Academic literature on the topic 'Aggregated data'

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Journal articles on the topic "Aggregated data"

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HASSANI, HOSSEIN, ABDOL SOOFI, and MOHAMMAD SADEGH AVAZALIPOUR. "FORECASTING GDP WITH AGGREGATED AND SECTORAL DATA." Fluctuation and Noise Letters 10, no. 03 (2011): 249–65. http://dx.doi.org/10.1142/s0219477511000533.

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We use the Singular Spectrum Analysis (SSA), a forecasting method which is based on the noise reduction procedure, in prediction of the Iranian gross domestic product (GDP). Two different approaches are considered in forecasting the series. In the first approach, we apply SSA to the aggregate GDP series. In the second approach, we predict the GDP by first forecasting the GDP of the sectors of the economy, and then sum the predicted values as the forecast of the aggregate GDP. We measured the prediction accuracy of both approaches using various criteria, and found that predictions based on the
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Jarjoura, D. "Inferences from Aggregated Data." Academic Emergency Medicine 10, no. 8 (2003): 881–82. http://dx.doi.org/10.1197/aemj.10.8.881.

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Aadland, David. "Detrending time-aggregated data." Economics Letters 89, no. 3 (2005): 287–93. http://dx.doi.org/10.1016/j.econlet.2005.06.001.

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Toth, Daniell. "Data Smearing: An Approach to Disclosure Limitation for Tabular Data." Journal of Official Statistics 30, no. 4 (2014): 839–57. http://dx.doi.org/10.2478/jos-2014-0050.

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Abstract Statistical agencies often collect sensitive data for release to the public at aggregated levels in the form of tables. To protect confidential data, some cells are suppressed in the publicly released data. One problem with this method is that many cells of interest must be suppressed in order to protect a much smaller number of sensitive cells. Another problem is that the covariates used to aggregate and level of aggregation must be fixed before the data is released. Both of these restrictions can severely limit the utility of the data. We propose a new disclosure limitation method t
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Seater, John J. "TESTING THE PERMANENT-INCOME/LIFE-CYCLE HYPOTHESIS WITH AGGREGATE DATA." Macroeconomic Dynamics 2, no. 3 (1998): 401–25. http://dx.doi.org/10.1017/s1365100598008062.

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The aggregate implications of the permanent-income/life-cycle hypothesis (PILCH) are derived rigorously. Virtually all empirical rejections of PILCH based on aggregated data are shown to result from misspecifications or from characteristics of aggregate data that have been overlooked. Valid aggregate tests are proposed. Those based on a properly formulated aggregate consumption function may be superior to those based on Euler-equation methods.
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Gelsema, Tjalling. "The Logic of Aggregated Data." Acta Cybernetica 24, no. 2 (2019): 211–48. http://dx.doi.org/10.14232/actacyb.24.2.2019.4.

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A notion of generalization-specialization is introduced that is more expressive than the usual notion from, e.g., the UML or RDF-based languages. This notion is incorporated in a typed formal language for modeling aggregated data. Soundness with respect to a sets-and-functions semantics is shown subsequently. Finally, a notion of congruence is introduced. With it terms in the language that have identical semantics, i.e., synonyms, can be discovered. The resulting formal language is well-suited for capturing faithfully aggregated data in such a way that it can serve as the foundation for corpor
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Linton, Oliver, and Yoon-Jae Whang. "NONPARAMETRIC ESTIMATION WITH AGGREGATED DATA." Econometric Theory 18, no. 2 (2002): 420–68. http://dx.doi.org/10.1017/s0266466602182089.

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We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intrafamily component but require that observations from different families be independent. We establish consistency and asymptotic normality for our procedures. As usual, the rates of convergence can be very slow depending on the behavior of the characteristic function at infinity. We investigate the practical performance of our method in a simple Monte Carlo experiment.
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Bowman, K. O., and M. A. Kastenbaum. "Overdispersion of aggregated genetic data." Mutation Research/Environmental Mutagenesis and Related Subjects 272, no. 2 (1992): 133–37. http://dx.doi.org/10.1016/0165-1161(92)90041-j.

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Nicoletti, Cheti, and Nicky Best. "Quantile regression with aggregated data." Economics Letters 117, no. 2 (2012): 401–4. http://dx.doi.org/10.1016/j.econlet.2012.06.011.

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Hu, Jinyu, Juan Luo, Yuxi Zhang, Panwu Wang, and Yu Liu. "Location-Based Data Aggregation in 6LoWPAN." International Journal of Distributed Sensor Networks 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/912926.

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Location-based information has recently been exploited to assist the aggregated process of data, thereby reducing the spatial redundancy efficiently. The constraints nature in 6LoWPAN becomes one of the major concerns in data aggregation methods. However, traditional CSMA/CA in MAC layer may cause significant transmission and control overhead as well as delay on listening and competing for channels. It is a low efficient way to transfer IPv6 packet due to the big packet header. To overcome these shortages, in this paper, we propose LDAA, a location-based novel data aggregation model that aggre
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Dissertations / Theses on the topic "Aggregated data"

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Tanaka, Yusuke. "Probabilistic Models for Spatially Aggregated Data." Kyoto University, 2020. http://hdl.handle.net/2433/253422.

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Mouhoub, Mohamed Lamine. "Aggregated Search of Data and Services." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLED066/document.

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Ces dernières années ont témoigné du succès du projet Linked Open Data (LOD) et de la croissance du nombre de sources de données sémantiques disponibles sur le web. Cependant, il y a encore beaucoup de données qui ne sont pas encore mises à disposition dans le LOD telles que les données sur demande, les données de capteurs etc. Elles sont néanmoins fournies par des API des services Web. L'intégration de ces données au LOD ou dans des applications de mashups apporterait une forte valeur ajoutée. Cependant, chercher de tels services avec les outils de découverte de services existants nécessite u
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Samita, Sembakutti. "Analysis of aggregated plant disease incidence data." Thesis, University of Edinburgh, 1995. http://hdl.handle.net/1842/27331.

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If diseased plants (or plant units) are randomly dispersed, the frequency distribution of diseased plants (or plant units) per sample may be described by a binomial distribution, and statistical analyses may be based on the linear logistic model. Since most disease incidence data do not have a random spatial pattern, the binomial distribution can hardly ever, in practice, be used to describe observed frequencies. In this study, the use of conditional probability distributions, such as the logistic-normal binomial distribution, for such data is illustrated. Both descriptive distribution fitting
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Rastogi, Tanay. "Load Identification from Aggregated Data using Generative Modeling." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249599.

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In the view of an exponential increase in demand for energy, there is a need to come up with a sustainable energy consumption system in residential buildings. Several pieces of research show that this can be achieved by providing real-time energy consumption feedback of each appliance to its residents. This can be achieved through Non-Intrusive Load Monitoring System (NILM) that disaggregates the electricity consumption of individual appliances from the total energy consumption of a household. The state-of-art NILM have several challenges that preventing its large-scale implementation due to i
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Folia, Maria Myrto. "Inference in stochastic systems with temporally aggregated data." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/inference-in-stochastic-systems-with-temporally-aggregated-data(17940c86-e6b3-4f7d-8a43-884bbf72b39e).html.

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The stochasticity of cellular processes and the small number of molecules in a cell make deterministic models inappropriate for modelling chemical reactions at the single cell level. The Chemical Master Equation (CME) is widely used to describe the evolution of biochemical reactions inside cells stochastically but is computationally expensive. The Linear Noise Approximation (LNA) is a popular method for approximating the CME in order to carry out inference and parameter estimation in stochastic models. Data from stochastic systems is often aggregated over time. One such example is in luminesce
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Davis, Brett Andrew, and Brett Davis@abs gov au. "Inference for Discrete Time Stochastic Processes using Aggregated Survey Data." The Australian National University. Faculty of Economics and Commerce, 2003. http://thesis.anu.edu.au./public/adt-ANU20040806.104137.

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We consider a longitudinal system in which transitions between the states are governed by a discrete time finite state space stochastic process X. Our aim, using aggregated sample survey data of the form typically collected by official statistical agencies, is to undertake model based inference for the underlying process X. We will develop inferential techniques for continuing sample surveys of two distinct types. First, longitudinal surveys in which the same individuals are sampled in each cycle of the survey. Second, cross-sectional surveys which sample the same population in successive cycl
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Marklund, Emil. "Bayesian inference in aggregated hidden Markov models." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-243090.

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Single molecule experiments study the kinetics of molecular biological systems. Many such studies generate data that can be described by aggregated hidden Markov models, whereby there is a need of doing inference on such data and models. In this study, model selection in aggregated Hidden Markov models was performed with a criterion of maximum Bayesian evidence. Variational Bayes inference was seen to underestimate the evidence for aggregated model fits. Estimation of the evidence integral by brute force Monte Carlo integration theoretically always converges to the correct value, but it conver
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Broc, Camilo. "Variable selection for data aggregated from different sources with group of variable structure." Thesis, Pau, 2019. http://www.theses.fr/2019PAUU3048.

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Durant les dernières décennies, la quantité de données disponibles en génétique a consi-dérablement augmenté. D’une part, une amélioration des technologies de séquençage demolécules a permis de réduire fortement le coût d’extraction du génome humain. D’autrepart, des consortiums internationaux d’institutions ont permis la mise en commun de lacollecte de données sur de larges populations. Cette quantité de données nous permetd’espérer mieux comprendre les mécanismes régissant le fonctionnement de nos cellules.Dans ce contexte, l’épidémiologie génétique est un domaine cherchant à déterminer lare
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Molitor, Torsten. "Coverage Prediction for Inter-Frequency Handover using Machine Learning with Aggregated Training Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-286676.

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An important application of Machine Learning (ML) in mobile networks is to predict if a user device has coverage on a frequency other than the current serving frequency. This is a use-case called Secondary Carrier Prediction (SCP). In this thesis we deduce if data across different cells and frequencies can be successfully combined when learning this task, thus reducing the number of models that require training. Aggregation of data involves several challenges, such as different prevalences and varying amounts of available data, but more importantly the possibility of achieving synergies in tra
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MacKelvie, Erin. "A Comparison of Traditional Aggregated Data to a Comprehensive Second-by-Second Data Depiction in Functional Analysis Graphs." Scholarly Commons, 2021. https://scholarlycommons.pacific.edu/uop_etds/3730.

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Functional analyses (FAs) are an important component of treatment and the data gathered from FAs are often graphed in an aggregate or summary format, such as mean rate per session. Given the prevalence of undifferentiated analyses, it may be that this common method of data depiction is incomplete. In this paper, we compare the traditional aggregate method to a comprehensive second-by-second demonstration of the data including all appropriate and inappropriate responses emitted, as well as programmed and accidental antecedent and consequent variables, which may help further clarify the results
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Books on the topic "Aggregated data"

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Ferguson, Walter L. Pesticide use on selected crops: Aggregated data, 1977-80. U.S. Dept. of Agriculture, Economic Research Service, 1985.

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Ferguson, Walter L. Pesticide use on selected crops: Aggregated data, 1977-80. U.S. Dept. of Agriculture, Economic Research Service, 1985.

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United States. Dept. of Agriculture. Economic Research Service., ed. Pesticide use on selected crops: Aggregated data, 1977-80. U.S. Dept. of Agriculture, Economic Research Service, 1985.

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Ferguson, Walter L. Pesticide use on selected crops: Aggregated data, 1977-80. U.S. Dept. of Agriculture, Economic Research Service, 1985.

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Hildén, Jonatan, and Laura Koivunen-Niemi. Learn to Create a Visualization of Aggregated Time Data in Python With Data From ACEA (2020). SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529605211.

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Adamson, Christopher. Mastering Data Warehouse Aggregates. John Wiley & Sons, Ltd., 2006.

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Bagnoli, Luca, and Massimo Cini, eds. La cooperazione sociale nell'area metropolitana fiorentina. Firenze University Press, 2009. http://dx.doi.org/10.36253/978-88-8453-415-6.

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This study proposes a reading of the financial statements of co-operatives operating within the Florentine metropolitan area, with a view to underscoring business aspects of a quantitative and monetary nature. The entrepreneurial nature of the co-operatives is taken as read, focusing as with any other corporate entity on assets and economic results as indicators of success. The financial statements were collected from co-operatives with their registered offices in the provinces of Florence, Prato and Pistoia for the financial years 2004-2007, and the accounts were then aggregated, reclassified
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Bayoumi, Tamim A. Estimating trade equations from aggregate bilateral data. International Monetary Fund, Asia and Pacific Department, 1999.

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Vasconcellos, Klaus Leite Pinto. Aspects of forecasting aggregate and discrete data. typescript, 1992.

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FGBOU, VO. Digital analytics and financial security control of socially significant organizations. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1863937.

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The monograph is devoted to the formation of the concept of digital financial security analytics. The use of the digital environment and big data analysis tools in the system of monitoring sectoral risks and monitoring the activities of socially significant organizations from the position of the ESG strategy is disclosed. At the same time, financial security is considered as an aggregated result of the action of economic, environmental and social factors in a rapidly changing economy.
 It covers several key areas that make it possible to digitalize and improve the effectiveness of monitor
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Book chapters on the topic "Aggregated data"

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Zimmermann, Albrecht, and Björn Bringmann. "Aggregated Subset Mining." In Advances in Knowledge Discovery and Data Mining. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01307-2_66.

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Chen, Qixin, Hongye Guo, Kedi Zheng, and Yi Wang. "Aggregated Supply Curves Forecasting." In Data Analytics in Power Markets. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4975-2_11.

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Buchin, Kevin, Maike Buchin, Marc van Kreveld, Maarten Löffler, Jun Luo, and Rodrigo I. Silveira. "Clusters in Aggregated Health Data." In Headway in Spatial Data Handling. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-68566-1_5.

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Huo, Xiaoming, Cheng Huang, and Xuelei Sherry Ni. "Scattered Data and Aggregated Inference." In Handbook of Big Data Analytics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-18284-1_4.

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Acs, Gergely, Szilvia Lestyán, and Gergely Biczók. "Privacy of Aggregated Mobility Data." In Encyclopedia of Cryptography, Security and Privacy. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-642-27739-9_1575-1.

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Wang, Yi, Qixin Chen, and Chongqing Kang. "Aggregated Load Forecasting with Sub-profiles." In Smart Meter Data Analytics. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2624-4_12.

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Aimoto, Yoshifumi, and Hisashi Kashima. "Matrix Factorization With Aggregated Observations." In Advances in Knowledge Discovery and Data Mining. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37456-2_44.

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Bayliss, David. "Aggregated Data Analysis in HPCC Systems." In Big Data Technologies and Applications. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44550-2_8.

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Wojtusiak, Janusz, and Ancha Baranova. "Model Learning from Published Aggregated Data." In Learning Structure and Schemas from Documents. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22913-8_17.

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Canonne, Clément, and Ronitt Rubinfeld. "Testing Probability Distributions Underlying Aggregated Data." In Automata, Languages, and Programming. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43948-7_24.

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Conference papers on the topic "Aggregated data"

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Bax, Eric, and Charlotte Bax. "SAFE – Secure Aggregated Frequency Estimates." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9378135.

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Andrews, Keith, Majda Osmić, and Gerhard Schagerl. "Aggregated parallel coordinates." In i-KNOW '15: 15th International Conference on Knowledge Technologies and Data-Driven Business. ACM, 2015. http://dx.doi.org/10.1145/2809563.2809588.

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Wallner, Günter, Nour Halabi, and Pejman Mirza-Babaei. "Aggregated Visualization of Playtesting Data." In CHI '19: CHI Conference on Human Factors in Computing Systems. ACM, 2019. http://dx.doi.org/10.1145/3290605.3300593.

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Rubin, Andee. "Using Data for Good: A Matter of Geography." In Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. International Association for Statistical Education, 2022. http://dx.doi.org/10.52041/iase.icots11.t2i2.

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The purpose of this research is to learn how youth aged 11–14 understand highly aggregated data about social and economic conditions, especially related to the United Nations Sustainable Development Goals. We designed an after-school program that introduces students to data broadly in the context of “using data for social good.” Using CODAP, an educational data visualization tool, students explore data about countries’ health and education indicators. We observe that youth are highly engaged with these data yet sometimes struggle to make sense of the aggregate values that hide variability with
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Kristiansen, Raymond, and Chris Petrich. "Extracting human capital from aggregated data." In 2016 International Symposium on Small-scale Intelligent Manufacturing Systems (SIMS). IEEE, 2016. http://dx.doi.org/10.1109/sims.2016.7802898.

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Kaaniche, Nesrine, Eunjin Jung, and Ashish Gehani. "Efficiently Validating Aggregated IoT Data Integrity." In 2018 IEEE Fourth International Conference on Big Data Computing Service and Applications (BigDataService). IEEE, 2018. http://dx.doi.org/10.1109/bigdataservice.2018.00046.

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"AGGREGATED ACCOUNTING OF MEMORY USAGE IN JAVA." In 4th International Conference on Software and Data Technologies. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0002253701770185.

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Jung, Soon-Gyo, Jisun An, Haewoon Kwak, Moeed Ahmad, Lene Nielsen, and Bernard J. Jansen. "Persona Generation from Aggregated Social Media Data." In CHI '17: CHI Conference on Human Factors in Computing Systems. ACM, 2017. http://dx.doi.org/10.1145/3027063.3053120.

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Mikhalskii, A. I., V. P. Gorlischev, D. A. Jdanov, and P. Grigoriev. "Splitting of aggregated medical and demographic data." In 2017 IEEE 11th International Conference on Application of Information and Communication Technologies (AICT). IEEE, 2017. http://dx.doi.org/10.1109/icaict.2017.8686994.

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Woodbridge, Jonathan, Bobak Mortazavi, Majid Sarrafzadeh, and Alex A. T. Bui. "Aggregated Indexing of Biomedical Time Series Data." In 2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology (HISB). IEEE, 2012. http://dx.doi.org/10.1109/hisb.2012.13.

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Reports on the topic "Aggregated data"

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Breza, Emily, Arun Chandrasekhar, Tyler McCormick, and Mengjie Pan. Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data. National Bureau of Economic Research, 2017. http://dx.doi.org/10.3386/w23491.

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Garrett, Thomas A. Aggregated vs. Disaggregated Data in Regression Analysis: Implications for Inference. Federal Reserve Bank of St. Louis, 2002. http://dx.doi.org/10.20955/wp.2002.024.

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van der Sloot, Bart. The Quality of Life: Protecting Non-personal Interests and Non-personal Data in the Age of Big Data. Universitätsbibliothek J. C. Senckenberg, Frankfurt am Main, 2021. http://dx.doi.org/10.21248/gups.64579.

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Under the current legal paradigm, the rights to privacy and data protection provide natural persons with subjective rights to protect their private interests, such as related to human dignity, individual autonomy and personal freedom. In principle, when data processing is based on non-personal or aggregated data or when such data pro- cesses have an impact on societal, rather than individual interests, citizens cannot rely on these rights. Although this legal paradigm has worked well for decades, it is increasingly put under pressure because Big Data processes are typically based indis- crimin
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Bond, W., Maria Seale, and Jeffrey Hensley. A dynamic hyperbolic surface model for responsive data mining. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/43886.

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Data management systems impose structure on data via a static representation schema or data structure. Information from the data is extracted by executing queries based on predefined operators. This paradigm restricts the searchability of the data to concepts and relationships that are known or assumed to exist among the objects. While this is an effective and efficient means of retrieving simple information, we propose that such a structure severely limits the ability to derive breakthrough knowledge that exists in data under the guise of “unknown unknowns.” A dynamic system will alleviate th
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Snyder, Victor A., Dani Or, Amos Hadas, and S. Assouline. Characterization of Post-Tillage Soil Fragmentation and Rejoining Affecting Soil Pore Space Evolution and Transport Properties. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7580670.bard.

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Tillage modifies soil structure, altering conditions for plant growth and transport processes through the soil. However, the resulting loose structure is unstable and susceptible to collapse due to aggregate fragmentation during wetting and drying cycles, and coalescense of moist aggregates by internal capillary forces and external compactive stresses. Presently, limited understanding of these complex processes often leads to consideration of the soil plow layer as a static porous medium. With the purpose of filling some of this knowledge gap, the objectives of this Project were to: 1) Identif
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Cavalli, Nicolò. Future orientation and fertility: cross-national evidence using Google search. Verlag der Österreichischen Akademie der Wissenschaften, 2020. http://dx.doi.org/10.1553/populationyearbook2020.res06.

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Using digital traces to investigate demographic behaviours, I leverage in this paper aggregated web search data to develop a Future Orientation Index for 200 countries and territories across the world. This index is expressed as the ratio of Google search volumes for ‘next year’ (e.g., 2021) to search volumes for ‘current year’ (e.g., 2020), adjusted for country-level internet penetration rates. I show that countries with lower levels of future orientation also have higher levels of fertility. Fertility rates decrease quickly as future orientation levels increase; but at the highest levels of
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Beaulieu, J. Joseph, and Jeffrey Miron. Seasonal Unit Roots in Aggregate U.S. Data. National Bureau of Economic Research, 1992. http://dx.doi.org/10.3386/t0126.

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Vecherin, Sergey, Derek Chang, Emily Wells, et al. Assessment of the COVID-19 infection risk at a workplace through stochastic microexposure modeling. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/43740.

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The COVID-19 pandemic has a significant impact on economy. Decisions regarding the reopening of businesses should account for infection risks. This paper describes a novel model for COVID-19 infection risks and policy evaluations. The model combines the best principles of the agent-based, microexposure, and probabilistic modeling approaches. It takes into account specifics of a workplace, mask efficiency, and daily routines of employees, but does not require specific interagent rules for simulations. Likewise, it does not require knowledge of microscopic disease related parameters. Instead, th
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Petrin, Amil, and James Levinsohn. Measuring Aggregate Productivity Growth Using Plant-Level Data. National Bureau of Economic Research, 2005. http://dx.doi.org/10.3386/w11887.

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Bachmann, Rüdiger, and Peter Zorn. What Drives Aggregate Investment? Evidence from German Survey Data. National Bureau of Economic Research, 2013. http://dx.doi.org/10.3386/w18990.

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