The creation of tools, techniques and methodologies to support the manipulation of large data sets has been receiving special attention of both scientific and industrial communities, in order to discover new ways of d...
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The creation of tools, techniques and methodologies to support the manipulation of large data sets has been receiving special attention of both scientific and industrial communities, in order to discover new ways of dealing with the underlying information, including learning purposes, identification of patterns, decision making support, amongst others. However, making use of computing resources to enhance awareness and understanding of software information and the software itself is still a challenge in software/systemsengineering, since it involves the identification of suitable mechanisms, adequate abstractions, and studies on stimulation of the human perceptive and cognitive abilities. This paper presents some of the challenges in this context, based on current trends of software development lifecycle, program comprehension, and software engineering education. At the end, a special focus is given on ongoing research on using and improving current mechanisms for supporting software reuse practices and software comprehension in general.
The breakage-fusion-bridge (BFB) mechanism was proposed over seven decades ago and is a source of genomic variability and gene amplification in cancer. Here we formally model and analyze the BFB mechanism, to our know...
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Table of contents A1 Introduction to the 8th Annual Conference on the science of Dissemination and Implementation: Optimizing Personal and Population Health David Chambers, Lisa Simpson D1 Discussion forum: Population...
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Table of contents A1 Introduction to the 8th Annual Conference on the science of Dissemination and Implementation: Optimizing Personal and Population Health David Chambers, Lisa Simpson D1 Discussion forum: Population health D&I research Felicia Hill-Briggs D2 Discussion forum: Global health D&I research Gila Neta, Cynthia Vinson D3 Discussion forum: Precision medicine and D&I research David Chambers S1 Predictors of community therapists’ use of therapy techniques in a large public mental health system Rinad Beidas, Steven Marcus, Gregory Aarons, Kimberly Hoagwood, Sonja Schoenwald, Arthur Evans, Matthew Hurford, Ronnie Rubin, Trevor Hadley, Frances Barg, Lucia Walsh, Danielle Adams, David Mandell S2 Implementing brief cognitive behavioral therapy (CBT) in primary care: Clinicians’ experiences from the field Lindsey Martin, Joseph Mignogna, Juliette Mott, Natalie Hundt, Michael Kauth, Mark Kunik, Aanand Naik, Jeffrey Cully S3 Clinician competence: Natural variation, factors affecting, and effect on patient outcomes Alan McGuire, Dominique White, Tom Bartholomew, John McGrew, Lauren Luther, Angie Rollins, Michelle Salyers S4 Exploring the multifaceted nature of sustainability in community-based prevention: A mixed-method approach Brittany Cooper, Angie Funaiole S5 Theory informed behavioral health integration in primary care: Mixed methods evaluation of the implementation of routine depression and alcohol screening and assessment Julie Richards, Amy Lee, Gwen Lapham, Ryan Caldeiro, Paula Lozano, Tory Gildred, Carol Achtmeyer, Evette Ludman, Megan Addis, Larry Marx, Katharine Bradley S6 Enhancing the evidence for specialty mental health probation through a hybrid efficacy and implementation study Tonya VanDeinse, Amy Blank Wilson, Burgin Stacey, Byron Powell, Alicia Bunger, Gary Cuddeback S7 Personalizing evidence-based child mental health care within a fiscally mandated policy reform Miya Barnett, Nicole Stadnick, Lauren Brookman-Frazee, Anna Lau S8 Levera
The context-awareness is a central aspect in the design of pervasive systems, characterizing their ability to adapt its structure and behavior. The context-aware exception handling (CAEH) is an existing approach emplo...
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The context-awareness is a central aspect in the design of pervasive systems, characterizing their ability to adapt its structure and behavior. The context-aware exception handling (CAEH) is an existing approach employed to design exception handling in pervasive systems. In this approach, the context is used to define, detect, propagate, and handle exceptions. CAEH is a complex and error prone activity, needing designers' insights and domain expertise to identify and characterize contextual exceptions. However, despite the existence of formal methods to analyze the adaptive behavior of pervasive systems, such methods lack specific support to specify the CAEH behavior. In this paper, we propose a formal model to reason about the CAEH behavior. It comprises an extension of the Kripke Structure to model the context evolution of a pervasive system and a transformation function that derivates the CAEH control flow from that proposed structure.
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 ...
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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%.
A solution to the state estimation problem of systems with unmeasurable non-zero mean inputs/disturbances, which do not satisfy the disturbance decoupling conditions, is given using the Kalman filtering and Bayesian e...
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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 requ...
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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).
We report results of the study of the low-frequency noise in thin films of bismuth selenide topological insulators, which were mechanically exfoliated from bulk crystals via "graphene-like" procedures. From ...
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Artificial bee colony (ABC) is an optimization algorithm inspired on the intelligent behavior of honey bee swarms. It is suitable to be applied when mathematical techniques are impractical or provide suboptimal soluti...
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Visualization of highway traffic environments in virtual reality plays a key role on fidelity of simulation and validity of driving behaviors in driving simulator studies. This paper describes a procedure to replicate...
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Visualization of highway traffic environments in virtual reality plays a key role on fidelity of simulation and validity of driving behaviors in driving simulator studies. This paper describes a procedure to replicate a signalized intersection with many complex features into a driving simulator's 3-D databases through building a graphical visual database, constructing a road motion database, and creating simulated traffic. The validity of the visualization was assessed via the comparison of the drivers' speeds in the simulator and the speed data at the real intersection. It was found that both speed data follow normal distributions and have equal means for each intersection approach;however, that the speeds measured in the driving simulator have a larger variability than those measured in the field. The users' subjective evaluation results indicated that 92% subjects could recognize the simulated intersection in the driving simulator experiment. Therefore, the strategy of geo-specific environment modeling would be useful for studying driving behaviors in virtual environments.
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