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Privacy Preserving OLAP over Distributed XML Data: A Theoretically-Sound Secure-Multiparty-Computation Approach

Alfredo Cuzzocrea, Elisa Bertino
2011 Journal of computer and system sciences (Print)  
The framework has many novel features ranging from nice theoretical properties to an effective and efficient protocol, called Secure Distributed OLAP aggregation protocol (SDO).  ...  In order to fulfill this gap, we propose a novel Secure Multiparty Computation (SMC)-based privacy preserving OLAP framework for distributed collections of XML documents.  ...  ii) the definition of a novel task for Privacy Preserving Distributed Data Mining tailored to OLAP over distributed XML documents, called secure distributed OLAP aggregation task; (iii) an innovative approach  ... 
doi:10.1016/j.jcss.2011.02.004 fatcat:ut45awj5qfayzmagxwiq4g5fga

A novel approach for approximate aggregations over arrays

Yi Wang, Yu Su, Gagan Agrawal
2015 Proceedings of the 27th International Conference on Scientific and Statistical Database Management - SSDBM '15  
Data -Sample-Based • Unable to capture both distributions -Histogram-Based • No spatial distribution -Wavelet-Based • No value distribution (by mapping a data cube to an array) • Restricted to SUM, COUNT  ...  can be found in histogram literature A Novel Binning Strategy • Conventional Binning Strategies -Equi-width/equi-depth binning -Not necessarily a good approximation • V-Optimized Binning Strategy  ... 
doi:10.1145/2791347.2791349 dblp:conf/ssdbm/WangSA15 fatcat:kp756sz4a5c4fi2fcimi5qkhne

Robust nuclear signal reconstruction by a novel ensemble model aggregation procedure

P. Baraldi, E. Zio, G. Gola, D. Roverso, M. Hoffmann
2010 International Journal of Nuclear Knowledge Management  
In this work, three different methods for aggregating the model outcomes are investigated and a novel procedure is proposed for obtaining robust ensembleaggregated outputs.  ...  Each model in the ensemble handles a small group of signals and the outcomes of all models are eventually combined to provide the final outcome.  ...  A novel procedure based on the combination of the MD and TM aggregation approaches is then proposed.  ... 
doi:10.1504/ijnkm.2010.031153 fatcat:ctyhekyqzrbndb5ttbjgvatcuu

Estimating Aggregate Properties In Relational Networks With Unobserved Data [article]

Varun Embar, Sriram Srinivasan, Lise Getoor
2020 arXiv   pre-print
To compute the expectation tractably for probabilistic soft logic, one of the SRL approaches that we study, we introduce a novel sampling framework.  ...  For SRL-based approaches that can infer a joint distribution over the missing attributes, we also estimate these properties as an expectation over the distribution.  ...  Another approach, which we refer to as the Expected Aggregate approach, is to model the unobserved attributes as RVs, define a joint probability distribution over them, and take the expectation of the  ... 
arXiv:2001.05617v2 fatcat:bgs7j6hbmvashmyafj7amc6e54

Bayesian aggregation of expert judgment data for quantification of human failure probabilities for radiotherapy [chapter]

L. Podofillini, D. Pandya, F. Emert, A.J. Lomax, V.N. Dang, G. Sansavini
2018 Safety and Reliability – Safe Societies in a Changing World  
A Bayesian aggregation model is used to aggregate the judgments collected during elicitation sessions with domain experts.  ...  The probabilities are used as input for the development of a Human Reliability Analysis (HRA) method specific for radiotherapy.  ...  The authors would also like to thank the personnel working at PSI's CPT for their cooperation and support.  ... 
doi:10.1201/9781351174664-62 fatcat:cy2tyelrfjebfl7enbcwcuegci

General Supervision via Probabilistic Transformations [article]

Santiago Mazuelas, Aritz Perez
2019 arXiv   pre-print
The results show that GRRM can handle different types of training data in a unified manner, and enable new supervision schemes that aggregate general ensembles of training data.  ...  Different types of training data have led to numerous schemes for supervised classification.  ...  Since the probability distribution of test variables is unknown, expected losses are evaluated with respect to a surrogate probability distribution obtained from training data.  ... 
arXiv:1901.08552v1 fatcat:xafqsvg54zeu5i4bnvhuwzajpe

Long Tail Uncertainty Distributions in Novel Risk Probability Classification

O. Schwabe, E. Shehab, J. Erkoyuncu
2015 Procedia CIRP  
Future research is recommended to identify relevant parametric risk probability variable (relationships) and to determine whether risk probability can be predicated.  ...  of probability in approx. 70% of aggregated risk profiles were identified, whereby approx. 40% of these exhibit long tail (leptokurtic) characteristics.  ...  Acknowledgements The authors would like to thank the Rolls-Royce plc. risk group and risk management community for data access and guidance in interpreting the data contained therein.  ... 
doi:10.1016/j.procir.2015.04.033 fatcat:5af4cvp4pvfyhicff2vynmhrh4

Page 141 of The Journal of Animal Ecology Vol. 75, Issue 1 [page]

2006 The Journal of Animal Ecology  
As & tends to infinity, the negative bino- mial describes a Poisson distribution. Based on the negative binomial distribution, the absence probability in a sample is p)(a) = (1 + ,/k)*.  ...  , is the mean abundance across sampling, k is a clumping parameter of the species’ distribution from highly aggregated at A =0 to random at k = +e (Wright 1991).  ... 

A Novel Technique for Link Recovery in Energy Efficient DRINA Protocol for Wireless Sensor Network

Mankirat Kaur, Anjana Sharma, Bhupinder Kaur
2016 IJARCCE  
In this paper, we are proposing a new technique on enhancement of DRINA protocol, to reduce battery consumption and recover link failure. It will be based on the static clustering using relay nodes.  ...  In these conditions, we focus to reduce the battery consumption of the sensor nodes.  ...  J 1 to N *compute probability of distribution of advance nodes from normal nodes* 6. J(A)  1 to J * compute probability of distribution of super nodes from advanced nodes* 7.  ... 
doi:10.17148/ijarcce.2016.5126 fatcat:2toyvmcq5bempekusq4bxbfk3e

Towards Enabling Probabilistic Databases for Participatory Sensing

Quoc Viet Hung Nguyen, Saket Sathe, Thang Duong, Karl Aberer
2014 Proceedings of the 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing  
This paradigm enables to collect a huge amount of data from the crowd for world-wide applications, without spending cost to buy dedicated sensors.  ...  We approach the problem in two steps. In the first step, we generate probabilistic times series from raw time series using a dynamical model from the time series literature.  ...  . • Section III: We adopt a novel approach to generate probabilistic time series from sensor data. This approach models a reading from each sensor by a probability distribution.  ... 
doi:10.4108/icst.collaboratecom.2014.257239 dblp:conf/colcom/HungSDA14 fatcat:ft7uuzxoxveurmrnpmxdcjtm2i

Non-parametric Depth Distribution Modelling based Depth Inference for Multi-view Stereo [article]

Jiayu Yang, Jose M. Alvarez, Miaomiao Liu
2022 arXiv   pre-print
In general, those approaches assume that the depth of each pixel follows a unimodal distribution.  ...  As we perform local search around these multiple hypotheses in subsequent levels, our approach does not maintain the rigid depth spatial ordering and, therefore, we introduce a sparse cost aggregation  ...  We address the second problem by a novel sparse cost volume formulation and a sparse cost aggregation network that retain rigid spatial relation. Multi-modal disparity distribution modeling.  ... 
arXiv:2205.03783v1 fatcat:siyzfen2zjdhflllwwcnf743pa

Guest editorial: special issue on ranking in databases

Ihab Ilyas
2009 Distributed and parallel databases  
This special issue of the Distributed and Parallel Databases solicited contributions that address novel and important challenges in supporting ranking in database systems.  ...  compute-then-sort approach.  ...  Rank aggregation in distributed environments The paper titled "Distributed Top-k Aggregation Queries at Large" focuses on optimizing top-k query processing algorithms in distributed environments.  ... 
doi:10.1007/s10619-009-7052-9 fatcat:gvbfloijajfqxjzsmcstvmcphi

Novel semi-automated fluorescence microscope imaging algorithm for monitoring IgG aggregates in serum

Shravan Sreenivasan, Deepak Sonawat, Shyamapada Mandal, Kedar Khare, Anurag S. Rathore
2021 Scientific Reports  
To overcome various complexities associated with the existing analytical techniques for analyzing aggregates in serum, a novel florescence microscopy-based image processing approach was developed.  ...  The proposed algorithm offers an approach for analysis of aggregates in serum that is simpler to implement and is complementary to existing approaches.  ...  Conclusions The role of a novel image processing algorithm to analyze fluorescence microscope images was shown to monitor the fate of aggregates of therapeutic IgG samples in serum.  ... 
doi:10.1038/s41598-021-90623-7 pmid:34059715 fatcat:xvlgh4hdxzdxhbl774r672pr64

A Probabilistic Approach to Service Selection with Conditional Contracts and Usage Patterns [chapter]

Adrian Klein, Fuyuki Ishikawa, Bernhard Bauer
2009 Lecture Notes in Computer Science  
Therefore, we propose a probabilistic approach to service selection as follows: First, to address the inherent variability in the actual values of NFPs at runtime, we treat them as probability distributions  ...  Further, we depict a typical scenario, which serves both as a motivation for our approach, and as a basis for its evaluation.  ...  As already explained, we first apply the function to the values of the probability distributions itself, before aggregating everything into one utility value uv to make full use of the probability distributions  ... 
doi:10.1007/978-3-642-10383-4_17 fatcat:svao6w7ocbg7lbrqnqeeaileuu

Piecewise Polynomial Aggregation as Preprocessing for Data Numerical Modeling

B S Dobronets, O A Popova
2018 Journal of Physics, Conference Series  
Data aggregation issues for numerical modeling are reviewed in the present study. polynomial models. A suitable example of such approach is the spline.  ...  To demonstrate the degree of the correspondence of the proposed methods to reality, the authors developed a theoretical framework and considered numerical examples devoted to time series aggregation.  ...  This approach allows one to represent accurately enough the arbitrary distribution.  ... 
doi:10.1088/1742-6596/1015/3/032028 fatcat:r5omtrwfrvd6zd2n5aymdb3sw4
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