheme suitable for IEEE floating-point data. Our new Bit Grooming algorithm alternately shaves (to zero) and sets (to one) the least significant bits ofmore » consecutive values to preserve a desired precision. This is a symmetric, two-sided variant of an algorithm sometimes called Bit Shaving that quantizes values solely by zeroing bits. Our variation eliminates the artificial low bias produced by always zeroing bits, and makes Bit Grooming more suitable for arrays and multi-dimensional fields whose mean statistics are important. Bit Grooming relies on standard lossless compression to achieve the actual reduction in storage space, so we tested Bit Grooming by applying the DEFLATE compression algorithm to bit-groomed and full-precision climate data stored in netCDF3, netCDF4, HDF4, and HDF5 formats. Bit Grooming reduces the storage space required by initially uncompressed and compressed climate data by 25–80 and 5–65 %, respectively, for single-precision values (the most common case for climate data) quantized to retain 1–5 decimal digits of precision. The potential reduction is greater for double-precision datasets. When used aggressively (i.e., preserving only 1–2 digits), Bit Grooming produces storage reductions comparable to other quantization techniques such as Linear Packing. Unlike Linear Packing, whose guaranteed precision rapidly degrades within the relatively narrow dynamic range of values that it can compress, Bit Grooming guarantees the specified precision throughout the full floating-point range. Data quantization by Bit Grooming is irreversible (i.e., lossy) yet transparent, meaning that no extra processing is required by data users/readers. Hence Bit Grooming can easily reduce data storage volume without sacrificing scientific precision or imposing extra burdens on users.« less

A CMOS Imager with Focal Plane Compression using Predictive Coding

NASA Technical Reports Server (NTRS)

Leon-Salas, Walter D.; Balkir, Sina; Sayood, Khalid; Schemm, Nathan; Hoffman, Michael W.

2007-01-01

This paper presents a CMOS image sensor with focal-plane compression. The design has a column-level architecture and it is based on predictive coding techniques for image decorrelation. The prediction operations are performed in the analog domain to avoid quantization noise and to decrease the area complexity of the circuit, The prediction residuals are quantized and encoded by a joint quantizer/coder circuit. To save area resources, the joint quantizerlcoder circuit exploits common circuitry between a single-slope analog-to-digital converter (ADC) and a Golomb-Rice entropy coder. This combination of ADC and encoder allows the integration of the entropy coder at the column level. A prototype chip was fabricated in a 0.35 pm CMOS process. The output of the chip is a compressed bit stream. The test chip occupies a silicon area of 2.60 mm x 5.96 mm which includes an 80 X 44 APS array. Tests of the fabricated chip demonstrate the validity of the design.

Quantum self-gravitating collapsing matter in a quantum geometry

NASA Astrophysics Data System (ADS)

Campiglia, Miguel; Gambini, Rodolfo; Olmedo, Javier; Pullin, Jorge

2016-09-01

The problem of how space-time responds to gravitating quantum matter in full quantum gravity has been one of the main questions that any program of quantization of gravity should address. Here we analyze this issue by considering the quantization of a collapsing null shell coupled to spherically symmetric loop quantum gravity. We show that the constraint algebra of canonical gravity is Abelian both classically and when quantized using loop quantum gravity techniques. The Hamiltonian constraint is well defined and suitable Dirac observables characterizing the problem were identified at the quantum level. We can write the metric as a parameterized Dirac observable at the quantum level and study the physics of the collapsing shell and black hole formation. We show how the singularity inside the black hole is eliminated by loop quantum gravity and how the shell can traverse it. The construction is compatible with a scenario in which the shell tunnels into a baby universe inside the black hole or one in which it could emerge through a white hole.

Group theoretical quantization of isotropic loop cosmology

NASA Astrophysics Data System (ADS)

Livine, Etera R.; Martín-Benito, Mercedes

2012-06-01

We achieve a group theoretical quantization of the flat Friedmann-Robertson-Walker model coupled to a massless scalar field adopting the improved dynamics of loop quantum cosmology. Deparemetrizing the system using the scalar field as internal time, we first identify a complete set of phase space observables whose Poisson algebra is isomorphic to the su(1,1) Lie algebra. It is generated by the volume observable and the Hamiltonian. These observables describe faithfully the regularized phase space underlying the loop quantization: they account for the polymerization of the variable conjugate to the volume and for the existence of a kinematical nonvanishing minimum volume. Since the Hamiltonian is an element in the su(1,1) Lie algebra, the dynamics is now implemented as SU(1, 1) transformations. At the quantum level, the system is quantized as a timelike irreducible representation of the group SU(1, 1). These representations are labeled by a half-integer spin, which gives the minimal volume. They provide superselection sectors without quantization anomalies and no factor ordering ambiguity arises when representing the Hamiltonian. We then explicitly construct SU(1, 1) coherent states to study the quantum evolution. They not only provide semiclassical states but truly dynamical coherent states. Their use further clarifies the nature of the bounce that resolves the big bang singularity.

Mixed Linear/Square-Root Encoded Single-Slope Ramp Provides Low-Noise ADC with High Linearity for Focal Plane Arrays

NASA Technical Reports Server (NTRS)

Wrigley, Chris J.; Hancock, Bruce R.; Newton, Kenneth W.; Cunningham, Thomas J.

2013-01-01

Single-slope analog-to-digital converters (ADCs) are particularly useful for onchip digitization in focal plane arrays (FPAs) because of their inherent monotonicity, relative simplicity, and efficiency for column-parallel applications, but they are comparatively slow. Squareroot encoding can allow the number of code values to be reduced without loss of signal-to-noise ratio (SNR) by keeping the quantization noise just below the signal shot noise. This encoding can be implemented directly by using a quadratic ramp. The reduction in the number of code values can substantially increase the quantization speed. However, in an FPA, the fixed pattern noise (FPN) limits the use of small quantization steps at low signal levels. If the zero-point is adjusted so that the lowest column is onscale, the other columns, including those at the center of the distribution, will be pushed up the ramp where the quantization noise is higher. Additionally, the finite frequency response of the ramp buffer amplifier and the comparator distort the shape of the ramp, so that the effective ramp value at the time the comparator trips differs from the intended value, resulting in errors. Allowing increased settling time decreases the quantization speed, while increasing the bandwidth increases the noise. The FPN problem is solved by breaking the ramp into two portions, with some fraction of the available code values allocated to a linear ramp and the remainder to a quadratic ramp. To avoid large transients, both the value and the slope of the linear and quadratic portions should be equal where they join. The span of the linear portion must cover the minimum offset, but not necessarily the maximum, since the fraction of the pixels above the upper limit will still be correctly quantized, albeit with increased quantization noise. The required linear span, maximum signal and ratio of quantization noise to shot noise at high signal, along with the continuity requirement, determines the number of code values that must be allocated to each portion. The distortion problem is solved by using a lookup table to convert captured code values back to signal levels. The values in this table will be similar to the intended ramp value, but with a correction for the finite bandwidth effects. Continuous-time comparators are used, and their bandwidth is set below the step rate, which smoothes the ramp and reduces the noise. No settling time is needed, as would be the case for clocked comparators, but the low bandwidth enhances the distortion of the non-linear portion. This is corrected by use of a return lookup table, which differs from the one used to generate the ramp. The return lookup table is obtained by calibrating against a stepped precision DC reference. This results in a residual non-linearity well below the quantization noise. This method can also compensate for differential non-linearity (DNL) in the DAC used to generate the ramp. The use of a ramp with a combination of linear and quadratic portions for a single-slope ADC is novel. The number of steps is minimized by keeping the step size just below the photon shot noise. This in turn maximizes the speed of the conversion. High resolution is maintained by keeping small quantization steps at low signals, and noise is minimized by allowing the lowest analog bandwidth, all without increasing the quantization noise. A calibrated return lookup table allows the system to maintain excellent linearity.

Memory-efficient decoding of LDPC codes

NASA Technical Reports Server (NTRS)

Kwok-San Lee, Jason; Thorpe, Jeremy; Hawkins, Jon

2005-01-01

We present a low-complexity quantization scheme for the implementation of regular (3,6) LDPC codes. The quantization parameters are optimized to maximize the mutual information between the source and the quantized messages. Using this non-uniform quantized belief propagation algorithm, we have simulated that an optimized 3-bit quantizer operates with 0.2dB implementation loss relative to a floating point decoder, and an optimized 4-bit quantizer operates less than 0.1dB quantization loss.

Improved optical flow motion estimation for digital image stabilization

NASA Astrophysics Data System (ADS)

Lai, Lijun; Xu, Zhiyong; Zhang, Xuyao

2015-11-01

Optical flow is the instantaneous motion vector at each pixel in the image frame at a time instant. The gradient-based approach for optical flow computation can't work well when the video motion is too large. To alleviate such problem, we incorporate this algorithm into a pyramid multi-resolution coarse-to-fine search strategy. Using pyramid strategy to obtain multi-resolution images; Using iterative relationship from the highest level to the lowest level to obtain inter-frames' affine parameters; Subsequence frames compensate back to the first frame to obtain stabilized sequence. The experiment results demonstrate that the promoted method has good performance in global motion estimation.

A CU-Level Rate and Distortion Estimation Scheme for RDO of Hardware-Friendly HEVC Encoders Using Low-Complexity Integer DCTs.

PubMed

Lee, Bumshik; Kim, Munchurl

2016-08-01

In this paper, a low complexity coding unit (CU)-level rate and distortion estimation scheme is proposed for High Efficiency Video Coding (HEVC) hardware-friendly implementation where a Walsh-Hadamard transform (WHT)-based low-complexity integer discrete cosine transform (DCT) is employed for distortion estimation. Since HEVC adopts quadtree structures of coding blocks with hierarchical coding depths, it becomes more difficult to estimate accurate rate and distortion values without actually performing transform, quantization, inverse transform, de-quantization, and entropy coding. Furthermore, DCT for rate-distortion optimization (RDO) is computationally high, because it requires a number of multiplication and addition operations for various transform block sizes of 4-, 8-, 16-, and 32-orders and requires recursive computations to decide the optimal depths of CU or transform unit. Therefore, full RDO-based encoding is highly complex, especially for low-power implementation of HEVC encoders. In this paper, a rate and distortion estimation scheme is proposed in CU levels based on a low-complexity integer DCT that can be computed in terms of WHT whose coefficients are produced in prediction stages. For rate and distortion estimation in CU levels, two orthogonal matrices of 4×4 and 8×8 , which are applied to WHT that are newly designed in a butterfly structure only with addition and shift operations. By applying the integer DCT based on the WHT and newly designed transforms in each CU block, the texture rate can precisely be estimated after quantization using the number of non-zero quantized coefficients and the distortion can also be precisely estimated in transform domain without de-quantization and inverse transform required. In addition, a non-texture rate estimation is proposed by using a pseudoentropy code to obtain accurate total rate estimates. The proposed rate and the distortion estimation scheme can effectively be used for HW-friendly implementation of HEVC encoders with 9.8% loss over HEVC full RDO, which much less than 20.3% and 30.2% loss of a conventional approach and Hadamard-only scheme, respectively.

Secure coherent optical multi-carrier system with four-dimensional modulation space and Stokes vector scrambling.

PubMed

Zhang, Lijia; Liu, Bo; Xin, Xiangjun

2015-06-15

A secure enhanced coherent optical multi-carrier system based on Stokes vector scrambling is proposed and experimentally demonstrated. The optical signal with four-dimensional (4D) modulation space has been scrambled intra- and inter-subcarriers, where a multi-layer logistic map is adopted as the chaotic model. An experiment with 61.71-Gb/s encrypted multi-carrier signal is successfully demonstrated with the proposed method. The results indicate a promising solution for the physical secure optical communication.

MISR 17.6 KM Gridded Cloud Motion Vectors: Overview and Assessment

NASA Technical Reports Server (NTRS)

Mueller, Kevin; Garay, Michael; Moroney, Catherine; Jovanovic, Veljko

2012-01-01

The MISR (Multi-angle Imaging SpectroRadiometer) instrument on the Terra satellite has been retrieving cloud motion vectors (CMVs) globally and almost continuously since early in 2000. In February 2012 the new MISR Level 2 Cloud product was publicly released, providing cloud motion vectors at 17.6 km resolution with improved accuracy and roughly threefold increased coverage relative to the 70.4 km resolution vectors of the current MISR Level 2 Stereo product (which remains available). MISR retrieves both horizontal cloud motion and height from the apparent displacement due to parallax and movement of cloud features across three visible channel (670nm) camera views over a span of 200 seconds. The retrieval has comparable accuracy to operational atmospheric motion vectors from other current sensors, but holds the additional advantage of global coverage and finer precision height retrieval that is insensitive to radiometric calibration. The MISR mission is expected to continue operation for many more years, possibly until 2019, and Level 2 Cloud has the possibility of being produced with a sensing-to-availability lag of 5 hours. This report compares MISR CMV with collocated motion vectors from arctic rawinsonde sites, and from the GOES and MODISTerra instruments. CMV at heights below 3 km exhibit the smallest differences, as small as 3.3 m/s for MISR and GOES. Clouds above 3 km exhibit larger differences, as large as 8.9 m/s for MISR and MODIS. Typical differences are on the order of 6 m/s.

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

2017-07-01

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

Design and Implementation of Multi-Input Adaptive Signal Extractions.

DTIC Science & Technology

1982-09-01

deflected gradient) algorithm requiring only N+ l multiplications per adaptation step. Additional quantization is introduced to eliminate all multiplications...noise cancellation for intermittent-signal applications," IEEE Trans. Information Theory, Vol. IT-26. Nov. 1980, pp. 746-750. 1-2 J. Kazakoff and W. A...cancellation," Proc. IEEE, July 1981, Vol. 69, pp. 846-847. *I-10 P. L . Kelly and W. A. Gardner, "Pilot-Directed Adaptive Signal Extraction," Dept. of

G14A-06- Analysis of the DORIS, GNSS, SLR, VLBI and Gravimetric Time Series at the GGOS Core Sites

NASA Technical Reports Server (NTRS)

Moreaux, G.; Lemoine, F.; Luceri, V.; Pavlis, E.; MacMillan, D.; Bonvalot, S.; Saunier, J.

2017-01-01

Analysis of the time series at the 3-4 multi-technique GGOS sites to analyze and compare the spectral content of the space geodetic and gravity time series. Evaluate the level of agreement between the space geodesy measurements and the physical tie vectors.

Optical memory based on quantized atomic center-of-mass motion.

PubMed

Lopez, J P; de Almeida, A J F; Felinto, D; Tabosa, J W R

2017-11-01

We report a new type of optical memory using a pure two-level system of cesium atoms cooled by the magnetically assisted Sisyphus effect. The optical information of a probe field is stored in the coherence between quantized vibrational levels of the atoms in the potential wells of a 1-D optical lattice. The retrieved pulse shows Rabi oscillations with a frequency determined by the reading beam intensity and are qualitatively understood in terms of a simple theoretical model. The exploration of the external degrees of freedom of an atom may add another capability in the design of quantum-information protocols using light.

A simple method for evaluating the wavefront compensation error of diffractive liquid-crystal wavefront correctors.

PubMed

Cao, Zhaoliang; Mu, Quanquan; Hu, Lifa; Lu, Xinghai; Xuan, Li

2009-09-28

A simple method for evaluating the wavefront compensation error of diffractive liquid-crystal wavefront correctors (DLCWFCs) for atmospheric turbulence correction is reported. A simple formula which describes the relationship between pixel number, DLCWFC aperture, quantization level, and atmospheric coherence length was derived based on the calculated atmospheric turbulence wavefronts using Kolmogorov atmospheric turbulence theory. It was found that the pixel number across the DLCWFC aperture is a linear function of the telescope aperture and the quantization level, and it is an exponential function of the atmosphere coherence length. These results are useful for people using DLCWFCs in atmospheric turbulence correction for large-aperture telescopes.

Security Enhancement of Wireless Sensor Networks Using Signal Intervals

PubMed Central

Moon, Jaegeun; Jung, Im Y.; Yoo, Jaesoo

2017-01-01

Various wireless technologies, such as RF, Bluetooth, and Zigbee, have been applied to sensor communications. However, the applications of Bluetooth-based wireless sensor networks (WSN) have a security issue. In one pairing process during Bluetooth communication, which is known as simple secure pairing (SSP), the devices are required to specify I/O capability or user interference to prevent man-in-the-middle (MITM) attacks. This study proposes an enhanced SSP in which a nonce to be transferred is converted to a corresponding signal interval. The quantization level, which is used to interpret physical signal intervals, is renewed at every connection by the transferred nonce and applied to the next nonce exchange so that the same signal intervals can represent different numbers. Even if attackers eavesdrop on the signals, they cannot understand what is being transferred because they cannot determine the quantization level. Furthermore, the proposed model does not require exchanging passkeys as data, and the devices are secure in the case of using a fixed PIN. Subsequently, the new quantization level is calculated automatically whenever the same devices attempt to connect with each other. Therefore, the pairing process can be protected from MITM attacks and be convenient for users. PMID:28368341

Security Enhancement of Wireless Sensor Networks Using Signal Intervals.

PubMed

Moon, Jaegeun; Jung, Im Y; Yoo, Jaesoo

2017-04-02

Various wireless technologies, such as RF, Bluetooth, and Zigbee, have been applied to sensor communications. However, the applications of Bluetooth-based wireless sensor networks (WSN) have a security issue. In one pairing process during Bluetooth communication, which is known as simple secure pairing (SSP), the devices are required to specify I/O capability or user interference to prevent man-in-the-middle (MITM) attacks. This study proposes an enhanced SSP in which a nonce to be transferred is converted to a corresponding signal interval. The quantization level, which is used to interpret physical signal intervals, is renewed at every connection by the transferred nonce and applied to the next nonce exchange so that the same signal intervals can represent different numbers. Even if attackers eavesdrop on the signals, they cannot understand what is being transferred because they cannot determine the quantization level. Furthermore, the proposed model does not require exchanging passkeys as data, and the devices are secure in the case of using a fixed PIN. Subsequently, the new quantization level is calculated automatically whenever the same devices attempt to connect with each other. Therefore, the pairing process can be protected from MITM attacks and be convenient for users.

An Alternative to the Gauge Theoretic Setting

NASA Astrophysics Data System (ADS)

Schroer, Bert

2011-10-01

The standard formulation of quantum gauge theories results from the Lagrangian (functional integral) quantization of classical gauge theories. A more intrinsic quantum theoretical access in the spirit of Wigner's representation theory shows that there is a fundamental clash between the pointlike localization of zero mass (vector, tensor) potentials and the Hilbert space (positivity, unitarity) structure of QT. The quantization approach has no other way than to stay with pointlike localization and sacrifice the Hilbert space whereas the approach built on the intrinsic quantum concept of modular localization keeps the Hilbert space and trades the conflict creating pointlike generation with the tightest consistent localization: semiinfinite spacelike string localization. Whereas these potentials in the presence of interactions stay quite close to associated pointlike field strengths, the interacting matter fields to which they are coupled bear the brunt of the nonlocal aspect in that they are string-generated in a way which cannot be undone by any differentiation. The new stringlike approach to gauge theory also revives the idea of a Schwinger-Higgs screening mechanism as a deeper and less metaphoric description of the Higgs spontaneous symmetry breaking and its accompanying tale about "God's particle" and its mass generation for all the other particles.

Optimized universal color palette design for error diffusion

NASA Astrophysics Data System (ADS)

Kolpatzik, Bernd W.; Bouman, Charles A.

1995-04-01

Currently, many low-cost computers can only simultaneously display a palette of 256 color. However, this palette is usually selectable from a very large gamut of available colors. For many applications, this limited palette size imposes a significant constraint on the achievable image quality. We propose a method for designing an optimized universal color palette for use with halftoning methods such as error diffusion. The advantage of a universal color palette is that it is fixed and therefore allows multiple images to be displayed simultaneously. To design the palette, we employ a new vector quantization method known as sequential scalar quantization (SSQ) to allocate the colors in a visually uniform color space. The SSQ method achieves near-optimal allocation, but may be efficiently implemented using a series of lookup tables. When used with error diffusion, SSQ adds little computational overhead and may be used to minimize the visual error in an opponent color coordinate system. We compare the performance of the optimized algorithm to standard error diffusion by evaluating a visually weighted mean-squared-error measure. Our metric is based on the color difference in CIE L*AL*B*, but also accounts for the lowpass characteristic of human contrast sensitivity.

Development of a good-quality speech coder for transmission over noisy channels at 2.4 kb/s

NASA Astrophysics Data System (ADS)

Viswanathan, V. R.; Berouti, M.; Higgins, A.; Russell, W.

1982-03-01

This report describes the development, study, and experimental results of a 2.4 kb/s speech coder called harmonic deviations (HDV) vocoder, which transmits good-quality speech over noisy channels with bit-error rates of up to 1%. The HDV coder is based on the linear predictive coding (LPC) vocoder, and it transmits additional information over and above the data transmitted by the LPC vocoder, in the form of deviations between the speech spectrum and the LPC all-pole model spectrum at a selected set of frequencies. At the receiver, the spectral deviations are used to generate the excitation signal for the all-pole synthesis filter. The report describes and compares several methods for extracting the spectral deviations from the speech signal and for encoding them. To limit the bit-rate of the HDV coder to 2.4 kb/s the report discusses several methods including orthogonal transformation and minimum-mean-square-error scalar quantization of log area ratios, two-stage vector-scalar quantization, and variable frame rate transmission. The report also presents the results of speech-quality optimization of the HDV coder at 2.4 kb/s.

Metaplectic-c Quantomorphisms

NASA Astrophysics Data System (ADS)

Vaughan, Jennifer

2015-03-01

In the classical Kostant-Souriau prequantization procedure, the Poisson algebra of a symplectic manifold (M,ω) is realized as the space of infinitesimal quantomorphisms of the prequantization circle bundle. Robinson and Rawnsley developed an alternative to the Kostant-Souriau quantization process in which the prequantization circle bundle and metaplectic structure for (M,ω) are replaced by a metaplectic-c prequantization. They proved that metaplectic-c quantization can be applied to a larger class of manifolds than the classical recipe. This paper presents a definition for a metaplectic-c quantomorphism, which is a diffeomorphism of metaplectic-c prequantizations that preserves all of their structures. Since the structure of a metaplectic-c prequantization is more complicated than that of a circle bundle, we find that the definition must include an extra condition that does not have an analogue in the Kostant-Souriau case. We then define an infinitesimal quantomorphism to be a vector field whose flow consists of metaplectic-c quantomorphisms, and prove that the space of infinitesimal metaplectic-c quantomorphisms exhibits all of the same properties that are seen for the infinitesimal quantomorphisms of a prequantization circle bundle. In particular, this space is isomorphic to the Poisson algebra C^∞(M).

An adaptive evolutionary multi-objective approach based on simulated annealing.

PubMed

Li, H; Landa-Silva, D

2011-01-01

A multi-objective optimization problem can be solved by decomposing it into one or more single objective subproblems in some multi-objective metaheuristic algorithms. Each subproblem corresponds to one weighted aggregation function. For example, MOEA/D is an evolutionary multi-objective optimization (EMO) algorithm that attempts to optimize multiple subproblems simultaneously by evolving a population of solutions. However, the performance of MOEA/D highly depends on the initial setting and diversity of the weight vectors. In this paper, we present an improved version of MOEA/D, called EMOSA, which incorporates an advanced local search technique (simulated annealing) and adapts the search directions (weight vectors) corresponding to various subproblems. In EMOSA, the weight vector of each subproblem is adaptively modified at the lowest temperature in order to diversify the search toward the unexplored parts of the Pareto-optimal front. Our computational results show that EMOSA outperforms six other well established multi-objective metaheuristic algorithms on both the (constrained) multi-objective knapsack problem and the (unconstrained) multi-objective traveling salesman problem. Moreover, the effects of the main algorithmic components and parameter sensitivities on the search performance of EMOSA are experimentally investigated.

Monopoles for gravitation and for higher spin fields

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

Bunster, Claudio; Portugues, Ruben; Cnockaert, Sandrine

2006-05-15

We consider massless higher spin gauge theories with both electric and magnetic sources, with a special emphasis on the spin two case. We write the equations of motion at the linear level (with conserved external sources) and introduce Dirac strings so as to derive the equations from a variational principle. We then derive a quantization condition that generalizes the familiar Dirac quantization condition, and which involves the conserved charges associated with the asymptotic symmetries for higher spins. Next we discuss briefly how the result extends to the nonlinear theory. This is done in the context of gravitation, where the Taub-NUTmore » solution provides the exact solution of the field equations with both types of sources. We rederive, in analogy with electromagnetism, the quantization condition from the quantization of the angular momentum. We also observe that the Taub-NUT metric is asymptotically flat at spatial infinity in the sense of Regge and Teitelboim (including their parity conditions). It follows, in particular, that one can consistently consider in the variational principle configurations with different electric and magnetic masses.« less

Number-phase entropic squeezing and nonclassical properties of a three-level atom interacting with a two-mode field: intensity-dependent coupling, deformed Kerr medium, and detuning effects

NASA Astrophysics Data System (ADS)

Faghihi, Mohammad Javad; Tavassoly, Mohammad Kazem

2013-11-01

In this paper, we follow our presented model in J. Opt. Soc. Am. B {\\bf 30}, 1109--1117 (2013), in which the interaction between a $\\Lambda$-type three-level atom and a quantized two-mode radiation field in a cavity in the presence of nonlinearities is studied. After giving a brief review on the procedure of obtaining the state vector of the atom-field system, some further interesting and important physical features (which are of particular interest in the quantum optics field of research) of the whole system state, i.e., the number-phase entropic uncertainty relation (based on the two-mode Pegg-Barnett formalism) and some of the nonclassicality signs consist of sub-Poissonian statistics, Cauchy-Schwartz inequality and two kinds of squeezing phenomenon are investigated. During our presentation, the effects of intensity-dependent coupling, deformed Kerr medium and the detuning parameters on the depth and domain of each of the mentioned nonclassical criteria of the considered quantum system are studied, in detail. It is shown that each of the mentioned nonclassicality aspects can be obtained by appropriately choosing the related parameters.

Automated vector selection of SIVQ and parallel computing integration MATLAB™: Innovations supporting large-scale and high-throughput image analysis studies.

PubMed

Cheng, Jerome; Hipp, Jason; Monaco, James; Lucas, David R; Madabhushi, Anant; Balis, Ulysses J

2011-01-01

Spatially invariant vector quantization (SIVQ) is a texture and color-based image matching algorithm that queries the image space through the use of ring vectors. In prior studies, the selection of one or more optimal vectors for a particular feature of interest required a manual process, with the user initially stochastically selecting candidate vectors and subsequently testing them upon other regions of the image to verify the vector's sensitivity and specificity properties (typically by reviewing a resultant heat map). In carrying out the prior efforts, the SIVQ algorithm was noted to exhibit highly scalable computational properties, where each region of analysis can take place independently of others, making a compelling case for the exploration of its deployment on high-throughput computing platforms, with the hypothesis that such an exercise will result in performance gains that scale linearly with increasing processor count. An automated process was developed for the selection of optimal ring vectors to serve as the predicate matching operator in defining histopathological features of interest. Briefly, candidate vectors were generated from every possible coordinate origin within a user-defined vector selection area (VSA) and subsequently compared against user-identified positive and negative "ground truth" regions on the same image. Each vector from the VSA was assessed for its goodness-of-fit to both the positive and negative areas via the use of the receiver operating characteristic (ROC) transfer function, with each assessment resulting in an associated area-under-the-curve (AUC) figure of merit. Use of the above-mentioned automated vector selection process was demonstrated in two cases of use: First, to identify malignant colonic epithelium, and second, to identify soft tissue sarcoma. For both examples, a very satisfactory optimized vector was identified, as defined by the AUC metric. Finally, as an additional effort directed towards attaining high-throughput capability for the SIVQ algorithm, we demonstrated the successful incorporation of it with the MATrix LABoratory (MATLAB™) application interface. The SIVQ algorithm is suitable for automated vector selection settings and high throughput computation.

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.

Mathematics of Quantization and Quantum Fields

NASA Astrophysics Data System (ADS)

Dereziński, Jan; Gérard, Christian

2013-03-01

Preface; 1. Vector spaces; 2. Operators in Hilbert spaces; 3. Tensor algebras; 4. Analysis in L2(Rd); 5. Measures; 6. Algebras; 7. Anti-symmetric calculus; 8. Canonical commutation relations; 9. CCR on Fock spaces; 10. Symplectic invariance of CCR in finite dimensions; 11. Symplectic invariance of the CCR on Fock spaces; 12. Canonical anti-commutation relations; 13. CAR on Fock spaces; 14. Orthogonal invariance of CAR algebras; 15. Clifford relations; 16. Orthogonal invariance of the CAR on Fock spaces; 17. Quasi-free states; 18. Dynamics of quantum fields; 19. Quantum fields on space-time; 20. Diagrammatics; 21. Euclidean approach for bosons; 22. Interacting bosonic fields; Subject index; Symbols index.

Perceptual distortion analysis of color image VQ-based coding

NASA Astrophysics Data System (ADS)

Charrier, Christophe; Knoblauch, Kenneth; Cherifi, Hocine

1997-04-01

It is generally accepted that a RGB color image can be easily encoded by using a gray-scale compression technique on each of the three color planes. Such an approach, however, fails to take into account correlations existing between color planes and perceptual factors. We evaluated several linear and non-linear color spaces, some introduced by the CIE, compressed with the vector quantization technique for minimum perceptual distortion. To study these distortions, we measured contrast and luminance of the video framebuffer, to precisely control color. We then obtained psychophysical judgements to measure how well these methods work to minimize perceptual distortion in a variety of color space.

High Performance Compression of Science Data

NASA Technical Reports Server (NTRS)

Storer, James A.; Carpentieri, Bruno; Cohn, Martin

1994-01-01

Two papers make up the body of this report. One presents a single-pass adaptive vector quantization algorithm that learns a codebook of variable size and shape entries; the authors present experiments on a set of test images showing that with no training or prior knowledge of the data, for a given fidelity, the compression achieved typically equals or exceeds that of the JPEG standard. The second paper addresses motion compensation, one of the most effective techniques used in interframe data compression. A parallel block-matching algorithm for estimating interframe displacement of blocks with minimum error is presented. The algorithm is designed for a simple parallel architecture to process video in real time.

Theoretical nuclear physics

NASA Astrophysics Data System (ADS)

Rost, E.; Shephard, J. R.

1992-08-01

This report discusses the following topics: Exact 1-loop vacuum polarization effects in 1 + 1 dimensional QHD; exact 1-fermion loop contributions in 1 + 1 dimensional solitons; exact scalar 1-loop contributions in 1 + 3 dimensions; exact vacuum calculations in a hyper-spherical basis; relativistic nuclear matter with self-consistent correlation energy; consistent RHA-RPA for finite nuclei; transverse response functions in the (triangle)-resonance region; hadronic matter in a nontopological soliton model; scalar and vector contributions to (bar p)p yields (bar lambda)lambda reaction; 0+ and 2+ strengths in pion double-charge exchange to double giant-dipole resonances; and nucleons in a hybrid sigma model including a quantized pion field.

Participatory Risk Mapping of Malaria Vector Exposure in Northern South America using Environmental and Population Data

PubMed Central

Fuller, D.O.; Troyo, A.; Alimi, T.O.; Beier, J.C.

2014-01-01

Malaria elimination remains a major public health challenge in many tropical regions, including large areas of northern South America. In this study, we present a new high spatial resolution (90 × 90 m) risk map for Colombia and surrounding areas based on environmental and human population data. The map was created through a participatory multi-criteria decision analysis in which expert opinion was solicited to determine key environmental and population risk factors, different fuzzy functions to standardize risk factor inputs, and variable factor weights to combine risk factors in a geographic information system. The new risk map was compared to a map of malaria cases in which cases were aggregated to the municipio (municipality) level. The relationship between mean municipio risk scores and total cases by muncípio showed a weak correlation. However, the relationship between pixel-level risk scores and vector occurrence points for two dominant vector species, Anopheles albimanus and An. darlingi, was significantly different (p < 0.05) from a random point distribution, as was a pooled point distribution for these two vector species and An. nuneztovari. Thus, we conclude that the new risk map derived based on expert opinion provides an accurate spatial representation of risk of potential vector exposure rather than malaria transmission as shown by the pattern of malaria cases, and therefore it may be used to inform public health authorities as to where vector control measures should be prioritized to limit human-vector contact in future malaria outbreaks. PMID:24976656

BRST quantization of cosmological perturbations

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

Armendariz-Picon, Cristian; Şengör, Gizem

2016-11-08

BRST quantization is an elegant and powerful method to quantize theories with local symmetries. In this article we study the Hamiltonian BRST quantization of cosmological perturbations in a universe dominated by a scalar field, along with the closely related quantization method of Dirac. We describe how both formalisms apply to perturbations in a time-dependent background, and how expectation values of gauge-invariant operators can be calculated in the in-in formalism. Our analysis focuses mostly on the free theory. By appropriate canonical transformations we simplify and diagonalize the free Hamiltonian. BRST quantization in derivative gauges allows us to dramatically simplify the structuremore » of the propagators, whereas Dirac quantization, which amounts to quantization in synchronous gauge, dispenses with the need to introduce ghosts and preserves the locality of the gauge-fixed action.« less

Aharonov–Anandan quantum phases and Landau quantization associated with a magnetic quadrupole moment

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

Fonseca, I.C.; Bakke, K., E-mail: kbakke@fisica.ufpb.br

The arising of geometric quantum phases in the wave function of a moving particle possessing a magnetic quadrupole moment is investigated. It is shown that an Aharonov–Anandan quantum phase (Aharonov and Anandan, 1987) can be obtained in the quantum dynamics of a moving particle with a magnetic quadrupole moment. In particular, it is obtained as an analogue of the scalar Aharonov–Bohm effect for a neutral particle (Anandan, 1989). Besides, by confining the quantum particle to a hard-wall confining potential, the dependence of the energy levels on the geometric quantum phase is discussed and, as a consequence, persistent currents can arisemore » from this dependence. Finally, an analogue of the Landau quantization is discussed. -- Highlights: •Scalar Aharonov–Bohm effect for a particle possessing a magnetic quadrupole moment. •Aharonov–Anandan quantum phase for a particle with a magnetic quadrupole moment. •Dependence of the energy levels on the Aharonov–Anandan quantum phase. •Landau quantization associated with a particle possessing a magnetic quadrupole moment.« less

Quantum transport in graphene Hall bars: Effects of side gates

NASA Astrophysics Data System (ADS)

Petrović, M. D.; Peeters, F. M.

2017-05-01

Quantum electron transport in side-gated graphene Hall bars is investigated in the presence of quantizing external magnetic fields. The asymmetric potential of four side-gates distorts the otherwise flat bands of the relativistic Landau levels, and creates new propagating states in the Landau spectrum (i.e. snake states). The existence of these new states leads to an interesting modification of the bend and Hall resistances, with new quantizing plateaus appearing in close proximity of the Landau levels. The electron guiding in this system can be understood by studying the current density profiles of the incoming and outgoing modes. From the fact that guided electrons fully transmit without any backscattering (similarly to edge states), we are able to analytically predict the values of the quantized resistances, and they match the resistance data we obtain with our numerical (tight-binding) method. These insights in the electron guiding will be useful in predicting the resistances for other side-gate configurations, and possibly in other system geometries, as long as there is no backscattering of the guided states.

Deformation of second and third quantization

NASA Astrophysics Data System (ADS)

Faizal, Mir

2015-03-01

In this paper, we will deform the second and third quantized theories by deforming the canonical commutation relations in such a way that they become consistent with the generalized uncertainty principle. Thus, we will first deform the second quantized commutator and obtain a deformed version of the Wheeler-DeWitt equation. Then we will further deform the third quantized theory by deforming the third quantized canonical commutation relation. This way we will obtain a deformed version of the third quantized theory for the multiverse.

Compression of digital images over local area networks. Appendix 1: Item 3. M.S. Thesis

NASA Technical Reports Server (NTRS)

Gorjala, Bhargavi

1991-01-01

Differential Pulse Code Modulation (DPCM) has been used with speech for many years. It has not been as successful for images because of poor edge performance. The only corruption in DPC is quantizer error but this corruption becomes quite large in the region of an edge because of the abrupt changes in the statistics of the signal. We introduce two improved DPCM schemes; Edge correcting DPCM and Edge Preservation Differential Coding. These two coding schemes will detect the edges and take action to correct them. In an Edge Correcting scheme, the quantizer error for an edge is encoded using a recursive quantizer with entropy coding and sent to the receiver as side information. In an Edge Preserving scheme, when the quantizer input falls in the overload region, the quantizer error is encoded and sent to the receiver repeatedly until the quantizer input falls in the inner levels. Therefore these coding schemes increase the bit rate in the region of an edge and require variable rate channels. We implement these two variable rate coding schemes on a token wing network. Timed token protocol supports two classes of messages; asynchronous and synchronous. The synchronous class provides a pre-allocated bandwidth and guaranteed response time. The remaining bandwidth is dynamically allocated to the asynchronous class. The Edge Correcting DPCM is simulated by considering the edge information under the asynchronous class. For the simulation of the Edge Preserving scheme, the amount of information sent each time is fixed, but the length of the packet or the bit rate for that packet is chosen depending on the availability capacity. The performance of the network, and the performance of the image coding algorithms, is studied.

Phase-factor-dependent symmetries and quantum phases in a three-level cavity QED system.

PubMed

Fan, Jingtao; Yu, Lixian; Chen, Gang; Jia, Suotang

2016-05-03

Unlike conventional two-level particles, three-level particles may support some unitary-invariant phase factors when they interact coherently with a single-mode quantized light field. To gain a better understanding of light-matter interaction, it is thus necessary to explore the phase-factor-dependent physics in such a system. In this report, we consider the collective interaction between degenerate V-type three-level particles and a single-mode quantized light field, whose different components are labeled by different phase factors. We mainly establish an important relation between the phase factors and the symmetry or symmetry-broken physics. Specifically, we find that the phase factors affect dramatically the system symmetry. When these symmetries are breaking separately, rich quantum phases emerge. Finally, we propose a possible scheme to experimentally probe the predicted physics of our model. Our work provides a way to explore phase-factor-induced nontrivial physics by introducing additional particle levels.

Multi-centre diagnostic classification of individual structural neuroimaging scans from patients with major depressive disorder.

PubMed

Mwangi, Benson; Ebmeier, Klaus P; Matthews, Keith; Steele, J Douglas

2012-05-01

Quantitative abnormalities of brain structure in patients with major depressive disorder have been reported at a group level for decades. However, these structural differences appear subtle in comparison with conventional radiologically defined abnormalities, with considerable inter-subject variability. Consequently, it has not been possible to readily identify scans from patients with major depressive disorder at an individual level. Recently, machine learning techniques such as relevance vector machines and support vector machines have been applied to predictive classification of individual scans with variable success. Here we describe a novel hybrid method, which combines machine learning with feature selection and characterization, with the latter aimed at maximizing the accuracy of machine learning prediction. The method was tested using a multi-centre dataset of T(1)-weighted 'structural' scans. A total of 62 patients with major depressive disorder and matched controls were recruited from referred secondary care clinical populations in Aberdeen and Edinburgh, UK. The generalization ability and predictive accuracy of the classifiers was tested using data left out of the training process. High prediction accuracy was achieved (~90%). While feature selection was important for maximizing high predictive accuracy with machine learning, feature characterization contributed only a modest improvement to relevance vector machine-based prediction (~5%). Notably, while the only information provided for training the classifiers was T(1)-weighted scans plus a categorical label (major depressive disorder versus controls), both relevance vector machine and support vector machine 'weighting factors' (used for making predictions) correlated strongly with subjective ratings of illness severity. These results indicate that machine learning techniques have the potential to inform clinical practice and research, as they can make accurate predictions about brain scan data from individual subjects. Furthermore, machine learning weighting factors may reflect an objective biomarker of major depressive disorder illness severity, based on abnormalities of brain structure.

Detection of laryngeal function using speech and electroglottographic data.

PubMed

Childers, D G; Bae, K S

1992-01-01

The purpose of this research was to develop quantitative measures for the assessment of laryngeal function using speech and electroglottographic (EGG) data. We developed two procedures for the detection of laryngeal pathology: 1) a spectral distortion measure using pitch synchronous and asynchronous methods with linear predictive coding (LPC) vectors and vector quantization (VQ) and 2) analysis of the EGG signal using time interval and amplitude difference measures. The VQ procedure was conjectured to offer the possibility of circumventing the need to estimate the glottal volume velocity wave-form by inverse filtering techniques. The EGG procedure was to evaluate data that was "nearly" a direct measure of vocal fold vibratory motion and thus was conjectured to offer the potential for providing an excellent assessment of laryngeal function. A threshold based procedure gave 75.9 and 69.0% probability of pathological detection using procedures 1) and 2), respectively, for 29 patients with pathological voices and 52 normal subjects. The false alarm probability was 9.6% for the normal subjects.

Condition monitoring of 3G cellular networks through competitive neural models.

PubMed

Barreto, Guilherme A; Mota, João C M; Souza, Luis G M; Frota, Rewbenio A; Aguayo, Leonardo

2005-09-01

We develop an unsupervised approach to condition monitoring of cellular networks using competitive neural algorithms. Training is carried out with state vectors representing the normal functioning of a simulated CDMA2000 network. Once training is completed, global and local normality profiles (NPs) are built from the distribution of quantization errors of the training state vectors and their components, respectively. The global NP is used to evaluate the overall condition of the cellular system. If abnormal behavior is detected, local NPs are used in a component-wise fashion to find abnormal state variables. Anomaly detection tests are performed via percentile-based confidence intervals computed over the global and local NPs. We compared the performance of four competitive algorithms [winner-take-all (WTA), frequency-sensitive competitive learning (FSCL), self-organizing map (SOM), and neural-gas algorithm (NGA)] and the results suggest that the joint use of global and local NPs is more efficient and more robust than current single-threshold methods.

Meson effective mass in the isospin medium in hard-wall AdS/QCD model

NASA Astrophysics Data System (ADS)

Mamedov, Shahin

2016-02-01

We study a mass splitting of the light vector, axial-vector, and pseudoscalar mesons in the isospin medium in the framework of the hard-wall model. We write an effective mass definition for the interacting gauge fields and scalar field introduced in gauge field theory in the bulk of AdS space-time. Relying on holographic duality we obtain a formula for the effective mass of a boundary meson in terms of derivative operator over the extra bulk coordinate. The effective mass found in this way coincides with the one obtained from finding of poles of the two-point correlation function. In order to avoid introducing distinguished infrared boundaries in the quantization formula for the different mesons from the same isotriplet we introduce extra action terms at this boundary, which reduces distinguished values of this boundary to the same value. Profile function solutions and effective mass expressions were found for the in-medium ρ , a_1, and π mesons.

Quantization selection in the high-throughput H.264/AVC encoder based on the RD

NASA Astrophysics Data System (ADS)

Pastuszak, Grzegorz

2013-10-01

In the hardware video encoder, the quantization is responsible for quality losses. On the other hand, it allows the reduction of bit rates to the target one. If the mode selection is based on the rate-distortion criterion, the quantization can also be adjusted to obtain better compression efficiency. Particularly, the use of Lagrangian function with a given multiplier enables the encoder to select the most suitable quantization step determined by the quantization parameter QP. Moreover, the quantization offset added before discarding the fraction value after quantization can be adjusted. In order to select the best quantization parameter and offset in real time, the HD/SD encoder should be implemented in the hardware. In particular, the hardware architecture should embed the transformation and quantization modules able to process the same residuals many times. In this work, such an architecture is used. Experimental results show what improvements in terms of compression efficiency are achievable for Intra coding.

Multi-resolution extension for transmission of geodata in a mobile context

NASA Astrophysics Data System (ADS)

Follin, Jean-Michel; Bouju, Alain; Bertrand, Frédéric; Boursier, Patrice

2005-03-01

A solution is proposed for the management of multi-resolution vector data in a mobile spatial information visualization system. The client-server architecture and the models of data and transfer of the system are presented first. The aim of this system is to reduce data exchanged between client and server by reusing data already present on the client side. Then, an extension of this system to multi-resolution data is proposed. Our solution is based on the use of increments in a multi-scale database. A database architecture where data sets for different predefined scales are precomputed and stored on the server side is adopted. In this model, each object representing the same real world entities at different levels of detail has to be linked beforehand. Increments correspond to the difference between two datasets with different levels of detail. They are transmitted in order to increase (or decrease) the detail to the client upon request. They include generalization and refinement operators allowing transitions between the different levels. Finally, a framework suited to the transfer of multi-resolution data in a mobile context is presented. This allows reuse of data locally available at different levels of detail and, in this way, reduces the amount of data transferred between client and server.

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.

Multi-color incomplete Cholesky conjugate gradient methods for vector computers

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

Poole, E.L.

1986-01-01

This research is concerned with the solution on vector computers of linear systems of equations. Ax = b, where A is a large, sparse symmetric positive definite matrix with non-zero elements lying only along a few diagonals of the matrix. The system is solved using the incomplete Cholesky conjugate gradient method (ICCG). Multi-color orderings are used of the unknowns in the linear system to obtain p-color matrices for which a no-fill block ICCG method is implemented on the CYBER 205 with O(N/p) length vector operations in both the decomposition of A and, more importantly, in the forward and back solvesmore » necessary at each iteration of the method. (N is the number of unknowns and p is a small constant). A p-colored matrix is a matrix that can be partitioned into a p x p block matrix where the diagonal blocks are diagonal matrices. The matrix is stored by diagonals and matrix multiplication by diagonals is used to carry out the decomposition of A and the forward and back solves. Additionally, if the vectors across adjacent blocks line up, then some of the overhead associated with vector startups can be eliminated in the matrix vector multiplication necessary at each conjugate gradient iteration. Necessary and sufficient conditions are given to determine which multi-color orderings of the unknowns correspond to p-color matrices, and a process is indicated for choosing multi-color orderings.« less

Full Spectrum Conversion Using Traveling Pulse Wave Quantization

DTIC Science & Technology

2017-03-01

Full Spectrum Conversion Using Traveling Pulse Wave Quantization Michael S. Kappes Mikko E. Waltari IQ-Analog Corporation San Diego, California...temporal-domain quantization technique called Traveling Pulse Wave Quantization (TPWQ). Full spectrum conversion is defined as the complete...pulse width measurements that are continuously generated hence the name “traveling” pulse wave quantization. Our TPWQ-based ADC is composed of a

Exact semiclassical expansions for one-dimensional quantum oscillators

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

Delabaere, E.; Dillinger, H.; Pham, F.

1997-12-01

A set of rules is given for dealing with WKB expansions in the one-dimensional analytic case, whereby such expansions are not considered as approximations but as exact encodings of wave functions, thus allowing for analytic continuation with respect to whichever parameters the potential function depends on, with an exact control of small exponential effects. These rules, which include also the case when there are double turning points, are illustrated on various examples, and applied to the study of bound state or resonance spectra. In the case of simple oscillators, it is thus shown that the Rayleigh{endash}Schr{umlt o}dinger series is Borelmore » resummable, yielding the exact energy levels. In the case of the symmetrical anharmonic oscillator, one gets a simple and rigorous justification of the Zinn-Justin quantization condition, and of its solution in terms of {open_quotes}multi-instanton expansions.{close_quotes} {copyright} {ital 1997 American Institute of Physics.}« less

Multi-indexed (q-)Racah polynomials

NASA Astrophysics Data System (ADS)

Odake, Satoru; Sasaki, Ryu

2012-09-01

As the second stage of the project multi-indexed orthogonal polynomials, we present, in the framework of ‘discrete quantum mechanics’ with real shifts in one dimension, the multi-indexed (q-)Racah polynomials. They are obtained from the (q-)Racah polynomials by the multiple application of the discrete analogue of the Darboux transformations or the Crum-Krein-Adler deletion of ‘virtual state’ vectors, in a similar way to the multi-indexed Laguerre and Jacobi polynomials reported earlier. The virtual state vectors are the ‘solutions’ of the matrix Schrödinger equation with negative ‘eigenvalues’, except for one of the two boundary points.

Multi-indexed Meixner and little q-Jacobi (Laguerre) polynomials

NASA Astrophysics Data System (ADS)

Odake, Satoru; Sasaki, Ryu

2017-04-01

As the fourth stage of the project multi-indexed orthogonal polynomials, we present the multi-indexed Meixner and little q-Jacobi (Laguerre) polynomials in the framework of ‘discrete quantum mechanics’ with real shifts defined on the semi-infinite lattice in one dimension. They are obtained, in a similar way to the multi-indexed Laguerre and Jacobi polynomials reported earlier, from the quantum mechanical systems corresponding to the original orthogonal polynomials by multiple application of the discrete analogue of the Darboux transformations or the Crum-Krein-Adler deletion of virtual state vectors. The virtual state vectors are the solutions of the matrix Schrödinger equation on all the lattice points having negative energies and infinite norm. This is in good contrast to the (q-)Racah systems defined on a finite lattice, in which the ‘virtual state’ vectors satisfy the matrix Schrödinger equation except for one of the two boundary points.

Advanced development of atmospheric models. [SEASAT Program support

NASA Technical Reports Server (NTRS)

Kesel, P. G.; Langland, R. A.; Stephens, P. L.; Welleck, R. E.; Wolff, P. M.

1979-01-01

A set of atmospheric analysis and prediction models was developed in support of the SEASAT Program existing objective analysis models which utilize a 125x125 polar stereographic grid of the Northern Hemisphere, which were modified in order to incorporate and assess the impact of (real or simulated) satellite data in the analysis of a two-day meteorological scenario in January 1979. Program/procedural changes included: (1) a provision to utilize winds in the sea level pressure and multi-level height analyses (1000-100 MBS); (2) The capability to perform a pre-analysis at two control levels (1000 MBS and 250 MBS); (3) a greater degree of wind- and mass-field coupling, especially at these controls levels; (4) an improved facility to bogus the analyses based on results of the preanalysis; and (5) a provision to utilize (SIRS) satellite thickness values and cloud motion vectors in the multi-level height analysis.

Multi-perspective views of students’ difficulties with one-dimensional vector and two-dimensional vector

NASA Astrophysics Data System (ADS)

Fauzi, Ahmad; Ratna Kawuri, Kunthi; Pratiwi, Retno

2017-01-01

Researchers of students’ conceptual change usually collects data from written tests and interviews. Moreover, reports of conceptual change often simply refer to changes in concepts, such as on a test, without any identification of the learning processes that have taken place. Research has shown that students have difficulties with vectors in university introductory physics courses and high school physics courses. In this study, we intended to explore students’ understanding of one-dimensional and two-dimensional vector in multi perspective views. In this research, we explore students’ understanding through test perspective and interviews perspective. Our research study adopted the mixed-methodology design. The participants of this research were sixty students of third semester of physics education department. The data of this research were collected by testand interviews. In this study, we divided the students’ understanding of one-dimensional vector and two-dimensional vector in two categories, namely vector skills of the addition of one-dimensionaland two-dimensional vector and the relation between vector skills and conceptual understanding. From the investigation, only 44% of students provided correct answer for vector skills of the addition of one-dimensional and two-dimensional vector and only 27% students provided correct answer for the relation between vector skills and conceptual understanding.

Two-terminal video coding.

PubMed

Yang, Yang; Stanković, Vladimir; Xiong, Zixiang; Zhao, Wei

2009-03-01

Following recent works on the rate region of the quadratic Gaussian two-terminal source coding problem and limit-approaching code designs, this paper examines multiterminal source coding of two correlated, i.e., stereo, video sequences to save the sum rate over independent coding of both sequences. Two multiterminal video coding schemes are proposed. In the first scheme, the left sequence of the stereo pair is coded by H.264/AVC and used at the joint decoder to facilitate Wyner-Ziv coding of the right video sequence. The first I-frame of the right sequence is successively coded by H.264/AVC Intracoding and Wyner-Ziv coding. An efficient stereo matching algorithm based on loopy belief propagation is then adopted at the decoder to produce pixel-level disparity maps between the corresponding frames of the two decoded video sequences on the fly. Based on the disparity maps, side information for both motion vectors and motion-compensated residual frames of the right sequence are generated at the decoder before Wyner-Ziv encoding. In the second scheme, source splitting is employed on top of classic and Wyner-Ziv coding for compression of both I-frames to allow flexible rate allocation between the two sequences. Experiments with both schemes on stereo video sequences using H.264/AVC, LDPC codes for Slepian-Wolf coding of the motion vectors, and scalar quantization in conjunction with LDPC codes for Wyner-Ziv coding of the residual coefficients give a slightly lower sum rate than separate H.264/AVC coding of both sequences at the same video quality.

Applying cybernetic technology to diagnose human pulmonary sounds.

PubMed

Chen, Mei-Yung; Chou, Cheng-Han

2014-06-01

Chest auscultation is a crucial and efficient method for diagnosing lung disease; however, it is a subjective process that relies on physician experience and the ability to differentiate between various sound patterns. Because the physiological signals composed of heart sounds and pulmonary sounds (PSs) are greater than 120 Hz and the human ear is not sensitive to low frequencies, successfully making diagnostic classifications is difficult. To solve this problem, we constructed various PS recognition systems for classifying six PS classes: vesicular breath sounds, bronchial breath sounds, tracheal breath sounds, crackles, wheezes, and stridor sounds. First, we used a piezoelectric microphone and data acquisition card to acquire PS signals and perform signal preprocessing. A wavelet transform was used for feature extraction, and the PS signals were decomposed into frequency subbands. Using a statistical method, we extracted 17 features that were used as the input vectors of a neural network. We proposed a 2-stage classifier combined with a back-propagation (BP) neural network and learning vector quantization (LVQ) neural network, which improves classification accuracy by using a haploid neural network. The receiver operating characteristic (ROC) curve verifies the high performance level of the neural network. To expand traditional auscultation methods, we constructed various PS diagnostic systems that can correctly classify the six common PSs. The proposed device overcomes the lack of human sensitivity to low-frequency sounds and various PS waves, characteristic values, and a spectral analysis charts are provided to elucidate the design of the human-machine interface.

Quantizing and sampling considerations in digital phased-locked loops

NASA Technical Reports Server (NTRS)

Hurst, G. T.; Gupta, S. C.

1974-01-01

The quantizer problem is first considered. The conditions under which the uniform white sequence model for the quantizer error is valid are established independent of the sampling rate. An equivalent spectral density is defined for the quantizer error resulting in an effective SNR value. This effective SNR may be used to determine quantized performance from infinitely fine quantized results. Attention is given to sampling rate considerations. Sampling rate characteristics of the digital phase-locked loop (DPLL) structure are investigated for the infinitely fine quantized system. The predicted phase error variance equation is examined as a function of the sampling rate. Simulation results are presented and a method is described which enables the minimum required sampling rate to be determined from the predicted phase error variance equations.

Semantic classification of business images

NASA Astrophysics Data System (ADS)

Erol, Berna; Hull, Jonathan J.

2006-01-01

Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

PubMed

Ortiz-Ramón, Rafael; Larroza, Andrés; Ruiz-España, Silvia; Arana, Estanislao; Moratal, David

2018-05-14

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Experimental formation of a fractional vortex in a superconducting bi-layer

NASA Astrophysics Data System (ADS)

Tanaka, Y.; Yamamori, H.; Yanagisawa, T.; Nishio, T.; Arisawa, S.

2018-05-01

We report the experimental formation of a fractional vortex generated by using a thin superconducting bi-layer in the form of a niobium bi-layer, observed as a magnetic flux distribution image taken by a scanning superconducting quantum interference device (SQUID) microscope. Thus, we demonstrated that multi-component superconductivity can be realized by an s-wave conventional superconductor, because, in these superconductors, the magnetic flux is no longer quantized as it is destroyed by the existence of an inter-component phase soliton (i-soliton).

Image splitting and remapping method for radiological image compression

NASA Astrophysics Data System (ADS)

Lo, Shih-Chung B.; Shen, Ellen L.; Mun, Seong K.

1990-07-01

A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in our radiological image compression study. In our experiments, we tested the impact of this decomposition method on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used was full-frame bit-allocation in the discrete cosine transform domain, which has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square-error and a high compression ratio. The parameters we used in this study were mean-square-error and the bit rate required for the compressed file. In addition to these parameters, the difference between the original and reconstructed images will be presented so that the specific artifacts generated by both techniques can be discerned by visual perception.

Reducing the Volume of NASA Earth-Science Data

NASA Technical Reports Server (NTRS)

Lee, Seungwon; Braverman, Amy J.; Guillaume, Alexandre

2010-01-01

A computer program reduces data generated by NASA Earth-science missions into representative clusters characterized by centroids and membership information, thereby reducing the large volume of data to a level more amenable to analysis. The program effects an autonomous data-reduction/clustering process to produce a representative distribution and joint relationships of the data, without assuming a specific type of distribution and relationship and without resorting to domain-specific knowledge about the data. The program implements a combination of a data-reduction algorithm known as the entropy-constrained vector quantization (ECVQ) and an optimization algorithm known as the differential evolution (DE). The combination of algorithms generates the Pareto front of clustering solutions that presents the compromise between the quality of the reduced data and the degree of reduction. Similar prior data-reduction computer programs utilize only a clustering algorithm, the parameters of which are tuned manually by users. In the present program, autonomous optimization of the parameters by means of the DE supplants the manual tuning of the parameters. Thus, the program determines the best set of clustering solutions without human intervention.

Digital Model of Fourier and Fresnel Quantized Holograms

NASA Astrophysics Data System (ADS)

Boriskevich, Anatoly A.; Erokhovets, Valery K.; Tkachenko, Vadim V.

Some models schemes of Fourier and Fresnel quantized protective holograms with visual effects are suggested. The condition to arrive at optimum relationship between the quality of reconstructed images, and the coefficient of data reduction about a hologram, and quantity of iterations in the reconstructing hologram process has been estimated through computer model. Higher protection level is achieved by means of greater number both bi-dimensional secret keys (more than 2128) in form of pseudorandom amplitude and phase encoding matrixes, and one-dimensional encoding key parameters for every image of single-layer or superimposed holograms.

Comparing the performance of two CBIRS indexing schemes

NASA Astrophysics Data System (ADS)

Mueller, Wolfgang; Robbert, Guenter; Henrich, Andreas

2003-01-01

Content based image retrieval (CBIR) as it is known today has to deal with a number of challenges. Quickly summarized, the main challenges are firstly, to bridge the semantic gap between high-level concepts and low-level features using feedback, secondly to provide performance under adverse conditions. High-dimensional spaces, as well as a demanding machine learning task make the right way of indexing an important issue. When indexing multimedia data, most groups opt for extraction of high-dimensional feature vectors from the data, followed by dimensionality reduction like PCA (Principal Components Analysis) or LSI (Latent Semantic Indexing). The resulting vectors are indexed using spatial indexing structures such as kd-trees or R-trees, for example. Other projects, such as MARS and Viper propose the adaptation of text indexing techniques, notably the inverted file. Here, the Viper system is the most direct adaptation of text retrieval techniques to quantized vectors. However, while the Viper query engine provides decent performance together with impressive user-feedback behavior, as well as the possibility for easy integration of long-term learning algorithms, and support for potentially infinite feature vectors, there has been no comparison of vector-based methods and inverted-file-based methods under similar conditions. In this publication, we compare a CBIR query engine that uses inverted files (Bothrops, a rewrite of the Viper query engine based on a relational database), and a CBIR query engine based on LSD (Local Split Decision) trees for spatial indexing using the same feature sets. The Benchathlon initiative works on providing a set of images and ground truth for simulating image queries by example and corresponding user feedback. When performing the Benchathlon benchmark on a CBIR system (the System Under Test, SUT), a benchmarking harness connects over internet to the SUT, performing a number of queries using an agreed-upon protocol, the multimedia retrieval markup language (MRML). Using this benchmark one can measure the quality of retrieval, as well as the overall (speed) performance of the benchmarked system. Our Benchmarks will draw on the Benchathlon"s work for documenting the retrieval performance of both inverted file-based and LSD tree based techniques. However in addition to these results, we will present statistics, that can be obtained only inside the system under test. These statistics will include the number of complex mathematical operations, as well as the amount of data that has to be read from disk during operation of a query.

Berezin-Toeplitz quantization and naturally defined star products for Kähler manifolds

NASA Astrophysics Data System (ADS)

Schlichenmaier, Martin

2018-04-01

For compact quantizable Kähler manifolds the Berezin-Toeplitz quantization schemes, both operator and deformation quantization (star product) are reviewed. The treatment includes Berezin's covariant symbols and the Berezin transform. The general compact quantizable case was done by Bordemann-Meinrenken-Schlichenmaier, Schlichenmaier, and Karabegov-Schlichenmaier. For star products on Kähler manifolds, separation of variables, or equivalently star product of (anti-) Wick type, is a crucial property. As canonically defined star products the Berezin-Toeplitz, Berezin, and the geometric quantization are treated. It turns out that all three are equivalent, but different.

A Fast Reduced Kernel Extreme Learning Machine.

PubMed

Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua

2016-04-01

In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred. Copyright © 2015 Elsevier Ltd. All rights reserved.

Subharmonic resonances in high-order wave mixing in the quantized atomic motion in a one-dimensional optical lattice

NASA Astrophysics Data System (ADS)

Lopez, J. P.; de Almeida, A. J. F.; Tabosa, J. W. R.

2018-03-01

We report on the observation of subharmonic resonances in high-order wave mixing associated with the quantized vibrational levels of atoms trapped in a one-dimensional optical lattice created by two intense nearly counterpropagating coupling beams. These subharmonic resonances, occurring at ±1 /2 and ±1 /3 of the frequency separation between adjacent vibrational levels, are observed through phase-match angularly resolved six- and eight-wave mixing processes. We investigate how these resonances evolve with the intensity of the incident probe beam, which couples with one of the coupling beams to create anharmonic coherence gratings between adjacent vibrational levels. Our experimental results also show evidence of high-order processes associated with coherence involving nonadjacent vibrational levels. Moreover, we also demonstrate that these induced high-order coherences can be stored in the medium and the associated optical information retrieved after a controlled storage time.

Gain in computational efficiency by vectorization in the dynamic simulation of multi-body systems

NASA Technical Reports Server (NTRS)

Amirouche, F. M. L.; Shareef, N. H.

1991-01-01

An improved technique for the identification and extraction of the exact quantities associated with the degrees of freedom at the element as well as the flexible body level is presented. It is implemented in the dynamic equations of motions based on the recursive formulation of Kane et al. (1987) and presented in a matrix form, integrating the concepts of strain energy, the finite-element approach, modal analysis, and reduction of equations. This technique eliminates the CPU intensive matrix multiplication operations in the code's hot spots for the dynamic simulation of the interconnected rigid and flexible bodies. A study of a simple robot with flexible links is presented by comparing the execution times on a scalar machine and a vector-processor with and without vector options. Performance figures demonstrating the substantial gains achieved by the technique are plotted.

MLP: A Parallel Programming Alternative to MPI for New Shared Memory Parallel Systems

NASA Technical Reports Server (NTRS)

Taft, James R.

1999-01-01

Recent developments at the NASA AMES Research Center's NAS Division have demonstrated that the new generation of NUMA based Symmetric Multi-Processing systems (SMPs), such as the Silicon Graphics Origin 2000, can successfully execute legacy vector oriented CFD production codes at sustained rates far exceeding processing rates possible on dedicated 16 CPU Cray C90 systems. This high level of performance is achieved via shared memory based Multi-Level Parallelism (MLP). This programming approach, developed at NAS and outlined below, is distinct from the message passing paradigm of MPI. It offers parallelism at both the fine and coarse grained level, with communication latencies that are approximately 50-100 times lower than typical MPI implementations on the same platform. Such latency reductions offer the promise of performance scaling to very large CPU counts. The method draws on, but is also distinct from, the newly defined OpenMP specification, which uses compiler directives to support a limited subset of multi-level parallel operations. The NAS MLP method is general, and applicable to a large class of NASA CFD codes.

Luminescence studies of HgCdTe- and InAsSb-based quantum-well structures

NASA Astrophysics Data System (ADS)

Izhnin, I. I.; Izhnin, A. I.; Fitsych, O. I.; Voitsekhovskii, A. V.; Gorn, D. I.; Semakova, A. A.; Bazhenov, N. L.; Mynbaev, K. D.; Zegrya, G. G.

2018-04-01

Results of photoluminescence studies of single-quantum-well HgCdTe-based structures and electroluminescence studies of multiple-quantum-well InAsSb-based structures are reported. HgCdTe structures were grown with molecular beam epitaxy on GaAs substrates. InAsSb-based structures were grown with metal-organic chemical vapor deposition on InAs substrates. The common feature of luminescence spectra of all the structures was the presence of peaks with the energy much larger than that of calculated optical transitions between the first quantization levels for electrons and heavy holes. Possibility of observation of optical transitions between the quantization levels of electrons and first and/or second heavy and light hole levels is discussed in the paper in relation to the specifics of the electronic structure of the materials under consideration.

No chiral truncation of quantum log gravity?

NASA Astrophysics Data System (ADS)

Andrade, Tomás; Marolf, Donald

2010-03-01

At the classical level, chiral gravity may be constructed as a consistent truncation of a larger theory called log gravity by requiring that left-moving charges vanish. In turn, log gravity is the limit of topologically massive gravity (TMG) at a special value of the coupling (the chiral point). We study the situation at the level of linearized quantum fields, focussing on a unitary quantization. While the TMG Hilbert space is continuous at the chiral point, the left-moving Virasoro generators become ill-defined and cannot be used to define a chiral truncation. In a sense, the left-moving asymptotic symmetries are spontaneously broken at the chiral point. In contrast, in a non-unitary quantization of TMG, both the Hilbert space and charges are continuous at the chiral point and define a unitary theory of chiral gravity at the linearized level.

Surveillance of Arthropod Vector-Borne Infectious Diseases Using Remote Sensing Techniques: A Review

PubMed Central

Kalluri, Satya; Gilruth, Peter; Rogers, David; Szczur, Martha

2007-01-01

Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between remote sensing scientists and biologists, and the availability of sophisticated, statistical geographic information system and image processing algorithms in a desktop environment creates a fertile research environment. The use of remote sensing techniques to map vector-borne diseases has evolved significantly over the past 25 years. In this paper, we review the status of remote sensing studies of arthropod vector-borne diseases due to mosquitoes, ticks, blackflies, tsetse flies, and sandflies, which are responsible for the majority of vector-borne diseases in the world. Examples of simple image classification techniques that associate land use and land cover types with vector habitats, as well as complex statistical models that link satellite-derived multi-temporal meteorological observations with vector biology and abundance, are discussed here. Future improvements in remote sensing applications in epidemiology are also discussed. PMID:17967056

Dielectric properties of classical and quantized ionic fluids.

PubMed

Høye, Johan S

2010-06-01

We study time-dependent correlation functions of classical and quantum gases using methods of equilibrium statistical mechanics for systems of uniform as well as nonuniform densities. The basis for our approach is the path integral formalism of quantum mechanical systems. With this approach the statistical mechanics of a quantum mechanical system becomes the equivalent of a classical polymer problem in four dimensions where imaginary time is the fourth dimension. Several nontrivial results for quantum systems have been obtained earlier by this analogy. Here, we will focus upon the presence of a time-dependent electromagnetic pair interaction where the electromagnetic vector potential that depends upon currents, will be present. Thus both density and current correlations are needed to evaluate the influence of this interaction. Then we utilize that densities and currents can be expressed by polarizations by which the ionic fluid can be regarded as a dielectric one for which a nonlocal susceptibility is found. This nonlocality has as a consequence that we find no contribution from a possible transverse electric zero-frequency mode for the Casimir force between metallic plates. Further, we establish expressions for a leading correction to ab initio calculations for the energies of the quantized electrons of molecules where now retardation effects also are taken into account.

First integrals of motion in a gauge covariant framework, Killing-Maxwell system and quantum anomalies

NASA Astrophysics Data System (ADS)

Visinescu, M.

2012-10-01

Hidden symmetries in a covariant Hamiltonian framework are investigated. The special role of the Stackel-Killing and Killing-Yano tensors is pointed out. The covariant phase-space is extended to include external gauge fields and scalar potentials. We investigate the possibility for a higher-order symmetry to survive when the electromagnetic interactions are taken into account. Aconcrete realization of this possibility is given by the Killing-Maxwell system. The classical conserved quantities do not generally transfer to the quantized systems producing quantum gravitational anomalies. As a rule the conformal extension of the Killing vectors and tensors does not produce symmetry operators for the Klein-Gordon operator.

Asymptotics of the evolution semigroup associated with a scalar field in the presence of a non-linear electromagnetic field

NASA Astrophysics Data System (ADS)

Albeverio, Sergio; Tamura, Hiroshi

2018-04-01

We consider a model describing the coupling of a vector-valued and a scalar homogeneous Markovian random field over R4, interpreted as expressing the interaction between a charged scalar quantum field coupled with a nonlinear quantized electromagnetic field. Expectations of functionals of the random fields are expressed by Brownian bridges. Using this, together with Feynman-Kac-Itô type formulae and estimates on the small time and large time behaviour of Brownian functionals, we prove asymptotic upper and lower bounds on the kernel of the transition semigroup for our model. The upper bound gives faster than exponential decay for large distances of the corresponding resolvent (propagator).

High performance compression of science data

NASA Technical Reports Server (NTRS)

Storer, James A.; Cohn, Martin

1994-01-01

Two papers make up the body of this report. One presents a single-pass adaptive vector quantization algorithm that learns a codebook of variable size and shape entries; the authors present experiments on a set of test images showing that with no training or prior knowledge of the data, for a given fidelity, the compression achieved typically equals or exceeds that of the JPEG standard. The second paper addresses motion compensation, one of the most effective techniques used in the interframe data compression. A parallel block-matching algorithm for estimating interframe displacement of blocks with minimum error is presented. The algorithm is designed for a simple parallel architecture to process video in real time.

Coherent distributions for the rigid rotator

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

Grigorescu, Marius

2016-06-15

Coherent solutions of the classical Liouville equation for the rigid rotator are presented as positive phase-space distributions localized on the Lagrangian submanifolds of Hamilton-Jacobi theory. These solutions become Wigner-type quasiprobability distributions by a formal discretization of the left-invariant vector fields from their Fourier transform in angular momentum. The results are consistent with the usual quantization of the anisotropic rotator, but the expected value of the Hamiltonian contains a finite “zero point” energy term. It is shown that during the time when a quasiprobability distribution evolves according to the Liouville equation, the related quantum wave function should satisfy the time-dependent Schrödingermore » equation.« less

Visual communications and image processing '92; Proceedings of the Meeting, Boston, MA, Nov. 18-20, 1992

NASA Astrophysics Data System (ADS)

Maragos, Petros

The topics discussed at the conference include hierarchical image coding, motion analysis, feature extraction and image restoration, video coding, and morphological and related nonlinear filtering. Attention is also given to vector quantization, morphological image processing, fractals and wavelets, architectures for image and video processing, image segmentation, biomedical image processing, and model-based analysis. Papers are presented on affine models for motion and shape recovery, filters for directly detecting surface orientation in an image, tracking of unresolved targets in infrared imagery using a projection-based method, adaptive-neighborhood image processing, and regularized multichannel restoration of color images using cross-validation. (For individual items see A93-20945 to A93-20951)

SAR data compression: Application, requirements, and designs

NASA Technical Reports Server (NTRS)

Curlander, John C.; Chang, C. Y.

1991-01-01

The feasibility of reducing data volume and data rate is evaluated for the Earth Observing System (EOS) Synthetic Aperture Radar (SAR). All elements of data stream from the sensor downlink data stream to electronic delivery of browse data products are explored. The factors influencing design of a data compression system are analyzed, including the signal data characteristics, the image quality requirements, and the throughput requirements. The conclusion is that little or no reduction can be achieved in the raw signal data using traditional data compression techniques (e.g., vector quantization, adaptive discrete cosine transform) due to the induced phase errors in the output image. However, after image formation, a number of techniques are effective for data compression.

Controller design for a class of nonlinear MIMO coupled system using multiple models and second level adaptation.

PubMed

Pandey, Vinay Kumar; Kar, Indrani; Mahanta, Chitralekha

2017-07-01

In this paper, an adaptive control method using multiple models with second level adaptation is proposed for a class of nonlinear multi-input multi-output (MIMO) coupled systems. Multiple estimation models are used to tune the unknown parameters at the first level. The second level adaptation provides a single parameter vector for the controller. A feedback linearization technique is used to design a state feedback control. The efficacy of the designed controller is validated by conducting real time experiment on a laboratory setup of twin rotor MIMO system (TRMS). The TRMS setup is discussed in detail and the experiments were performed for regulation and tracking problem for pitch and yaw control using different reference signals. An Extended Kalman Filter (EKF) has been used to observe the unavailable states of the TRMS. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Quantization and fractional quantization of currents in periodically driven stochastic systems. I. Average currents

NASA Astrophysics Data System (ADS)

Chernyak, Vladimir Y.; Klein, John R.; Sinitsyn, Nikolai A.

2012-04-01

This article studies Markovian stochastic motion of a particle on a graph with finite number of nodes and periodically time-dependent transition rates that satisfy the detailed balance condition at any time. We show that under general conditions, the currents in the system on average become quantized or fractionally quantized for adiabatic driving at sufficiently low temperature. We develop the quantitative theory of this quantization and interpret it in terms of topological invariants. By implementing the celebrated Kirchhoff theorem we derive a general and explicit formula for the average generated current that plays a role of an efficient tool for treating the current quantization effects.

On the Improvement of Convergence Performance for Integrated Design of Wind Turbine Blade Using a Vector Dominating Multi-objective Evolution Algorithm

NASA Astrophysics Data System (ADS)

Wang, L.; Wang, T. G.; Wu, J. H.; Cheng, G. P.

2016-09-01

A novel multi-objective optimization algorithm incorporating evolution strategies and vector mechanisms, referred as VD-MOEA, is proposed and applied in aerodynamic- structural integrated design of wind turbine blade. In the algorithm, a set of uniformly distributed vectors is constructed to guide population in moving forward to the Pareto front rapidly and maintain population diversity with high efficiency. For example, two- and three- objective designs of 1.5MW wind turbine blade are subsequently carried out for the optimization objectives of maximum annual energy production, minimum blade mass, and minimum extreme root thrust. The results show that the Pareto optimal solutions can be obtained in one single simulation run and uniformly distributed in the objective space, maximally maintaining the population diversity. In comparison to conventional evolution algorithms, VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation for handling complex problems of multi-variables, multi-objectives and multi-constraints. This provides a reliable high-performance optimization approach for the aerodynamic-structural integrated design of wind turbine blade.

Efficient compression of molecular dynamics trajectory files.

PubMed

Marais, Patrick; Kenwood, Julian; Smith, Keegan Carruthers; Kuttel, Michelle M; Gain, James

2012-10-15

We investigate whether specific properties of molecular dynamics trajectory files can be exploited to achieve effective file compression. We explore two classes of lossy, quantized compression scheme: "interframe" predictors, which exploit temporal coherence between successive frames in a simulation, and more complex "intraframe" schemes, which compress each frame independently. Our interframe predictors are fast, memory-efficient and well suited to on-the-fly compression of massive simulation data sets, and significantly outperform the benchmark BZip2 application. Our schemes are configurable: atomic positional accuracy can be sacrificed to achieve greater compression. For high fidelity compression, our linear interframe predictor gives the best results at very little computational cost: at moderate levels of approximation (12-bit quantization, maximum error ≈ 10(-2) Å), we can compress a 1-2 fs trajectory file to 5-8% of its original size. For 200 fs time steps-typically used in fine grained water diffusion experiments-we can compress files to ~25% of their input size, still substantially better than BZip2. While compression performance degrades with high levels of quantization, the simulation error is typically much greater than the associated approximation error in such cases. Copyright © 2012 Wiley Periodicals, Inc.

Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding.

PubMed

Ki, Sehwan; Bae, Sung-Ho; Kim, Munchurl; Ko, Hyunsuk

2018-07-01

Conventional predictive video coding-based approaches are reaching the limit of their potential coding efficiency improvements, because of severely increasing computation complexity. As an alternative approach, perceptual video coding (PVC) has attempted to achieve high coding efficiency by eliminating perceptual redundancy, using just-noticeable-distortion (JND) directed PVC. The previous JNDs were modeled by adding white Gaussian noise or specific signal patterns into the original images, which were not appropriate in finding JND thresholds due to distortion with energy reduction. In this paper, we present a novel discrete cosine transform-based energy-reduced JND model, called ERJND, that is more suitable for JND-based PVC schemes. Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as preprocessing that can be applied for perceptual video coding. The two JNQD models can automatically adjust JND levels based on given quantization step sizes. One of the two JNQD models, called LR-JNQD, is based on linear regression and determines the model parameter for JNQD based on extracted handcraft features. The other JNQD model is based on a convolution neural network (CNN), called CNN-JNQD. To our best knowledge, our paper is the first approach to automatically adjust JND levels according to quantization step sizes for preprocessing the input to video encoders. In experiments, both the LR-JNQD and CNN-JNQD models were applied to high efficiency video coding (HEVC) and yielded maximum (average) bitrate reductions of 38.51% (10.38%) and 67.88% (24.91%), respectively, with little subjective video quality degradation, compared with the input without preprocessing applied.

Optimal Quantization Scheme for Data-Efficient Target Tracking via UWSNs Using Quantized Measurements.

PubMed

Zhang, Senlin; Chen, Huayan; Liu, Meiqin; Zhang, Qunfei

2017-11-07

Target tracking is one of the broad applications of underwater wireless sensor networks (UWSNs). However, as a result of the temporal and spatial variability of acoustic channels, underwater acoustic communications suffer from an extremely limited bandwidth. In order to reduce network congestion, it is important to shorten the length of the data transmitted from local sensors to the fusion center by quantization. Although quantization can reduce bandwidth cost, it also brings about bad tracking performance as a result of information loss after quantization. To solve this problem, this paper proposes an optimal quantization-based target tracking scheme. It improves the tracking performance of low-bit quantized measurements by minimizing the additional covariance caused by quantization. The simulation demonstrates that our scheme performs much better than the conventional uniform quantization-based target tracking scheme and the increment of the data length affects our scheme only a little. Its tracking performance improves by only 4.4% from 2- to 3-bit, which means our scheme weakly depends on the number of data bits. Moreover, our scheme also weakly depends on the number of participate sensors, and it can work well in sparse sensor networks. In a 6 × 6 × 6 sensor network, compared with 4 × 4 × 4 sensor networks, the number of participant sensors increases by 334.92%, while the tracking accuracy using 1-bit quantized measurements improves by only 50.77%. Overall, our optimal quantization-based target tracking scheme can achieve the pursuit of data-efficiency, which fits the requirements of low-bandwidth UWSNs.

Hyperspectral recognition of processing tomato early blight based on GA and SVM

NASA Astrophysics Data System (ADS)

Yin, Xiaojun; Zhao, SiFeng

2013-03-01

Processing tomato early blight seriously affect the yield and quality of its.Determine the leaves spectrum of different disease severity level of processing tomato early blight.We take the sensitive bands of processing tomato early blight as support vector machine input vector.Through the genetic algorithm(GA) to optimize the parameters of SVM, We could recognize different disease severity level of processing tomato early blight.The result show:the sensitive bands of different disease severity levels of processing tomato early blight is 628-643nm and 689-692nm.The sensitive bands are as the GA and SVM input vector.We get the best penalty parameters is 0.129 and kernel function parameters is 3.479.We make classification training and testing by polynomial nuclear,radial basis function nuclear,Sigmoid nuclear.The best classification model is the radial basis function nuclear of SVM. Training accuracy is 84.615%,Testing accuracy is 80.681%.It is combined GA and SVM to achieve multi-classification of processing tomato early blight.It is provided the technical support of prediction processing tomato early blight occurrence, development and diffusion rule in large areas.

An OpenACC-Based Unified Programming Model for Multi-accelerator Systems

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

Kim, Jungwon; Lee, Seyong; Vetter, Jeffrey S

2015-01-01

This paper proposes a novel SPMD programming model of OpenACC. Our model integrates the different granularities of parallelism from vector-level parallelism to node-level parallelism into a single, unified model based on OpenACC. It allows programmers to write programs for multiple accelerators using a uniform programming model whether they are in shared or distributed memory systems. We implement a prototype of our model and evaluate its performance with a GPU-based supercomputer using three benchmark applications.

Co-Labeling for Multi-View Weakly Labeled Learning.

PubMed

Xu, Xinxing; Li, Wen; Xu, Dong; Tsang, Ivor W

2016-06-01

It is often expensive and time consuming to collect labeled training samples in many real-world applications. To reduce human effort on annotating training samples, many machine learning techniques (e.g., semi-supervised learning (SSL), multi-instance learning (MIL), etc.) have been studied to exploit weakly labeled training samples. Meanwhile, when the training data is represented with multiple types of features, many multi-view learning methods have shown that classifiers trained on different views can help each other to better utilize the unlabeled training samples for the SSL task. In this paper, we study a new learning problem called multi-view weakly labeled learning, in which we aim to develop a unified approach to learn robust classifiers by effectively utilizing different types of weakly labeled multi-view data from a broad range of tasks including SSL, MIL and relative outlier detection (ROD). We propose an effective approach called co-labeling to solve the multi-view weakly labeled learning problem. Specifically, we model the learning problem on each view as a weakly labeled learning problem, which aims to learn an optimal classifier from a set of pseudo-label vectors generated by using the classifiers trained from other views. Unlike traditional co-training approaches using a single pseudo-label vector for training each classifier, our co-labeling approach explores different strategies to utilize the predictions from different views, biases and iterations for generating the pseudo-label vectors, making our approach more robust for real-world applications. Moreover, to further improve the weakly labeled learning on each view, we also exploit the inherent group structure in the pseudo-label vectors generated from different strategies, which leads to a new multi-layer multiple kernel learning problem. Promising results for text-based image retrieval on the NUS-WIDE dataset as well as news classification and text categorization on several real-world multi-view datasets clearly demonstrate that our proposed co-labeling approach achieves state-of-the-art performance for various multi-view weakly labeled learning problems including multi-view SSL, multi-view MIL and multi-view ROD.

The myeloid-binding peptide adenoviral vector enables multi-organ vascular endothelial gene targeting.

PubMed

Lu, Zhi Hong; Kaliberov, Sergey; Zhang, Jingzhu; Muz, Barbara; Azab, Abdel K; Sohn, Rebecca E; Kaliberova, Lyudmila; Du, Yingqiu; Curiel, David T; Arbeit, Jeffrey M

2014-08-01

Vascular endothelial cells (ECs) are ideal gene therapy targets as they provide widespread tissue access and are the first contact surfaces following intravenous vector administration. Human recombinant adenovirus serotype 5 (Ad5) is the most frequently used gene transfer system because of its appreciable transgene payload capacity and lack of somatic mutation risk. However, standard Ad5 vectors predominantly transduce liver but not the vasculature following intravenous administration. We recently developed an Ad5 vector with a myeloid cell-binding peptide (MBP) incorporated into the knob-deleted, T4 fibritin chimeric fiber (Ad.MBP). This vector was shown to transduce pulmonary ECs presumably via a vector handoff mechanism. Here we tested the body-wide tropism of the Ad.MBP vector, its myeloid cell necessity, and vector-EC expression dose response. Using comprehensive multi-organ co-immunofluorescence analysis, we discovered that Ad.MBP produced widespread EC transduction in the lung, heart, kidney, skeletal muscle, pancreas, small bowel, and brain. Surprisingly, Ad.MBP retained hepatocyte tropism albeit at a reduced frequency compared with the standard Ad5. While binding specifically to myeloid cells ex vivo, multi-organ Ad.MBP expression was not dependent on circulating monocytes or macrophages. Ad.MBP dose de-escalation maintained full lung-targeting capacity but drastically reduced transgene expression in other organs. Swapping the EC-specific ROBO4 for the CMV promoter/enhancer abrogated hepatocyte expression but also reduced gene expression in other organs. Collectively, our multilevel targeting strategy could enable therapeutic biological production in previously inaccessible organs that pertain to the most debilitating or lethal human diseases.

Two generalizations of Kohonen clustering

NASA Technical Reports Server (NTRS)

Bezdek, James C.; Pal, Nikhil R.; Tsao, Eric C. K.

1993-01-01

The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.

LVQ and backpropagation neural networks applied to NASA SSME data

NASA Technical Reports Server (NTRS)

Doniere, Timothy F.; Dhawan, Atam P.

1993-01-01

Feedfoward neural networks with backpropagation learning have been used as function approximators for modeling the space shuttle main engine (SSME) sensor signals. The modeling of these sensor signals is aimed at the development of a sensor fault detection system that can be used during ground test firings. The generalization capability of a neural network based function approximator depends on the training vectors which in this application may be derived from a number of SSME ground test-firings. This yields a large number of training vectors. Large training sets can cause the time required to train the network to be very large. Also, the network may not be able to generalize for large training sets. To reduce the size of the training sets, the SSME test-firing data is reduced using the learning vector quantization (LVQ) based technique. Different compression ratios were used to obtain compressed data in training the neural network model. The performance of the neural model trained using reduced sets of training patterns is presented and compared with the performance of the model trained using complete data. The LVQ can also be used as a function approximator. The performance of the LVQ as a function approximator using reduced training sets is presented and compared with the performance of the backpropagation network.

Perceptual Optimization of DCT Color Quantization Matrices

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Statler, Irving C. (Technical Monitor)

1994-01-01

Many image compression schemes employ a block Discrete Cosine Transform (DCT) and uniform quantization. Acceptable rate/distortion performance depends upon proper design of the quantization matrix. In previous work, we showed how to use a model of the visibility of DCT basis functions to design quantization matrices for arbitrary display resolutions and color spaces. Subsequently, we showed how to optimize greyscale quantization matrices for individual images, for optimal rate/perceptual distortion performance. Here we describe extensions of this optimization algorithm to color images.

Lentiviral gene ontology (LeGO) vectors equipped with novel drug-selectable fluorescent proteins: new building blocks for cell marking and multi-gene analysis.

PubMed

Weber, K; Mock, U; Petrowitz, B; Bartsch, U; Fehse, B

2010-04-01

Vector-encoded fluorescent proteins (FPs) facilitate unambiguous identification or sorting of gene-modified cells by fluorescence-activated cell sorting (FACS). Exploiting this feature, we have recently developed lentiviral gene ontology (LeGO) vectors (www.LentiGO-Vectors.de) for multi-gene analysis in different target cells. In this study, we extend the LeGO principle by introducing 10 different drug-selectable FPs created by fusing one of the five selection marker (protecting against blasticidin, hygromycin, neomycin, puromycin and zeocin) and one of the five FP genes (Cerulean, eGFP, Venus, dTomato and mCherry). All tested fusion proteins allowed both fluorescence-mediated detection and drug-mediated selection of LeGO-transduced cells. Newly generated codon-optimized hygromycin- and neomycin-resistance genes showed improved expression as compared with their ancestors. New LeGO constructs were produced at titers >10(6) per ml (for non-concentrated supernatants). We show efficient combinatorial marking and selection of various cells, including mesenchymal stem cells, simultaneously transduced with different LeGO constructs. Inclusion of the cytomegalovirus early enhancer/chicken beta-actin promoter into LeGO vectors facilitated robust transgene expression in and selection of neural stem cells and their differentiated progeny. We suppose that the new drug-selectable markers combining advantages of FACS and drug selection are well suited for numerous applications and vector systems. Their inclusion into LeGO vectors opens new possibilities for (stem) cell tracking and functional multi-gene analysis.

Tripartite entanglement dynamics and entropic squeezing of a three-level atom interacting with a bimodal cavity field

NASA Astrophysics Data System (ADS)

Faghihi, M. J.; Tavassoly, M. K.; Bagheri Harouni, M.

2014-04-01

In this paper, we study the interaction between a Λ-type three-level atom and two quantized electromagnetic fields which are simultaneously injected in a bichromatic cavity surrounded by a Kerr medium in the presence of field-field interaction (parametric down conversion) and detuning parameters. By applying a canonical transformation, the introduced model is reduced to a well-known form of the generalized Jaynes-Cummings model. Under particular initial conditions which may be prepared for the atom and the field, the time evolution of the state vector of the entire system is analytically evaluated. Then, the dynamics of the atom is studied through the evolution of the atomic population inversion. In addition, two different measures of entanglement between the tripartite system (three entities make the system: two field modes and one atom), i.e., von Neumann and linear entropy are investigated. Also, two kinds of entropic uncertainty relations, from which entropy squeezing can be obtained, are discussed. In each case, the influences of the detuning parameters and Kerr medium on the above nonclassicality features are analyzed in detail via numerical results. It is illustrated that the amount of the above-mentioned physical phenomena can be tuned by choosing the evolved parameters, appropriately.

Real-Time Visual Tracking through Fusion Features

PubMed Central

Ruan, Yang; Wei, Zhenzhong

2016-01-01

Due to their high-speed, correlation filters for object tracking have begun to receive increasing attention. Traditional object trackers based on correlation filters typically use a single type of feature. In this paper, we attempt to integrate multiple feature types to improve the performance, and we propose a new DD-HOG fusion feature that consists of discriminative descriptors (DDs) and histograms of oriented gradients (HOG). However, fusion features as multi-vector descriptors cannot be directly used in prior correlation filters. To overcome this difficulty, we propose a multi-vector correlation filter (MVCF) that can directly convolve with a multi-vector descriptor to obtain a single-channel response that indicates the location of an object. Experiments on the CVPR2013 tracking benchmark with the evaluation of state-of-the-art trackers show the effectiveness and speed of the proposed method. Moreover, we show that our MVCF tracker, which uses the DD-HOG descriptor, outperforms the structure-preserving object tracker (SPOT) in multi-object tracking because of its high-speed and ability to address heavy occlusion. PMID:27347951

Zero-field magnetic response functions in Landau levels

PubMed Central

Gao, Yang; Niu, Qian

2017-01-01

We present a fresh perspective on the Landau level quantization rule; that is, by successively including zero-field magnetic response functions at zero temperature, such as zero-field magnetization and susceptibility, the Onsager’s rule can be corrected order by order. Such a perspective is further reinterpreted as a quantization of the semiclassical electron density in solids. Our theory not only reproduces Onsager’s rule at zeroth order and the Berry phase and magnetic moment correction at first order but also explains the nature of higher-order corrections in a universal way. In applications, those higher-order corrections are expected to curve the linear relation between the level index and the inverse of the magnetic field, as already observed in experiments. Our theory then provides a way to extract the correct value of Berry phase as well as the magnetic susceptibility at zero temperature from Landau level fan diagrams in experiments. Moreover, it can be used theoretically to calculate Landau levels up to second-order accuracy for realistic models. PMID:28655849

Statistical analysis of dispersion relations in turbulent solar wind fluctuations using Cluster data

NASA Astrophysics Data System (ADS)

Perschke, C.; Narita, Y.

2012-12-01

Multi-spacecraft measurements enable us to resolve three-dimensional spatial structures without assuming Taylor's frozen-in-flow hypothesis. This is very useful to study frequency-wave vector diagram in solar wind turbulence through direct determination of three-dimensional wave vectors. The existence and evolution of dispersion relation and its role in fully-developed plasma turbulence have been drawing attention of physicists, in particular, if solar wind turbulence represents kinetic Alfvén or whistler mode as the carrier of spectral energy among different scales through wave-wave interactions. We investigate solar wind intervals of Cluster data for various flow velocities with a high-resolution wave vector analysis method, Multi-point Signal Resonator technique, at the tetrahedral separation about 100 km. Magnetic field data and ion data are used to determine the frequency- wave vector diagrams in the co-moving frame of the solar wind. We find primarily perpendicular wave vectors in solar wind turbulence which justify the earlier discussions about kinetic Alfvén or whistler wave. The frequency- wave vector diagrams confirm (a) wave vector anisotropy and (b) scattering in frequencies.

Simultaneous Conduction and Valence Band Quantization in Ultrashallow High-Density Doping Profiles in Semiconductors

NASA Astrophysics Data System (ADS)

Mazzola, F.; Wells, J. W.; Pakpour-Tabrizi, A. C.; Jackman, R. B.; Thiagarajan, B.; Hofmann, Ph.; Miwa, J. A.

2018-01-01

We demonstrate simultaneous quantization of conduction band (CB) and valence band (VB) states in silicon using ultrashallow, high-density, phosphorus doping profiles (so-called Si:P δ layers). We show that, in addition to the well-known quantization of CB states within the dopant plane, the confinement of VB-derived states between the subsurface P dopant layer and the Si surface gives rise to a simultaneous quantization of VB states in this narrow region. We also show that the VB quantization can be explained using a simple particle-in-a-box model, and that the number and energy separation of the quantized VB states depend on the depth of the P dopant layer beneath the Si surface. Since the quantized CB states do not show a strong dependence on the dopant depth (but rather on the dopant density), it is straightforward to exhibit control over the properties of the quantized CB and VB states independently of each other by choosing the dopant density and depth accordingly, thus offering new possibilities for engineering quantum matter.

Thermopower and the Fractional Quantized Hall Effect in the N=1 Landau Level

NASA Astrophysics Data System (ADS)

Chickering, W. E.; Eisenstein, J. P.; Pfeiffer, L. N.; West, K. W.

2012-02-01

Having recently eliminated an issue involving long thermal time constants [1], we are now able to resolve diffusion thermopower deep into the fractional quantized Hall effect (FQHE) regime. In this talk we report measurements of thermopower in the first excited (N=1) Landau level as a continuous function of magnetic field down to temperatures as low as 30mK. Above 50mK we can clearly resolve the ν = 5/2 as well as ν = 7/3, 8/3, and 14/5 FQHEs in both the electrical and thermoelectrical transport. Below 50mK a prominent feature of the electrical transport in the first excited Landau level is the Re-entrant Integer Quantized Hall Effect (RIQHE) which is associated with insulating collective phases [2]. In this temperature regime the thermopower exhibits a series of intriguing sign reversals that are as yet not fully understood. We will conclude with a brief discussion of the connection between thermopower and the entropy of the 2D electron system. This connection is invoked by a recent prediction [3] of the thermopower at ν = 5/2, which assumes the ground state is the non-Abelian Moore-Read paired composite fermion state.[4pt] [1] Chickering, Phys. Rev. B 81, 245319 (2010)[0pt] [2] Eisenstein, Phys. Rev. Lett. 88, 076801 (2002)[0pt] [3] Yang, Phys. Rev. B 79, 115317 (2009)

Quantum Bath Refrigeration towards Absolute Zero: Challenging the Unattainability Principle

NASA Astrophysics Data System (ADS)

Kolář, M.; Gelbwaser-Klimovsky, D.; Alicki, R.; Kurizki, G.

2012-08-01

A minimal model of a quantum refrigerator, i.e., a periodically phase-flipped two-level system permanently coupled to a finite-capacity bath (cold bath) and an infinite heat dump (hot bath), is introduced and used to investigate the cooling of the cold bath towards absolute zero (T=0). Remarkably, the temperature scaling of the cold-bath cooling rate reveals that it does not vanish as T→0 for certain realistic quantized baths, e.g., phonons in strongly disordered media (fractons) or quantized spin waves in ferromagnets (magnons). This result challenges Nernst’s third-law formulation known as the unattainability principle.

Quantization of Spontaneously Broken Gauge Theory Based on the Bft-Bfv Formalism

NASA Astrophysics Data System (ADS)

Kim, Yong-Wan; Park, Young-Jai

We quantize the spontaneously broken Abelian U(1) Higgs model by using the improved BFT and BFV formalisms. We construct the BFT physical fields and obtain the firstclass observables including the Hamiltonian in terms of these fields. We also explicitly show that there are exact form invariances between the second-class and first-class quantities. Then, according to the BFV formalism, we derive the corresponding Lagrangian having U(1) gauge symmetry. We also discuss at the classical level how one easily gets the first-class Lagrangian from the symmetry-broken second-class Lagrangian.

Analog Landau-He-McKellar-Wilkens quantization due to noninertial effects of the Fermi-Walker reference frame

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

Bakke, Knut

2010-05-15

We will show that when a neutral particle with permanent electric dipole moment interacts with a specific field configuration when the local reference frames of the observers are Fermi-Walker transported, the Landau quantization analog to the He-McKellar-Wilkens setup arises in the nonrelativistic quantum dynamics of the neutral particle due the noninertial effects of the Fermi-Walker reference frame. We show that the noninertial effects do not break the infinity degeneracy of the energy levels, but in this case, the cyclotron frequency depends on the angular velocity.

Quantum bath refrigeration towards absolute zero: challenging the unattainability principle.

PubMed

Kolář, M; Gelbwaser-Klimovsky, D; Alicki, R; Kurizki, G

2012-08-31

A minimal model of a quantum refrigerator, i.e., a periodically phase-flipped two-level system permanently coupled to a finite-capacity bath (cold bath) and an infinite heat dump (hot bath), is introduced and used to investigate the cooling of the cold bath towards absolute zero (T=0). Remarkably, the temperature scaling of the cold-bath cooling rate reveals that it does not vanish as T→0 for certain realistic quantized baths, e.g., phonons in strongly disordered media (fractons) or quantized spin waves in ferromagnets (magnons). This result challenges Nernst's third-law formulation known as the unattainability principle.

Scalable hybrid computation with spikes.

PubMed

Sarpeshkar, Rahul; O'Halloran, Micah

2002-09-01

We outline a hybrid analog-digital scheme for computing with three important features that enable it to scale to systems of large complexity: First, like digital computation, which uses several one-bit precise logical units to collectively compute a precise answer to a computation, the hybrid scheme uses several moderate-precision analog units to collectively compute a precise answer to a computation. Second, frequent discrete signal restoration of the analog information prevents analog noise and offset from degrading the computation. And, third, a state machine enables complex computations to be created using a sequence of elementary computations. A natural choice for implementing this hybrid scheme is one based on spikes because spike-count codes are digital, while spike-time codes are analog. We illustrate how spikes afford easy ways to implement all three components of scalable hybrid computation. First, as an important example of distributed analog computation, we show how spikes can create a distributed modular representation of an analog number by implementing digital carry interactions between spiking analog neurons. Second, we show how signal restoration may be performed by recursive spike-count quantization of spike-time codes. And, third, we use spikes from an analog dynamical system to trigger state transitions in a digital dynamical system, which reconfigures the analog dynamical system using a binary control vector; such feedback interactions between analog and digital dynamical systems create a hybrid state machine (HSM). The HSM extends and expands the concept of a digital finite-state-machine to the hybrid domain. We present experimental data from a two-neuron HSM on a chip that implements error-correcting analog-to-digital conversion with the concurrent use of spike-time and spike-count codes. We also present experimental data from silicon circuits that implement HSM-based pattern recognition using spike-time synchrony. We outline how HSMs may be used to perform learning, vector quantization, spike pattern recognition and generation, and how they may be reconfigured.

Reliable and Efficient Parallel Processing Algorithms and Architectures for Modern Signal Processing. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Liu, Kuojuey Ray

1990-01-01

Least-squares (LS) estimations and spectral decomposition algorithms constitute the heart of modern signal processing and communication problems. Implementations of recursive LS and spectral decomposition algorithms onto parallel processing architectures such as systolic arrays with efficient fault-tolerant schemes are the major concerns of this dissertation. There are four major results in this dissertation. First, we propose the systolic block Householder transformation with application to the recursive least-squares minimization. It is successfully implemented on a systolic array with a two-level pipelined implementation at the vector level as well as at the word level. Second, a real-time algorithm-based concurrent error detection scheme based on the residual method is proposed for the QRD RLS systolic array. The fault diagnosis, order degraded reconfiguration, and performance analysis are also considered. Third, the dynamic range, stability, error detection capability under finite-precision implementation, order degraded performance, and residual estimation under faulty situations for the QRD RLS systolic array are studied in details. Finally, we propose the use of multi-phase systolic algorithms for spectral decomposition based on the QR algorithm. Two systolic architectures, one based on triangular array and another based on rectangular array, are presented for the multiphase operations with fault-tolerant considerations. Eigenvectors and singular vectors can be easily obtained by using the multi-pase operations. Performance issues are also considered.

Chem Ed Compacts.

ERIC Educational Resources Information Center

Wolf, Walter A., Ed.

1980-01-01

Presents three reports: a description for an upper-level course in protein chemistry; a technique for generating many unique unknowns for the determination of molecular weight by viscosity; and an analogy for quantization of energy levels in which molecules are considered as books in a library. (CS)

A Power Transformers Fault Diagnosis Model Based on Three DGA Ratios and PSO Optimization SVM

NASA Astrophysics Data System (ADS)

Ma, Hongzhe; Zhang, Wei; Wu, Rongrong; Yang, Chunyan

2018-03-01

In order to make up for the shortcomings of existing transformer fault diagnosis methods in dissolved gas-in-oil analysis (DGA) feature selection and parameter optimization, a transformer fault diagnosis model based on the three DGA ratios and particle swarm optimization (PSO) optimize support vector machine (SVM) is proposed. Using transforming support vector machine to the nonlinear and multi-classification SVM, establishing the particle swarm optimization to optimize the SVM multi classification model, and conducting transformer fault diagnosis combined with the cross validation principle. The fault diagnosis results show that the average accuracy of test method is better than the standard support vector machine and genetic algorithm support vector machine, and the proposed method can effectively improve the accuracy of transformer fault diagnosis is proved.

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

Serwer, Philip, E-mail: serwer@uthscsa.edu; Wright, Elena T.; Liu, Zheng

DNA packaging of phages phi29, T3 and T7 sometimes produces incompletely packaged DNA with quantized lengths, based on gel electrophoretic band formation. We discover here a packaging ATPase-free, in vitro model for packaged DNA length quantization. We use directed evolution to isolate a five-site T3 point mutant that hyper-produces tail-free capsids with mature DNA (heads). Three tail gene mutations, but no head gene mutations, are present. A variable-length DNA segment leaks from some mutant heads, based on DNase I-protection assay and electron microscopy. The protected DNA segment has quantized lengths, based on restriction endonuclease analysis: six sharp bands of DNAmore » missing 3.7–12.3% of the last end packaged. Native gel electrophoresis confirms quantized DNA expulsion and, after removal of external DNA, provides evidence that capsid radius is the quantization-ruler. Capsid-based DNA length quantization possibly evolved via selection for stalling that provides time for feedback control during DNA packaging and injection. - Graphical abstract: Highlights: • We implement directed evolution- and DNA-sequencing-based phage assembly genetics. • We purify stable, mutant phage heads with a partially leaked mature DNA molecule. • Native gels and DNase-protection show leaked DNA segments to have quantized lengths. • Native gels after DNase I-removal of leaked DNA reveal the capsids to vary in radius. • Thus, we hypothesize leaked DNA quantization via variably quantized capsid radius.« less

Dimensional quantization effects in the thermodynamics of conductive filaments

NASA Astrophysics Data System (ADS)

Niraula, D.; Grice, C. R.; Karpov, V. G.

2018-06-01

We consider the physical effects of dimensional quantization in conductive filaments that underlie operations of some modern electronic devices. We show that, as a result of quantization, a sufficiently thin filament acquires a positive charge. Several applications of this finding include the host material polarization, the stability of filament constrictions, the equilibrium filament radius, polarity in device switching, and quantization of conductance.

Nearly associative deformation quantization

NASA Astrophysics Data System (ADS)

Vassilevich, Dmitri; Oliveira, Fernando Martins Costa

2018-04-01

We study several classes of non-associative algebras as possible candidates for deformation quantization in the direction of a Poisson bracket that does not satisfy Jacobi identities. We show that in fact alternative deformation quantization algebras require the Jacobi identities on the Poisson bracket and, under very general assumptions, are associative. At the same time, flexible deformation quantization algebras exist for any Poisson bracket.

Dimensional quantization effects in the thermodynamics of conductive filaments.

PubMed

Niraula, D; Grice, C R; Karpov, V G

2018-06-29

We consider the physical effects of dimensional quantization in conductive filaments that underlie operations of some modern electronic devices. We show that, as a result of quantization, a sufficiently thin filament acquires a positive charge. Several applications of this finding include the host material polarization, the stability of filament constrictions, the equilibrium filament radius, polarity in device switching, and quantization of conductance.

Face recognition via sparse representation of SIFT feature on hexagonal-sampling image

NASA Astrophysics Data System (ADS)

Zhang, Daming; Zhang, Xueyong; Li, Lu; Liu, Huayong

2018-04-01

This paper investigates a face recognition approach based on Scale Invariant Feature Transform (SIFT) feature and sparse representation. The approach takes advantage of SIFT which is local feature other than holistic feature in classical Sparse Representation based Classification (SRC) algorithm and possesses strong robustness to expression, pose and illumination variations. Since hexagonal image has more inherit merits than square image to make recognition process more efficient, we extract SIFT keypoint in hexagonal-sampling image. Instead of matching SIFT feature, firstly the sparse representation of each SIFT keypoint is given according the constructed dictionary; secondly these sparse vectors are quantized according dictionary; finally each face image is represented by a histogram and these so-called Bag-of-Words vectors are classified by SVM. Due to use of local feature, the proposed method achieves better result even when the number of training sample is small. In the experiments, the proposed method gave higher face recognition rather than other methods in ORL and Yale B face databases; also, the effectiveness of the hexagonal-sampling in the proposed method is verified.

Quantized transport and steady states of Floquet topological insulators

NASA Astrophysics Data System (ADS)

Esin, Iliya; Rudner, Mark S.; Refael, Gil; Lindner, Netanel H.

2018-06-01

Robust electronic edge or surface modes play key roles in the fascinating quantized responses exhibited by topological materials. Even in trivial materials, topological bands and edge states can be induced dynamically by a time-periodic drive. Such Floquet topological insulators (FTIs) inherently exist out of equilibrium; the extent to which they can host quantized transport, which depends on the steady-state population of their dynamically induced edge states, remains a crucial question. In this work, we obtain the steady states of two-dimensional FTIs in the presence of the natural dissipation mechanisms present in solid state systems. We give conditions under which the steady-state distribution resembles that of a topological insulator in the Floquet basis. In this state, the distribution in the Floquet edge modes exhibits a sharp feature akin to a Fermi level, while the bulk hosts a small density of excitations. We determine the regimes where topological edge-state transport persists and can be observed in FTIs.

Submonolayer Quantum Dot Infrared Photodetector

NASA Technical Reports Server (NTRS)

Ting, David Z.; Bandara, Sumith V.; Gunapala, Sarath D.; Chang, Yia-Chang

2010-01-01

A method has been developed for inserting submonolayer (SML) quantum dots (QDs) or SML QD stacks, instead of conventional Stranski-Krastanov (S-K) QDs, into the active region of intersubband photodetectors. A typical configuration would be InAs SML QDs embedded in thin layers of GaAs, surrounded by AlGaAs barriers. Here, the GaAs and the AlGaAs have nearly the same lattice constant, while InAs has a larger lattice constant. In QD infrared photodetector, the important quantization directions are in the plane perpendicular to the normal incidence radiation. In-plane quantization is what enables the absorption of normal incidence radiation. The height of the S-K QD controls the positions of the quantized energy levels, but is not critically important to the desired normal incidence absorption properties. The SML QD or SML QD stack configurations give more control of the structure grown, retains normal incidence absorption properties, and decreases the strain build-up to allow thicker active layers for higher quantum efficiency.

Topological quantization in units of the fine structure constant.

PubMed

Maciejko, Joseph; Qi, Xiao-Liang; Drew, H Dennis; Zhang, Shou-Cheng

2010-10-15

Fundamental topological phenomena in condensed matter physics are associated with a quantized electromagnetic response in units of fundamental constants. Recently, it has been predicted theoretically that the time-reversal invariant topological insulator in three dimensions exhibits a topological magnetoelectric effect quantized in units of the fine structure constant α=e²/ℏc. In this Letter, we propose an optical experiment to directly measure this topological quantization phenomenon, independent of material details. Our proposal also provides a way to measure the half-quantized Hall conductances on the two surfaces of the topological insulator independently of each other.

Multi-Objective Community Detection Based on Memetic Algorithm

PubMed Central

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

Multi-objective community detection based on memetic algorithm.

PubMed

Wu, Peng; Pan, Li

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

A novel computer-aided detection system for pulmonary nodule identification in CT images

NASA Astrophysics Data System (ADS)

Han, Hao; Li, Lihong; Wang, Huafeng; Zhang, Hao; Moore, William; Liang, Zhengrong

2014-03-01

Computer-aided detection (CADe) of pulmonary nodules from computer tomography (CT) scans is critical for assisting radiologists to identify lung lesions at an early stage. In this paper, we propose a novel approach for CADe of lung nodules using a two-stage vector quantization (VQ) scheme. The first-stage VQ aims to extract lung from the chest volume, while the second-stage VQ is designed to extract initial nodule candidates (INCs) within the lung volume. Then rule-based expert filtering is employed to prune obvious FPs from INCs, and the commonly-used support vector machine (SVM) classifier is adopted to further reduce the FPs. The proposed system was validated on 100 CT scans randomly selected from the 262 scans that have at least one juxta-pleural nodule annotation in the publicly available database - Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). The two-stage VQ only missed 2 out of the 207 nodules at agreement level 1, and the INCs detection for each scan took about 30 seconds in average. Expert filtering reduced FPs more than 18 times, while maintaining a sensitivity of 93.24%. As it is trivial to distinguish INCs attached to pleural wall versus not on wall, we investigated the feasibility of training different SVM classifiers to further reduce FPs from these two kinds of INCs. Experiment results indicated that SVM classification over the entire set of INCs was in favor of, where the optimal operating of our CADe system achieved a sensitivity of 89.4% at a specificity of 86.8%.

Computer Based Behavioral Biometric Authentication via Multi-Modal Fusion

DTIC Science & Technology

2013-03-01

the decisions made by each individual modality. Fusion of features is the simple concatenation of feature vectors from multiple modalities to be...of Features BayesNet MDL 330 LibSVM PCA 80 J48 Wrapper Evaluator 11 3.5.3 Ensemble Based Decision Level Fusion. In ensemble learning multiple ...The high fusion percentages validate our hypothesis that by combining features from multiple modalities, classification accuracy can be improved. As

On the Dequantization of Fedosov's Deformation Quantization

NASA Astrophysics Data System (ADS)

Karabegov, Alexander V.

2003-08-01

To each natural deformation quantization on a Poisson manifold M we associate a Poisson morphism from the formal neighborhood of the zero section of the cotangent bundle to M to the formal neighborhood of the diagonal of the product M x M~, where M~ is a copy of M with the opposite Poisson structure. We call it dequantization of the natural deformation quantization. Then we "dequantize" Fedosov's quantization.

Using game theory for perceptual tuned rate control algorithm in video coding

NASA Astrophysics Data System (ADS)

Luo, Jiancong; Ahmad, Ishfaq

2005-03-01

This paper proposes a game theoretical rate control technique for video compression. Using a cooperative gaming approach, which has been utilized in several branches of natural and social sciences because of its enormous potential for solving constrained optimization problems, we propose a dual-level scheme to optimize the perceptual quality while guaranteeing "fairness" in bit allocation among macroblocks. At the frame level, the algorithm allocates target bits to frames based on their coding complexity. At the macroblock level, the algorithm distributes bits to macroblocks by defining a bargaining game. Macroblocks play cooperatively to compete for shares of resources (bits) to optimize their quantization scales while considering the Human Visual System"s perceptual property. Since the whole frame is an entity perceived by viewers, macroblocks compete cooperatively under a global objective of achieving the best quality with the given bit constraint. The major advantage of the proposed approach is that the cooperative game leads to an optimal and fair bit allocation strategy based on the Nash Bargaining Solution. Another advantage is that it allows multi-objective optimization with multiple decision makers (macroblocks). The simulation results testify the algorithm"s ability to achieve accurate bit rate with good perceptual quality, and to maintain a stable buffer level.

Face verification system for Android mobile devices using histogram based features

NASA Astrophysics Data System (ADS)

Sato, Sho; Kobayashi, Kazuhiro; Chen, Qiu

2016-07-01

This paper proposes a face verification system that runs on Android mobile devices. In this system, facial image is captured by a built-in camera on the Android device firstly, and then face detection is implemented using Haar-like features and AdaBoost learning algorithm. The proposed system verify the detected face using histogram based features, which are generated by binary Vector Quantization (VQ) histogram using DCT coefficients in low frequency domains, as well as Improved Local Binary Pattern (Improved LBP) histogram in spatial domain. Verification results with different type of histogram based features are first obtained separately and then combined by weighted averaging. We evaluate our proposed algorithm by using publicly available ORL database and facial images captured by an Android tablet.

Feature weighting using particle swarm optimization for learning vector quantization classifier

NASA Astrophysics Data System (ADS)

Dongoran, A.; Rahmadani, S.; Zarlis, M.; Zakarias

2018-03-01

This paper discusses and proposes a method of feature weighting in classification assignments on competitive learning artificial neural network LVQ. The weighting feature method is the search for the weight of an attribute using the PSO so as to give effect to the resulting output. This method is then applied to the LVQ-Classifier and tested on the 3 datasets obtained from the UCI Machine Learning repository. Then an accuracy analysis will be generated by two approaches. The first approach using LVQ1, referred to as LVQ-Classifier and the second approach referred to as PSOFW-LVQ, is a proposed model. The result shows that the PSO algorithm is capable of finding attribute weights that increase LVQ-classifier accuracy.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop.

PubMed

Li, Lian-Hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop

PubMed Central

Li, Lian-hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility. PMID:26414758

High intensity multi beam design of SANS instrument for Dhruva reactor

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

Abbas, Sohrab, E-mail: abbas@barc.gov.in; Aswal, V. K.; Désert, S.

A new and versatile design of Small Angle Neutron Scattering (SANS) instrument based on utilization of multi-beam is presented. The multi-pinholes and multi-slits as SANS collimator for medium flux Dhruva rearctor have been proposed and their designs have been validated using McStas simulations. Various instrument configurations to achieve different minimum wave vector transfers in scattering experiments are envisioned. These options enable smooth access to minimum wave vector transfers as low as ~ 6×10{sup −4} Å{sup −1} with a significant improvement in neutron intensity, allowing faster measurements. Such angularly well defined and intense neutron beam will allow faster SANS studies ofmore » agglomerates larger than few tens of nm.« less

New adaptive color quantization method based on self-organizing maps.

PubMed

Chang, Chip-Hong; Xu, Pengfei; Xiao, Rui; Srikanthan, Thambipillai

2005-01-01

Color quantization (CQ) is an image processing task popularly used to convert true color images to palletized images for limited color display devices. To minimize the contouring artifacts introduced by the reduction of colors, a new competitive learning (CL) based scheme called the frequency sensitive self-organizing maps (FS-SOMs) is proposed to optimize the color palette design for CQ. FS-SOM harmonically blends the neighborhood adaptation of the well-known self-organizing maps (SOMs) with the neuron dependent frequency sensitive learning model, the global butterfly permutation sequence for input randomization, and the reinitialization of dead neurons to harness effective utilization of neurons. The net effect is an improvement in adaptation, a well-ordered color palette, and the alleviation of underutilization problem, which is the main cause of visually perceivable artifacts of CQ. Extensive simulations have been performed to analyze and compare the learning behavior and performance of FS-SOM against other vector quantization (VQ) algorithms. The results show that the proposed FS-SOM outperforms classical CL, Linde, Buzo, and Gray (LBG), and SOM algorithms. More importantly, FS-SOM achieves its superiority in reconstruction quality and topological ordering with a much greater robustness against variations in network parameters than the current art SOM algorithm for CQ. A most significant bit (MSB) biased encoding scheme is also introduced to reduce the number of parallel processing units. By mapping the pixel values as sign-magnitude numbers and biasing the magnitudes according to their sign bits, eight lattice points in the color space are condensed into one common point density function. Consequently, the same processing element can be used to map several color clusters and the entire FS-SOM network can be substantially scaled down without severely scarifying the quality of the displayed image. The drawback of this encoding scheme is the additional storage overhead, which can be cut down by leveraging on existing encoder in an overall lossy compression scheme.

A novel retinal vessel extraction algorithm based on matched filtering and gradient vector flow

NASA Astrophysics Data System (ADS)

Yu, Lei; Xia, Mingliang; Xuan, Li

2013-10-01

The microvasculature network of retina plays an important role in the study and diagnosis of retinal diseases (age-related macular degeneration and diabetic retinopathy for example). Although it is possible to noninvasively acquire high-resolution retinal images with modern retinal imaging technologies, non-uniform illumination, the low contrast of thin vessels and the background noises all make it difficult for diagnosis. In this paper, we introduce a novel retinal vessel extraction algorithm based on gradient vector flow and matched filtering to segment retinal vessels with different likelihood. Firstly, we use isotropic Gaussian kernel and adaptive histogram equalization to smooth and enhance the retinal images respectively. Secondly, a multi-scale matched filtering method is adopted to extract the retinal vessels. Then, the gradient vector flow algorithm is introduced to locate the edge of the retinal vessels. Finally, we combine the results of matched filtering method and gradient vector flow algorithm to extract the vessels at different likelihood levels. The experiments demonstrate that our algorithm is efficient and the intensities of vessel images exactly represent the likelihood of the vessels.

Quantum Computing and Second Quantization

DOE PAGES

Makaruk, Hanna Ewa

2017-02-10

Quantum computers are by their nature many particle quantum systems. Both the many-particle arrangement and being quantum are necessary for the existence of the entangled states, which are responsible for the parallelism of the quantum computers. Second quantization is a very important approximate method of describing such systems. This lecture will present the general idea of the second quantization, and discuss shortly some of the most important formulations of second quantization.

Quantum Computing and Second Quantization

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

Makaruk, Hanna Ewa

Quantum computers are by their nature many particle quantum systems. Both the many-particle arrangement and being quantum are necessary for the existence of the entangled states, which are responsible for the parallelism of the quantum computers. Second quantization is a very important approximate method of describing such systems. This lecture will present the general idea of the second quantization, and discuss shortly some of the most important formulations of second quantization.

Stochastic quantization of (λϕ4)d scalar theory: Generalized Langevin equation with memory kernel

NASA Astrophysics Data System (ADS)

Menezes, G.; Svaiter, N. F.

2007-02-01

The method of stochastic quantization for a scalar field theory is reviewed. A brief survey for the case of self-interacting scalar field, implementing the stochastic perturbation theory up to the one-loop level, is presented. Then, it is introduced a colored random noise in the Einstein's relations, a common prescription employed by one of the stochastic regularizations, to control the ultraviolet divergences of the theory. This formalism is extended to the case where a Langevin equation with a memory kernel is used. It is shown that, maintaining the Einstein's relations with a colored noise, there is convergence to a non-regularized theory.

Semiclassical theory of Landau levels and magnetic breakdown in topological metals

NASA Astrophysics Data System (ADS)

Alexandradinata, A.; Glazman, Leonid

2018-04-01

The Bohr-Sommerfeld quantization rule lies at the heart of the semiclassical theory of a Bloch electron in a magnetic field. This rule is predictive of Landau levels and de Haas-van Alphen oscillations for conventional metals, as well as for a host of topological metals which have emerged in the recent intercourse between band theory, crystalline symmetries, and topology. The essential ingredients in any quantization rule are connection formulas that match the semiclassical (WKB) wave function across regions of strong quantum fluctuations. Here, we propose (a) a multicomponent WKB wave function that describes transport within degenerate-band subspaces, and (b) the requisite connection formulas for saddle points and type-II Dirac points, where tunneling respectively occurs within the same band, and between distinct bands. (a) and (b) extend previous works by incorporating phase corrections that are subleading in powers of the field; these corrections include the geometric Berry phase, and account for the orbital magnetic moment and the Zeeman coupling. A comprehensive symmetry analysis is performed for such phase corrections occurring in closed orbits, which is applicable to solids in any (magnetic) space group. We have further formulated a graph-theoretic description of semiclassical orbits. This allows us to systematize the construction of quantization rules for a large class of closed orbits (with or without tunneling), as well as to formulate the notion of a topological invariant in semiclassical magnetotransport—as a quantity that is invariant under continuous deformations of the graph. Landau levels in the presence of tunneling are generically quasirandom, i.e., disordered on the scale of nearest-neighbor level spacings but having longer-ranged correlations; we develop a perturbative theory to determine Landau levels in such quasirandom spectra.

Image-adapted visually weighted quantization matrices for digital image compression

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1994-01-01

A method for performing image compression that eliminates redundant and invisible image components is presented. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

A multi-layered mechanistic modelling approach to understand how effector genes extend beyond phytoplasma to modulate plant hosts, insect vectors and the environment.

PubMed

Tomkins, Melissa; Kliot, Adi; Marée, Athanasius Fm; Hogenhout, Saskia A

2018-03-13

Members of the Candidatus genus Phytoplasma are small bacterial pathogens that hijack their plant hosts via the secretion of virulence proteins (effectors) leading to a fascinating array of plant phenotypes, such as witch's brooms (stem proliferations) and phyllody (retrograde development of flowers into vegetative tissues). Phytoplasma depend on insect vectors for transmission, and interestingly, these insect vectors were found to be (in)directly attracted to plants with these phenotypes. Therefore, phytoplasma effectors appear to reprogram plant development and defence to lure insect vectors, similarly to social engineering malware, which employs tricks to lure people to infected computers and webpages. A multi-layered mechanistic modelling approach will enable a better understanding of how phytoplasma effector-mediated modulations of plant host development and insect vector behaviour contribute to phytoplasma spread, and ultimately to predict the long reach of phytoplasma effector genes. Copyright © 2018. Published by Elsevier Ltd.

Generic absence of strong singularities in loop quantum Bianchi-IX spacetimes

NASA Astrophysics Data System (ADS)

Saini, Sahil; Singh, Parampreet

2018-03-01

We study the generic resolution of strong singularities in loop quantized effective Bianchi-IX spacetime in two different quantizations—the connection operator based ‘A’ quantization and the extrinsic curvature based ‘K’ quantization. We show that in the effective spacetime description with arbitrary matter content, it is necessary to include inverse triad corrections to resolve all the strong singularities in the ‘A’ quantization. Whereas in the ‘K’ quantization these results can be obtained without including inverse triad corrections. Under these conditions, the energy density, expansion and shear scalars for both of the quantization prescriptions are bounded. Notably, both the quantizations can result in potentially curvature divergent events if matter content allows divergences in the partial derivatives of the energy density with respect to the triad variables at a finite energy density. Such events are found to be weak curvature singularities beyond which geodesics can be extended in the effective spacetime. Our results show that all potential strong curvature singularities of the classical theory are forbidden in Bianchi-IX spacetime in loop quantum cosmology and geodesic evolution never breaks down for such events.

FPGA-Based Efficient Hardware/Software Co-Design for Industrial Systems with Consideration of Output Selection

NASA Astrophysics Data System (ADS)

Deliparaschos, Kyriakos M.; Michail, Konstantinos; Zolotas, Argyrios C.; Tzafestas, Spyros G.

2016-05-01

This work presents a field programmable gate array (FPGA)-based embedded software platform coupled with a software-based plant, forming a hardware-in-the-loop (HIL) that is used to validate a systematic sensor selection framework. The systematic sensor selection framework combines multi-objective optimization, linear-quadratic-Gaussian (LQG)-type control, and the nonlinear model of a maglev suspension. A robustness analysis of the closed-loop is followed (prior to implementation) supporting the appropriateness of the solution under parametric variation. The analysis also shows that quantization is robust under different controller gains. While the LQG controller is implemented on an FPGA, the physical process is realized in a high-level system modeling environment. FPGA technology enables rapid evaluation of the algorithms and test designs under realistic scenarios avoiding heavy time penalty associated with hardware description language (HDL) simulators. The HIL technique facilitates significant speed-up in the required execution time when compared to its software-based counterpart model.

Comparative study of the requantization of the time-dependent mean field for the dynamics of nuclear pairing

NASA Astrophysics Data System (ADS)

Ni, Fang; Nakatsukasa, Takashi

2018-04-01

To describe quantal collective phenomena, it is useful to requantize the time-dependent mean-field dynamics. We study the time-dependent Hartree-Fock-Bogoliubov (TDHFB) theory for the two-level pairing Hamiltonian, and compare results of different quantization methods. The one constructing microscopic wave functions, using the TDHFB trajectories fulfilling the Einstein-Brillouin-Keller quantization condition, turns out to be the most accurate. The method is based on the stationary-phase approximation to the path integral. We also examine the performance of the collective model which assumes that the pairing gap parameter is the collective coordinate. The applicability of the collective model is limited for the nuclear pairing with a small number of single-particle levels, because the pairing gap parameter represents only a half of the pairing collective space.

Anti-resonance scattering at defect levels in the quantum conductance of a one-dimensional system

NASA Astrophysics Data System (ADS)

Sun, Z. Z.; Wang, Y. P.; Wang, X. R.

2002-03-01

For the ballistic quantum transport, the conductance of one channel is quantized to a value of 2e^2/h described by the Landauer formula. In the presence of defects, electrons will be scattered by these defects. Thus the conductance will deviate from the values of the quantized conductance. We show that an anti-resonance scattering can occur when an extra defect level is introduced into a conduction band. At the anti-resonance scattering, exact one quantum conductance is destroyed. The conductance takes a non-zero value when the Fermi energy is away from the anti-resonance scattering. The result is consistent with recent numerical calculations given by H. J. Choi et al. (Phys. Rev. Lett. 84, 2917(2000)) and P. L. McEuen et al. (Phys. Rev. Lett. 83, 5098(1999)).

Assessing the vulnerability of Brazilian municipalities to the vectorial transmission of Trypanosoma cruzi using multi-criteria decision analysis.

PubMed

Vinhaes, Márcio Costa; de Oliveira, Stefan Vilges; Reis, Priscilleyne Ouverney; de Lacerda Sousa, Ana Carolina; Silva, Rafaella Albuquerque E; Obara, Marcos Takashi; Bezerra, Cláudia Mendonça; da Costa, Veruska Maia; Alves, Renato Vieira; Gurgel-Gonçalves, Rodrigo

2014-09-01

Despite the dramatic reduction in Trypanosoma cruzi vectorial transmission in Brazil, acute cases of Chagas disease (CD) continue to be recorded. The identification of areas with greater vulnerability to the occurrence of vector-borne CD is essential to prevention, control, and surveillance activities. In the current study, data on the occurrence of domiciliated triatomines in Brazil (non-Amazonian regions) between 2007 and 2011 were analyzed. Municipalities' vulnerability was assessed based on socioeconomic, demographic, entomological, and environmental indicators using multi-criteria decision analysis (MCDA). Overall, 2275 municipalities were positive for at least one of the six triatomine species analyzed (Panstrongylus megistus, Triatoma infestans, Triatoma brasiliensis, Triatoma pseudomaculata, Triatoma rubrovaria, and Triatoma sordida). The municipalities that were most vulnerable to vector-borne CD were mainly in the northeast region and exhibited a higher occurrence of domiciliated triatomines, lower socioeconomic levels, and more extensive anthropized areas. Most of the 39 new vector-borne CD cases confirmed between 2001 and 2012 in non-Amazonian regions occurred within the more vulnerable municipalities. Thus, MCDA can help to identify the states and municipalities that are most vulnerable to the transmission of T. cruzi by domiciliated triatomines, which is critical for directing adequate surveillance, prevention, and control activities. The methodological approach and results presented here can be used to enhance CD surveillance in Brazil. Copyright © 2014 Elsevier B.V. All rights reserved.

A spatially explicit metapopulation model and cattle trade analysis suggests key determinants for the recurrent circulation of rift valley Fever virus in a pilot area of madagascar highlands.

PubMed

Nicolas, Gaëlle; Chevalier, Véronique; Tantely, Luciano Michaël; Fontenille, Didier; Durand, Benoît

2014-12-01

Rift Valley fever (RVF) is a vector-borne zoonotic disease that causes high morbidity and mortality in ruminants. In 2008-2009, a RVF outbreak affected the whole Madagascar island, including the Anjozorobe district located in Madagascar highlands. An entomological survey showed the absence of Aedes among the potential RVF virus (RVFV) vector species identified in this area, and an overall low abundance of mosquitoes due to unfavorable climatic conditions during winter. No serological nor virological sign of infection was observed in wild terrestrial mammals of the area, suggesting an absence of wild RVF virus (RVFV) reservoir. However, a three years serological and virological follow-up in cattle showed a recurrent RVFV circulation. The objective of this study was to understand the key determinants of this unexpected recurrent transmission. To achieve this goal, a spatial deterministic discrete-time metapopulation model combined with cattle trade network was designed and parameterized to reproduce the local conditions using observational data collected in the area. Three scenarios that could explain the RVFV recurrent circulation in the area were analyzed: (i) RVFV overwintering thanks to a direct transmission between cattle when viraemic cows calve, vectors being absent during the winter, (ii) a low level vector-based circulation during winter thanks to a residual vector population, without direct transmission between cattle, (iii) combination of both above mentioned mechanisms. Multi-model inference methods resulted in a model incorporating both a low level RVFV winter vector-borne transmission and a direct transmission between animals when viraemic cows calve. Predictions satisfactorily reproduced field observations, 84% of cattle infections being attributed to vector-borne transmission, and 16% to direct transmission. These results appeared robust according to the sensitivity analysis. Interweaving between agricultural works in rice fields, seasonality of vector proliferation, and cattle exchange practices could be a key element for understanding RVFV circulation in this area of Madagascar highlands.

Pseudo-Kähler Quantization on Flag Manifolds

NASA Astrophysics Data System (ADS)

Karabegov, Alexander V.

A unified approach to geometric, symbol and deformation quantizations on a generalized flag manifold endowed with an invariant pseudo-Kähler structure is proposed. In particular cases we arrive at Berezin's quantization via covariant and contravariant symbols.

Instant-Form and Light-Front Quantization of Field Theories

NASA Astrophysics Data System (ADS)

Kulshreshtha, Usha; Kulshreshtha, Daya Shankar; Vary, James

2018-05-01

In this work we consider the instant-form and light-front quantization of some field theories. As an example, we consider a class of gauged non-linear sigma models with different regularizations. In particular, we present the path integral quantization of the gauged non-linear sigma model in the Faddeevian regularization. We also make a comparision of the possible differences in the instant-form and light-front quantization at appropriate places.

Quantization improves stabilization of dynamical systems with delayed feedback

NASA Astrophysics Data System (ADS)

Stepan, Gabor; Milton, John G.; Insperger, Tamas

2017-11-01

We show that an unstable scalar dynamical system with time-delayed feedback can be stabilized by quantizing the feedback. The discrete time model corresponds to a previously unrecognized case of the microchaotic map in which the fixed point is both locally and globally repelling. In the continuous-time model, stabilization by quantization is possible when the fixed point in the absence of feedback is an unstable node, and in the presence of feedback, it is an unstable focus (spiral). The results are illustrated with numerical simulation of the unstable Hayes equation. The solutions of the quantized Hayes equation take the form of oscillations in which the amplitude is a function of the size of the quantization step. If the quantization step is sufficiently small, the amplitude of the oscillations can be small enough to practically approximate the dynamics around a stable fixed point.

On Correspondence of BRST-BFV, Dirac, and Refined Algebraic Quantizations of Constrained Systems

NASA Astrophysics Data System (ADS)

Shvedov, O. Yu.

2002-11-01

The correspondence between BRST-BFV, Dirac, and refined algebraic (group averaging, projection operator) approaches to quantizing constrained systems is analyzed. For the closed-algebra case, it is shown that the component of the BFV wave function corresponding to maximal (minimal) value of number of ghosts and antighosts in the Schrodinger representation may be viewed as a wave function in the refined algebraic (Dirac) quantization approach. The Giulini-Marolf group averaging formula for the inner product in the refined algebraic quantization approach is obtained from the Batalin-Marnelius prescription for the BRST-BFV inner product, which should be generally modified due to topological problems. The considered prescription for the correspondence of states is observed to be applicable to the open-algebra case. The refined algebraic quantization approach is generalized then to the case of nontrivial structure functions. A simple example is discussed. The correspondence of observables for different quantization methods is also investigated.

Quantization of geometric phase with integer and fractional topological characterization in a quantum Ising chain with long-range interaction.

PubMed

Sarkar, Sujit

2018-04-12

An attempt is made to study and understand the behavior of quantization of geometric phase of a quantum Ising chain with long range interaction. We show the existence of integer and fractional topological characterization for this model Hamiltonian with different quantization condition and also the different quantized value of geometric phase. The quantum critical lines behave differently from the perspective of topological characterization. The results of duality and its relation to the topological quantization is presented here. The symmetry study for this model Hamiltonian is also presented. Our results indicate that the Zak phase is not the proper physical parameter to describe the topological characterization of system with long range interaction. We also present quite a few exact solutions with physical explanation. Finally we present the relation between duality, symmetry and topological characterization. Our work provides a new perspective on topological quantization.

Polar Cooperative Navigation Algorithm for Multi-Unmanned Underwater Vehicles Considering Communication Delays.

PubMed

Yan, Zheping; Wang, Lu; Wang, Tongda; Yang, Zewen; Chen, Tao; Xu, Jian

2018-03-30

To solve the navigation accuracy problems of multi-Unmanned Underwater Vehicles (multi-UUVs) in the polar region, a polar cooperative navigation algorithm for multi-UUVs considering communication delays is proposed in this paper. UUVs are important pieces of equipment in ocean engineering for marine development. For UUVs to complete missions, precise navigation is necessary. It is difficult for UUVs to establish true headings because of the rapid convergence of Earth meridians and the severe polar environment. Based on the polar grid navigation algorithm, UUV navigation in the polar region can be accomplished with the Strapdown Inertial Navigation System (SINS) in the grid frame. To save costs, a leader-follower type of system is introduced in this paper. The leader UUV helps the follower UUVs to achieve high navigation accuracy. Follower UUVs correct their own states based on the information sent by the leader UUV and the relative position measured by ultra-short baseline (USBL) acoustic positioning. The underwater acoustic communication delay is quantized by the model. In this paper, considering underwater acoustic communication delay, the conventional adaptive Kalman filter (AKF) is modified to adapt to polar cooperative navigation. The results demonstrate that the polar cooperative navigation algorithm for multi-UUVs that considers communication delays can effectively navigate the sailing of multi-UUVs in the polar region.

Polar Cooperative Navigation Algorithm for Multi-Unmanned Underwater Vehicles Considering Communication Delays

PubMed Central

Yan, Zheping; Wang, Lu; Wang, Tongda; Yang, Zewen; Chen, Tao; Xu, Jian

2018-01-01

To solve the navigation accuracy problems of multi-Unmanned Underwater Vehicles (multi-UUVs) in the polar region, a polar cooperative navigation algorithm for multi-UUVs considering communication delays is proposed in this paper. UUVs are important pieces of equipment in ocean engineering for marine development. For UUVs to complete missions, precise navigation is necessary. It is difficult for UUVs to establish true headings because of the rapid convergence of Earth meridians and the severe polar environment. Based on the polar grid navigation algorithm, UUV navigation in the polar region can be accomplished with the Strapdown Inertial Navigation System (SINS) in the grid frame. To save costs, a leader-follower type of system is introduced in this paper. The leader UUV helps the follower UUVs to achieve high navigation accuracy. Follower UUVs correct their own states based on the information sent by the leader UUV and the relative position measured by ultra-short baseline (USBL) acoustic positioning. The underwater acoustic communication delay is quantized by the model. In this paper, considering underwater acoustic communication delay, the conventional adaptive Kalman filter (AKF) is modified to adapt to polar cooperative navigation. The results demonstrate that the polar cooperative navigation algorithm for multi-UUVs that considers communication delays can effectively navigate the sailing of multi-UUVs in the polar region. PMID:29601537

Spacetime algebra as a powerful tool for electromagnetism

NASA Astrophysics Data System (ADS)

Dressel, Justin; Bliokh, Konstantin Y.; Nori, Franco

2015-08-01

We present a comprehensive introduction to spacetime algebra that emphasizes its practicality and power as a tool for the study of electromagnetism. We carefully develop this natural (Clifford) algebra of the Minkowski spacetime geometry, with a particular focus on its intrinsic (and often overlooked) complex structure. Notably, the scalar imaginary that appears throughout the electromagnetic theory properly corresponds to the unit 4-volume of spacetime itself, and thus has physical meaning. The electric and magnetic fields are combined into a single complex and frame-independent bivector field, which generalizes the Riemann-Silberstein complex vector that has recently resurfaced in studies of the single photon wavefunction. The complex structure of spacetime also underpins the emergence of electromagnetic waves, circular polarizations, the normal variables for canonical quantization, the distinction between electric and magnetic charge, complex spinor representations of Lorentz transformations, and the dual (electric-magnetic field exchange) symmetry that produces helicity conservation in vacuum fields. This latter symmetry manifests as an arbitrary global phase of the complex field, motivating the use of a complex vector potential, along with an associated transverse and gauge-invariant bivector potential, as well as complex (bivector and scalar) Hertz potentials. Our detailed treatment aims to encourage the use of spacetime algebra as a readily available and mature extension to existing vector calculus and tensor methods that can greatly simplify the analysis of fundamentally relativistic objects like the electromagnetic field.

Particle definitions and the information loss paradox

NASA Astrophysics Data System (ADS)

Venditti, Alex

An investigation of information loss in black hole spacetimes is performed. We demonstrate that the definition of particles as energy levels of the Harmonic oscillator will not have physical significance in general and is thus not a good instrument to study the radiation of black holes. This is due to the ambiguity of the choice of coordinates on the phase space of the quantum field. We demonstrate how to identify quantum states in the functional Schrodinger picture. We demonstrate that information is truly lost in the case of a Vaidya black hole (a black hole formed from null dust) if we neglect back reaction. This is done by quantizing the constrained classical system of a Klein-Gordon field in a Vaidya background. The interaction picture of quantum mechanics can be applied to this system. We find a physically well motivated vacuum state for a spherically symmetric spacetime with an extra conformal Killing vector. We also demonstrate how to calculate the response of a particle detector in the a LeMaitre-Tolman-Bondi spacetime with a selfsimilarity. Finally, some of the claims and confusion surrounding Unruh radiation, Hawking radiation and the equivalence principle are investigated and shown to be false.

Multigrid Equation Solvers for Large Scale Nonlinear Finite Element Simulations

DTIC Science & Technology

1999-01-01

purpose of the second partitioning phase , on each SMP, is to minimize the communication within the SMP; even if a multi - threaded matrix vector product...8.7 Comparison of model with experimental data for send phase of matrix vector product on ne grid...140 8.4 Matrix vector product phase times : : : : : : : : : : : : : : : : : : : : : : : 145 9.1 Flat and

From classical to quantum mechanics: ``How to translate physical ideas into mathematical language''

NASA Astrophysics Data System (ADS)

Bergeron, H.

2001-09-01

Following previous works by E. Prugovečki [Physica A 91A, 202 (1978) and Stochastic Quantum Mechanics and Quantum Space-time (Reidel, Dordrecht, 1986)] on common features of classical and quantum mechanics, we develop a unified mathematical framework for classical and quantum mechanics (based on L2-spaces over classical phase space), in order to investigate to what extent quantum mechanics can be obtained as a simple modification of classical mechanics (on both logical and analytical levels). To obtain this unified framework, we split quantum theory in two parts: (i) general quantum axiomatics (a system is described by a state in a Hilbert space, observables are self-adjoints operators, and so on) and (ii) quantum mechanics proper that specifies the Hilbert space as L2(Rn); the Heisenberg rule [pi,qj]=-iℏδij with p=-iℏ∇, the free Hamiltonian H=-ℏ2Δ/2m and so on. We show that general quantum axiomatics (up to a supplementary "axiom of classicity") can be used as a nonstandard mathematical ground to formulate physical ideas and equations of ordinary classical statistical mechanics. So, the question of a "true quantization" with "ℏ" must be seen as an independent physical problem not directly related with quantum formalism. At this stage, we show that this nonstandard formulation of classical mechanics exhibits a new kind of operation that has no classical counterpart: this operation is related to the "quantization process," and we show why quantization physically depends on group theory (the Galilei group). This analytical procedure of quantization replaces the "correspondence principle" (or canonical quantization) and allows us to map classical mechanics into quantum mechanics, giving all operators of quantum dynamics and the Schrödinger equation. The great advantage of this point of view is that quantization is based on concrete physical arguments and not derived from some "pure algebraic rule" (we exhibit also some limit of the correspondence principle). Moreover spins for particles are naturally generated, including an approximation of their interaction with magnetic fields. We also recover by this approach the semi-classical formalism developed by E. Prugovečki [Stochastic Quantum Mechanics and Quantum Space-time (Reidel, Dordrecht, 1986)].

PGA/MOEAD: a preference-guided evolutionary algorithm for multi-objective decision-making problems with interval-valued fuzzy preferences

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin; Zhong, ShiSheng

2018-02-01

In this research, we propose a preference-guided optimisation algorithm for multi-criteria decision-making (MCDM) problems with interval-valued fuzzy preferences. The interval-valued fuzzy preferences are decomposed into a series of precise and evenly distributed preference-vectors (reference directions) regarding the objectives to be optimised on the basis of uniform design strategy firstly. Then the preference information is further incorporated into the preference-vectors based on the boundary intersection approach, meanwhile, the MCDM problem with interval-valued fuzzy preferences is reformulated into a series of single-objective optimisation sub-problems (each sub-problem corresponds to a decomposed preference-vector). Finally, a preference-guided optimisation algorithm based on MOEA/D (multi-objective evolutionary algorithm based on decomposition) is proposed to solve the sub-problems in a single run. The proposed algorithm incorporates the preference-vectors within the optimisation process for guiding the search procedure towards a more promising subset of the efficient solutions matching the interval-valued fuzzy preferences. In particular, lots of test instances and an engineering application are employed to validate the performance of the proposed algorithm, and the results demonstrate the effectiveness and feasibility of the algorithm.

Vista/F-16 Multi-Axis Thrust Vectoring (MATV) control law design and evaluation

NASA Technical Reports Server (NTRS)

Zwerneman, W. D.; Eller, B. G.

1994-01-01

For the Multi-Axis Thrust Vectoring (MATV) program, a new control law was developed using multi-axis thrust vectoring to augment the aircraft's aerodynamic control power to provide maneuverability above the normal F-16 angle of attack limit. The control law architecture was developed using Lockheed Fort Worth's offline and piloted simulation capabilities. The final flight control laws were used in flight test to demonstrate tactical benefits gained by using thrust vectoring in air-to-air combat. Differences between the simulator aerodynamics data base and the actual aircraft aerodynamics led to significantly different lateral-directional flying qualities during the flight test program than those identified during piloted simulation. A 'dial-a-gain' flight test control law update was performed in the middle of the flight test program. This approach allowed for inflight optimization of the aircraft's flying qualities. While this approach is not preferred over updating the simulator aerodynamic data base and then updating the control laws, the final selected gain set did provide adequate lateral-directional flying qualities over the MATV flight envelope. The resulting handling qualities and the departure resistance of the aircraft allowed the 422nd_squadron pilots to focus entirely on evaluating the aircraft's tactical utility.

Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

NASA Astrophysics Data System (ADS)

Hosseini-Golgoo, S. M.; Bozorgi, H.; Saberkari, A.

2015-06-01

Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively.

Noncommutative gerbes and deformation quantization

NASA Astrophysics Data System (ADS)

Aschieri, Paolo; Baković, Igor; Jurčo, Branislav; Schupp, Peter

2010-11-01

We define noncommutative gerbes using the language of star products. Quantized twisted Poisson structures are discussed as an explicit realization in the sense of deformation quantization. Our motivation is the noncommutative description of D-branes in the presence of topologically non-trivial background fields.

Quantized discrete space oscillators

NASA Technical Reports Server (NTRS)

Uzes, C. A.; Kapuscik, Edward

1993-01-01

A quasi-canonical sequence of finite dimensional quantizations was found which has canonical quantization as its limit. In order to demonstrate its practical utility and its numerical convergence, this formalism is applied to the eigenvalue and 'eigenfunction' problem of several harmonic and anharmonic oscillators.

Solving the multi-frequency electromagnetic inverse source problem by the Fourier method

NASA Astrophysics Data System (ADS)

Wang, Guan; Ma, Fuming; Guo, Yukun; Li, Jingzhi

2018-07-01

This work is concerned with an inverse problem of identifying the current source distribution of the time-harmonic Maxwell's equations from multi-frequency measurements. Motivated by the Fourier method for the scalar Helmholtz equation and the polarization vector decomposition, we propose a novel method for determining the source function in the full vector Maxwell's system. Rigorous mathematical justifications of the method are given and numerical examples are provided to demonstrate the feasibility and effectiveness of the method.

A simple and reliable multi-gene transformation method for switchgrass.

PubMed

Ogawa, Yoichi; Shirakawa, Makoto; Koumoto, Yasuko; Honda, Masaho; Asami, Yuki; Kondo, Yasuhiro; Hara-Nishimura, Ikuko

2014-07-01

A simple and reliable Agrobacterium -mediated transformation method was developed for switchgrass. Using this method, many transgenic plants carrying multiple genes-of-interest could be produced without untransformed escape. Switchgrass (Panicum virgatum L.) is a promising biomass crop for bioenergy. To obtain transgenic switchgrass plants carrying a multi-gene trait in a simple manner, an Agrobacterium-mediated transformation method was established by constructing a Gateway-based binary vector, optimizing transformation conditions and developing a novel selection method. A MultiRound Gateway-compatible destination binary vector carrying the bar selectable marker gene, pHKGB110, was constructed to introduce multiple genes of interest in a single transformation. Two reporter gene expression cassettes, GUSPlus and gfp, were constructed independently on two entry vectors and then introduced into a single T-DNA region of pHKGB110 via sequential LR reactions. Agrobacterium tumefaciens EHA101 carrying the resultant binary vector pHKGB112 and caryopsis-derived compact embryogenic calli were used for transformation experiments. Prolonged cocultivation for 7 days followed by cultivation on media containing meropenem improved transformation efficiency without overgrowth of Agrobacterium, which was, however, not inhibited by cefotaxime or Timentin. In addition, untransformed escape shoots were completely eliminated during the rooting stage by direct dipping the putatively transformed shoots into the herbicide Basta solution for a few seconds, designated as the 'herbicide dipping method'. It was also demonstrated that more than 90 % of the bar-positive transformants carried both reporters delivered from pHKGB112. This simple and reliable transformation method, which incorporates a new selection technique and the use of a MultiRound Gateway-based binary vector, would be suitable for producing a large number of transgenic lines carrying multiple genes.

HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2014-01-01

Protein subcellular localization prediction, as an essential step to elucidate the functions in vivo of proteins and identify drugs targets, has been extensively studied in previous decades. Instead of only determining subcellular localization of single-label proteins, recent studies have focused on predicting both single- and multi-location proteins. Computational methods based on Gene Ontology (GO) have been demonstrated to be superior to methods based on other features. However, existing GO-based methods focus on the occurrences of GO terms and disregard their relationships. This paper proposes a multi-label subcellular-localization predictor, namely HybridGO-Loc, that leverages not only the GO term occurrences but also the inter-term relationships. This is achieved by hybridizing the GO frequencies of occurrences and the semantic similarity between GO terms. Given a protein, a set of GO terms are retrieved by searching against the gene ontology database, using the accession numbers of homologous proteins obtained via BLAST search as the keys. The frequency of GO occurrences and semantic similarity (SS) between GO terms are used to formulate frequency vectors and semantic similarity vectors, respectively, which are subsequently hybridized to construct fusion vectors. An adaptive-decision based multi-label support vector machine (SVM) classifier is proposed to classify the fusion vectors. Experimental results based on recent benchmark datasets and a new dataset containing novel proteins show that the proposed hybrid-feature predictor significantly outperforms predictors based on individual GO features as well as other state-of-the-art predictors. For readers' convenience, the HybridGO-Loc server, which is for predicting virus or plant proteins, is available online at http://bioinfo.eie.polyu.edu.hk/HybridGoServer/.

Thermal field theory and generalized light front quantization

NASA Astrophysics Data System (ADS)

Weldon, H. Arthur

2003-04-01

The dependence of thermal field theory on the surface of quantization and on the velocity of the heat bath is investigated by working in general coordinates that are arbitrary linear combinations of the Minkowski coordinates. In the general coordinates the metric tensor gμν¯ is nondiagonal. The Kubo-Martin-Schwinger condition requires periodicity in thermal correlation functions when the temporal variable changes by an amount -i/(T(g00¯)). Light-front quantization fails since g00¯=0; however, various related quantizations are possible.

Multi-Spectral Stereo Atmospheric Remote Sensing (STARS) for Retrieval of Cloud Properties and Cloud-Motion Vectors

NASA Astrophysics Data System (ADS)

Kelly, M. A.; Boldt, J.; Wilson, J. P.; Yee, J. H.; Stoffler, R.

2017-12-01

The multi-spectral STereo Atmospheric Remote Sensing (STARS) concept has the objective to provide high-spatial and -temporal-resolution observations of 3D cloud structures related to hurricane development and other severe weather events. The rapid evolution of severe weather demonstrates a critical need for mesoscale observations of severe weather dynamics, but such observations are rare, particularly over the ocean where extratropical and tropical cyclones can undergo explosive development. Coincident space-based measurements of wind velocity and cloud properties at the mesoscale remain a great challenge, but are critically needed to improve the understanding and prediction of severe weather and cyclogenesis. STARS employs a mature stereoscopic imaging technique on two satellites (e.g. two CubeSats, two hosted payloads) to simultaneously retrieve cloud motion vectors (CMVs), cloud-top temperatures (CTTs), and cloud geometric heights (CGHs) from multi-angle, multi-spectral observations of cloud features. STARS is a pushbroom system based on separate wide-field-of-view co-boresighted multi-spectral cameras in the visible, midwave infrared (MWIR), and longwave infrared (LWIR) with high spatial resolution (better than 1 km). The visible system is based on a pan-chromatic, low-light imager to resolve cloud structures under nighttime illumination down to ¼ moon. The MWIR instrument, which is being developed as a NASA ESTO Instrument Incubator Program (IIP) project, is based on recent advances in MWIR detector technology that requires only modest cooling. The STARS payload provides flexible options for spaceflight due to its low size, weight, power (SWaP) and very modest cooling requirements. STARS also meets AF operational requirements for cloud characterization and theater weather imagery. In this paper, an overview of the STARS concept, including the high-level sensor design, the concept of operations, and measurement capability will be presented.

Thrust vector control of upper stage with a gimbaled thruster during orbit transfer

NASA Astrophysics Data System (ADS)

Wang, Zhaohui; Jia, Yinghong; Jin, Lei; Duan, Jiajia

2016-10-01

In launching Multi-Satellite with One-Vehicle, the main thruster provided by the upper stage is mounted on a two-axis gimbal. During orbit transfer, the thrust vector of this gimbaled thruster (GT) should theoretically pass through the mass center of the upper stage and align with the command direction to provide orbit transfer impetus. However, it is hard to be implemented from the viewpoint of the engineering mission. The deviations of the thrust vector from the command direction would result in large velocity errors. Moreover, the deviations of the thrust vector from the upper stage mass center would produce large disturbance torques. This paper discusses the thrust vector control (TVC) of the upper stage during its orbit transfer. Firstly, the accurate nonlinear coupled kinematic and dynamic equations of the upper stage body, the two-axis gimbal and the GT are derived by taking the upper stage as a multi-body system. Then, a thrust vector control system consisting of the special attitude control of the upper stage and the gimbal rotation of the gimbaled thruster is proposed. The special attitude control defined by the desired attitude that draws the thrust vector to align with the command direction when the gimbal control makes the thrust vector passes through the upper stage mass center. Finally, the validity of the proposed method is verified through numerical simulations.

Invariant Connections in Loop Quantum Gravity

NASA Astrophysics Data System (ADS)

Hanusch, Maximilian

2016-04-01

Given a group {G}, and an abelian {C^*}-algebra {A}, the antihomomorphisms {Θ\\colon G→ {Aut}(A)} are in one-to-one with those left actions {Φ\\colon G× {Spec}(A)→ {Spec}(A)} whose translation maps {Φ_g} are continuous; whereby continuities of {Θ} and {Φ} turn out to be equivalent if {A} is unital. In particular, a left action {φ\\colon G × X→ X} can be uniquely extended to the spectrum of a {C^*}-subalgebra {A} of the bounded functions on {X} if {φ_g^*(A)subseteq A} holds for each {gin G}. In the present paper, we apply this to the framework of loop quantum gravity. We show that, on the level of the configuration spaces, quantization and reduction in general do not commute, i.e., that the symmetry-reduced quantum configuration space is (strictly) larger than the quantized configuration space of the reduced classical theory. Here, the quantum-reduced space has the advantage to be completely characterized by a simple algebraic relation, whereby the quantized reduced classical space is usually hard to compute.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Characterizing the Nash equilibria of three-player Bayesian quantum games

NASA Astrophysics Data System (ADS)

Solmeyer, Neal; Balu, Radhakrishnan

2017-05-01

Quantum games with incomplete information can be studied within a Bayesian framework. We analyze games quantized within the EWL framework [Eisert, Wilkens, and Lewenstein, Phys Rev. Lett. 83, 3077 (1999)]. We solve for the Nash equilibria of a variety of two-player quantum games and compare the results to the solutions of the corresponding classical games. We then analyze Bayesian games where there is uncertainty about the player types in two-player conflicting interest games. The solutions to the Bayesian games are found to have a phase diagram-like structure where different equilibria exist in different parameter regions, depending both on the amount of uncertainty and the degree of entanglement. We find that in games where a Pareto-optimal solution is not a Nash equilibrium, it is possible for the quantized game to have an advantage over the classical version. In addition, we analyze the behavior of the solutions as the strategy choices approach an unrestricted operation. We find that some games have a continuum of solutions, bounded by the solutions of a simpler restricted game. A deeper understanding of Bayesian quantum game theory could lead to novel quantum applications in a multi-agent setting.

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping

PubMed Central

Rossi, Alessandro; Tanttu, Tuomo; Hudson, Fay E.; Sun, Yuxin; Möttönen, Mikko; Dzurak, Andrew S.

2015-01-01

As mass-produced silicon transistors have reached the nano-scale, their behavior and performances are increasingly affected, and often deteriorated, by quantum mechanical effects such as tunneling through single dopants, scattering via interface defects, and discrete trap charge states. However, progress in silicon technology has shown that these phenomena can be harnessed and exploited for a new class of quantum-based electronics. Among others, multi-layer-gated silicon metal-oxide-semiconductor (MOS) technology can be used to control single charge or spin confined in electrostatically-defined quantum dots (QD). These QD-based devices are an excellent platform for quantum computing applications and, recently, it has been demonstrated that they can also be used as single-electron pumps, which are accurate sources of quantized current for metrological purposes. Here, we discuss in detail the fabrication protocol for silicon MOS QDs which is relevant to both quantum computing and quantum metrology applications. Moreover, we describe characterization methods to test the integrity of the devices after fabrication. Finally, we give a brief description of the measurement set-up used for charge pumping experiments and show representative results of electric current quantization. PMID:26067215

Generalized radiation-field quantization method and the Petermann excess-noise factor

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

Cheng, Y.-J.; Siegman, A.E.; E.L. Ginzton Laboratory, Stanford University, Stanford, California 94305

2003-10-01

We propose a generalized radiation-field quantization formalism, where quantization does not have to be referenced to a set of power-orthogonal eigenmodes as conventionally required. This formalism can be used to directly quantize the true system eigenmodes, which can be non-power-orthogonal due to the open nature of the system or the gain/loss medium involved in the system. We apply this generalized field quantization to the laser linewidth problem, in particular, lasers with non-power-orthogonal oscillation modes, and derive the excess-noise factor in a fully quantum-mechanical framework. We also show that, despite the excess-noise factor for oscillating modes, the total spatially averaged decaymore » rate for the laser atoms remains unchanged.« less

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

PubMed

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

2017-01-01

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

BFV approach to geometric quantization

NASA Astrophysics Data System (ADS)

Fradkin, E. S.; Linetsky, V. Ya.

1994-12-01

A gauge-invariant approach to geometric quantization is developed. It yields a complete quantum description for dynamical systems with non-trivial geometry and topology of the phase space. The method is a global version of the gauge-invariant approach to quantization of second-class constraints developed by Batalin, Fradkin and Fradkina (BFF). Physical quantum states and quantum observables are respectively described by covariantly constant sections of the Fock bundle and the bundle of hermitian operators over the phase space with a flat connection defined by the nilpotent BVF-BRST operator. Perturbative calculation of the first non-trivial quantum correction to the Poisson brackets leads to the Chevalley cocycle known in deformation quantization. Consistency conditions lead to a topological quantization condition with metaplectic anomaly.

Deformation quantization of fermi fields

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

Galaviz, I.; Garcia-Compean, H.; Departamento de Fisica, Centro de Investigacion y de Estudios Avanzados del IPN, P.O. Box 14-740, 07000 Mexico, D.F.

2008-04-15

Deformation quantization for any Grassmann scalar free field is described via the Weyl-Wigner-Moyal formalism. The Stratonovich-Weyl quantizer, the Moyal *-product and the Wigner functional are obtained by extending the formalism proposed recently in [I. Galaviz, H. Garcia-Compean, M. Przanowski, F.J. Turrubiates, Weyl-Wigner-Moyal Formalism for Fermi Classical Systems, arXiv:hep-th/0612245] to the fermionic systems of infinite number of degrees of freedom. In particular, this formalism is applied to quantize the Dirac free field. It is observed that the use of suitable oscillator variables facilitates considerably the procedure. The Stratonovich-Weyl quantizer, the Moyal *-product, the Wigner functional, the normal ordering operator, and finally,more » the Dirac propagator have been found with the use of these variables.« less

Polymer-Fourier quantization of the scalar field revisited

NASA Astrophysics Data System (ADS)

Garcia-Chung, Angel; Vergara, J. David

2016-10-01

The polymer quantization of the Fourier modes of the real scalar field is studied within algebraic scheme. We replace the positive linear functional of the standard Poincaré invariant quantization by a singular one. This singular positive linear functional is constructed as mimicking the singular limit of the complex structure of the Poincaré invariant Fock quantization. The resulting symmetry group of such polymer quantization is the subgroup SDiff(ℝ4) which is a subgroup of Diff(ℝ4) formed by spatial volume preserving diffeomorphisms. In consequence, this yields an entirely different irreducible representation of the canonical commutation relations, nonunitary equivalent to the standard Fock representation. We also compared the Poincaré invariant Fock vacuum with the polymer Fourier vacuum.

A New Suite of Plasmid Vectors for Fluorescence-Based Imaging of Root Colonizing Pseudomonads

DOE PAGES

Wilton, Rosemarie; Ahrendt, Angela J.; Shinde, Shalaka; ...

2018-02-01

In the terrestrial ecosystem, plant-microbe symbiotic associations are ecologically and economically important processes. To better understand these associations at structural and functional levels, different molecular and biochemical tools are applied. In this study, we have constructed a suite of vectors that incorporates several new elements into the rhizosphere stable, broad-host vector pME6031. The new vectors are useful for studies requiring multi-color tagging and visualization of plant-associated, Gram negative bacterial strains such as Pseudomonas plant growth promotion and biocontrol strains. A number of genetic elements, including constitutive promoters and signal peptides that target secretion to the periplasm, have been evaluated. Severalmore » next generation fluorescent proteins, namely mTurquoise2, mNeonGreen, mRuby2, DsRed-Express2 and E2-Crimson have been incorporated into the vectors for whole cell labeling or protein tagging. Secretion of mTurquoise2 and mNeonGreen into the periplasm of Pseudomonas fluorescens SBW25 has also been demonstrated, providing a vehicle for tagging proteins in the periplasmic compartment. A higher copy number version of select plasmids has been produced by introduction of a previously described repA mutation, affording an increase in protein expression levels. The utility of these plasmids for fluorescence-based imaging is demonstrated by root colonization of Solanum lycopersicum seedlings by P. fluorescens SBW25 in a hydroponic growth system. As a result, the plasmids are stably maintained during root colonization in the absence of selective pressure for more than two weeks.« less

A New Suite of Plasmid Vectors for Fluorescence-Based Imaging of Root Colonizing Pseudomonads

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

Wilton, Rosemarie; Ahrendt, Angela J.; Shinde, Shalaka

In the terrestrial ecosystem, plant-microbe symbiotic associations are ecologically and economically important processes. To better understand these associations at structural and functional levels, different molecular and biochemical tools are applied. In this study, we have constructed a suite of vectors that incorporates several new elements into the rhizosphere stable, broad-host vector pME6031. The new vectors are useful for studies requiring multi-color tagging and visualization of plant-associated, Gram negative bacterial strains such as Pseudomonas plant growth promotion and biocontrol strains. A number of genetic elements, including constitutive promoters and signal peptides that target secretion to the periplasm, have been evaluated. Severalmore » next generation fluorescent proteins, namely mTurquoise2, mNeonGreen, mRuby2, DsRed-Express2 and E2-Crimson have been incorporated into the vectors for whole cell labeling or protein tagging. Secretion of mTurquoise2 and mNeonGreen into the periplasm of Pseudomonas fluorescens SBW25 has also been demonstrated, providing a vehicle for tagging proteins in the periplasmic compartment. A higher copy number version of select plasmids has been produced by introduction of a previously described repA mutation, affording an increase in protein expression levels. The utility of these plasmids for fluorescence-based imaging is demonstrated by root colonization of Solanum lycopersicum seedlings by P. fluorescens SBW25 in a hydroponic growth system. As a result, the plasmids are stably maintained during root colonization in the absence of selective pressure for more than two weeks.« less

A vector radiative transfer model for coupled atmosphere and ocean systems based on successive order of scattering method.

PubMed

Zhai, Peng-Wang; Hu, Yongxiang; Trepte, Charles R; Lucker, Patricia L

2009-02-16

A vector radiative transfer model has been developed for coupled atmosphere and ocean systems based on the Successive Order of Scattering (SOS) Method. The emphasis of this study is to make the model easy-to-use and computationally efficient. This model provides the full Stokes vector at arbitrary locations which can be conveniently specified by users. The model is capable of tracking and labeling different sources of the photons that are measured, e.g. water leaving radiances and reflected sky lights. This model also has the capability to separate florescence from multi-scattered sunlight. The delta - fit technique has been adopted to reduce computational time associated with the strongly forward-peaked scattering phase matrices. The exponential - linear approximation has been used to reduce the number of discretized vertical layers while maintaining the accuracy. This model is developed to serve the remote sensing community in harvesting physical parameters from multi-platform, multi-sensor measurements that target different components of the atmosphere-oceanic system.

A Novel Degradation Identification Method for Wind Turbine Pitch System

NASA Astrophysics Data System (ADS)

Guo, Hui-Dong

2018-04-01

It’s difficult for traditional threshold value method to identify degradation of operating equipment accurately. An novel degradation evaluation method suitable for wind turbine condition maintenance strategy implementation was proposed in this paper. Based on the analysis of typical variable-speed pitch-to-feather control principle and monitoring parameters for pitch system, a multi input multi output (MIMO) regression model was applied to pitch system, where wind speed, power generation regarding as input parameters, wheel rotation speed, pitch angle and motor driving currency for three blades as output parameters. Then, the difference between the on-line measurement and the calculated value from the MIMO regression model applying least square support vector machines (LSSVM) method was defined as the Observed Vector of the system. The Gaussian mixture model (GMM) was applied to fitting the distribution of the multi dimension Observed Vectors. Applying the model established, the Degradation Index was calculated using the SCADA data of a wind turbine damaged its pitch bearing retainer and rolling body, which illustrated the feasibility of the provided method.

Multi-robot task allocation based on two dimensional artificial fish swarm algorithm

NASA Astrophysics Data System (ADS)

Zheng, Taixiong; Li, Xueqin; Yang, Liangyi

2007-12-01

The problem of task allocation for multiple robots is to allocate more relative-tasks to less relative-robots so as to minimize the processing time of these tasks. In order to get optimal multi-robot task allocation scheme, a twodimensional artificial swarm algorithm based approach is proposed in this paper. In this approach, the normal artificial fish is extended to be two dimension artificial fish. In the two dimension artificial fish, each vector of primary artificial fish is extended to be an m-dimensional vector. Thus, each vector can express a group of tasks. By redefining the distance between artificial fish and the center of artificial fish, the behavior of two dimension fish is designed and the task allocation algorithm based on two dimension artificial swarm algorithm is put forward. At last, the proposed algorithm is applied to the problem of multi-robot task allocation and comparer with GA and SA based algorithm is done. Simulation and compare result shows the proposed algorithm is effective.

Automatic sleep staging using multi-dimensional feature extraction and multi-kernel fuzzy support vector machine.

PubMed

Zhang, Yanjun; Zhang, Xiangmin; Liu, Wenhui; Luo, Yuxi; Yu, Enjia; Zou, Keju; Liu, Xiaoliang

2014-01-01

This paper employed the clinical Polysomnographic (PSG) data, mainly including all-night Electroencephalogram (EEG), Electrooculogram (EOG) and Electromyogram (EMG) signals of subjects, and adopted the American Academy of Sleep Medicine (AASM) clinical staging manual as standards to realize automatic sleep staging. Authors extracted eighteen different features of EEG, EOG and EMG in time domains and frequency domains to construct the vectors according to the existing literatures as well as clinical experience. By adopting sleep samples self-learning, the linear combination of weights and parameters of multiple kernels of the fuzzy support vector machine (FSVM) were learned and the multi-kernel FSVM (MK-FSVM) was constructed. The overall agreement between the experts' scores and the results presented was 82.53%. Compared with previous results, the accuracy of N1 was improved to some extent while the accuracies of other stages were approximate, which well reflected the sleep structure. The staging algorithm proposed in this paper is transparent, and worth further investigation.

Instabilities caused by floating-point arithmetic quantization.

NASA Technical Reports Server (NTRS)

Phillips, C. L.

1972-01-01

It is shown that an otherwise stable digital control system can be made unstable by signal quantization when the controller operates on floating-point arithmetic. Sufficient conditions of instability are determined, and an example of loss of stability is treated when only one quantizer is operated.

Dynamic State Estimation of Power Systems With Quantization Effects: A Recursive Filter Approach.

PubMed

Hu, Liang; Wang, Zidong; Liu, Xiaohui

2016-08-01

In this paper, a recursive filter algorithm is developed to deal with the state estimation problem for power systems with quantized nonlinear measurements. The measurements from both the remote terminal units and the phasor measurement unit are subject to quantizations described by a logarithmic quantizer. Attention is focused on the design of a recursive filter such that, in the simultaneous presence of nonlinear measurements and quantization effects, an upper bound for the estimation error covariance is guaranteed and subsequently minimized. Instead of using the traditional approximation methods in nonlinear estimation that simply ignore the linearization errors, we treat both the linearization and quantization errors as norm-bounded uncertainties in the algorithm development so as to improve the performance of the estimator. For the power system with such kind of introduced uncertainties, a filter is designed in the framework of robust recursive estimation, and the developed filter algorithm is tested on the IEEE benchmark power system to demonstrate its effectiveness.

Canonical quantization of classical mechanics in curvilinear coordinates. Invariant quantization procedure

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

Błaszak, Maciej, E-mail: blaszakm@amu.edu.pl; Domański, Ziemowit, E-mail: ziemowit@amu.edu.pl

In the paper is presented an invariant quantization procedure of classical mechanics on the phase space over flat configuration space. Then, the passage to an operator representation of quantum mechanics in a Hilbert space over configuration space is derived. An explicit form of position and momentum operators as well as their appropriate ordering in arbitrary curvilinear coordinates is demonstrated. Finally, the extension of presented formalism onto non-flat case and related ambiguities of the process of quantization are discussed. -- Highlights: •An invariant quantization procedure of classical mechanics on the phase space over flat configuration space is presented. •The passage tomore » an operator representation of quantum mechanics in a Hilbert space over configuration space is derived. •Explicit form of position and momentum operators and their appropriate ordering in curvilinear coordinates is shown. •The invariant form of Hamiltonian operators quadratic and cubic in momenta is derived. •The extension of presented formalism onto non-flat case and related ambiguities of the quantization process are discussed.« less

Helicity amplitudes for QCD with massive quarks

NASA Astrophysics Data System (ADS)

Ochirov, Alexander

2018-04-01

The novel massive spinor-helicity formalism of Arkani-Hamed, Huang and Huang provides an elegant way to calculate scattering amplitudes in quantum chromodynamics for arbitrary quark spin projections. In this note we compute two families of tree-level QCD amplitudes with one massive quark pair and n - 2 gluons. The two cases include all gluons with identical helicity and one opposite-helicity gluon being color-adjacent to one of the quarks. Our results naturally incorporate the previously known amplitudes for both quark spins quantized along one of the gluonic momenta. In the all-multiplicity formulae presented here the spin quantization axes can be tuned at will, which includes the case of the definite-helicity quark states.

Quantization of the Szekeres system

NASA Astrophysics Data System (ADS)

Paliathanasis, A.; Zampeli, Adamantia; Christodoulakis, T.; Mustafa, M. T.

2018-06-01

We study the quantum corrections on the Szekeres system in the context of canonical quantization in the presence of symmetries. We start from an effective point-like Lagrangian with two integrals of motion, one corresponding to the Hamiltonian and the other to a second rank killing tensor. Imposing their quantum version on the wave function results to a solution which is then interpreted in the context of Bohmian mechanics. In this semiclassical approach, it is shown that there is no quantum corrections, thus the classical trajectories of the Szekeres system are not affected at this level. Finally, we define a probability function which shows that a stationary surface of the probability corresponds to a classical exact solution.

Gravity quantized: Loop quantum gravity with a scalar field

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

Domagala, Marcin; Kaminski, Wojciech; Giesel, Kristina

2010-11-15

...''but we do not have quantum gravity.'' This phrase is often used when analysis of a physical problem enters the regime in which quantum gravity effects should be taken into account. In fact, there are several models of the gravitational field coupled to (scalar) fields for which the quantization procedure can be completed using loop quantum gravity techniques. The model we present in this paper consists of the gravitational field coupled to a scalar field. The result has similar structure to the loop quantum cosmology models, except that it involves all the local degrees of freedom of the gravitational fieldmore » because no symmetry reduction has been performed at the classical level.« less

Stationary drag photocurrent caused by strong effective running wave in quantum wires: Quantization of current

NASA Astrophysics Data System (ADS)

Entin, M. V.; Magarill, L. I.

2010-02-01

The stationary current induced by a strong running potential wave in one-dimensional system is studied. Such a wave can result from illumination of a straight quantum wire with special grating or spiral quantum wire by circular-polarized light. The wave drags electrons in the direction correlated with the direction of the system symmetry and polarization of light. In a pure system the wave induces minibands in the accompanied system of reference. We study the effect in the presence of impurity scattering. The current is an interplay between the wave drag and impurity braking. It was found that the drag current is quantized when the Fermi level gets into energy gaps.

Statistics of the quantized microwave electromagnetic field in mesoscopic elements at low temperature

NASA Astrophysics Data System (ADS)

Virally, Stéphane; Olivier Simoneau, Jean; Lupien, Christian; Reulet, Bertrand

2018-03-01

The quantum behavior of the electromagnetic field in mesoscopic elements is intimately linked to the quantization of the charge. In order to probe nonclassical aspects of the field in those elements, it is essential that thermal noise be reduced to the quantum level, i.e. to scales where kT ≲ hν. This is easily achieved in dilution refrigerators for frequencies of a few GHz, i.e. in the microwave domain. Several recent experiments have highlighted the link between discrete charge transport and discrete photon emission in simple mesoscopic elements such as a tunnel junction. Photocount statistics are inferred from the measurement of continuous variables such as the quadratures of the field.

Competing Phases of 2D Electrons at ν = 5/2 and 7/3

NASA Astrophysics Data System (ADS)

Xia, Jing

2011-03-01

The N=1 Landau level (LL) exhibits collective electronic phenomena characteristic of both fractional quantum Hall (FQHE) states seen in the lowest LL and anisotropic nematic states in the higher LLs. A modest in-plane magnetic field B| | is sufficient to destroy the fractional quantized Hall states at ν = 5 / 2 (and 7/2) and replace them with anisotropic compressible nematic phases, revealing the close competition between the two. We find that at larger B| | these anisotropic phases ν = 5 / 2 can themselves be replaced by a new isotropic state, dubbed re-entrant isotropic compressible (RIC) phase. We present strong evidence that this transition is a consequence of the mixing of Landau levels from different electric subbands in the confinement potential. In addition, we find that with B| | , the normally isotropic ν = 7 / 3 FQHE state can transform into an anisotropic phase with an accurately quantized Hall plateau but an anisotropic longitudinal resistivities. As temperature is lowered towards zero, ρxx diminishes while ρyy tends to diverge, reminiscent of the anisotropic nematic states, while surprisingly ρxy and ρyx remain quantized at 3 h / 7e2 , indicating a completely new quantum phase. This work represents a collaboration with J.P. Eisenstein (Caltech) and L.N. Pfeiffer and K.W West (Princeton), and is supported by Microsoft Project Q.

Detection of Road Surface States from Tire Noise Using Neural Network Analysis

NASA Astrophysics Data System (ADS)

Kongrattanaprasert, Wuttiwat; Nomura, Hideyuki; Kamakura, Tomoo; Ueda, Koji

This report proposes a new processing method for automatically detecting the states of road surfaces from tire noises of passing vehicles. In addition to multiple indicators of the signal features in the frequency domain, we propose a few feature indicators in the time domain to successfully classify the road states into four categories: snowy, slushy, wet, and dry states. The method is based on artificial neural networks. The proposed classification is carried out in multiple neural networks using learning vector quantization. The outcomes of the networks are then integrated by the voting decision-making scheme. Experimental results obtained from recorded signals for ten days in the snowy season demonstrated that an accuracy of approximately 90% can be attained for predicting road surface states using only tire noise data.

Conductance dips and spin precession in a nonuniform waveguide with spin–orbit coupling

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

Malyshev, A. I., E-mail: malyshev@phys.unn.ru; Kozulin, A. S.

An infinite waveguide with a nonuniformity, a segment of finite length with spin–orbit coupling, is considered in the case when the Rashba and Dresselhaus parameters are identical. Analytical expressions have been derived in the single-mode approximation for the conductance of the system for an arbitrary initial spin state. Based on numerical calculations with several size quantization modes, we have detected and described the conductance dips arising when the waves are localized in the nonuniformity due to the formation of an effective potential well in it. We show that allowance for the evanescent modes under carrier spin precession in an effectivemore » magnetic field does not lead to a change in the direction of the average spin vector at the output of the system.« less

Heavy and Heavy-Light Mesons in the Covariant Spectator Theory

NASA Astrophysics Data System (ADS)

Stadler, Alfred; Leitão, Sofia; Peña, M. T.; Biernat, Elmar P.

2018-05-01

The masses and vertex functions of heavy and heavy-light mesons, described as quark-antiquark bound states, are calculated with the Covariant Spectator Theory (CST). We use a kernel with an adjustable mixture of Lorentz scalar, pseudoscalar, and vector linear confining interaction, together with a one-gluon-exchange kernel. A series of fits to the heavy and heavy-light meson spectrum were calculated, and we discuss what conclusions can be drawn from it, especially about the Lorentz structure of the kernel. We also apply the Brodsky-Huang-Lepage prescription to express the CST wave functions for heavy quarkonia in terms of light-front variables. They agree remarkably well with light-front wave functions obtained in the Hamiltonian basis light-front quantization approach, even in excited states.

Application of two neural network paradigms to the study of voluntary employee turnover.

PubMed

Somers, M J

1999-04-01

Two neural network paradigms--multilayer perceptron and learning vector quantization--were used to study voluntary employee turnover with a sample of 577 hospital employees. The objectives of the study were twofold. The 1st was to assess whether neural computing techniques offered greater predictive accuracy than did conventional turnover methodologies. The 2nd was to explore whether computer models of turnover based on neural network technologies offered new insights into turnover processes. When compared with logistic regression analysis, both neural network paradigms provided considerably more accurate predictions of turnover behavior, particularly with respect to the correct classification of leavers. In addition, these neural network paradigms captured nonlinear relationships that are relevant for theory development. Results are discussed in terms of their implications for future research.

Coherent state quantization of quaternions

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

Muraleetharan, B., E-mail: bbmuraleetharan@jfn.ac.lk, E-mail: santhar@gmail.com; Thirulogasanthar, K., E-mail: bbmuraleetharan@jfn.ac.lk, E-mail: santhar@gmail.com

Parallel to the quantization of the complex plane, using the canonical coherent states of a right quaternionic Hilbert space, quaternion field of quaternionic quantum mechanics is quantized. Associated upper symbols, lower symbols, and related quantities are analyzed. Quaternionic version of the harmonic oscillator and Weyl-Heisenberg algebra are also obtained.

Performance Analysis for Channel Estimation With 1-Bit ADC and Unknown Quantization Threshold

NASA Astrophysics Data System (ADS)

Stein, Manuel S.; Bar, Shahar; Nossek, Josef A.; Tabrikian, Joseph

2018-05-01

In this work, the problem of signal parameter estimation from measurements acquired by a low-complexity analog-to-digital converter (ADC) with $1$-bit output resolution and an unknown quantization threshold is considered. Single-comparator ADCs are energy-efficient and can be operated at ultra-high sampling rates. For analysis of such systems, a fixed and known quantization threshold is usually assumed. In the symmetric case, i.e., zero hard-limiting offset, it is known that in the low signal-to-noise ratio (SNR) regime the signal processing performance degrades moderately by ${2}/{\\pi}$ ($-1.96$ dB) when comparing to an ideal $\\infty$-bit converter. Due to hardware imperfections, low-complexity $1$-bit ADCs will in practice exhibit an unknown threshold different from zero. Therefore, we study the accuracy which can be obtained with receive data processed by a hard-limiter with unknown quantization level by using asymptotically optimal channel estimation algorithms. To characterize the estimation performance of these nonlinear algorithms, we employ analytic error expressions for different setups while modeling the offset as a nuisance parameter. In the low SNR regime, we establish the necessary condition for a vanishing loss due to missing offset knowledge at the receiver. As an application, we consider the estimation of single-input single-output wireless channels with inter-symbol interference and validate our analysis by comparing the analytic and experimental performance of the studied estimation algorithms. Finally, we comment on the extension to multiple-input multiple-output channel models.

Expansion of the Gateway MultiSite Recombination Cloning Toolkit

PubMed Central

Shearin, Harold K.; Dvarishkis, Alisa R.; Kozeluh, Craig D.; Stowers, R. Steven

2013-01-01

Precise manipulation of transgene expression in genetic model organisms has led to advances in understanding fundamental mechanisms of development, physiology, and genetic disease. Transgene construction is, however, a precondition of transgene expression, and often limits the rate of experimental progress. Here we report an expansion of the modular Gateway MultiSite recombination-cloning platform for high efficiency transgene assembly. The expansion includes two additional destination vectors and entry clones for the LexA binary transcription system, among others. These new tools enhance the expression levels possible with Gateway MultiSite generated transgenes and make possible the generation of LexA drivers and reporters with Gateway MultiSite cloning. In vivo data from transgenic Drosophila functionally validating each novel component are presented and include neuronal LexA drivers, LexAop2 red and green fluorescent synaptic vesicle reporters, TDC2 and TRH LexA, GAL4, and QF drivers, and LexAop2, UAS, and QUAS channelrhodopsin2 T159C reporters. PMID:24204935

Diverse and abundant multi-drug resistant E. coli in Matang mangrove estuaries, Malaysia

PubMed Central

Ghaderpour, Aziz; Ho, Wing Sze; Chew, Li-Lee; Bong, Chui Wei; Chong, Ving Ching; Thong, Kwai-Lin; Chai, Lay Ching

2015-01-01

E.coli, an important vector distributing antimicrobial resistance in the environment, was found to be multi-drug resistant, abundant, and genetically diverse in the Matang mangrove estuaries, Malaysia. One-third (34%) of the estuarine E. coli was multi-drug resistant. The highest antibiotic resistance prevalence was observed for aminoglycosides (83%) and beta-lactams (37%). Phylogenetic groups A and B1, being the most predominant E. coli, demonstrated the highest antibiotic resistant level and prevalence of integrons (integron I, 21%; integron II, 3%). Detection of phylogenetic group B23 downstream of fishing villages indicates human fecal contamination as a source of E. coli pollution. Enteroaggregative E. coli (1%) were also detected immediately downstream of the fishing village. The results indicated multi-drug resistance among E. coli circulating in Matang estuaries, which could be reflective of anthropogenic activities and aggravated by bacterial and antibiotic discharges from village lack of a sewerage system, aquaculture farms and upstream animal husbandry. PMID:26483759

A Scatter-Based Prototype Framework and Multi-Class Extension of Support Vector Machines

PubMed Central

Jenssen, Robert; Kloft, Marius; Zien, Alexander; Sonnenburg, Sören; Müller, Klaus-Robert

2012-01-01

We provide a novel interpretation of the dual of support vector machines (SVMs) in terms of scatter with respect to class prototypes and their mean. As a key contribution, we extend this framework to multiple classes, providing a new joint Scatter SVM algorithm, at the level of its binary counterpart in the number of optimization variables. This enables us to implement computationally efficient solvers based on sequential minimal and chunking optimization. As a further contribution, the primal problem formulation is developed in terms of regularized risk minimization and the hinge loss, revealing the score function to be used in the actual classification of test patterns. We investigate Scatter SVM properties related to generalization ability, computational efficiency, sparsity and sensitivity maps, and report promising results. PMID:23118845

Optimized multi-level elongated quinary patterns for the assessment of thyroid nodules in ultrasound images.

PubMed

Raghavendra, U; Gudigar, Anjan; Maithri, M; Gertych, Arkadiusz; Meiburger, Kristen M; Yeong, Chai Hong; Madla, Chakri; Kongmebhol, Pailin; Molinari, Filippo; Ng, Kwan Hoong; Acharya, U Rajendra

2018-04-01

Ultrasound imaging is one of the most common visualizing tools used by radiologists to identify the location of thyroid nodules. However, visual assessment of nodules is difficult and often affected by inter- and intra-observer variabilities. Thus, a computer-aided diagnosis (CAD) system can be helpful to cross-verify the severity of nodules. This paper proposes a new CAD system to characterize thyroid nodules using optimized multi-level elongated quinary patterns. In this study, higher order spectral (HOS) entropy features extracted from these patterns appropriately distinguished benign and malignant nodules under particle swarm optimization (PSO) and support vector machine (SVM) frameworks. Our CAD algorithm achieved a maximum accuracy of 97.71% and 97.01% in private and public datasets respectively. The evaluation of this CAD system on both private and public datasets confirmed its effectiveness as a secondary tool in assisting radiological findings. Copyright © 2018 Elsevier Ltd. All rights reserved.

Educational Information Quantization for Improving Content Quality in Learning Management Systems

ERIC Educational Resources Information Center

Rybanov, Alexander Aleksandrovich

2014-01-01

The article offers the educational information quantization method for improving content quality in Learning Management Systems. The paper considers questions concerning analysis of quality of quantized presentation of educational information, based on quantitative text parameters: average frequencies of parts of speech, used in the text; formal…

BFV quantization on hermitian symmetric spaces

NASA Astrophysics Data System (ADS)

Fradkin, E. S.; Linetsky, V. Ya.

1995-02-01

Gauge-invariant BFV approach to geometric quantization is applied to the case of hermitian symmetric spaces G/ H. In particular, gauge invariant quantization on the Lobachevski plane and sphere is carried out. Due to the presence of symmetry, master equations for the first-class constraints, quantum observables and physical quantum states are exactly solvable. BFV-BRST operator defines a flat G-connection in the Fock bundle over G/ H. Physical quantum states are covariantly constant sections with respect to this connection and are shown to coincide with the generalized coherent states for the group G. Vacuum expectation values of the quantum observables commuting with the quantum first-class constraints reduce to the covariant symbols of Berezin. The gauge-invariant approach to quantization on symplectic manifolds synthesizes geometric, deformation and Berezin quantization approaches.

An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

PubMed Central

Jing, Luyang; Wang, Taiyong; Zhao, Ming; Wang, Peng

2017-01-01

A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. PMID:28230767

Application of information-retrieval methods to the classification of physical data

NASA Technical Reports Server (NTRS)

Mamotko, Z. N.; Khorolskaya, S. K.; Shatrovskiy, L. I.

1975-01-01

Scientific data received from satellites are characterized as a multi-dimensional time series, whose terms are vector functions of a vector of measurement conditions. Information retrieval methods are used to construct lower dimensional samples on the basis of the condition vector, in order to obtain these data and to construct partial relations. The methods are applied to the joint Soviet-French Arkad project.

Segmentation of tumor and edema along with healthy tissues of brain using wavelets and neural networks.

PubMed

Demirhan, Ayşe; Toru, Mustafa; Guler, Inan

2015-07-01

Robust brain magnetic resonance (MR) segmentation algorithms are critical to analyze tissues and diagnose tumor and edema in a quantitative way. In this study, we present a new tissue segmentation algorithm that segments brain MR images into tumor, edema, white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). The detection of the healthy tissues is performed simultaneously with the diseased tissues because examining the change caused by the spread of tumor and edema on healthy tissues is very important for treatment planning. We used T1, T2, and FLAIR MR images of 20 subjects suffering from glial tumor. We developed an algorithm for stripping the skull before the segmentation process. The segmentation is performed using self-organizing map (SOM) that is trained with unsupervised learning algorithm and fine-tuned with learning vector quantization (LVQ). Unlike other studies, we developed an algorithm for clustering the SOM instead of using an additional network. Input feature vector is constructed with the features obtained from stationary wavelet transform (SWT) coefficients. The results showed that average dice similarity indexes are 91% for WM, 87% for GM, 96% for CSF, 61% for tumor, and 77% for edema.

Spin wave modes in out-of-plane magnetized nanorings

NASA Astrophysics Data System (ADS)

Zhou, X.; Tartakovskaya, E. V.; Kakazei, G. N.; Adeyeye, A. O.

2017-07-01

We investigated the spin wave modes in flat circular permalloy rings with a canted external bias field using ferromagnetic resonance spectroscopy. The external magnetic field H was large enough to saturate the samples. For θ =0∘ (perpendicular geometry), three distinct resonance peaks were observed experimentally. In the case of the cylindrical symmetry violation due to H inclination from normal to the ring plane (the angle θ of H inclination was varied in the 0∘-6∘ range), the splitting of all initial peaks appeared. The distance between neighbor split peaks increased with the θ increment. Unexpectedly, the biggest splitting was observed for the mode with the smallest radial wave vector. This special feature of splitting behavior is determined by the topology of the ring shape. Developed analytical theory revealed that in perpendicular geometry, each observed peak is a combination of signals from the set of radially quantized spin wave excitation with almost the same radial wave vectors, radial profiles, and frequencies, but with different azimuthal dependencies. This degeneracy is a consequence of circular symmetry of the system and can be removed by H inclination from the normal. Our findings were further supported by micromagnetic simulations.

Novel Integration of Frame Rate Up Conversion and HEVC Coding Based on Rate-Distortion Optimization.

PubMed

Guo Lu; Xiaoyun Zhang; Li Chen; Zhiyong Gao

2018-02-01

Frame rate up conversion (FRUC) can improve the visual quality by interpolating new intermediate frames. However, high frame rate videos by FRUC are confronted with more bitrate consumption or annoying artifacts of interpolated frames. In this paper, a novel integration framework of FRUC and high efficiency video coding (HEVC) is proposed based on rate-distortion optimization, and the interpolated frames can be reconstructed at encoder side with low bitrate cost and high visual quality. First, joint motion estimation (JME) algorithm is proposed to obtain robust motion vectors, which are shared between FRUC and video coding. What's more, JME is embedded into the coding loop and employs the original motion search strategy in HEVC coding. Then, the frame interpolation is formulated as a rate-distortion optimization problem, where both the coding bitrate consumption and visual quality are taken into account. Due to the absence of original frames, the distortion model for interpolated frames is established according to the motion vector reliability and coding quantization error. Experimental results demonstrate that the proposed framework can achieve 21% ~ 42% reduction in BDBR, when compared with the traditional methods of FRUC cascaded with coding.

Self-Organizing-Map Program for Analyzing Multivariate Data

NASA Technical Reports Server (NTRS)

Li, P. Peggy; Jacob, Joseph C.; Block, Gary L.; Braverman, Amy J.

2005-01-01

SOM_VIS is a computer program for analysis and display of multidimensional sets of Earth-image data typified by the data acquired by the Multi-angle Imaging Spectro-Radiometer [MISR (a spaceborne instrument)]. In SOM_VIS, an enhanced self-organizing-map (SOM) algorithm is first used to project a multidimensional set of data into a nonuniform three-dimensional lattice structure. The lattice structure is mapped to a color space to obtain a color map for an image. The Voronoi cell-refinement algorithm is used to map the SOM lattice structure to various levels of color resolution. The final result is a false-color image in which similar colors represent similar characteristics across all its data dimensions. SOM_VIS provides a control panel for selection of a subset of suitably preprocessed MISR radiance data, and a control panel for choosing parameters to run SOM training. SOM_VIS also includes a component for displaying the false-color SOM image, a color map for the trained SOM lattice, a plot showing an original input vector in 36 dimensions of a selected pixel from the SOM image, the SOM vector that represents the input vector, and the Euclidean distance between the two vectors.

Describing complex cells in primary visual cortex: a comparison of context and multi-filter LN models.

PubMed

Westö, Johan; May, Patrick J C

2018-05-02

Receptive field (RF) models are an important tool for deciphering neural responses to sensory stimuli. The two currently popular RF models are multi-filter linear-nonlinear (LN) models and context models. Models are, however, never correct and they rely on assumptions to keep them simple enough to be interpretable. As a consequence, different models describe different stimulus-response mappings, which may or may not be good approximations of real neural behavior. In the current study, we take up two tasks: First, we introduce new ways to estimate context models with realistic nonlinearities, that is, with logistic and exponential functions. Second, we evaluate context models and multi-filter LN models in terms of how well they describe recorded data from complex cells in cat primary visual cortex. Our results, based on single-spike information and correlation coefficients, indicate that context models outperform corresponding multi-filter LN models of equal complexity (measured in terms of number of parameters), with the best increase in performance being achieved by the novel context models. Consequently, our results suggest that the multi-filter LN-model framework is suboptimal for describing the behavior of complex cells: the context-model framework is clearly superior while still providing interpretable quantizations of neural behavior.

Verification of Electromagnetic Physics Models for Parallel Computing Architectures in the GeantV Project

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

Amadio, G.; et al.

An intensive R&D and programming effort is required to accomplish new challenges posed by future experimental high-energy particle physics (HEP) programs. The GeantV project aims to narrow the gap between the performance of the existing HEP detector simulation software and the ideal performance achievable, exploiting latest advances in computing technology. The project has developed a particle detector simulation prototype capable of transporting in parallel particles in complex geometries exploiting instruction level microparallelism (SIMD and SIMT), task-level parallelism (multithreading) and high-level parallelism (MPI), leveraging both the multi-core and the many-core opportunities. We present preliminary verification results concerning the electromagnetic (EM) physicsmore » models developed for parallel computing architectures within the GeantV project. In order to exploit the potential of vectorization and accelerators and to make the physics model effectively parallelizable, advanced sampling techniques have been implemented and tested. In this paper we introduce a set of automated statistical tests in order to verify the vectorized models by checking their consistency with the corresponding Geant4 models and to validate them against experimental data.« less

A Algebraic Approach to the Quantization of Constrained Systems: Finite Dimensional Examples.

NASA Astrophysics Data System (ADS)

Tate, Ranjeet Shekhar

1992-01-01

General relativity has two features in particular, which make it difficult to apply to it existing schemes for the quantization of constrained systems. First, there is no background structure in the theory, which could be used, e.g., to regularize constraint operators, to identify a "time" or to define an inner product on physical states. Second, in the Ashtekar formulation of general relativity, which is a promising avenue to quantum gravity, the natural variables for quantization are not canonical; and, classically, there are algebraic identities between them. Existing schemes are usually not concerned with such identities. Thus, from the point of view of canonical quantum gravity, it has become imperative to find a framework for quantization which provides a general prescription to find the physical inner product, and is flexible enough to accommodate non -canonical variables. In this dissertation I present an algebraic formulation of the Dirac approach to the quantization of constrained systems. The Dirac quantization program is augmented by a general principle to find the inner product on physical states. Essentially, the Hermiticity conditions on physical operators determine this inner product. I also clarify the role in quantum theory of possible algebraic identities between the elementary variables. I use this approach to quantize various finite dimensional systems. Some of these models test the new aspects of the algebraic framework. Others bear qualitative similarities to general relativity, and may give some insight into the pitfalls lurking in quantum gravity. The previous quantizations of one such model had many surprising features. When this model is quantized using the algebraic program, there is no longer any unexpected behaviour. I also construct the complete quantum theory for a previously unsolved relativistic cosmology. All these models indicate that the algebraic formulation provides powerful new tools for quantization. In (spatially compact) general relativity, the Hamiltonian is constrained to vanish. I present various approaches one can take to obtain an interpretation of the quantum theory of such "dynamically constrained" systems. I apply some of these ideas to the Bianchi I cosmology, and analyze the issue of the initial singularity in quantum theory.

Chern-Simons Term: Theory and Applications.

NASA Astrophysics Data System (ADS)

Gupta, Kumar Sankar

1992-01-01

We investigate the quantization and applications of Chern-Simons theories to several systems of interest. Elementary canonical methods are employed for the quantization of abelian and nonabelian Chern-Simons actions using ideas from gauge theories and quantum gravity. When the spatial slice is a disc, it yields quantum states at the edge of the disc carrying a representation of the Kac-Moody algebra. We next include sources in this model and their quantum states are shown to be those of a conformal family. Vertex operators for both abelian and nonabelian sources are constructed. The regularized abelian Wilson line is proved to be a vertex operator. The spin-statistics theorem is established for Chern-Simons dynamics using purely geometrical techniques. Chern-Simons action is associated with exotic spin and statistics in 2 + 1 dimensions. We study several systems in which the Chern-Simons action affects the spin and statistics. The first class of systems we study consist of G/H models. The solitons of these models are shown to obey anyonic statistics in the presence of a Chern-Simons term. The second system deals with the effect of the Chern -Simons term in a model for high temperature superconductivity. The coefficient of the Chern-Simons term is shown to be quantized, one of its possible values giving fermionic statistics to the solitons of this model. Finally, we study a system of spinning particles interacting with 2 + 1 gravity, the latter being described by an ISO(2,1) Chern-Simons term. An effective action for the particles is obtained by integrating out the gauge fields. Next we construct operators which exchange the particles. They are shown to satisfy the braid relations. There are ambiguities in the quantization of this system which can be exploited to give anyonic statistics to the particles. We also point out that at the level of the first quantized theory, the usual spin-statistics relation need not apply to these particles.

A Quantized Metric As an Alternative to Dark Matter

NASA Astrophysics Data System (ADS)

Maker, Joel

2010-03-01

The cosmological spherical symmetry background metric coefficient (g44≡) g00= 1-2GM/c^2r should be inserted into a Dirac equation σμ(gμμγ^μψ/xμ)-φψ = 0 (1,Maker) to make it generally covariant. The spin of this cosmological Dirac object is nearly unobservable due to inertial frame dragging and has rotational L(L+1) δɛ and oscillatory ɛ interactions with external objects at distance away r>>10^10 LY. The inside and outside frequencies φ match at the boundary allowing the outside metric eigenvalues to propagate inside. To include the correct 3 lepton masses in this Dirac equation we must use ansatz goo= e^i(2ɛ+δɛ) with ɛ=.06, δɛ=.00058. For local metric effects our ansatz is goo=e^iδɛ. Here the metric coefficient goo levels off to the quantized value e^iδɛ in the galaxy halo: goo=1-2GM/rc^2-> rel(e^iδɛ) =cos(δɛ)= 1-(δɛ)^2/2 ->(δɛ)^2/2=2GM/rc^2 for this circular motion v^2/r=GM/r^2=c^2(δɛ)^2/4r ->v^2 =c^2(δɛ)^2/4 =87km/sec)^2 100km/sec)^2. So the metric acts to quantize v. Note also there is rotational energy quantization for the δɛ rotational states that goes as: (L(L+1)) .5ex1 -.1em/ -.15em.25ex2 mv^2 ->√L(L+1) v. Thus differences in v are proportional to L, L being an integer. Therefore δv = kL so v = 1k, v = 2k, v = 3k, v = 4k. v=N (the above ˜100km/sec) with dark matter then not required to give these high halo velocities. Recent nearby galaxy Doppler halo velocity data strongly support this velocity quantization result.

Three-dimensional tool radius compensation for multi-axis peripheral milling

NASA Astrophysics Data System (ADS)

Chen, Youdong; Wang, Tianmiao

2013-05-01

Few function about 3D tool radius compensation is applied to generating executable motion control commands in the existing computer numerical control (CNC) systems. Once the tool radius is changed, especially in the case of tool size changing with tool wear in machining, a new NC program has to be recreated. A generic 3D tool radius compensation method for multi-axis peripheral milling in CNC systems is presented. The offset path is calculated by offsetting the tool path along the direction of the offset vector with a given distance. The offset vector is perpendicular to both the tangent vector of the tool path and the orientation vector of the tool axis relative to the workpiece. The orientation vector equations of the tool axis relative to the workpiece are obtained through homogeneous coordinate transformation matrix and forward kinematics of generalized kinematics model of multi-axis machine tools. To avoid cutting into the corner formed by the two adjacent tool paths, the coordinates of offset path at the intersection point have been calculated according to the transition type that is determined by the angle between the two tool path tangent vectors at the corner. Through the verification by the solid cutting simulation software VERICUT® with different tool radiuses on a table-tilting type five-axis machine tool, and by the real machining experiment of machining a soup spoon on a five-axis machine tool with the developed CNC system, the effectiveness of the proposed 3D tool radius compensation method is confirmed. The proposed compensation method can be suitable for all kinds of three- to five-axis machine tools as a general form.

Quantization Distortion in Block Transform-Compressed Data

NASA Technical Reports Server (NTRS)

Boden, A. F.

1995-01-01

The popular JPEG image compression standard is an example of a block transform-based compression scheme; the image is systematically subdivided into block that are individually transformed, quantized, and encoded. The compression is achieved by quantizing the transformed data, reducing the data entropy and thus facilitating efficient encoding. A generic block transform model is introduced.

Confidence level estimation in multi-target classification problems

NASA Astrophysics Data System (ADS)

Chang, Shi; Isaacs, Jason; Fu, Bo; Shin, Jaejeong; Zhu, Pingping; Ferrari, Silvia

2018-04-01

This paper presents an approach for estimating the confidence level in automatic multi-target classification performed by an imaging sensor on an unmanned vehicle. An automatic target recognition algorithm comprised of a deep convolutional neural network in series with a support vector machine classifier detects and classifies targets based on the image matrix. The joint posterior probability mass function of target class, features, and classification estimates is learned from labeled data, and recursively updated as additional images become available. Based on the learned joint probability mass function, the approach presented in this paper predicts the expected confidence level of future target classifications, prior to obtaining new images. The proposed approach is tested with a set of simulated sonar image data. The numerical results show that the estimated confidence level provides a close approximation to the actual confidence level value determined a posteriori, i.e. after the new image is obtained by the on-board sensor. Therefore, the expected confidence level function presented in this paper can be used to adaptively plan the path of the unmanned vehicle so as to optimize the expected confidence levels and ensure that all targets are classified with satisfactory confidence after the path is executed.

Probabilistic distance-based quantizer design for distributed estimation

NASA Astrophysics Data System (ADS)

Kim, Yoon Hak

2016-12-01

We consider an iterative design of independently operating local quantizers at nodes that should cooperate without interaction to achieve application objectives for distributed estimation systems. We suggest as a new cost function a probabilistic distance between the posterior distribution and its quantized one expressed as the Kullback Leibler (KL) divergence. We first present the analysis that minimizing the KL divergence in the cyclic generalized Lloyd design framework is equivalent to maximizing the logarithmic quantized posterior distribution on the average which can be further computationally reduced in our iterative design. We propose an iterative design algorithm that seeks to maximize the simplified version of the posterior quantized distribution and discuss that our algorithm converges to a global optimum due to the convexity of the cost function and generates the most informative quantized measurements. We also provide an independent encoding technique that enables minimization of the cost function and can be efficiently simplified for a practical use of power-constrained nodes. We finally demonstrate through extensive experiments an obvious advantage of improved estimation performance as compared with the typical designs and the novel design techniques previously published.

Quantization and Superselection Sectors I:. Transformation Group C*-ALGEBRAS

NASA Astrophysics Data System (ADS)

Landsman, N. P.

Quantization is defined as the act of assigning an appropriate C*-algebra { A} to a given configuration space Q, along with a prescription mapping self-adjoint elements of { A} into physically interpretable observables. This procedure is adopted to solve the problem of quantizing a particle moving on a homogeneous locally compact configuration space Q=G/H. Here { A} is chosen to be the transformation group C*-algebra corresponding to the canonical action of G on Q. The structure of these algebras and their representations are examined in some detail. Inequivalent quantizations are identified with inequivalent irreducible representations of the C*-algebra corresponding to the system, hence with its superselection sectors. Introducing the concept of a pre-Hamiltonian, we construct a large class of G-invariant time-evolutions on these algebras, and find the Hamiltonians implementing these time-evolutions in each irreducible representation of { A}. “Topological” terms in the Hamiltonian (or the corresponding action) turn out to be representation-dependent, and are automatically induced by the quantization procedure. Known “topological” charge quantization or periodicity conditions are then identically satisfied as a consequence of the representation theory of { A}.

Adenovirus vector infection of non-small-cell lung cancer cells is a trigger for multi-drug resistance mediated by P-glycoprotein.

PubMed

Tomono, Takumi; Kajita, Masahiro; Yano, Kentaro; Ogihara, Takuo

2016-08-05

P-glycoprotein (P-gp) is an ATP-binding cassette protein involved in cancer multi-drug resistance (MDR). It has been reported that infection with some bacteria and viruses induces changes in the activities of various drug-metabolizing enzymes and transporters, including P-gp. Although human adenoviruses (Ad) cause the common cold, the effect of Ad infection on MDR in cancer has not been established. In this study, we investigated whether Ad infection is a cause of MDR in A549, H441 and HCC827 non-small-cell lung cancer (NSCLC) cell lines, using an Ad vector system. We found that Ad vector infection of NSCLC cell lines induced P-gp mRNA expression, and the extent of induction was dependent on the number of Ad vector virus particles and the infection time. Heat-treated Ad vector, which is not infectious, did not alter P-gp mRNA expression. Uptake experiments with doxorubicin (DOX), a P-gp substrate, revealed that DOX accumulation was significantly decreased in Ad vector-infected A549 cells. The decrease of DOX uptake was blocked by verapamil, a P-gp inhibitor. Our results indicated that Ad vector infection of NSCLC cells caused MDR mediated by P-gp overexpression. The Ad vector genome sequence is similar to that of human Ad, and therefore human Ad infection of lung cancer patients may lead to chemoresistance in the clinical environment. Copyright © 2016 Elsevier Inc. All rights reserved.

Improved Autoassociative Neural Networks

NASA Technical Reports Server (NTRS)

Hand, Charles

2003-01-01

Improved autoassociative neural networks, denoted nexi, have been proposed for use in controlling autonomous robots, including mobile exploratory robots of the biomorphic type. In comparison with conventional autoassociative neural networks, nexi would be more complex but more capable in that they could be trained to do more complex tasks. A nexus would use bit weights and simple arithmetic in a manner that would enable training and operation without a central processing unit, programs, weight registers, or large amounts of memory. Only a relatively small amount of memory (to hold the bit weights) and a simple logic application- specific integrated circuit would be needed. A description of autoassociative neural networks is prerequisite to a meaningful description of a nexus. An autoassociative network is a set of neurons that are completely connected in the sense that each neuron receives input from, and sends output to, all the other neurons. (In some instantiations, a neuron could also send output back to its own input terminal.) The state of a neuron is completely determined by the inner product of its inputs with weights associated with its input channel. Setting the weights sets the behavior of the network. The neurons of an autoassociative network are usually regarded as comprising a row or vector. Time is a quantized phenomenon for most autoassociative networks in the sense that time proceeds in discrete steps. At each time step, the row of neurons forms a pattern: some neurons are firing, some are not. Hence, the current state of an autoassociative network can be described with a single binary vector. As time goes by, the network changes the vector. Autoassociative networks move vectors over hyperspace landscapes of possibilities.

Multi-stage Vector-Borne Zoonoses Models: A Global Analysis.

PubMed

Bichara, Derdei; Iggidr, Abderrahman; Smith, Laura

2018-04-25

A class of models that describes the interactions between multiple host species and an arthropod vector is formulated and its dynamics investigated. A host-vector disease model where the host's infection is structured into n stages is formulated and a complete global dynamics analysis is provided. The basic reproduction number acts as a sharp threshold, that is, the disease-free equilibrium is globally asymptotically stable (GAS) whenever [Formula: see text] and that a unique interior endemic equilibrium exists and is GAS if [Formula: see text]. We proceed to extend this model with m host species, capturing a class of zoonoses where the cross-species bridge is an arthropod vector. The basic reproduction number of the multi-host-vector, [Formula: see text], is derived and shown to be the sum of basic reproduction numbers of the model when each host is isolated with an arthropod vector. It is shown that the disease will persist in all hosts as long as it persists in one host. Moreover, the overall basic reproduction number increases with respect to the host and that bringing the basic reproduction number of each isolated host below unity in each host is not sufficient to eradicate the disease in all hosts. This is a type of "amplification effect," that is, for the considered vector-borne zoonoses, the increase in host diversity increases the basic reproduction number and therefore the disease burden.

Relational symplectic groupoid quantization for constant poisson structures

NASA Astrophysics Data System (ADS)

Cattaneo, Alberto S.; Moshayedi, Nima; Wernli, Konstantin

2017-09-01

As a detailed application of the BV-BFV formalism for the quantization of field theories on manifolds with boundary, this note describes a quantization of the relational symplectic groupoid for a constant Poisson structure. The presence of mixed boundary conditions and the globalization of results are also addressed. In particular, the paper includes an extension to space-times with boundary of some formal geometry considerations in the BV-BFV formalism, and specifically introduces into the BV-BFV framework a "differential" version of the classical and quantum master equations. The quantization constructed in this paper induces Kontsevich's deformation quantization on the underlying Poisson manifold, i.e., the Moyal product, which is known in full details. This allows focussing on the BV-BFV technology and testing it. For the inexperienced reader, this is also a practical and reasonably simple way to learn it.

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

Barone, Fiorella; Graffi, Sandro

We consider on L{sup 2}(T{sup 2}) the Schrödinger operator family L{sub ε}:ε∈R with domain and action defined as D(L{sub ε})=H{sup 2}(T{sup 2}), L{sub ε}u=−(1/2)ℏ{sup 2}(α{sub 1}∂{sub φ{sub 1}{sup 2}}+α{sub 2}∂{sub φ{sub 2}{sup 2}})u−iℏ(γ{sub 1}∂{sub φ{sub 1}}+γ{sub 2}∂{sub φ{sub 2}})u+εVu. Here ε∈R, α= (α{sub 1}, α{sub 2}), γ= (γ{sub 1}, γ{sub 2}) are vectors of complex non-real frequencies, and V a pseudodifferential operator of order zero. L{sub ε} represents the Weyl quantization of the Hamiltonian family L{sub ε}(ξ,x)=(1/2)(α{sub 1}ξ{sub 1}{sup 2}+α{sub 2}ξ{sub 2}{sup 2})+γ{sub 1}ξ{sub 1}+γ{sub 2}ξ{sub 2}+εV(ξ,x) defined on the phase space R{sup 2}×T{sup 2}, where V(ξ,x)∈C{sup 2}(R{sup 2}×T{sup 2};R). Wemore » prove the uniform convergence with respect to ℏ∈[0, 1] of the quantum normal form, which reduces to the classical one for ℏ= 0. This result simultaneously entails an exact quantization formula for the quantum spectrum as well as a convergence criterion for the classical Birkhoff normal form generalizing a well known theorem of Cherry.« less

Multi-component dark matter through a radiative Higgs portal

DOE PAGES

DiFranzo, Anthony; Univ. of California, Irvine, CA; Rutgers Univ., Piscataway, NJ; ...

2017-01-18

Here, we study a multi-component dark matter model where interactions with the Standard Model are primarily via the Higgs boson. The model contains vector-like fermions charged undermore » $$SU(2)_W \\times U(1)_Y$$ and under the dark gauge group, $$U(1)^\\prime$$. This results in two dark matter candidates. A spin-1 and a spin-1/2 candidate, which have loop and tree-level couplings to the Higgs, respectively. We explore the resulting effect on the dark matter relic abundance, while also evaluating constraints on the Higgs invisible width and from direct detection experiments. Generally, we find that this model is highly constrained when the fermionic candidate is the predominant fraction of the dark matter relic abundance.« less

Hierarchical vs non-hierarchical audio indexation and classification for video genres

NASA Astrophysics Data System (ADS)

Dammak, Nouha; BenAyed, Yassine

2018-04-01

In this paper, Support Vector Machines (SVMs) are used for segmenting and indexing video genres based on only audio features extracted at block level, which has a prominent asset by capturing local temporal information. The main contribution of our study is to show the wide effect on the classification accuracies while using an hierarchical categorization structure based on Mel Frequency Cepstral Coefficients (MFCC) audio descriptor. In fact, the classification consists in three common video genres: sports videos, music clips and news scenes. The sub-classification may divide each genre into several multi-speaker and multi-dialect sub-genres. The validation of this approach was carried out on over 360 minutes of video span yielding a classification accuracy of over 99%.

Vector-borne diseases models with residence times - A Lagrangian perspective.

PubMed

Bichara, Derdei; Castillo-Chavez, Carlos

2016-11-01

A multi-patch and multi-group modeling framework describing the dynamics of a class of diseases driven by the interactions between vectors and hosts structured by groups is formulated. Hosts' dispersal is modeled in terms of patch-residence times with the nonlinear dynamics taking into account the effective patch-host size. The residence times basic reproduction number R 0 is computed and shown to depend on the relative environmental risk of infection. The model is robust, that is, the disease free equilibrium is globally asymptotically stable (GAS) if R 0 ≤1 and a unique interior endemic equilibrium is shown to exist that is GAS whenever R 0 >1 whenever the configuration of host-vector interactions is irreducible. The effects of patchiness and groupness, a measure of host-vector heterogeneous structure, on the basic reproduction number R 0 , are explored. Numerical simulations are carried out to highlight the effects of residence times on disease prevalence. Copyright © 2016 Elsevier Inc. All rights reserved.

Shape Sensing Using a Multi-Core Optical Fiber Having an Arbitrary Initial Shape in the Presence of Extrinsic Forces

NASA Technical Reports Server (NTRS)

Rogge, Matthew D. (Inventor); Moore, Jason P. (Inventor)

2014-01-01

Shape of a multi-core optical fiber is determined by positioning the fiber in an arbitrary initial shape and measuring strain over the fiber's length using strain sensors. A three-coordinate p-vector is defined for each core as a function of the distance of the corresponding cores from a center point of the fiber and a bending angle of the cores. The method includes calculating, via a controller, an applied strain value of the fiber using the p-vector and the measured strain for each core, and calculating strain due to bending as a function of the measured and the applied strain values. Additionally, an apparent local curvature vector is defined for each core as a function of the calculated strain due to bending. Curvature and bend direction are calculated using the apparent local curvature vector, and fiber shape is determined via the controller using the calculated curvature and bend direction.

On multi-sensitivity with respect to a vector

NASA Astrophysics Data System (ADS)

Jiao, Lixin; Wang, Lidong; Li, Fengquan; Liu, Heng

2018-05-01

Consider the surjective continuous map f: X → X defined on a compact metric space X. Let 𝒦(X) be the space of all non-empty compact subsets of X equipped with the Hausdorff metric and define f¯: 𝒦(X) →𝒦(X) by f¯(A) = {f(a),a ∈ A} for any A ∈𝒦(X). In this paper, we introduce several stronger versions of sensitivities, such as multi-sensitivity with respect to a vector, 𝒩-sensitivity, strong multi-sensitivity. We obtain some basic properties of the concepts of these sensitivities and discuss the relationships with other sensitivities for continuous self-map on [0,1]. Some sufficient conditions for a dynamical system to be 𝒩-sensitive are presented. Also, it is shown that the strong multi-sensitivity of f implies that f¯ is 𝒩-sensitive. In turn, the 𝒩-sensitivity of f¯ implies that f is 𝒩-sensitive. In particular, it is proved that if f is a multi-transitive map with dense periodic sets, then f is 𝒩-sensitive. Finally, we give a multi-sensitive example which is not 𝒩-sensitive.

Splitting Times of Doubly Quantized Vortices in Dilute Bose-Einstein Condensates

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

Huhtamaeki, J. A. M.; Pietilae, V.; Virtanen, S. M. M.

2006-09-15

Recently, the splitting of a topologically created doubly quantized vortex into two singly quantized vortices was experimentally investigated in dilute atomic cigar-shaped Bose-Einstein condensates [Y. Shin et al., Phys. Rev. Lett. 93, 160406 (2004)]. In particular, the dependency of the splitting time on the peak particle density was studied. We present results of theoretical simulations which closely mimic the experimental setup. We show that the combination of gravitational sag and time dependency of the trapping potential alone suffices to split the doubly quantized vortex in time scales which are in good agreement with the experiments.

Response of two-band systems to a single-mode quantized field

NASA Astrophysics Data System (ADS)

Shi, Z. C.; Shen, H. Z.; Wang, W.; Yi, X. X.

2016-03-01

The response of topological insulators (TIs) to an external weakly classical field can be expressed in terms of Kubo formula, which predicts quantized Hall conductivity of the quantum Hall family. The response of TIs to a single-mode quantized field, however, remains unexplored. In this work, we take the quantum nature of the external field into account and define a Hall conductance to characterize the linear response of a two-band system to the quantized field. The theory is then applied to topological insulators. Comparisons with the traditional Hall conductance are presented and discussed.

Quantized Iterative Learning Consensus Tracking of Digital Networks With Limited Information Communication.

PubMed

Xiong, Wenjun; Yu, Xinghuo; Chen, Yao; Gao, Jie

2017-06-01

This brief investigates the quantized iterative learning problem for digital networks with time-varying topologies. The information is first encoded as symbolic data and then transmitted. After the data are received, a decoder is used by the receiver to get an estimate of the sender's state. Iterative learning quantized communication is considered in the process of encoding and decoding. A sufficient condition is then presented to achieve the consensus tracking problem in a finite interval using the quantized iterative learning controllers. Finally, simulation results are given to illustrate the usefulness of the developed criterion.

Adenovirus vector infection of non-small-cell lung cancer cells is a trigger for multi-drug resistance mediated by P-glycoprotein

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

Tomono, Takumi; Kajita, Masahiro; Yano, Kentaro

P-glycoprotein (P-gp) is an ATP-binding cassette protein involved in cancer multi-drug resistance (MDR). It has been reported that infection with some bacteria and viruses induces changes in the activities of various drug-metabolizing enzymes and transporters, including P-gp. Although human adenoviruses (Ad) cause the common cold, the effect of Ad infection on MDR in cancer has not been established. In this study, we investigated whether Ad infection is a cause of MDR in A549, H441 and HCC827 non-small-cell lung cancer (NSCLC) cell lines, using an Ad vector system. We found that Ad vector infection of NSCLC cell lines induced P-gp mRNAmore » expression, and the extent of induction was dependent on the number of Ad vector virus particles and the infection time. Heat-treated Ad vector, which is not infectious, did not alter P-gp mRNA expression. Uptake experiments with doxorubicin (DOX), a P-gp substrate, revealed that DOX accumulation was significantly decreased in Ad vector-infected A549 cells. The decrease of DOX uptake was blocked by verapamil, a P-gp inhibitor. Our results indicated that Ad vector infection of NSCLC cells caused MDR mediated by P-gp overexpression. The Ad vector genome sequence is similar to that of human Ad, and therefore human Ad infection of lung cancer patients may lead to chemoresistance in the clinical environment. -- Highlights: •Adenovirus vector infection induced P-gp mRNA expression in three NSCLC cell lines. •Adenovirus vector infection enhanced P-gp-mediated doxorubicin efflux from the cells. •The increase of P-gp was not mediated by nuclear receptors (PXR, CAR) or COX-2.« less

Nilpotent symmetries in supergroup field cosmology

NASA Astrophysics Data System (ADS)

Upadhyay, Sudhaker

2015-06-01

In this paper, we study the gauge invariance of the third quantized supergroup field cosmology which is a model for multiverse. Further, we propose both the infinitesimal (usual) as well as the finite superfield-dependent BRST symmetry transformations which leave the effective theory invariant. The effects of finite superfield-dependent BRST transformations on the path integral (so-called void functional in the case of third quantization) are implemented. Within the finite superfield-dependent BRST formulation, the finite superfield-dependent BRST transformations with specific parameter switch the void functional from one gauge to another. We establish this result for the most general gauge with the help of explicit calculations which holds for all possible sets of gauge choices at both the classical and the quantum levels.

Line splitting and modified atomic decay of atoms coupled with N quantized cavity modes

NASA Astrophysics Data System (ADS)

Zhu, Yifu

1992-05-01

We study the interaction of a two-level atom with N non-degenerate quantized cavity modes including dissipations from atomic decay and cavity damps. In the strong coupling regime, the absorption or emission spectrum of weakly excited atom-cavity system possesses N + 1 spectral peaks whose linewidths are the weighted averages of atomic and cavity linewidths. The coupled system shows subnatural (supernatural) atomic decay behavior if the photon loss rates from the N cavity modes are smaller (larger) than the atomic decay rate. If N cavity modes are degenerate, they can be treated effectively as a single mode. In addition, we present numerical calculations for N = 2 to characterize the system evolution from the weak coupling to strong coupling limits.

Chiral vacuum fluctuations in quantum gravity.

PubMed

Magueijo, João; Benincasa, Dionigi M T

2011-03-25

We examine tensor perturbations around a de Sitter background within the framework of Ashtekar's variables and its cousins parameterized by the Immirzi parameter γ. At the classical level we recover standard cosmological perturbation theory, with illuminating insights. Quantization leads to real novelties. In the low energy limit we find a second quantized theory of gravitons which displays different vacuum fluctuations for right and left gravitons. Nonetheless right and left gravitons have the same (positive) energies, resolving a number of paradoxes suggested in the literature. The right-left asymmetry of the vacuum fluctuations depends on γ and the ordering of the Hamiltonian constraint, and it would leave a distinctive imprint in the polarization of the cosmic microwave background, thus opening quantum gravity to observational test.

Performance of noncoherent MFSK channels with coding

NASA Technical Reports Server (NTRS)

Butman, S. A.; Lyon, R. F.

1974-01-01

Computer simulation of data transmission over a noncoherent channel with predetection signal-to-noise ratio of 1 shows that convolutional coding can reduce the energy requirement by 4.5 dB at a bit error rate of 0.001. The effects of receiver quantization and choice of number of tones are analyzed; nearly optimum performance is attained with eight quantization levels and sixteen tones at predetection S/N ratio of 1. The effects of changing predetection S/N ratio are also analyzed; for lower predetection S/N ratio, accurate extrapolations can be made from the data, but for higher values, the results are more complicated. These analyses will be useful in designing telemetry systems when coherence is limited by turbulence in the signal propagation medium or oscillator instability.

Progress with viral vectored malaria vaccines: A multi-stage approach involving "unnatural immunity".

PubMed

Ewer, Katie J; Sierra-Davidson, Kailan; Salman, Ahmed M; Illingworth, Joseph J; Draper, Simon J; Biswas, Sumi; Hill, Adrian V S

2015-12-22

Viral vectors used in heterologous prime-boost regimens are one of very few vaccination approaches that have yielded significant protection against controlled human malaria infections. Recently, protection induced by chimpanzee adenovirus priming and modified vaccinia Ankara boosting using the ME-TRAP insert has been correlated with the induction of potent CD8(+) T cell responses. This regimen has progressed to field studies where efficacy against infection has now been reported. The same vectors have been used pre-clinically to identify preferred protective antigens for use in vaccines against the pre-erythrocytic, blood-stage and mosquito stages of malaria and this work is reviewed here for the first time. Such antigen screening has led to the prioritization of the PfRH5 blood-stage antigen, which showed efficacy against heterologous strain challenge in non-human primates, and vectors encoding this antigen are in clinical trials. This, along with the high transmission-blocking activity of some sexual-stage antigens, illustrates well the capacity of such vectors to induce high titre protective antibodies in addition to potent T cell responses. All of the protective responses induced by these vectors exceed the levels of the same immune responses induced by natural exposure supporting the view that, for subunit vaccines to achieve even partial efficacy in humans, "unnatural immunity" comprising immune responses of very high magnitude will need to be induced. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Determinants of Health Service Responsiveness in Community-Based Vector Surveillance for Chagas Disease in Guatemala, El Salvador, and Honduras.

PubMed

Hashimoto, Ken; Zúniga, Concepción; Romero, Eduardo; Morales, Zoraida; Maguire, James H

2015-01-01

Central American countries face a major challenge in the control of Triatoma dimidiata, a widespread vector of Chagas disease that cannot be eliminated. The key to maintaining the risk of transmission of Trypanosoma cruzi at lowest levels is to sustain surveillance throughout endemic areas. Guatemala, El Salvador, and Honduras integrated community-based vector surveillance into local health systems. Community participation was effective in detection of the vector, but some health services had difficulty sustaining their response to reports of vectors from the population. To date, no research has investigated how best to maintain and reinforce health service responsiveness, especially in resource-limited settings. We reviewed surveillance and response records of 12 health centers in Guatemala, El Salvador, and Honduras from 2008 to 2012 and analyzed the data in relation to the volume of reports of vector infestation, local geography, demography, human resources, managerial approach, and results of interviews with health workers. Health service responsiveness was defined as the percentage of households that reported vector infestation for which the local health service provided indoor residual spraying of insecticide or educational advice. Eight potential determinants of responsiveness were evaluated by linear and mixed-effects multi-linear regression. Health service responsiveness (overall 77.4%) was significantly associated with quarterly monitoring by departmental health offices. Other potential determinants of responsiveness were not found to be significant, partly because of short- and long-term strategies, such as temporary adjustments in manpower and redistribution of tasks among local participants in the effort. Consistent monitoring within the local health system contributes to sustainability of health service responsiveness in community-based vector surveillance of Chagas disease. Even with limited resources, countries can improve health service responsiveness with thoughtful strategies and management practices in the local health systems.