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Mining Big Neuron Morphological Data
2018
Computational Intelligence and Neuroscience
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Neuromorphology is important because of the interplay between the shape and functionality of neurons and the far-reaching impact on the diagnostics and therapeutics in neurological disorders. ...
The advent of automatic tracing and reconstruction technology has led to a surge in the number of neurons 3D reconstruction data and consequently the neuromorphology research. ...
Steven Grieco for his help providing us the neurons drawing. ...
doi:10.1155/2018/8234734
pmid:30034462
pmcid:PMC6035829
fatcat:uxzd4n26kncqvairpvhcy6arwq
The Nuclear Techniques and the Selection of Model Parameters in Big Data
2014
International Journal of Database Theory and Application
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Now a large scale of data every day, the large-scale data is usually in the form of database storage. ...
Standard SVM using existing quadratic programming algorithm, the training time to sample index scale growth, and put the whole Hesse matrix (Hessian) in memory, the size of its space occupied by the square ...
People want to find useful rules or knowledge, for business analysis and decision, scientific exploration, production testing, thus was born the Data Mining technology (Data Mining,) [1] . ...
doi:10.14257/ijdta.2014.7.6.14
fatcat:b5kbf5is6vcy7pfu4aqrwwcume
Survey of Data Mining and Applications (Review from 1996 to Now)
[chapter]
2012
Data Mining Applications in Engineering and Medicine
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Survey of Data Mining and Applications (Review from 1996 to Now) 5 Decision trees can be divided into two types as regression trees and classification trees. ...
Introduction The science of extracting useful information from large data sets or databases is named as data mining. ...
This technique tends to be highly accurate and fast, making it useful on large databases. Model is simple and intuitive. ...
doi:10.5772/48803
fatcat:dyey6yk475d5toy7v2wxgsmq7m
Self organization of a massive document collection
2000
IEEE Transactions on Neural Networks
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Index Terms-Data mining, exploratory data analysis, knowledge discovery, large databases, parallel implementation, random projection, self-organizing map (SOM), textual documents. ...
The main goal in our work has been to scale up the SOM algorithm to be able to deal with large amounts of high-dimensional data. ...
ACKNOWLEDGMENT The authors wish to thank the European Patent Office and the National Board of Patents and Registration of Finland for their help with the patent collection, and the Academy of Finland for ...
doi:10.1109/72.846729
pmid:18249786
fatcat:xutvle4otbdbvb6yrwau2y5rwm
Neural Networks in Big Data and Web Search
2018
Data
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In addition to the challenge of crawling and indexing information within the enormous size and scale of the Internet, e-commerce customers and general Web users should not stay confident that the products ...
The use of artificial intelligence (AI) based on neural networks and deep learning in learning relevance and ranking is also analyzed, including its utilization in Big Data analysis and semantic applications ...
rule mining that chooses highly business-efficient products among the candidate recommendable products [118] . ...
doi:10.3390/data4010007
fatcat:2irxpdvtfrclrbndkrubl5jvqq
Recent Advance in Content-based Image Retrieval: A Literature Survey
[article]
2017
arXiv
pre-print
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The explosive increase and ubiquitous accessibility of visual data on the Web have led to the prosperity of research activity in image search or retrieval. ...
With the ignorance of visual content as a ranking clue, methods with text search techniques for visual retrieval may suffer inconsistency between the text words and visual content. ...
of large scale image search. ...
arXiv:1706.06064v2
fatcat:m52xwsw5pzfzdbxo5o6dye2gde
Prediction of lung tumor types based on protein attributes by machine learning algorithms
2013
SpringerPlus
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and two NB models applied on original database and newly created ones from attribute weighting models; models accuracies calculated through 10-fold cross and wrapper validation (just for SVM algorithms ...
This is the first report suggesting that the combination of protein features and attribute weighting models with machine learning algorithms can be effectively used to predict the type of lung cancer tumors ...
Briefly, main database (FCdb) transformed to SVM format and scaled by grid search (to avoid attributes in greater numeric ranges dominating those in smaller numeric ranges) and to find the optimal values ...
doi:10.1186/2193-1801-2-238
pmid:23888262
pmcid:PMC3710575
fatcat:fsmcuq6ptvgyrgysylnmk6uc5q
Enriching Image Retrieval System through CNN for Sketches and Images
2019
International journal of recent technology and engineering
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The image search is performed using the CNN through K means Clustering and Haar wavelets. ...
So as a tiny step towards this, this research article proposes a model of image retrieval using the input as image sketch and images using the histogram features and Region of interest based on the position ...
done by a computer vision system and is highly helpful in segregating large databases. ...
doi:10.35940/ijrte.b3619.098319
fatcat:5mxuihnhsnb6bh7jyst2z366na
Accelerating text mining workloads in a MapReduce-based distributed GPU environment
2013
Journal of Parallel and Distributed Computing
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access and effective use of shared memory. ...
Since the initial steps of text mining are typically data-intensive, and the ease of deployment of algorithms is an important factor in developing advanced applications, we introduce a flexible, distributed ...
Nutch is an open source web-search project that relies on Hadoop to distribute the workload of crawling and indexing, and uses Lucene as its back-end for building the inverted index [8] . ...
doi:10.1016/j.jpdc.2012.10.001
fatcat:tem562gscfgqlpea3n6quj3qtq
Combined artificial intelligence modeling for production forecast in a petroleum production field
2019
CT&F - Ciencia
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ANN and FIS (fuzzy inference systems) predictive models identification is developed after the data mining process. ...
This paper presents the results about using a methodology that combines two artificial intelligence (AI) models to predict the oil, water and gas production in a Colombian petroleum field. ...
Inner iterative process performs searching task, deleting variables one-byone until finding which should be eliminated to enhance the accuracy of the model. ...
doi:10.29047/01225383.149
fatcat:lavxkg4xkzcqte7ad244ujlz64
Estimation of the Rock Deformation Modulus and RMR Based on Data Mining Techniques
2012
Geotechnical and Geological Engineering
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In this work Data Mining tools are used to develop new and innovative models for the estimation of the rock deformation modulus and the Rock Mass Rating (RMR). ...
A database published by Chun et al. (2008) was used to develop these models. ...
For a more correct definition of E, considering all factors which govern deformation behaviour of the rock mass, large scale in situ tests are needed. ...
doi:10.1007/s10706-012-9498-1
fatcat:juti5k5c7rek5gdwebcsp4jvne
Better Software Analytics via "DUO": Data Mining Algorithms Using/Used-by Optimizers
[article]
2019
arXiv
pre-print
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Our conclusion, hence, is that for software analytics it is possible, useful and necessary to combine data mining and optimization using DUO. ...
This paper claims that a new field of empirical software engineering research and practice is emerging: data mining using/used-by optimizers for empirical studies or DUO. ...
Acknowledgements Earlier work ultimately leading to the present one was inspired by the NII Shonan Meeting on Data-Driven Search-based Software Engineering (goo.gl/f8D3EC), December 11-14, 2017 ...
arXiv:1812.01550v2
fatcat:dgqfzythkfbjzhnikasiqfp3ze
Intelligent Collaborative Quality Assurance System for Wind Turbine Supply Chain Management
2013
International Journal of Advanced Computer Science and Applications
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This proposed system provides intelligent functions for quality prediction, pattern recognition and data mining. A case study for wind turbines is given to demonstrate this approach. ...
The results show that such a system can assure product quality improved in a continuous process. ...
Useful knowledge can be obtained from data mining. ...
doi:10.14569/ijacsa.2013.040206
fatcat:kmv3oeclhzcp3hp5vhhu7ruvki
On Integrating Information Visualization Techniques into Data Mining: A Review
[article]
2015
arXiv
pre-print
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More specifically, we study the intersection from a data mining point of view, explore how information visualization can be used to complement and improve different stages of data mining through established ...
Information visualization and data mining are two research field with such goal. ...
Important techniques include exploring connectivity in large graph structures with graded color scale encoding on the path, supporting visual search and analysis with keyword search and attribute filtering ...
arXiv:1503.00202v1
fatcat:ucl72q5hwnccxdqeuksly4uu3q
Data Analysis of Wireless Networks Using Computational Intelligence
2018
Journal of Communications
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The increase in the use of wireless local networks and the use of services from satellites is also noticed. ...
The high utilization rate of mobile devices for various purposes makes clear the need to monitor wireless networks to ensure the integrity and confidentiality of the information transmitted. ...
This anomaly is based on the large-scale transmission of RTS frames or frames for a short period of time [15] . ...
doi:10.12720/jcm.13.11.618-626
fatcat:unnadgncc5d5xkaikojbbkd27a
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