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Inaugural IEEE-IES Digital Ecosystems and Technologies Conference, DEST

作者： Rodrigo Pereira dos Santos Cláudia Maria Lima Werner Computer Science and System Engineering Department COPPE Federal University of Rio de Janeiro Rio de Janeiro Brazil

Since systems and software development processes present challenges beyond the technical side, Software Ecosystems (SECOs) have emerged as an approach to improve Software engineering (SE) mindset in industry, considering relations among companies and stakeholders. Developing a system has been changed to designing and maintaining a platform and its interface in order to support multiple products developed by a set of distributed and different third-part developers. This fact changes software industry because it requires linking an architectural, a business and a social-based environment in an integrated way and it focuses on software reuse processes. This concern motivated a proposal of a framework for SECOs management and engineering called ReuseECOS. The approach aims at outlining a set of steps that combines those three bases (or dimensions) of SECOs and joins different perspectives in SECOs research literature through a survey. In this paper, the focus is on the last dimension, that is, the social one. A preliminary analysis, done on a Software Reuse Lab's SECOs at coppe/UFRJ, points out that concepts explored by researchers can be merged in a broader SE approach.

关键词： Knowledge engineering Context Organizations Communities Software reusability

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

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Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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Introducing Software Process Tailoring to BPMN: BPMNt

Introducing Software Process Tailoring to BPMN: BPMNt

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International Conference on Software and system Process (ICSSP)

作者： Raquel M. Pillat Toacy C. Oliveira Fabio L. Fonseca Systems Engineering and Computer Science Program-PESC / COPPE Federal University of Rio de Janeiro Rio de Janeiro Brazil

BPMN 2.0 is a widely used notation to model business process that has associated tools and techniques to facilitate process management, execution and monitoring. As a result using BPMN to model Software Development Process (SDP) can leverage on the BPMN's infrastructure to improve SDP quality. Nevertheless, when using BPMN to model Software Processes one can observe the lack of an important feature: means to represent process tailoring. This article introduces the BPMNt, a conservative extension to BPMN that aims at aggregating a tailoring representation mechanism as the one found at SPEM 2.0. BPMNt uses the extensibility classes already present in the BPMN meta-model. Our work also presents an example to illustrate the approach.

关键词： Software Business Unified modeling language programming Adaptation models Standards Semantics

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UbiRE: A game for teaching requirements in the context of ubiquitous systems

UbiRE: A game for teaching requirements in the context of ub...

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Conferencia Latinoamericana En Informatica (CLEI)

作者： Thaiana Lima Beatriz Campos Rodrigo Santos Claudia Werner Computer Science and System Engineering Department COPPE-Federal University of Rio de Janeiro Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781467307949

Considering the computer science challenge related to quality in technology development, the teaching and learning process of Software engineering (SE) takes an important role because it impacts the formation of human resources. However, SE does not explore the broader development and use of didactic material such as games. These resources can propitiate an experience that reflects typical situations of real world and motivate students. This paper presents UbiRE, a game to understand Requirements engineering in the context of ubiquitous systems. Its design, development and initial evaluation experience is discussed from a development process of educational game perspective, contributing to improve this process in the SE education scenario.

关键词： Software Java Erbium Games Education Visualization Context

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The global financial markets: An ultra-large-scale systems perspective

The global financial markets: An ultra-large-scale systems p...

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17th Monterey Workshop on Large-Scale Complex IT systems, LSCITS 2012

作者： Cliff, Dave Northrop, Linda UK Large Scale Complex IT System Initiative Department of Computer Science University of Bristol Bristol BS8 1UB United Kingdom Research Technology and System Solutions Program Software Engineering Institute Carnegie-Mellon University Pittsburgh PA 15213 United States

ISBN: (纸本)9783642340581

We argue here that, in recent years, the world's financial markets have become a globally interconnected complex adaptive ultra-large-scale socio-technical system-of-systems, and that this has important consequences for how the financial markets should be engineered and managed in future. Major failures in the financial markets can now occur at super-human speeds, as was witnessed in the "Flash Crash" of May 6th 2010. Events such as the Flash Crash may become more commonplace in future, unless lessons are learned from other fields where complex adaptive socio-technical systems-of-systems have to be engineered for high-integrity, safety-critical applications. In this document we review the literature on failures in risky technology and high-integrity approaches to safety-critical SoS engineering. We conclude with an argument that, in the specific case of the global financial markets, there is an urgent need to develop major national strategic modeling and predictive simulation capabilities, comparable to national-scale meteorological monitoring and modeling capabilities. The intent here is not to predict the price-movements of particular financial instruments or asset classes, but rather to provide test-rigs for principled evaluation of systemic risk, estimating probability density functions over spaces of possible outcomes, and thereby identifying potentially high-consequence failure modes in the simulations, before they occur in real life, by which time it is typically too late. © 2012 Springer-Verlag.

关键词： Information technology

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Formalizing the situation of a business process activity

Formalizing the situation of a business process activity

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International Conference on computer Supported Cooperative Work in Design

作者： Talita da Cunha Mattos Flávia Maria Santoro Kate Revoredo Vanessa Tavares Nunes Postgraduate Information Systems Program UNIRIO Rio de Janeiro Brazil COPPE/PESC-Systems Engineering and Computer Science Program UFRJ Rio de Janeiro Brazil

Business processes are dynamic and constantly evolving. Contextual elements that had not yet been identified and represented can arise and influence the execution of each process instance in diverse manners. In this scenario, the identification of these elements is considered of great importance. This paper proposes a formalism for context associated with business processes that intends to identify the situation of an activity in order to subsidize decisions to be taken within the execution of a process.

关键词： Computational modeling Context Psychology Media Navigation

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On region-based fault tolerant design of distributed file storage in networks

On region-based fault tolerant design of distributed file st...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Sujogya Banerjee Shahrzad Shirazipourazad Arunabha Sen Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University Tempe AZ USA

ISBN: (纸本)9781467307734;9781467307758

Distributed storage of data files in different nodes of a network enhances the reliability of the data by offering protection against node failure. In the (N,K),N ≥ K file distribution scheme, from a file F of size |F|, N segments of size |F|/K are created in such a way that it is possible to reconstruct the entire file, just by accessing any K segments. For the reconstruction scheme to work it is essential that the K segments of the file are stored in nodes that are connected in the network. However in case of node failures the network might become disconnected (i.e., split into several connected components). We focus on node failures that are spatially-correlated or region-based. Such failures are often encountered in disaster situations or natural calamities where only the nodes in the disaster zone are affected. The goal of this research is to devise a file segment distribution scheme so that, even if the network becomes disconnected due to any region fault, at least one of the largest connected components will have at least K distinct file segments with which to reconstruct the entire file. The distribution scheme will also ensure that the total storage requirement is minimized. We provide an optimal solution through Integer Linear programming and an approximation solution with a guaranteed performance bound of O(ln n) to solve the problem for any arbitrary network. The performance of the approximation algorithm is evaluated by simulation on two real networks.

关键词： Image color analysis Color Approximation algorithms Robustness Approximation methods Layout Encoding

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The Use of Support Vector Machine and Genetic Algorithms to Predict Protein Function

The Use of Support Vector Machine and Genetic Algorithms to ...

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IEEE International Conference on systems, Man, and Cybernetics

作者： Walkiria K. Resende Renato A. Nascimento Carolina R. Xavier Iara F. Lopes Cristianc N. Nobre Department of Computer Science Universidade Federal de Sao Joao del Rei - UFSJ Department of Computer Science Pontificia Universidade Catolica de Minas Gerais PUC/MG Civil Engineering Program COPPE - UFRJ

ISBN: (纸本)9781467317139

In Bio informatics, the prediction of protein function is considered a very important task but also difficult. Using a set of enzymes represented by Hydrolase, Isomerase, Ligase, Lyase, Transferase and Oxidoreductase classes, previously used by Dobson et ah, this paper proposes a self-learning process able to predict their classes, based on their primary and secondary structures, through a Support Vector Machine (SVM) classifier and genetic algorithm. An SVM can he characterized as a supervised machine learning algorithm capable of resolving linear and non-linear classification problems. During the learning process, both the training data and the corresponding output are presented to the SVM to allow its parameters to he adjusted. This study utilized genetic algorithms - optimization heuristics often used to estimate parameters - to adjust the main parameters of the classifier such as kernel function type and parameter C, which provides the relationship between the training error and the margin of separation between classes. In this specific prediction problem, the results indicate that the best function is an RBF where width is 6.1 and C is 6.9. Using these parameters, the classifier obtains an average accuracy of 79.74%.

关键词： Component: Proteins Prediction Support Vector Machine Genetic Algorithms protein structure function Support Vector Network Genetic Algorithm (GA) Classifiers Learning processes secondary structures

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Multiobjective optimization for project portfolio selection 12

Multiobjective optimization for project portfolio selection

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14th International Conference on Genetic and Evolutionary Computation Companion, GECCO'12 Companion

作者： De Barros, Márcio O. Costa, Hélio R. Figueiredo, Fábio V. Da Rocha, Ana Regina C. Post-graduate Information Systems Program - PPGI UNIRIO Av. Pasteur 458 Urca - Rio de Janeiro RJ Brazil COPPE UFRJ System Engineering and Computer Science Department Caixa Postal: 68511 CEP: 21945-970 - Rio de Janeiro Brazil CCA-RJ Brazilian Air Force Ponta do Galeão s/no Ilha do Governador CEP: 21941-510 - Rio de Janeiro Brazil

ISBN: (纸本)9781450311786

This paper proposes a multiobjective heuristic search approach to support a project portfolio selection technique on scenarios with a large number of candidate projects. The original formulation for the technique requires analyzing all combinations of candidate projects, which is unfeasible when more than a few alternatives are available. We have used a multiobjective genetic algorithm to partially explore the search space of project combinations and select the most effective ones. We present an experimental study based on four project selection problems that compares the results found by the genetic algorithm to those yielded by a non-systematic search procedure. Results show evidence that the project selection technique can be used in large-scale scenarios and that GA presents better results than simpler search strategy. Copyright is held by the author/owner(s).

关键词： Multiobjective optimization

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Mediating process adaptation through a goal-oriented context-aware approach

Mediating process adaptation through a goal-oriented context...

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International Conference on computer Supported Cooperative Work in Design

作者： Vanessa Tavares Nunes Cláudia M. Lima Werner Flávia Maria Santoro COPPE/PESC-Systems Engineering and Computer Science Program UFRJ Rio de Janeiro Brazil NP2Tec and Postgraduate Information Systems Program UNIRIO Rio de Janeiro Brazil

Complexity and dynamism of day-to-day activities in organizations are inextricably linked, one impacting the other, increasing the challenges for constant adaptation on the way to organize work to address emerging demands. Market is demanding systems that are aware of organizations processes and able to evolve and adapt to new situations in everyday working activities. We argue that flexibility in processes could be managed in real time, by PAIS (Process-aware Information systems), using context information collected in the work environment. This paper proposes CGAdapt, a context management architecture approach that aims to improve and automate dynamic process adaptation. We explain how process adaptation may occur in real time through an existent scenario using this proposal and discuss the value of context-awareness to reason about process alternative adaptations in a goal oriented approach.

关键词： Context Materials Business Adaptation models Analytical models

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