Planning Design Iterations

Companies developing new products have a wide variety of product development (PD) processes from which to choose. Each process offers a different method of iteration to manage risk. Companies must therefore consider the nature and level of risks they face in order to determine the most appropriate iteration and PD process. This paper identifies principles of risk and iteration inherent in product development and then explains how several different PD processes manage risk through iteration. It explains current research on PD decision criteria and concludes by proposing a framework to help companies better select PD processes.Singapore-MIT Alliance (SMA

New Acceleration of Nearly Optimal Univariate Polynomial Root-findERS

Univariate polynomial root-finding has been studied for four millennia and is still the subject of intensive research. Hundreds of efficient algorithms for this task have been proposed. Two of them are nearly optimal. The first one, proposed in 1995, relies on recursive factorization of a polynomial, is quite involved, and has never been implemented. The second one, proposed in 2016, relies on subdivision iterations, was implemented in 2018, and promises to be practically competitive, although user's current choice for univariate polynomial root-finding is the package MPSolve, proposed in 2000, revised in 2014, and based on Ehrlich's functional iterations. By proposing and incorporating some novel techniques we significantly accelerate both subdivision and Ehrlich's iterations. Moreover our acceleration of the known subdivision root-finders is dramatic in the case of sparse input polynomials. Our techniques can be of some independent interest for the design and analysis of polynomial root-finders.Comment: 89 pages, 5 figures, 2 table

Strategies for mlearning integration : evaluating a case study of staging and scaffolding mlearning integration across a three-year bachelor’s degree

This paper outlines the third iteration of integrating mobile web 2.0 within a Bachelors level course. An analysis and comparison of the impact of mobile web 2.0 across all three years of the 2009 course enables the development of implementation strategies that can be used to integrate mlearning into other tertiary courses, and inform the design of further Product Design mlearning integration iterations

Optimal surface profile design of deployable mesh reflectors via a force density strategy

Based on a force density method coupled with optimal design of node positions, a novel approach for optimal surface profile design of mesh reflectors is presented. Uniform tension is achieved by iterations on coefficients of force density. The positions of net nodes are recalculated in each iteration so that the faceting RMS error of the reflector surface is minimized. Applications of both prime focus and offset configurations are demonstrated. The simulation results show the effectiveness of the proposed approach

Using Optimization to Obtain a Width-Independent, Parallel, Simpler, and Faster Positive SDP Solver

We study the design of polylogarithmic depth algorithms for approximately solving packing and covering semidefinite programs (or positive SDPs for short). This is a natural SDP generalization of the well-studied positive LP problem. Although positive LPs can be solved in polylogarithmic depth while using only $\tilde{O}(\log^{2} n/\varepsilon^2)$ parallelizable iterations, the best known positive SDP solvers due to Jain and Yao require $O(\log^{14} n /\varepsilon^{13})$ parallelizable iterations. Several alternative solvers have been proposed to reduce the exponents in the number of iterations. However, the correctness of the convergence analyses in these works has been called into question, as they both rely on algebraic monotonicity properties that do not generalize to matrix algebra. In this paper, we propose a very simple algorithm based on the optimization framework proposed for LP solvers. Our algorithm only needs $\tilde{O}(\log^2 n / \varepsilon^2)$ iterations, matching that of the best LP solver. To surmount the obstacles encountered by previous approaches, our analysis requires a new matrix inequality that extends Lieb-Thirring's inequality, and a sign-consistent, randomized variant of the gradient truncation technique proposed in

VLSI top-down design based on the separation of hierarchies

Despite the presence of structure, interactions between the three views on VLSI design still lead to lengthy iterations. By separating the hierarchies for the respective views, the interactions are reduced. This separated hierarchy allows top-down design with functional abstractions as exemplified by an experimental self-timed CMOS RISC computer design