[Book review] Peter Reimann and Hans Spada (eds), Learning in Humans and Machines: Towards an Interdisciplinary Learning Science

Review of: Peter Reimann and Hans Spada (eds), Learning in Humans and Machines: Towards an Interdisciplinary Learning Science, Pergamon. (1995). ISBN: 978-0080425696

Digital Forestry: A white paper

Digital Forestry has been proposed as “the science, technology, and art of systematically acquiring, integrating, analyzing, and applying digital information to support sustainable forests.” Although rooted in traditional forestry disciplines, Digital Forestry draws from a host of other fields that, in the past few decades, have become important for implementing the concept of forest ecosystem management and the principle of sustainable forestry. Digital Forestry is a framework that links all facets of forestry information at local, national, and global levels through an organized digital network. It is anticipated that a new set of principles will be established when practicing Digital Forestry concept for the evolution of forestry education, research, and practices as the 21st century unfolds.

Approximation Algorithms for a Symmetric Quadratic Knapsack Problem and its Scheduling Applications

We consider a knapsack problem to minimize a symmetric quadratic function. We demonstrate that this symmetric quadratic knapsack problem is relevant to two problems of single machine scheduling: the problem of minimizing the weighted sum of the completion times with a single machine non-availability interval under the non-resumable scenario; and the problem of minimizing the total weighted earliness and tardiness with respect to a common small due date. We develop a polynomial-time approximation algorithm that delivers a constant worst-case performance ratio for a special form of the symmetric quadratic knapsack problem. We adapt that algorithm to our scheduling problems and achieve a better performance. For the problems under consideration no fixed-ratio approximation algorithms have been previously known.

Addressing time intervals

One of the fundamental questions regarding the temporal ontology is what is time composed of. While the traditional time structure is based on a set of points, a notion that has been prevalently adopted in classical physics and mathematics, it has also been noticed that intervals have been widely adopted for expre~sion of common sense temporal knowledge, especially in the domain of artificial intelligence. However, there has been a longstanding debate on how intervals should be addressed, leading to two different approaches to the treatment of intervals. In the first, intervals are addressed as derived objects constructed from points, e.g., as sets of points, or as pairs of points. In the second, intervals are taken as primitive themselves. This article provides a critical examination of these two approaches. By means of proposing a definition of intervals in terms of points and types, we shall demonstrate that, while the two different approaches have been viewed as rivals in the literature, they are actually reducible to logically equivalent expressions under some requisite interpretations, and therefore they can also be viewed as allies.