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An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks
2014
BMC Systems Biology
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Methods: In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. ...
Then, an algorithm of probability isomorphic based on circuit simulation is proposed. ...
An earlier version of this article was published for the IEEE International Conference on Bioinformatics and Biomedicine (BIBM) held on December 18-21, 2013 [34] . ...
doi:10.1186/1752-0509-8-s3-s6
pmid:25350277
pmcid:PMC4243085
fatcat:zurgajtmazdfzhkdg2yc4bpahy
Secure Decision-Making Approach to Improve Knowledge Management Based on Online Samples
2018
International Journal of Intelligent Engineering and Systems
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Also, analysis proves our algorithm is better in terms of quality parameters than the existing algorithms. ...
Our mechanism is simulated and the results show a considerable improvement in the decision-making process. ...
Then, based on the classification values the probability of the frequently occurring data sets is founded. With the help of the frequently occurring datasets, a decision is taken. ...
doi:10.22266/ijies2018.0228.06
fatcat:m4ejb7p5hjga3cwj2xfv2tf2lm
The Role of Artificial Intelligence (AI) in Condition Monitoring and Diagnostic Engineering Management (COMADEM): A Literature Survey
2021
American Journal of Artificial Intelligence
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AI techniques such as, knowledge based systems, expert systems, artificial neural networks, genetic algorithms, fuzzy logic, casebased reasoning and any combination of these techniques (hybrid systems) ...
In this paper, an attempt is made to review the role of artificial intelligence in condition monitoring and diagnostic engineering management of modern engineering assets. ...
IMOS has a rule base for selecting an appropriate model for application based on identification of maintenance data pattern. ...
doi:10.11648/j.ajai.20210501.12
fatcat:gvplqmpqubdw3pquik5eavux5u
Associative pattern recognition for biological regulation data
2017
ACM SIGBioinformatics Record
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In this dissertation, we propose a series of associative pattern recognition algorithms in biological regulation studies. ...
In gene regulatory network inference, we propose a framework for refining weak networks based on transcription factor binding sites, thus improved the precision of predicted edges by up to 52%. ...
Because TFTS calculate the gene-motif scores based on the topology of the preliminary network, the performance is highly dependent on the accuracy of the network inference algorithms and on the size of ...
doi:10.1145/3148241.3148242
fatcat:nticslp3bra55iksan3hwzvq2i
Welcome message from the General Chairs
2009
2009 International Workshop on Satellite and Space Communications
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Based on these rigorous reviews, IES 2014 accepted 106 papers for inclusion in the conference program, which represents an acceptance rate of 69%. ...
All accepted papers will be included in the Proceeding of Adaptation, Learning and Optimization Series published by Springer-Verlag. ...
On the other hand, advances in data mining, an important section in data engineering and automated learning, also assist optimization algorithm designers to develop better methods. ...
doi:10.1109/iwssc.2009.5286448
fatcat:wcu4uzasizhzjmdkzyekynnqwi
Large-scale, Small-scale Systems
[chapter]
2006
Cognitive Systems - Information Processing Meets Brain Science
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The objective of the project is to examine recent progress in two major areas of research -computer science and neuroscience, and their related fields -and to understand whether progress in understanding ...
cognition in living systems has new insights to offer those researching the construction of artificial cognitive systems. ...
Acknowledgements The authors thank Flaviu Adrian Marginean for his help and background work in the construction of this document. ...
doi:10.1016/b978-012088566-4/50005-2
fatcat:mr7mjjmsingjxoiia3yrblsvbq
Program book
2010
2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010)
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FLAME is a flexible suffix tree based algorithm that can be used to find frequent patterns with a variety of definitions of motif (pattern) models. ...
and is based on an efficient and novel group key management scheme. ...
SMDB'10 will be a one-day workshop where accepted papers are presented in an informal and interactive setting. Participation in the workshop is not limited to authors of accepted papers. ...
doi:10.1109/icdew.2010.5452773
fatcat:oyq2tujbvjfpxjlyixux5q57vu
Defense Advanced Research Projects Agency (Darpa) Fiscal Year 2016 Budget Estimates
2015
Zenodo
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The Defense Advanced Research Projects Agency (DARPA) FY2016 amounted to $2.868 billion in the President's request to support high-risk, high-reward research. ...
-Examine repair and synthesis strategies to automatically discover commonalities and fix anomalies in input programs based on mining semantic patterns in the corpus. ...
FY 2016 Plans: -Design VLSI and analog circuits based on novel steep-turn-on transistor devices for applications such as lower power imagers, pattern recognition, and scavenging self-powered electronics ...
doi:10.5281/zenodo.1215366
fatcat:cqn5tyfixjanzp5x3tgfkpedri
27th Annual Computational Neuroscience Meeting (CNS*2018): Part One
2018
BMC Neuroscience
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All network simulations carried out with NEST (http:// www.nest-simul ator.org). ...
Acknowledgements We thank Ramón Huerta for his useful discussions on this work. This research was supported by the Spanish Government projects TIN2014-54580-R and TIN2017-84452-R. ...
The method reduces the computational costs for extraction of all possible repeated spike patterns by employing frequent itemset mining. ...
doi:10.1186/s12868-018-0452-x
pmid:30373544
pmcid:PMC6205781
fatcat:xv7pgbp76zbdfksl545xof2vzy
A Holistic Review of Soft Computing Techniques
2017
Applied and Computational Mathematics
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This paper gives an insight on four major consortiums of SC that sprang from the concept of cybernetics, explores and reviews the different techniques, methodologies; application areas and algorithms are ...
formulated to give an idea on how these computing techniques are applied to create intelligent agents to solve a variety of problems. ...
Artificial neural networks are, as their name indicates, computational networks which attempt to simulate, in a gross manner, the networks of nerve cell (neurons) of the biological (human or animal) central ...
doi:10.11648/j.acm.20170602.15
fatcat:pfmgraicunfijho23usu3pfn3a
A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures
2010
Neurocomputing
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The underlying philosophy is based on human child development [26] , the knowledge representations involved are neural network based, and a number of novel learning algorithms are involved, especially ...
network's performance, and an action network that controls actuators based on the activity in inference network. ...
He became known in the 1990s for his research on the use of genetic algorithms to evolve neural networks using three dimensional cellular automata inside field programmable gate arrays. ...
doi:10.1016/j.neucom.2010.08.012
fatcat:hlvx44gvcrcfniu34miufwnwsu
Graph Summarization Methods and Applications: A Survey
[article]
2018
arXiv
pre-print
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While advances in computing resources have made processing enormous amounts of data possible, human ability to identify patterns in such data has not scaled accordingly. ...
Finally, we discuss applications of summarization on real-world graphs and conclude by describing some open problems in the field. ...
SUBDUE [Cook and Holder 1994] , one of the most famous frequent-pattern mining methods, is applied in areas as diverse as chemical compound analysis, scene analysis, and CAD circuit design analysis. ...
arXiv:1612.04883v3
fatcat:fhg2g5eldfdgfkzoqdmbfl5er4
Advancing Science through Mining Libraries, Ontologies, and Communities
2011
Journal of Biological Chemistry
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the spaghetti of underlying ontologies, and synthesize novel knowledge and hypotheses. ...
With the emergence of digitized data regarding networks of scientific authorship, institutions and resources, we explore the possibility of accounting for social dependencies and cultural biases in reasoning ...
Given some set of observed symptoms, one can compute probabilities along arcs of the network to compare the likelihood of each disease (20) . ...
doi:10.1074/jbc.r110.176370
pmid:21566119
pmcid:PMC3129146
fatcat:2vfoe7pimva6lkmcqpf35r7kbm
Building patient-specific models for receptor tyrosine kinase signaling networks
2021
The FEBS Journal
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Here, we introduce recent advances in cancer systems biology aimed at personalized medicine, with focus on the receptor tyrosine kinase signaling network. ...
More recently, machine learning methods have emerged that can be used for mining omics data and classifying patient. ...
Parameter estimation is an important issue in ODE modeling, but biological modeling in general is being analyzed on a larger scale [123] . ...
doi:10.1111/febs.15831
pmid:33755310
fatcat:eobfm6tbdbhz3b2tddgrg3ktyi
Cognitive Radio Network with Enhanced Protocol for Maximum Throughputs
2012
IOSR Journal of Electrical and Electronics Engineering
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In this paper, a Cognitive Radio based Medium Access Control (CR-MAC) protocol for wireless sensor networks that utilizes cognitive radio transmission is used. ...
In cognitive radio (CR) networks, identifying the available spectrum resource through spectrum sensing, deciding on the optimal sensing and transmission times, and coordinating with the other users for ...
[72] proposed an efficient Genetic-Wrapper Algorithm based data mining for feature subset selection in a power quality pattern recognition application. ...
doi:10.9790/1676-0350105
fatcat:pfyv3ft2y5dtzcsiebfywnijtm
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