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Mining Big Neuron Morphological Data

Maryamossadat Aghili, Ruogu Fang
2018 Computational Intelligence and Neuroscience  
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

Chunhong Wang
2014 International Journal of Database Theory and Application  
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]

Adem Karahoca, Dilek Karahoca, Mert anver
2012 Data Mining Applications in Engineering and Medicine  
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

T. Kohonen, S. Kaski, K. Lagus, J. Salojarvi, J. Honkela, V. Paatero, A. Saarela
2000 IEEE Transactions on Neural Networks  
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

Will Serrano
2018 Data  
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]

Wengang Zhou, Houqiang Li, Qi Tian
2017 arXiv   pre-print
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

Faezeh Hosseinzadeh, Amir KayvanJoo, Mansuor Ebrahimi, Bahram Goliaei
2013 SpringerPlus  
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  
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

Peter Wittek, Sándor Darányi
2013 Journal of Parallel and Distributed Computing  
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

Marco Antonio Ruiz- Serna, Guillermo Arturo Alzate- Espinosa, Andrés Felipe Obando- Montoya, Hernán Dario Álvarez- Zapata
2019 CT&F - Ciencia  
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

Francisco F. Martins, Tiago F. S. Miranda
2012 Geotechnical and Geological Engineering  
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]

Amritanshu Agrawal, Tim Menzies, Leandro L. Minku, Markus Wagner, Zhe Yu
2019 arXiv   pre-print
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 (, 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  
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]

Keqian Li
2015 arXiv   pre-print
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

Daniel R. Canêdo, Universidade de Brasília-UnB/Departamento de Engenharia Elétrica, Brasília, Brazil, Alexandre R. S. Romariz
2018 Journal of Communications  
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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