Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

On Educational psychology: A cognitive view.

https://homepages.fhv.at/hgb/New-Papers/CMAME07_BS07b.pdf

Robust Optimization - A Comprehensive Survey

Sustainability in the construction industry: A review of recent developments based on LCA

This paper shows that an evolutionary design paradigm in engineering design education will contribute to freshman engineering design education and consequently to student retention. Evolutionary design represents a tool to contribute to student retention because it addresses student interest, it involves teamwork, it demystifies the design process, and additionally it acknowledges the demands of industry. Evolutionary product design, instead of designing a product from scratch, is often used to improve the product and better fulfill the customers’ expectations, while reducing the development time and cost. On the freshman level, it is advisable to focus on the first area, information recovery. As one phase of evolutionary design, reverse engineering lends itself to this end. In this paper, the example of a two-cycle gas weed trimmer subjected to reverse engineering is used to demonstrate how a freshman engineering design program can benefit from evolutionary design. Evolutionary design can serve as a retention tool in freshman engineering by appealing to student interest, incorporating teamwork, recognizing the demands of industry, and demystifying the design process.

Evolutionary Design Paradigm As A Retention Tool

One of the ways to determine the inherent reliability of a design is to test it under controlled environments based on the product usage that is understood by the development requirements. This can be accomplished by performing a reliability growth test on the product. A testing approach can be developed that enhances the product reliability and reduces the production testing cycle. Research performed to date points to the fact that this proposed methodology may not exist, and is the focus of continued research to refine the development of an approach to fill this gap. The combining of multiple testing approaches in order to ensure that the reliability requirement is met or exceeded while at the same time having the capability to reduce the testing cycle time when required due to schedule and cost constraints has not been addressed in the open literature till date. The methodology is to utilize a combination of multiple testing approaches to accomplish this task by exploring complementary testing ideas from various technologies that have been utilized previously with documented success. This approach demonstrated that component-level testing reduced the product-level failures by greater than 80% while at the same time reducing the schedule to complete all testing. Copyright © 2009 John Wiley & Sons, Ltd.

An Approach That Can Quickly Assess Product Reliability

This chapter gives a brief summary of probabilistic prognostics and health management (PPHM) and presents a framework to implement PPHM to predict remaining useful life (RUL) of energy systems efficiently and with minimal uncertainty. The chapter also presents the way forward by indicating that an interdisciplinary research is critical so as consortium of multidiscipline experts will come together and discuss the implementation of the framework for enhanced RUL prediction. The prediction of RUL with minimal uncertainty will significantly lower or avoid the downtime of energy systems and thereby reduce the cost of energy. The reduction in cost will make renewable energy, like wind energy, cheaper.

Probabilistic Prognostics and Health Management: A Brief Summary

This paper presents results produced by a domain-independent system development model that enables objective and quantitative calculation of certain development cycle characteristics. The presentation recounts the model’s motivation and includes an outline of the model’s structure. The outline shows that the model is constructive. As such, it provides an explanatory mechanism for the results that it produces, not just a representation of qualitative observations or measured data. The model is a Statistical Agent-based Model of Development and Evaluation (SAbMDE); and it appears to be novel with respect to previous design theory and methodology work. This paper focuses on one development cycle characteristic: resource utilization. The model’s resource estimation capability is compared to Boehm’s long-used software development estimation techniques. His Cone of Uncertainty (COU) captures project estimation accuracy empirically at project start but intuitively over a project’s duration. SAbMDE calculates estimation accuracy at start up and over project duration; and SAbMDE duplicates the COU’s empirical values. Additionally, SAbMDE produces results very similar to the Constructive Cost Model (COCOMO) effort estimation for a wide range of input values.

Stephen Ekwaro-Osire

Papers

Evolutionary Design Paradigm As A Retention Tool

An Approach That Can Quickly Assess Product Reliability

Probabilistic Prognostics and Health Management: A Brief Summary

Development Cycle Modeling: Resource Estimation

An approach that can quickly assess product reliability