Concurrent Smalltalk on the Message-Driven Processor

Concurrent Smalltalk is the primary language used for programming the J- Machine, a MIMD message-passing computer containing thousands of 36-bit processors connected by a very low latency network. This thesis describes in detail Concurrent Smalltalk and its implementation on the J-Machine, including the Optimist II global optimizing compiler and Cosmos fine-grain parallel operating system. Quantitative and qualitative results are presented.

Proactive Detection and Recovery of Lost Mobile Phones

This paper describes the successful implementation of a prototype software application that independently and proactively detects whether a mobile phone is lost or misused. When the mobile phone is detected as being lost or misused, the application takes steps to mitigate the impact of loss and to gather evidence. The goal is to aid in the recovery of the mobile phone. The prototype works regardless of the cellular infrastructure the mobile phone is operating in and makes minimum demands on the owner of the mobile phone. The prototype was developed on Nokia 6600 mobile phones that run Symbian Operating System 7.0s. Development was done using Nokia’s Series 60 Developer’s Platform 2.0.

Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers

The Support Vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special cases. In the RBF case, the SV algorithm automatically determines centers, weights and threshold such as to minimize an upper bound on the expected test error. The present study is devoted to an experimental comparison of these machines with a classical approach, where the centers are determined by $k$--means clustering and the weights are found using error backpropagation. We consider three machines, namely a classical RBF machine, an SV machine with Gaussian kernel, and a hybrid system with the centers determined by the SV method and the weights trained by error backpropagation. Our results show that on the US postal service database of handwritten digits, the SV machine achieves the highest test accuracy, followed by the hybrid approach. The SV approach is thus not only theoretically well--founded, but also superior in a practical application.

Granular Attrition due to Rotary Valve in a Pneumatic Conveying System

The rotary valve is a widely used mechanical device in many solids-handling industrial processes. However, it may also be responsible for most of the attrition effects occurring in a typical process. In this study, the attrition effects occurring in a rotary valve operating as a stand-alone device and as part of a pneumatic conveying system were investigated. In the former case granular attrition was carried out at three different rotary valve speeds and the experimental results obtained were found to be in good agreement with the Gwyn correlation. In the latter case three typical air flow rates were used in the pneumatic conveying system. The size distribution of the attrition product obtained at the lowest air flow rate used was not adequately described by the Gwyn correlation. The attrition process and mechanisms involved were analysed and the minimum size of the attrition product obtained from both modes of operations was found to be similar.