Digital Commons Network^™

Lattice Quantum Algorithm For The Schrodinger Wave Equation In 2+1 Dimensions With A Demonstration By Modeling Soliton Instabilities, Jeffrey Yepez, George Vahala, Linda L. Vahala

Electrical & Computer Engineering Faculty Publications

A lattice-based quantum algorithm is presented to model the non-linear Schrödinger-like equations in 2 + 1 dimensions. In this lattice-based model, using only 2 qubits per node, a sequence of unitary collide (qubit-qubit interaction) and stream (qubit translation) operators locally evolve a discrete field of probability amplitudes that in the long-wavelength limit accurately approximates a non-relativistic scalar wave function. The collision operator locally entangles pairs of qubits followed by a streaming operator that spreads the entanglement throughout the two dimensional lattice. The quantum algorithmic scheme employs a non-linear potential that is proportional to the moduli square of the wave function. …

Principal Component Analysis For Predicting Transcription-Factor Binding Motifs From Array-Derived Data, Yunlong Liu, Matthew P Vincenti, Hiroki Yokota

Dartmouth Scholarship

The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to transcription-factor binding motifs (TFBMs). In order to select a critical set of TFBMs from genomic DNA information and an array-derived data, an efficient algorithm to solve a combinatorial optimization problem is required. Although computational approaches based on evolutionary algorithms are commonly employed, an analytical algorithm would be useful to predict TFBMs at nearly no computational cost and evaluate varying modelling conditions. Singular value decomposition (SVD) is a powerful method to derive primary components of a given matrix. Applying SVD …

Using Genetic Algorithms To Map First-Principles Results To Model Hamiltonians: Application To The Generalized Ising Model For Alloys, Gus L. W. Hart, Volker Blum, Michael J. Walorski, Alex Zunger

Faculty Publications

The cluster expansion method provides a standard framework to map first-principles generated energies for a few selected configurations of a binary alloy onto a finite set of pair and many-body interactions between the alloyed elements. These interactions describe the energetics of all possible configurations of the same alloy, which can hence be readily used to identify ground state structures and, through statistical mechanics solutions, find finite-temperature properties. In practice, the biggest challenge is to identify the types of interactions which are most important for a given alloy out of the many possibilities. We describe a genetic algorithm which automates this …

Near-Infrared Characterization Of Breast Tumors In Vivo Using Spectrally-Constrained Reconstruction, Subhadra Srinivasan, Brian W. Pogue, Ben Brooksby, Shudong Jiang, Hamid Dehghani, Christine Kogel, Wendy A. Wells, Steven P. Poplack, Keith D. Paulsen

Dartmouth Scholarship

Multi-wavelength Near-Infrared (NIR) Tomography was utilized in this study to non-invasively quantify physiological parameters of breast tumors using direct spectral reconstruction. Frequency domain NIR measurements were incorporated with a new spectrally constrained direct chromophore and scattering image reconstruction algorithm, which was validated in simulations and experimental phantoms. Images of total hemoglobin, oxygen saturation, water, and scatter parameters were obtained with higher accuracy than previously reported. Using this spectral approach, in vivo NIR images are presented and interpreted through a series of case studies (n=6 subjects) having differing abnormalities. The corresponding mammograms and ultrasound images are also evaluated. Three of six …

Contrast-Detail Analysis Characterizing Diffuse Optical Fluorescence Tomography Image Reconstruction, Scott C. Davis, Brian W. Pogue, Hamid Dehghani, Keith D. Paulsen

Dartmouth Scholarship

Contrast-detail analysis is used to evaluate the imaging performance of diffuse optical fluorescence tomography (DOFT), characterizing spatial resolution limits, signal-to-noise limits, and the trade-off between object contrast and size. Reconstructed images of fluorescence yield from simulated noisy data were used to determine the contrast-to-noise ratio (CNR). A threshold of CNR=3 was used to approximate a lowest acceptable noise level in the image, as a surrogate measure for human detection of objects. For objects 0.5 cm inside the edge of a simulated tissue region, the smallest diameter that met this criteria was approximately 1.7 mm, regardless of contrast level, and test …

Boosted Decision Trees For Word Recognition In Handwritten Document Retrieval, Nicholas Howe, Toni M. Rath, R. Manmatha

Computer Science: Faculty Publications

Recognition and retrieval of historical handwritten material is an unsolved problem. We propose a novel approach to recognizing and retrieving handwritten manuscripts, based upon word image classification as a key step. Decision trees with normalized pixels as features form the basis of a highly accurate AdaBoost classifier, trained on a corpus of word images that have been resized and sampled at a pyramid of resolutions. To stem problems from the highly skewed distribution of class frequencies, word classes with very few training samples are augmented with stochastically altered versions of the originals. This increases recognition performance substantially. On a standard …

A Three-Dimensional Fdtd Subgridding Method With Separate Spatial And Temporal Subgridding Interfaces, Kai Xiao, David Pommerenke, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

The idea of separating the spatial and temporal subgridding interfaces is introduced in this paper. Based on this idea, the spatial and temporal subgridding algorithms can be developed and analyzed separately. The spatial algorithm was given in the previous paper. In this paper, the temporal subgridding algorithm is described and the stability is illustrated by the analytical formulation of a one-dimensional model. An FDTD code that combines the spatial and temporal subgridding algorithms is implemented. Numerical test models are calculated to show the stability and accuracy of the proposed method.

Hot Event Detection And Summarization By Graph Modeling And Matching, Yuxin Peng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a new approach for hot event detection and summarization of news videos. The approach is mainly based on two graph algorithms: optimal matching (OM) and normalized cut (NC). Initially, OM is employed to measure the visual similarity between all pairs of events under the one-to-one mapping constraint among video shots. Then, news events are represented as a complete weighted graph and NC is carried out to globally and optimally partition the graph into event clusters. Finally, based on the cluster size and globality of events, hot events can be automatically detected and selected as the summaries of …

Wide-Band Lorentzian Media In The Fdtd Algorithm, Marina Koledintseva, James L. Drewniak, David Pommerenke, Giulio Antonini, Antonio Orlandi, Konstantin Rozanov

Electrical and Computer Engineering Faculty Research & Creative Works

This paper considers the case of a wide-band Lorentzian (WBL) algorithm in the finite-difference time-domain (FDTD) modeling of dispersive media. It is shown herein that the WBL model is a physically meaningful and practically useful case of the frequency behavior of materials along with the Debye and narrow-band Lorentzian (NBL). The recursive convolution algorithms for the finite-difference time-domain technique for NBL and WBL models differ. The Debye model, which is suitable for comparatively low-frequency dispersive materials, may not have sufficient number of parameters for describing the wide-band material, especially if this material exhibits pronounced absorption at higher frequencies. It is …

Live Data Views: Programming Pervasive Applications That Use “Timely” And “Dynamic” Data, Jay Black, Paul Castro, Archan Misra, Jerome White

Research Collection School Of Computing and Information Systems

In the absence of generic programming abstractions for dynamic data in most enterprise programming environments, individual applications treat data streams as a special case requiring custom programming. With the growing number of live data sources such as RSS feeds, messaging and presence servers, multimedia streams, and sensor data. a general-purpose client-server programming model is needed to easily incorporate live data into applications. In this paper, we present Live Data Views, a programming abstraction that represents live data as a time-windowed view over a set of data streams. Live Data Views allow applications to create and retrieve stateful abstractions of dynamic …

Quadratic Regression Analysis For Gene Discovery And Pattern Recognition For Non-Cyclic Short Time-Course Microarray Experiments, Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage of the fact that time is a continuous variable, and existing clustering methods often group biologically unrelated genes together.

RESULTS: We propose a quadratic regression method for identification of differentially expressed genes and classification of genes based on their temporal expression profiles for non-cyclic short time-course microarray data. This method treats time as a continuous variable, therefore preserves actual time information. We applied this method to a microarray time-course study of gene expression at short …

'Paclims': A Component Lim System For High-Throughput Functional Genomic Analysis, Nicole Donofrio, Ravi Rajagopalon, Douglas Brown, Stephen Diener, Donald Windham, Shelly Nolin, Anna Floyd, Thomas Mitchell, Natalia Galadima, Sara Tucker, Marc J. Orbach, Gayatri Patel, Mark Farman, Vishal Pampanwar, Cari Soderlund, Yong-Hwan Lee, Ralph A. Dean

Plant Pathology Faculty Publications

BACKGROUND: Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the approximately 11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required.

RESULTS: …

Hydrogeophysical Investigation At Luxor, Southern Egypt, Ahmed Ismail, Neil Lennart Anderson, J. David Rogers

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Over the past 35 years, the exposed stone foundations of the ancient Egyptian monuments at Luxor have deteriorated at an alarmingly accelerated rate. Accelerated deterioration is attributable to three principal factors: 1) excavation and exposure of foundation stone; 2) construction of the Aswan High Dam; and 3) changes in the regional groundwater regime. In an effort to better elucidate the hydrostratigraphy in the Luxor study area that extends from the River Nile to the boundaries of the Nile Valley and covers about 70 km², a geophysical/hydrological investigation was conducted. Forty Schlumberger vertical electrical soundings (VES), two approximately 6 …

Decision Support For Watershed Management Using Evolutionary Algorithms, Misgana K. Muleta, John W. Nicklow

Civil and Environmental Engineering

An integrative computational methodology is developed for the management of nonpoint source pollution from watersheds. The associated decision support system is based on an interface between evolutionary algorithms (EAs) and a comprehensive watershed simulation model, and is capable of identifying optimal or near-optimal land use patterns to satisfy objectives. Specifically, a genetic algorithm (GA) is linked with the U.S. Department of Agriculture’s Soil and Water Assessment Tool (SWAT) for single objective evaluations, and a Strength Pareto Evolutionary Algorithm has been integrated with SWAT for multiobjective optimization. The model can be operated at a small spatial scale, such as a farm …

Random Numbers, Chaos Theory, And Cogitation: A Search For The Minimal Creativity Standard In Copyright Law, Ralph D. Clifford

Faculty Publications

This article explores the second type of expressive work, those where there is a question if the author’s contribution is qualitatively sufficient, to determine how much creativity and of what type is required to sustain a copyright. Initially, the historic standards of creativity use before Fiest was decided in 1991 will be presented. Then, after a brief discussion of Fiest, the scientific basis of creativity will be explored. Next, the confusion regarding creativity that exists in the lower courts will serve to expose the source of misapplication of the law – a disconnect between how courts perceive creativity and …

An Efficient Scheme For Authenticating Public Keys In Sensor Networks, Wenliang Du, Ronghua Wang, Peng Ning

Electrical Engineering and Computer Science - All Scholarship

With the advance of technology, Public Key Cryptography (PKC) will sooner or later be widely used in wireless sensor networks. Recently, it has been shown that the performance of some public key algorithms, such as Elliptic Curve Cryptography (ECC), is already close to being practical on sensor nodes. However, the energy consumption of PKC is still expensive, especially compared to symmetric-key algorithms. To maximize the lifetime of batteries, we should minimize the use of PKC whenever possible in sensor networks. This paper investigates how to replace one of the important PKC operations–the public key authentication–with symmetric key operations that are …

Multiple Description Distributed Image Coding With Side Information For Mobile Wireless Transmission, Min Wu, Daewon Song, Chang Wen Chen

Electrical Engineering and Computer Science Faculty Publications

Multiple description coding (MDC) is a source coding technique that involves coding the source information into multiple descriptions, and then transmitting them over different channels in packet network or error-prone wireless environment to achieve graceful degradation if parts of descriptions are lost at the receiver. In this paper, we proposed a multiple description distributed wavelet zero tree image coding system for mobile wireless transmission. We provide two innovations to achieve an excellent error resilient capability. First, when MDC is applied to wavelet subband based image coding, it is possible to introduce correlation between the descriptions in each subband. We consider …

Using Incomplete Citation Data For Medline Results Ranking., Jorge R Herskovic, Elmer V Bernstam

Journal Articles

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts …