Analysis of Back Propagation Neural Network Method for Heart Disease Recognition: 10.4018/IJOCI.2019040104: ECG is the recording of the electrical activity of the heart, and has become one of the most important tools in the diagnosis of heart diseases. ECG signal is
View more ,Natural gas commonly contains water as a contaminant that can condense to water or form gas hydrates, which causes a range of problems during gas production, transportation, and processing. Therefore, the removal of gas moisture is of great importance. A common and popular method for removing water contamination from natural gas is using solid dehydrators. Calcium chloride is a nonregenerative desiccant to dehydrate natural gas. With continual water adsorption, CaCl2 changes to consecutively higher states of hydration, finally producing a CaCl2 brine solution. This method does not require heating or moving parts. In addition, it does not react with H2S or CO2. These features make this method a popular one for drying natural gas. Nevertheless, precise and simple methods are needed to predict the water content of natural gas dried by calcium chloride dehydrator units. In this study, an intelligent method, called the radial basis function neural network, was incorporated to predict the ...
TY - GEN. T1 - A proposal of «neuron mask» in neural network algorithm for combinatorial optimization problems. AU - Takenaka, Y.. AU - Funabiki, N.. AU - Nishikawa, S.. PY - 1997/12/1. Y1 - 1997/12/1. N2 - A constraint resolution scheme of the Hopfield neural network named «neuron mask» is presented for a class of combinatorial optimization problems. Neuron mask always satisfies constraints of selecting a solution candidate from each group so as to force the state of the neural network into a solution space. This paper presents the definition of neuron mask and the introduction into the neural network through the N-queens problem. The performance is verified by simulations on three computation modes, where neuron mask improves the performance of the neural network.. AB - A constraint resolution scheme of the Hopfield neural network named «neuron mask» is presented for a class of combinatorial optimization problems. Neuron mask always satisfies constraints of selecting a solution candidate ...
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The aim of the research work is to propose an improved iris recognition system using Artificial Neural Network. Personal Authentication and Identity become a challenging task for us. The most recent development in the field of Information Technology with regard to individual authentication and their security moves towards biometric based programmed individual authentication framework. Iris recognition system is being effectively used in places where security is paramount. Iris identification has been found to be very effective in authentication due to its unique features. Iris recognition will perceive a man by breaking down his iris image. Each individual has unique iris and it remains stable throughout the life time of an individual. Iris is an internal organ that is highly secured by the eyelid and cornea. A neural network was created and the partitioned iris image data were given as the inputs. Here the Artificial Neural Network had to compare the iris image with the stored image and ...
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TY - JOUR. T1 - Ab initio quantum mechanical/molecular mechanical molecular dynamics simulation of enzyme catalysis. T2 - The case of histone lysine methyltransferase SET7/9. AU - Wang, Shenglong. AU - Hu, Po. AU - Zhang, Yingkai. PY - 2007/4/12. Y1 - 2007/4/12. N2 - To elucidate enzyme catalysis through computer simulation, a prerequisite is to reliably compute free energy barriers for both enzyme and solution reactions. By employing on-the-fly Born-Oppenheimer molecular dynamics simulations with the ab initio quantum mechanical/molecular mechanical approach and the umbrella sampling method, we have determined free energy profiles for the methyl-transfer reaction catalyzed by the histone lysine methyltransferase SET7/9 and its corresponding uncatalyzed reaction in aqueous solution, respectively. Our calculated activation free energy barrier for the enzyme catalyzed reaction is 22.5 kcal/mol, which agrees very well with the experimental value of 20.9 kcal/mol. The difference in potential of mean ...
The present invention relates to a cassette magnetic tape machine suitable for data read-write on a magnetic tape by utilizing a reading/writing head of a magnetic disk driver. The cassette magnetic tape machine comprises a part A with the size and the shape suitable for the magnetic disk driver to be inserted so that a magnetic tape part is positioned in a position L, and the driver head is conveniently used for transmitting data. The cassette magnetic tape machine comprises a magnetic tape medium, a recording device, a storing device, a conveying device and a connector, wherein the recording device records the magnetic tape medium according to the reading/writing head of the driver; the storing device for storing the magnetic tape medium part is excluded from the part A; the conveying device is used for conveying the magnetic tape medium in the reading/writing head of the magnetic disk driver. The connector which can convey the magnetic tape by a motor of a magnetic disk driver shaft can also
TY - JOUR. T1 - The influence of the amplitude of low-frequency fluctuations on resting-state functional connectivity. AU - Di, Xin. AU - Kim, Eun H.. AU - Huang, Chu Chung. AU - Tsai, Shih Jen. AU - Lin, Ching Po. AU - Biswal, Bharat B.. PY - 2013/3/18. Y1 - 2013/3/18. N2 - Studies of brain functional connectivity have provided a better understanding of organization and integration of large-scale brain networks. Functional connectivity using resting-state functional magnetic resonance imaging (fMRI) is typically based upon the correlations of the low-frequency fluctuation of fMRI signals. Reproducible spatial maps in the brain have also been observed using the amplitude of low-frequency fluctuations (ALFF) in resting-state. However, little is known about the influence of the ALFF on the functional connectivity measures. In the present study, we analyzed resting-state fMRI data on 79 healthy old individuals. Spatial independent component analysis (ICA) and regions of interest (ROIs) based ...
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Until now, a comprehensive textbook covering both ordinary differential equations (ODEs) and partial differential equations (PDEs) didn't exist. We propose a neural network based approach for extracting models from dynamic data using ordinary and partial differential equations. Ordinary and Partial Differential Equations Proceedings of the Fourth Conference Held at Dundee, Scotland March 30 - April 2, 1976 E.g. This textbook can be tailored for courses in numerical differential equations and numerical analysis as well as traditional courses in ordinary and/or partial differential equations. 6) (vi) Nonlinear Differential Equations and Stability (Ch. Intended primarily for engineering and science students. Maple is the world leader in finding exact solutions to ordinary and partial differential equations. An ordinary differential equation involves a derivative over a single variable, usually in an univariate context, whereas a partial differential equation involves several (partial) derivatives ...
TY - CONF. T1 - Reward networks changes in the brain of pathological gamblers: a resting state functional magnetic resonance imaging study. AU - Gagliardo, Cesare. AU - La Barbera, Daniele. AU - Piccoli, Tommaso. AU - Marrale, Maurizio. AU - Lagalla, Roberto. AU - Maniaci, Giuseppe. AU - Cannizzaro, Carla. AU - Collura, Giorgio. AU - La Tona, Giuseppe. PY - 2018. Y1 - 2018. N2 - Aims and objectivesTo investigate functional connectivity changes in pathological gamblers (PGs) in comparison to healthy controls (HCs) by means of resting state functional Magnetic Resonance Imaging (RS-fMRI).Methods and materialsThirteen HCs and fourteen PGs were recruited (all right handed males; drugs free; mean age 35.96±9.56). All subjects underwent brain scan using a 1,5T MRI scanner. Activations data of functionally linked brain regions were obtained using a multi-session temporal concatenated Independent Component Analysis (concat-ICA). The resulted components were than matched and compared between groups. ...
Microcomputers in Biochemical Education PDF/EPUB É Microcomputers in PDF \ An introduction to microcomputers in biochemistry Int J Biochem ; An introduction to microcomputers in biochemistry Giles IG PMID PubMed indexed for MEDLINE Microcomputers in biochemistry a practical Microcomputers in biochemistry a practical approach edited by CFA Bryce IRL Press at Oxford University Press; Oxford.
Fifth International Conference on Genetic Algorithms ICGA93 17-22 July, 1993 University of Illinois at Urbana-Champaign PRELIMINARY ANNOUNCEMENT The Fifth International Conference on Genetic Algorithms (ICGA-93), will be held July 17-22, 1993 at the University of Illinois at Urbana-Champaign. This meeting brings together an international community of researchers and practitioners from academia and industry interested in algorithms suggested by the processes of natural evolution. Topics of interest will include the design, analysis, and application of genetic algorithms in optimization and machine learning. Machine learning architectures of interest include classifier systems and connectionist schemes that use genetic algorithms. Papers discussing how genetic algorithms are related to evolving system modeling (e.g., modeling of nervous system evolution, computational ethology, artificial life, economics, etc.) are also encouraged. A formal call for papers for ICGA-93 will be released in the ...
PURPOSE: Research on the measurement of HIV risk demonstrates that interview mode can affect reporting; however, few studies have applied these findings to assessments of hormonal contraceptive use. This paper examines how audio computer-assisted self-interviewing (ACASI) influenced reports of hormonal contraceptive use and pregnancy among Zimbabwean women. METHODS: Using a
TY - JOUR. T1 - Prediction of hydration free energies for aliphatic and aromatic chloro derivatives using molecular dynamics simulations with the OPLS-AA force field. AU - Beckstein, Oliver. AU - Iorga, Bogdan I.. PY - 2012/5. Y1 - 2012/5. N2 - All-atom molecular dynamics computer simulations were used to blindly predict the hydration free energies of a range of chloro-organic compounds as part of the SAMPL3 challenge. All compounds were parameterized within the framework of the OPLS-AA force field, using an established protocol to compute the absolute hydration free energy via a windowed free energy perturbation approach and thermodynamic integration. Three different approaches to deriving partial charge parameters were pursued: (1) using existing OPLS-AA atom types and charges with minor adjustments of partial charges on equivalent connecting atoms; (2) calculation of quantum mechanical charges via geometry optimization, followed by electrostatic potential (ESP) fitting, using Jaguar at the ...
A major problem for manufacturers of cracked spores Ganoderma lucidum, a traditional functional food/Chinese medicine (TCM), is to ensure that raw materials are consistent as received from the producer. To address this, a feed-forward artificial neural network (ANN) method assisted by linear discriminant analysis (LDA) and principal component analysis (PCA) was developed for the spectroscopic discrimination of cracked spores of Ganoderma lucidum from uncracked spores. 120 samples comprising cracked spores, uncracked spores and concentrate of Ganoderma lucidum were analyzed. Differences in the absorption spectra located at ν1 (1143 - 1037 cm-1), ν2 (1660 - 1560 cm-1), ν3 (1745 - 1716 cm-1) and ν4 (2845 - 2798 cm-1) were identified by applying fourier transform infra-red (FTIR) spectroscopy and used as variables for discriminant analysis. The utilization of spectra frequencies offered maximum chemical information provided by the absorption spectra. Uncracked spores gave rise to characteristic spectrum
In a computed protein multiple sequence alignment, the coreness of a column is the fraction of its substitutions that are in so-called core columns of the gold-standard reference alignment of its proteins. In benchmark suites of protein reference alignments, the core columns of the reference alignment are those that can be confidently labeled as correct, usually due to all residues in the column being sufficiently close in the spatial superposition of the known three-dimensional structures of the proteins. Typically the accuracy of a protein multiple sequence alignment that has been computed for a benchmark is only measured with respect to the core columns of the reference alignment. When computing an alignment in practice, however, a reference alignment is not known, so the coreness of its columns can only be predicted. We develop for the first time a predictor of column coreness for protein multiple sequence alignments. This allows us to predict which columns of a computed alignment are core, and
The present invention discloses a central vacuum system of the hospital-purpose microcomputer controller, which includes a control valve and a collection tube, the collection tube through a line connected to the control valve; the control valve for the central vacuum system is connected to the hospital; end of the tube for collecting a liquid to be sucked at the connection, and is provided with the pipe path of the collection bottle collection tube for collecting a liquid reflux; the collection bottle provided finish portion of the outlet tube outlet is provided close to the collection bottle; the collection path between the tube and the control valve of the collection bottle, provided with an anti-overflow bottle, the bottle overfill the electrode, and the a control electrode connected to the microcomputer circuit module, configured to, when the anti-flooding liquid overflow bottle is controlled by the microcomputer of the control valve is closed. As a result of a control valve connected to a
TY - GEN. T1 - A novel dimensionality reduction technique based on independent component analysis for modeling microarray gene expression data. AU - Liu, Han. AU - Kustra, Rafal. AU - Zhang, Ji. PY - 2004/12/1. Y1 - 2004/12/1. N2 - DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. But one challenge of microarray studies is the fact that the number n of samples collected is relatively small compared to the number p of genes per sample which are usually in thousands. In statistical terms this very large number of predictors compared to a small number of samples or observations makes the classification problem difficult. This is known as the "curse of dimensionality problem". An efficient way to solve this problem is by using dimensionality reduction techniques. Principle Component Analysis(PCA) is a leading method for ...
Introduction: Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. Early differentiation between both types of dementia may be challenging due to heterogeneity and overlap of symptoms. Here, we apply resting state functional magnetic resonance imaging (fMRI) to study functional brain connectivity differences between AD and bvFTD.Methods: We used resting state fMRI data of 31 AD patients, 25 bvFTD patients, and 29 controls from two centers specialized in dementia. We studied functional connectivity throughout the entire brain, applying two different analysis techniques, studying network-to-region and region-to-region connectivity. A general linear model approach was used to study group differences, while controlling for physiological noise, age, gender, study center, and regional gray matter volume.Results: Given gray matter differences, we observed decreased network-to-region connectivity in bvFTD between (a) lateral visual
Hemiplegic cerebral palsy is characterized by unilateral upper limb impairment and patients often compensate by performing most tasks with their unaffected arm. Constraint-induced movement therapy (CIMT) directly combats this learned non-use by casting the unaffected arm and forcing the patient to repetitively practice skills with the hemiplegic limb. Subjects with hemiplegic cerebral palsy were recruited from Holland Bloorview Kids Rehabilitation Hospital, Thames Valley Children's Centre and McMaster Children's Hospital. MRI acquisitions and clinical evaluations were collected at baseline, 1 and 6-months later. The case group participated in a CIMT camp after baseline evaluations and was compared to an untreated control group. Resting state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) acquisitions quantify global network organization and neural integrity, respectively, and found alterations in multiple resting state network connectivity patterns and significantly
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TY - JOUR. T1 - Artificial intelligence to detect tympanic membrane perforations. AU - Habib, A.-R.. AU - Wong, E.. AU - Sacks, R.. AU - Singh, N.. PY - 2020/4/1. Y1 - 2020/4/1. N2 - Objective. To explore the feasibility of constructing a proof-of-concept artificial intelligence algorithm to detect tympanic membrane perforations, for future application in under-resourced rural settings. Methods A retrospective review was conducted of otoscopic images analysed using transfer learning with Google's Inception-V3 convolutional neural network architecture. The 'gold standard' 'ground truth' was defined by otolaryngologists. Perforation size was categorised as less than one-third (small), one-third to two-thirds (medium), or more than two-thirds (large) of the total tympanic membrane diameter. Results A total of 233 tympanic membrane images were used (183 for training, 50 for testing). The algorithm correctly identified intact and perforated tympanic membranes (overall accuracy = 76.0 per cent, 95 per ...
China Microcomputer Control Horizontal Cylindrical Pressure Steam Sterilizer /Autoclave, Find details about China Portable Stainless Steel Steam Sterilizer, Vertical Pressure Steam Sterilizer from Microcomputer Control Horizontal Cylindrical Pressure Steam Sterilizer /Autoclave - Labmen Instrument Technology Limited
Author(s): Connolly, CG; Wu, J; Ho, TC; Hoeft, F; Wolkowitz, O; Eisendrath, S; Frank, G; Hendren, R; Max, JE; Paulus, MP; Tapert, SF; Banerjee, D; Simmons, AN; Yang, TT | Abstract: Background Very few studies have been performed to understand the underlying neural substrates of adolescent major depressive disorder (MDD). Studies in depressed adults have demonstrated that the subgenual anterior cingulate cortex (sgACC) plays a pivotal role in depression and have revealed aberrant patterns of resting-state functional connectivity (RSFC). Here, we examine the RSFC of the sgACC in medication-naïve first-episode adolescents with MDD. Methods Twenty-three adolescents with MDD and 36 well-matched control subjects underwent functional magnetic resonance imaging to assess the RSFC of the sgACC. Results We observed elevated connectivity between the sgACC and the insula and between the sgACC and the amygdala in the MDD group compared with the control subjects. Decreased connectivity between the sgACC and the
The International Federation of Operational Research Societies IFORS is an umbrella organization comprising the national Operations Research societies of over forty five countries from four geographical regions: Asia Pacific, Europe, North America, South America
International Conference on Computer Graphics Theory and Applications 2015. GRAPP 2015 is part of 10th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.
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Deep neural networks have recently been applied to the study of brain disorders such as autism spectrum disorder (ASD) with great success. However, the internal logics of these networks are difficult to interpret, especially with regard to how specific network architecture decisions are made. In this paper, we study an interpretable neural network model as a method to identify ASD participants from functional magnetic resonance imaging (fMRI) data and interpret results of the model in a precise and consistent manner. First, we propose an interpretable fully connected neural network (FCNN) to classify two groups, ASD versus healthy controls (HC), based on input data from resting-state functional connectivity (rsFC) between regions of interests (ROIs). The proposed FCNN model is a piecewise linear neural network (PLNN) which uses piecewise linear function LeakyReLU as its activation function. We experimentally compared the FCNN model against widely used classification models including support vector
TY - JOUR. T1 - Monte Carlo simulation of xenon adsorption with dealumination of an idealized mordenite structure. AU - Nivarthi, Sriram S.. AU - Van Tassel, Paul R.. AU - Davis, H. Ted. AU - McCormick, Alon V.. N1 - Copyright: Copyright 2014 Elsevier B.V., All rights reserved.. PY - 1995/1. Y1 - 1995/1. N2 - Grand canonical Monte Carlo simulations were used to study the effect of dealumination on adsorption of xenon in an idealized structural model of Na-mordenite. Simulations were carried out at Si/Al ratios of 5, 11, and ∞, chosen to represent prototype cation occupancies. A recent experimental study of xenon adsorption in mordenites with different Si/Al ratios found unexpected nonmonotonic trends. In disagreement with experiment, the isotherms of our idealized zeolite changed monotonically with the degree of dealumination. This trend supports recent observations that significant structural chages result from dealumination.. AB - Grand canonical Monte Carlo simulations were used to study ...
Title: A Research on Bioinformatics Prediction of Protein Subcellular Localization. VOLUME: 4 ISSUE: 3. Author(s):Gang Fang, Guirong Tao and Shemin Zhang. Affiliation:Department of Life Science, Xi'an University of Arts and Science, Xi'an 710065, China.. Keywords:Bioinformatics, prediction, protein subcellular localization, localizome, proteomics, database. Abstract: Protein subcellular localization is one of the key characteristic to understand its biological function. Proteins are transported to specific organelles and suborganelles after they are synthesized. They take part in cell activity and function efficiently when correctly localized. Inaccurate subcellular localization will have great impact on cellular function. Prediction of protein subcellular localization is one of the important areas in protein function research. Now it becomes the hot issue in bioinformatics. In this review paper, the recent progress on bioinformatics research of protein subcellular localization and its prospect ...
Computer-Aided Drug Design ??An Overview -- Prediction of Human Drug Targets and their Interactions Using Machine Learning Methods: Current and Future Perspectives -- Practices in Molecular Docking and Structure-based Virtual Screening -- Phylogenetic and Conservation Based Approaches to Predict Protein Functional Sites -- De novo design of Ligands using Computational Methods -- Molecular Dynamics Simulation and the Prediction of Druggable Binding Sites -- Virtual Ligand Screening using PL-PatchSurfer2, a Molecular Surface-based Protein-ligand Docking Method -- Fragment Based Ligand Designing -- Molecular Dynamics as a Tool for Virtual Ligand Screening -- Building Molecular Interaction Networks from Microarray Data for Drug Target Screening -- Absolute Alchemical Free Energy Calculations for Ligand Binding -- Evaluation of Protein-ligand Docking by Cyscore -- Molecular Dynamics Simulations of Protein-drug Complexes:혻 A Computational Protocol for Investigating the Interactions of Small-Molecule ...
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Background The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test
TY - JOUR. T1 - Effects of Naltrexone on Large-Scale Network Interactions in Methamphetamine Use Disorder. AU - Kohno, Milky. AU - Morales, Angelica M.. AU - Dennis, Laura E.. AU - McCready, Holly. AU - Hoffman, William F.. AU - Korthuis, P. Todd. PY - 2019/9/3. Y1 - 2019/9/3. N2 - Naltrexone attenuates craving, and the subjective effects of methamphetamine and extended-release naltrexone (XR-NTX) reduces functional connectivity between regions of the striatum and limbic cortex. Naltrexone modulates neural activity at dopaminergic synapses; however, it is unclear whether naltrexone has an effect on large-scale brain networks. Functional networks interact to coordinate behavior, and as substance-use disorders are associated with an imbalance between reward and cognitive control networks, treatment approaches that target interactive brain systems underlying addiction may be a useful adjunct for behavioral therapies. The objective of this study was to examine the effect of XR-NTX on large-scale ...
Don't draft a computer-related agreement without this guide Richard Raysman and Peter Brown have opened their files to bring you over 100 user-friendly forms and agreements. In Computer Law: Drafting and Negotiating Forms and Agreements book and CD you will find discussions of such key topics as: hardware acquisition, financing and maintenance; software licensing, development and maintenance; antitrust law; copyright, patent and trade secret protection of software; the Internet and electronic communications; domain name registration; the computer contracting process; outsourcing; resellers; software publishing; work for hire; electronic fund transfers; the status of source codes under bankruptcy; and litigating computer actions, including the use of expert witnesses.Computer Law: Drafting and Negotiating Forms and Agreements includes an overview of computer technology, featuring a unique computer law glossary, and keeps you up to date on the latest legislative developments and significant state and
Markov Chain Monte Carlo simulation has received considerable attention within the past decade as reportedly one of the most powerful techniques for the first passage probability estimation of dynamic systems. A very popular method in this direction capable of estimating probability of rare events with low computation cost is the subset simulation (SS). The idea of the method is to break a rare event into a sequence of more probable events which are easy to be estimated based on the conditional simulation techniques. Recently, two algorithms have been proposed in order to increase the efficiency of the method by modifying the conditional sampler. In this paper, applicability of the original SS is compared to the recently introduced modifications of the method on a wind turbine model. The model incorporates a PID pitch controller which aims at keeping the rotational speed of the wind turbine rotor equal to its nominal value. Finally Monte Carlo simulations are performed which allow assessment of ...
Task-based fMRI has been used to study the effects of experimental inflammation on the human brain, but it remains unknown whether intrinsic connectivity in the brain at rest changes during a sickness response. Here, we investigated the effect of experimental inflammation on connectivity between areas relevant for monitoring of bodily states, motivation, and subjective symptoms of sickness. In a double blind randomized controlled trial, 52 healthy volunteers were injected with 0.6 ng/kg LPS (lipopolysaccharide) or placebo, and participated in a resting state fMRI experiment after approximately 2h 45 minutes. Resting state fMRI data were available from 48 participants, of which 28 received LPS and 20 received placebo. Bilateral anterior and bilateral posterior insula sections were used as seed regions and connectivity with bilateral orbitofrontal and cingulate (anterior and middle) cortices was investigated. Back pain, headache and global sickness increased significantly after as compared to ...
Research of the Section for Artificial Intelligence and Decision Support (AID) focusses on Artificial Intelligence technology and computer-based decison support and its use in the medical domain. This includes the development of software systems for intelligent data analysis, knowledge-based systems technology for decision support and therapy planning, and natural language processing which deals with automatic processing of text and speech.. The department offers lectures in Artificial Intelligence on an introductory as well as an advanced level. With regard to particular study programmes, we offer courses for students of Medicine and of Medical Informatics, as well as for students of the Middle European Master Programme in Cognitive Science. Courses are also offered for computer science students in a cooperation with the University of Vienna.. The department was founded in 1977 as an institute of the Medical Faculty of the University of Vienna. In 2004, it became part of the Center for Brain ...
By Dipayan Mitra. Scientists have developed a new artificial intelligence technology that can spot shipwrecks from the ocean surface and also from the air. The University of Texas collaborated with the United State Navy's underwater archeology branch to develop this new artificial intelligence software capable of detecting shipwrecks with an accuracy rate of 92%. The newly developed computer model is now ready to be deployed in order to identify unmapped shipwrecks on the coasts of the United States and Puerto Rico. The artificial intelligence algorithm was fed with images of shipwrecks and underwater topology to enable it to recognize unknown wrecks. The platform uses images from publicly available databases of pictures collected from various parts of the globe and the National Oceanic and Atmospheric Administration's database of shipwrecks. It also uses lidar and sonar-based imageries of the seafloor to carry out its operations more accurately. The lead researcher of the project, Leila ...
TY - JOUR. T1 - Surface structure of methanol/water solutions via sum frequency orientational analysis and molecular dynamics simulation. AU - Ishihara, Takashi. AU - Ishiyama, Tatsuya. AU - Morita, Akihiro. N1 - Publisher Copyright: © 2015 American Chemical Society.. PY - 2015/5/7. Y1 - 2015/5/7. N2 - Polarization dependence of sum frequency generation (SFG) spectroscopy has been widely discussed to detect molecular orientation at surfaces. The present work examines the orientational analysis by molecular dynamics (MD) simulation of methanol/water mixture surfaces with varying concentrations. We calculated by MD the surface structure of the solutions and their SFG spectra in the methyl C-H stretching region, and directly analyzed the relations. The MD calculations reported that (i) the SFG signal of the methyl symmetric stretching exhibits a turnover behavior with increasing concentration and (ii) the polarization ratio is almost invariant over the concentration, while (iii) the orientation of ...
TY - JOUR. T1 - Distributed learning in wireless sensor networks. AU - Predd, Joel B.. AU - Kulkarni, Sanjeev R.. AU - Poor, H. Vincent. N1 - Funding Information: This research was supported in part by the Army Research Office under Grant DAAD19-00-1-0466, in part by Draper Laboratory under IR&D 6002 Grant DL-H-546263, in part by the National Science Foundation under Grants CCR-02055214 and CCR-0312413, and in part by the U.S. Army Pantheon Project.. PY - 2006/7. Y1 - 2006/7. N2 - Distributed learning is a relatively young area as compared to (parametric) decentralized detection and estimation, wireless sensor networks (WSNs), and machine learning. This paper decomposes the literature on distributed learning according to two general research themes: distributed learning in WSNs with a fusion center, where the focus is on how learning is effected when communication constraints limit access to training data; and distributed learning in WSNs with in-network processing, where the focus is on how ...
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Objective: Vestibular signals are involved in higher cortical functions like spatial orientation and its disorders. Vestibular dysfunction contributes, for example, to spatial neglect which can be transiently improved by caloric stimulation. The exact roles and mechanisms of the vestibular and visual systems for the recovery of neglect are not yet known. Methods: Resting-state functional connectivity (fc) magnetic resonance imaging was recorded in a patient with hemispatial neglect during the acute phase and after recovery 6 months later following a right middle cerebral artery infarction before and after caloric vestibular stimulation. Seeds in the vestibular [parietal operculum (OP2)], the parietal [posterior parietal cortex (PPC);7A, hIP3], and the visual cortex (VC) were used for the analysis. Results: During the acute stage after caloric stimulation the fc of the right OP2 to the left OP2, the anterior cingulum, and the para/hippocampus was increased bilaterally (i.e., the vestibular ...
The 37th IEEE International Conference on Computer Design encompasses a wide range of topics in the research, design, and implementation of computer systems and their components. ICCD's multi-disciplinary emphasis provides an ideal environment for developers and researchers to discuss practical and theoretical work covering systems and applications, computer architecture, verification and test, design tools and methodologies, circuit design, and technology.. ...
The combination of gene expression profiling with linkage analysis has become a powerful paradigm for mapping gene expression quantitative trait loci (eQTL). To date, most studies have searched for eQTL by analyzing gene expression traits one at a time. As thousands of expression traits are typically analyzed, this can reduce power because of the need to correct for the number of hypothesis tests performed. In addition, gene expression traits exhibit a complex correlation structure, which is ignored when analyzing traits individually. To address these issues, we applied two different multivariate dimension reduction techniques, the Singular Value Decomposition (SVD) and Independent Component Analysis (ICA) to gene expression traits derived from a cross between two strains of Saccharomyces cerevisiae. Both methods decompose the data into a set of meta-traits, which are linear combinations of all the expression traits. The meta-traits were enriched for several Gene Ontology categories including metabolic
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The topics of interest to the conference include, but are not limited to:. Computer Science: Information Technology, Green Computing, Machine Learning, Smart Computing, Predictive Analysis, Mobile Programming, big data, Computer architecture, Computational & Synthetic Biology, Computer Graphics, Vision, Animation, Game Science, Computing for Development, Data Management, Human Computer Interaction, Natural Language Processing, Programming Languages and Software Engineering, Robotics, Security & Privacy, Systems and Networking, Theory of Computation, Ubiquitous Computing, Wireless and Sensor Systems, Using IT to reduce carbon emissions, Energy-aware computing, Smart grid and micro grids, Sustainable computing.. Optimization: Mathematical Programming, Continues optimization, Combinatorial optimization, Discreet optimization, Ant colony optimization, Fuzzy logic, Genetic algorithm, Genetic programming, variable neighbourhood search, Support vector machine, Cuckoo search, Simulated annealing, Bat ...