Algorithms: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.Software: Sequential operating programs and data which instruct the functioning of a digital computer.Pattern Recognition, Automated: In INFORMATION RETRIEVAL, machine-sensing or identification of visible patterns (shapes, forms, and configurations). (Harrod's Librarians' Glossary, 7th ed)Computer Simulation: Computer-based representation of physical systems and phenomena such as chemical processes.Computational Biology: A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets.Reproducibility of Results: The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results.Artificial Intelligence: Theory and development of COMPUTER SYSTEMS which perform tasks that normally require human intelligence. Such tasks may include speech recognition, LEARNING; VISUAL PERCEPTION; MATHEMATICAL COMPUTING; reasoning, PROBLEM SOLVING, DECISION-MAKING, and translation of language.Models, Statistical: Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.Sensitivity and Specificity: Binary classification measures to assess test results. Sensitivity or recall rate is the proportion of true positives. Specificity is the probability of correctly determining the absence of a condition. (From Last, Dictionary of Epidemiology, 2d ed)Cluster Analysis: A set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both.Image Processing, Computer-Assisted: A technique of inputting two-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer.Sequence Analysis, Protein: A process that includes the determination of AMINO ACID SEQUENCE of a protein (or peptide, oligopeptide or peptide fragment) and the information analysis of the sequence.Sequence Alignment: The arrangement of two or more amino acid or base sequences from an organism or organisms in such a way as to align areas of the sequences sharing common properties. The degree of relatedness or homology between the sequences is predicted computationally or statistically based on weights assigned to the elements aligned between the sequences. This in turn can serve as a potential indicator of the genetic relatedness between the organisms.Image Interpretation, Computer-Assisted: Methods developed to aid in the interpretation of ultrasound, radiographic images, etc., for diagnosis of disease.Phantoms, Imaging: Devices or objects in various imaging techniques used to visualize or enhance visualization by simulating conditions encountered in the procedure. Phantoms are used very often in procedures employing or measuring x-irradiation or radioactive material to evaluate performance. Phantoms often have properties similar to human tissue. Water demonstrates absorbing properties similar to normal tissue, hence water-filled phantoms are used to map radiation levels. Phantoms are used also as teaching aids to simulate real conditions with x-ray or ultrasonic machines. (From Iturralde, Dictionary and Handbook of Nuclear Medicine and Clinical Imaging, 1990)Models, Genetic: Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.Signal Processing, Computer-Assisted: Computer-assisted processing of electric, ultrasonic, or electronic signals to interpret function and activity.Software Validation: The act of testing the software for compliance with a standard.Imaging, Three-Dimensional: The process of generating three-dimensional images by electronic, photographic, or other methods. For example, three-dimensional images can be generated by assembling multiple tomographic images with the aid of a computer, while photographic 3-D images (HOLOGRAPHY) can be made by exposing film to the interference pattern created when two laser light sources shine on an object.Sequence Analysis, DNA: A multistage process that includes cloning, physical mapping, subcloning, determination of the DNA SEQUENCE, and information analysis.Image Enhancement: Improvement of the quality of a picture by various techniques, including computer processing, digital filtering, echocardiographic techniques, light and ultrastructural MICROSCOPY, fluorescence spectrometry and microscopy, scintigraphy, and in vitro image processing at the molecular level.Markov Chains: A stochastic process such that the conditional probability distribution for a state at any future instant, given the present state, is unaffected by any additional knowledge of the past history of the system.Proteins: Linear POLYPEPTIDES that are synthesized on RIBOSOMES and may be further modified, crosslinked, cleaved, or assembled into complex proteins with several subunits. The specific sequence of AMINO ACIDS determines the shape the polypeptide will take, during PROTEIN FOLDING, and the function of the protein.Databases, Protein: Databases containing information about PROTEINS such as AMINO ACID SEQUENCE; PROTEIN CONFORMATION; and other properties.Bayes Theorem: A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.Gene Expression Profiling: The determination of the pattern of genes expressed at the level of GENETIC TRANSCRIPTION, under specific circumstances or in a specific cell.Monte Carlo Method: In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993)Computer Graphics: The process of pictorial communication, between human and computers, in which the computer input and output have the form of charts, drawings, or other appropriate pictorial representation.Automation: Controlled operation of an apparatus, process, or system by mechanical or electronic devices that take the place of human organs of observation, effort, and decision. (From Webster's Collegiate Dictionary, 1993)Databases, Factual: Extensive collections, reputedly complete, of facts and data garnered from material of a specialized subject area and made available for analysis and application. The collection can be automated by various contemporary methods for retrieval. The concept should be differentiated from DATABASES, BIBLIOGRAPHIC which is restricted to collections of bibliographic references.Oligonucleotide Array Sequence Analysis: Hybridization of a nucleic acid sample to a very large set of OLIGONUCLEOTIDE PROBES, which have been attached individually in columns and rows to a solid support, to determine a BASE SEQUENCE, or to detect variations in a gene sequence, GENE EXPRESSION, or for GENE MAPPING.Neural Networks (Computer): A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.Numerical Analysis, Computer-Assisted: Computer-assisted study of methods for obtaining useful quantitative solutions to problems that have been expressed mathematically.Models, Theoretical: Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.User-Computer Interface: The portion of an interactive computer program that issues messages to and receives commands from a user.Data Compression: Information application based on a variety of coding methods to minimize the amount of data to be stored, retrieved, or transmitted. Data compression can be applied to various forms of data, such as images and signals. It is used to reduce costs and increase efficiency in the maintenance of large volumes of data.Fuzzy Logic: Approximate, quantitative reasoning that is concerned with the linguistic ambiguity which exists in natural or synthetic language. At its core are variables such as good, bad, and young as well as modifiers such as more, less, and very. These ordinary terms represent fuzzy sets in a particular problem. Fuzzy logic plays a key role in many medical expert systems.Artifacts: Any visible result of a procedure which is caused by the procedure itself and not by the entity being analyzed. Common examples include histological structures introduced by tissue processing, radiographic images of structures that are not naturally present in living tissue, and products of chemical reactions that occur during analysis.Diagnosis, Computer-Assisted: Application of computer programs designed to assist the physician in solving a diagnostic problem.Databases, Genetic: Databases devoted to knowledge about specific genes and gene products.Data Interpretation, Statistical: Application of statistical procedures to analyze specific observed or assumed facts from a particular study.Models, Biological: Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.Normal Distribution: Continuous frequency distribution of infinite range. Its properties are as follows: 1, continuous, symmetrical distribution with both tails extending to infinity; 2, arithmetic mean, mode, and median identical; and 3, shape completely determined by the mean and standard deviation.Information Storage and Retrieval: Organized activities related to the storage, location, search, and retrieval of information.Likelihood Functions: Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters.Radiographic Image Interpretation, Computer-Assisted: Computer systems or networks designed to provide radiographic interpretive information.Genomics: The systematic study of the complete DNA sequences (GENOME) of organisms.Internet: A loose confederation of computer communication networks around the world. The networks that make up the Internet are connected through several backbone networks. The Internet grew out of the US Government ARPAnet project and was designed to facilitate information exchange.Decision Trees: A graphic device used in decision analysis, series of decision options are represented as branches (hierarchical).Radiographic Image Enhancement: Improvement in the quality of an x-ray image by use of an intensifying screen, tube, or filter and by optimum exposure techniques. Digital processing methods are often employed.Subtraction Technique: Combination or superimposition of two images for demonstrating differences between them (e.g., radiograph with contrast vs. one without, radionuclide images using different radionuclides, radiograph vs. radionuclide image) and in the preparation of audiovisual materials (e.g., offsetting identical images, coloring of vessels in angiograms).Programming Languages: Specific languages used to prepare computer programs.Wavelet Analysis: Signal and data processing method that uses decomposition of wavelets to approximate, estimate, or compress signals with finite time and frequency domains. It represents a signal or data in terms of a fast decaying wavelet series from the original prototype wavelet, called the mother wavelet. This mathematical algorithm has been adopted widely in biomedical disciplines for data and signal processing in noise removal and audio/image compression (e.g., EEG and MRI).Computing Methodologies: Computer-assisted analysis and processing of problems in a particular area.Signal-To-Noise Ratio: The comparison of the quantity of meaningful data to the irrelevant or incorrect data.Data Mining: Use of sophisticated analysis tools to sort through, organize, examine, and combine large sets of information.Protein Interaction Mapping: Methods for determining interaction between PROTEINS.Models, Molecular: Models used experimentally or theoretically to study molecular shape, electronic properties, or interactions; includes analogous molecules, computer-generated graphics, and mechanical structures.Wireless Technology: Techniques using energy such as radio frequency, infrared light, laser light, visible light, or acoustic energy to transfer information without the use of wires, over both short and long distances.Support Vector Machines: Learning algorithms which are a set of related supervised computer learning methods that analyze data and recognize patterns, and used for classification and regression analysis.Automatic Data Processing: Data processing largely performed by automatic means.Software Design: Specifications and instructions applied to the software.Sequence Analysis, RNA: A multistage process that includes cloning, physical mapping, subcloning, sequencing, and information analysis of an RNA SEQUENCE.ComputersMolecular Sequence Data: Descriptions of specific amino acid, carbohydrate, or nucleotide sequences which have appeared in the published literature and/or are deposited in and maintained by databanks such as GENBANK, European Molecular Biology Laboratory (EMBL), National Biomedical Research Foundation (NBRF), or other sequence repositories.Stochastic Processes: Processes that incorporate some element of randomness, used particularly to refer to a time series of random variables.Genome: The genetic complement of an organism, including all of its GENES, as represented in its DNA, or in some cases, its RNA.Gene Regulatory Networks: Interacting DNA-encoded regulatory subsystems in the GENOME that coordinate input from activator and repressor TRANSCRIPTION FACTORS during development, cell differentiation, or in response to environmental cues. The networks function to ultimately specify expression of particular sets of GENES for specific conditions, times, or locations.ROC Curve: A graphic means for assessing the ability of a screening test to discriminate between healthy and diseased persons; may also be used in other studies, e.g., distinguishing stimuli responses as to a faint stimuli or nonstimuli.Equipment Design: Methods of creating machines and devices.Models, Chemical: Theoretical representations that simulate the behavior or activity of chemical processes or phenomena; includes the use of mathematical equations, computers, and other electronic equipment.Probability: The study of chance processes or the relative frequency characterizing a chance process.Predictive Value of Tests: In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.Chromosome Mapping: Any method used for determining the location of and relative distances between genes on a chromosome.Phylogeny: The relationships of groups of organisms as reflected by their genetic makeup.Magnetic Resonance Imaging: Non-invasive method of demonstrating internal anatomy based on the principle that atomic nuclei in a strong magnetic field absorb pulses of radiofrequency energy and emit them as radiowaves which can be reconstructed into computerized images. The concept includes proton spin tomographic techniques.Time Factors: Elements of limited time intervals, contributing to particular results or situations.Base Sequence: The sequence of PURINES and PYRIMIDINES in nucleic acids and polynucleotides. It is also called nucleotide sequence.Discriminant Analysis: A statistical analytic technique used with discrete dependent variables, concerned with separating sets of observed values and allocating new values. It is sometimes used instead of regression analysis.Cone-Beam Computed Tomography: Computed tomography modalities which use a cone or pyramid-shaped beam of radiation.Tomography, X-Ray Computed: Tomography using x-ray transmission and a computer algorithm to reconstruct the image.Least-Squares Analysis: A principle of estimation in which the estimates of a set of parameters in a statistical model are those quantities minimizing the sum of squared differences between the observed values of a dependent variable and the values predicted by the model.Nonlinear Dynamics: The study of systems which respond disproportionately (nonlinearly) to initial conditions or perturbing stimuli. Nonlinear systems may exhibit "chaos" which is classically characterized as sensitive dependence on initial conditions. Chaotic systems, while distinguished from more ordered periodic systems, are not random. When their behavior over time is appropriately displayed (in "phase space"), constraints are evident which are described by "strange attractors". Phase space representations of chaotic systems, or strange attractors, usually reveal fractal (FRACTALS) self-similarity across time scales. Natural, including biological, systems often display nonlinear dynamics and chaos.Programming, Linear: A technique of operations research for solving certain kinds of problems involving many variables where a best value or set of best values is to be found. It is most likely to be feasible when the quantity to be optimized, sometimes called the objective function, can be stated as a mathematical expression in terms of the various activities within the system, and when this expression is simply proportional to the measure of the activities, i.e., is linear, and when all the restrictions are also linear. It is different from computer programming, although problems using linear programming techniques may be programmed on a computer.Equipment Failure Analysis: The evaluation of incidents involving the loss of function of a device. These evaluations are used for a variety of purposes such as to determine the failure rates, the causes of failures, costs of failures, and the reliability and maintainability of devices.Genome, Human: The complete genetic complement contained in the DNA of a set of CHROMOSOMES in a HUMAN. The length of the human genome is about 3 billion base pairs.Proteomics: The systematic study of the complete complement of proteins (PROTEOME) of organisms.Databases, Nucleic Acid: Databases containing information about NUCLEIC ACIDS such as BASE SEQUENCE; SNPS; NUCLEIC ACID CONFORMATION; and other properties. Information about the DNA fragments kept in a GENE LIBRARY or GENOMIC LIBRARY is often maintained in DNA databases.Principal Component Analysis: Mathematical procedure that transforms a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components.Polymorphism, Single Nucleotide: A single nucleotide variation in a genetic sequence that occurs at appreciable frequency in the population.Amino Acid Sequence: The order of amino acids as they occur in a polypeptide chain. This is referred to as the primary structure of proteins. It is of fundamental importance in determining PROTEIN CONFORMATION.Computer Communication Networks: A system containing any combination of computers, computer terminals, printers, audio or visual display devices, or telephones interconnected by telecommunications equipment or cables: used to transmit or receive information. (Random House Unabridged Dictionary, 2d ed)Natural Language Processing: Computer processing of a language with rules that reflect and describe current usage rather than prescribed usage.Tomography: Imaging methods that result in sharp images of objects located on a chosen plane and blurred images located above or below the plane.Proteome: The protein complement of an organism coded for by its genome.

An effective approach for analyzing "prefinished" genomic sequence data. (1/42270)

Ongoing efforts to sequence the human genome are already generating large amounts of data, with substantial increases anticipated over the next few years. In most cases, a shotgun sequencing strategy is being used, which rapidly yields most of the primary sequence in incompletely assembled sequence contigs ("prefinished" sequence) and more slowly produces the final, completely assembled sequence ("finished" sequence). Thus, in general, prefinished sequence is produced in excess of finished sequence, and this trend is certain to continue and even accelerate over the next few years. Even at a prefinished stage, genomic sequence represents a rich source of important biological information that is of great interest to many investigators. However, analyzing such data is a challenging and daunting task, both because of its sheer volume and because it can change on a day-by-day basis. To facilitate the discovery and characterization of genes and other important elements within prefinished sequence, we have developed an analytical strategy and system that uses readily available software tools in new combinations. Implementation of this strategy for the analysis of prefinished sequence data from human chromosome 7 has demonstrated that this is a convenient, inexpensive, and extensible solution to the problem of analyzing the large amounts of preliminary data being produced by large-scale sequencing efforts. Our approach is accessible to any investigator who wishes to assimilate additional information about particular sequence data en route to developing richer annotations of a finished sequence.  (+info)

A computational screen for methylation guide snoRNAs in yeast. (2/42270)

Small nucleolar RNAs (snoRNAs) are required for ribose 2'-O-methylation of eukaryotic ribosomal RNA. Many of the genes for this snoRNA family have remained unidentified in Saccharomyces cerevisiae, despite the availability of a complete genome sequence. Probabilistic modeling methods akin to those used in speech recognition and computational linguistics were used to computationally screen the yeast genome and identify 22 methylation guide snoRNAs, snR50 to snR71. Gene disruptions and other experimental characterization confirmed their methylation guide function. In total, 51 of the 55 ribose methylated sites in yeast ribosomal RNA were assigned to 41 different guide snoRNAs.  (+info)

Referenceless interleaved echo-planar imaging. (3/42270)

Interleaved echo-planar imaging (EPI) is an ultrafast imaging technique important for applications that require high time resolution or short total acquisition times. Unfortunately, EPI is prone to significant ghosting artifacts, resulting primarily from system time delays that cause data matrix misregistration. In this work, it is shown mathematically and experimentally that system time delays are orientation dependent, resulting from anisotropic physical gradient delays. This analysis characterizes the behavior of time delays in oblique coordinates, and a new ghosting artifact caused by anisotropic delays is described. "Compensation blips" are proposed for time delay correction. These blips are shown to remove the effects of anisotropic gradient delays, eliminating the need for repeated reference scans and postprocessing corrections. Examples of phantom and in vivo images are shown.  (+info)

An evaluation of elongation factor 1 alpha as a phylogenetic marker for eukaryotes. (4/42270)

Elongation factor 1 alpha (EF-1 alpha) is a highly conserved ubiquitous protein involved in translation that has been suggested to have desirable properties for phylogenetic inference. To examine the utility of EF-1 alpha as a phylogenetic marker for eukaryotes, we studied three properties of EF-1 alpha trees: congruency with other phyogenetic markers, the impact of species sampling, and the degree of substitutional saturation occurring between taxa. Our analyses indicate that the EF-1 alpha tree is congruent with some other molecular phylogenies in identifying both the deepest branches and some recent relationships in the eukaryotic line of descent. However, the topology of the intermediate portion of the EF-1 alpha tree, occupied by most of the protist lineages, differs for different phylogenetic methods, and bootstrap values for branches are low. Most problematic in this region is the failure of all phylogenetic methods to resolve the monophyly of two higher-order protistan taxa, the Ciliophora and the Alveolata. JACKMONO analyses indicated that the impact of species sampling on bootstrap support for most internal nodes of the eukaryotic EF-1 alpha tree is extreme. Furthermore, a comparison of observed versus inferred numbers of substitutions indicates that multiple overlapping substitutions have occurred, especially on the branch separating the Eukaryota from the Archaebacteria, suggesting that the rooting of the eukaryotic tree on the diplomonad lineage should be treated with caution. Overall, these results suggest that the phylogenies obtained from EF-1 alpha are congruent with other molecular phylogenies in recovering the monophyly of groups such as the Metazoa, Fungi, Magnoliophyta, and Euglenozoa. However, the interrelationships between these and other protist lineages are not well resolved. This lack of resolution may result from the combined effects of poor taxonomic sampling, relatively few informative positions, large numbers of overlapping substitutions that obscure phylogenetic signal, and lineage-specific rate increases in the EF-1 alpha data set. It is also consistent with the nearly simultaneous diversification of major eukaryotic lineages implied by the "big-bang" hypothesis of eukaryote evolution.  (+info)

Hierarchical cluster analysis applied to workers' exposures in fiberglass insulation manufacturing. (5/42270)

The objectives of this study were to explore the application of cluster analysis to the characterization of multiple exposures in industrial hygiene practice and to compare exposure groupings based on the result from cluster analysis with that based on non-measurement-based approaches commonly used in epidemiology. Cluster analysis was performed for 37 workers simultaneously exposed to three agents (endotoxin, phenolic compounds and formaldehyde) in fiberglass insulation manufacturing. Different clustering algorithms, including complete-linkage (or farthest-neighbor), single-linkage (or nearest-neighbor), group-average and model-based clustering approaches, were used to construct the tree structures from which clusters can be formed. Differences were observed between the exposure clusters constructed by these different clustering algorithms. When contrasting the exposure classification based on tree structures with that based on non-measurement-based information, the results indicate that the exposure clusters identified from the tree structures had little in common with the classification results from either the traditional exposure zone or the work group classification approach. In terms of the defining homogeneous exposure groups or from the standpoint of health risk, some toxicological normalization in the components of the exposure vector appears to be required in order to form meaningful exposure groupings from cluster analysis. Finally, it remains important to see if the lack of correspondence between exposure groups based on epidemiological classification and measurement data is a peculiarity of the data or a more general problem in multivariate exposure analysis.  (+info)

A new filtering algorithm for medical magnetic resonance and computer tomography images. (6/42270)

Inner views of tubular structures based on computer tomography (CT) and magnetic resonance (MR) data sets may be created by virtual endoscopy. After a preliminary segmentation procedure for selecting the organ to be represented, the virtual endoscopy is a new postprocessing technique using surface or volume rendering of the data sets. In the case of surface rendering, the segmentation is based on a grey level thresholding technique. To avoid artifacts owing to the noise created in the imaging process, and to restore spurious resolution degradations, a robust Wiener filter was applied. This filter working in Fourier space approximates the noise spectrum by a simple function that is proportional to the square root of the signal amplitude. Thus, only points with tiny amplitudes consisting mostly of noise are suppressed. Further artifacts are avoided by the correct selection of the threshold range. Afterwards, the lumen and the inner walls of the tubular structures are well represented and allow one to distinguish between harmless fluctuations and medically significant structures.  (+info)

Efficacy of ampicillin plus ceftriaxone in treatment of experimental endocarditis due to Enterococcus faecalis strains highly resistant to aminoglycosides. (7/42270)

The purpose of this work was to evaluate the in vitro possibilities of ampicillin-ceftriaxone combinations for 10 Enterococcus faecalis strains with high-level resistance to aminoglycosides (HLRAg) and to assess the efficacy of ampicillin plus ceftriaxone, both administered with humanlike pharmacokinetics, for the treatment of experimental endocarditis due to HLRAg E. faecalis. A reduction of 1 to 4 dilutions in MICs of ampicillin was obtained when ampicillin was combined with a fixed subinhibitory ceftriaxone concentration of 4 micrograms/ml. This potentiating effect was also observed by the double disk method with all 10 strains. Time-kill studies performed with 1 and 2 micrograms of ampicillin alone per ml or in combination with 5, 10, 20, 40, and 60 micrograms of ceftriaxone per ml showed a > or = 2 log10 reduction in CFU per milliliter with respect to ampicillin alone and to the initial inoculum for all 10 E. faecalis strains studied. This effect was obtained for seven strains with the combination of 2 micrograms of ampicillin per ml plus 10 micrograms of ceftriaxone per ml and for six strains with 5 micrograms of ceftriaxone per ml. Animals with catheter-induced endocarditis were infected intravenously with 10(8) CFU of E. faecalis V48 or 10(5) CFU of E. faecalis V45 and were treated for 3 days with humanlike pharmacokinetics of 2 g of ampicillin every 4 h, alone or combined with 2 g of ceftriaxone every 12 h. The levels in serum and the pharmacokinetic parameters of the humanlike pharmacokinetics of ampicillin or ceftriaxone in rabbits were similar to those found in humans treated with 2 g of ampicillin or ceftriaxone intravenously. Results of the therapy for experimental endocarditis caused by E. faecalis V48 or V45 showed that the residual bacterial titers in aortic valve vegetations were significantly lower in the animals treated with the combinations of ampicillin plus ceftriaxone than in those treated with ampicillin alone (P < 0.001). The combination of ampicillin and ceftriaxone showed in vitro and in vivo synergism against HLRAg E. faecalis.  (+info)

The muscle chloride channel ClC-1 has a double-barreled appearance that is differentially affected in dominant and recessive myotonia. (8/42270)

Single-channel recordings of the currents mediated by the muscle Cl- channel, ClC-1, expressed in Xenopus oocytes, provide the first direct evidence that this channel has two equidistant open conductance levels like the Torpedo ClC-0 prototype. As for the case of ClC-0, the probabilities and dwell times of the closed and conducting states are consistent with the presence of two independently gated pathways with approximately 1.2 pS conductance enabled in parallel via a common gate. However, the voltage dependence of the common gate is different and the kinetics are much faster than for ClC-0. Estimates of single-channel parameters from the analysis of macroscopic current fluctuations agree with those from single-channel recordings. Fluctuation analysis was used to characterize changes in the apparent double-gate behavior of the ClC-1 mutations I290M and I556N causing, respectively, a dominant and a recessive form of myotonia. We find that both mutations reduce about equally the open probability of single protopores and that mutation I290M yields a stronger reduction of the common gate open probability than mutation I556N. Our results suggest that the mammalian ClC-homologues have the same structure and mechanism proposed for the Torpedo channel ClC-0. Differential effects on the two gates that appear to modulate the activation of ClC-1 channels may be important determinants for the different patterns of inheritance of dominant and recessive ClC-1 mutations.  (+info)

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 ...
This is the eleventh post in an article series about MITs lecture course Introduction to Algorithms. In this post I will review lecture sixteen, which introduces the concept of Greedy Algorithms, reviews Graphs and applies the greedy Prims Algorithm to the Minimum Spanning Tree (MST) Problem.. The previous lecture introduced dynamic programming. Dynamic programming was used for finding solutions to optimization problems. In such problems there can be many possible solutions. Each solution has a value, and we want to find a solution with the optimal (minimum or maximum) value. Greedy algorithms are another set of methods for finding optimal solution. A greedy algorithm always makes the choice that looks best at the moment. That is, it makes a locally optimal choice in the hope that this choice will lead to a globally optimal solution. Greedy algorithms do not always yield optimal solutions, but for many problems they do. In this lecture it is shown that a greedy algorithm gives an optimal ...
Feature selection is a useful tool for identifying which features, or attributes, of a dataset cause or explain the phenomena that the dataset describes, and improving the efficiency and accuracy of learning algorithms for discovering such phenomena. Consequently, feature selection has been studied intensively in machine learning research. However, while feature selection algorithms that exhibit excellent accuracy have been developed, they are seldom used for analysis of high-dimensional data because high-dimensional data usually include too many instances and features, which make traditional feature selection algorithms inefficient. To eliminate this limitation, we tried to improve the run-time performance of two of the most accurate feature selection algorithms known in the literature. The result is two accurate and fast algorithms, namely sCwc and sLcc. Multiple experiments with real social media datasets have demonstrated that our algorithms improve the performance of their original algorithms
TAMU01A23 TAMU01A24 TAMU01B19 TAMU01B24 TAMU01C24 TAMU01D14 TAMU01D17 TAMU01G19 TAMU01K11 TAMU01K23 TAMU01L14 TAMU01M08 TAMU02A06 TAMU02A09 TAMU02B04 TAMU02C12 TAMU02C19 TAMU02D13 TAMU02D21 TAMU02G01 TAMU02K03 TAMU02L21 TAMU02M17 TAMU02M19 TAMU02N13 TAMU02N19 TAMU02P07 TAMU03A01 TAMU03A07 TAMU03B06 TAMU03D01 TAMU03D04 TAMU03D14 TAMU03E08 TAMU03E24 TAMU03F15 TAMU03G12 TAMU03I06 TAMU03I10 TAMU03I19 TAMU03K15 TAMU03K24 TAMU03L11 TAMU03M07 TAMU03M08 TAMU03M12 TAMU03N18 TAMU03N20 TAMU03N24 TAMU03P22 TAMU04A20 TAMU04C13 TAMU04E12 TAMU04E18 TAMU04F06 TAMU04F17 TAMU04G01 TAMU04G23 TAMU04G24 TAMU04H24 TAMU04I08 TAMU04J06 TAMU04M09 TAMU04M16 TAMU04N08 TAMU04N11 TAMU04O11 TAMU04O15 TAMU04O20 TAMU04P09 TAMU05A16 TAMU05C18 TAMU05C21 TAMU05D19 TAMU05E07 TAMU05F04 TAMU05F05 TAMU05F08 TAMU05G19 TAMU05G21 TAMU05H08 TAMU05L01 TAMU05L24 TAMU05M02 TAMU05N06 TAMU05N19 TAMU05N24 TAMU05O02 TAMU05O12 TAMU05O19 TAMU05O21 TAMU06D16 TAMU06K02 TAMU06K13 TAMU06K19 TAMU06L04 TAMU06L07 TAMU06L10 TAMU06M20 TAMU06P06 TAMU06P12 ...
Analysis of genomes evolving by inversions leads to a general combinatorial problem of Sorting by Reversals , MIN-SBR, the problem of sorting a permutation by a minimum number of reversals. Following a series of preliminary results, Hannenhalli and Pevzner developed the first exact polynomial time algorithm for the problem of sorting signed permutations by reversals, and a polynomial time algorithm for a special case of unsigned permutations. The best known approximation algorithm for MIN-SBR, due to Christie, gives a performance ratio of 1.5. In this paper, by exploiting the polynomial time algorithm for sorting signed permutations and by developing a new approximation algorithm for maximum cycle decomposition of breakpoint graphs, we design a new 1.375-algorithm for the MIN-SBR problem.. ...
Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold that defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we propose a new inference algorithm that incorporates mutual information (MI), conditional mutual information (CMI), and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Multiple, often conflicting objectives arise naturally in most real-world optimization scenarios. As evolutionary algorithms possess several characteristics due to which they are well suited to this type of problem, evolution-based methods have been used for multiobjective optimization for more than a decade. Meanwhile evolutionary multiobjective optimization has become established as a separate subdiscipline combining the fields of evolutionary computation and classical multiple criteria decision making. In this paper, the basic principles of evolutionary multiobjective optimization are discussed from an algorithm design perspective. The focus is on the major issues such as fitness assignment, diversity preservation, and elitism in general rather than on particular algorithms. Different techniques to implement these strongly related concepts will be discussed, and further important aspects such as constraint handling and
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Efficient Risk Profiling Using Bayesian Networks and Particle Swarm Optimization Algorithm: 10.4018/978-1-4666-9458-3.ch004: Chapter introduce usage of particle swarm optimization algorithm and explained methodology, as a tool for discovering customer profiles based on previously
Particle Swarm Optimization Algorithm as a Tool for Profiling from Predictive Data Mining Models: 10.4018/978-1-5225-0788-8.ch033: This chapter introduces the methodology of particle swarm optimization algorithm usage as a tool for finding customer profiles based on a previously developed
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This volume emphasises on theoretical results and algorithms of combinatorial optimization with provably good performance, in contrast to heuristics. It documents the relevant knowledge on combinatorial optimization and records those problems and algorithms of this discipline.Korte, Bernhard is the author of Combinatorial Optimization Theory and Algorithms, published 2005 under ISBN 9783540256847 and ISBN 3540256849. [read more] ...
DNA computing is a new computing paradigm which uses bio-molecular as information storage media and biochemical tools as information processing operators. It has shows many successful and promising results for various applications. Since DNA reactions are probabilistic reactions, it can cause the different results for the same situations, which can be regarded as errors in the computation. To overcome the drawbacks, much works have focused to design the error-minimized DNA sequences to improve the reliability of DNA computing. In this research, Population-based Ant Colony Optimization (P-ACO) is proposed to solve the DNA sequence optimization. PACO approach is a meta-heuristic algorithm that uses some ants to obtain the solutions based on the pheromone in their colony. The DNA sequence design problem is modelled by four nodes, representing four DNA bases (A, T, C, and G). The results from the proposed algorithm are compared with other sequence design methods, which are Genetic Algorithm (GA), ...
In machine learning, weighted majority algorithm (WMA) is a meta-learning algorithm used to construct a compound algorithm from a pool of prediction algorithms, which could be any type of learning algorithms, classifiers, or even real human experts.[1][2] The algorithm assumes that we have no prior knowledge about the accuracy of the algorithms in the pool, but there are sufficient reasons to believe that one or more will perform well. Assume that the problem is a binary decision problem. To construct the compound algorithm, a positive weight is given to each of the algorithms in the pool. The compound algorithm then collects weighted votes from all the algorithms in the pool, and gives the prediction that has a higher vote. If the compound algorithm makes a mistake, the algorithms in the pool that contributed to the wrong predicting will be discounted by a certain ratio β where 0,β,1. It can be shown that the upper bounds on the number of mistakes made in a given sequence of predictions from ...
In mathematics, the greedy algorithm for Egyptian fractions is a greedy algorithm, first described by Fibonacci, for transforming rational numbers into Egyptian fractions. An Egyptian fraction is a representation of an irreducible fraction as a sum of distinct unit fractions, as e.g. 5/6 = 1/2 + 1/3. As the name indicates, these representations have been used as long ago as ancient Egypt, but the first published systematic method for constructing such expansions is described in the Liber Abaci (1202) of Leonardo of Pisa (Fibonacci). It is called a greedy algorithm because at each step the algorithm chooses greedily the largest possible unit fraction that can be used in any representation of the remaining fraction. Fibonacci actually lists several different methods for constructing Egyptian fraction representations (Sigler 2002, chapter II.7). He includes the greedy method as a last resort for situations when several simpler methods fail; see Egyptian fraction for a more detailed listing of these ...
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Sudoku puzzles are an excellent testbed for evolutionary algorithms. The puzzles are accessible enough to be enjoyed by people. However the more complex puzzles require thousands of iterations before a solution is found by an evolutionary algorithm. If we were attempting to compare evolutionary algorithms we could count their iterations to solution as a indicator of relative efficiency. However all evolutionary algorithms include a process of random mutation for solution candidates. I will show that by improving the random mutation behaviours I was able to solve problems with minimal evolutionary optimisation. Experiments demonstrated the random mutation was at times more effective at solving the harder problems than the evolutionary algorithms. This implies that the quality of random mutation may have a significant impact on the performance of evolutionary algorithms with sudoku puzzles. Additionally this random mutation may
TY - JOUR. T1 - Multiobjective process planning and scheduling using improved vector evaluated genetic algorithm with archive. AU - Zhang, Wenqiang. AU - Fujimura, Shigeru. PY - 2012/5. Y1 - 2012/5. N2 - Multiobjective process planning and scheduling (PPS) is a most important practical but very intractable combinatorial optimization problem in manufacturing systems. Many researchers have used multiobjective evolutionary algorithms (moEAs) to solve such problems; however, these approaches could not achieve satisfactory results in both efficacy (quality, i.e., convergence and distribution) and efficiency (speed). As classical moEAs, nondominated sorting genetic algorithm II (NSGA-II) and SPEA2 can get good efficacy but need much CPU time. Vector evaluated genetic algorithm (VEGA) also cannot be applied owing to its poor efficacy. This paper proposes an improved VEGA with archive (iVEGA-A) to deal with multiobjective PPS problems, with consideration being given to the minimization of both makespan ...
In this thesis we focus on subexponential algorithms for NP-hard graph problems: exact and parameterized algorithms that have a truly subexponential running time behavior. For input instances of size n we study exact algorithms with running time 2O(√n) and parameterized algorithms with running time 2O(√k) ·nO(1) with parameter k, respectively. We study a class of problems for which we design such algorithms for three different types of graph classes: planar graphs, graphs of bounded genus, and H-minor-free graphs. We distinguish between unconnected and connected problems, and discuss how to conceive parameterized and exact algorithms for such problems. We improve upon existing dynamic programming techniques used in algorithms solving those problems. We compare tree-decomposition and branch-decomposition based dynamic programming algorithms and show how to unify both algorithms to one single algorithm. Then we give a dynamic programming technique that reduces much of the computation involved ...
The discovery of single-nucleotide polymorphisms (SNPs) has important implications in a variety of genetic studies on human diseases and biological functions. One valuable approach proposed for SNP discovery is based on base-specific cleavage and mass spectrometry. However, it is still very challenging to achieve the full potential of this SNP discovery approach. In this study, we formulate two new combinatorial optimization problems. While both problems are aimed at reconstructing the sample sequence that would attain the minimum number of SNPs, they search over different candidate sequence spaces. The first problem, denoted as , limits its search to sequences whose in silico predicted mass spectra have all their signals contained in the measured mass spectra. In contrast, the second problem, denoted as
The phase retrieval problem is of paramount importance in various areas of applied physics and engineering. The state of the art for solving this problem in two dimensions relies heavily on the pioneering work of Gerchberg, Saxton, and Fienup. Despite the widespread use of the algorithms proposed by these three researchers, current mathematical theory cannot explain their remarkable success. Nevertheless, great insight can be gained into the behavior, the shortcomings, and the performance of these algorithms from their possible counterparts in convex optimization theory. An important step in this direction was made two decades ago when the error reduction algorithm was identified as a nonconvex alternating projection algorithm. Our purpose is to formulate the phase retrieval problem with mathematical care and to establish new connections between well-established numerical phase retrieval schemes and classical convex optimization methods. Specifically, it is shown that Fienups basic input-output ...
For machine learning algorithms, what you do is split the data up into training, testing, and validation sets.But as I mentioned, this is more of a proof of concept, to show how to apply genetic algorithms to find trading strategies.. Most of the time when someone talks about trading algorithm, they are talking about predictive algorithms. 4. Predictive algorithms There is a whole class.Algorithm-based stock trading is shrouded in mystery at financial firms.In this paper, we are concerned with the problem of efficiently trading a large position on the market place.Algorithms will evaluate suppliers, define how our cars operate.. HiFREQ is a powerful algorithmic engine for high frequency trading that gives traders the ability to employ HFT strategies for EQ, FUT, OPT and FX trading.QuantConnect provides a free algorithm backtesting tool and financial data so engineers can design algorithmic trading strategies.Artificial intelligence, Machine learning and High frequency trading.Unfortunately, the ...
Unsupervised image segmentation is an important component in many image understanding algorithms and practical vision systems. However, evaluation of segmentation algorithms thus far has been largely subjective, leaving a system designer to judge the effectiveness of a technique based only on intuition and results in the form of a few example segmented images. This is largely due to image segmentation being an ill-defined problem-there is no unique ground-truth segmentation of an image against which the output of an algorithm may be compared. This paper demonstrates how a recently proposed measure of similarity, the normalized probabilistic rand (NPR) index, can be used to perform a quantitative comparison between image segmentation algorithms using a hand-labeled set of ground-truth segmentations. We show that the measure allows principled comparisons between segmentations created by different algorithms, as well as segmentations on different images. We outline a procedure for algorithm ...
Course Description: In this course students will learn about parallel algorithms. The emphasis will be on algorithms that can be used on shared-memory parallel machines such as multicore architectures. The course will include both a theoretical component and a programming component. Topics to be covered include: modeling the cost of parallel algorithms, lower-bounds, and parallel algorithms for sorting, graphs, computational geometry, and string operations. The programming language component will include data-parallelism, threads, futures, scheduling, synchronization types, transactional memory, and message passing. Course Requirements: There will be bi-weekly assignments, two exams (midterm and final), and a final project. Each student will be required to scribe one lecture. Your grade will be partitioned into: 10% scribe notes, 40% assignments, 20% project, 15% midterm, 15% final. Policies: For homeworks, unless stated otherwise, you can look up material on the web and books, but you cannot ...
The article presents a general view of a class of decomposition algorithms for training Support Vector Machines (SVM) which are motivated by the method of feasible directions. The first such algorithm for the pattern recognition SVM has been proposed by Joachims in 1999. Its extension to the regression SVM – the maximal inconsistency algorithm – has been recently presented by the author. A detailed account of both algorithms is carried out, complemented by theoretical investigation of the relationship between the two algorithms. It is proved that the two algorithms are equivalent for the pattern recognition SVM, and the feasible direction interpretation of the maximal inconsistency algorithm is given for the regression SVM. The experimental results demonstrate an order of magnitude decrease of training time in comparison with training without decomposition, and, most importantly, provide experimental evidence of the linear
Downloadable (with restrictions)! This paper introduces a second-order differentiability smoothing technique to the classical l 1 exact penalty function for constrained optimization problems(COP). Error estimations among the optimal objective values of the nonsmooth penalty problem, the smoothed penalty problem and the original optimization problem are obtained. Based on the smoothed problem, an algorithm for solving COP is proposed and some preliminary numerical results indicate that the algorithm is quite promising. Copyright Springer Science+Business Media, LLC 2013
The Parallel Algorithms Project conducts a dedicated research to address the solution of problems in applied mathematics by proposing advanced numerical algorithms to be used on massively parallel computing platforms. The Parallel Algorithms Project is especially considering problems known to be out of reach of standard current numerical methods due to, e.g., the large-scale nature or the nonlinearity of the problem, the stochastic nature of the data, or the practical constraint to obtain reliable numerical results in a limited amount of computing time. This research is mostly performed in collaboration with other teams at CERFACS and the shareholders of CERFACS as outlined in this report.. This research roadmap is known to be quite ambitious and we note that the major research topics have evolved over the past years. The main current focus concerns both the design of algorithms for the solution of sparse linear systems coming from the discretization of partial differential equations and the ...
A global optimization approach for the factor analysis of wireline logging data sets is presented. Oilfield well logs are processed together to give an estimate to factor logs by using an adaptive genetic algorithm. Nonlinear relations between the first factor and essential petrophysical parameters of shaly-sand reservoirs are revealed, which are used to predict the values of shale volume and permeability directly from the factor scores. Independent values of the relevant petrophysical properties are given by inverse modeling and well-known deterministic methods. Case studies including the evaluation of hydrocarbon formations demonstrate the feasibility of the improved algorithm of factor analysis. Comparative numerical analysis made between the genetic algorithm-based factor analysis procedure and the independent well log analsis methods shows consistent results. By factor analysis, an independent in-situ estimate to shale content and permeability is given, which may improve the reservoir model and
This paper describes optimal location and sizing of static var compensator (SVC) based on Particle Swarm Optimization for minimization of transmission losses considering cost function. Particle Swarm Optimization (PSO) is population-based stochastic search algorithms approaches as the potential techniques to solving such a problem. For this study, static var compensator (SVC) is chosen as the compensation device. Validation through the implementation on the IEEE 30-bus system indicated that PSO is feasible to achieve the task. The simulation results are compared with those obtained from Evolutionary Programming (EP) technique in the attempt to highlight its merit.. ...
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): In this paper, we present a new strongly polynomial time algorithm for the minimum cost flow problem, based on a refinement of the Edmonds-Karp scaling technique. Our algorithm solves the uncapacitated minimum cost flow problem as a sequence of O(n log n) shortest path problems on networks with n nodes and m arcs and runs in O(n log n (m + n log n)) time. Using a standard transformation, thjis approach yields an O(m log n (m + n log n)) algorithm for the capacitated minimum cost flow problem. This algorithm improves the best previous strongly polynomial time algorithm, due to Z. Galil and E. Tardos, by a factor of n 2 /m. Our algorithm for the capacitated minimum cost flow problem is even more efficient if the number of arcs with finite upper bounds, say n, is much less than m. In this case, the running time of the algorithm is O((m + n)log n(m + n log n)).
A multiscale design and multiobjective optimization procedure is developed to design a new type of graded cellular hip implant. We assume that the prosthesis design domain is occupied by a unit cell representing the building block of the implant. An optimization strategy seeks the best geometric parameters of the unit cell to minimize bone resorption and interface failure, two conflicting objective functions. Using the asymptotic homogenization method, the microstructure of the implant is replaced by a homogeneous medium with an effective constitutive tensor. This tensor is used to construct the stiffness matrix for the finite element modeling (FEM) solver that calculates the value of each objective function at each iteration. As an example, a 2D finite element model of a left implanted femur is developed. The relative density of the lattice material is the variable of the multiobjective optimization, which is solved through the non-dominated sorting genetic algorithm II (NSGA-II). The set of ...
However, there is no reason that you should be limited to one algorithm in your solutions. Experienced analysts will sometimes use one algorithm to determine the most effective inputs (that is, variables), and then apply a different algorithm to predict a specific outcome based on that data. SQL Server data mining lets you build multiple models on a single mining structure, so within a single data mining solution you might use a clustering algorithm, a decision trees model, and a naïve Bayes model to get different views on your data. You might also use multiple algorithms within a single solution to perform separate tasks: for example, you could use regression to obtain financial forecasts, and use a neural network algorithm to perform an analysis of factors that influence sales.. ...
We propose a general purpose variational inference algorithm that forms a natural counterpart of gradient descent for optimization. Our method iteratively transports a set of particles to match the target distribution, by applying a form of functional gradient descent that minimizes the KL divergence. Empirical studies are performed on various real world models and datasets, on which our method is competitive with existing state-of-the-art methods. The derivation of our method is based on a new theoretical result that connects the derivative of KL divergence under smooth transforms with Steins identity and a recently proposed kernelized Stein discrepancy, which is of independent interest. |P /|
Follicular patterned lesions of the thyroid are problematic and interpretation is often subjective. While thyroid experts are comfortable with their own criteria and thresholds, those encountering these lesions sporadically have a degree of uncertainty with a proportion of cases. The purpose of this review is to highlight the importance of proper diligent sampling of an encapsulated thyroid lesion (in totality in many cases), examination for capsular and vascular invasion, and finally the assessment of nuclear changes that are pathognomonic of papillary thyroid carcinoma (PTC). Based on these established criteria, an algorithmic approach is suggested using known, accepted terminology. The importance of unequivocal, clear-cut nuclear features of PTC as opposed to inconclusive features is stressed. If the nuclear features in an encapsulated, non-invasive follicular patterned lesion fall short of those encountered in classical PTC, but nonetheless are still worrying or concerning, the term ...
View published article Trauma to Lisfrancs Joint, An Algorithmic Approach, published in Lower Extremity Review by Amol Saxena DPM, Palo Alto, CA. Dr Saxena specializes in sports medicine and surgery of the foot and ankle.
We study the problem of finding the cycle of minimum cost-to-time ratio in a directed graph with n nodes and m edges. This problem has a long history in combinatorial optimization and has recently seen interesting applications in the context of quantitative verification. We focus on strongly polynomial algorithms to cover the use-case where the weights are relatively large compared to the size of the graph. Our main result is an algorithm with running time ~O(m^{3/4} n^{3/2}), which gives the first improvement over Megiddos ~O(n^3) algorithm [JACM83] for sparse graphs (We use the notation ~O(.) to hide factors that are polylogarithmic in n.) We further demonstrate how to obtain both an algorithm with running time n^3/2^{Omega(sqrt(log n)} on general graphs and an algorithm with running time ~O(n) on constant treewidth graphs. To obtain our main result, we develop a parallel algorithm for negative cycle detection and single-source shortest paths that might be of independent interest ...
Algorithm portfolios are known to offer robust performances, efficiently overcoming the weakness of every single algorithm on some particular problem instances. Two complementary approaches to get the best out of an algorithm portfolio is to achieve algorithm selection (AS), and to define a scheduler, sequentially launching a few algorithms on a limited computational budget each. The presented Algorithm Selector And Prescheduler system relies on the joint optimization of a pre-scheduler and a per instance AS, selecting an algorithm well-suited to the problem instance at hand. ASAP has been thoroughly evaluated against the state-of-the-art during the ICON challenge for algorithm selection, receiving an honourable mention. Its evaluation on several combinatorial optimization benchmarks exposes surprisingly good results of the simple heuristics used; some extensions thereof are presented and discussed in the paper.
Basic concepts. Definition and specification of algorithms. Computational complexity and asymptotic estimates of running time. Sorting algorithms and divide and conquer algorithms. Graphs and networks. Basic graph theory definitions. Algorithms for the reachability problem in a graph. Spanning trees. Algorithms for finding a minimum-cost spanning tree in a graph. Shortest paths. Algorithms for finding one or more shortest paths in graph with nonnegative arc or general arc lengths but not negative length circuits. Network flow algorithms. Flows in capacitated networks, algorithms to find the maximum flow in a network and max-flow min-cut theorems. Matchings. Weighted and unweighted matchings in bipartite graphs, algorithms to find a maximum weight/cardinality matching, the Koenig-Egervary theorem and its relationship with the vertex cover problem. Computational complexity theory. The P and NP classes. Polynomial reductions. NP-completeness and NP-hardness. Exponential-time algorithms. Implicit ...
Current face recognition algorithms use hand-crafted features or extract features by deep learning. This paper presents a face recognition algorithm based on improved deep networks that can automatically extract the discriminative features of the target more accurately. Firstly,this algorithm uses ZCA( Zero-mean Component Analysis) whitening to preprocess the input images in order to reduce the correlation between features and the complexity of the training networks.Then,it organically combines convolution,pooling and stacked sparse autoencoder to get a deep network feature extractor.The convolution kernels are achieved through a separate unsupervised learning model. The improved deep networks get an automatic deep feature extractor through preliminary training and fine-tuning. Finally,the softmax regression model is used to classify the extracted features. This algorithm is tested on several commonly used face databases. It is indicated that the performance is better than the traditional methods and
In the paper we present some guidelines for the application of nonparametric statistical tests and post-hoc procedures devised to perform multiple comparisons of machine learning algorithms. We emphasize that it is necessary to distinguish between pairwise and multiple comparison tests. We show that the pairwise Wilcoxon test, when employed to multiple comparisons, will lead to overoptimistic conclusions. We carry out intensive normality examination employing ten different tests showing that the output of machine learning algorithms for regression problems does not satisfy normality requirements. We conduct experiments on nonparametric statistical tests and post-hoc procedures designed for multiple 1 × N and N × N comparisons with six different neural regression algorithms over 29 benchmark regression data sets. Our investigation proves the usefulness and strength of multiple comparison statistical procedures to analyse and select machine learning algorithms ...
This paper describes a parallel genetic algorithm developed for the solution of the set partitioning problem- a difficult combinatorial optimization problem used by many airlines as a mathematical model for flight crew scheduling. The genetic algorithm is based on an island model where multiple independent subpopulations each run a steady-state genetic algorithm on their own subpopulation and occasionally fit strings migrate between the subpopulations. Tests on forty real-world set partitioning problems were carried out on up to 128 nodes of an IBM SP1 parallel computer. We found that performance, as measured by the quality of the solution found and the iteration on which it was found, improved as additional subpopulations were added to the computation. With larger numbers of subpopulations the genetic algorithm was regularly able to find the optimal solution to problems having up to a few thousand integer variables. In two cases, high- quality integer feasible solutions were found for problems with 36,
This paper focuses on the iterative parameter estimation algorithms for dual-frequency signal models that are disturbed by stochastic noise. The key of the work is to overcome the difficulty that the signal model is a highly nonlinear function with respect to frequencies. A gradient-based iterative (GI) algorithm is presented based on the gradient search. In order to improve the estimation accuracy of the GI algorithm, a Newton iterative algorithm and a moving data window gradient-based iterative algorithm are proposed based on the moving data window technique. Comparative simulation results are provided to illustrate the effectiveness of the proposed approaches for estimating the parameters of signal models.
Improving the Performance of the RISE Algorithm - Ideally, a multi-strategy learning algorithm performs better than its component approaches. RISE is a multi-strategy algorithm that combines rule induction and instance-based learning. It achieves higher accuracy than some state-of-the-art learning algorithms, but for large data sets it has a very high average running time. This work presents the analysis and experimental evaluation of SUNRISE, a new multi-strategy learning algorithm based on RISE. The SUNRISE algorithm was developed to be faster than RISE with similar accuracy. Comparing the results of the experimental evaluation of the two algorithms, it could be verified that the new algorithm achieves comparable accuracy to that of the RISE algorithm but in a lower average running time.
This paper proposes two parallel algorithms called an even region parallel algorithm (ERPA) and an even strip parallel algorithm (ESPA) respectively for ex
Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance.
NIPS 2013 Workshop on Greedy Algorithms, Frank-Wolfe and Friends - A modern perspective Keywords: Frank-Wolfe Algorithm, greedy algorithms, first-order optimization, convex optimization, signal processing, machine learning
In this paper we present a robust parsing algorithm based on the link grammar formalism for parsing natural languages. Our algorithm is a natural extension of the original dynamic programming recognition algorithm which recursively counts the number of linkages between two words in the input sentence. The modified algorithm uses the notion of a null link in order to allow a connection between any pair of adjacent words, regardless of their dictionary definitions. The algorithm proceeds by making three dynamic programming passes. In the first pass, the input is parsed using the original algorithm which enforces the constraints on links to ensure grammaticality. In the second pass, the total cost of each substring of words is computed, where cost is determined by the number of null links necessary to parse the substring. The final pass counts the total number of parses with minimal cost. All of the original pruning techniques have natural counterparts in the robust algorithm. When used together ...
This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. These three models are: a sequential model, a modified global parallel genetic algorithm model and a new proposed parallel genetic algorithm model we called the Trigger Model (TM). The reduction of the implementation processing time is the basic motivation of genetic algorithms parallelization. In this work, parallel virtual machine (PVM), which is a portable message-passing programming system, designed to link separate host machines to form a virtual machine which is a single, manageable computing resource, is used in a distributed heterogeneous environment. The best result was reached and The TM model was clearly performing better than the other two models. ...
Some simple algorithms commonly used in computer science are linear search algorithms, arrays and bubble sort algorithms. Insertion sorting algorithms are also often used by computer...
The LDDMM Validation section provides input data, processing and visualization examples for LDDMM to ensure correctness of the resultant data. These examples are useful tests when LDDMM is run on new environments or platforms. Example images show atlas volume in red. On the left, the original target is in grey. On the right, the deformed atlas is pictured. A sample LDDMM command is posted with each example (click here or type ...
Algorithms[edit]. In terms of numerical analysis, isotonic regression involves finding a weighted least-squares fit x. ∈. R. n ... These two algorithms can be seen as each other's dual, and both have a computational complexity of O. (. n. ). .. {\ ... a simple iterative algorithm for solving this quadratic program is called the pool adjacent violators algorithm. Conversely, ... Leeuw, Jan de; Hornik, Kurt; Mair, Patrick (2009). "Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and ...
Algorithms[edit]. *Datafly algorithm. References[edit]. *^ Nadri H, Rahimi B, Timpka T, Sedghi S (August 2017). "The Top 100 ... algorithms and systems to be developed. Thus, computer scientists working in computational health informatics and health ...
Algorithms[edit]. Roussopoulos (1973) and Lehot (1974) described linear time algorithms for recognizing line graphs and ... While adding vertices to L, maintain a graph G for which L = L(G); if the algorithm ever fails to find an appropriate graph G, ... Roussopoulos, N. D. (1973), "A max {m,n} algorithm for determining the graph H from its line graph G", Information Processing ... Lehot, Philippe G. H. (1974), "An optimal algorithm to detect a line graph and output its root graph", Journal of the ACM, 21: ...
Algorithms[edit]. The "TCP Foo" names for the algorithms appear to have originated in a 1996 paper by Kevin Fall and Sally ... The overall algorithm here is called fast recovery.. Once ssthresh is reached, TCP changes from slow-start algorithm to the ... Congestion control algorithms are classified in relation to network awareness, meaning the extent to which these algorithms are ... The additive increase/multiplicative decrease (AIMD) algorithm is a closed-loop control algorithm. AIMD combines linear growth ...
Algorithms[edit]. Bose, Buss & Lubiw (1998) showed that it is possible to determine in polynomial time whether a given ...
Algorithms[edit]. Stan implements gradient-based Markov chain Monte Carlo (MCMC) algorithms for Bayesian inference, stochastic ... Optimization algorithms: *Limited-memory BFGS (Stan's default optimization algorithm). *Broyden-Fletcher-Goldfarb-Shanno ... MCMC algorithms: *No-U-Turn sampler[1][3] (NUTS), a variant of HMC and Stan's default MCMC engine ...
Some[who?] have theorized that the precise length of intervals does not have a great impact on algorithm effectiveness,[8] ... Without a program, the user has to schedule physical flashcards; this is time-intensive and limits users to simple algorithms ... SM-family of algorithms (SuperMemo): SM-0 (a paper implementation) to SM-17 (in SuperMemo 17) ... The program schedules pairs based on spaced repetition algorithms. ...
Algorithms[edit]. *finding boundaries of level sets after image segmentation *Edge detection ...
Algorithms[edit]. There are several algorithms designed to perform dithering. One of the earliest, and still one of the most ... error-diffusion algorithms typically produce images that more closely represent the original than simpler dithering algorithms. ... Some dither algorithms use noise that has more energy in the higher frequencies so as to lower the energy in the critical audio ... This may be the simplest dithering algorithm there is, but it results in immense loss of detail and contouring.[16] ...
5 Algorithms *5.1 Optimally coloring special classes of graphs. *5.2 Algorithms that use more than the optimal number of colors ... The time for the algorithm is bounded by the time to edge color a bipartite graph, O(m log Δ) using the algorithm of Cole, Ost ... Karloff, Howard J.; Shmoys, David B. (1987), "Efficient parallel algorithms for edge coloring problems", Journal of Algorithms ... and his algorithm solves the two subproblems recursively. The total time for his algorithm is O(m log m). ...
Discrete Algorithms (SODA '99), pp. 310-316. .. *. Erdős, P.; Lovász, L.; Simmons, A.; Straus, E. G. (1973), "Dissection graphs ... Algorithms[edit]. Constructing an arrangement means, given as input a list of the lines in the arrangement, computing a ... Chan, T. (1999), Remarks on k-level algorithms in the plane, archived from the original on 2010-11-04. . ... Algorithm Engineering (WAE '99), Lecture Notes in Computer Science, 1668, Springer-Verlag, pp. 139-153, doi:10.1007/3-540-48318 ...
Algorithms[edit]. There are various algorithms for the diagnosis of heart failure. For example, the algorithm used by the ... ESC algorithm[edit]. The ESC algorithm weights the following parameters in establishing the diagnosis of heart failure:[54] ... In contrast, the more extensive algorithm by the European Society of Cardiology (ESC) weights the difference between supporting ... Using a special pacing algorithm, biventricular cardiac resynchronization therapy (CRT) can initiate a normal sequence of ...
Algorithms[edit]. wolfSSH uses the cryptographic services provided by wolfCrypt.[2] wolfCrypt Provides RSA, ECC, Diffie-Hellman ...
Clarkson (1995) defines two algorithms, a recursive algorithm and an iterative algorithm, for linear programming based on ... Algorithms[edit]. Seidel[edit]. Seidel (1991) gave an algorithm for low-dimensional linear programming that may be adapted to ... and suggests a combination of the two that calls the iterative algorithm from the recursive algorithm. The recursive algorithm ... Discrete Algorithms, pp. 423-429. .. *. Chazelle, Bernard; Matoušek, Jiří (1996), "On linear-time deterministic algorithms for ...
A fourth algorithm, not as commonly used, is the reverse-delete algorithm, which is the reverse of Kruskal's algorithm. Its ... Algorithms[edit]. In all of the algorithms below, m is the number of edges in the graph and n is the number of vertices. ... found a linear time randomized algorithm based on a combination of Borůvka's algorithm and the reverse-delete algorithm.[3][4] ... Classic algorithms[edit]. The first algorithm for finding a minimum spanning tree was developed by Czech scientist Otakar ...
... for arbitrary graphs the shortest path may require slower algorithms such as Dijkstra's algorithm or the Bellman-Ford algorithm ... Path algorithms[edit]. Some algorithms become simpler when used on DAGs instead of general graphs, based on the principle of ... In many randomized algorithms in computational geometry, the algorithm maintains a history DAG representing the version history ... Jungnickel, Dieter (2012), Graphs, Networks and Algorithms, Algorithms and Computation in Mathematics, 5, Springer, pp. 92-93, ...
ALS algorithms[edit]. ALS assumes that basic life support (bag-mask administration of oxygen and chest compressions) are ... The main algorithm of ALS, which is invoked when actual cardiac arrest has been established, relies on the monitoring of the ... Resuscitation Council UK adult ALS algorithm 2005 Archived October 8, 2007, at the Wayback Machine. ... although they may employ slightly modified version of the Medical algorithm. In the United States, Paramedic level services are ...
Algorithm and variant Output size. (bits) Internal state size. (bits) Block size. (bits) Rounds Operations Security (in bits) ... All SHA-family algorithms, as FIPS-approved security functions, are subject to official validation by the CMVP, a joint program ... SHA-1: A 160-bit hash function which resembles the earlier MD5 algorithm. This was designed by the National Security Agency ( ... The Secure Hash Algorithms are a family of cryptographic hash functions published by the National Institute of Standards and ...
Iterative Reconstruction Algorithm[2][edit]. Main article: Iterative reconstruction. Iterative algorithm is computationally ... Reconstruction algorithms[edit]. Practical reconstruction algorithms have been developed to implement the process of ... Fourier-Domain Reconstruction Algorithm[4][edit]. Reconstruction can be made using interpolation. Assume N. {\displaystyle N}. ... Back Projection Algorithm[2][edit]. In practice of tomographic image reconstruction, often a stabilized and discretized version ...
An algorithm is applied to the six images to recreate the high dynamic range radiance map of the original scene (a high dynamic ... Despite this, if algorithms could not sufficiently map tones and colors, a skilled artist was still needed, as is the case with ... Those algorithms are more complicated than the global ones; they can show artifacts (e.g. halo effect and ringing); and the ... Tone mapping algorithms[edit]. *Perceptually Based Tone Mapping for Low-Light Conditions ...
Design and algorithms[edit]. Video search has evolved slowly through several basic search formats which exist today and all use ... Rather than applying a text search algorithm after speech-to-text processing is completed, some engines use a phonetic search ... Many efforts to improve video search including both human powered search as well as writing algorithm that recognize what's ... depends entirely on the searcher and the algorithm that the owner has chosen. That's why it has always been discussed and now ...
Use of algorithms[edit]. Data is being generated by algorithms, and the algorithms associate preferences with the user's ... Algorithms may also be manipulated. In February 2015, Coca-Cola ran into trouble over an automated, algorithm-generated bot ... algorithm-generated bot was tricked into tweeting a racial slur from the official team account.[17] ...
There have been several generations of HTM algorithms.[6]. Zeta 1: first generation node algorithms[edit]. During training, a ... Cortical learning algorithms: second generation[edit]. The second generation of HTM learning algorithms was drastically ... Cortical Learning Algorithm Tutorial: CLA Basics, talk about the cortical learning algorithm (CLA) used by the HTM model on ... 1 HTM structure and algorithms *1.1 Zeta 1: first generation node algorithms ...
Girvan-Newman algorithm[edit]. Another commonly used algorithm for finding communities is the Girvan-Newman algorithm.[1] This ... The classic algorithm to find these is the Bron-Kerbosch algorithm. The overlap of these can be used to define communities in ... Testing methods of finding communities algorithms[edit]. The evaluation of algorithms, to detect which are better at detecting ... practical algorithms are based on approximate optimization methods such as greedy algorithms, simulated annealing, or spectral ...
Pseudo-Marginal Metropolis-Hastings algorithm. Bayesian algorithms and methods[edit]. Bayesian statistics is often used for ...
Cache-Oblivious Algorithms. Masters thesis, MIT. 1999. *^ Kumar, Piyush. "Cache-Oblivious Algorithms" (PDF). Algorithms for ... In computing, a cache-oblivious algorithm (or cache-transcendent algorithm) is an algorithm designed to take advantage of a CPU ... An optimal cache-oblivious algorithm is a cache-oblivious algorithm that uses the cache optimally (in an asymptotic sense, ... Optimal cache-oblivious algorithms are known for the Cooley-Tukey FFT algorithm, matrix multiplication, sorting, matrix ...
In general, algorithms that "learned" how to find correct matches out of larger image datasets outperformed those that only had ... How well do facial recognition algorithms cope with a million strangers?. Engineering , News releases , Research , Technology ... All of the algorithms suffered in accuracy when confronted with more distractions, but some fared much better than others. ... But the SIAT MMLab algorithm developed by a research team from China, which learned on a smaller number of images, bucked that ...
What are algorithms, Algorithms as technology, Evolution of Algorithms, Design of Algorithm, Need of Correctness of Algorithm, ... Design and Analysis of Algorithms (DAA) Unit I . Fundamentals (09 Hours). The Role of Algorithms in Computing - ... Embedded Algorithms: Embedded system scheduling (power optimized scheduling algorithm), sorting algorithm for embedded systems ... Unit VI . Multi-threaded and Distributed Algorithms (09 Hours). Multi-threaded Algorithms - Introduction, Performance measures ...
the algorithms conform to [. XML Namespaces. ], otherwise if [. XML 1.1. ] is in use, algorithms conform to [. XML Namespaces ... This appendix contains several namespace algorithms, such as namespace normalization algorithm that fixes namespace information ... Appendix B: Namespaces Algorithms. Editors: Arnaud Le Hors, IBM. Elena Litani, IBM. Table of contents. *B.1 Namespace ... The algorithm will then continue and consider the element child2. , will no longer find a namespace declaration mapping the ...
Python implementations of various algorithms, more Python algorithm implementations, and still more Python algorithms. ... Nov: 2: Dijkstras algorithm (Chapter 14). Nov. 4: Minimum spanning trees (Chapter 15). Week 7: Midterm; dynamic programming. ... 2: Approximation algorithms (Chapter 18). Final exam:. Dec. 5 (Monday), 4:00 - 6:00 (per schedule) Other Course-Related ... 28: Streaming algorithms (not in text; see Graham Cormodes slides on finding frequent items and the Wikipedia article on ...
... algorithms are also quite common topics in interviews. There are many interview questions about search and sort algorithms. ... All of these algorithms will be discussed in this chapter.. Keywords. Binary Search Edit Distance Sort Algorithm Edit Operation ... There are many interview questions about search and sort algorithms. Backtracking, dynamic programming, and greedy algorithms ... This process is experimental and the keywords may be updated as the learning algorithm improves. ...
Algorithms Software Software. Free, secure and fast downloads from the largest Open Source applications and software directory ... The engine is a library of already tested algorithms,include collaborative filtering. We will try to add some new algorithms ... Algorithms Software. * Get your Apps to customers 5x faster with RAD Studio.. The easiest and most powerful cross platform ... Hot topics in Algorithms Software. panda cron c# barcode c# usps barcode inventory c# visualization tools expression parser ...
Algorithms Software Software. Free, secure and fast downloads from the largest Open Source applications and software directory ... Algorithms (3) * Internet (2) * WWW/HTTP (2) * Indexing/Search (1) * Scientific/Engineering (1) * Artificial Intelligence (1) * ...
The algorithm (and therefore the program code) is simpler than other algorithms, especially compared to strong algorithms that ... An algorithm combining a constraint-model-based algorithm with backtracking would have the advantage of fast solving time, and ... In his paper Sudoku as a Constraint Problem,[12] Helmut Simonis describes many reasoning algorithms based on constraints which ... Algorithms designed for graph colouring are also known to perform well with Sudokus.[11] It is also possible to express a ...
SNCStream: A Social Network-based Data Stream Clustering Algorithm. In ACM 30th Symposium On Applied Computing (ACM SAC), 2015 ... In order to make use of these algorithms you will need to use MOA framework, which you can find at {M}assive {O}nline {A} ... In order to use these algorithms, please download both moa.jar and sizeofag.jar from {M}assive {O}nline {A}nalysis Framework. ... You can also unzip MOAs any of the JAR files, add the source code for the algorithms desired to moa.classifiers/moa.clusterers ...
In this chapter we introduce the important concept of approximation algorithms. So far we have dealt mostly with polynomially ... Here approximation algorithms must be mentioned in the first place.. Keywords. Approximation Algorithm Chromatic Number Vertex ... Slavík, P. [1997]: A tight analysis of the greedy algorithm for set cover. Journal of Algorithms 25 (1997), 237-254CrossRef ... Korte B., Vygen J. (2012) Approximation Algorithms. In: Combinatorial Optimization. Algorithms and Combinatorics, vol 21. ...
Hiring algorithms create a selection process that offers no transparency and is not monitored. Applicants struck from an ... Inadvertent or intentional, the ability to detect bias of an algorithm is extremely difficult because it can occur at any stage ... The data to build these algorithms increase exponentially.. One video interview service, HireVue, boasts of its ability to ... Although often historic biases are inadvertently built into algorithms and reflect human prejudices, recent scholarship by ...
Come to Women Who Codes bi-weekly algorithms meetup!This week we will be hosted by Megaphone (Panoply rebrande ... Interested in sharpening your problem solving skills and learning more about algorithms? ... We typically implement and discuss algorithms in the meetup - laptops are recommended, but not necessary.. Please RSVP at least ... Interested in sharpening your problem solving skills and learning more about algorithms? Come to Women Who Codes bi-weekly ...
The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics ... This book presents a unified treatment of many different kinds of planning algorithms. ... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads ... between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered ...
Examples of Parallel Algorithms *Primes *Sparse Matrix Multiplication *Planar Convex-Hull *Three Other Algorithms *Summary * ... Other algorithms. *An online tutorial. *Some animations of parallel algorithms (requires X windows). *A page of resources on ... A brief overview of the current state in parallel algorithms. Includes pointers to good books on parallel algorithms. *A ... Programming Parallel Algorithms. Guy E. Blelloch. Computer Science Department. Carnegie Mellon University This page is an ...
A randomized algorithm is an algorithm that uses random numbers to influence the choices it makes in the course of its ... For many applications a randomized algorithm is the fastest algorithm available, or the simplest, or both. ... Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth ... A randomized algorithm is an algorithm that uses random numbers to influence the choices it makes in the course of its ...
Beginning Algorithms A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing ... Beginning Algorithms. A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing ... The Boyer-Moore Algorithm * 16.4.1. Creating the Tests * 16.4.1.1. How It Works ... This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and ...
Pyramid Algorithms presents a unique approach to understanding, analyzing, and computing the most common polynomial and spline ... Chapter 7: B-Spline Approximation and the de Boor Algorithm * 7.1 The de Boor Algorithm ... Pyramid Algorithms presents a unique approach to understanding, analyzing, and computing the most common polynomial and spline ... Chapter 8: Pyramid Algorithms for Multisided Bezier Patches * 8.1 Barycentric Coordinates for Convex Polygons ...
Conversely, research on algorithms and their complexity has established new perspectives in ... ... Combinatorial mathematics has substantially influenced recent trends and developments in the theory of algorithms and its ... Conversely, research on algorithms and their complexity has established new perspectives in discrete mathematics. This new ... Combinatorial mathematics has substantially influenced recent trends and developments in the theory of algorithms and its ...
Algorithms and Data Sciences. Two features are common to much of the field of Algorithms- mathematical guarantees of time and ... Visit: Algorithms and Data Sciences. Cryptography. Cryptographic algorithms are the core mathematical ingredients of most ... Distributed Computation, Streaming Algorithms and the study of Communication requirements in Algorithms have all received some ... Novel machine learning algorithms and paradigms. *Foundational aspects of optimization techniques, including new algorithms and ...
Editorial Algorithms. More Editorial Algorithms. Analysing and curating web content. This project looks at ways to ... Using Algorithms to Understand Content gets more technical and looks at our attempts at teaching algorithms (including Machine ... Create novel technology, or adopt state-of-the art algorithms to create a unique layer of understanding about the wealth of ... What might happen if algorithms and machine learning were to search out content from the BBC archive for BBC Four audiences? ...
This video of a talk at TED though challenges that whole theory though and makes us all think again about algorithms and how ... Even though most people dont even know that they are seeing content based on algorithms its widely believed that they are a ... out the volume and leaving us with the important content but those editors are increasingly being replaced by algorithms on ...
Assign 2 (algorithms in NESL) handed out (see notes). Assigned Reading: Parallel Algorithms up through 10.3 ... Asynchronous Algorithms I. Final project proposal due.. Notes on Asynchronous Algorithms (Updated April 19th) ... Course Description: In this course students will learn about parallel algorithms. The emphasis will be on algorithms that can ... Topics to be covered include: modeling the cost of parallel algorithms, lower-bounds, and parallel algorithms for sorting, ...
... sound algorithm. , , Assume X is an algorithm representing the human mathematical , intelligence. The point is not that man ... Re: Penrose and algorithms Bruno Marchal Fri, 29 Jun 2007 02:57:47 -0700 ...
By analysing the explanation of the classical heapsort algorithm via the method of levels of abstraction mainly due to Floridi ... an algorithm does, the algorithm designer focuses on "how" an algorithm achieves its result. In our example, the algorithm ... The algorithm designers explanation So, the algorithm designer is able to show that his pseudo-code, the LoA he constructed, ... Algorithms and Their Explanations * 1. Algorithms and Their Explanations CiE 2014 - History and Philosophy of Computing 24th ...
  • XForms Processors are free (and encouraged) to skip or optimize any steps in this algorithm, as long as the end result is the same. (w3.org)
  • Two features are common to much of the field of Algorithms- mathematical guarantees of time and space for even the worst-case input and random access to the entire input. (microsoft.com)
  • A focus of ours has been developing mathematical models under which simple algorithms (often ones used widely in practice) have provable guarantees of time and space. (microsoft.com)
  • Cryptographic algorithms are the core mathematical ingredients of most solutions to security problems. (microsoft.com)
  • But whether you know algorithms down to highly mathematical abstractions or simple as a fuzzy series of steps that transform input into output, it can be helpful to visualize what's going on under the hood. (slashdot.org)
  • Isolated conventional algorithms or closed-loop mathematical modeling are not enough in scenarios in which a system must react dynamically to unpredictable events such as traffic jams, road blocks or staff absences. (fraunhofer.de)
  • We will study asymptotic complexity and mathematical analysis of algorithms, design techniques, data structures, and possible applications. (unc.edu)
  • The Algorithms for Threat Detection (ATD) program will support research projects to develop the next generation of mathematical and statistical algorithms for analysis of large spatiotemporal datasets with application to quantitative models of human dynamics. (nsf.gov)
  • Mathematical maturity and comfort with undergraduate algorithms and basic probability. (utexas.edu)
  • In elementary arithmetic, a standard algorithm or method is a specific method of computation which is conventionally taught for solving particular mathematical problems. (wikipedia.org)
  • Backtracking, dynamic programming, and greedy algorithms are useful tools to solve many problems posed in coding interviews. (springer.com)
  • Some hobbyists have developed computer programs that will solve Sudoku puzzles using a backtracking algorithm, which is a type of brute force search. (wikipedia.org)
  • Although it has been established that approximately 6.67 x 10 21 final grids exist, a brute force algorithm can be a practical method to solve Sudoku puzzles. (wikipedia.org)
  • One programmer reported that such an algorithm may typically require as few as 15,000 cycles, or as many as 900,000 cycles to solve a Sudoku, each cycle being the change in position of a "pointer" as it moves through the cells of a Sudoku. (wikipedia.org)
  • Unlike the latter however, optimisation algorithms do not necessarily require problems to be logic-solvable, giving them the potential to solve a wider range of problems. (wikipedia.org)
  • The most challenging problems in complexity theory include proving lower bounds on the complexity of natural problems and hence proving inherent limitations on all conceivable algorithms that solve such problems. (microsoft.com)
  • We apply our expertise in computational geometry and I/O-efficient algorithms to solve these problems in a rigorous way. (tue.nl)
  • When using an evolutionary algorithm to solve a problem, the programmer must supply a set of basic functions that the program should be able to use in order to accomplish its goal, as well as supply a definition of how close the program came to achieving its goal. (archive.org)
  • An algorithm is a sequence of steps or instructions that outline how to solve a particular problem. (encyclopedia.com)
  • Once you've identified the problem you're trying to solve -- or the business result you're trying to achieve -- the algorithm sets forth the steps that will get you where you want to go. (informationweek.com)
  • Each chapter describes real problems and then presents algorithms to solve them. (mit.edu)
  • The world is full of problems, but not every problem has a good algorithm that can solve it. (uib.no)
  • This follow-up course Algorithms focuses on the design and analysis of provably efficient algorithms to solve optimization problems such as finding shortest paths in a network, or comparing the similarity of two strings of DNA. (tue.nl)
  • The primary topics in this part of the specialization are: asymptotic ('Big-oh') notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts). (coursera.org)
  • The idea (and name) for cache-oblivious algorithms was conceived by Charles E. Leiserson as early as 1996 and first published by Harald Prokop in his master's thesis at the Massachusetts Institute of Technology in 1999. (wikipedia.org)
  • The textbook by Cormen, Leiserson, and Rivest is by far the most useful and comprehensive reference on standard algorithms. (hmc.edu)
  • Cache-oblivious algorithms are contrasted with explicit blocking , as in loop nest optimization , which explicitly breaks a problem into blocks that are optimally sized for a given cache. (wikipedia.org)
  • Becker, A., and Geiger, D. : Optimization of Pearl's method of conditioning and greedy-like approximation algorithms for the vertex feedback set problem. (springer.com)
  • Many subfields such as Machine Learning and Optimization have adapted their algorithms to handle such clusters. (stanford.edu)
  • Following the development of basic combinatorial optimization techniques in the 1960s and 1970s, a main open question was to develop a theory of approximation algorithms. (springer.com)
  • In each of the 27 chapters an important combinatorial optimization problem is presented and one or more approximation algorithms for it are clearly and concisely described and analyzed. (springer.com)
  • In this paper we propose a benchmark for verification of properties of fault-tolerant clock synchronization algorithms, namely, a benchmark of a TTEthernet network, where properties of the clock synchronization algorithm as implemented in a TTEthernet network can be verified, and optimization techniques for verification purposes can be applied. (easychair.org)
  • Typically, a cache-oblivious algorithm works by a recursive divide and conquer algorithm , where the problem is divided into smaller and smaller subproblems. (wikipedia.org)
  • Internet Engineering Task Force (IETF) M. Jones Request for Comments: 7518 Microsoft Category: Standards Track May 2015 ISSN: 2070-1721 JSON Web Algorithms (JWA) Abstract This specification registers cryptographic algorithms and identifiers to be used with the JSON Web Signature (JWS), JSON Web Encryption (JWE), and JSON Web Key (JWK) specifications. (ietf.org)
  • Some of these editorial parameters are extracted using standard algorithms (such as the Flesch-Kincaid readability test ), others use our in-house language processing technology, and others still are built on experimental machine learning algorithms. (bbc.co.uk)
  • Students' alternative algorithms are often just as correct, efficient, and generalizable as the standard algorithms, and maintain emphasis on the meaning of the quantities involved, especially as relates to place values (something that is usually lost in the memorization of standard algorithms). (wikipedia.org)
  • Mulmuley, Ketan (1994) Computational Geometry: An Introduction through Randomized Algorithms, Prentice-Hall, Englewood Cliffs NJ (ISBN: 0-13-336363-5). (hmc.edu)
  • Obviously - you'll still need some of the algorithms for analyzing the object graph and figuring out what might be a memory leak or not, and tools like MAT have these of course. (infoq.com)
  • The subarea within algorithms research studying the visualization of graphs is called graph drawing, and it is one of the focus areas of our group. (tue.nl)
  • The XForms recalculation algorithm considers model items and model item properties to be vertices in a directed graph. (w3.org)
  • Lecture 6: Graph contraction, star contraction, MST algorithms. (stanford.edu)
  • No. 1 was the algorithm that creates the connection graph, the social networking graph. (cio.com)
  • Finally, you'll finish the course by applying more advanced algorithms, such as hash tables, graph algorithms, and K-nearest. (manning.com)
  • Distributed Computation, Streaming Algorithms and the study of Communication requirements in Algorithms have all received some attention. (microsoft.com)
  • Obviously, even a book as large as Cormen cannot cover all useful algorithms. (hmc.edu)
  • Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. (manning.com)
  • Get a sneak peek at the fun, illustrated, and friendly examples you'll find in Grokking Algorithms on YouTube . (manning.com)
  • Grokking Algorithms by Adit Bhargava is available at manning.com in pBook, eBook, and liveBook formats. (manning.com)
  • The Role of Algorithms in Computing - What are algorithms, Algorithms as technology, Evolution of Algorithms, Design of Algorithm, Need of Correctness of Algorithm, Confirming correctness of Algorithm - sample examples, Iterative algorithm design issues. (google.com)
  • With/their many years of experience in teaching algorithms courses, Richard Johnsonbaugh and Marcus Schaefer include applications of algorithms, examples, end-of-section exercises, end-of-chapter exercises, solutions to selected exercises, and notes to help the reader understand and master algorithms. (informit.com)
  • Includes more than 300 worked examples, which provide motivation, clarify concepts, and show how to develop algorithms, demonstrate applications of the theory, and elucidate proofs. (informit.com)
  • Among the examples he cited were a robo-cleaner that maps out the best way to do housework, and the online trading algorithms that are increasingly controlling Wall Street. (bbc.co.uk)
  • Algorithms in Motion introduces you to the world of algorithms and how to use them as effectively as possible through high-quality video-based lessons, real-world examples, and built-in exercises, so you can put what you learn into practice. (manning.com)
  • The algorithms are presented in pseudocode and can readily be implemented in a computer language. (mit.edu)
  • In general, algorithms that "learned" how to find correct matches out of larger image datasets outperformed those that only had access to smaller training datasets. (washington.edu)
  • This book presents a unified treatment of many different kinds of planning algorithms. (psu.edu)
  • Mr Meaney is keen to play down the role of algorithms in Hollywood. (bbc.co.uk)
  • How well do facial recognition algorithms cope with a million strangers? (washington.edu)
  • It is the first benchmark that tests facial recognition algorithms at a million scale. (washington.edu)
  • Facial recognition algorithms that fared well with 10,000 distracting images all experienced a drop in accuracy when confronted with 1 million images. (washington.edu)
  • Don a pair of these near-infrared LED-studded goggles and any facial-recognition algorithms that work on infrared cameras will be blocked by the lights, says its inventor. (fastcompany.com)
  • Optimal cache-oblivious algorithms are known for the Cooley-Tukey FFT algorithm , matrix multiplication , sorting , matrix transposition , and several other problems. (wikipedia.org)
  • Amortized Analysis - Binary, Binomial and Fibonacci heaps, Dijkstra's Shortest path algorithm, Splay Trees, Time-Space trade-off, Introduction to Tractable and Non-tractable Problems, Introduction to Randomized and Approximate algorithms, Embedded Algorithms: Embedded system scheduling (power optimized scheduling algorithm), sorting algorithm for embedded systems. (google.com)
  • Hochbaum, D.S. : Approximation Algorithms for NP -Hard Problems. (springer.com)
  • The primary goal of research in complexity theory may be viewed as understanding the inherent difficulty of problems in terms of the resources algorithms for those problems need. (microsoft.com)
  • Lower bounds integrated into sections that discuss problems -e.g. after presentation of several sorting algorithms, text discusses lower bound for comparison-based sorting. (informit.com)
  • It contains elegant combinatorial theory, useful and interesting algorithms, and deep results about the intrinsic complexity of combinatorial problems. (springer.com)
  • Clinical management algorithms for common and unusual obstetric problems have been developed to help guide practitioners to the best treatment options for patients. (wiley.com)
  • Algorithms - established processes for solving computational problems-are the foundation of computer programming. (manning.com)
  • Algorithms in Motion teaches you how to apply common algorithms to the practical problems you face every day as a programmer. (manning.com)
  • I will further apply this framework to extend Myerson's celebrated characterization of optimal single-item auctions to multiple items (Myerson 1981), design mechanisms for job scheduling (Nisan and Ronen 1999), and resolve other problems at the interface of algorithms and game theory. (princeton.edu)
  • Students learn in Algorithms (2ILC0) that many computational problems are NP-hard. (tue.nl)
  • It is widely believed that for such problems, no algorithm exists that always finds the optimal solution efficiently (in polynomial time). (tue.nl)
  • One way to deal with NP-hard problems is to use approximation algorithms, as discussed in Advanced Algorithms (2IMA10), or to apply heuristics. (tue.nl)
  • The goal is then to develop so-called FPT algorithms (for Fixed-Parameter Tractable), for which the exponential dependency of the running time (which is most likely unavoidable for NP-hard problems) is not on the input size n, but only on the parameter k. (tue.nl)
  • There is a wide variety of algorithmic techniques for designing FPT algorithms for NP-hard problems. (tue.nl)
  • However, there are also problems for which (for the given parameterization) FPT algorithms do not exist (under appropriate complexity-theoretic assumptions such as P! (tue.nl)
  • The 7th Workshop on Algorithm Engineering and Experiments ( ALENEX05 ) and the 2nd Workshop on Analytic Algorithmics and Combinatorics ( ANALCO05 ) will be held immediately preceding the conference at the same location. (siam.org)
  • For the use in teaching, they propose a slight generalization of the CYK algorithm, "without compromising efficiency of the algorithm, clarity of its presentation, or simplicity of proofs" ( Lange & Leiß 2009 ). (princeton.edu)
  • Employers increasingly rely on algorithms to determine who advances through application portals to an interview. (fastcompany.com)
  • The rest of us rely on algorithms for much of our daily Web and mobile interactions, though we're not always conscious of the important role they play. (informationweek.com)
  • Conversely, research on algorithms and their complexity has established new perspectives in discrete mathematics. (springer.com)
  • Nevertheless, a burst of research on algorithms written specifically for NISQs might enable these devices to perform certain calculations more efficiently than classic computers. (scientificamerican.com)
  • We take a closer look at the origins of the word algorithm, what it means for business today, and how companies such as Google and Airbnb use them. (informationweek.com)
  • Graphical illustrations of a heap of sort algorithms. (merlot.org)
  • In tuning for a specific machine, one may use a hybrid algorithm which uses blocking tuned for the specific cache sizes at the bottom level, but otherwise uses the cache-oblivious algorithm. (wikipedia.org)
  • A simple hybrid algorithm, which does one swap followed by some number of iterations of Lloyd's. (umd.edu)
  • Great way to quickly recap the most common algorithms. (manning.com)
  • Editors play a vital role in sifting out the volume and leaving us with the important content but those editors are increasingly being replaced by algorithms on sites like Facebook and Google and pretty much most of the other big sites you use on the web. (thenextweb.com)
  • His research focuses on designing algorithms that address constraints imposed by the strategic nature of people that interact with them. (princeton.edu)
  • Come to Women Who Code's bi-weekly algorithms meetup! (meetup.com)
  • We typically implement and discuss algorithms in the meetup - laptops are recommended, but not necessary. (meetup.com)
  • More distinct elements algorithms and lower bounds. (utexas.edu)
  • Oleeo commissioned the Department of Computer Science at University College London to look into how algorithms can ensure that they don't inadvertently fall into gender bias, comments Charles Hipps, chief executive officer for Oleeo. (forbes.com)
  • Motwani, Rajeev and Prabhakar Raghaven (1995) Randomized Algorithms, Cambridge Univ. (hmc.edu)