On Languages Accepted by P/T Systems Composed of joins

Recently, some studies linked the computational power of abstract computing systems based on multiset rewriting to models of Petri nets and the computation power of these nets to their topology. In turn, the computational power of these abstract computing devices can be understood by just looking at their topology, that is, information flow. Here we continue this line of research introducing J languages and proving that they can be accepted by place/transition systems whose underlying net is composed only of joins. Moreover, we investigate how J languages relate to other families of formal languages. In particular, we show that every J language can be accepted by a log n space-bounded non-deterministic Turing machine with a one-way read-only input. We also show that every J language has a semilinear Parikh map and that J languages and context-free languages (CFLs) are incomparable

Subnanometer Translation of Microelectromechanical Systems Measured by Discrete Fourier Analysis of CCD Images

Abstract—In-plane linear displacements of microelectromechanical systems are measured with subnanometer accuracy by observing the periodic micropatterns with a charge-coupled device camera attached to an optical microscope. The translation of the microstructure is retrieved from the video by phase-shift computation using discrete Fourier transform analysis. This approach is validated through measurements on silicon devices featuring steep-sided periodic microstructures. The results are consistent with the electrical readout of a bulk micromachined capacitive sensor, demonstrating the suitability of this technique for both calibration and sensing. Using a vibration isolation table, a standard deviation of σ = 0.13 nm could be achieved, enabling a measurement resolution of 0.5 nm (4σ) and a subpixel resolution better than 1/100 pixel. [2010-0170

The Quantum Frontier

The success of the abstract model of computation, in terms of bits, logical operations, programming language constructs, and the like, makes it easy to forget that computation is a physical process. Our cherished notions of computation and information are grounded in classical mechanics, but the physics underlying our world is quantum. In the early 80s researchers began to ask how computation would change if we adopted a quantum mechanical, instead of a classical mechanical, view of computation. Slowly, a new picture of computation arose, one that gave rise to a variety of faster algorithms, novel cryptographic mechanisms, and alternative methods of communication. Small quantum information processing devices have been built, and efforts are underway to build larger ones. Even apart from the existence of these devices, the quantum view on information processing has provided significant insight into the nature of computation and information, and a deeper understanding of the physics of our universe and its connections with computation. We start by describing aspects of quantum mechanics that are at the heart of a quantum view of information processing. We give our own idiosyncratic view of a number of these topics in the hopes of correcting common misconceptions and highlighting aspects that are often overlooked. A number of the phenomena described were initially viewed as oddities of quantum mechanics. It was quantum information processing, first quantum cryptography and then, more dramatically, quantum computing, that turned the tables and showed that these oddities could be put to practical effect. It is these application we describe next. We conclude with a section describing some of the many questions left for future work, especially the mysteries surrounding where the power of quantum information ultimately comes from.Comment: Invited book chapter for Computation for Humanity - Information Technology to Advance Society to be published by CRC Press. Concepts clarified and style made more uniform in version 2. Many thanks to the referees for their suggestions for improvement

On the Algorithmic Nature of the World

We propose a test based on the theory of algorithmic complexity and an experimental evaluation of Levin's universal distribution to identify evidence in support of or in contravention of the claim that the world is algorithmic in nature. To this end we have undertaken a statistical comparison of the frequency distributions of data from physical sources on the one hand--repositories of information such as images, data stored in a hard drive, computer programs and DNA sequences--and the frequency distributions generated by purely algorithmic means on the other--by running abstract computing devices such as Turing machines, cellular automata and Post Tag systems. Statistical correlations were found and their significance measured.Comment: Book chapter in Gordana Dodig-Crnkovic and Mark Burgin (eds.) Information and Computation by World Scientific, 2010. (http://www.idt.mdh.se/ECAP-2005/INFOCOMPBOOK/). Paper website: http://www.mathrix.org/experimentalAIT

Computation-aware intra-mode decision for H.264 coding and transcoding

[[abstract]]been equipped with modern video codecs. Video communications, especially for encoding H.264 format bit-stream, however, are usually very power-consuming, leading to rather limited communication period for mobile devices powered by batteries. Computation-aware video coding can effectively extend the battery life. In this paper, we propose a computation-aware intra mode decision for H.264 coding and transcoding applications. The proposed algorithm optimizes the visual quality by adaptively adjusting the number of prediction modes in mode decision under a given computation constraint. We introduce a new concept of computation buffer and formulate the computation control of mode decision as a rate-distortion optimization problem of computation buffer control. Experimental results show that our proposed algorithm can effectively control the computational complexity while maintaining good RD-performance and satisfying the given computation constraint.[[fileno]]2030144030046[[department]]電機工程學