Search results for "computer.software_genre"

showing 10 items of 3858 documents

Evolution-Oriented User-Centric Data Warehouse

2011

Data warehouses tend to evolve, because of changes in data sources and business requirements of users. All these kinds of changes must be properly handled, therefore, data warehouse development is never-ending process. In this paper we propose the evolution-oriented user-centric data warehouse design, which on the one hand allows to manage data warehouse evolution automatically or semi-automatically, and on the other hand it provides users with the understandable, easy and transparent data analysis possibilities. The proposed approach supports versions of data warehouse schemata and data semantics.

Business requirementsDatabaseComputer scienceProcess (engineering)Data transformationInformationSystems_DATABASEMANAGEMENTDimensional modelingcomputer.software_genrecomputerData warehouseUser-centered designData semantics
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Human-in-the-Loop Conversation Agent for Customer Service

2020

This paper describes a prototype system for partial automation of customer service operations of a mobile telecommunications operator with a human-in-the loop conversational agent. The agent consists of an intent detection system for identifying the types of customer requests that it can handle appropriately, a slot filling information extraction system that integrates with the customer service database for a rule-based treatment of the common scenarios, and a template-based language generation system that builds response candidates that can be approved or amended by customer service operators. The main focus of this paper is on the system architecture and machine learning system structure …

Business requirementsbusiness.industryComputer sciencemedia_common.quotation_subject020206 networking & telecommunications02 engineering and technologycomputer.software_genreAutomationInformation extraction0202 electrical engineering electronic engineering information engineeringSystems architectureHuman-in-the-loop020201 artificial intelligence & image processingConversationMobile telephonyDialog systembusinessSoftware engineeringcomputermedia_common
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MEDLEM database, a data collection on large Elasmobranchs in the Mediterranean and Black seas

2020

The Mediterranean Large Elasmobranchs Monitoring (MEDLEM) database contains more than 3,000 records (with more than 4,000 individuals) of large elasmobranch species from 21 different countries around the Mediterranean and Black seas, observed from 1666 to 2017. The principal species included in the archive are the devil ray (1,868 individuals), the basking shark (935 individuals), the blue shark (622 individuals), and the great white shark (342 individuals). In the last decades, other species such as the thresher shark (187 individuals), the shortfin mako (180 individuals), and the spiny butterfly ray (138) were reported with increasing frequency. This was possibly due to increased public a…

Bycatch; databases; geographical distribution; large elasinobranchs; Mediterranean and Black seas; sharks0106 biological sciencesMediterranean climate2417.05 Biología Marina2510.01 Oceanografía Biológicalarge elasmobranchsMediterranean and Black seascetorhinus-maximus gunnerusOceanographycomputer.software_genre01 natural sciencesBasking sharkPesqueríasThresher shark1st recordsbiologyDatabaseconservationBycatch; databases; geographical distribution; large elasmobranchs; Mediterranean and Black seas; sharks04 agricultural and veterinary sciencescarcharhinidaeGeographyMediterranean and black seacoastbasking sharkLarge elasmobranchcarcharodon-carcharias linnaeusEnvironmental Engineeringdatabases[SDE.MCG]Environmental Sciences/Global ChangesFishingSede Central IEOAquatic Sciencesharksplumbeus chondrichthyesDatabasesharks.biology.animal[SDV.BA.ZV]Life Sciences [q-bio]/Animal biology/Vertebrate Zoologysharks; by-catch; databases; large elasmobranchs; geographical distribution; Mediterranean and Black seasgeographical distributionBycatch ; databases ; geographical distribution ; large elasinobranchs ; Mediterranean and Black seas ; sharks14. Life underwaterEcology Evolution Behavior and Systematicslarge elasinobranchs010604 marine biology & hydrobiologybiology.organism_classificationlamniformes cetorhinidaeby-catchBycatchGreat white sharkBycatchButterfly ray040102 fisheries0401 agriculture forestry and fisheriesConservation status[SDE.BE]Environmental Sciences/Biodiversity and Ecologycomputer
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ImageRover: A Content-Based Image Browser for the World Wide Web

1997

ImageRover is a search-by-image-content navigation tool for the World Wide Web (WWW). To gather images expediently, the image collection subsystem utilizes a distributed fleet of WWW robots running on different computers. The image robots gather information about the images they find, computing the appropriate image decompositions and indices, and store this extracted information in vector form for searches based on image content. At search time, users can iteratively guide the search through the selection of relevant examples. Search performance is made efficient through the use of an approximate, optimized k-d tree algorithm. The system employs a novel relevance feedback algorithm that se…

CBIRInformation retrievalDistributed databasebusiness.industryComputer scienceSearch engine indexingRelevance feedbackcomputer.software_genreWorld Wide WebInformation extractionTree (data structure)RobotThe InternetbusinessImage retrievalcomputer
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Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive Model

2021

Predicting student performance as early as possible and analysing to which extent initial student behaviour could lead to failure or success is critical in introductory programming (CS1) courses, for allowing prompt intervention in a move towards alleviating their high failure rate. However, in CS1 performance prediction, there is a serious lack of studies that interpret the predictive model’s decisions. In this sense, we designed a long-term study using very fine-grained log-data of 2056 students, collected from the first two weeks of CS1 courses. We extract features that measure how students deal with deadlines, how they fix errors, how much time they spend programming, and so forth. Subs…

COMPUTADOR NO ENSINOGeneral Computer ScienceComputer scienceProcess (engineering)business.industryGeneral EngineeringFailure rateMachine learningcomputer.software_genreField (computer science)Identification (information)Black boxLeverage (statistics)General Materials ScienceArtificial intelligencePrescriptive analyticsConstruct (philosophy)businesscomputerIEEE Access
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A Statistical Study to Analyze the Impact of External Weather Change on Chronic Pulmonary Infection in South Norway with Machine Learning Algorithms

2021

In this paper, we analyzed the holistic impact of external weather on chronic pulmonary infection in the Agder region with traditional machine learning algorithms. Millions of people are diagnosed with Chronic Obstructive Pulmonary Disease (COPD). Our study is dedicated in the Agder region, the Southern part of Norway. Norway has four seasons – winter (December-February), late winter/spring (March-May), Summer (June-August), and Autumn (September-November) in a year with average annual temperature approx. 7.5 °C | 45.5 °F and an annual rainfall of 1260 mm or 49.6 in. in Kristiansand. As predicted by the World Health Organization (WHO), in 2016, Norway suffered from 8% mortality due to c(1)h…

COPDbusiness.industryLate winterPulmonary diseasePulmonary infectionLogistic regressionmedicine.diseaseMachine learningcomputer.software_genreWorld healthGeographyAir temperaturemedicineArtificial intelligencebusinessAlgorithmcomputerPrognostic models
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Managing Multi-center Flow Cytometry Data for Immune Monitoring.

2014

With the recent results of promising cancer vaccines and immunotherapy 1 – 5 , immune monitoring has become increasingly relevant for measuring treatment-induced effects on T cells, and an essential tool for shedding light on the mechanisms responsible for a successful treatment. Flow cytometry is the canonical multi-parameter assay for the fine characterization of single cells in solution, and is ubiquitously used in pre-clinical tumor immunology and in cancer immunotherapy trials. Current state-of-the-art polychromatic flow cytometry involves multi-step, multi-reagent assays followed by sample acquisition on sophisticated instruments capable of capturing up to 20 parameters per cell at a…

Cancer ResearchComputer scienceData managementREST APIdata provenancecomputer.software_genrelcsh:RC254-282automated analysisData modelinglaboratory informatics03 medical and health sciences0302 clinical medicineLaboratory informaticsreproducible analysisFlow cytometry030304 developmental biologyOriginal Research0303 health sciencesApplication programming interfacebusiness.industrymetadatalcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogensData scienceAutomationMetadataManagement information systemsOncologyData miningdata managementbusinesscomputer030215 immunologyCommunication channelCancer informatics
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Precision sampling fuels precision oncology: an evolutionary perspective.

2021

Intratumor heterogeneity (ITH) develops in malignant tumors. Precision sampling that captures this tumor variability is essential for the implementation of precision oncology. We highlight the necessity to update current sampling protocols and implement a strategy to ensure ITH detection and characterization. A cost-effective strategy for such sampling has been modeled in clear cell renal cell carcinoma (CCRCC).

Cancer ResearchComputer sciencePerspective (graphical)Sampling (statistics)medicine.diseasecomputer.software_genreBiological EvolutionKidney NeoplasmsClear cell renal cell carcinomaOncologyIntratumor heterogeneityPrecision oncologymedicineHumansData miningPrecision MedicinecomputerCarcinoma Renal CellTrends in cancer
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Fuzzy subgroup mining for gene associations

2004

When studying the therapeutic efficacy of potential new drugs, it would be much more efficient to use predictors in order to assess their toxicity before going into clinical trials. One promising line of research has focused on the discovery of sets of candidate gene profiles to be used as toxicity indicators in future drug development. In particular genomic microarrays may be used to analyze the causality relationship between the administration of the drugs and the so-called gene expression, a parameter typically used by biologists to measure its influence at gene level. This kind of experiments involves a high throughput analysis of noisy and particularly unreliable data, which makes the …

Candidate geneApriori algorithmMeasure (data warehouse)Fuzzy control systemBiologycomputer.software_genreCausalityFuzzy logicComputingMethodologies_PATTERNRECOGNITIONDrug developmentData miningddc:004Throughput (business)computer
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Gene Set to Diseases (GS2D): disease enrichment analysis on human gene sets with literature data

2016

Large sets of candidate genes derived from high-throughput biological experiments can be characterized by functional enrichment analysis. The analysis consists of comparing the functions of one gene set against that of a background gene set. Then, functions related to a significant number of genes in the gene set are expected to be relevant. Web tools offering disease enrichment analysis on gene sets are often based on gene-disease associations from manually curated or experimental data that is accurate but does not cover all diseases discussed in the literature. Using associations automatically derived from literature data could be a cost effective method to improve the coverage of disease…

Candidate genebusiness.industryBig dataExperimental dataGenomicsBiologycomputer.software_genreSet (abstract data type)WorkflowData miningToxicogenomicsbusinesscomputerGeneGenomics and Computational Biology
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