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A multi-criteria model for planning and fine-tuning distributed Scrum projects

A multi-criteria model for planning and fine-tuning distribu...

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6th IEEE International Conference on Global Software Engineering, ICGSE 2011

作者： Almeida, Luis Henrique Albuquerque, Adriano Bessa Pinheiro, Plácido Rogério Graduate Program in Applied Computer Science University of Fortaleza Fortaleza 60811-905 Brazil

ISBN: (纸本)9780769545035

Distributed software development is a fact of life for many projects. It is well established that distance makes difficult to interact and to cooperate effectively. Scrum emphasizes communication, reduces coordination and control overhead;therefore it has enormous potential to help the management of distributed projects and has been increasingly used. Successfully managing the combined use of DSD and Scrum is a complex task and it requires carefully planning. Despite the importance and complexity of this type of problem, there seems to be a lack of reports, in the literature, of models that could support project managers dealing with these decision contexts. This paper presents a multi-criteria decision model for planning and finetuning such project plans. This model was developed using cognitive mapping and MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique). The application of the model is demonstrated, followed by conclusion and remarks about future work. © 2011 IEEE.

关键词： Software design

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Genetic and ranking-based selection of components for multilabel classifier ensembles

Genetic and ranking-based selection of components for multil...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： Nathanael Costa André L. V. Coelho Graduate Program in Applied Informatics University of Fortaleza-UNIFOR Fortaleza Brazil

This paper deals with the problem of selecting (aka pruning) components for multilabel classifier ensembles. Three methods, one based on a genetic algorithm (GA) and the others based on ranking, are applied for this purpose. In particular, we investigate the adoption of different multilabel classification measures to play the role of the objective function of these methods, paying special attention to how the choice of one measure affects the accuracy of the pruned ensembles as gauged by other measures. A preliminary empirical analysis is conducted on five problems and the results achieved indicate that the classification performance of pruned ensembles as estimated by a given multilabel measure may significantly vary according to the measure adopted for selecting the components. Moreover, although the pruning methods used can yield significant gains in terms of ensemble size reduction, the ensemble models they generate usually lag behind when contrasted to those equipped with the whole sets of components.

关键词： Accuracy Genetic algorithms Loss measurement Training Particle measurements Atmospheric measurements Hybrid intelligent systems

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On ensembles of biclusters generated by NichePSO

On ensembles of biclusters generated by NichePSO

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Congress on Evolutionary Computation

作者： Lara Menezes André L. V. Coelho Graduate Program in Applied Informatics University of Fortaleza-UNIFOR Fortaleza Ceara Brazil

Ensemble methods combine multiple models into a single framework for coping better with Machine Learning tasks. Recently, the well-known Bagging approach was adapted to solve biclustering problems, where the objective is to find large sub-groups of samples and attributes of the data matrix with the samples showing high correlation over the attributes. In this paper, aiming at the generation of more diverse and high-quality biclusters to be fused through an ensemble perspective, we have adopted a well-known multimodal Particle Swarm Optimization algorithm, namely NichePSO. In particular, the study brings a preliminary comparative assessment of the biclustering results delivered by NichePSO operating alone and by two ensemble settings (one of which is Bagging) operating on the biclusters produced by NichePSO. The assessment was done based on bioinformatics and collaborative filtering datasets, and the results achieved so far reveal the usefulness of ensembling the repertory of biclusters produced by NichePSO.

关键词： Bagging Bioinformatics Probability Coherence Particle swarm optimization Context Indexes

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Visually inspecting the search behavior of Harmony Search and its variants with Viz3D

Visually inspecting the search behavior of Harmony Search an...

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Congress on Evolutionary Computation

作者： Marcelo Lotif André L. V. Coelho Graduate Program in Applied Informatics (MIA) University of Fortaleza-UNIFOR Fortaleza Ceara Brazil

The aim of this study is to assess the Harmony Search (HS) meta-heuristic and some of its variants when submitted to benchmark continuous optimization problems to reveal whether and how such variants change the patterns of search behavior exhibited by the canonical version. For this purpose, a new Visual Mining tool based on the Viz3D algorithm was developed to aid in the visualization of how the HS algorithms effectively explore the search space. The results achieved provide evidence that the gains in performance usually promoted by the HS variants are indeed related to noticeable modifications in the search behavior as displayed by the original version.

关键词： Visualization Optimization Search problems Data visualization Nickel Data mining Algorithm design and analysis

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Applying multi-criteria decision analysis to global software development with scrum project planning

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6th International Conference on Rough Sets and Knowledge Technology, RSKT 2011

作者： Almeida, Luis Henrique Pinheiro, Plácido Rogério Albuquerque, Adriano Bessa CPQi IT Offshore Solutions Av. Washington Soares 909 60.811-341 Fortaleza Brazil University of Fortaleza Graduate Program in Applied Computer Science Av. Washington Soares 1321 60811-905 Fortaleza Brazil

ISBN: (纸本)9783642244247

Distributed Software Development (DSD) projects have become a common reality for many organizations. Scrum is a consolidated Agile methodology and has been increasingly used in a distributed fashion. As distance makes difficult to interact and to cooperate effectively, it is paramount to use methodologies like Scrum that emphasizes communication, reduces coordination and control overhead. Successfully planning and managing the combined use of DSD and Scrum is a complex task and requires carefully planning. Despite the importance and complexity of this type of problem, there seems to be a lack of reports, in the literature, of models that could support managers dealing with such decision context. This paper applies a multi-criteria decision model on the choice of DSD Scrum project plans that have a better chance of success. The model, presented in [1], was developed using cognitive mapping and MACBETH[2]. The application of the model is demonstrated, followed by conclusion and future work. © 2011 Springer-Verlag.

关键词： Project management

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A hybrid model in the selection of prototypes for educational tools: An applicability in verbal decision analysis

A hybrid model in the selection of prototypes for educationa...

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IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, MCDM

作者： Thais Cristina Sampaio Machado Andréa Carvalho Menezes Isabelle Tamanini Placido Rogerio Pinheiro Graduate Program in Applied Computer Sciences University of Fortaleza-UNIFOR Fortaleza Brazil

Aiming to answer the growing demand for professionals with knowledge about software processes, this paper presents ideas for creating educational tools that supports its teaching. The paper defines six options of prototypes of educational tools and illustrates the study of preferences elicitation in the application of a hybrid method using ORCLASS and PACOM methodologies from verbal decision analysis (VDA) framework to classify and rank the prototypes according to the decision maker preferences. The application with prototypes was chosen because the software engineering is an area that allows the wide research in the preferences elicitation process. The research results show that, the adoption of qualitative methods of decision support, can benefit significantly the selection of the interface aiming to use the selected interface from the approved group and ranked for future development of real educational tools applications.

关键词： Prototypes Decision making Navigation Software Filling Education Games

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Combining different ways to generate diversity in bagging models: An evolutionary approach

Combining different ways to generate diversity in bagging mo...

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International Joint Conference on Neural Networks (IJCNN)

作者： Diego S. C. Nascimento Anne M. P. Canuto Lígia M. M. Silva André L. V. Coelho Informatics and Applied Mathematics Department Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Graduate Program in Applied Informatics University of Fortaleza-UNIFOR Fortaleza Ceara Brazil

Bagging algorithm has been proven to be effective when dealing with on different classification problems. However, the success of Bagging depends strongly on the diversity level reached by the individual classifiers of the ensemble models. Diversity in ensemble can be obtained when the individual classifiers are built using different circumstances, such as parameter settings, training datasets and learning algorithms. This paper presents a new approach which combines these three different ways to obtain high diversity in Bagging models, aiming, as a consequence, to obtain high levels of accuracy for the ensembles. In the proposed approach, in order to obtain the optimal configurations of features and classifiers in Bagging models, we have applied an evolutionary approach composed of two genetic algorithm instances. In order to validate the proposed approach, experiments involving 10 classification algorithms have been conducted, applying the resulting Bagging structures in 5 pattern classification datasets taken from the UCI repository. In addition, we analyze the performance of the resulting Bagging structures in terms of two recently proposed diversity measures, referred to as good and bad.

关键词： Diversity reception Genetic algorithms Bagging Accuracy Training Biological cells Correlation

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Tackling the biclustering problem with cooperative coevolutionary algorithms

Tackling the biclustering problem with cooperative coevoluti...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Lara Menezes André L. V. Coelho Graduate Program in Applied Informatics University of Fortaleza-UNIFOR Fortaleza Ceara Brazil

The biclustering problem consists in simultaneously clustering rows and columns of a data matrix. The aim of this paper is to empirically assess the performance of cooperative coevolution as an alternative approach for coping with the task of discovering good and sizeable biclusters. For this purpose, two cooperative coevolutionary algorithms, one configured with genetic algorithms (GAs) and another configured with particle swarm optimization (PSO), have been investigated through experiments conducted over two real-world problems. The results achieved reveal that, when compared with simple GA, standard PSO, and the PSO-GA hybrid algorithms, the coevolutionary models (especially the ones configured with PSO) usually prevail in terms of discovering larger coherent biclusters, but lag behind in terms of computational efficiency.

关键词： Algorithm design and analysis Gallium Gene expression Bioinformatics Clustering algorithms Particle swarm optimization Intelligent systems

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Comparison of two pro totype-based multicriteria classification methods

Comparison of two pro totype-based multicriteria classificat...

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2009 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, MCDM 2009

作者： Filho, Amaury T. Brasil Pinheiro, Plácido R. Coelho, André L. V. Costa, Nathanael C. Master of Science Program in Applied Informatics University of Fortaleza Fortaleza CE Brazil

ISBN: (纸本)9781424427642

In the present study, we introduce an experimental analysis conducted over two Multicriteria Decision Aid (MCDA) classification methods that have been successfully applied to real world problems. Different from other studies on MCDA classifiers, which put more emphasis on the development of new methods, this work compares the effectiveness of two MCDA nominal classifiers under the same conditions. In such regard, we developed a customized genetic algorithm to calibrate their control parameters automatically under some different sets of reference alternatives, also known as prototypes. Moreover, the experiments we have realized so far, involving different datasets, reveal that there are still some gaps in existing MCDA methods that can lead to an improvement of the methodology for the classification problems. We understand that this sort of empirical assessment is interesting as it reveals how robust/sensitive the MCDA classifiers could be to the choice of cut-off thresholds and prototypes for distinct problems. ©2009 IEEE.

关键词： Classification (of information)

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Towards the neuropsychological diagnosis of alzheimer's disease: A hybrid model in decision making

Towards the neuropsychological diagnosis of alzheimer's dise...

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作者： De Castro, Ana Karoline Araujo Pinheiro, Placido Rogerio Pinheiro, Mirian Caliope Dantas Graduate Program in Applied Informatics University of Fortaleza Av. Washington Soares 1321 - Bloco J CEP: 60811-905 Fortaleza Ceara Brazil

ISBN: (纸本)9783642047565

Dementias are syndromes described by a decline in memory and other neuropsychological changes especially occurring in the elderly and increasing exponentially in function of age. Due to this fact and the therapeutical limitations in the most advanced stage of the disease, diagnosis of Alzheimer's disease is extremely important and it can provide better life conditions to patients and their families. This work presents a hybrid model, combining Influence Diagrams and the Multicriteria Method, for aiding to discover, from a battery of tests, which are the most attractive questions, in relation to the stages of CDR (Clinical Dementia Rating) in decision making for the diagnosis of Alzheimer's disease. This disease is the most common dementia. Influence Diagram is implemented using GeNie tool. Next, the judgment matrixes are constructed to obtain cardinal value scales which are implemented through MACBETH Multicriteria Methodology. The modeling and evaluation processes were carried out through a battery of standardized assessments for the evaluation of cases with Alzheimer's disease developed by Consortium to Establish a Registry for Alzheimer's disease (CERAD). © 2009 Springer Berlin Heidelberg.

关键词： Diagnosis

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