Impacts of climate change of seaports: A survey of knowledge, perceptions, and planning efforts among port administrators

Port authorities from around the world were surveyed to ascertain how administrators feel climate change might impact their operations, what level of change would be problematic, and how they plan to adapt to new conditions. The survey was distributed to 350 major ports through two leading international port organizations, the International Association of Ports and Harbors and the American Association of Port Authorities. (PDF contains 4 pages)

Vocational education for the development of knowledge system in fisheries sector

The paper aims to give the concept and functional approach of knowledge system with reference to the fisheries sector. The background and strategies to develop knowledge workers by translating the concept of knowledge system are presented. The job opportunities given in the paper strengthen the need of the development of knowledge workers through vocational education and training. The Vocational Education Programme in the backdrop can be effective both in the formal system of education through different models suggested and through the non-formal system. The modular courses varying from 50 hours and 2-3 weeks to 6 months or one year can be introduced in the formal system as pre-vocational modules (50-h duration) in IX-X classes in vocational institutions, and the non-governmental organizations/Krishi Vigyan Kendras/Indian Council of Agricultural Research may offer occupation-based modules (2-3 weeks to 6 months). The strategic approach for the development of knowledge system highlighting various issues is also suggested.

Decision making at the front end of innovation: The hidden influence of knowledge and decision criteria

Decision making at the front end of innovation is critical for the success of companies. This paper presents a method, called decision making based on knowledge (DeBK), which was created to analyze the decision-making process at the front end. The method evaluates the knowledge of project information and the importance of decision criteria, compiling a measure that indicates whether decisions are founded on available knowledge and what criteria are in fact being considered to delineate them. The potential contribution of DeBK is corroborated through two projects that faced decision-making issues at the front end of innovation. © 2014 RADMA and John Wiley & Sons Ltd.

The Role of Knowledge in Visual Shape Representation

This report shows how knowledge about the visual world can be built into a shape representation in the form of a descriptive vocabulary making explicit the important geometrical relationships comprising objects' shapes. Two computational tools are offered: (1) Shapestokens are placed on a Scale-Space Blackboard, (2) Dimensionality-reduction captures deformation classes in configurations of tokens. Knowledge lies in the token types and deformation classes tailored to the constraints and regularities ofparticular shape worlds. A hierarchical shape vocabulary has been implemented supporting several later visual tasks in the two-dimensional shape domain of the dorsal fins of fishes.

Roles of Knowledge in Motor Learning

The goal of this thesis is to apply the computational approach to motor learning, i.e., describe the constraints that enable performance improvement with experience and also the constraints that must be satisfied by a motor learning system, describe what is being computed in order to achieve learning, and why it is being computed. The particular tasks used to assess motor learning are loaded and unloaded free arm movement, and the thesis includes work on rigid body load estimation, arm model estimation, optimal filtering for model parameter estimation, and trajectory learning from practice. Learning algorithms have been developed and implemented in the context of robot arm control. The thesis demonstrates some of the roles of knowledge in learning. Powerful generalizations can be made on the basis of knowledge of system structure, as is demonstrated in the load and arm model estimation algorithms. Improving the performance of parameter estimation algorithms used in learning involves knowledge of the measurement noise characteristics, as is shown in the derivation of optimal filters. Using trajectory errors to correct commands requires knowledge of how command errors are transformed into performance errors, i.e., an accurate model of the dynamics of the controlled system, as is demonstrated in the trajectory learning work. The performance demonstrated by the algorithms developed in this thesis should be compared with algorithms that use less knowledge, such as table based schemes to learn arm dynamics, previous single trajectory learning algorithms, and much of traditional adaptive control.