Готові списки джерел за темами / Data with gaps

Добірка наукової літератури з теми "Data with gaps"

Автор: Grafiati
Опубліковано: 30 травня 2022
Оновлено: 31 травня 2022

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Статті в журналах з теми "Data with gaps"

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Zielinski, Sarah. "Filling gaps in ecosystem data." Eos, Transactions American Geophysical Union 87, no. 26 (2006): 254. http://dx.doi.org/10.1029/2006eo260004.

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Aldhous, Peter. "Gaps loom in satellite data." Nature 355, no. 6362 (February 1992): 662. http://dx.doi.org/10.1038/355662a0.

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Pearman, Francis A., F. Chris Curran, Benjamin Fisher, and Joseph Gardella. "Are Achievement Gaps Related to Discipline Gaps? Evidence From National Data." AERA Open 5, no. 4 (October 2019): 233285841987544. http://dx.doi.org/10.1177/2332858419875440.

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There is growing interest in the relation between the racial achievement gap and the racial discipline gap. However, few studies have examined this relation at the national level. This study combines data from the Stanford Education Data Archive and the Civil Rights Data Collection and employs a district fixed effects analysis to examine whether and the extent to which racial discipline gaps are related to racial achievement gaps in Grades 3 through 8 in districts across the United States. In bivariate models, we find evidence that districts with larger racial discipline gaps have larger racial achievement gaps (and vice versa). Though other district-level differences account for the positive association between the Hispanic-White discipline gap and the Hispanic-White achievement gap, we find robust evidence that the positive association between the Black-White discipline gap and the Black-White achievement gap persists after controlling for a multitude of confounding factors. We also find evidence that the mechanisms connecting achievement to disciplinary outcomes are more salient for Black than White students.
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Shroff, Sangeeta. "Data Gaps in Agricultural Statistics:Some Issues." Artha Vijnana: Journal of The Gokhale Institute of Politics and Economics 58, no. 3 (September 1, 2016): 228. http://dx.doi.org/10.21648/arthavij/2016/v58/i3/147827.

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Cameron, Erin K., Inês S. Martins, Patrick Lavelle, Jérôme Mathieu, Leho Tedersoo, Felix Gottschall, Carlos A. Guerra, et al. "Global gaps in soil biodiversity data." Nature Ecology & Evolution 2, no. 7 (June 4, 2018): 1042–43. http://dx.doi.org/10.1038/s41559-018-0573-8.

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SCHNEIDER, MARY ELLEN. "Decoding Care Transitions Despite Data Gaps." Hospitalist News 5, no. 4 (April 2012): 3. http://dx.doi.org/10.1016/s1875-9122(12)70080-9.

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Gilbert, Natasha. "Data gaps threaten chemical safety law." Nature 475, no. 7355 (July 2011): 150–51. http://dx.doi.org/10.1038/475150a.

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Golbus, Jessica R., W. Nicholson Price, and Brahmajee K. Nallamothu. "Privacy Gaps for Digital Cardiology Data." Circulation 141, no. 8 (February 25, 2020): 613–15. http://dx.doi.org/10.1161/circulationaha.119.044966.

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Marqués, José Manuel, Fernando Ávila, Anahí Rodríguez-Martínez, Raúl Morales-Reséndiz, Antonio Marcos, Tamara Godoy, Pablo Villalobos, et al. "Policy report on FinTech data gaps." Latin American Journal of Central Banking 2, no. 3 (September 2021): 100037. http://dx.doi.org/10.1016/j.latcb.2021.100037.

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See, Craig R., Mark B. Green, Ruth D. Yanai, Amey S. Bailey, John L. Campbell, and Jeremy Hayward. "Quantifying uncertainty in annual runoff due to missing data." PeerJ 8 (July 21, 2020): e9531. http://dx.doi.org/10.7717/peerj.9531.

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Анотація:
Long-term streamflow datasets inevitably include gaps, which must be filled to allow estimates of runoff and ultimately catchment water budgets. Uncertainty introduced by filling gaps in discharge records is rarely, if ever, reported. We characterized the uncertainty due to streamflow gaps in a reference watershed at the Hubbard Brook Experimental Forest (HBEF) from 1996 to 2009 by simulating artificial gaps of varying duration and flow rate, with the objective of quantifying their contribution to uncertainty in annual streamflow. Gaps were filled using an ensemble of regressions relating discharge from nearby streams, and the predicted flow was compared to the actual flow. Differences between the predicted and actual runoff increased with both gap length and flow rate, averaging 2.8% of the runoff during the gap. At the HBEF, the sum of gaps averaged 22 days per year, with the lowest and highest annual uncertainties due to gaps ranging from 1.5 mm (95% confidence interval surrounding mean runoff) to 21.1 mm. As a percentage of annual runoff, uncertainty due to gap filling ranged from 0.2–2.1%, depending on the year. Uncertainty in annual runoff due to gaps was small at the HBEF, where infilling models are based on multiple similar catchments in close proximity to the catchment of interest. The method demonstrated here can be used to quantify uncertainty due to gaps in any long-term streamflow data set, regardless of the gap-filling model applied.
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Більше джерел

Дисертації з теми "Data with gaps"

1

Pinell, Graciela Tejada. "Spatial assessment of data gaps for estimating biomass across the brazilian Amazon." Instituto Nacional de Pesquisas Espaciais (INPE), 2017. http://urlib.net/sid.inpe.br/mtc-m21b/2017/06.16.22.29.

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Анотація:
Amazon forest provides fundamental ecosystem services such as biodiversity conservation, water cycling and carbon sequestration. Given the large extent of Brazilian forests, 75% of the Amazon Basin, there is great uncertainty in the storage of aboveground biomass (AGB) carbon stocks. There is a significant difference between AGB estimates and an urgent need to improve AGB estimates to support the National Communications (NC) of Brazil to the United Nations Framework Convention on Climate Change and Reducing Emissions from Deforestation and Degradation (REDD+). Whether for NC, REDD+ or for the carbon emissions modeling, stakeholders, policy makers and scientists have to decide which AGB product, dataset or combination of data to use, according to its availability, scale and coverage. The purpose of this study was to assess forest AGB spatial data gaps across the Brazilian Amazon. To achieve this goal, we conducted an extensive review and analysis of the AGB datasets coverage. AGB stakeholders connections were made through a social network analysis. Also, AGB maps variability within different environmental factors maps (soil, vegetation, topography and climate) were analyzed. Using difference and statistical analyses of AGB maps and, through a spatial multicriteria evaluation, we obtained a forest AGB spatial data gaps map for the Brazilian Amazon. The spatial coverage of AGB field and airborne LiDAR data shows great areas without AGB data and, even though stakeholders have connections, few datasets are available. By quantifying AGB maps and field data variability within multiple environmental factors, we provide valuable elements for understanding the current AGB data in function of climate, soils, vegetation and geomorphology. The main differences between AGB maps are found next to the rivers (mainly the Amazon River), in Amapá, northeast of Pará and central and north Amazon States, these areas coincide with areas of higher AGB. The forest AGB spatial data gaps map, which refers to places with no field or LiDAR data and where AGB maps differ the most, show the priority areas for further AGB assessments in the Brazilian Amazon. This study can be a useful tool for policy makers and different stakeholders working on AGB on which to base their decisions to choose AGB data or products for National Communications, REDD+, or carbon emissions modeling.
A floresta amazônica fornece serviços ecossistêmicos fundamentais, como conservação da biodiversidade, ciclagem a água e sequestro de carbono. Dada a grande extensão das florestas brasileiras, 75% da Bacia Amazônica, existe uma grande incerteza nos estoques de carbono da biomassa acima do solo (AGB) armazenados na região. As estimativas de AGB existentes diferem significativamente entre si e há uma necessidade urgente de melhorá-las, uma vez que podem dar suporte às Comunicações Nacionais (NC) do Brasil para a Convenção-Quadro das Nações Unidas sobre Mudanças do Clima (UNFCCC) e Redução das Emissões por Desmatamento e Degradação florestal (REDD+). Seja para NC, REDD+ ou para a modelagem de emissões de carbono, as partes interessadas, os tomadores de decisão e os cientistas devem decidir qual produto, conjunto de dados ou combinação de dados de AGB usar, de acordo com sua disponibilidade, escala e cobertura. Com o objetivo de suprir esta demanda, neste estudo, avaliamos as lacunas de dados espaciais de AGB da floresta na Amazônia brasileira. Para isso, fizemos uma extensa revisão e análise da cobertura dos conjuntos de dados disponíveis. As conexões entre as partes interessadas foram feitas usando a social network analysis. Além disso, analisamos a variabilidade dos mapas de AGB em função de diferentes fatores ambientais (solo, vegetação, topografia e clima). Foram feitas também análises estatísticas e das diferenças entre os mapas de AGB e, com uma avaliação espacial multicritério, produzimos um mapa das lacunas de dados de AGB para a floresta amazônica brasileira. A cobertura espacial de AGB e os dados LiDAR aéreos mostram grandes áreas sem informação e, mesmo que as partes interessadas tenham conexões, poucos conjuntos de dados estão disponíveis. Ao quantificar os mapas de AGB e a variabilidade dos dados de campo em múltiplos fatores ambientais, fornecemos elementos valiosos para a compreensão dos dados de AGB atuais em função do clima, dos solos, da vegetação e da geomorfologia. As principais diferenças entre os mapas são encontradas ao lado dos rios (principalmente o rio Amazonas), no Amapá, no nordeste do Pará e nos estados amazônicos do centro e norte, coincidindo com áreas de maior AGB. O mapa de lacunas de dados espaciais de AGB da floresta,que se refere a locais sem dados de campo ou LiDAR e também onde os mapas da AGB diferem mais, mostram as áreas prioritárias para futuras avaliações de AGB na Amazônia brasileira. Este estudo é uma ferramenta útil para os formuladores de políticas e as diferentes partes interessadas que trabalham na AGB, que terá que devem decidir quais dados ou produtos da AGB devem usar para Comunicação Nacional, REDD + ou modelagem de emissões de carbono.
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2

McHugh, Alyson Elizabeth. "Missing baseline information for British Columbia's forests : can timber cruise data fill some gaps?" Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/778.

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Assessing trends in forest ecosystems requires a thorough understanding of a benchmark or condition against which changes can be measured. Timber cruise information is a valuable source of baseline data, and has potential to be used in monitoring the effectiveness of management actions taken to maintain biodiversity and other societal values during and after harvesting. The objective of this study was to assess the efficacy of using these data as baseline information in FREP (Forest and Range Evaluation Program) Stand Level Biodiversity (SLB) assessments. Using three different data sources (timber cruise data, FREP pre-harvest data, and FREP post-harvest data), I conducted a pre- and post-harvest survey and evaluated trends in indicators within and across seven cutblocks. Mean densities for live and standing dead trees by diameter class, total live and dead trees, functional snags, large trees, tree species composition, coarse woody debris, and a number of qualitative indicators were analyzed. Results indicate that similarities exist between several characteristics within the timber cruise and pre- and post-harvest FREP data. For example, there was substantial overlap between stand structural characteristics assessed by the three methods. However, some discrepancies were identified. Large trees (live, dead and live and dead combined) were evident in very small numbers in the timber cruise and data were not consistent with pre-harvest FREP data. The number of tree species identified in FREP data was generally lower than timber cruise data, with the species absent in the FREP data generally being recorded as rare in the timber cruise. Some important stand structural attributes are not collected under the current timber cruise protocol. This research has identified some possible limitations of using timber cruise statistics as baseline information for FREP SLB monitoring. Forests are dynamic, rare forest elements may be misrepresented in all three samples, and some potentially valuable data are currently missing from timber cruise statistics. However, the opportunities that timber cruise data provide as a provincial baseline dataset are immense, and further exploration and study could identify ways to improve the compatibility, efficiency, and utility of these data in FREP Stand Level Biodiversity monitoring.
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3

Xiang, Yun. "Ethnic differences in achievement growth: Longitudinal data analysis of math achievement in a hierarchical linear modeling framework." Thesis, Boston College, 2009. http://hdl.handle.net/2345/676.

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Thesis advisor: Henry Braun
Given the call for greater understanding of racial inequality in student achievement in K-12 education, this study contributes a comprehensive, quantitative, longitudinal examination of the achievement gap phenomenon, with particular attention to the organization characteristics of schools and school districts. Employing data from a large number of districts in a single state, it examines the trends in achievement and the growth in achievement after the passage of NCLB. It focuses on mathematics performance from grade 6 to grade 8. Both a traditional descriptive approach and one employing Hierarchical Linear Models were applied and compared. The purpose was not to determine which methodology is superior but to provide complementary perspectives. The comparison between the two approaches revealed similar trends in achievement gaps, but the HLM approach offered a more nuanced description. Nonetheless the results suggest that it is useful to employ both approaches. As to the main question regarding ethnicity, it appears that even if student ethnicity is confounded with other indicators, such as initial score and socio-economic status, it is still an important predictor of both achievement gaps and achievement growth gaps. Moreover, demographic profiles at the school and district levels were also associated with these gaps
Thesis (PhD) — Boston College, 2009
Submitted to: Boston College. Lynch School of Education
Discipline: Educational Research, Measurement, and Evaluation
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4

Gyau-Boakye, Philip. "Filling gaps in hydrological runoff data series in West-Africa = Ergänzung lückenhafter Abflussreihen in West-Afrika /." Bochum : Ruhr-Univ, 1993. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=006430220&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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5

Guttieres, Donovan G. "Closing gaps in global access to biologic medicines : building tools to evaluate innovations in biomanufacturing." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117892.

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Анотація:
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 127-134).
Low-and-Middle Income Countries (LMICs) are experiencing a growing need for safe, effective, and affordable health services, especially medicines. Such trends are in part due to a continued epidemiologic transition from infectious to chronic, non-communicable diseases (NCDs). Today, NCDs account for a large portion of total global disease burden: 70% of deaths as per the World Health Organization (WHO). NCDs are projected to continue to undercut economic productivity and drive up health spending. Many NCDs are effectively treated using biologic therapies; or large molecules produced by, or involving, living cells. Recently, some of these therapies have been included on the WHO Model List of Essential Medicines. However, the molecular, manufacturing, regulatory, and supply chain features of biologics lead to relatively higher costs and complexity compared to small-molecule drugs, with implications on widespread access. As part of the Global Action Plan for the Prevention and Control of NCDs 2013-2020, an 80% target for global availability of affordable essential medicines has been set for all public and private providers. In order to reach this target, there is need to better understand the complex barriers to accessing biologics across the biopharmaceutical value chain. Current gaps in access indicate the potential need to re-orient the biopharmaceutical system in order to meet future projected healthcare demand in terms of quantity, quality, and affordability. There is also growing uncertainty within the biopharmaceutical ecosystem as to the best use of resources, design of policies, and development of technologies that will have the most cost-effective impact on maximizing the supply of and access to such biologics. This research specifically focuses on the manufacturing component of biologics access, providing an analysis of the benefits and risks across different production networks, with varying number and location of facilities. A cost modeling tool is presented for quantitatively analyzing different manufacturing design options. This is accomplished by comparing the cost of good (COGs) and net present cost (NPC) of different scenarios, using Trastuzumab (a monoclonal antibody drug used to treat HER-2+ breast cancer) as a case study. Finally, future research questions are presented, aimed at better understanding the drivers of variability in manufacturing cost across manufacturing networks, especially when considering differences in product type, locations, regulatory jurisdictions, geopolitical zones, and sociocultural norms. In light of changing global health patterns and increasing demand for quality, affordable care, the thesis presents tools that can be generalized for addressing tradeoffs, short-and- long term effects, and intended-and-unintended consequences of investments in global health. It holds the potential for assessing the potential impact of various innovations (policies, technologies, organizational structures and more) on complex, dynamic systems and provide an evidence-base to better inform future areas of research, design of policies, and development of technologies.
by Donovan G. Guttieres.
S.M. in Technology and Policy
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6

Hofuku, Yoyoi, Shinya Cho, Tomohiro Nishida, and Susumu Kanemune. "Why is programming difficult? : proposal for learning programming in “small steps” and a prototype tool for detecting “gaps”." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6445/.

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In this article, we propose a model for an understanding process that learners can use while studying programming. We focus on the “small step” method, in which students learn only a few concepts for one program to avoid having trouble with learning programming. We also analyze the difference in the description order between several C programming textbooks on the basis of the model. We developed a tool to detect “gaps” (a lot of concepts to be learned in a program) in programming textbooks.
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Feighan, Kelly. "A QUANTITATIVE ANALYSIS OF MARITAL AGE GAPS IN THE U.S. BETWEEN 1970 AND 2014." Diss., Temple University Libraries, 2018. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/494818.

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Анотація:
Sociology
Ph.D.
Measuring spouses’ ages allows us to explore larger sociological issues about marriage, such as whether narrowing gaps signal gender progress or if a rise in female-older unions reveals a status change. Using Census and American Community Survey data, I test the merits of beauty-exchange and status homogamy theories as explanations for how heterosexual marital age gaps changed over a 40-year period of social and economic revolution. Analyses address questions about how age gaps compared for people with different characteristics, whether similarly aged couples exhibited greater educational and socio-economic homogamy than others, and if the odds of being in age-heterogamous marriages changed. Chapter 4 provides the historical context of U.S. marriages from 1910 on, and shows that while disadvantaged groups retreated from marriage, the percentage of individuals with greater education and income who married remained high. Age homogamy rose over 100 years due to a decline in marriages involving much-older husbands rather than increases in wife-older unions. Results in Chapter 5 show that mean age gaps decreased significantly over time for first-married individuals by most—but not all—characteristics. Gaps narrowed for those who were White, Black, other race, or of Hispanic origin; from any age group; with zero, one, or two wage earners; with any level of education; and from most types of interracial pairs. One exception was that mean age gaps increased between Asian wives and White husbands, and Asian women’s odds of having a much older husband were higher than the odds for racially homogamous women. Those odds increased over time. Findings lent support for status homogamy theory, since same-age couples showed greater educational homogamy than others in any decade, but showed mixed support for beauty exchange. In 2010-14, the median spousal earnings gap was wider in husband-older marriages than age-homogamous ones; however, the reverse was true in 1980. Women-older first or remarriages exhibited the smallest median earnings gaps in 1980 and 2010-14, and women in these marriages contributed a greater percentage of the family income than other women in 2010-14 (43.6% vs 36.9%, respectively). The odds of being in age-heterogamous unions were significantly higher for persons who were remarried, from older age groups, from certain racial backgrounds, in some interracial marriages, less educated, and from lower SES backgrounds. Age and remarriage showed the greatest impact on odds ratios. While age homogamy increased overall, the odds of being a much older spouse (11+ years older) increased dramatically for remarried men and women between 1970 and 1980, and then remained high in 2010-14. Remarried women’s odds of being the much older wife versus a same-age spouse were 20.7 times that of the odds of first-married women in 2010-14. Other results showed that Black men’s odds of being with a much-older wife compared to one around the same age were about 2.5 times that of the odds of White men in each decade. Hispanic men’s odds of being in a first marriage with a much-older wife versus one of the same age were also twice the odds of White men in 1980 and 2010-14. Analyses demonstrated that marital age gaps have, indeed, changed significantly since the second-wave women’s movement, and that while age homogamy increased, the odds of being age heterogamous also shifted for people with different characteristics.
Temple University--Theses
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Blomberg, Madeleine. "Biggest Skills Needs & Gaps : Case Study of Sandvik Coromant & Microsoft." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300053.

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In our increasingly digital age, the pace of digital transformation requires continuous learning. Microsoft CEO Satya Nadella put it simply when wanting Microsoft to transition from a culture of "know-it-all" to a culture of "learn-it-all". The most valuable commodity for leaders to do is to set an example for lifelong learning and to find opportunities to encourage others to do the same, allowing each employee to take responsibility for skilling up [18]. This study identifies prioritized skills and assesses what skills gaps exist from these. A maturity framework is developed to measure the level of skills within three dimensions “Technical and Digital skills”, “People and organization skills” and “Strategy skills” and is composed of 30 attributes (Table 1). This study uses Sandvik Coromant as a use case for assessing skill gaps and Microsoft as a use case for how to fulfil the gaps. This study contributes to the manufacturing sector by identifying prioritized skills, empirically establishing a maturity framework and providing an evaluation of Sandvik Cormorant’s current skills gap including how to fulfil these skills gaps by programs, tools or initiatives.
I vår alltmer digitala värld kräver takten i digital transformation kontinuerligt lärande. Microsofts vd Satya Nadella uttrycker att Microsoft ska övergå från en kultur av "veta allt" till en kultur av "lära sig allt". Den mest värdefulla tillgången för ledare är att föregå med gott exempel för livslångt lärande och hitta möjligheter att uppmuntra andra att göra detsamma, så att varje anställd kan ta ansvar för kompetensutveckling [18]. Denna studie identifierar prioriterade kompetenser och bedömer vilka kompetensgap som existerar i dessa. Ett mognadsramverk utvecklas för att mäta kompetensnivån inom tre dimensioner ”Tekniska och digitala färdigheter”, ”Människor och organisationsfärdigheter” och “Strategifärdigheter” och består av 30 attribut (tabell 1). Denna studie använder Sandvik Coromant som ett användningsfall för att bedöma kompetensgap och Microsoft som ett användningsfall för hur man ska kunna uppfylla gapen. Denna studie bidrar till tillverkningssektorn genom att identifiera prioriterade färdigheter, empiriskt upprätta ett mognadsramverk och ge en utvärdering av Sandvik Cormorants nuvarande kompetensgap inklusive hur man kan uppfylla dessa kompetensgap genom program, verktyg eller initiativ.
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9

Nordström, Fanny, and Claudia Järvelä. "Digital Competencies and Data Literacy in Digital Transformations : Experience from the Technology Consultants." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-450947.

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Анотація:
The digital revolution is challenging both individuals and organizations to be more comfortable using various digital technologies. Digital technologies enable and generate high amounts of data, but people are not very good at interpreting or making sense of it. This study aimed to explore the role of digital competencies and data literacy in digital transformations and identify the consequences the lack of digital competencies and data literacy can cause within digital transformation projects. The authors studied technology consultants' perspectives with experience in digital transformation projects using an exploratory qualitative research design building on the empirical data gathered from semi-structured interviews. The authors were able to identify that the technology consultants perceived digital competencies as crucial skills for individuals to possess in digital transformations. At the same time, data literacy was not considered a crucial skill in the context of digital transformations. Regarding the consequences of a digital skills gap, the technology consultants saw issues within the implementation of the project, delays, or indirect waste of resources like monetary assets.
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10

Irfan, Kamran. "Adaptation of the generic crop model STICS for rice (Oryza sativa L.) using farm data in Camargue." Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM4355.

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Анотація:
Le modèle de culture STICS a été adapté pour la culture du riz inondé et la capacité de prédiction du modèle a été évaluée pour la simulation de la biomasse à la récolte et du rendement en grains. La base de données utilisée pour ce travail résulte de la collecte de données au champ sur des parcelles en Camargue (sud-Est de la France) gérées par les agriculteurs. Pour la modélisation, ne disposant que très peu de données d’expérimentation, une procédure originale d’utilisation des données obtenues à la ferme a été développée. Ce travail est composé de trois phases: (i) une analyse de la base de données initiale constituée d’informations sur 472 parcelles, 33 variétés et 11 sols aux propriétés physiques différentes et collectées entre 1984 et 2009 dans toute la Camargue; (ii) la sélection des options et des formalismes pertinents pour la culture du riz, (iii) la préparation du jeu de données pour la modélisation par élimination des parcelles dont les rendements sont limités par des facteurs non pris en compte dans le modèle; (iv) la paramétrisation et la simulation des variables choisies.Les résultats de l’application de STICS au riz sont satisfaisants pour près de 80% des parcelles utilisées pour la base de données de calibration. L’accord entre les simulations et les observations est meilleur lorsque les informations d’entrée du modèle sont complètes. Les simulations de la biomasse et du rendement en grains sont d’une qualité légèrement plus faible pour la base de données de validation que pour la base da calibration
The crop model STICS was adapted for the flooded rice and model’s prediction ability was evaluated by the simulation of the plant biomass at harvest as well as the grain yield. The dataset used for this purpose was collected from the fields situated in whole Camargue (Southern France) and managed by the farmers. We introduced an original procedure to use the farm data instead of experimentation for modeling. This work was carried out in three phases, (i) analysis of the initial database of 472 fields, 33 different varieties and 11 physically different soils grown in the whole Camargue between 1984 and 2009, (ii) selection of the options of formalisms relevant to the rice crop, (iii) preparation of dataset for modeling by eliminating the fields in which the yields were limited by the factors not taken into account by the model and (iv) parameterization and the simulation of the selected target variables. The results of the application of STICS to rice crop were satisfactory for almost 80% of the fields of calibration data. Particularly, there was a good agreement between simulations and measurements of the situations with complete information regarding to the inputs. The simulation patterns for both the plant biomass and the grain yield of dataset of validation are similar as that of dataset of calibration exhibiting slightly reduced simulation quality. More discrepancies were observed in the simulations made by the model calculated dates of different phenological stages compared to the simulations run by using the observed dates of same stages
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Книги з теми "Data with gaps"

1

Schneider, Joanne Thacker. Foster care: Fraught with data gaps and inadequate services. Sacramento, CA (Box 942849, Sacramento 94249-0001): Assembly Office of Research, 1989.

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Benaka, Lee R. Fisheries release mortality: Identifying, prioritizing, and resolving data gaps. Silver Spring, Maryland: U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, 2014.

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Fund, International Monetary. Price pressure gaps: An application of P* using Korean data. [Washington]: International Monetary Fund, European and Research Departments, 1991.

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Workshop on Nursing Data Gaps and Needs (1985 Washington, D.C.). Report of the workshop: Nursing Data Gaps & Needs, September 1985. [Rockville, MD]: The Division, 1986.

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Workshop on Nursing Data Gaps and Needs (1985 Washington, D.C.). Report of the workshop: Nursing Data Gaps & Needs, September 1985. [Rockville, MD]: The Division, 1986.

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Ahmad, Raza. Analysis of gaps in data-based interventions in reproductive health in Pakistan. Islamabad: Leads Pakistan, 2007.

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Hurst, Jill Ann. DialogWeb/FT: Navigating the periodical jungle : titles, variants, data gaps, and duplications. Woodstock, GA: Hermograph Press, 1999.

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Regional Community Forestry Training Center for Asia-Pacific (Bangkok, Thailand), ed. Forestry and poverty data in Viet Nam: Status, gaps, and potential uses. Bangkok, Thailand: Regional Community Forestry Training Center for Asia and the Pacific, 2009.

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Bower, Aimee. Equipment sustainment data in standard Army management information systems: Needs, gaps, and opportunities. Santa Monica, CA: RAND, 2012.

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Wahyunto. Peatland distribution in Sumatra and Kalimantan: Explanation of its data sets including source of information, accuracy, data constraints, and gaps. Bogor: Wetlands International, Indonesia Programme, 2008.

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Частини книг з теми "Data with gaps"

1

Fernandes da Silva, E. C. "GaAs: energy gaps." In New Data and Updates for I-VII, III-V, III-VI and IV-VI Compounds, 209. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-48529-2_88.

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Talukder, Asoke K. "Bridging the Inferential Gaps in Healthcare." In Big Data Analytics, 31–43. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-93620-4_3.

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Battersby, Jane. "Data gaps and the politics of data." In Sustainable Food System Assessment, 93–110. Milton Park, Abingdon, Oxon ;: Routledge, 2019. http://dx.doi.org/10.4324/9780429439896-5.

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Fernandes da Silva, E. C. "AlAs: energy gaps." In New Data and Updates for III-V, II-VI and I-VII Compounds, 59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-92140-0_47.

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Gutowski, J., K. Sebald, and T. Voss. "CdO: energy gaps." In New Data and Updates for III-V, II-VI and I-VII Compounds, 287. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-92140-0_209.

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Gutowski, J., K. Sebald, and T. Voss. "CdSe: energy gaps." In New Data and Updates for III-V, II-VI and I-VII Compounds, 302. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-92140-0_221.

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Chu, J. "HgS: energy gaps." In New Data and Updates for III-V, II-VI and I-VII Compounds, 392. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-92140-0_288.

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8

Richard, Antoine, Lior Fine, Offer Rozenstein, Josef Tanny, Matthieu Geist, and Cedric Pradalier. "Filling Gaps in Micro-meteorological Data." In Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 101–17. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67670-4_7.

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Fernandes da Silva, E. C. "AlAs: energy gaps." In New Data and Updates for I-VII, III-V, III-VI and IV-VI Compounds, 172. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-48529-2_65.

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Meyer, B. K. "AlN: energy gaps." In New Data and Updates for I-VII, III-V, III-VI and IV-VI Compounds, 197. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-48529-2_81.

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Тези доповідей конференцій з теми "Data with gaps"

1

Caviggioli, Federico, Alessandra Colombelli, and Chiara Ravetti. "Star inventors and gender gaps in patented innovations." In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671913.

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Dipti Kumar, Vijay, and Paulo Alencar. "Software engineering for big data projects: Domains, methodologies and gaps." In 2016 IEEE International Conference on Big Data (Big Data). IEEE, 2016. http://dx.doi.org/10.1109/bigdata.2016.7840938.

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David Strang, Kenneth, and Zhaohao Sun. "Meta-analysis of big data security and privacy: Scholarly literature gaps." In 2016 IEEE International Conference on Big Data (Big Data). IEEE, 2016. http://dx.doi.org/10.1109/bigdata.2016.7841101.

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Lockwood, M., and D. Hamilton. "Identifying Oceanographic Data Gaps in the EEZ." In OCEANS '86. IEEE, 1986. http://dx.doi.org/10.1109/oceans.1986.1160323.

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HUANG, Yitong, Clark BOWMAN, Olivia WALCH, and Daniel FORGER. "Phase Estimation from Noisy Data with Gaps." In 2019 13th International conference on Sampling Theory and Applications (SampTA). IEEE, 2019. http://dx.doi.org/10.1109/sampta45681.2019.9030828.

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Andoni, Alexandr, Assaf Naor, Aleksandar Nikolov, Ilya Razenshteyn, and Erik Waingarten. "Data-dependent hashing via nonlinear spectral gaps." In STOC '18: Symposium on Theory of Computing. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3188745.3188846.

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"FILLING THE GAPS USING GOOGLE 5-GRAMS CORPUS." In 5th International Conference on Software and Data Technologies. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002932204380443.

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Mushtaq, S. Sutar, M. A. Kadampur, and Anis Fatima Najeem Mulla. "Finding redundant patterns with gaps in sequential data." In 2014 International Conference on Power Automation and Communication (INPAC). IEEE, 2014. http://dx.doi.org/10.1109/inpac.2014.6981148.

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Doerry, Armin W., Fred M. Dickey, and Louis A. Romero. "Windowing functions for SAR data with spectral gaps." In AeroSense 2003, edited by Edmund G. Zelnio and Frederick D. Garber. SPIE, 2003. http://dx.doi.org/10.1117/12.487265.

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Kenneally, Erin, Lucien Randazzese, and David Balenson. "Cyber Risk Economics Capability Gaps Research Strategy." In 2018 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA). IEEE, 2018. http://dx.doi.org/10.1109/cybersa.2018.8551399.

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Звіти організацій з теми "Data with gaps"

1

Boone, Jonathan, Layton Breithaupt,, Maria Stevens, Benjamin Webb, John Green, Joshua Fairley, and Stephanie Price. Urban terrain data availability and gaps. Engineer Research and Development Center (U.S.), July 2019. http://dx.doi.org/10.21079/11681/33387.

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MAXTED, MAXCINE. DATA CALL QUESTIONS RELATED TO POTENTIAL NEPA/DATA GAPS. Office of Scientific and Technical Information (OSTI), November 2020. http://dx.doi.org/10.2172/1716720.

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Giles Álvarez, Laura, Juan Carlos Vargas-Moreno, and Leonardo Pacheco Tenório Cavalcanti. Maps for Gaps: A Geospatial Approach to Estimating Development Gaps in Haiti. Inter-American Development Bank, December 2021. http://dx.doi.org/10.18235/0003811.

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Анотація:
This paper presents the results of a development gap analysis for Haiti using a geospatial approach. Gaps are calculated and characterized by means of qualitative and quantitative techniques, including macroeconomic, microeconomic, and geospatial data analyses. The analysis identifies, presents, and discusses 16 sectoral gaps. It is then expanded by overlapping the sectoral gaps to identify possible relations and spillover effects between them. The results suggest that transportation, early childhood education, and crime and insecurity gaps are the most significant in terms of the area and population affected. Results also show that 24 percent of the area of the country and 9.9 percent of Haitians are affected by nine or more overlapping gaps, particularly in the Nord-Ouest, Artibonite, and Centre departments. In terms of the links between sectors, crime and insecurity gaps tend to overlap with gaps in early childhood education and employment opportunities.
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4

Fahey, Éamonn, Frances McGinnity, and Emma Quinn. Data for monitoring integration: Gaps, challenges and opportunities. ESRI, March 2019. http://dx.doi.org/10.26504/bkmnext373.pdf.

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5

Wells, Beric E., Dean E. Kurath, Lenna A. Mahoney, Yasuo Onishi, James L. Huckaby, Scott K. Cooley, Carolyn A. Burns, et al. Hanford Waste Physical and Rheological Properties: Data and Gaps. Office of Scientific and Technical Information (OSTI), August 2011. http://dx.doi.org/10.2172/1025093.

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Yin, Tianzhixi, Jianming Lian, John Buckheit, and Rui Fan. Bridging Power System Protection Gaps with Data-driven Approaches. Office of Scientific and Technical Information (OSTI), February 2021. http://dx.doi.org/10.2172/1771797.

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7

Stock, James. Data Gaps and the Policy Response to the Novel Coronavirus. Cambridge, MA: National Bureau of Economic Research, March 2020. http://dx.doi.org/10.3386/w26902.

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Arnold, Zachary, Joanne Boisson, Lorenzo Bongiovanni, Daniel Chou, Carrie Peelman, and Ilya Rahkovsky. Using Machine Learning to Fill Gaps in Chinese AI Market Data. Center for Security and Emerging Technology, February 2021. http://dx.doi.org/10.51593/20200064.

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Анотація:
In this proof-of-concept project, CSET and Amplyfi Ltd. used machine learning models and Chinese-language web data to identify Chinese companies active in artificial intelligence. Most of these companies were not labeled or described as AI-related in two high-quality commercial datasets. The authors' findings show that using structured data alone—even from the best providers—will yield an incomplete picture of the Chinese AI landscape.
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DiJoseph, Patricia, Brian Tetreault, and Marin Kress. AIS data case Study : identifying AIS coverage gaps on the Ohio River in CY2018. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/40886.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) describes a method for evaluating the received coverage from Automatic Identification System (AIS) shore sites and the availability of historic vessel position reports along the Ohio River. The network of AIS shoreside sites installed and operated by the US Army Corps of Engineers (USACE) and the US Coast Guard (USCG) receive information transmitted from vessels; however, reception of these transmissions is generally line-of-sight between the vessel and the AIS site antenna. Reception may also be affected by factors such as the quality of the transceiver installation aboard the vessel as well as the state of the equipment at the receiving site. Understanding how to define and quantify coverage gaps along the inland river system can inform research utilizing AIS data, provide information on the performance of the AIS network, and provide guidance for efforts to address identified coverage gaps
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Frank, Jereme, Aaron Weiskittel, David Walker, James A. Westfall, Philip J. Radtke, David L. R. Affleck, John Coulston, and David W. MacFarlane. Gaps in available data for modeling tree biomass in the United States. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station, 2019. http://dx.doi.org/10.2737/nrs-gtr-184.

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