University of Windsor

About: University of Windsor is a education organization based out in Windsor, Ontario, Canada. It is known for research contribution in the topics: Population & Argumentation theory. The organization has 10654 authors who have published 22307 publications receiving 435906 citations. The organization is also known as: UWindsor & Assumption University of Windsor.

Optimal production and pricing policy for a closed loop system

Abstract: A closed loop system is investigated, in which the manufacturer has two channels to satisfy the demand: manufacturing brand-new products and remanufacturing returns into as-new products. Remanufactured products have no difference from brand-new products and can be sold in the same market at the same price. The demand is uncertain and sensitive to the selling price, while the return is also stochastic and sensitive to the acquisition price of used products. A mathematical model is developed to maximize the overall profit of the system by simultaneously determining the selling price, the production quantities for brand-new products and remanufactured products, and the acquisition price of used products. Some properties of the problem are analyzed, based on which a solution procedure is presented. Through a numerical example, the impacts of the uncertainties of both demand and return on the production plan, selling price, and the acquisition price of used products are analyzed.

Theory and applications of the double-base number system

Abstract: In this paper, we analyze some of the main properties of a double base number system, using bases 2 and 3; in particular, we emphasize the sparseness of the representation. A simple geometric interpretation allows an efficient implementation of the basic arithmetic operations and we introduce an index calculus for logarithmic-like arithmetic with considerable hardware reductions in lookup table size. We discuss the application of this number system in the area of digital signal processing; we illustrate the discussion with examples of finite impulse response filtering.

An Integrated Class-Imbalanced Learning Scheme for Diagnosing Bearing Defects in Induction Motors

Abstract: This paper focuses on the development of an integrated scheme for diagnosing bearing defects in induction motors, under the class-imbalanced condition. This scheme comprises of four main modules: segmentation, feature extraction, feature reduction, and fault classification. Various state-of-the-art techniques have been devised in the feature extraction and reduction modules to extract informative sets of features from a raw vibration signal, filter redundant features, and produce the most distinct features for the following module. The fault classification module adapts various state-of-the-art class-imbalanced learning techniques for diagnosing bearing defects. This module contains a novel imputation-based oversampling technique for class-imbalanced learning. This integrated diagnostic scheme is evaluated on three experimental scenarios with different imbalance ratios. The reasonable diagnostic performances confirm the ability of the proposed novel class-imbalanced learning technique in diagnosing bearing defects, independently from the imbalance ratios.

Connectivity, Recruitment Variation, and the Structure of Reef Fish Communities

Abstract: Coral reefs contain the most speciose communities of fishes on this planet, so it is appropriate to use these to explore how fish species are organized into communities. While descriptive data suggest that the diverse communities of fish on coral reefs are equilibrial assemblages of species, all finely adapted to specific and unique ecological roles, these are highly dynamic, non-equilibrial assemblages with structure driven more by patterns of recruitment and loss of individual fishes, than by patterns of resource allocation among differently adapted phenotypes. As a consequence, local assemblages differ in structure, and structure wanders through time. Individual fish are confronted by different mixes of species in different times and places. The recruitment process that drives these dynamics is complex, being governed by several mechanisms, and local populations receive some portion of their recruitment from distant sources. Information on this connectivity among local populations is critically important for management which is based increasingly on use of marine protected areas (no-take zones) both to conserve, and to provide sustainable fisheries. At present, however, we do not know the spatial scale or the extent of this connectivity, and this critical knowledge gap impedes both management, and fundamental understanding.