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Classification and Comparison of Agile Methods
2010
2010 Seventh International Conference on the Quality of Information and Communications Technology
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This manuscript describes a technique and its tool support to perform comparisons on agile methods, based on a set of relevant features and attributes. ...
With this set of attributes, by analysing the practices proposed by each method, we are able to assess (1) the coverage degree for the considered KAs and (2) the agility degree. ...
Section 4 is the central part of the manuscript and presents the classification and comparison of XP and Scrum, based on the proposed analysis method. ...
doi:10.1109/quatic.2010.71
dblp:conf/quatic/FernandesA10
fatcat:4jyz6msl3rhepknm3kcjk2auxi
A Technique to Classify and Compare Agile Methods
[chapter]
2010
Lecture Notes in Business Information Processing
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This manuscript describes a technique to perform comparisons on agile methods, based on a set of relevant features and attributes. ...
With this set of attributes, by analyzing the practices proposed by each method, we are able to assess (1) the coverage degree for the considered KAs and (2) the agility degree. ...
A fifth attribute, which relates the Agile Manifesto principles and the practices advocated by a given agile method, was selected to assess the agility degree of the methods. ...
doi:10.1007/978-3-642-13054-0_44
fatcat:us6sifszgjfypawwmorz2ptrma
A Proposed Model Of Agile Methodology In Software Development
2016
Zenodo
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Agile Software development has been increasing popularity and replacing the traditional methods of software develop-ment. ...
Random Forest performs better as compare to General Regression Neural Network (GRNN).The researchers will perform comparison between Random Forest and all types (GRNN, PNN, GMDH, and CCNN) of Neural Network ...
Jehad Ali compared the classification results of two models i.e. Random Forest and J48 for classifying twenty versatile datasets. In it shown the comparison results obtained from methods i.e. ...
doi:10.5281/zenodo.57031
fatcat:zncd6bcwifdf3g5h4nrhweob7u
Few Is Enough: Task-Augmented Active Meta-Learning for Brain Cell Classification
[article]
2020
arXiv
pre-print
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In this paper, we propose a tAsk-auGmented actIve meta-LEarning (AGILE) method to efficiently adapt DNNs to new tasks by using a small number of training examples. ...
Using only 1% of the training data and a single update step, we achieved 90% accuracy on the new cell type classification task, a 50% points improvement over a state-of-the-art meta-learning algorithm. ...
This work was supported by the National Science Foundation (nsf-iis 1910973), and the Intramural Research Program of the National Institute of Neurological Disorders and Stroke, National Institutes of ...
arXiv:2007.05009v1
fatcat:nmxko4vk4nef3erwwp4ehw3hiq
Classification of Functional and Non-functional Requirements in Agile by Cluster Neuro-Genetic Approach
2016
International Journal of Software Engineering and Its Applications
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It is implemented on two data sets and further analysis, and comparison of this model is made with an another implemented model (SVM with RBF kernel) based on precision, recall, and accuracy. ...
Agile development is truly the need of the hour due to its numerous advantages which are in line with the present business trends. ...
This paper proposes an automatic approach based on supervised learning for classification of functional and non-functional requirements in agile development. ...
doi:10.14257/ijseia.2016.10.10.13
fatcat:pxmzbnywzjd23dddfqjuytp42i
Microarray-Based RNA Profiling of Breast Cancer: Batch Effect Removal Improves Cross-Platform Consistency
2014
BioMed Research International
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In conclusion, the study emphasizes the importance of utilizing proper batch adjustment methods when integrating data across different batches and platforms. ...
Different technologies are available, but lack of standardization makes it challenging to compare and integrate data. ...
Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper. ...
doi:10.1155/2014/651751
pmid:25101291
pmcid:PMC4101981
fatcat:qsyskeyhkzds5jeuyzkibzr2cq
A Feature-Based Tool-Selection Classification for Agile Software Development
2015
Proceedings of the 27th International Conference on Software Engineering and Knowledge Engineering
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Agile software development methods offer a solution to these issues, but problems remain over evaluation along with the offering of the correct agile software as well as a collection of agile tools. ...
The purpose of this paper is to introduce best tools and features, criteria used for evaluating currently existing tools and propose a classification model to right agile tool selection. ...
The main points of the paper are detailed statistics in the agile methods in projects, and the information about adopting agile methods [7] . ...
doi:10.18293/seke2015-234
dblp:conf/seke/TaheriS15
fatcat:hb57zdjbsndatbkc2xg6pjzife
An Appraisal of Existing Evaluation Frameworks for Agile Methodologies
2008
15th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems (ecbs 2008)
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But existing evaluation frameworks and comparison tools do not satisfy all the needs of project managers and method engineers. ...
The emergence of agile software development methodologies, and the sheer number of the variants introduced, has raised the need for evaluation and comparison efforts, mostly in order to facilitate the ...
and comparison of agile methods (4-DAT) − Provides a mechanism for quantitative measurement of the degree of agility in any given method − Method scope − Agility − Agile Values − Software Process
Table ...
doi:10.1109/ecbs.2008.32
dblp:conf/ecbs/TaromiradR08
fatcat:6kbnx3kgfzex7nrmqqyzb3mbu4
Cost-Effective Supervised Learning Models for Software Effort Estimation in Agile Environments
2016
2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC)
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It is shown that selected machine learning methods perform better than Planning Poker estimates in the later stages of a project. ...
The Auto-Estimate leverages features extracted from Agile story cards, and their actual effort time. ...
This research is supported by the NSF under Grant No. 0753710, the CERCS I/UCRC and industry sponsors. ...
doi:10.1109/compsac.2016.85
dblp:conf/compsac/MoharreriSRR16
fatcat:smi26zkh3rgcvl2osbzl55fko4
An Improvement in Defect Detection Efficiency -A Review
2016
Indian Journal of Science and Technology
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Along with Agile methodology, defect comparison and classification of defects based on defect rate with respect to the standard threshold values, at each stage of the design process can be employed. ...
In memory analytics can be employed for Defect classification. This method provides effectiveness of defect classification and rates defect as low, high and medium. ...
Classification of the defects is further carried out based on priority and severity of the defect. ...
doi:10.17485/ijst/2016/v9i45/106490
fatcat:2e7rkfetdbf7foeebc6meuezfq
Resolution Agile Remote Sensing for Detection of Hazardous Material Spills
2016
Transportation Research Record
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The third section will develop the methods and models of rapid feature extraction and classification. ...
This research introduces and benchmarks the performance of a low-complexity method of hyperspectral image classification. ...
ACKNOWLEDGEMENTS The University Transportation Center, a program of the United States Department of Transportation, sponsored this research through its Mountain Plains Consortium (MPC). ...
doi:10.3141/2547-08
fatcat:tyrahinqfncdja7mcmli2jiwui
Agile Transition and Adoption Frameworks, Issues and Factors: A Systematic Mapping
2020
IEEE Access
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In order to adopt specific agile methods and to accommodate lean principles, many organizations need to tailor their processes. ...
Finally, a list of 154 situational factors affecting the agile transition and adoption process is proposed. ...
The results of the framework comparison and analysis is presented in Section V.A. ...
doi:10.1109/access.2020.2967839
fatcat:lms4pgyn3nhyhjrdqm24rofvra
Comparison of the Agilent, ROMA/NimbleGen and Illumina platforms for classification of copy number alterations in human breast tumors
2008
BMC Genomics
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Various platforms, brands and underlying technologies are available, facing the user with many choices regarding platform sensitivity and number, localization, and density distribution of probes. ...
Illumina, Infinium, and BeadArray are registered trademarks or trademarks of Illumina, Inc. All other brands and names contained herein are the property of their respective owners. ...
Nordgard and Grethe I. G. Alnaes for their contributions in the Illumina experiments and for clustering of the Illumina data. ...
doi:10.1186/1471-2164-9-379
pmid:18691401
pmcid:PMC2547478
fatcat:4oic3rwvbjcvll256pap7ordbi
Gene Expression Profiles for Predicting Metastasis in Breast Cancer: A Cross-Study Comparison of Classification Methods
2012
The Scientific World Journal
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This study compares the performance of seven classification methods and the effect of voting for predicting metastasis outcome in breast cancer patients, in three situations: within the same dataset or ...
Machine learning has increasingly been used with microarray gene expression data and for the development of classifiers using a variety of methods. ...
Acknowledgments This work was funded by the Danish Ministry of Interior, the Danish Strategically Research Council and DBCG-TIBCAT, the Clinical Institute at the University of Southern Denmark and the ...
doi:10.1100/2012/380495
pmid:23251101
pmcid:PMC3515909
fatcat:wteo6en4yjet7ojavj7asg3zfe
Three methods for optimization of cross-laboratory and cross-platform microarray expression data
2007
Nucleic Acids Research
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ACKNOWLEDGEMENTS This project has been funded in whole or in part with Federal funds from the National Institute of Allergies and Infectious Diseases, National Institutes of Health, Department of Health ...
and Human Services, under Contract No. ...
(B) is a comparison among the Agilent normalization methods. (C) and (D) compare highly processed Affymetrix data with Agilent methods. ...
doi:10.1093/nar/gkl1133
pmid:17478523
pmcid:PMC1904274
fatcat:2wf6e7ahwjcopl6l6533ke5fhi
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