Relevant bibliographies by topics / Dataset IMPACT

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Dataset IMPACT'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Dataset IMPACT"

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Althnian, Alhanoof, Duaa AlSaeed, Heyam Al-Baity, et al. "Impact of Dataset Size on Classification Performance: An Empirical Evaluation in the Medical Domain." Applied Sciences 11, no. 2 (2021): 796. http://dx.doi.org/10.3390/app11020796.

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Dataset size is considered a major concern in the medical domain, where lack of data is a common occurrence. This study aims to investigate the impact of dataset size on the overall performance of supervised classification models. We examined the performance of six widely-used models in the medical field, including support vector machine (SVM), neural networks (NN), C4.5 decision tree (DT), random forest (RF), adaboost (AB), and naïve Bayes (NB) on eighteen small medical UCI datasets. We further implemented three dataset size reduction scenarios on two large datasets and analyze the performanc
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Tarek, Mostafa, François P. Brissette, and Richard Arsenault. "Large-Scale Analysis of Global Gridded Precipitation and Temperature Datasets for Climate Change Impact Studies." Journal of Hydrometeorology 21, no. 11 (2020): 2623–40. http://dx.doi.org/10.1175/jhm-d-20-0100.1.

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AbstractCurrently, there are a large number of diverse climate datasets in existence, which differ, sometimes greatly, in terms of their data sources, quality control schemes, estimation procedures, and spatial and temporal resolutions. Choosing an appropriate dataset for a given application is therefore not a simple task. This study compares nine global/near-global precipitation datasets and three global temperature datasets over 3138 North American catchments. The chosen datasets all meet the minimum requirement of having at least 30 years of available data, so they could all potentially be
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Khreis, Haneen, Kees de Hoogh, Josias Zietsman, and Mark J. Nieuwenhuijsen. "The Impact of Different Validation Datasets on Air Quality Modeling Performance." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 25 (2018): 57–66. http://dx.doi.org/10.1177/0361198118780682.

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Many studies rely on air pollution modeling such as land use regression (LUR) or atmospheric dispersion (AD) modeling in epidemiological and health impact assessments. Generally, these models are only validated using one validation dataset and their estimates at select receptor points are generalized to larger areas. The primary objective of this paper was to explore the effect of different validation datasets on the validation of air quality models. The secondary objective was to explore the effect of the model estimates’ spatial resolution on the models’ validity at different locations. Annu
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Xu, Hanzhang, Yaolin Pei, Matthew Dupre, and Bei Wu. "Existing Datasets to Study the Impact of Internal Migration on Caregiving Arrangements." Innovation in Aging 4, Supplement_1 (2020): 750. http://dx.doi.org/10.1093/geroni/igaa057.2703.

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Abstract Massive rural-to-urban migration in China has a significant impact on caregiving arrangements among Chinese older adults. To stimulate research on the intersection of migration and caregiving, we conducted an inventory of longitudinal aging survey datasets that included older adults from mainland China. Large public available datasets that included measures related to migration and caregiving were searched and reviewed for eligibility. Key characteristics of each dataset, including study design, sample size, and measures, were extracted. Seven eligible datasets were identified, and fi
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Tarek, Mostafa, François Brissette, and Richard Arsenault. "Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies." Hydrology and Earth System Sciences 25, no. 6 (2021): 3331–50. http://dx.doi.org/10.5194/hess-25-3331-2021.

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Abstract. Climate change impact studies require a reference climatological dataset providing a baseline period to assess future changes and post-process climate model biases. High-resolution gridded precipitation and temperature datasets interpolated from weather stations are available in regions of high-density networks of weather stations, as is the case in most parts of Europe and the United States. In many of the world's regions, however, the low density of observational networks renders gauge-based datasets highly uncertain. Satellite, reanalysis and merged product datasets have been used
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Zhan, Xianghao, Yiheng Li, Yuzhe Liu, et al. "The relationship between brain injury criteria and brain strain across different types of head impacts can be different." Journal of The Royal Society Interface 18, no. 179 (2021): 20210260. http://dx.doi.org/10.1098/rsif.2021.0260.

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Multiple brain injury criteria (BIC) are developed to quickly quantify brain injury risks after head impacts. These BIC originated from different head impact types (e.g. sports and car crashes) are widely used in risk evaluation. However, the accuracy of using the BIC on brain injury risk estimation across head impact types has not been evaluated. Physiologically, brain strain is often considered the key parameter of brain injury. To evaluate the BIC's risk estimation accuracy across five datasets comprising different head impact types, linear regression was used to model 95% maximum principal
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Antuña, J. C., J. A. Añel, and L. Gimeno. "Impact of missing sounding reports on mandatory levels and tropopause statistics: a case study." Annales Geophysicae 24, no. 10 (2006): 2445–49. http://dx.doi.org/10.5194/angeo-24-2445-2006.

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Abstract. This paper describes the effect of missing sounding reports on temperature and pressure mean values for mandatory levels using the aerological information from the Camagüey Meteorological Centre. Also it is described the effect of missing data on mean temperature and pressure values at the multiple tropopause levels. The case study belongs to one station for a time lag of eight years. Up to the present these types of studies have been conducted using simulated datasets. The present one uses a real inhomogeneous radiosonde dataset. The main reason for missing reports were transmission
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Van Hulse, Jason, Taghi M. Khoshgoftaar, and Amri Napolitano. "Evaluating the Impact of Data Quality on Sampling." Journal of Information & Knowledge Management 10, no. 03 (2011): 225–45. http://dx.doi.org/10.1142/s021964921100295x.

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Learning from imbalanced training data can be a difficult endeavour, and the task is made even more challenging if the data is of low quality or the size of the training dataset is small. Data sampling is a commonly used method for improving learner performance when data is imbalanced. However, little effort has been put forth to investigate the performance of data sampling techniques when data is both noisy and imbalanced. In this work, we present a comprehensive empirical investigation of the impact of changes in four training dataset characteristics — dataset size, class distribution, noise
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Lebedev, Iliya. "Dataset segmentation considering the information about impact factors." Information and Control Systems, no. 3 (June 29, 2021): 29–38. http://dx.doi.org/10.31799/1684-8853-2021-3-29-38.

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Introduction: The application of machine learning methods involves the collection and processing of data which comes from the recording elements in the offline mode. Most models are trained on historical data and then used in forecasting, classification, search for influencing factors or impacts, and state analysis. In the long run, the data value ranges can change, affecting the quality of the classification algorithms and leading to the situation when the models should be constantly trained or readjusted taking into account the input data. Purpose: Development of a technique to improve the q
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Drusch, Matthias. "Sea Ice Concentration Analyses for the Baltic Sea and Their Impact on Numerical Weather Prediction." Journal of Applied Meteorology and Climatology 45, no. 7 (2006): 982–94. http://dx.doi.org/10.1175/jam2376.1.

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Abstract Sea ice concentration plays a fundamental role in the exchange of water and energy between the ocean and the atmosphere. Global real-time datasets of sea ice concentration are based on satellite observations, which do not necessarily resolve small-scale patterns or coastal features. In this study, the global National Centers for Environmental Prediction (NCEP) 0.5° sea ice concentration dataset is compared with a regional high-resolution analysis for the Baltic Sea produced 2 times per week by the Swedish Meteorological and Hydrological Institute (SMHI). In general, the NCEP dataset e
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Dissertations / Theses on the topic "Dataset IMPACT"

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Kvist, Eric, and Rhodin Sandro Lockvall. "A comparative study between MLP and CNN for noise reduction on images : The impact of different input dataset sizes and the impact of different types of noise on performance." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259654.

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Images damaged by noise present a problem that can be addressed by performing noise-reduction using neural networks. This thesis analyses the performance of two different neural networks, a Mulilayer Perceptron (MLP) and a Convolutional Neural Network (CNN), when performing noise reduction on images. Specifically focusing on the impact of the size of dataset used to train the two different kinds of neural networks has on the performance, as well as how well these two networks perform when reducing different types of noise. This in an attempt to determine whether the use of the more modern type
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Kim, Kyoung Tae. "The Impact of the 2007 Recession on the Retirement Decisions of U.S. Households: Evidence from the 2007-2009 Survey of Consumer Finances Panel Dataset." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406072629.

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Kohút, Jan. "Aktivní učení pro rozpoznávání textu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403210.

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The aim of this Master's thesis is to design methods of active learning and to experiment with datasets of historical documents. A large and diverse dataset IMPACT of more than one million lines is used for experiments. I am using neural networks to check the readability of lines and correctness of their annotations. Firstly, I compare architectures of convolutional and recurrent neural networks with bidirectional LSTM layer. Next, I study different ways of learning neural networks using methods of active learning. Mainly I use active learning to adapt neural networks to documents that the neu
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Cohen, Raviv. "Impact of caricature-based datasets on demographic inference." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=117195.

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The widespread adoption of social networking platforms has generated interest in studying groups of users. Interest in the composition of groups has led to the development of methods to infer demographic attributes of participants such as such as age, ethnicity, and political orientation. While all demographic inference methods report excellent performance, there is a concern that this is the product of the way the dataset was constructed and not just the methods accuracy. In our research we observed an overemphasis on classifying users that exhibit easy-to-classify traits ; we call such users
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Bourdon, Céline. "Recherche d’associations entre microARNs, variants génétiques et QTL laitiers chez les bovins, caprins et ovins RumimiR: a detailed microRNA database focused on ruminant species In silicowhole genome SNP dataset analyses identify variations in microRNAs with a potential impact on dairy traits in bovine, caprine and ovine species." Thesis, université Paris-Saclay, 2021. http://www.theses.fr/2021UPASL020.

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La sélection génomique, qui repose sur la prédiction de la valeur génétique des animaux candidats à la sélection à partir de l'information fournie par de très nombreux marqueurs génétiques en utilisant des marqueurs neutres, est un levier pertinent et pérenne. La recherche des mutations causales et leur intégration dans les évaluations génomiques permettraient un gain de précision important. Il est donc essentiel de mieux caractériser les mutations causales responsables de la variabilité des caractères quantitatifs liés à l’efficacité de production et à la qualité des produits tels que le lait
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Simonian, Gregory Vahag Aghabekian. "Double Trouble: The Impact of Binarity on Large Stellar Rotation Datasets." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1563439631310165.

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Mutuc, Maria Erlinda Manalo. "Increase in Calorie Intake Due to Eggplant Grafting: Proof of Concept With the Use of Minimum Datasets." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/9645.

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Eggplant grafting implemented implemented in two field sites in the Philippines, in Nueva Ecija and Pangasinan are used as proofs of concept to illustrate and validate the feasibility of an impact assessment framework for determining the nutritional impact of technology-oriented agricultural activities. Nutritional impacts are assessed by disaggregating the market demand curve into demand curves by income groups using their separate price elasticities of demand. Considering only price effects, the increase in yields following a per unit cost reduction due to eggplant grafting has positive effe
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Mewes, Thorsten [Verfasser]. "The impact of the spectral dimension of hyperspectral datasets on plant disease detection / Thorsten Mewes." Bonn : Universitäts- und Landesbibliothek Bonn, 2011. http://d-nb.info/101621667X/34.

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Le, Bel Paul David. "Performance Evaluation of a Low Impact Development Retrofit for Urban Stormwater Treatment." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/48656.

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The goal of Low Impact Development (LID) is to mimic the pre-development hydrologic regime of a catchment through infiltration, filtration, storage, evaporation, and detention of post-development runoff using small-scale hydrologic controls close to the source. A LID facility located in Northern Virginia was examined for pollutant removal and hydrologic performance. The treatment train included four in-line grass swales followed by a bioretention cell with a gravel base. The facility retained 85% of the rainfall. Influent and effluent pollutant loads were calculated using three common substitu
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Insola, Federica. "Studio di Life Cycle Assessment per la creazione di dataset sul mix elettrico nazionale per la Banca Dati Italiana LCA." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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La tesi, svolta a seguito di un tirocinio presso ENEA, ha come scopo quello di sviluppare uno studio LCA sul mix nazionale di produzione e consumo di energia elettrica al fine di individuare quantitativamente i potenziali impatti ambientali che ne derivano per poter creare successivamente i dataset da inserire nella banca dati nazionale LCA sviluppata nel progetto europeo Arcadia - Approccio ciclo di vita nei contratti pubblici e banca dati italiana LCA per l’uso efficiente delle risorse, in collaborazione con ENEA. Si è scelto di iniziare l’elaborato fornendo un quadro generale sulla metodolo
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Books on the topic "Dataset IMPACT"

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Kusumawardhani, Niken, Rezanti Pramana, Nurmala Saputri, and Daniel Suryadarma. Heterogeneous impact of internet availability on female labour market outcomes in an emerging economy: Evidence from Indonesia. 49th ed. UNU-WIDER, 2021. http://dx.doi.org/10.35188/unu-wider/2021/987-7.

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Greater female labour market participation has important positive implications not only for women’s empowerment and the well-being of their families but also for the economy they live in. In this paper, we examine the various effects of internet availability on women’s labour market outcomes in Indonesia. As each worker subgroup tends to respond differently to changes in technology, examining the heterogeneity in the impact of internet availability on female labour market outcomes is central to our research. By constructing a district-level longitudinal dataset covering the period 2007–18, we
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Cette, Gilbert, Jimmy Lopez, and Jacques Mairesse. Labour Market Regulations and Capital Intensity. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198821878.003.0009.

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What is the impact of labour market regulations as measured by the OECD indicator of employment protection legislation (EPL) on capital and skill composition? Precisely, this study investigates the effects of changes in EPL on changes in four types of capital and three components of labour skill. They include construction, non-ICT, ICT, and R&D capital components on the one hand, and low-, medium-, and highly-skilled labour on the other. Our analysis is grounded on a large country–industry panel dataset of fourteen OECD countries, and eighteen manufacturing and market service industries, f
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Ganguli, Ina, Ricardo Hausmann, and Martina Viarengo. Career Dynamics and Gender Gaps Among Employees in the Microfinance Sector. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198829591.003.0009.

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Microfinance institutions (MFIs) are commonly identified as empowering women and making them key actors in generating social change and economic development. Yet little is known about the gender parity among employees within the lending institutions themselves and how this can impact development. While MFIs are increasingly important as employers in the developing world, there is little micro-level evidence about gender differences among MFI employees and MFIs’ relation to economic development. We use a unique panel dataset of employees from Latin America’s largest MFI to show that gender gaps
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Barbiellini Amidei, Federico, John Cantwell, and Anna Spadavecchia. Innovation and Foreign Technology. Edited by Gianni Toniolo. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199936694.013.0014.

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The chapter explores the long-run evolution of Italy's performance in technological innovation as a function of international technology transfer, reconstructing the different phases and dimensions of Italian innovative activity, tracking the transfer of foreign technological knowledge through a number of channels, analyzing the impact of imported technology. The study is based on a newly constructed dataset, over the 1861-2009 period, composed of variables related to innovation activity performance, foreign technology transfer, and domestic absorptive and innovative capability. The analysis h
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Shibata, Saori. Contesting Precarity in Japan. Cornell University Press, 2020. http://dx.doi.org/10.7591/cornell/9781501749926.001.0001.

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This book details the new forms of workers' protest and opposition that have developed as Japan's economy has transformed over the past three decades and highlights their impact upon the country's policymaking process. Drawing on a new dataset charting protest events from the 1980s to the present, the book produces the first systematic study of Japan's new precarious labor movement. It details the movement's rise during Japan's post-bubble economic transformation and highlights the different and innovative forms of dissent that mark the end of the country's famously non-confrontational industr
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Burt, Stephen, and Tim Burt. Oxford Weather and Climate since 1767. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198834632.001.0001.

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Oxford Weather and Climate since 1767 provides a detailed description and analysis of the weather records made at the Radcliffe Observatory in Oxford, the longest continuous series of single-site weather records in Britain and one of the longest in the world. The earliest records date from 1767, and daily records are unbroken since November 1813. The records allow the reconstruction of 200-year temperature and rainfall series and places the Oxford records in the context of long-term climate change. In this, the first full publication of the entire dataset, the long Oxford record is both celebr
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Fung, Courtney J. China and Intervention at the UN Security Council. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198842743.001.0001.

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What explains China’s response to intervention at the UN Security Council? China and Intervention at the UN Security Council argues that status is an overlooked determinant in understanding its decisions, even in the apex cases that are shadowed by a public discourse calling for regime change in Sudan, Libya, and Syria. The book posits that China reconciles its status dilemma as it weighs decisions to intervene: seeking recognition from both its intervention peer groups of great powers and developing states. Understanding the impact and scope conditions of status answers why China has taken ce
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Barker, Nathan, C. Austin Davis, Paula López-Peña, et al. Migration and the labour market impacts of COVID-19. UNU-WIDER, 2020. http://dx.doi.org/10.35188/unu-wider/2020/896-2.

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Using detailed microdata, we document how migration-dependent households are especially vulnerable during the COVID-19 pandemic. We create pre- and post-COVID panel datasets for three populations in Bangladesh and Nepal, leveraging experimental and observational variation in prior migration dependence. We report 25 per cent greater declines in earnings and fourfold greater prevalence of food insecurity among migrant households since March. Causes include lower migration rates, less remittance income per migrant, isolation in origin communities, and greater health risks. We compile a large set
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Germano, Roy. Optimism in Times of Crisis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190862848.003.0004.

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Using a variety of survey datasets, this chapter explores the impact of remittances in fifty Latin American, Caribbean, Middle Eastern, North African, and sub-Saharan African countries. The first part of this chapter provides an overview of trends in the flow of migrants and remittances throughout these developing regions. The remainder of the chapter uses survey data to analyze the effects of remittances on economic grievances during the global food and financial crises that struck many economies between 2008 and 2011. The results indicate that remittances are strongly associated with feeling
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Ferraty, Frédéric, and Philippe Vieu. Kernel Regression Estimation for Functional Data. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.4.

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This article provides an overview of recent nonparametric and semiparametric advances in kernel regression estimation for functional data. In particular, it considers the various statistical techniques based on kernel smoothing ideas that have recently been developed for functional regression estimation problems. The article first examines nonparametric functional regression modelling before discussing three popular functional regression estimates constructed by means of kernel ideas, namely: the Nadaraya-Watson convolution kernel estimate, the kNN functional estimate, and the local linear fun
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Book chapters on the topic "Dataset IMPACT"

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Amamra, Abdelfattah, Chamseddine Talhi, and Jean-Marc Robert. "Impact of Dataset Representation on Smartphone Malware Detection Performance." In Trust Management VII. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38323-6_12.

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Linjordet, Trond, and Krisztian Balog. "Impact of Training Dataset Size on Neural Answer Selection Models." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15712-8_59.

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Sbai, Othman, Camille Couprie, and Mathieu Aubry. "Impact of Base Dataset Design on Few-Shot Image Classification." In Computer Vision – ECCV 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58517-4_35.

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Sinha, Ankur, and Tanmay Khandait. "Impact of News on the Commodity Market: Dataset and Results." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73103-8_41.

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Wanderley, Miguel D. de S., Leonardo de A. e. Bueno, Cleber Zanchettin, and Adriano L. I. Oliveira. "The Impact of Dataset Complexity on Transfer Learning over Convolutional Neural Networks." In Artificial Neural Networks and Machine Learning – ICANN 2017. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68612-7_66.

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Charte, Francisco, Antonio Rivera, María José del Jesus, and Francisco Herrera. "On the Impact of Dataset Complexity and Sampling Strategy in Multilabel Classifiers Performance." In Lecture Notes in Computer Science. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32034-2_42.

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Olaniyan, Olumide A., Vincent O. Ajayi, Kamoru A. Lawal, and Ugbah Paul Akeh. "Impact of Moisture Flux and Vertical Wind Shear on Forecasting Extreme Rainfall Events in Nigeria." In African Handbook of Climate Change Adaptation. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42091-8_98-1.

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AbstractThis chapter investigates extreme rainfall events that caused flood during summer months of June–September 2010–2014. The aim is to determine the impact of horizontal moisture flux divergence (HMFD) and vertical wind shear on forecasting extreme rainfall events over Nigeria. Wind divergence and convective available potential energy (CAPE) were also examined to ascertain their threshold values during the events. The data used include rainfall observation from 40 synoptic stations across Nigeria, reanalyzed datasets from ECMWF at 0.125° × 0.125° resolution and the Tropical Rainfall Measuring Mission (TRMM) dataset at resolution of 0.25° × 0.25°. The ECMWF datasets for the selected days were employed to derive the moisture flux divergence, wind shear, and wind convergence. The derived meteorological parameters and the CAPE were spatially analyzed and superimposed on the precipitation obtained from the satellite data. The mean moisture flux and CAPE for some northern Nigerian stations were also plotted for 3 days prior to and 3 days after the storm. The result showed that HMFD and CAPE increased few days before the storm and peak on the day of the storms, and then declined afterwards. HMFD values above 1.0 × 10−6 g kg−1 s−1 is capable of producing substantial amount of rainfall mostly above 50 mm while wind shear has a much weaker impact on higher rainfall amount than moisture availability. CAPE above 1000 Jkg−1 and 1500 Jk−1 are favorable for convection over the southern and northern Nigeria, respectively. The study recommends quantitative analysis of moisture flux as a valuable short-term severe storm predictor and should be considered in the prediction of extreme rainfall.
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Olaniyan, Olumide A., Vincent O. Ajayi, Kamoru A. Lawal, and Ugbah Paul Akeh. "Impact of Moisture Flux and Vertical Wind Shear on Forecasting Extreme Rainfall Events in Nigeria." In African Handbook of Climate Change Adaptation. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_98.

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AbstractThis chapter investigates extreme rainfall events that caused flood during summer months of June–September 2010–2014. The aim is to determine the impact of horizontal moisture flux divergence (HMFD) and vertical wind shear on forecasting extreme rainfall events over Nigeria. Wind divergence and convective available potential energy (CAPE) were also examined to ascertain their threshold values during the events. The data used include rainfall observation from 40 synoptic stations across Nigeria, reanalyzed datasets from ECMWF at 0.125° × 0.125° resolution and the Tropical Rainfall Measuring Mission (TRMM) dataset at resolution of 0.25° × 0.25°. The ECMWF datasets for the selected days were employed to derive the moisture flux divergence, wind shear, and wind convergence. The derived meteorological parameters and the CAPE were spatially analyzed and superimposed on the precipitation obtained from the satellite data. The mean moisture flux and CAPE for some northern Nigerian stations were also plotted for 3 days prior to and 3 days after the storm. The result showed that HMFD and CAPE increased few days before the storm and peak on the day of the storms, and then declined afterwards. HMFD values above 1.0 × 10−6 g kg−1 s−1 is capable of producing substantial amount of rainfall mostly above 50 mm while wind shear has a much weaker impact on higher rainfall amount than moisture availability. CAPE above 1000 Jkg−1 and 1500 Jk−1 are favorable for convection over the southern and northern Nigeria, respectively. The study recommends quantitative analysis of moisture flux as a valuable short-term severe storm predictor and should be considered in the prediction of extreme rainfall.
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Caluña, Giovanny, Lorena Guachi-Guachi, and Ramiro Brito. "Convolutional Neural Networks for Automatic Classification of Diseased Leaves: The Impact of Dataset Size and Fine-Tuning." In Computational Science and Its Applications – ICCSA 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58799-4_68.

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Mendez, Mauro, Saul Calderon, and Pascal N. Tyrrell. "Using Cluster Analysis to Assess the Impact of Dataset Heterogeneity on Deep Convolutional Network Accuracy: A First Glance." In Communications in Computer and Information Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41005-6_21.

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Conference papers on the topic "Dataset IMPACT"

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Papadopoulos, Christos, Stefan Pletschacher, Christian Clausner, and Apostolos Antonacopoulos. "The IMPACT dataset of historical document images." In the 2nd International Workshop. ACM Press, 2013. http://dx.doi.org/10.1145/2501115.2501130.

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Vercosa, Luiz Felipe, Rodrigo Lira, Rodrigo Monteiro, et al. "Impact of Unusual Features in Credit Scoring Problem." In Symposium on Knowledge Discovery, Mining and Learning. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/kdmile.2020.11962.

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Standard features used for Credit Scoring includes mainly registration and financial data from customers. However, exploring new features is of great interest for financial companies, since slight improvements in the person score directly impact the company revenue. In this work, we categorize features from open credit scoring datasets and compare them with the features found in a real company dataset. The company dataset contains unusual feature groups such as historical, geolocation, web behavior, and demographic data. We performed bivariate tests using the Kolmogorov-Smirnov metric and feat
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Murray, Hazel, and David Malone. "Exploring the Impact of Password Dataset Distribution on Guessing." In 2018 16th Annual Conference on Privacy, Security and Trust (PST). IEEE, 2018. http://dx.doi.org/10.1109/pst.2018.8514194.

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Ohira, Masao, Yutaro Kashiwa, Yosuke Yamatani, et al. "A Dataset of High Impact Bugs: Manually-Classified Issue Reports." In 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories (MSR). IEEE, 2015. http://dx.doi.org/10.1109/msr.2015.78.

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Vergoulis, Thanasis, Ilias Kanellos, Claudio Atzori, et al. "BIP! DB: A Dataset of Impact Measures for Scientific Publications." In WWW '21: The Web Conference 2021. ACM, 2021. http://dx.doi.org/10.1145/3442442.3451369.

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Sharma, D. K. "Information Measure Computation and its Impact in MI COCO Dataset." In 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2021. http://dx.doi.org/10.1109/icaccs51430.2021.9441788.

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Jain, Mayank, Mukta Jain, Tarek AlSkaif, and Soumyabrata Dev. "Impact of Load Demand Dataset Characteristics on Clustering Validation Indices." In 2021 International Conference on Smart Energy Systems and Technologies (SEST). IEEE, 2021. http://dx.doi.org/10.1109/sest50973.2021.9543285.

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Yilmaz, Bedir, Mehmet Fatih Amasyali, Muhammet Balcilar, Erkan Uslu, and Sirma Yavuz. "Impact of artificial dataset enlargement on performance of deformable part models." In 2016 24th Signal Processing and Communication Application Conference (SIU). IEEE, 2016. http://dx.doi.org/10.1109/siu.2016.7495710.

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Tourancheau, Sylvain, Florent Autrusseau, Z. M. Parvez Sazzad, and Yuukou Horita. "Impact of subjective dataset on the performance of image quality metrics." In 2008 15th IEEE International Conference on Image Processing. IEEE, 2008. http://dx.doi.org/10.1109/icip.2008.4711767.

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Barros, Pablo, Nikhil Churamani, Angelica Lim, and Stefan Wermter. "The OMG-Empathy Dataset: Evaluating the Impact of Affective Behavior in Storytelling." In 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII). IEEE, 2019. http://dx.doi.org/10.1109/acii.2019.8925530.

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Reports on the topic "Dataset IMPACT"

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Gao, Xin, Aiko Kikkawa, and Jong Woo Kang. Evaluating the Impact of Remittances on Human Capital Investment in the Kyrgyz Republic. Asian Development Bank, 2021. http://dx.doi.org/10.22617/wps210189-2.

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Remittances from overseas can encourage human capital investment, but empirical studies have shown mixed evidence. This paper uses a 5-year panel dataset in the Kyrgyz Republic to examine the impact of remittances on the human capital formation of school-age children. After correcting for endogeneities with instrumental variables, the study finds that remittances have negative impacts on educational achievement. Extended hours of farm labor by children and increased expenditure on durable goods are identified among recipient households. To mitigate negative effects of remittances on children’s
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Avellán, Leopoldo, Claudia Calderón, Giulia Lotti, and Z’leste Wanner. Knowledge for Development: the IDB's Impact in the Region. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003387.

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By analyzing a novel dataset on publications by the Inter-American Development Bank (IDB), we shed light on the extent to which the knowledge production of a multilateral development bank can reach its beneficiaries. We find that IDB publications are downloaded mostly in the American continent, with Colombia, Peru, Mexico and the United States leading the ranking. Moreover, during the COVID-19 pandemic downloads of IDB publications increased, both in the world and in Latin America and the Caribbean. Some characteristics of publications are significantly associated with higher numbers of downlo
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Park, Donghyun, Arief Ramayandi, and Shu Tian. Debt Buildup and Currency Vulnerability: Evidence from Global Markets. Asian Development Bank, 2020. http://dx.doi.org/10.22617/wps200289-2.

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In this study, we examine how public and private debt buildup is related to currency depreciation pressure. Our empirical analysis of a panel dataset of 59 advanced and emerging markets reveals that both private and public debt exacerbate currency vulnerability. However, the evidence of a significant effect on currency depreciation pressure is more robust and consistent for private debt than public debt. Furthermore, we find that excessive private debt buildup can be particularly harmful in emerging markets. In addition, our evidence suggests that greater dependence on external financing exace
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Ayala-García, Jhorland, Sandy Dall'erba, and William C. Ridley. Externalities of extreme natural disasters on local tax capacity. Banco de la República de Colombia, 2021. http://dx.doi.org/10.32468/dtseru.299.

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This paper studies the impact of extreme weather events on the local tax revenue across Colombian municipalities. We follow a two-step approach to evaluate to what extent a municipality’s tax revenue depends on natural disasters taking place both locally and in its trade partners. In the first step, we estimate a gravity model of bilateral trade and construct a trade flow matrix allowing us to measure the strength of the economic relationships between cities. To do so, we build a novel dataset describing the inter-city trade flows for road transported goods in Colombia for the period 2015–2019
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Ahumada, Hildegart, Eduardo A. Cavallo, Santos Espina-Mairal, and Fernando Navajas. Sectoral Productivity Growth, COVID-19 Shocks, and Infrastructure. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003411.

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This paper examines sectoral productivity shocks of the COVID-19 pandemic, their aggregate impact, and the possible compensatory effects of improving productivity in infrastructure-related sectors. We employ the KLEMS annual dataset for a group of OECD and Latin America and the Caribbean countries, complemented with high-frequency data for 2020. First, we estimate a panel vector autoregression of growth rates in sector level labor productivity to specify the nature and size of sectoral shocks using the historical data. We then run impulse-response simulations of one standard deviation shocks i
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Dawson, Samantha, Luke Wallace, and Baskaran Sundaram. Catalogue of Timor-Leste datasets and data records: vulnerability assessment of climate change impacts on groundwater resources in Timor-Leste. Geoscience Australia, 2012. http://dx.doi.org/10.11636/record.2012.056.

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Beuermann, Diether, Nicolas L. Bottan, Bridget Hoffmann, Jeetendra Khadan, and Diego A. Vera-Cossio. Suriname COVID-19 Survey. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003266.

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This dataset constitutes a panel follow-up to the 2016/2017 Suriname Survey of Living Conditions. It measures welfare related variables before and after the onset of the COVID-19 pandemic including labor market outcomes, financial literacy, and food security. The survey was executed in August 2020. The Suriname COVID-19 Survey is a project of the Inter-American Development Bank (IDB). It collected data on critical socioeconomic topics in the context of the COVID-19 pandemic to support policymaking and help mitigate the crisis impacts on the populations welfare. The survey recontacted household
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Tennant, David. Business Surveys on the Impact of COVID-19 on Jamaican Firms. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003251.

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The datasets come from two surveys of Jamaican businesses conducted between May and June 2020. Two sets of self-administered surveys were conducted using Survey Monkey. A very small sample of financial institutions was surveyed to gain perspective on the challenges facing financiers as a result of the pandemic, and their efforts to respond to such challenges. Nine financial institutions completed this survey, and the results were used to complement the information derived from the second and major survey. The second survey targeted non-financial businesses operating in Jamaica. The sample of f
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Alviarez, Vanessa, Michele Fioretti, Ken Kikkawa, and Monica Morlacco. Two-Sided Market Power in Firm-to-Firm Trade. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003493.

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Firms in global value chains (GVCs) are granular and exert bargaining power over the terms of trade. We show that these features are crucial to understanding the well-established variation in prices and pass-through across importers and exporters. We develop a novel theory of prices in GVCs, which tractably nests a wide range of bilateral concentration and bargaining power configurations. We test and evaluate the models predictions using a novel dataset merging transaction-level U.S. import data with balance sheet data for both U.S. importers and foreign exporters. Our pricing framework enhanc
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Michalak, Julia, Josh Lawler, John Gross, and Caitlin Littlefield. A strategic analysis of climate vulnerability of national park resources and values. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2287214.

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The U.S. national parks have experienced significant climate-change impacts and rapid, on-going changes are expected to continue. Despite the significant climate-change vulnerabilities facing parks, relatively few parks have conducted comprehensive climate-change vulnerability assessments, defined as assessments that synthesize vulnerability information from a wide range of sources, identify key climate-change impacts, and prioritize vulnerable park resources (Michalak et al. In review). In recognition that funding and planning capacity is limited, this project was initiated to identify geogra
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