Дисертації з теми "Data Importance"
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Törnqvist, Christian. "Evaluating the Importance of Disk-locality for Data Analytics Workloads : Evaluating the Importance of Disk-locality for Data Analytics Workloads." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-410212.
Повний текст джерелаStephens, Joshua J. "Data Governance Importance and Effectiveness| Health System Employee Perception." Thesis, Central Michigan University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10751061.
Повний текст джерелаThe focus of this study was to understand how health system employees define Data Governance (DG), how they perceive its importance and effectiveness to their role and how it may impact strategic outcomes of the organization. Having a better understanding of employee perceptions will help identify areas of education, process improvement and opportunities for more structured data governance within the healthcare industry. Additionally, understanding how employees associate each of these domains to strategic outcomes, will help inform decision-makers on how best to align the Data Governance strategy with that of the organization.
This research is intended to expand the data governance community’s knowledge about how health system employee demographics influence their perceptions of Data Governance. Very little academic research has been done to-date, which is unfortunate given the value of employee engagement to an organization’s culture juxtaposed to the intent of Data Governance to change that culture into one that fully realizes the value of its data and treats it as a corporate asset. This lack of understanding leads to two distinct problems: executive resistance toward starting a Data Governance Program due to the lack of association between organizational strategic outcomes and Data Governance, and employee, or cultural, resistance to the change Data Governance brings to employee roles and processes.
The dataset for this research was provided by a large mid-west health system’s Enterprise Data Governance Program and was collected internally through an electronic survey. A mixed methods approach was taken. The first analysis intended to see how employees varied in their understanding of the definition of data governance as represented by the Data Management Association’s DAMA Wheel. The last three research questions focused on determining which factors influence a health system employee’s perception of the importance, effectiveness, and impact Data Governance has on their role and on the organization.
Perceptions on the definition of Data Governance varied slightly for Gender, Management Role, IT Role, and Role Tenure, and the thematic analysis identified a lack of understanding of Data Governance by health system employees. Perceptions of Data Governance importance and effectiveness varied by participants’ gender, and organizational role as part of analytics, IT, and Management. In general, employees perceive a deficit of data governance to their role based on their perceptions of importance and effectiveness. Lastly, employee perceptions of the impact of Data Governance on strategic outcomes varied among participants by gender for Cost of Care and by Analytics Role for Quality of Analytics. For both Quality of Care and Patient Experience, perceptions did not vary.
Perceptions related to the impact of Data Governance on strategic outcomes found that Data Quality Management was most impactful to all four strategic outcomes included in the study: quality of care, cost of care, patient experience, and quality of analytics. Leveraging the results of this study to tailor communication, education and training, and roles and responsibilities required for a successful implementation of Data Governance in healthcare should be considered by DG practitioners and executive leadership implementing or evaluating a DG Program within a healthcare organization. Additionally, understanding employee perceptions of Data Governance and their impact to strategic outcomes will provide meaningful insight to executive leadership who have difficulty connecting the cost of Data Governance to the value realization, which is moving the organization closer to achieving the Triple Aim by benefiting from their data.
Bordoloi, Udeepta Dutta. "Importance-driven algorithms for scientific visualization." Connect to this title online, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1118952958.
Повний текст джерелаTitle from first page of PDF file. Document formatted into pages; contains xiv, 126 p.; also includes graphics. Includes bibliographical references (p. 119-126). Available online via OhioLINK's ETD Center
Northrop, Amanda Rosalind. "Importance of various data sources in deterministic stock assessment models." Thesis, Rhodes University, 2008. http://hdl.handle.net/10962/d1002811.
Повний текст джерелаWan, Shuyan. "Likelihood-based procedures for obtaining confidence intervals of disease Loci with general pedigree data." The Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=osu1164815591.
Повний текст джерелаMatthäus, Antje, and Markus Dammers. "Computational underground short-term mine planning: the importance of real-time data." Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2018. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-231345.
Повний текст джерелаMafu, Thandile John. "Modelling of multi-state panel data : the importance of the model assumptions." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95994.
Повний текст джерелаENGLISH ABSTRACT: A multi-state model is a way of describing a process in which a subject moves through a series of states in continuous time. The series of states might be the measurement of a disease for example in state 1 we might have subjects that are free from disease, in state 2 we might have subjects that have a disease but the disease is mild, in state 3 we might have subjects having a severe disease and in last state 4 we have those that die because of the disease. So Markov models estimates the transition probabilities and transition intensity rates that describe the movement of subjects between these states. The transition might be for example a particular subject or patient might be slightly sick at age 30 but after 5 years he or she might be worse. So Markov model will estimate what probability will be for that patient for moving from state 2 to state 3. Markov multi-state models were studied in this thesis with the view of assessing the Markov models assumptions such as homogeneity of the transition rates through time, homogeneity of the transition rates across the subject population and Markov property or assumption. The assessments of these assumptions were based on simulated panel or longitudinal dataset which was simulated using the R package named msm package developed by Christopher Jackson (2014). The R code that was written using this package is attached as appendix. Longitudinal dataset consists of repeated measurements of the state of a subject and the time between observations. The period of time with observations in longitudinal dataset is being made on subject at regular or irregular time intervals until the subject dies then the study ends.
AFRIKAANSE OPSOMMING: ’n Meertoestandmodel is ’n manier om ’n proses te beskryf waarin ’n subjek in ’n ononderbroke tydperk deur verskeie toestande beweeg. Die verskillende toestande kan byvoorbeeld vir die meting van siekte gebruik word, waar toestand 1 uit gesonde subjekte bestaan, toestand 2 uit subjekte wat siek is, dog slegs matig, toestand 3 uit subjekte wat ernstig siek is, en toestand 4 uit subjekte wat aan die siekte sterf. ’n Markov-model raam die oorgangswaarskynlikhede en -intensiteit wat die subjekte se vordering deur hierdie toestande beskryf. Die oorgang is byvoorbeeld wanneer ’n bepaalde subjek of pasiënt op 30-jarige ouderdom net lig aangetas is, maar na vyf jaar veel ernstiger siek is. Die Markov-model raam dus die waarskynlikheid dat so ’n pasiënt van toestand 2 tot toestand 3 sal vorder. Hierdie tesis het ondersoek ingestel na Markov-meertoestandmodelle ten einde die aannames van die modelle, soos die homogeniteit van oorgangstempo’s oor tyd, die homogeniteit van oorgangstempo’s oor die subjekpopulasie en tipiese Markov-eienskappe, te beoordeel. Die beoordeling van hierdie aannames was gegrond op ’n gesimuleerde paneel of longitudinale datastel wat met behulp van Christopher Jackson (2014) se R-pakket genaamd msm gesimuleer is. Die R-kode wat met behulp van hierdie pakket geskryf is, word as bylae aangeheg. Die longitudinale datastel bestaan uit herhaalde metings van die toestand waarin ’n subjek verkeer en die tydsverloop tussen waarnemings. Waarnemings van die longitudinale datastel word met gereelde of ongereelde tussenposes onderneem totdat die subjek sterf, wanneer die studie dan ook ten einde loop.
Matthäus, Antje, and Markus Dammers. "Computational underground short-term mine planning: the importance of real-time data." TU Bergakademie Freiberg, 2017. https://tubaf.qucosa.de/id/qucosa%3A23194.
Повний текст джерелаKaponen, Martina. "Fairness and parameter importance in logistic regression models of criminal sentencing data." Thesis, Uppsala universitet, Tillämpad matematik och statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-417359.
Повний текст джерелаNalini, Ramakrishna Sindhu Kanya. "Component importance indices and failure prevention using outage data in distribution systems." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-287173.
Повний текст джерелаAvbrott i strömförsörjningen är oundvikliga på grund av fel i distributionsnätet för kraftsystemet. Dessa avbrott är inte bara dyra för kunderna utan också för distributionssystemoperatören i form av påföljder. Ökad systemredundans eller användning av komponentspecifika sensorer kan hjälpa till att minska avbrott. Dessa alternativ är dock inte alltid ekonomiskt genomförbara. Därför är det nödvändigt att kontrollera om det finns andra möjligheter för att minska risken för avbrott. Data lagrade i transformatorstationer kan användas för att minska risken för avbrott genom att härleda komponentviktindex följt av rangordning och förutsäga avbrott. I denna avhandling härleds viktighetsindex genom att identifiera de kritiska komponenterna i nätet och tilldela index baserat på vissa kriterier. Felprognoserna gjordes baserat på de väderförhållanden som observerades under avbrott. komponentviktighetsindex härleds och rankas baserat på komponenternas urladdningstid, frekvens och påverkan av avbrott. Detta hjälper till att prioritera komponenter enligt det valda kriteriet och anpassa övervakningsstrategier genom att fokusera på de mest kritiska komponenterna. Baserat på kategoriska Naive Bayes utvecklas en modell för att förutsäga sannolikheten för fel / fel, plats och komponenttyp som sannolikt kommer att påverkas under en viss uppsättning väderförhållanden. Resultaten från komponentviktighetsindexen visar att varje komponents rang varierar beroende på det valda kriteriet. Vissa komponenter rankas dock högt i alla metoder. Dessa komponenter är kritiska och behöver fokuserad övervakning. Tillförlitligheten hos resultat från komponentviktindex beror till stor del på tidsramen för avbrottsdata som beaktas för analys. Prognosmodellen kan varna distributionssystemoperatören om möjliga avbrott i nätverket för en viss uppsättning väderförhållanden. Förutsägelsen av plats och komponenttyp som sannolikt kommer att påverkas är dock relativt felaktig, eftersom antalet avbrott som beaktas i tidsramen är lågt. Genom att uppdatera modellen regelbundet med nya data skulle förutsägelserna vara mer exakta.
Williams, Rachel L. "The importance and effectiveness of volunteer-collected data in ecology and conservation." Thesis, University of Gloucestershire, 2012. http://eprints.glos.ac.uk/2459/.
Повний текст джерелаFang, Tongtong. "Learning from noisy labelsby importance reweighting: : a deep learning approach." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264125.
Повний текст джерелаFelaktiga annoteringar kan sänka klassificeringsprestanda.Speciellt för djupa nätverk kan detta leda till dålig generalisering. Nyligen har brusrobust djup inlärning överträffat andra inlärningsmetoder när det gäller hantering av komplexa indata Befintligta resultat från djup inlärning kan dock inte tillhandahålla rimliga viktomfördelningskriterier. För att hantera detta kunskapsgap och inspirerat av domänanpassning föreslår vi en ny robust djup inlärningsmetod som använder omviktning. Omviktningen görs genom att minimera den maximala medelavvikelsen mellan förlustfördelningen av felmärkta och korrekt märkta data. I experiment slår den föreslagna metoden andra metoder. Resultaten visar en stor forskningspotential för att tillämpa domänanpassning. Dessutom motiverar den föreslagna metoden undersökningar av andra intressanta problem inom domänanpassning genom att möjliggöra smarta omviktningar.
王達才 and Tat-choi Wong. "The strategic importance of information systems to airline revenue management." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B31266873.
Повний текст джерелаHjerpe, Adam. "Computing Random Forests Variable Importance Measures (VIM) on Mixed Numerical and Categorical Data." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-185496.
Повний текст джерелаRandom Forest (RF) är en populär prediktormodell som visat goda resultat vid en stor uppsättning applikationsstudier. Modellen ger hög prediktionsprecision, har förmåga att modellera komplex högdimensionell data och modellen har vidare visat goda resultat vid interkorrelerade prediktorvariabler. Detta projekt undersöker ett mått, variabel importance measure (VIM) erhållna från RF modellen, för att beräkna graden av association mellan prediktorvariabler och målvariabeln. Projektet undersöker känsligheten hos VIM vid kvalitativt prediktorbrus och undersöker VIMs förmåga att differentiera prediktiva variabler från variabler som endast, med aveende på målvariableln, beskriver brus. Att differentiera prediktiva variabler vid övervakad inlärning kan användas till att öka robustheten hos klassificerare, öka prediktionsprecisionen, reducera data dimensionalitet och VIM kan användas som ett verktyg för att utforska relationer mellan prediktorvariabler och målvariablel.
Xu, Yan. "Using data to answer questions of public health importance for ACT Health, with an emphasis on routinely-collected linked data." Master's thesis, Canberra, ACT : The Australian National University, 2017. http://hdl.handle.net/1885/144601.
Повний текст джерела梁南柱 and Nam-chu Alexander Leung. "The strategic importance of information system/technology to the Hong Kong Polytechnic University." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B31266708.
Повний текст джерелаReibold, Florian [Verfasser], and C. [Akademischer Betreuer] Dachsbacher. "Data-driven global importance sampling for physically-based rendering / Florian Reibold ; Betreuer: C. Dachsbacher." Karlsruhe : KIT-Bibliothek, 2021. http://d-nb.info/1228439281/34.
Повний текст джерелаFaronius, Hofmann Therese, and Linda Håkansson. "Visualization Design Effects on Credibility and Data Perception, and the Importance of Digital Interaction." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-453694.
Повний текст джерелаEn graf kan ge insikt i data som annars är svår att analysera. It-företaget Assedons mål är att konvertera data till digitala interaktiva lösningar som gör data förståelig för deras klienter. Målet med denna studie var att skapa en interaktiv visuell representation av Arbetsförmedlingens data i ett användarvänligt gränssnitt. Detta gjordes genom att skapa digitala grafer som anses trovärdiga och fördelaktiga för datauppfattningen. Målet var även att undersöka hur datauppfattningen av digitala grafer påverkades av interaktion med dessa grafer. Studien utfördes genom att intervjua 19 personer från olika bakgrunder med användning av kvalitativa och kvantitativa intervjutekniker. Deltagarna i studien visades tre olika interaktiva designer av en graf typ och betygsatte dessa samt kommenterade. Resultaten visade att en digital graf är mer sannolik att uppfattas som trovärdig om den ser modern och professionell ut. Datauppfattningen påverkades av flera faktorer, främst färgvalen som kan förtydliga data, men även förvirra läsaren. Avslutningsvis, så kan interaktion erbjuda en ytterligare dimension till grafer och därmed förbättra förståelsen av data. Dock till en viss gräns, är grafen för svår att evaluera utan tillgång till interaktionen så förloras syftet med grafen och interaktionen blir en nödvändighet istället för en tillgång.
Lindmark, Jessica. "Betydelse av datakvalitet vid modellering av grundvatten : The Importance of Data Quality in Groundwater Modelling." Thesis, Uppsala universitet, Luft-, vatten och landskapslära, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-260204.
Повний текст джерелаFritz, Eric Ryan. "Relational database models and other software and their importance in data analysis, storage, and communication." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1468081.
Повний текст джерелаLeung, Kwok-wing, and 梁國榮. "The strategic importance of information systems in the electricity supply industry in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B31266691.
Повний текст джерелаNybacka, A. (Aino). "The role of consumers’ knowledge and attitudes in determining the importance of privacy in big data marketing." Master's thesis, University of Oulu, 2018. http://urn.fi/URN:NBN:fi:oulu-201806062496.
Повний текст джерелаLai, Kam-hung Jimmy, and 黎錦鴻. "The strategic importance of information technology (IT) to the credit card business of a local banking group." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B3126721X.
Повний текст джерелаKimes, Ryan Vincent. "Quantifying the Effects of Correlated Covariates on Variable Importance Estimates from Random Forests." VCU Scholars Compass, 2006. http://scholarscompass.vcu.edu/etd/1433.
Повний текст джерелаDoubleday, Kevin. "Generation of Individualized Treatment Decision Tree Algorithm with Application to Randomized Control Trials and Electronic Medical Record Data." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/613559.
Повний текст джерелаJankovsky, Zachary Kyle. "Development of Computational and Data Processing Tools for ADAPT to Assist Dynamic Probabilistic Risk Assessment." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524194454292866.
Повний текст джерелаTwum, Amoako Benjamin. "The importance of Business Intelligence as a decision-making tool : case study electricity company of Ghana (E.C.G)." Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-17652.
Повний текст джерелаProgram: Masterutbildning i Informatik
Lubanski, Adam Roman. "Returns to the delivery and support of information services for academic research and learning : the importance of data and information support." Thesis, University College London (University of London), 1999. http://discovery.ucl.ac.uk/10019785/.
Повний текст джерелаGORDOS, PYGMALION-ALEXANDROS, and JONAS BULOVAS. "The importance of supplier information quality in purchasing of transport services." Thesis, KTH, Industriell Marknadsföring och Entreprenörskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-236510.
Повний текст джерелаEn viktig förutsättning för framgångsrik integration av leverantörskedjor ligger i förmågan att omvandla data till information, kombinerat med en strukturerad lagrings- och delningsprocess. Syftet med denna masteruppsats är att undersöka potentiell relation mellan leverantörers datakvalitet och hur effektivt inköpet av transporttjänsterna är. Utfallet av uppsatsen understryker vikten av att beakta leverantörers datakvalitet i alla delar av en upphandling. Som produkt av denna uppsats har en utvärderingsmall för leverantörers datakvalitet utvecklats. Den består av fyra dimensioner – Hanterbarhet, tillgänglighet, noggrannhet samt fullständighet. De olika dimensionerna är viktade specifikt för det studerade företaget – Cramo, för att fastslå kvalitetsindex för ett urval av deras transportörer. En koefficient - k1- infördes för att representera förhållandet mellan transportkostnad och försäljning. Detta för att underlätta identifieringen av potentiell relation mellan datakvalitet och transportkostnad. Depåer vars transportörer kunde uppvisa en högre datakvalitet hade ett lägre koefficientvärde (k1). Alltså fanns ett samband mellan hög datakvalitet och lägre transportkostnad i förhållande till försäljning. Den utvecklade bedömningsmallen är anpassningsbar – dimensioner och mått kan enkelt adderas eller elimineras utifrån rådande omständigheter i varje fall. Bedömningsmallen ger möjlighet till en mer objektiv och harmoniserad leverantörsbedömning. Mallen understryker även vikten av att beakta den totala kostnaden under avtalstiden. Kunskapen från denna uppsats kring vikten av datakvalitet gällande just transportinköp kan även generaliseras till andra fall där företag strävar mot bättre informerade strategiska beslut.
Ladieu, François. "Importance des fluctuations spatio-temporelles et des non linéarités pour le transport dans les verres isolants." Habilitation à diriger des recherches, Université Paris Sud - Paris XI, 2003. http://tel.archives-ouvertes.fr/tel-00003424.
Повний текст джерелаTang, Han, and Han Tang. "The Importance of Prior Geologic Information on Hydraulic Tomography Analysis at the North Campus Research Site (NCRS)." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/621836.
Повний текст джерелаTaylor, La'Shan Denise. "Assessing Health Status, Disease Burden, and Quality of Life in Appalachia Tennessee: The Importance of Using Multiple Data Sources in Health Research." Digital Commons @ East Tennessee State University, 2009. https://dc.etsu.edu/etd/1889.
Повний текст джерелаSaunders, Gary University of Ballarat. "Pharmacovigilance Decision Support: The value of Disproportionality Analysis Signal Detection Methods, the development and testing of Covariability Techniques, and the importance of Ontology." University of Ballarat, 2006. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12755.
Повний текст джерелаDoctor of Philosophy
Saunders, Gary. "Pharmacovigilance Decision Support: The value of Disproportionality Analysis Signal Detection Methods, the development and testing of Covariability Techniques, and the importance of Ontology." University of Ballarat, 2006. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15382.
Повний текст джерелаDoctor of Philosophy
Posey, Orlando Guy. "Client/Server Systems Performance Evaluation Measures Use and Importance: a Multi-Site Case Study of Traditional Performance Measures Applied to the Client/Server Environment." Thesis, University of North Texas, 1999. https://digital.library.unt.edu/ark:/67531/metadc277882/.
Повний текст джерелаLangham, J. "The importance of data quality and risk assessment in developing measures of comparative outcome : the National Study of Subarachnoid Haemorrhage, a case study." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549778.
Повний текст джерелаFortuin, Mildred. "A geographic information systems approach to the identification of Table Mountain group aquifer "type areas" of ecological importance." Thesis, University of the Western Cape, 2004. http://etd.uwc.ac.za/index.php?module=etd&.
Повний текст джерелаtype areas"
for further detailed research into the impacts of large-scale groundwater abstraction from the Table Mountain group aquifer system based on the nature and functioning of ecosystems across groundwater dependent ecosystem boundaries of a regional scale.
Roxbergh, Linus. "Language Classification of Music Using Metadata." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-379625.
Повний текст джерелаSternberg, Sebastian [Verfasser], and Thomas [Akademischer Betreuer] Gschwend. "No public, no power? Analyzing the importance of public support for constitutional review with novel data and machine learning methods / Sebastian Sternberg ; Betreuer: Thomas Gschwend." Mannheim : Universitätsbibliothek Mannheim, 2019. http://d-nb.info/1196009902/34.
Повний текст джерелаBoland, Paul William. "Morphometric analysis of data inherent in examination by magnetic resonance imaging : importance to natural history, prognosis and disease staging of squamous carcinoma of the oral cavity." Thesis, University of Oxford, 2010. http://ora.ox.ac.uk/objects/uuid:934e1e5a-24db-40ab-ab54-5e58901a9c2a.
Повний текст джерелаRudelius, Johan, and Erik Zetterström. "The importance of data when training a CNN for medical diagnostics : A study of how dataset size and format affects the learning process of a CNN." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280355.
Повний текст джерелаSedan CAD utvecklades under mitten av 1950-talet har det har blivit allt mer populärt att utnyttja den beräkningskapacitet som moderna datorer tillför inom det medicinska området. Att hudcancer är så vanligt förekommande ledde till att en grupp av forskare från Stanford år 2017 tränade ett CNN som kunde prestera bättre än certifierade hudläkare i flera klassifikationstester av hudcancer. Stanfordstudien gav upphov till en studie av Boman och Volminger som försökte replikera resultaten med offentligt tillgängliga data. Men de lyckades inte uppnå samma prestanda. Syftet med denna studie var inledningsvis att bygga på Boman och Volmingers arbete. Men på grund av att en stor del av den träningsdata som de använde var otillgänglig så var jämförelser svåra att göra och fokus skiftades därmed till att förändra andra delar av metoden. Modellerna i detta arbete uppnådde en 3-vägs- klassifikationsträffsäkerhet på 82,2% och 87,3% för den balanserade modellen respektive den obalanserade modellen. Den balanserade modellen tränades på en uppsättning data som slumpmässigt över- och undersamplats för att göra klasserna lika stora. Detta resulterade i bättre genomsnittlig sensitivitet och specificitet på bekostnad av en relativt liten förlust i klassifikationsträffsäkerhet. Trots att klassifikationsträffsäkerheten var bättre för dessa modeller än den från Boman och Volmingers arbete, så är det svårt att dra några slutsatser eftersom metodiken i detta arbete avvek från den tidigare studien.
Elmsjö, Albert. "Selectivity in NMR and LC-MS Metabolomics : The Importance of Sample Preparation and Separation, and how to Measure Selectivity in LC-MS Metabolomics." Doctoral thesis, Uppsala universitet, Avdelningen för analytisk farmaceutisk kemi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-318296.
Повний текст джерелаRéau, Manon. "Importance des données inactives dans les modèles : application aux méthodes de criblage virtuel en santé humaine et environnementale." Thesis, Paris, CNAM, 2019. http://www.theses.fr/2019CNAM1251/document.
Повний текст джерелаVirtual screening is widely used in early stages of drug discovery and to build toxicity prediction models. Commonly used protocols include an evaluation of the performances of different tools on benchmarking databases before applying them for prospective studies. The content of benchmarking tools is a critical point; most benchmarking databases oppose active data to putative inactive due to the scarcity of published inactive data in the literature. Nonetheless, experimentally validated inactive data also bring information. Therefore, we constructed the NR-DBIND, a database dedicated to nuclear receptors that contains solely experimentally validated active and inactive data. The importance of the integration of inactive data in docking and pharmacophore models construction was evaluated using the NR-DBIND data. Virtual screening protocols were used to resolve the potential binding mode of small molecules on FXR, NRP-1 et TNF⍺
Pirathiban, Ramethaa. "Improving species distribution modelling: Selecting absences and eliciting variable usefulness for input into standard algorithms or a Bayesian hierarchical meta-factor model." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/134401/1/Ramethaa_Pirathiban_Thesis.pdf.
Повний текст джерелаTavakkoli, Timon-Amir [Verfasser], Sohrab [Akademischer Betreuer] [Gutachter] Fratz, Peter [Gutachter] Ewert, and Alfred [Gutachter] Hager. "Importance of Hemodynamic Right and Left Ventricular Parameters and CPET-Data in Fallot-Patients and Patients with Fallot-like Pathologies / Timon-Amir Tavakkoli ; Gutachter: Peter Ewert, Sohrab Fratz, Alfred Hager ; Betreuer: Sohrab Fratz." München : Universitätsbibliothek der TU München, 2016. http://d-nb.info/1114393940/34.
Повний текст джерелаCarneiro, Murillo Guimarães. "Redes complexas para classificação de dados via conformidade de padrão, caracterização de importância e otimização estrutural." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-01022017-100223/.
Повний текст джерелаData classification is a machine learning and data mining task in which a classifier is trained over a set of labeled data instances in such a way that the labels of new instances can be predicted. Traditionally, classification techniques define decision boundaries in the data space according to the physical features of a training set and a new data item is classified by verifying its relative position to the boundaries. Such kind of classification, which is only based on the physical attributes of the data, makes traditional techniques unable to detect semantic relationship existing among the data such as the pattern formation, for instance. On the other hand, recent works have shown the use of complex networks is a promissing way to capture spatial, topological and functional relationships of the data, as the network representation unifies structure, dynamic and functions of the networked system. In this thesis, the main objective is the development of methods and heuristics based on complex networks for data classification. The main contributions comprise the concepts of pattern conformation, data importance and network structural optimization. For pattern conformation, in which complex networks are employed to estimate the membership of a test item according to the data formation pattern, we present, in this thesis, a simple hybrid technique where physical and topological associations are produced from the same network. For data importance, we present a technique which considers the individual importance of the data items in order to determine the label of a given test item. The concept of importance here is derived from PageRank formulation, the ranking measure behind the Googles search engine used to calculate the importance of webpages. For network structural optimization, we present a bioinspired framework, which is able to build up the network while optimizing a task-oriented quality function such as classification, dimension reduction, etc. The last investigation presented in this thesis exploits the graph representation and its hability to detect classes of arbitrary distributions for the task of semantic role diffusion. In all investigations, a wide range of experiments in artificial and real-world data sets, and many comparisons with well-known and widely used techniques are also presented. In summary, the experimental results reveal that the advantages and new concepts provided by the use of networks represent relevant contributions to the areas of classification, learning systems and complex networks.
Goble, Peter. "Maximizing the utility of available root zone soil moisture data for drought monitoring purposes in the Upper Colorado River Basin and western High Plains, and assessing the interregional importance of root zone soil moisture on warm season water." Thesis, Colorado State University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10139009.
Повний текст джерелаRoot Zone Soil Moisture (RZSM) data have both drought monitoring and seasonal forecasting applications. It is the lifeblood of vegetation, an integral component of the hydrologic system, a determining factor in irrigation requirements, and works to govern the means by which energy imbalances are settled between land and atmosphere. The National Integrated Drought Information System (NIDIS) has worked in conjunction with the Colorado Climate Center to improve regional drought early warning through enhanced monitoring and understanding of RZSM. The chief goals of this research have been as follows: 1. Examine regional drought monitoring in the Upper Colorado River Basin and eastern Colorado with specific inquiry as to soil moisture’s role in the process. 2. Develop operational products that can be used to improve the weekly drought monitoring process in the Upper Colorado River Basin and eastern Colorado with an emphasis on utilization of soil moisture data. 3. Review in-situ soil moisture data from high elevation Snow Telemetry measurement sites in Colorado in order to understand the descriptive climatology of soil moisture over the Colorado Rockies. 4. Compare output from soil sensors installed by the Snow Telemetry and Colorado Agricultural Meteorological Network using current calibration methods in order to better understand application of direct comparison between output from the two different sensor types. Engineer a soil moisture core measurement protocol that is reliable within ten percent of the true volumetric water content value. This protocol, if successful on a local plot, will be expanded to alpha testers around the United States and used by the USDA for drought monitoring as well as NASA for ground validation of the Soil Moisture Active Passive (SMAP) Satellite. 5. Expose the seasonality and spatial variability of positive feedbacks that occur between RZSM and the atmosphere across the Upper Colorado River Basin and western High Plains using reanalysis data from the North American Land Data Assimilation System Phase-2 (NLDAS).
Regional drought monitoring was found to involve assimilation of data from a bevy of sources. The decision-making process includes assessment of precipitation, soil moisture, snowpack, vegetative health, streamflow, reservoir levels, reference evapotranspiration, surface air temperature, and ground reports from the regional agricultural sector. Drought monitoring was expanded upon in this research through the development of several products intended for future Colorado Climate Center use. In-situ soil moisture timeseries are now being created from select SNOTEL and SCAN measurement sites. Reservoir monitoring graphics are being produced to accompany spatial analyses downloaded from the bureau of reclamation. More soil moisture data is being used, and now come from an ensemble of models rather than just the VIC model.
While only ten years of data were collected in analyzing the descriptive soil moisture climatology of the Colorado Rockies, these data were telling in terms of the expected seasonal cycle of soil moisture at high elevations. SNOTEL measurements reveal that soil moisture levels peak prior to snowmelt, large decreases in soil moisture are expected in June and early July, a slight recovery is anticipated in association with the North American Monsoon, and the sign of near-surface water balance flips back to positive in the first two weeks of September before soils freeze. Seasonal variance and distribution of volumetric water content varies in ways that are useful to understand from a drought monitoring standpoint. The data show that measurements are affected when soil freezes.
Comparing output from soil sensor relays using sensor types and calibration methods consistent with current SNOTEL and CoAgMet specifications revealed large differences in output regardless of being subject to the same meteorologic conditions.
Soil moisture measurement protocol development proved to be a trial and error process. The data collected at Christman Field was not sufficient proof that soil coring results did come within ten percent of ground truth perhaps due to microscale variations in infiltration. It was possible to develop a protocol of an acceptable standard that could be followed by citizen scientist for an estimated cost of $50.
Results from statistical modeling of post-processed NLDAS data from the last 30 years point primarily to a time frame between May and July in which soil moisture anomalies become significantly correlated with seasonal temperature and precipitation anomalies. This time of year is partially characterized by a climatologic maximization of downwelling solar radiation and a northward recession of the polar jet, but also precedes the anticipated arrival of the North American Monsoon. (Abstract shortened by ProQuest.)
West, Adam. "Hunting for humans in forest ecosystems : are the traces of Iron-age people detectable? : an investigation into the importance of Iron-age slash-an-burn agriculture in KwaZulu-Natal forests using compositional and demographic data and carbon isotope techniques." Master's thesis, University of Cape Town, 1999. http://hdl.handle.net/11427/23678.
Повний текст джерелаAlet, Ferran (Alet I. Puig). "Finding important entities in continuous streaming data." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118027.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (pages 65-67).
In many applications that involve processing high-dimensional data, it is important to identify a small set of entities that account for a significant fraction of detections. Rather than formalize this as a clustering problem, in which all detections must be grouped into hard or soft categories, we formalize it as an instance of the frequent items or heavy hitters problem, which finds groups of tightly clustered objects that have a high density in the feature space. We show that the heavy hitters formulation generates solutions that are more accurate and effective than the clustering formulation. In addition, we present a novel online algorithm for heavy hitters, called HAC, which addresses problems in continuous space, and demonstrate its effectiveness on real video and household domains.
by Ferran Alet.
S.M.
Korkmaz, Gulberal Kircicegi Yoksul. "Mining Microarray Data For Biologically Important Gene Sets." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614266/index.pdf.
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