37 research outputs found

    A Novel Evolutionary Algorithm with Column and Sub-Block Local Search for Sudoku Puzzles

    Get PDF
    Sudoku puzzles are not only popular intellectual games but also NP-hard combinatorial problems related to various real-world applications, which have attracted much attention worldwide. Although many efficient tools, such as evolutionary computation (EC) algorithms, have been proposed for solving Sudoku puzzles, they still face great challenges with regard to hard and large instances of Sudoku puzzles. Therefore, to efficiently solve Sudoku puzzles, this paper proposes a genetic algorithm (GA)-based method with a novel local search technology called local search-based GA (LSGA). The LSGA includes three novel design aspects. First, it adopts a matrix coding scheme to represent individuals and designs the corresponding crossover and mutation operations. Second, a novel local search strategy based on column search and sub-block search is proposed to increase the convergence speed of the GA. Third, an elite population learning mechanism is proposed to let the population evolve by learning the historical optimal solution. Based on the above technologies, LSGA can greatly improve the search ability for solving complex Sudoku puzzles. LSGA is compared with some state-of-the-art algorithms at Sudoku puzzles of different difficulty levels and the results show that LSGA performs well in terms of both convergence speed and success rates on the tested Sudoku puzzle instances

    Virtual Reality Games for Motor Rehabilitation

    Get PDF
    This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

    A forensics software toolkit for DNA steganalysis.

    Get PDF
    Recent advances in genetic engineering have allowed the insertion of artificial DNA strands into the living cells of organisms. Several methods have been developed to insert information into a DNA sequence for the purpose of data storage, watermarking, or communication of secret messages. The ability to detect, extract, and decode messages from DNA is important for forensic data collection and for data security. We have developed a software toolkit that is able to detect the presence of a hidden message within a DNA sequence, extract that message, and then decode it. The toolkit is able to detect, extract, and decode messages that have been encoded with a variety of different coding schemes. The goal of this project is to enable our software toolkit to determine with which coding scheme a message has been encoded in DNA and then to decode it. The software package is able to decode messages that have been encoded with every variation of most of the coding schemes described in this document. The software toolkit has two different options for decoding that can be selected by the user. The first is a frequency analysis approach that is very commonly used in cryptanalysis. This approach is very fast, but is unable to decode messages shorter than 200 words accurately. The second option is using a Genetic Algorithm (GA) in combination with a Wisdom of Artificial Crowds (WoAC) technique. This approach is very time consuming, but can decode shorter messages with much higher accuracy

    ACMS 18th Biennial Conference Proceedings

    Get PDF
    Association of Christians in the Mathematical Sciences 18th Biennial Conference Proceedings, June 1-4, 2011, Westmont College, Santa Barbara, CA

    ABQ Free Press, February 15, 2017

    Get PDF
    https://digitalrepository.unm.edu/abq_free_press/1081/thumbnail.jp

    Why join a team?

    Get PDF
    We present experiments exploring why high ability workers join teams with less able co-workers when there are no short-term financial benefits. We distinguish between two explanations: pro-social preferences and expected long-term financial gains from teaching future teammates. Participants perform a real-effort task and decide whether to work independently or join a two-person team. Treatments vary the payment scheme (piece rate or revenue sharing), whether teammates can communicate, and the role of teaching. High ability workers are more willing to join teams in the absence of revenue sharing and less willing to join teams when they cannot communicate. When communication is possible, the choice of high ability workers to join teams is driven by expected future financial gains from teaching rather than some variety of pro-social preferences. This result has important implications for the role of adverse selection in determining the productivity of teams

    Lab Labor: What Can Labor Economists Learn from the Lab?

    Get PDF
    This paper surveys the contributions of laboratory experiments to labor economics. We begin with a discussion of methodological issues: why (and when) is a lab experiment the best approach; how do laboratory experiments compare to field experiments; and what are the main design issues? We then summarize the substantive contributions of laboratory experiments to our understanding of principal-agent interactions, social preferences, union-firm bargaining, arbitration, gender differentials, discrimination, job search, and labor markets more generally.personnel economics, principal-agent theory, laboratory experiments, labor economics

    Lab Labor: What Can Labor Economists Learn from the Lab?

    Get PDF
    This chapter surveys the contributions of laboratory experiments to labor economics. We begin with a discussion of methodological issues: why (and when) is a lab experiment the best approach; how do laboratory experiments compare to field experiments; and what are the main design issues? We then summarize the substantive contributions of laboratory experiments to our understanding of principal-agent interactions, social preferences, union-firm bargaining, arbitration, gender differentials, discrimination, job search, and labor markets more generally.

    Columbia Chronicle (12/12/2011)

    Get PDF
    Student newspaper from December 12, 2011 entitled The Columbia Chronicle. This issue is 48 pages and is listed as Volume 47, Number 15. Cover story: \u27Occupy\u27 confronts Columbia Editor-in-Chief: Brianna Wellenhttps://digitalcommons.colum.edu/cadc_chronicle/1836/thumbnail.jp
    corecore