158 Chapters
Medium 9781601322470

An Automated Deduction of a "Sasaki-Implication-Restricted" Foulis-Holland Theorem from Orthomodular Quantum Logic: Part 1

Hamid R. Arabnia; David de la Fuente; Elena B. Kozerenko; Peter M. LaMonica; Raymond A. Liuzzi; Todd Waskiewicz; George Jandieri; Ashu M. G. Solo; Ivan Nunes da Silva; Fernando G. Tinetti; and Fadi Thabtah (Editors) Mercury Learning and Information PDF

402

Int'l Conf. Artificial Intelligence | ICAI'13 |

An Automated Deduction of a "SasakiImplication-Restricted" Foulis-Holland Theorem from Orthomodular Quantum Logic: Part 1

Jack K. Horner

P. O. Box 266

Los Alamos, New Mexico 87544 USA

ICAI 2013

Abstract

The optimization of quantum computing circuitry and compilers at some level must be expressed in terms of quantum-mechanical behaviors and operations. The algebra, C(H), of closed linear subspaces of

(equivalently, the system of linear operators on (observables in)) a Hilbert space is a logic of the system of

"measurement-propositions" quantum mechanical systems and is a model of an ortholattice (OL). An OL can thus be thought of as a kind of “quantum logic” (QL). C(H) is also a model of an orthomodular lattice

(OML), which is an ortholattice to which the orthomodular law has been conjoined. An OML can thus be regarded as an orthomodular (quantum) logic (OMLogic). Now a QL can be thought of as a BL in which the distributive law does not hold. Under certain commutativity conditions, a QL does satisfy the distributive law; among the most well known of these relationships are the Foulis-Holland theorems

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Medium 9781601322470

Computer-based Method for Association Response in Autonomous Conversation

Hamid R. Arabnia; David de la Fuente; Elena B. Kozerenko; Peter M. LaMonica; Raymond A. Liuzzi; Todd Waskiewicz; George Jandieri; Ashu M. G. Solo; Ivan Nunes da Silva; Fernando G. Tinetti; and Fadi Thabtah (Editors) Mercury Learning and Information PDF

118

Int'l Conf. Artificial Intelligence | ICAI'13 |

Computer-based Method for Association Response in Autonomous Conversation

Eriko Yoshimura1, Misako Imono2, Seiji Tsuchiya1 and Hirokazu Watabe1

1

Dept. of Intelligent Information Engineering & Sciences, Faculty of Science and Engineering

Doshisha University, Kyo-Tanabe, Kyoto, Japan

2

Dept. of Knowledge Engineering & Computer Sciences, Graduate School of Engineering,

Doshisha University, Kyo-Tanabe, Kyoto, Japan

Abstract - In this paper, the authors propose a method that incorporates mechanisms for handling ambiguity in speech and the ability of humans to create associations, and for formulating replies based on rule base knowledge and common knowledge, that go beyond the level that can be achieved using only conventional natural language processing and vast repositories of sample patterns. In this paper, the authors propose a method for associated replies elicited from information relating to the place as an example of how the common knowledge and associative ability described earlier are applied.

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Medium 9781601322470

Improved Multi-objective PSO for Semi-desirable Facility Location Problem

Hamid R. Arabnia; David de la Fuente; Elena B. Kozerenko; Peter M. LaMonica; Raymond A. Liuzzi; Todd Waskiewicz; George Jandieri; Ashu M. G. Solo; Ivan Nunes da Silva; Fernando G. Tinetti; and Fadi Thabtah (Editors) Mercury Learning and Information PDF

Int'l Conf. Artificial Intelligence | ICAI'13 |

239

Improved Multi-objective PSO for Semi-desirable Facility Location

Problem

Bing Qi1 , Fangyang Shen2 , Heping Liu3 and Terry House 4

1 Department of Computer Science, Methodist University, Fayetteville, NC, USA

2 Department of Computer Science and technology, New York city College of Technology, Brooklyn, NY, USA

3 Department of industrial Engineering, Auburn University, Auburn, NC, USA

4 Department of Computer Science, Methodist University, Fayetteville, NC, USA

Abstract— Evolutionary optimization algorithms have been used to solve multiple objective problems. However, most of these methods have focused on search a sufficient Pareto front, and no efforts are made to explore the diverse Pareto optimal solutions corresponding to a Pareto front. Note that in semi-obnoxious facility location problems, diversifying

Pareto optimal solutions is important. The paper therefore suggests an improved multi-objective particle swarm optimization algorithm (MOPSO) to find diversified Pareto optimal solutions in the parameter space for semi-obnoxious facility location problems while achieving a similar Pareto front in the objective space. The improvement of MOPSO is obtained by introducing a new mechanism based on distances among Pareto optimal solutions. Three semiobnoxious facility location problems from the literature are used to evaluate the performance of the improved MOPSO.

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Medium 9781601322470

Association-Based Identification of Internet Users Interests

Hamid R. Arabnia; David de la Fuente; Elena B. Kozerenko; Peter M. LaMonica; Raymond A. Liuzzi; Todd Waskiewicz; George Jandieri; Ashu M. G. Solo; Ivan Nunes da Silva; Fernando G. Tinetti; and Fadi Thabtah (Editors) Mercury Learning and Information PDF

Int'l Conf. Artificial Intelligence | ICAI'13 |

77

Association-Based Identification of Internet Users

Interests

M. Charnine,1 A. Petrov,2 and I. Kuznetsov1

Institute for Informatics Problems, Russian Academy of Sciences, Moscow, Russia

2

Tinkoff Digital, Moscow, Russia

1

Abstract – The method to provide the Internet user with useful information, while using search engines is presented.

Here we mean the systematization of search results according to user’s interests, and also showing advertisement which could be interesting for the user. We introduce concept of

"user profile", consisting of keywords/terms, reflecting user interests. The discovering of such keywords is done by parsing user queries and visited websites. The proposed method uses a tree of categories linked to related websites and to the advertising. From these websites we retrieve primary keywords characterizing categories. The primary keywords are extended with new associated ones (called secondary) which were obtained by the methods of distributive semantics.

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Medium 9781601322470

Distribution Planning with Renewable Energy Units based on Modified Shuffled Frog Leaping Algorithm

Hamid R. Arabnia; David de la Fuente; Elena B. Kozerenko; Peter M. LaMonica; Raymond A. Liuzzi; Todd Waskiewicz; George Jandieri; Ashu M. G. Solo; Ivan Nunes da Silva; Fernando G. Tinetti; and Fadi Thabtah (Editors) Mercury Learning and Information PDF

Int'l Conf. Artificial Intelligence | ICAI'13 |

551

Distribution Planning with Renewable Energy Units based on Modified Shuffled Frog Leaping Algorithm

H. A. Shayanfar *

Center of Excellence for Power

System Automation and Operation,

Elect. Eng. Dept., Iran University of

Science and Technology, Tehran, Iran

O. Abedinia

Electrical Engineering Department,

Semnan University, Semnan, Iran

N. Amjady

Electrical Engineering Department,

Semnan University, Semnan, Iran

hashayanfar@yahoo.com, oveis.abedinia@gmail.com, n_amjady@yahoo.com

Abstract— The Distributed Generation (DG) has created a challenge and an opportunity for developing various novel technologies in power generation. DG prepares a multitude of services to utilities and consumers, containing standby generation, peaks chopping sufficiency, base load generation. In this paper a planning paradigm for network upgrade based on

Modified Shuffled Frog Leaping (MSFL) algorithm is proposed.

SFLA is a decrease based stochastic search method that begins with an initial population of frogs whose characteristics, known such as memes, represent the decision variables. The algorithm uses memetic evolution in the form of influencing of ideas from one individual to another in a local search. The paradigm is able to select amongst several choices equi-cost that one assuring the optimum in terms of voltage profile, considering various scenarios of DG penetration and load demand. The proposed algorithm is applied over the 30 lines, 28 buses power system.

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