Search results for "Source code"

showing 10 items of 61 documents

Tool Support for Model Driven Development of Pervasive Systems

2007

This work presents the PervML Generative Tool (PervGT) that supports a model driven method for the development of pervasive services in ubiquitous environments. The tool, which is based on the Eclipse platform, provides facilities for the graphical description of pervasive systems using PervML, a UML-like modeling language. Once the pervasive system is specified, the PervML model is used as input to a transformation engine that generates source code and other implementation assets. This generated code extends an OSGi-based framework in order to build the final pervasive applications

Context modelSource codeUbiquitous computingJavaModeling languageProgramming languagebusiness.industryComputer sciencemedia_common.quotation_subjectApplication softwarecomputer.software_genreFormal specificationInformation systemSoftware engineeringbusinesscomputermedia_commoncomputer.programming_languageFourth International Workshop on Model-Based Methodologies for Pervasive and Embedded Software (MOMPES'07)
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EXPERIMENTAL VALIDATION OF A FINITE DIFFERENCES TROMBE WALL MODEL

1983

ABSTRACT The paper describes a finite differences Trombe wall model validation, based on experimental data recorded at a passive systems test station in Central Italy. The computer code has been checked step by step, due to the different reliability of the data and to the various algorithms used in the code. Thus, cloudy and clear nights with no thermocirculation were simulated and compared with experimental data, then evening hours with thermocirculation, but no sun and, finally, a full day was simulated and compared. Some inaccuracy has been found in the simulation of wind effect on outer glass convective heat transfer coefficient. The code, however, has been found to provide data in reas…

ConvectionEngineeringSource codebusiness.industrymedia_common.quotation_subjectFinite differenceExperimental dataHeat transfer coefficientMechanicsCode (cryptography)Trombe wallbusinessSimulationReliability (statistics)media_common
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A quasi chemistry-transport model mode for EMAC

2010

Abstract. A quasi chemistry-transport model mode (QCTM) is presented for the numerical chemistry-climate simulation system ECHAM/MESSy Atmospheric Chemistry (EMAC). It allows for a quantification of chemical signals through suppression of any feedback between chemistry and dynamics. Noise would otherwise interfere too strongly. The signal is calculated from the difference of two QCTM simulations, a reference simulation and a sensitivity simulation. In order to avoid the feedbacks, the simulations adopt the following offline chemical fields: (a) offline mixing ratios of radiatively active substances enter the radiation scheme, (b) offline mixing ratios of nitric acid enter the scheme for re-…

ECHAMEMACSource codeQCTMNoise (signal processing)Chemistrymedia_common.quotation_subjectlcsh:QE1-996.5Mode (statistics)Computational physicslcsh:GeologyAtmospheric chemistrySensitivity (control systems)Mixing (physics)SimulationWater vapormedia_common
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Computer-assisted orientation and drawing of archaeological pottery.

2018

Archaeologists spend considerable time orienting and drawing ceramic fragments by hand for documentation, to infer their manufacture, the nature of the discovery site and its chronology, and to develop hypotheses about commercial and cultural exchanges, social organisation, resource exploitation, and taphonomic processes. This study presents a survey of existing solutions to the time-consuming problem of orienting and drawing pottery fragments. Orientation is based on the 3D geometry of pottery models, which can now be acquired in minutes with low-cost 3D scanners. Several methods are presented: they are based on normal vectors, or circle fittings, or profile fittings. All these methods see…

Engineering drawingSource code[SHS.ARCHEO]Humanities and Social Sciences/Archaeology and PrehistoryComputer sciencemedia_common.quotation_subject02 engineering and technologyConservation01 natural sciencesdocumentationRendering (computer graphics)010104 statistics & probabilityDocumentation0202 electrical engineering electronic engineering information engineering3D reconstruction0101 mathematicsComputingMilieux_MISCELLANEOUSmedia_commonSuite3D reconstruction020207 software engineeringComputer Graphics and Computer-Aided Design(semi-)automatic pottery orientationComputer Science ApplicationsWorkflowpottery illustrationArchaeologyAmbient occlusionPotteryInformation Systems
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Automatic Computation of Local Comfort Conditions in Buildings

2000

Publisher Summary A method for the automatic calculation of local comfort conditions in moderate indoor environment is been described in this chapter. It provides, among its output features, graphical maps of the PMV patterns. The program has been implemented on the commonly used operating system, and is characterized by a friendly usability, even by noncomputer expert users. The output of the code can be obtained not only in a graphical way but also in numerical formats. By using the program in conjunction with computer codes that provide the energy demand for climatization of buildings, it would be possible to evaluate the energy savings achieved in correspondence with the various adopted…

EngineeringSource codebusiness.industryComputationmedia_common.quotation_subjectDesign toolUsabilityCode (cryptography)Mean radiant temperaturebusinessEnergy (signal processing)SimulationEnvelope (motion)media_common
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Pattern Recognition Scheme for Large-Scale Cloud Detection over Landmarks

2020

Landmark recognition and matching is a critical step in many Image Navigation and Registration (INR) models for geostationary satellite services, as well as to maintain the geometric quality assessment (GQA) in the instrument data processing chain of Earth observation satellites. Matching the landmark accurately is of paramount relevance, and the process can be strongly impacted by the cloud contamination of a given landmark. This paper introduces a complete pattern recognition methodology able to detect the presence of clouds over landmarks using Meteosat Second Generation (MSG) data. The methodology is based on the ensemble combination of dedicated support vector machines (SVMs) dependent…

FOS: Computer and information sciencesAtmospheric ScienceMatching (statistics)Computer Science - Machine LearningSource code010504 meteorology & atmospheric sciencesComputer scienceComputer Vision and Pattern Recognition (cs.CV)media_common.quotation_subjectMultispectral image0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComputer Science - Computer Vision and Pattern RecognitionCloud computing02 engineering and technology01 natural sciencesMachine Learning (cs.LG)Computers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesmedia_commonLandmarkbusiness.industryPattern recognitionSupport vector machinePattern recognition (psychology)Geostationary orbitArtificial intelligencebusiness
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2014

The majority of next-generation sequencing short-reads can be properly aligned by leading aligners at high speed. However, the alignment quality can still be further improved, since usually not all reads can be correctly aligned to large genomes, such as the human genome, even for simulated data. Moreover, even slight improvements in this area are important but challenging, and usually require significantly more computational endeavor. In this paper, we present CUSHAW3, an open-source parallelized, sensitive and accurate short-read aligner for both base-space and color-space sequences. In this aligner, we have investigated a hybrid seeding approach to improve alignment quality, which incorp…

GeneticsMultidisciplinarySource codeHeuristic (computer science)business.industrymedia_common.quotation_subjectPipeline (computing)Sequence alignmentColor spaceBiologyRanking (information retrieval)SoftwarebusinessAlgorithmAlignment-free sequence analysismedia_commonPLOS ONE
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MetaCache-GPU: Ultra-Fast Metagenomic Classification

2021

The cost of DNA sequencing has dropped exponentially over the past decade, making genomic data accessible to a growing number of scientists. In bioinformatics, localization of short DNA sequences (reads) within large genomic sequences is commonly facilitated by constructing index data structures which allow for efficient querying of substrings. Recent metagenomic classification pipelines annotate reads with taxonomic labels by analyzing their $k$-mer histograms with respect to a reference genome database. CPU-based index construction is often performed in a preprocessing phase due to the relatively high cost of building irregular data structures such as hash maps. However, the rapidly growi…

Genomics (q-bio.GN)FOS: Computer and information sciencesSource codeComputer sciencemedia_common.quotation_subjectHash functionContext (language use)MinHashcomputer.software_genreData structureHash tableComputer Science - Distributed Parallel and Cluster ComputingFOS: Biological sciencesPreprocessorQuantitative Biology - GenomicsDistributed Parallel and Cluster Computing (cs.DC)Data miningcomputermedia_commonReference genome50th International Conference on Parallel Processing
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SimuRed: A flit-level event-driven simulator for multicomputer network performance evaluation

2009

The interconnection network is one of the most important multicomputer components, since it has a great impact on global system performance. Many models and simulators have been proposed to evaluate network performance. This paper presents SimuRed, an event-driven flit-level, cycle-accurate simulator to evaluate different orthogonal network configurations. The core of the simulator has been designed to be expandable and portable to different situations. Some of the advantages of this simulator over other similar tools are its visual interface, its fast execution and its simplicity. Moreover, it is multiplatform and its source code versions (C++ and Java) are freely available under GNU open-…

InterconnectionSource codeGeneral Computer ScienceComputer architecture simulatorJavaComputer scienceEvent (computing)business.industrymedia_common.quotation_subjectControl and Systems EngineeringEmbedded systemNetwork performancePolygon meshHypercubeElectrical and Electronic EngineeringbusinesscomputerSimulationmedia_commoncomputer.programming_languageComputers & Electrical Engineering
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Computer-Aided Detection for Prostate Cancer Detection based on Multi-Parametric Magnetic Resonance Imaging

2017

International audience; Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world. In the last decades, new imaging techniques based on magnetic resonance imaging (MRI) have been developed improving diagnosis. In practice, diagnosis is affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and diagnosis (CAD) systems are being designed to help radiologists in their clinical practice. We propose a CAD system taking advantage of all MRI modalities (i.e., T2-W-MRI, DCE-MRI, diffusion weighted (DW)-MRI, MRSI). The aim of this CAD system was to provide a probabilistic map of cancer…

Malemedicine.medical_specialtySource codemedia_common.quotation_subject[INFO.INFO-IM] Computer Science [cs]/Medical ImagingContrast MediaCAD[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer0302 clinical medicine[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Prostatemedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumans[ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML][SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingmedia_commonMulti parametricModality (human–computer interaction)[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingmedicine.diagnostic_testbusiness.industryProstatic NeoplasmsCancerMagnetic resonance imagingmedicine.diseaseMagnetic Resonance Imaging[STAT.ML] Statistics [stat]/Machine Learning [stat.ML]3. Good healthmedicine.anatomical_structureRadiologybusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing030217 neurology & neurosurgery
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