Digital Commons Network^™

Treatment For Adolescents With Depression Study (Tads): Safety Results., Graham Emslie, Christopher J. Kratochvil, Benedetto Vitiello, Susan Silva, Taryn Mayes, Steven Mcnulty, Elizabeth Weller, Bruce Waslick, Charles Casat, John Walkup, Sanjeev Pathak, Paul Rohde, Kelly Posner, John March, The Columbia Suicidality Classification Group, Tads Team

Journal Articles: Psychiatry

OBJECTIVE: To compare the rates of physical, psychiatric, and suicide-related events in adolescents with MDD treated with fluoxetine alone (FLX), cognitive-behavioral therapy (CBT), combination treatment (COMB), or placebo (PBO).

METHOD: Safety assessments included adverse events (AEs) collected by spontaneous report, as well as systematic measures for specific physical and psychiatric symptoms. Suicidal ideation and suicidal behavior were systematically assessed by self- and clinician reports. Suicidal events were also reanalyzed by the Columbia Group and expert raters using the Columbia-Classification Algorithm for Suicidal Assessment used in the U.S. Food and Drug Administration reclassification effort.

RESULTS: Depressed adolescents reported high rates of …

Improving Database Quality Through Eliminating Duplicate Records, Mingzhen Wei, Andrew H. Sung, Martha E. Cather

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Redundant or duplicate data are the most troublesome problem in database management and applications. Approximate field matching is the key solution to resolve the problem by identifying semantically equivalent string values in syntactically different representations. This paper considers token-based solutions and proposes a general field matching framework to generalize the field matching problem in different domains. By introducing a concept of String Matching Points (SMP) in string comparison, string matching accuracy and efficiency are improved, compared with other commonly-applied field matching algorithms. The paper discusses the development of field matching algorithms from the developed general framework. The framework and corresponding …

Optimal Band Selection For Hyperspectral Remote Sensing Of Aquatic Benthic Features - A Wavelet Filter Window Approach, Charles R. Bostater

Ocean Engineering and Marine Sciences Faculty Publications

This paper describes a wavelet based approach to derivative spectroscopy. The approach is utilized to select, through optimization, optimal channels or bands to use as derivative based remote sensing algorithms. The approach is applied to airborne and modeled or synthetic reflectance signatures of environmental media and features or objects within such media, such as benthic submerged vegetation canopies. The technique can also applied to selected pixels identified within a hyperspectral image cube obtained from an board an airborne, ground based, or subsurface mobile imaging system. This wavelet based image processing technique is an extremely fast numerical method to conduct higher …

Inherited Redundancy And Configurability Utilization For Repairing Nanowire Crossbars With Clustered Defects, Yadunandana Yellambalase, Minsu Choi, Yong-Bin Kim

Electrical and Computer Engineering Faculty Research & Creative Works

With the recent development of nanoscale materials and assembly techniques, it is envisioned to build high-density reconfigurable systems which have never been achieved by the photolithography. Various reconfigurable architectures have been proposed based on nanowire crossbar structure as the primitive building block. Unfortunately, high-density systems consisting of nanometer-scale elements are likely to have many imperfections and variations; thus, defect-tolerance is considered as one of the most exigent challenges. In this paper, we evaluate three different logic mapping algorithms with defect avoidance to circumvent clustered defective crosspoints in nanowire reconfigurable crossbar architectures. The effectiveness of inherited redundancy and configurability utilization is …

Characterizing Package/Pcb Pdn Interactions From A Full-Wave Finite-Difference Formulation, Shishuang Sun, David Pommerenke, James L. Drewniak, Kai Xiao, Sin-Ting Chen, Tzong-Lin Wu

Electrical and Computer Engineering Faculty Research & Creative Works

A novel approach of equivalent circuit model extraction is developed for modeling of integrated package and PCB power distribution networks (PDN). The integrated PDNs are formulated from a full-wave finite-difference algorithm, and the resulting matrix equations are converted to equivalent circuits. The equivalent circuits, as well as the decoupling capacitors and the attached circuit components, can be analyzed with a SPICE-like solver in both the time and frequency domains. The modeling of dielectric loss is also addressed. The method is used to model three PDN problems including a simple power bus, a BGA package mounting on a PCB, and a …

Extraction Of Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

In information retrieval, retrieving relevant passages, as opposed to whole documents, not only directly benefits the end user by filtering out the irrelevant information within a long relevant document, but also improves retrieval accuracy in general. A critical problem in passage retrieval is to extract coherent relevant passages accurately from a document, which we refer to as passage extraction. While much work has been done on passage retrieval, the passage extraction problem has not been seriously studied. Most existing work tends to rely on presegmenting documents into fixed-length passages which are unlikely optimal because the length of a relevant passage …

Bounded Search For De Novo Identification Of Degenerate Cis-Regulatory Elements, Jonathan M. Carlson, Arijit Chakravarty, Radhika S. Khetani, Robert H. Gross

Dartmouth Scholarship

The identification of statistically overrepresented sequences in the upstream regions of coregulated genes should theoretically permit the identification of potential cis-regulatory elements. However, in practice many cis-regulatory elements are highly degenerate, precluding the use of an exhaustive word-counting strategy for their identification. While numerous methods exist for inferring base distributions using a position weight matrix, recent studies suggest that the independence assumptions inherent in the model, as well as the inability to reach a global optimum, limit this approach.

Identification Of Gene Expression Patterns Using Planned Linear Contrasts, Hao Li, Constance L. Wood, Yushu Liu, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With the same timing of the initial change, genes which share similar patterns of expression for any number of sampling intervals from the beginning should be considered co-expressed at certain level(s) in the gene networks. In addition, multiple testing problems are complicated in experiments with multi-level treatments when thousands of genes are involved.

RESULTS: To address these issues, we first performed an ANOVA F test to identify significantly regulated genes. The Benjamini and …

Multiobjective Plan Selection Optimization For Traffic Responsive Control, Montasir M. Abbas, Anuj Sharma

Department of Civil and Environmental Engineering: Faculty Publications

Optimal coordination of traffic signals requires proper activation of timing plans to match current traffic conditions. One of the greatest challenges in configuring a traffic responsive plan selection control mode is how to select only n number of timing plans (restricted by traffic controller memory limitations) to address possibly all traffic conditions/states that can be encountered in the field, for a specific site, but most importantly, how to associate each of these traffic conditions to one of the n timing plans stored in the traffic controller. This paper uses a multiobjective non-dominated sorting genetic algorithm to (1) select the best …

Kalman Filtering With Inequality Constraints For Turbofan Engine Health Estimation, Daniel J. Simon, Donald L. Simon

Electrical and Computer Engineering Faculty Publications

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state-variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. Thus, two analytical methods to incorporate state-variable inequality constraints into the Kalman filter are now derived. The first method is a general technique that uses hard constraints to enforce inequalities on the state-variable estimates. The resultant filter is a combination …

Dissecting Trait Heterogeneity: A Comparison Of Three Clustering Methods Applied To Genotypic Data, Tricia A. Thornton-Wells, Jason H. Moore, Jonathan L. Haines

Dartmouth Scholarship

Background: Trait heterogeneity, which exists when a trait has been defined with insufficient specificity such that it is actually two or more distinct traits, has been implicated as a confounding factor in traditional statistical genetics of complex hu man disease. In the absence of de tailed phenotypic data collected consistently in combination with genetic data, unsupervised computational methodologies offer the potential for discovering underlying trait heteroge neity. The performance of three such methods – Bayesian Classification, Hyperg raph-Based Clustering, and Fuzzy k -Modes Clustering – appropriate for categorical data were comp ared. Also tested was the ability of these methods …

Engineering A Suburban Ad-Hoc Network, Mike Tyson, Ronald D. Pose, Carlo Kopp, Mohammad Rokonuzzaman, Muhammad Mahmudul Islam

Australian Information Warfare and Security Conference

Networks are growing in popularity, as wireless communication hardware, both fixed and mobile, becomes more common and affordable. The Monash Suburban Ad-Hoc Network (SAHN) project has devised a system that provides a highly secure and survivable ad-hoc network, capable of delivering broadband speeds to co-operating users within a fixed environment, such as a residential neighbourhood, or a campus. The SAHN can be used by residents within a community to exchange information, to share access to the Internet, providing last-mile access, or for local telephony and video conferencing. SAHN nodes are designed to be self-configuring and selfmanaging, relying on no experienced …

Bifurcation And Singularity Analysis Of A Molecular Network For The Induction Of Long-Term Memory, Hao Song, Paul Smolen, Evyatar Av-Ron, Douglas A. Baxter, John H H. Byrne

Journal Articles

Withdrawal reflexes of the mollusk Aplysia exhibit sensitization, a simple form of long-term memory (LTM). Sensitization is due, in part, to long-term facilitation (LTF) of sensorimotor neuron synapses. LTF is induced by the modulatory actions of serotonin (5-HT). Pettigrew et al. developed a computational model of the nonlinear intracellular signaling and gene network that underlies the induction of 5-HT-induced LTF. The model simulated empirical observations that repeated applications of 5-HT induce persistent activation of protein kinase A (PKA) and that this persistent activation requires a suprathreshold exposure of 5-HT. This study extends the analysis of the Pettigrew model by applying …

A Multivariate Prediction Model For Microarray Cross-Hybridization, Yian A. Chen, Cheng-Chung Chou, Xinghua Lu, Elizabeth H. Slate, Konan Peck, Wenying Xu, Eberhand O. Voit, Jonas S. Almeida

MUSC Faculty Journal Articles

Background: Expression microarray analysis is one of the most popular molecular diagnostic techniques in the post-genomic era. However, this technique faces the fundamental problem of potential cross-hybridization. This is a pervasive problem for both oligonucleotide and cDNA microarrays; it is considered particularly problematic for the latter. No comprehensive multivariate predictive modeling has been performed to understand how multiple variables contribute to (cross-) hybridization. Results: We propose a systematic search strategy using multiple multivariate models [multiple linear regressions, regression trees, and artificial neural network analyses (ANNs)] to select an effective set of predictors for hybridization. We validate this approach on a …

Crosscutting Score: An Indicator Metric For Aspect Orientation, Subhajit Datta

Research Collection School Of Computing and Information Systems

Aspect Oriented Programming (AOP) provides powerful techniques for modeling and implementing enterprise software systems. To leverage its full potential, AOP needs to be perceived in the context of existing methodologies such as Object Oriented Programming (OOP). This paper addresses an important question for AOP practitioners - how to decide whether a component is best modeled as a class or an aspect? Towards that end, we present an indicator metric, the Crosscutting Score and a method for its calculation and interpretation. We will illustrate our approach through a sample calculation.

Gpnn: Power Studies And Applications Of A Neural Network Method For Detecting Gene-Gene Interactions In Studies Of Human Disease, Alison A. Motsinger, Stephen L. Lee, George Mellick, Marylyn D. Ritchie

Dartmouth Scholarship

The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease.

The Convergence Of V-Cycle Multigrid Algorithms For Axisymmetric Laplace And Maxwell Equations, Jay Gopalakrishnan, Joseph E. Pasciak

Mathematics and Statistics Faculty Publications and Presentations

We investigate some simple finite element discretizations for the axisymmetric Laplace equation and the azimuthal component of the axisymmetric Maxwell equations as well as multigrid algorithms for these discretizations. Our analysis is targeted at simple model problems and our main result is that the standard V-cycle with point smoothing converges at a rate independent of the number of unknowns. This is contrary to suggestions in the existing literature that line relaxations and semicoarsening are needed in multigrid algorithms to overcome difficulties caused by the singularities in the axisymmetric Maxwell problems. Our multigrid analysis proceeds by applying the well known regularity …

Performance Evaluation Of Vertical Handoff Decision Algorithms In Heterogeneous Wireless Networks, Min Liu, Zhong-Cheng Li, Xiao-Bing Guo, Eryk Dutkiewicz, De-Kui Zhang

Faculty of Informatics - Papers (Archive)

In recent years, many research works have focused on vertical handoff (VHO) decision algorithms. However, evaluation scenarios in different papers are often quite different and there is no consensus on how to evaluate performance of VHO algorithms. In this paper, we address this important issue by proposing an approach for systematic and thorough performance evaluation of VHO algorithms. Firstly we define the evaluation criteria for VHO with two metrics: matching ratio and average ping-pong number. Subsequently we analyze the general movement characteristics of mobile hosts and identify a set of novel performance evaluation models for VHO algorithms. Equipped with these …

An Improved Ant Colony Algorithm With Diversified Solutions Based On The Immune Strategy, Ling Qin, Yi Pan, Ling Chen, Yixin Chen

Computer Science Faculty Publications

Background: Ant colony algorithm has emerged recently as a new meta- heuristic method, which is inspired from the behaviours of real ants for solving NP-hard problems. However, the classical ant colony algorithm also has its defects of stagnation and premature. This paper aims at remedying these problems.

Results: In this paper, we propose an adaptive ant colony algorithm that simulates the behaviour of biological immune system. The solutions of the problem are much more diversified than traditional ant colony algorithms.

Conclusion: The proposed method for improving the performance of traditional ant colony algorithm takes into account the polarization of the …

A Novel Approach To Phylogenetic Tree Construction Using Stochastic Optimization And Clustering, Ling Qin, Yixin Chen, Yi Pan, Ling Chen

Computer Science Faculty Publications

Background: The problem of inferring the evolutionary history and constructing the phylogenetic tree with high performance has become one of the major problems in computational biology.

Results: A new phylogenetic tree construction method from a given set of objects (proteins, species, etc.) is presented. As an extension of ant colony optimization, this method proposes an adaptive phylogenetic clustering algorithm based on a digraph to find a tree structure that defines the ancestral relationships among the given objects.

Conclusion: Our phylogenetic tree construction method is tested to compare its results with that of the genetic algorithm (GA). Experimental results show that …

Fitness Evaluation For Structural Optimisation Genetic Algorithms Using Neural Networks, Koren Ward, Timothy J. Mccarthy

Faculty of Informatics - Papers (Archive)

This paper relates to the optimisation of structural design using Genetic Algorithms (GAs) and presents an improved method for determining the fitness of genetic codes that represent possible design solutions by using a neural network to generalize fitness. Two problems that often impede design optimization using genetic algorithms are expensive fitness evaluation and high epistasis. In this paper we show that by using a neural network as a fitness approximator, optimal solutions to certain design problems can be achieved in significantly less generations and with considerably less fitness evaluations.

Automatic Colonic Polyp Detection Using Multiobjective Evolutionary Techniques, Jiang Li, Adam Huang, Jianhua Yao, Ingmar Bitter, Nicholas Petrick, Ronald M. Summers, Perry J. Pickhardt, J. Richard Choi

Electrical & Computer Engineering Faculty Publications

Colonie polyps appear like elliptical protrusions on the inner wall of the colon. Curvature based features for colonie polyp detection have proved to be successful in several computer-aided diagnostic CT colonography (CTC) systems. Some simple thresholds are set for those features for creating initial polyp candidates, sophisticated classification scheme are then applied on these polyp candidates to reduce false positives. There are two objective functions, the number of missed polyps and false positive rate, that need to be minimized when setting those thresholds. These two objectives conflict and it is usually difficult to optimize them both by a gradient search. …

Spatiotemporal Dynamics Of Networks Of Excitable Nodes, Aaron J. Steele, Mark Tinsley, Kenneth Showalter

Faculty & Staff Scholarship

No abstract provided.

Using Citation Data To Improve Retrieval From Medline., Elmer V Bernstam, Jorge R Herskovic, Yindalon Aphinyanaphongs, Constantin F Aliferis, Madurai G Sriram, William R Hersh

Journal Articles

OBJECTIVE: To determine whether algorithms developed for the World Wide Web can be applied to the biomedical literature in order to identify articles that are important as well as relevant. DESIGN AND MEASUREMENTS A direct comparison of eight algorithms: simple PubMed queries, clinical queries (sensitive and specific versions), vector cosine comparison, citation count, journal impact factor, PageRank, and machine learning based on polynomial support vector machines. The objective was to prioritize important articles, defined as being included in a pre-existing bibliography of important literature in surgical oncology. RESULTS Citation-based algorithms were more effective than noncitation-based algorithms at identifying important articles. …

Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …

Laboratory Diagnosis Of Tuberculosis In Primary Care, David Brett-Major, Thomas E. Walsh

Journal Articles: Epidemiology

No abstract provided.