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Software Module Fault Prediction using Convolutional Neural Network with Feature Selection
2016
International Journal of Software Engineering and Its Applications
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Feature selection methods used are InfoGain and Correlation. ...
A sequence of rigorous activities under certain constraints is followed to come up with reliable software. ...
The feature selection part will aim at removing irrelevant and redundant features for better prediction. ...
doi:10.14257/ijseia.2016.10.12.27
fatcat:br6q52awq5ewrm2aurkj26qmiu
MEEGIPS—A Modular EEG Investigation and Processing System for Visual and Automated Detection of High Frequency Oscillations
2019
Frontiers in Neuroinformatics
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In the context of the currently available tools and for the purpose of related local HFO study activities we aimed at converging the advantages of clinical and experimental systems by designing and developing ...
A functional and tested software package is the deliverable of this activity. ...
of the software. ...
doi:10.3389/fninf.2019.00020
pmid:31024284
pmcid:PMC6460903
fatcat:awdcokm6rzbftp4i5bllsvf3uu
A Multi-Agent Architecture for Data Analysis
2019
Future Internet
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After an introduction about the actor model and the software framework used for implementing the software library, this article underlines the main features of ActoDatA and presents its experimentation ...
ActoDatA (Actor Data Analysis) is an actor-based software library for the development of distributed data mining applications. ...
The next section provides an overview of the software framework used for the implementation of ActoDatA. ...
doi:10.3390/fi11020049
fatcat:ejwx7oczcrhslhks54st7dgv3q
JaTeCS an open-source JAva TExt Categorization System
[article]
2017
arXiv
pre-print
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.: data readers for many formats, including the most commonly used text corpora and lexical resources, natural language processing tools, multi-language support, methods for feature selection and weighting ...
It covers all the steps of an experimental activity, from reading the corpus to the evaluation of the experimental results. ...
, feature selection, classification, regression, clustering and data visualizations. ...
arXiv:1706.06802v1
fatcat:nxfaa5vsgvhrdarrrfczdhikuq
Malware Detection at the Microarchitecture Level using Machine Learning Techniques
[article]
2020
arXiv
pre-print
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Previous studies have already used binary classification to implement their malware detection after doing extensive feature reduction. ...
This results in a simple identification of software being either malware or benign. ...
For this experiment, we are using the Explorer application of WEKA for both feature selection and classification. ...
arXiv:2005.12019v1
fatcat:oik6razrajdubpi3cotctjr6nm
Ultrafast Neuromorphic Photonic Image Processing with a VCSEL Neuron
[article]
2021
arXiv
pre-print
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Furthermore, the photonic system is combined with a software-implemented spiking neural network yielding a full platform for complex image classification tasks. ...
This exploits the ability of a VCSEL-based photonic neuron to integrate temporally-encoded pixel data at high speed; and fire fast (100ps-long) optical spikes upon detecting desired image features. ...
Acknowledgments The authors acknowledge support from the UKRI Turing AI Acceleration Fellowships Programme (EP/V025198/1), the US Office of Naval Research Global (Grant ONRG-NICOP-N62909-18-1-2027), the ...
arXiv:2110.01617v1
fatcat:tuynzpsjwne5bk6f3iahvn6bnm
Adversarial Active Learning
2014
Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop - AISec '14
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, and propose a framework for experimentation and implementation of active learning systems in adversarial contexts. ...
Lastly, we present a software architecture, Security-oriented Active Learning Testbed (SALT), for the research and implementation of active learning applications in adversarial contexts. ...
of State Bureau of Democracy, Human Rights, and Labor. ...
doi:10.1145/2666652.2666656
dblp:conf/ccs/MillerKABDHTJT14
fatcat:pperfvpyvnbh5kkpwge2zk4b4u
Enhancing Big Data Feature Selection Using a Hybrid Correlation-Based Feature Selection
2021
Electronics
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This study proposes an alternate data extraction method that combines three well-known feature selection methods for handling large and problematic datasets: the correlation-based feature selection (CFS ...
Therefore, this study aims to solve the computational time complexity and increase the classification accuracy. ...
Both authors have implemented big data hardware and software in executing experimental work. ...
doi:10.3390/electronics10232984
fatcat:6ecdiy2s65ezbekb5whyhjc3be
The Impact of Software Team Project Measurements on Students' Performance in Software Engineering Education
2020
Journal of Education and Practice
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On the other hand, the feature selection phase uses evolutionary and PSO search techniques to capture the essential team activity measures for each time interval in both the software process and product ...
This paper mainly uses the classification and feature selection phases. ...
Figure 4 and Figure 5 show the experimental results on selected measures extracted using evolutionary and PSO search compared to entire measures for the software product and process, respectively. ...
doi:10.7176/jep/11-31-02
fatcat:hvthmrjemrgsphpzouxxmnf2we
Towards the Definition of a Flexible Hyperspectral Processing Chain: Preliminary Case Study Using High-Resolution Urban Data
2008
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium
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Specifically, the processing steps considered in our framework include [6] dimensionality reduction, feature selection, feature extraction and classification. ...
One of the main activities of Hyper-I-Net is to settle the basis for the definition and testing of a flexible hyperspectral data collection and processing chain, in which individual elements can be integrated ...
Specifically, the processing steps considered in our framework include [6] dimensionality reduction, feature selection, feature extraction and classification. ...
doi:10.1109/igarss.2008.4779165
dblp:conf/igarss/NairoukhTGDP08
fatcat:ha6mfey4nvezvjmqdb3lalzvla
Comparative Analysis of Selected Heterogeneous Classifiers for Software Defects Prediction Using Filter-Based Feature Selection Methods
2018
FUOYE Journal of Engineering and Technology
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The experimental results revealed that the application of feature selection to datasets before classification in software defects prediction is better and should be encouraged and Multilayer perceptron ...
In this study, the researchers investigated the effect of filter feature selection on classification techniques in software defects prediction. ...
FEATURE SELECTION There are three methods used for feature selection -Filter method, Wrapper method and Embedded method. ...
doi:10.46792/fuoyejet.v3i1.178
fatcat:m4cjd63o4jhtjhsbhxd57b5bge
Towards a software defect proneness model: feature selection
2021
Applied Aspects of Information Technology
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For the prepared sampling, the most important features that affect the quality of software code have been selected using the following methods of feature selection: Boruta, Stepwise selection, Exhaustive ...
A comparison of the effectiveness of different methods of feature selection has been put into practice, in particular, a study of the effect of the method of feature selection on the accuracy of classification ...
However, because different projects have been used for research, and software code metrics are widely accepted and widely used in software engineering, the authors believe that the code metrics they have ...
doi:10.15276/aait.04.2021.5
fatcat:khzta3sz3nejtjhe3rk623gwaa
Malware Detection Based on Opcode Dynamic Analysis
2020
EAI Endorsed Transactions on Security and Safety
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Finally, we implement our model by VerilogHDL, functional simulation was carried out in modelsim simulation software and its implementation cost was analyzed. ...
In order to deal with the above problems, this paper proposes a new scheme for dynamic opcode acquisition, the opcode information obtained from the software runtime is used for offline analysis. ...
Except for the CFS feature selection algorithm, the accuracy of classification algorithm increases with the N of N-gram under other feature selection algorithms. ...
doi:10.4108/eai.22-6-2021.170239
fatcat:gvpxc6btxva3dbev367eigmqlu
Pattern Recognition Software and Techniques for Biological Image Analysis
2010
PLoS Computational Biology
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We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays. ...
This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. ...
More information about feature selection and classification can be found in the Feature Selection and Classification section. ...
doi:10.1371/journal.pcbi.1000974
pmid:21124870
pmcid:PMC2991255
fatcat:a63kdds4grcoxiy3yyp25526hm
Artificial intelligence based neurofeedback
2019
Cybernetics and Physics
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The concept of control models of biological neural networks, and the set-up including equipment and software tools developed in IPME RAS in order to implement the proposed concept is described. as well ...
as the AI methods and programs proposed for use. ...
Figure 1 .Figure 2 . 12 Experimental Experimental setup and Software schematics -1
Figure 3 . 3 Experimental setup and Software schematics -2 learning model extracts suitable features from the raw data ...
doi:10.35470/2226-4116-2019-8-4-287-291
fatcat:yxyo6bfvwnfoxlp7gm5saduxqq
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