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Articles 1081 - 1110 of 2075
Full-Text Articles in Computer Sciences
Flexible Gating Of Contextual Influences In Natural Vision, Odelia Schwartz
Flexible Gating Of Contextual Influences In Natural Vision, Odelia Schwartz
Mathematics Colloquium Series
An appealing hypothesis suggests that neurons represent inputs in a coordinate system that is matched to the statistical structure of images in the natural environment. I discuss theoretical work on unsupervised learning of statistical regularities in natural images. In the model, Bayesian inference amounts to a generalized form of divisive normalization, a canonical computation that has been implicated in many neural areas. In our framework, divisive normalization is flexible: it is recruited only when the image is inferred to contain dependencies, and muted otherwise. I particularly focus on recent work in which we have applied this approach to understanding spatial …
Feedback-Driven Radiology Exam Report Retrieval With Semantics, Sarasi Lalithsena, Luis Tari, Anna Von Reden, Benjamin Wilson, Brian J. Kolowitz, John Kalafut, Steven Gustafson, Amit P. Sheth
Feedback-Driven Radiology Exam Report Retrieval With Semantics, Sarasi Lalithsena, Luis Tari, Anna Von Reden, Benjamin Wilson, Brian J. Kolowitz, John Kalafut, Steven Gustafson, Amit P. Sheth
Kno.e.sis Publications
Clinical documents are vital resources for radiologists to have a better understanding of patient history. The use of clinical documents can complement the often brief reasons for exams that are provided by physicians in order to perform more informed diagnoses. With the large number of study exams that radiologists have to perform on a daily basis, it becomes too time-consuming for radiologists to sift through each patient's clinical documents. It is therefore important to provide a capability that can present contextually relevant clinical documents, and at the same time satisfy the diverse information needs among radiologists from different specialties. In …
Social Health Signals, Ashutosh Sopan Jadhav, Swapnil Soni, Amit P. Sheth
Social Health Signals, Ashutosh Sopan Jadhav, Swapnil Soni, Amit P. Sheth
Kno.e.sis Publications
Recently Twitter, has emerged as one of the primary medium for sharing and seeking of the latest information related to variety of the topics including health information. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, identification of useful information from the deluge of tweets is one of the major challenge. Twitter search is limited to keyword based techniques to retrieve information for a given query and sometimes the results do not contain real-time information. Moreover, …
A Computational Model Of The Spread Of Ancient Human Populations Based On Mitochondrial Dna Samples, Peter Revesz
A Computational Model Of The Spread Of Ancient Human Populations Based On Mitochondrial Dna Samples, Peter Revesz
School of Computing: Conference and Workshop Papers
The extraction of mitochondrial DNA (mtDNA) from ancient human population samples provides important data for the reconstruction of population influences, spread and evolution from the Neolithic to the present. This paper presents a mtDNA-based similarity measure between pairs of human populations and a computational model for the evolution of human populations. In a computational experiment, the paper studies the mtDNA information from five Neolithic and Bronze Age populations, namely the Andronovo, the Bell Beaker, the Minoan, the Rössen and the Únětice populations. In the past these populations were identified as separate cultural groups based on geographic location, age and the …
Implicit Information Extraction From Clinical Notes, Sujan Perera
Implicit Information Extraction From Clinical Notes, Sujan Perera
Kno.e.sis Publications
We address the problem of extracting implicit information from the unstructured clinical notes. Here we introduce the problem of 'implicit entity recognition in clinical notes', propose a knowledge driven approach to address this problem and demonstrate the results of our initial experiments.
An Incremental Phylogenetic Tree Algorithm Based On Repeated Insertions Of Species, Peter Revesz, Zhiqiang Li
An Incremental Phylogenetic Tree Algorithm Based On Repeated Insertions Of Species, Peter Revesz, Zhiqiang Li
School of Computing: Conference and Workshop Papers
In this paper, we introduce a new phylogenetic tree algorithm that generates phylogenetic trees by repeatedly inserting species one-by-one. The incremental phylogenetic tree algorithm can work on proteins or DNA sequences. Computer experiments show that the new algorithm is better than the commonly used UPGMA and Neighbor Joining algorithms.
Ezdi's Semantics-Enhanced Linguistic, Nlp, And Ml Approach For Health Informatics, Raxit Goswami, Neil Shah, Amit P. Sheth
Ezdi's Semantics-Enhanced Linguistic, Nlp, And Ml Approach For Health Informatics, Raxit Goswami, Neil Shah, Amit P. Sheth
Kno.e.sis Publications
ezDI uses large and extensive knowledge graph to enhance linguistics, NLP and ML techniques to improve structured data extraction from millions of EMR records. It then normalizes it, and maps it with various computer-processable nomenclature such as SNOMED-CT, RxNorm, ICD-9, ICD-10, CPT, and LOINC. Furthermore, it applies advanced reasoning that exploited domain-specific and hierarchical relationships among entities in the knowledge graph to make the data actionable. These capabilities are part of its highly scalable AWS deployed heath intelligence platform that support healthcare informatics applications, including Computer Assisted Coding (CAC), Computerized Document Improvement (CDI), compliance and audit, and core measures and …
Mutations Of Adjacent Amino Acid Pairs Are Not Always Independent, Jyotsna Ramanan, Peter Revesz
Mutations Of Adjacent Amino Acid Pairs Are Not Always Independent, Jyotsna Ramanan, Peter Revesz
School of Computing: Conference and Workshop Papers
Evolutionary studies usually assume that the genetic mutations are independent of each other. This paper tests the independence hypothesis for genetic mutations with regard to protein coding regions. According to the new experimental results the independence assumption generally holds, but there are certain exceptions. In particular, the coding regions that represent two adjacent amino acids seem to change in ways that sometimes deviate significantly from the expected theoretical probability under the independence assumption.
Efficient Algorithms For Prokaryotic Whole Genome Assembly And Finishing, Abhishek Biswas
Efficient Algorithms For Prokaryotic Whole Genome Assembly And Finishing, Abhishek Biswas
Computer Science Theses & Dissertations
De-novo genome assembly from DNA fragments is primarily based on sequence overlap information. In addition, mate-pair reads or paired-end reads provide linking information for joining gaps and bridging repeat regions. Genome assemblers in general assemble long contiguous sequences (contigs) using both overlapping reads and linked reads until the assembly runs into an ambiguous repeat region. These contigs are further bridged into scaffolds using linked read information. However, errors can be made in both phases of assembly due to high error threshold of overlap acceptance and linking based on too few mate reads. Identical as well as similar repeat regions can …
A Gene-Based Association Method For Mapping Traits Using Reference Transcriptome Data, Eric R. Gamazon, Heather Wheeler, Kaanan P. Shah, Sahar V. Mozaffari, Keston Aquino-Michaels, Robert J. Carroll, Anne E. Eyler, Joshua C. Denny, Gtex Consortium, Dan L. Nicolae, Nancy J. Cox, Hae Kyung Im
A Gene-Based Association Method For Mapping Traits Using Reference Transcriptome Data, Eric R. Gamazon, Heather Wheeler, Kaanan P. Shah, Sahar V. Mozaffari, Keston Aquino-Michaels, Robert J. Carroll, Anne E. Eyler, Joshua C. Denny, Gtex Consortium, Dan L. Nicolae, Nancy J. Cox, Hae Kyung Im
Bioinformatics Faculty Publications
Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype. The approach estimates the component of gene expression determined by an individual’s genetic profile and correlates ‘imputed’ gene expression with the phenotype under investigation to identify genes involved in the etiology of the phenotype. Genetically regulated gene expression is estimated using whole-genome tissue-dependent prediction models trained with reference transcriptome data sets. PrediXcan enjoys …
Automatic Emotion Identification From Text, Wenbo Wang
Automatic Emotion Identification From Text, Wenbo Wang
Kno.e.sis Publications
Emotions are both prevalent in and essential to most aspects of our lives. They in- fluence our decision-making, affect our social relationships and shape our daily behavior. With the rapid growth of emotion-rich textual content, such as microblog posts, blog posts, and forum discussions, there is a growing need to develop algorithms and techniques for identifying people’s emotions expressed in text. It has valuable implications for the studies of suicide prevention, employee productivity, well-being of people, customer relationship management, etc. However, emotion identification is quite challenging partly due to the following reasons: i) It is a multi-class classification problem that …
Spontaneous Synchrony On Graphs And The Emergence Of Order From Disorder, Dylan Linville, Daniel Trugillo Martins Fontes
Spontaneous Synchrony On Graphs And The Emergence Of Order From Disorder, Dylan Linville, Daniel Trugillo Martins Fontes
Rose-Hulman Undergraduate Research Publications
From pulsars to pedestrians and bacteria to brain cells, objects that exhibit cyclical behavior, called oscillators, are found in a variety of different settings. When oscillators adjust their behavior in response to nearby oscillators, they often achieve a state of synchrony, in which they all have the same phase and frequency. Here, we explore the Kuramoto model, a simple and general model which describes oscillators as dynamical systems on a graph and has been used to study synchronization in systems ranging from firefly swarms to the power grid. We discuss analytical and numerical methods used to investigate the governing system …
Naturalists’ Perspectives On The Use Of Mobile Technology During A Nature Hike, Aubin Marishka Radzewicz St. Clair
Naturalists’ Perspectives On The Use Of Mobile Technology During A Nature Hike, Aubin Marishka Radzewicz St. Clair
Master's Theses
Naturalists act as our link between scientific knowledge and the public’s understanding of natural history and conservation efforts. In order for them to succeed, they need access to reference materials as well as up-to-date information (Mankin, Warner, & Anderson, 1999). Incorporating mobile technology (i.e. tablets) into naturalists’ endeavors in natural history and environmental education can be used as supportive and educational tools. My project investigated how newly trained naturalists used tablet technology while leading groups of children on nature hikes. I investigated naturalists’ views on the use of mobile technology as a tool during the hikes. My research was guided …
Scalable Euclidean Embedding For Big Data, Zohreh S. Alavi, Sagar Sharma, Lu Zhou, Keke Chen
Scalable Euclidean Embedding For Big Data, Zohreh S. Alavi, Sagar Sharma, Lu Zhou, Keke Chen
Kno.e.sis Publications
Euclidean embedding algorithms transform data defined in an arbitrary metric space to the Euclidean space, which is critical to many visualization techniques. At big-data scale, these algorithms need to be scalable to massive dataparallel infrastructures. Designing such scalable algorithms and understanding the factors affecting the algorithms are important research problems for visually analyzing big data. We propose a framework that extends the existing Euclidean embedding algorithms to scalable ones. Specifically, it decomposes an existing algorithm into naturally parallel components and non-parallelizable components. Then, data parallel implementations such as MapReduce and data reduction techniques are applied to the two categories of …
An Apache Hadoop Framework For Large-Scale Peptide Identification, Harinivesh Donepudi
An Apache Hadoop Framework For Large-Scale Peptide Identification, Harinivesh Donepudi
Masters Theses & Specialist Projects
Peptide identification is an essential step in protein identification, and Peptide Spectrum Match (PSM) data set is huge, which is a time consuming process to work on a single machine. In a typical run of the peptide identification method, PSMs are positioned by a cross correlation, a statistical score, or a likelihood that the match between the trial and hypothetical is correct and unique. This process takes a long time to execute, and there is a demand for an increase in performance to handle large peptide data sets. Development of distributed frameworks are needed to reduce the processing time, but …
Interdisciplinary Modeling For Water-Related Issues Graduate Course, Laurel Saito, Alexander Fernald, Timothy Link
Interdisciplinary Modeling For Water-Related Issues Graduate Course, Laurel Saito, Alexander Fernald, Timothy Link
All ECSTATIC Materials
The science and management of aquatic ecosystems is inherently interdisciplinary, with issues associated with hydrology, atmospheric science, water quality, geochemistry, sociology, economics, environmental science, and ecology. Addressing water resources issues in any one discipline invariably involves effects that concern other disciplines, and attempts to address one issue often have consequences that exacerbate existing issues or concerns, or create new ones (Jørgensen et al. 1992; Lackey et al. 1975; Straskraba 1994) due to the strongly interactive nature of key processes (Christensen et al. 1996). Thus, research and management of aquatic ecosystems must be interdisciplinary to be most effective, but such truly …
Evaluating A Potential Commercial Tool For Healthcare Application For People With Dementia, Tanvi Banerjee, Pramod Anantharam, William L. Romine, Larry Wayne Lawhorne
Evaluating A Potential Commercial Tool For Healthcare Application For People With Dementia, Tanvi Banerjee, Pramod Anantharam, William L. Romine, Larry Wayne Lawhorne
Kno.e.sis Publications
The widespread use of smartphones and sensors has made physiology, environment, and public health notifications amenable to continuous monitoring. Personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context, converting relevant medical knowledge into actionable information for better and timely decisions. We apply these principles in the healthcare domain of dementia. Specifically, in this study we validate one of our sensor platforms to ascertain whether it will be suitable for detecting physiological changes that may help us detect changes in people with dementia. This study shows …
Domain Specific Document Retrieval Framework For Real-Time Social Health Data, Swapnil Soni
Domain Specific Document Retrieval Framework For Real-Time Social Health Data, Swapnil Soni
Kno.e.sis Publications
With the advent of the web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these online services to share and seek health real-time information has in- creased exponentially. OHIS use web search engines or microblogging search services to seek out latest, relevant as well as reliable health in- formation. When OHIS turn to microblogging search services to search real-time content, trends and breaking news, etc. the search results are not promising. Two major challenges exist in the current microblogging search engines are keyword based techniques and results do not contain real-time information. To address these challenges, …
Subject Assessment Of In-Vehicle Auditory Warnings For Rail Grade Crossings, Steven Landry, Jayde Croschere, Myounghoon Jeon
Subject Assessment Of In-Vehicle Auditory Warnings For Rail Grade Crossings, Steven Landry, Jayde Croschere, Myounghoon Jeon
Michigan Tech Publications, Part 1
Human factors research has played an important role in reducing the incidents of vehicle-train collisions at rail grade crossings over the past 30 years. With the growing popularity of in-vehicle infotainment systems and GPS devices, new opportunities arise to cost-efficiently and effectively alert drivers of railroad crossings and to promote safer driving habits. To best utilize this in-vehicle technology, 32 auditory warnings (16 verbal, 7 train-related auditory icons, and 9 generic earcons) were generated and presented to 31 participants after a brief low-fidelity driving simulation. Participants rated each sound on eight dimensions deemed important in previous auditory warning literature. Preliminary …
Zernike Moments And Genetic Algorithm: Tutorial And Application, Oluleye Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen
Zernike Moments And Genetic Algorithm: Tutorial And Application, Oluleye Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen
Grain and Other Field Crops Research Articles
Aims/ objectives: To demontrate effectiveness of Zernike Moments for Image Classification. Zernike moment(ZM) is an excellent region-based moment which has attracted the attentions of many image processing researchers since its first application to image analysis. Many papers have been published on several works done on ZM but no single paper ever give a detailed information of how the computation of ZM is done from the time the image is captured to the computation of ZM. This work showed how to effectively apply ZM on RGB images. We have demonstrated the effectiveness of Zernike moment in image classification system. A neuro-genetic …
Spectrally-Resolved Imaging Of The Transverse Modes In Multimode Vcsels, Stephan A. Misak, Dan G. Dugmore, Kirsten A. Middleton, Evan R. Hale, Kelly R. Farner, Kent D. Choquette, Paul O. Leisher
Spectrally-Resolved Imaging Of The Transverse Modes In Multimode Vcsels, Stephan A. Misak, Dan G. Dugmore, Kirsten A. Middleton, Evan R. Hale, Kelly R. Farner, Kent D. Choquette, Paul O. Leisher
Rose-Hulman Undergraduate Research Publications
Vertical-cavity surface-emitting lasers (VCSELs) enable a range of applications such as data transmission, trace sensing, atomic clocks, and optical mice. For many of these applications, the output power and beam quality are both critical (i.e. high output power with good beam quality is desired). Multi-mode VCSELs offer much higher power than single-mode devices, but this comes at the expense of lower beam quality. Directly observing the resolved mode structure of multi-mode VCSELs would enable engineers to better understand the underlying physics and help them to develop multi-mode devices with improved beam quality. In this work, a low-cost, high-resolution (<3 >pm) …
"Time For Dabs": Analyzing Twitter Data On Butane Hash Oil Use, Raminta Daniulaityte, Robert G. Carlson, Farahnaz Golroo, Sanjaya Wijeratne, Edward W. Boyer, Silvia S. Martins, Ramzi W. Nahhas, Amit P. Sheth
"Time For Dabs": Analyzing Twitter Data On Butane Hash Oil Use, Raminta Daniulaityte, Robert G. Carlson, Farahnaz Golroo, Sanjaya Wijeratne, Edward W. Boyer, Silvia S. Martins, Ramzi W. Nahhas, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Trust Management: Multimodal Data Perspective, Krishnaprasad Thirunarayan
Trust Management: Multimodal Data Perspective, Krishnaprasad Thirunarayan
Kno.e.sis Publications
No abstract provided.
Work Integrated Learning In Stem In Australian Universities: Final Report: Submitted To The Office Of The Chief Scientist, Daniel Edwards, Kate Perkins, Jacob Pearce, Jennifer Hong
Work Integrated Learning In Stem In Australian Universities: Final Report: Submitted To The Office Of The Chief Scientist, Daniel Edwards, Kate Perkins, Jacob Pearce, Jennifer Hong
Higher education research
The Australian Council for Educational Research (ACER) undertook this study for the Office of the Chief Scientist (OCS). It explores the practice and application of Work Integrated Learning (WIL) in STEM, with a particular focus on natural and physical sciences, information technology, and agriculture departments in Australian universities. The project involved a detailed ‘stocktake’ of WIL in practice in these disciplines, with collection of information by interview, survey instruments, consultation with stakeholders and literature reviews. Every university in Australia was visited as part of this project, with interviews and consultation sessions gathering insight from more than 120 academics and support …
Dietary Microrna Database (Dmd): An Archive Database And Analytic Tool For Food-Borne Micrornas, Kevin Chiang, Jiang Shu, Janos Zempleni, Juan Cui
Dietary Microrna Database (Dmd): An Archive Database And Analytic Tool For Food-Borne Micrornas, Kevin Chiang, Jiang Shu, Janos Zempleni, Juan Cui
School of Computing: Faculty Publications
With the advent of high throughput technology, a huge amount of microRNA information has been added to the growing body of knowledge for non-coding RNAs. Here we present the Dietary MicroRNA Databases (DMD), the first repository for archiving and analyzing the published and novel microRNAs discovered in dietary resources. Currently there are fifteen types of dietary species, such as apple, grape, cow milk, and cow fat, included in the database originating from 9 plant and 5 animal species. Annotation for each entry, a mature microRNA indexed as DM0000*, covers information of the mature sequences, genome locations, hairpin structures of parental …
Isquest: Finding Insertion Sequences In Prokaryotic Sequence Fragment Data, Abhishek Biswas, David T. Gauthier, Desh Ranjan, Mohammad Zubair
Isquest: Finding Insertion Sequences In Prokaryotic Sequence Fragment Data, Abhishek Biswas, David T. Gauthier, Desh Ranjan, Mohammad Zubair
Computer Science Faculty Publications
Motivation: Insertion sequences (ISs) are transposable elements present in most bacterial and archaeal genomes that play an important role in genomic evolution. The increasing availability of sequenced prokaryotic genomes offers the opportunity to study ISs comprehensively, but development of efficient and accurate tools is required for discovery and annotation. Additionally, prokaryotic genomes are frequently deposited as incomplete, or draft stage because of the substantial cost and effort required to finish genome assembly projects. Development of methods to identify IS directly from raw sequence reads or draft genomes are therefore desirable. Software tools such as Optimized Annotation System for Insertion Sequences …
Entity Recommendations Using Hierarchical Knowledge Bases, Siva Kumar Cheekula, Pavan Kapanipathi, Derek Doran, Prateek Jain, Amit P. Sheth
Entity Recommendations Using Hierarchical Knowledge Bases, Siva Kumar Cheekula, Pavan Kapanipathi, Derek Doran, Prateek Jain, Amit P. Sheth
Kno.e.sis Publications
Recent developments in recommendation algorithms have focused on integrating Linked Open Data to augment traditional algorithms with background knowledge. These developments recognize that the integration of Linked Open Data may or better performance, particularly in cold start cases. In this paper, we explore if and how a specific type of Linked Open Data, namely hierarchical knowledge, may be utilized for recommendation systems. We propose a content-based recommendation approaches that adapts a spreading activation algorithm over the DBpedia category structure to identify entities of interest to the user. Evaluation of the algorithm over the Movielens dataset demonstrates that our method yields …
Exact Genome Alignment, Nandini Ghosh
Exact Genome Alignment, Nandini Ghosh
Theses
The increase in the volume of genomic data due to the decrease in the cost of whole genome sequencing techniques has opened up new avenues of research in the field of Bioinformatics, like comparative genomics and evolutionary dynamics. The fundamental task in these studies is to align the genome sequences accurately. Sequence alignment helps to identify regions of similarity between the sequences to establish their functional, evolutionary and structural relationship. The thesis investigates the performance of two sequence alignment programs LASTZ, a hash table based faster method and SSEARCH, a slower but more rigorous Smith-Waterman based approach, on whole genome …
Unsupervised Gene Regulatory Network Inference On Microarray Data, Nidhi Radia
Unsupervised Gene Regulatory Network Inference On Microarray Data, Nidhi Radia
Theses
Obtaining gene regulatory networks (GRNs) from expression data is a challenging and crucial task. Many computational methods and algorithms have been developed to infer gene networks for gene expression data, which are usually obtained from microarray experiments. A gene network is a method to depict the relation among clusters of genes. To infer gene networks, the unsupervised method is used in this study. The two types of data used are time-series data and steady-state data. The data is analyzed using various tools containing different algorithms and concepts. GRNs from time-series data tools are obtained using the Time-delayed Algorithm for the …
Identifying Modifier Genes In Sma Model Mice, Weiting Xu
Identifying Modifier Genes In Sma Model Mice, Weiting Xu
Theses
Spinal Muscular Atrophy (SMA) involves the loss of nerve cells called motor neurons in the spinal cord and is classified as a motor neuron disease, it affects 1 in 5000-10000 newborns, one of the leading genetic causes of infant death in USA. Mutations in the SMN1, UBA1, DYNC1H1 and VAPB genes cause spinal muscular atrophy. Extra copies of the SMN2 gene modify the severity of spinal muscular atrophy. Mutations in SMN1 (Motor Neuron 1) mainly causes SMA (Autosomal recessive inheritance). SMN1 gene mutations lead to a shortage of the SMN protein and SMN protein forms SMN complex …