Factors affecting end-user computing sophistication in small business

This thesis describes research on End-User Computing (EUC) in small business in an environment where no Information System (IS) support and expertise are available. The research aims to identify the factors that contribute to EUC Sophistication and understand the extent small firms are capable of developing their own applications. The intention is to assist small firms to adopt EUC, encourage better utilisation of their IT resources and gain the benefits associated with computerisation. The factors examined are derived inductively from previous studies where a model is developed to map these factors with the degree of sophistication associated with IT and EUC. This study attempts to combine the predictive power of quantitative research through surveys with the explanatory power of qualitative research through action-oriented case study. Following critical examination of the literature, a survey of IT Adoption and EUC was conducted. Instruments were then developed to measure EUC and IT Sophistication indexes based on sophistication constructs adapted from previous studies using data from the survey. This is followed by an in-depth action case study involving two small firms to investigate the EUC phenomenon in its real life context. The accumulated findings from these mixed research strategies are used to form the final model of EUC Sophistication in small business. Results of the study suggest both EUC Sophistication and the Presence of EUC in small business are affected by Management Support and Behaviour towards EUC. Additionally EUC Sophistication is also affected by the presence of an EUC Champion. Results are also consistent with respect to the independence between IT Sophistication and EUC Sophistication. The main research contributions include an accumulated knowledge of EUC in small business, the Model of EUC Sophistication, an instrument to measure EUC Sophistication Index for small firms, and a contribution to research methods in IS.

Meta level component-based framework for distributed computing applications

Adaptability for distributed object-oriented enterprise frameworks is a critical mission for system evolution. Today, building adaptive services is a complex task due to lack of adequate framework support in the distributed computing environment. In this thesis, we propose a Meta Level Component-Based Framework (MELC) which uses distributed computing design patterns as components to develop an adaptable pattern-oriented framework for distributed computing applications. We describe our novel approach of combining a meta architecture with a pattern-oriented framework, resulting in an adaptable framework which provides a mechanism to facilitate system evolution. The critical nature of distributed technologies requires frameworks to be adaptable. Our framework employs a meta architecture. It supports dynamic adaptation of feasible design decisions in the framework design space by specifying and coordinating meta-objects that represent various aspects within the distributed environment. The meta architecture in MELC framework can provide the adaptability for system evolution. This approach resolves the problem of dynamic adaptation in the framework, which is encountered in most distributed applications. The concept of using a meta architecture to produce an adaptable pattern-oriented framework for distributed computing applications is new and has not previously been explored in research. As the framework is adaptable, the proposed architecture of the pattern-oriented framework has the abilities to dynamically adapt new design patterns to address technical system issues in the domain of distributed computing and they can be woven together to shape the framework in future. We show how MELC can be used effectively to enable dynamic component integration and to separate system functionality from business functionality. We demonstrate how MELC provides an adaptable and dynamic run time environment using our system configuration and management utility. We also highlight how MELC will impose significant adaptability in system evolution through a prototype E-Bookshop application to assemble its business functions with distributed computing components at the meta level in MELC architecture. Our performance tests show that MELC does not entail prohibitive performance tradeoffs. The work to develop the MELC framework for distributed computing applications has emerged as a promising way to meet current and future challenges in the distributed environment.

A soft-computing-based method for the automatic discovery of fuzzy rules in databases:uses for academic research and management support in marketing

The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.

EPiCS:engineering proprioception in computing systems

Modern compute systems continue to evolve towards increasingly complex, heterogeneous and distributed architectures. At the same time, functionality and performance are no longer the only aspects when developing applications for such systems, and additional concerns such as flexibility, power efficiency, resource usage, reliability and cost are becoming increasingly important. This does not only raise the question of how to efficiently develop applications for such systems, but also how to cope with dynamic changes in the application behaviour or the system environment. The EPiCS Project aims to address these aspects through exploring self-awareness and self-expression. Self-awareness allows systems and applications to gather and maintain information about their current state and environment, and reason about their behaviour. Self-expression enables systems to adapt their behaviour autonomously to changing conditions. Innovations in EPiCS are based on systematic integration of research in concepts and foundations, customisable hardware/software platforms and operating systems, and self-aware networking and middleware infrastructure. The developed technologies are validated in three application domains: computational finance, distributed smart cameras and interactive mobile media systems. © 2012 IEEE.

Developments in technologies for human-centric mobile computing and applications

With recent expansions in technology, mobile computing continues to play a vital role in all aspects of our lives. Digital technology tools such as Web browsing, media tracking, social media, and emailing have made mobile technology more than just a means of communication but has widespread use in business and social networks. Developments in Technologies for Human-Centric Mobile Computing and Applications is a comprehensive collection of knowledge and practice in the development of technologies in human –centric mobile technology. This book focuses on the developmental aspects of mobile technology; bringing together researchers, educators, and practitioners to encourage readers to think outside of the box.

A survey of self-awareness and its application in computing systems

Novel computing systems are increasingly being composed of large numbers of heterogeneous components, each with potentially different goals or local perspectives, and connected in networks which change over time. Management of such systems quickly becomes infeasible for humans. As such, future computing systems should be able to achieve advanced levels of autonomous behaviour. In this context, the system's ability to be self-aware and be able to self-express becomes important. This paper surveys definitions and current understanding of self-awareness and self-expression in biology and cognitive science. Subsequently, previous efforts to apply these concepts to computing systems are described. This has enabled the development of novel working definitions for self-awareness and self-expression within the context of computing systems.

An Algorithm for Fresnel Diffraction Computing Based on Fractional Fourier Transform

The fractional Fourier transform (FrFT) is used for the solution of the diffraction integral in optics. A scanning approach is proposed for finding the optimal FrFT order. In this way, the process of diffraction computing is speeded up. The basic algorithm and the intermediate results at each stage are demonstrated.

On Distributed Oblivious Transfer

The paper has been presented at the International Conference Pioneers of Bulgarian Mathematics, Dedicated to Nikola Obreshkoff and Lubomir Tschakaloff , Sofia, July, 2006. The material in this paper was presented in part at INDOCRYPT 2002

Computing and Visualizing Solution Sets of Interval Linear Systems

The paper has been presented at the 12th International Conference on Applications of Computer Algebra, Varna, Bulgaria, June, 2006

Efficient Computing of some Vector Operations over GF(3) and GF(4)

The problem of efficient computing of the affine vector operations (addition of two vectors and multiplication of a vector by a scalar over GF (q)), and also the weight of a given vector, is important for many problems in coding theory, cryptography, VLSI technology etc. In this paper we propose a new way of representing vectors over GF (3) and GF (4) and we describe an efficient performance of these affine operations. Computing weights of binary vectors is also discussed.

An improved memory management scheme for large scale graph computing engine GraphChi

GraphChi is the first reported disk-based graph engine that can handle billion-scale graphs on a single PC efficiently. GraphChi is able to execute several advanced data mining, graph mining and machine learning algorithms on very large graphs. With the novel technique of parallel sliding windows (PSW) to load subgraph from disk to memory for vertices and edges updating, it can achieve data processing performance close to and even better than those of mainstream distributed graph engines. GraphChi mentioned that its memory is not effectively utilized with large dataset, which leads to suboptimal computation performances. In this paper we are motivated by the concepts of 'pin ' from TurboGraph and 'ghost' from GraphLab to propose a new memory utilization mode for GraphChi, which is called Part-in-memory mode, to improve the GraphChi algorithm performance. The main idea is to pin a fixed part of data inside the memory during the whole computing process. Part-in-memory mode is successfully implemented with only about 40 additional lines of code to the original GraphChi engine. Extensive experiments are performed with large real datasets (including Twitter graph with 1.4 billion edges). The preliminary results show that Part-in-memory mode memory management approach effectively reduces the GraphChi running time by up to 60% in PageRank algorithm. Interestingly it is found that a larger portion of data pinned in memory does not always lead to better performance in the case that the whole dataset cannot be fitted in memory. There exists an optimal portion of data which should be kept in the memory to achieve the best computational performance.