Engineering and Technology

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Application of a Class of Preconditioners to Large Scale Linear Programming Problems
(Springer, 1999) Baryamureeba, Venansius; Steihaug, Trond; Zhang, Yin
In most interior point methods for linear programming, a sequence of weighted linear least squares problems are solved, where the only changes from one iteration to the next are the weights and the right hand side. The weighted least squares problems are usually solved as weighted normal equations by the direct method of Cholesky factorization. In this paper, we consider solving the weighted normal equations by a preconditioned conjugate gradient method at every other iteration. We use a class of preconditioners based on a low rank correction to a Cholesky factorization obtained from the previous iteration. Numerical results show that when properly implemented, the approach of combining direct and iterative methods is promising
Generalized Association Rule Mining Using Genetic Algorithms
(Fountain Publishers, 2008) Wakabi-Waiswa, Peter P.; Baryamureeba, Venansius; Sarukesi, K.
We formulate a general Association rule mining model for extracting useful information from very large databases. An interactive Association rule mining system is designed using a combination of genetic algorithms and a modified a-priori based algorithm. The association rule mining problem is modeled as a multi-objective combinatorial problem which is solved using genetic algorithms. The combination of genetic algorithms with a-priori query optimization make association rule mining yield fast results. In this paper we use the same combination to extend it to a much more general context allowing efficient mining of very large databases for many different kinds of patterns. Given a large database of transactions, where each transaction consists of a set of items, and a taxonomy (is-a hierarchy) on the items, we find associations between items at any level of the taxonomy. We show how the idea can be used either in a general purpose mining system or in a next generation of conventional query optimizers.
ICT as an Engine for Uganda’s Economic Growth: The Role of and Opportunities for Makerere University
(Fountain Publishers Kampala, 2007) Baryamureeba, Venansius
The use of Information and Communications Technologies (ICT) to improve how goods are produced and services are delivered is a feature of everyday life in developed countries. If ICT is used appropriately, it has the potential to vastly improve productivity. Thus the issue for developing and least developed countries is how best to use ICT to achieve development objectives, given the operating constraints in these countries. The constraints are mainly lack of infrastructure and human capacity. It is now a known fact that ICT infrastructure readiness without adequate skilled ICT human capacity cannot lead to economic growth. In this paper we discuss the role of Makerere University and suggest opportunities for Makerere University in this area of ICT led –economic growth of Uganda.
ICT-enabled Services: A Critical Analysis of the Opportunities and Challenges in Uganda
(Fountain Publishers, 2008) Baryamureeba, Venansius
Information and Communications Technologies (ICTs), broadly defined, facilitate by electronic means the creation, storage, management and dissemination of information. ICT is both a vehicle for communication and a means of processing information. ICTs are part of the economic infrastructure that supports global production, trade, investment and capital flows. ICTs are means by which individuals, institutions and organizations network, undertake activities, and participate in the development process at local, national and global levels. Specifically the ICT industry is the main driver of the economies of countries like India and China. In Europe, according to the EU Commission’s annual progress report on i2010 [EU Annual report 2007], ICT drives 50% of EU growth. Denmark, The Netherlands, Finland, Sweden, The UK and Belgium -- all have higher broadband penetration rates than the USA and Japan. Technology is fuelling innovation and productivity, and there are signs of fundamental change in markets and user behavior, as countries move towards a knowledge-based economy.
The Impact of Equal Weighting of Low and High-Confidence Observations on Robust Linear Regression Computations
(BIT Numerical Mathematics, 2001) Baryamureeba, Venansius
Equal weighting of low- and high-confidence observations occurs for Huber, Talwar, and Barya weighting functions when Newton’s method is used to solve robust linear regression problems. This leads to easy updates and/or downdates of existing matrix factorizations or easy computation of coefficient matrices in linear systems from previous ones. Thus Newton’s method based on these functions has been shown to be computationally cheap. In this paper we show that a combination of Newton’s method and an iterative method is a promising approach for solving robust linear regression problems. We show that Newton’s method based on the Talwar function is an active set method. Further we show that it is possible to obtain improved estimates of the solution vector by combining a line search method like Newton’s method with an active set method.
Measuring Computing Research Excellence and Vitality
(Fountain Publishers, 2006) Ddembe, Williams; Baryamureeba, Venansius
Measuring computing excellence and vitality has become an important approach to understanding sustainable information and communication technology (ICT) for societal transformation and development around the world. In particular, developing countries are being encouraged to invest in ICT infrastructure so that they might experience the expected future social and economic benefits. This book is aimed at developing an integrated framework for measuring sustainable research excellence and vitality in computer science, in Uganda and the immediate African regions. Improving the sustainability and vitality of research capacity has become an important problem in information communication and technology (ICT), and more specifically computing research in the higher education setting for both developed and developing countries. There is little research on the factors that influence research excellence and vitality in computer science.
A Methodology for Feature Selection in Named Entity Recognition
(Fountain Publishers, 2007) Kitoogo, Fredrick Edward; Baryamureeba, Venansius
In this paper a methodology for feature selection in named entity recognition is proposed. Unlike traditional named entity recognition approaches which mainly consider accuracy improvement as the sole objective, the innovation here is manifested in the use of a multiobjective genetic algorithm which is employed for feature selection basing on various aspects including error rate reduction and time taken for evaluation, and also demonstrating the use of Pareto optimization. The proposed method is evaluated in the context of named entity recognition, using three different data sets and a K-nearest Neighbour machine learning algorithm. Comprehensive experiments demonstrate the feasibility of the methodology.
On Efficient Distribution of Data in Multicast Networks: QoS in Scalable Networks
(Springer, 2005) Lowu, Francis; Baryamureeba, Venansius
Multimedia applications or real-time applications such as audio and video on demand, teleconferencing and whiteboard sharing require Quality of Service (QoS) guarantee assurance. QoS constraints, namely required bandwidth, end-to-end delay and delay jitter are the major parameters that need to be satisfied in order to have quality assurance in a dynamic multicast network. In this paper we investigate the effect of the QoS constraints on multicast network applications and services during the processes of routing. Lastly, we propose linear routing tree algorithms for required bandwidth, end-to-end delay and delay jitter.
On the Convergence of an Inexact Primal-Dual Interior Point Method for Linear Programming
(Springer, 2005) Baryamureeba, Venansius; Steihaug, Trond
The inexact primal-dual interior point method which is discussed in this paper chooses a new iterate along an approximation to the Newton direction. The method is the Kojima, Megiddo, andMizuno globally convergent infeasible interior point algorithm. The inexact variation is shown to have the same convergence properties accepting a residue in both the primal and dual Newton step equation also for feasible iterates.
A Review of Termination Rules of an Inexact Primal-Dual Interior Point Method for Linear Programming Problems
(Investigación Operacional, 2018) Baryamureeba, Venansius; Steihaug, Trond; El Ghami, Mohamed
In this paper we apply the Inexact Newton theory on the perturbed KKT-conditions that are derived from the Karush-Kuhn-Tucker optimality conditions for the standard linear optimization problem. We discuss different formulations and accuracy requirements for the linear systems and show global convergence properties of the method.
The Role of Academia in Fostering Private Sector Competitiveness in ICT Development
(International Journal of Computing and ICT Research, 2007) Wanyama, Tom; Baryamureeba, Venansius
Increased adoption of eCommerce and Information and Communications Technology (ICT) in the private sector often leads to expanded economic growth by opening new markets, increasing access to market information, and improving efficiency [The Asia Foundation 2001]. For example, the use of eCommerce has the potential to expand the operations of Small and Medium Enterprises, and increase their competitiveness in the global supply chain network.

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