28 Slices
Medium 9781601324078

Pattern Recognition and Supporting Algorithms + Machine Learning and Applications + Learning Methods (Supervised and Unsupervised) and Data Mining

Editied By Hamid R. Arabnia, David de la Fuente, Roger Dziegiel, Elena B. Kozerenko, Peter M. LaMonica,Raymond A. Liuzzi, Jose A. Olivas, Todd Waskiewicz, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti (Editors) CSREA Press PDF

Int'l Conf. Artificial Intelligence | ICAI'15 |

571

Using Google Glass and Machine Learning to

Assist People with Memory Deficiencies

Thomas Way, Adam Bemiller, Raghavender Mysari and Corinne Reimers

Applied Computing Technology Laboratory

Department of Computing Sciences

Villanova University, Villanova PA 19085 thomas.way@villanova.edu

Abstract – Memory deficiencies may occur naturally with age and for a variety of reasons including

Alzheimer’s disease, depression, side-effects of drug use, stroke, and traumatic brain injury. Because memory loss can significantly interferes with daily life, many external memory aids have been developed, though most use a passive approach. In this paper, we report on the design and prototype development of a dynamic, wearable system, called ELEPHANT, to assist those with memory deficiencies. Our design uses the Google

Glass platform and a machine learning approach to intelligently retrieve stored photographic “memories” annotated with location, date, time, and activity information to enhance the memory of the user.

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Medium 9781601324078

XV Technical Session on Applications of Advanced AI Techniques to Information Management for Solving Company-Related Problems

Editied By Hamid R. Arabnia, David de la Fuente, Roger Dziegiel, Elena B. Kozerenko, Peter M. LaMonica,Raymond A. Liuzzi, Jose A. Olivas, Todd Waskiewicz, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti (Editors) CSREA Press PDF

Int'l Conf. Artificial Intelligence | ICAI'15 |

363

Application of the FTOPSIS ranking method to an industrial facility location problem

J. Puente1, I. Fernandez1, J. Lozano1, B. Ponte1, P. Priore1, D. de la Fuente1

1

Business Administration Department, University of Oviedo, Gijón, Spain

Abstract - Industrial location problems belong to the scope of multicriteria decision making (MCDM) given the high number of attributes to be considered in its planning and analysis.

This work deals with a problem with four potential sites and five influential subjective criteria. A panel of experts related to the problem makes a fuzzy valuation of these attributes allowing to capture the uncertainty inherent in the subjectivity of such assessments-. Similarly, using the AHP method, experts provide with compared importance ratings from pairs of these attributes, facilitating the calculation of their global weights of importance. Finally, the implementation of the

FTOPSIS method, produces the ranking of the potential sites for the location problem.

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Medium 9781601324078

Machine Translation, Natural Language Processing and Related Methods

Editied By Hamid R. Arabnia, David de la Fuente, Roger Dziegiel, Elena B. Kozerenko, Peter M. LaMonica,Raymond A. Liuzzi, Jose A. Olivas, Todd Waskiewicz, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti (Editors) CSREA Press PDF


WorldComp is an
international conference that serves researchers, scholars, professionals,
students, and academicians who are looking to both foster working
relationships and gain access to the latest research results. It is being
held jointly (same location and dates) with a number of other research
conferences; namely, The 2015 World Congress in Computer Science, Computer
Engineering, and Applied Computing (WORLDCOMP'15). The Congress is among the
top five largest annual gathering of researchers in computer science,
computer engineering and applied computing. We anticipate to have attendees
from about 85 countries/territories.

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Medium 9781601324078

Artificial Intellegence: Theory, Algorithms and Applications + Cognitive Science + Modeling

Editied By Hamid R. Arabnia, David de la Fuente, Roger Dziegiel, Elena B. Kozerenko, Peter M. LaMonica,Raymond A. Liuzzi, Jose A. Olivas, Todd Waskiewicz, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti (Editors) CSREA Press PDF

Int'l Conf. Artificial Intelligence | ICAI'15 |

407

Visual Intelligence: Toward Machine

Understanding of Video Content

Michael C. Burl, Russell L. Knight, Anthony C. Barrett

Jet Propulsion Laboratory, California Institute of Technology

4800 Oak Grove Drive, Pasadena, CA 91109

Abstract - This paper describes progress toward developing visual intelligence algorithms (VI) that can produce humanlike text descriptions (captions) from video inputs. Video frames are assumed to be generated according to an underlying “script’ that specifies a camera model and the content and action in a scene. VI is formulated as the problem of recovering the script (or relevant portions of the script) given a sequence of video frames. Three types of scripts at different levels of abstraction are recovered: C-scripts contain object detections, poses, and descriptive information on a frame-by-frame basis; B-scripts assign persistent IDs to objects across frames and “smooth” frame-by-frame information; A-scripts provide a symbolic representation of video content using a sparse timeline in which Planning

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Medium 9781601324078

Genetic Algorithms + Evolutionary Strategies and Computations + Optimization Methods

Editied By Hamid R. Arabnia, David de la Fuente, Roger Dziegiel, Elena B. Kozerenko, Peter M. LaMonica,Raymond A. Liuzzi, Jose A. Olivas, Todd Waskiewicz, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti (Editors) CSREA Press PDF

Int'l Conf. Artificial Intelligence | ICAI'15 |

69

Bound Smoothing with a Biased Random-Key Genetic Algorithm

Thiago Alves de Queiroz1 , Ivan da Silva Sendin2 , and Marcos Aur´elio Batista3 of Mathematics and Technology, Federal University of Goi´as - Campus Catal˜ao, Catal˜ao, Goi´as, Brazil.

E-mail: taq@ufg.br.

2 Faculty of Computing, Federal University of Uberlˆ andia, Uberlˆandia, Minas Gerais, Brazil.

E-mail: sendin@ufu.br.

3 Department of Computer Science, Federal University of Goi´ as - Campus Catal˜ao, Catal˜ao, Goi´as, Brazil.

E-mail: marcos.batista@catalao.ufg.br.

1 Institute

Abstract— In this work we solve a subproblem of the distance geometry problem in molecular conformation. The latter aims to determine the three-dimensional structure of a molecule from a set of imprecisely distances. We are interested only in the bound smoothing subproblem, which aims to tighten bounds from a set of lower and upper bounds on distance for pair of atoms. We apply a Biased

Random-Key Genetic Algorithm to solve this subproblem, where each entry of chromosomes indicates how to decrease a bound, with the fitness function measuring the violation of the triangle inequalities. Experimental results show the effectiveness of this algorithm to solve randomly generated instances for which real distances between atoms are known in advance.

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