**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.

**Computers**

**Molecular 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)## Java virtual machine

... the garbage-collection

**algorithm**used, and any internal optimization of the Java virtual machine instructions (their ...## Gene expression profiling in cancer

A hierarchical clustering

**algorithm**was used to group cell lines based on the similarity by which the pattern of gene ... The hierarchical clustering**algorithm**identified a subset of tumors that would have been labeled DLBCLs by traditional ...## Structural alignment software

Minami, S.; Sawada K.; Chikenji G. (Jan 2013). "MICAN : a protein structure alignment

**algorithm**that can handle Multiple-chains ... Janez Konc; Dušanka Janežič (2010). "ProBiS**algorithm**for detection of structurally similar protein binding sites by local ... Wang, Sheng; Jian Peng; Jinbo Xu (Sep 2011). "Alignment of distantly related protein structures:**algorithm**, bound and ...**Algorithms**for Molecular Biology. 7 (4): 4. doi:10.1186/1748-7188-7-4. PMC 3298807 . PMID 22336468. ...## Gene expression profiling

Apart from selecting a clustering

**algorithm**, user usually has to choose an appropriate proximity measure (distance or ...**Algorithms** Unlocked

... is a book by Thomas H. Cormen about the basic principles and applications of computer

**algorithms**. The book ... "**Algorithms**Unlocked". MIT Press. Retrieved April 30, 2015. MIT Press:**Algorithms**Unlocked. ... consists of ten chapters, and deals with the topics of searching, sorting, basic graph**algorithms**, string processing, the ...**Algorithms** (journal)

ACM Transactions on

**Algorithms**Algorithmica "About**Algorithms**".**Algorithms**. MDPI. 2013. Retrieved 2013-07-18. Iwama, Kazuo ( ...**Algorithms**is a peer-reviewed open access mathematics journal concerning design, analysis, and experiments on**algorithms**. The ... 2008), "Editor's Foreword",**Algorithms**, 1 (1): 1, doi:10.3390/a1010001 . Official website. ...## XDAIS **algorithms**

For instance, all XDAIS compliant

**algorithms**must implement an**Algorithm**Interface, called IALG. For those**algorithms**utilizing ... XDAIS or eXpressDsp**Algorithm**Interoperability Standard is a standard for**algorithm**development by Texas Instruments for the ... Problems are often caused in**algorithm**by hard-coding access to system resources that are used by other**algorithms**. DAIS ... The XDAIS standard address the issues of**algorithm**resource allocation and consumption on a DSP.**Algorithms**that comply with ...## Navigational **algorithms**

For n ≥ 2 observations DeWit/USNO Nautical Almanac/Compac Data, Least squares

**algorithm**for n LOPs Kaplan**algorithm**, USNO. For ... Navigational**algorithms**is a source of information whose purpose is to make available the scientific part of the art of ... running fixes The**algorithms**implemented are: For n = 2 observations An analytical solution of the two star sight problem of ... for navigational**algorithms**in other domains. An analytical solution of the two star sight problem of celestial navigation. ...## Standard **algorithms**

Students' alternative

**algorithms**are often just as correct, efficient, and generalizable as the standard**algorithms**, and ... In elementary arithmetic, a standard**algorithm**or method is a specific method of computation which is conventionally taught for ... something that is usually lost in the memorization of standard**algorithms**). The development of sophisticated calculators has ...## Quantum optimization **algorithms**

... and an

**algorithm**for learning the fit parameters. Because the quantum**algorithm**is mainly based on the HHL**algorithm**, it ... Among other quantum**algorithms**, there are quantum optimization**algorithms**which might suggest improvement in solving ... The best classical**algorithm**known runs polynomial time in the worst case. The quantum**algorithm**provides a quadratic ... The quantum least-squares fitting**algorithm**makes use of a version of Harrow, Hassidim, and Lloyd's quantum**algorithm**for ...## Convex hull **algorithms**

A much simpler

**algorithm**was developed by Chan in 1996, and is called Chan's**algorithm**. Known convex hull**algorithms**are listed ... Such**algorithms**are called output-sensitive**algorithms**. They may be asymptotically more efficient than Θ(n log n)**algorithms**in ... A number of**algorithms**are known for the three-dimensional case, as well as for arbitrary dimensions. Chan's**algorithm**is used ... This**algorithm**is also applicable to the three dimensional case. Monotone chain aka Andrew's**algorithm**- O(n log n) Published in ...## Kleitman-Wang **algorithms**

These constructions are based on recursive

**algorithms**. Kleitman and Wang gave these**algorithms**in 1973. The**algorithm**is based ... The Kleitman-Wang**algorithms**are two different**algorithms**in graph theory solving the digraph realization problem, i.e. the ... The**algorithm**is based on the following theorem. Let S = ( ( a 1 , b 1 ) , … , ( a n , b n ) ) {\displaystyle S=((a_{1},b_{1 ... In each step of the**algorithm**one constructs the arcs of a digraph with vertices v 1 , … , v n {\displaystyle v_{1},\dots ,v_{n ...## Sudoku solving **algorithms**

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 ...**Algorithms**designed for graph colouring are also known to perform well with Sudokus. It is also possible to express a Sudoku as ... Notice that the**algorithm**may discard all the previously tested values if it finds the existing set does not fulfil the ...## Timeline of **algorithms**

C4.5

**algorithm**, a descendent of ID3 decision tree**algorithm**, was developed by Ross Quinlan 1993 - Apriori**algorithm**developed ... Kruskal's**algorithm**developed by Joseph Kruskal 1957 - Prim's**algorithm**developed by Robert Prim 1957 - Bellman-Ford**algorithm**... 1**algorithm**developed by John Pollard 1975 - Genetic**algorithms**popularized by John Holland 1975 - Pollard's rho**algorithm**... It adds a soft-margin idea to the 1992**algorithm**by Boser, Nguyon, Vapnik, and is the**algorithm**that people usually refer to ...## Communication-avoiding **algorithms**

... are designed with the following objectives: Reorganize

**algorithms**to reduce communication ... Let A, B and C be square matrices of order n x n. The following naive**algorithm**implements C = C + A * B: for i = 1 to n for j ... The Blocked (Tiled) Matrix Multiplication**algorithm**reduces this dominant term. Consider A,B,C to be n/b-by-n/b matrices of b- ... Communication-Avoiding**Algorithms**minimize movement of data within a memory hierarchy for improving its running-time and energy ...## Deadlock prevention **algorithms**

...

**algorithms**, which track all cycles that cause deadlocks (including temporary deadlocks); and heuristics**algorithms**which don't ...**algorithms**, which track all cycles that cause deadlocks (including temporary deadlocks); and heuristics**algorithms**which don't ... A deadlock prevention**algorithm**organizes resource usage by each process to ensure that at least one process is always able to ... In computer science, deadlock prevention**algorithms**are used in concurrent programming when multiple processes must acquire ...## Introduction to **Algorithms**

... is a book by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The first ... "Introduction to

**Algorithms**-CiteSeerX citation query". CiteSeerX. The College of Information Sciences and Technology at Penn ... Each chapter focuses on an**algorithm**, and discusses its design techniques and areas of application. Instead of using a specific ... I Foundations 1 The Role of**Algorithms**in Computing 2 Getting Started 3 Growth of Functions 4 Divide-and-Conquer 5 ...## Analysis of **algorithms**

... determined from the worst case inputs to the

**algorithm**. The term "analysis of**algorithms**" was coined by Donald Knuth.**Algorithm**... Since**algorithms**are platform-independent (i.e. a given**algorithm**can be implemented in an arbitrary programming language on an ...**Algorithm**analysis is important in practice because the accidental or unintentional use of an inefficient**algorithm**can ... In computer science, the analysis of**algorithms**is the determination of the computational complexity of**algorithms**, that is the ...## Secure Hash **Algorithms**

The Secure Hash

**Algorithms**are a family of cryptographic hash functions published by the National Institute of Standards and ... view talk edit All SHA-family**algorithms**, the FIPS-approved security functions, are subject to official validation at the CMVP ... This was designed by the National Security Agency (NSA) to be part of the Digital Signature**Algorithm**. Cryptographic weaknesses ... "The MD5 Message-Digest**Algorithm**". Retrieved 2016-04-18. In the unlikely event that b is greater than 2^64, then only the low- ...## Dynamic problem (**algorithms**)

Incremental

**algorithms**, or online**algorithms**, are**algorithms**in which only additions of elements are allowed, possibly starting ... Decremental**algorithms**are**algorithms**in which only deletions of elements are allowed, starting with an initialization of a ... "Dynamic graph**algorithms**". In CRC Handbook of**Algorithms**and Theory of Computation, Chapter 22. CRC Press, 1997.. ... If both additions and deletions are allowed, the**algorithm**is sometimes called fully dynamic. Static problem For a set of N ...## Numerical **Algorithms** Group

Code and

**algorithms**for the library were contributed to the project by experts in the project, and elsewhere (for example, some ... The Numerical**Algorithms**Group: From 0-40 in a flurry of achievements 40 Years of NAG scrapbook NAG Numerical Routines NAG ... The Numerical**Algorithms**Group (NAG) is a software company which provides methods for the solution of mathematical and ... NAG was founded by Brian Ford and others in 1970 as the Nottingham**Algorithms**Group, a collaborative venture between the ...## Schema (genetic **algorithms**)

A schema is a template in computer science used in the field of genetic

**algorithms**that identifies a subset of strings with ... In evolutionary computing such as genetic**algorithms**and genetic programming, propagation refers to the inheritance of ...## Analysis of parallel **algorithms**

This article discusses the analysis of parallel

**algorithms**. Like in the analysis of "ordinary", sequential,**algorithms**, one is ... An**algorithm**that exhibits linear speedup is said to be scalable. Efficiency is the speedup per processor, Sp ∕ p. Parallelism ... Analysis of parallel**algorithms**is usually carried out under the assumption that an unbounded number of processors is available ... Minimizing the span is important in designing parallel**algorithms**, because the span determines the shortest possible execution ...## ACM Transactions on **Algorithms**

... (TALG) is a quarterly peer-reviewed scientific journal covering the field of

**algorithms**. It was ... Algorithmica**Algorithms**(journal) Gabow, Hal. "Journal of**Algorithms**Resignation". Department of Computer Science, University ... "ACM Transactions on**Algorithms**". 2013 Journal Citation Reports. Web of Science (Science ed.). Thomson Reuters. 2014. "ACM ... Apart from regular submissions, the journal also invites selected papers from the ACM-SIAM Symposium on Discrete**Algorithms**( ...## European Symposium on **Algorithms**

The European Symposium on

**Algorithms**(ESA) is an international conference covering the field of**algorithms**. It has been held ... Since 2001, ESA is co-located with other**algorithms**conferences and workshops in a combined meeting called ALGO. This is the ... The intended scope was all research in**algorithms**, theoretical as well as applied, carried out in the fields of computer ... WABI, the Workshop on**Algorithms**in Bioinformatics, was part of ALGO in 2001-2006 and 2008. WAOA, the Workshop on Approximation ...## Cache-oblivious **algorithm** - Wikipedia

Cache-Oblivious

https://en.wikipedia.org/wiki/Cache-oblivious_algorithm**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 ...## How well do facial recognition **algorithms** cope with a million strangers? | UW News

In general,

http://www.washington.edu/news/2016/06/23/how-well-do-facial-recognition-algorithms-cope-with-a-million-strangers/**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 ...## Namespaces **Algorithms**

the

http://www.w3.org/TR/DOM-Level-3-Core/namespaces-algorithms.html**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 ...**Algorithms**

Python implementations of various

https://www.ics.uci.edu/~eppstein/161/**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 ...## Advanced **Algorithms**

What are

https://sites.google.com/site/advancedalgorithmsaa/**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 ...**Algorithms** | SpringerLink

...

https://link.springer.com/chapter/10.1007/978-1-4302-4762-3_4**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 - SourceForge.net

**Algorithms**Software Software. Free, secure and fast downloads from the largest Open Source applications and software directory ... Hot topics in

**Algorithms**Software. cif jhprimeminer-t18v3 genetic

**algorithm**viscoelastic cuda codigos fonte java software ... PowerCiph Data Encryption

**Algorithm**. The PowerCiph Data Encryption

**Algorithm**is a versatile, yet simplistic, encryption ... pgapack, the parallel genetic

**algorithm**library is a powerfull genetic

**algorithm**library by D. Levine, Mathematics and Computer ...

**Algorithms** Software - SourceForge.net

**Algorithms**Software Software. Free, secure and fast downloads from the largest Open Source applications and software directory ... Can be used in testing various robotic

**algorithms**, and already used for comparison of path planning

**algorithms**like RRT, ... Hot topics in

**Algorithms**Software. nesting dxf nesting software nesting 2d nesting software dwg to dxf converter nesting dwg ... An easy to extend, highly graphical, easy to use 2D robot simulator specialized for path planning

**algorithms**. ...

## Beginning **Algorithms** [Book]

Beginning

https://www.oreilly.com/library/view/beginning-algorithms/9780764596742/**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** [Book]

Pyramid

https://www.oreilly.com/library/view/pyramid-algorithms/9781558603547/**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 ...**Algorithms** | InformIT

With/their many years of experience in teaching

http://www.informit.com/store/algorithms-9780023606922**algorithms**courses, Richard Johnsonbaugh and Marcus Schaefer include ... and notes to help the reader understand and master**algorithms**. ... applications of**algorithms**, examples, end-of-section exercises ...**Algorithms**is written for an introductory upper-level undergraduate or graduate course in**algorithms**. ... 6. Greedy**Algorithms**. 7. Dynamic Programming. 8. Text Searching. 9. Computational Algebra. 10. P and NP. 11. Coping with NP- ...## Sudoku solving **algorithms** - Wikipedia

The

https://en.wikipedia.org/wiki/Sudoku_solving_algorithms**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 ...## Conceptual **Algorithms**

Obviously - youll still need some of the

https://www.infoq.com/presentations/preston-werner-conceptual-algorithms**algorithms**for analyzing the object graph and figuring out what might be a memory ...**Algorithms** (ALG)

... The research The design and analysis of

https://www.tue.nl/en/our-university/departments/mathematics-and-computer-science/research/research-programs-computer-science/section-algorithms-and-visualization-av/algorithms-alg/**algorithms**and data structures forms one of the core areas within ... The subarea within**algorithms**research studying the visualization of graphs is called graph drawing, and it is one of the focus ...**Algorithms**for GIS and automated cartography. Spatial data play a central role in geographic information systems (GIS) and ... The**Algorithms**chair (ALG) performs fundamental research in this area, focusing on algorithmic problems for spatial data. Such ...**Algorithms**

matrix

https://www.cs.hmc.edu/~fleck/computer-vision-handbook/algorithms.html**algorithms*** computational geometry * median filter**algorithms**Handbook Main Page. Ownership, Maintenance, and ... For new techniques involving randomized**algorithms**, see * Motwani, Rajeev and Prabhakar Raghaven (1995) Randomized**Algorithms**, ...**Algorithms**. The textbook by Cormen, Leiserson, and Rivest is by far the most useful and comprehensive reference on standard ... When the analysis of an**algorithm**is not straightforward, you may need some high-powered tricks. For these, see * Sedgewick, ...## Approximation **Algorithms** | SpringerLink

In this chapter we introduce the important concept of approximation

https://link.springer.com/chapter/10.1007/978-3-642-24488-9_16**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. ...**Algorithms** Meetup | Meetup

Come to Women Who Codes bi-weekly

https://www.meetup.com/Women-Who-Code-DC/events/259532572/**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 ...## CP60 Parallel **Algorithms**

Parallel

https://www.siam.org/meetings/archives/op96/cp60.htm**Algorithms**. A Parallel Revised Simplex**Algorithm**using an Edge Weight Based Pricing Strategy J.A. Julian Hall and K.I. ... A Parallel Interior Random Vector**Algorithm**for Multistage Stochastic Linear Programs Ron Levkovitz, Technion-Israel Institute ...**Algorithms** and Combinatorics

Conversely, research on

https://www.springer.com/series/13**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 ...## CiteSeerX - Planning **Algorithms**

The subject lies at the crossroads between robotics, control theory, artificial intelligence,

http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.7086&rank=3**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 ...## Programming Parallel **Algorithms**

Examples of Parallel

http://www.cs.cmu.edu/~scandal/cacm.html**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 ...## Genetic **Algorithms**

... You are to write a genetic

https://www.cs.rochester.edu/~nelson/courses/csc_173/assignments/05.html**algorithm**program to find solutions to the following problems: * Find the ... What population size did you choose? How well does the genetic**algorithm**perform? How many generations does it take to find a ...## Sorting **Algorithms**

... Graphical illustrations of a heap of sort

https://www.merlot.org/merlot/viewMaterial.htm?id=75083**algorithms**. Just how much faster is QuickSort, anyway? ...## Genetic **Algorithms**

... (GA) are a computational paradigm inspired by the mechanics of natural evolution, ... and help explain why genetic

https://www.cs.rochester.edu/users/faculty/nelson/courses/csc_173/genetic-algs/**algorithms**work. Genetic**algorithms**are a popular line of current research, and there are many ... Concrete examples illustrate how to encode a problem for solution as a genetic**algorithm**, ... references describing both the theory of genetic**algorithms**and their use in practical problem solving. ...**Algorithms**

... Part III provides basic conceptual information to help you understand the

https://docs.oracle.com/cd/E11882_01/datamine.112/e16808/part3.htm**algorithms**supported by Oracle Data ... Also, if you have a general understanding of the workings of an**algorithm**, you will be better prepared to optimize its use with ... In cases where more than one**algorithm**is available for a given mining function, this information in these chapters should help ...Genetic AlgorithmsParallel AlgorithmsSort algorithmsTabu Search1996Detailed explanationsFundamentalsDivide and ConGoodrichGreedyHeaps2001ManipulateTypicallyLeisersonCopeEditorsParameterized complexityAlgorithmicProblemsDesignGraphMathematicsReferencesChaptersStructuresTopicsAnalysisApplicationsStandardProblemTheoryContentResearchWorkChapterComprehensiveGroupSoftware

- Genetic algorithms (GA) are a computational paradigm inspired by the mechanics of natural evolution, including survival of the fittest, reproduction, and mutation. (rochester.edu)
- Concrete examples illustrate how to encode a problem for solution as a genetic algorithm, and help explain why genetic algorithms work. (rochester.edu)
- Genetic algorithms are a popular line of current research, and there are many references describing both the theory of genetic algorithms and their use in practical problem solving. (rochester.edu)
- Code displayed, presumably from an IDE]] def getSolutionCosts(navigationCode): fuelStopCost = 15 extraComputationCost = 8 [[There is a giant arrow pointing to the next line]] thisAlgorithmBecomingSkynetCost = 999999999 waterCrossingCost = 45 Narration: Genetic algorithms tip: *Always* include this in your fitness function. (xkcd.com)

- 12. Parallel Algorithms. (informit.com)
- Some animations of parallel algorithms (requires X windows). (cmu.edu)
- A brief overview of the current state in parallel algorithms. (cmu.edu)
- Includes pointers to good books on parallel algorithms. (cmu.edu)

- There are many interview questions about search and sort algorithms. (springer.com)
- Graphical illustrations of a heap of sort algorithms. (merlot.org)

- Approaches for shuffling the numbers include simulated annealing , genetic algorithm and tabu search . (wikipedia.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)
- 1987, Frigo 1996 for matrix multiplication and LU decomposition, and Todd Veldhuizen 1996 for matrix algorithms in the Blitz++ library. (wikipedia.org)
- Sedgewick, Robert and Philippe Flajolet (1996) An Introduction to the Analysis of Algorithms, Addison-Wesley, Reading MA. (hmc.edu)
- Hochbaum, D.S. [1996]: Approximation Algorithms for NP -Hard Problems. (springer.com)
- Becker, A., and Geiger, D. [1996]: Optimization of Pearl's method of conditioning and greedy-like approximation algorithms for the vertex feedback set problem. (springer.com)

- Packed with detailed explanations and instructive examples, the book begins by offering you some fundamental data structures and then goes on to explain various sorting algorithms. (oreilly.com)

- The book consists of ten chapters, and deals with the topics of searching, sorting, basic graph algorithms, string processing, the fundamentals of cryptography and data compression, and an introduction to the theory of computation. (wikipedia.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)

- The course text will be "Algorithm Design and Applications" by Goodrich and Tamassia (Wiley, 2015). (uci.edu)

- Backtracking, dynamic programming, and greedy algorithms are useful tools to solve many problems posed in coding interviews. (springer.com)
- 6. Greedy Algorithms. (informit.com)

- 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)

- Covers distributed algorithms a topic recommended by the ACM (2001 report) for an undergraduate curriculum. (informit.com)
- Vazirani, V.V. [2001]: Approximation Algorithms. (springer.com)

- Additionally, bit operations can be viewed as special algorithms to manipulate binary integers. (springer.com)
- The focus on the structures and algorithms necessary to manipulate the information separates Biomedical Informatics from other medical disciplines where information content is the focus. (dmoztools.net)

- Cache-oblivious algorithms are typically analyzed using an idealized model of the cache, sometimes called the cache-oblivious model . (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)
- We typically implement and discuss algorithms in the meetup - laptops are recommended, but not necessary. (meetup.com)

- The textbook by Cormen, Leiserson, and Rivest is by far the most useful and comprehensive reference on standard algorithms. (hmc.edu)

- How well do facial recognition algorithms cope with a million strangers? (washington.edu)

- 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)

- Recent results -Such as Pearson's polynomial-time algorithm for the coin-changing problem and parameterized complexity. (informit.com)

- The Algorithms chair (ALG) performs fundamental research in this area, focusing on algorithmic problems for spatial data. (tue.nl)
- By analysing the explanation of the classical heapsort algorithm via the method of levels of abstraction mainly due to Floridi, we give a concrete and precise example of how to deal with algorithmic knowledge. (slideshare.net)

- Optimal cache-oblivious algorithms are known for the Cooley-Tukey FFT algorithm , matrix multiplication , sorting , matrix transposition , and several other problems. (wikipedia.org)
- 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)
- 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 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)
- Pyramid Algorithms presents a unique approach to understanding, analyzing, and computing the most common polynomial and spline curve and surface schemes used in computer-aided geometric design, employing a dynamic programming method based on recursive pyramids. (oreilly.com)
- The design and analysis of algorithms and data structures forms one of the core areas within computer science. (tue.nl)
- Algorithms is a peer-reviewed open access mathematics journal concerning design, analysis, and experiments on algorithms. (wikipedia.org)

- 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)

- pgapack, the parallel genetic algorithm library is a powerfull genetic algorithm library by D. Levine, Mathematics and Computer Science Division Argonne National Laboratory. (sourceforge.net)
- Combinatorial mathematics has substantially influenced recent trends and developments in the theory of algorithms and its applications. (springer.com)
- Conversely, research on algorithms and their complexity has established new perspectives in discrete mathematics. (springer.com)

- Provides a robust Companion Website that supplements the text by providing algorithm simulation software, PowerPoint ® slides, late breaking news about algorithms, references about the book's topics, computer programs, and more. (informit.com)

- In cases where more than one algorithm is available for a given mining function, this information in these chapters should help you make the most appropriate choice. (oracle.com)

- In addition to data structures, algorithms are also quite common topics in interviews. (springer.com)
- This is the only book to impart all this essential information-from the basics of algorithms, data structures, and performance characteristics to the specific algorithms used in development and programming tasks. (oreilly.com)
- In the end, you'll be prepared to build the algorithms and data structures most commonly encountered in day-to-day software development. (oreilly.com)
- This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and data structures. (oreilly.com)
- Informatics is an emerging discipline that has been defined as the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information. (dmoztools.net)

- Provides students with expanded explanations of particular topics and additional information on algorithms. (informit.com)
- Provides students with comprehensive chapter on topics with significant importance in algorithms. (informit.com)

- We need to test facial recognition on a planetary scale to enable practical applications - testing on a larger scale lets you discover the flaws and successes of recognition algorithms," said Ira Kemelmacher-Shlizerman , a UW assistant professor of computer science and the project's principal investigator. (washington.edu)
- Library Of Randomized Algorithms: Randomization is a powerful idea has applications in science and engineering. (sourceforge.net)
- More applications than other algorithms texts. (informit.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)

- It is using Artificial Neural Networks to enchance the results of standard algorithms. (sourceforge.net)
- 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)

- 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)
- Bar-Yehuda, R., and Even, S. : A linear-time approximation algorithm for the weighted vertex cover problem. (springer.com)
- Interested in sharpening your problem solving skills and learning more about algorithms? (meetup.com)

- This video of a talk at TED though challenges that whole theory though and makes us all think again about algorithms and how sites like Facebook and Google choose to serve us up content. (thenextweb.com)

- Even though most people don't even know that they are seeing content based on algorithms it's widely believed that they are a good thing because they make content more relevant and cut down on the amount of time you waste consuming information that you don't need to. (thenextweb.com)

- But the SIAT MMLab algorithm developed by a research team from China , which learned on a smaller number of images, bucked that trend by outperforming many others. (washington.edu)
- Our research in this area focuses on algorithms with provable guarantees on their I/O- and caching behavior. (tue.nl)

- Shows students how algorithms work to elucidate proofs. (informit.com)
- A Sudoku designed to work against the brute force algorithm. (wikipedia.org)
- Assuming the solver works from top to bottom (as in the animation), a puzzle with few clues (17), no clues in the top row, and has a solution "987654321" for the first row, would work in opposition to the algorithm. (wikipedia.org)

- All of these algorithms will be discussed in this chapter. (springer.com)
- In this chapter we introduce the important concept of approximation algorithms. (springer.com)

- A comprehensive library of algorithms in multiple languages, each having a detailed proof of correctness. (sourceforge.net)

- Which algorithm should be used to group classifiers. (google.com)

- A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently. (oreilly.com)
- the algorithm designer who takes the general speciﬁcations from the software designer and convert them into precise descriptions of what the programmer must implement. (slideshare.net)