1,721,005 research outputs found
Revisiting activity theory within the Internet of Things
No full textWith the emergence of the Internet of Things, interactions between humans and machines and indeed amongst machines themselves can be better understood using Leontiev's activity theory. This theory has been relevant to Human-Computer Interaction research for some time, but this paper revisits the underlying concepts with a particular emphasis on the Internet of Things. Newer approaches may be more appropriate to represent complex activities within their wider context, as opposed to the traditional (and limited) view of mediated activities at an individual level.<br/
Optimal Granularity for Service-Oriented Systems
No full textThe improved interoperability and business agility of business systems based on Service-Oriented Architecture SOA) has created an increased demand for the reengineering and migration of legacy software systems. The wide range of current migration techniques for legacy systems in different implementations technologies does not address important aspects of service granularity, which affect service reusability, governance, maintainability and cohesion. This paper proposes a novel framework for the effective identification of the key services in legacy code. The approach focuses on defining the right services based on standardized modelling languages (UML and BPMN). This framework provides effective guidelines for optimal service granularity for a wide range of possible service types
A progress report - Framework to Achieve Optimal Granularity for Service-Oriented Systems
No full textThe improved interoperability and business agility of software systems based on Service- Oriented Architecture (SOA) has created an increased demand for the reengineering and migration of legacy software systems. The wide range of current migration techniques for legacy systems implemented in different technologies does not address important aspects of service granularity, which affects service reusability, governance, maintainability and cohesion. This report provides an introduction to the field and discusses the key issues. Following this, a literature review of practical SOA approaches for building distributed systems is presented. A novel framework for the effective identification of the key services in legacy code is then presented, based on defining the right services using standardized modelling languages (UML and BPMN). This framework provides effective guidelines for determining the optimal service granularity over a wide range of possible service types. Finally, an outline plan for the future PhD research is presented together with the overall conclusion
Metrics for Measuring Service Operations Granularity
No full textService-Oriented Architecture (SOA) is intended to improve software interoperability by exposing dynamic applications as services. To evaluate the design of services in service-based systems, quality measurements are essential to decide tradeoffs between SOA quality attributes. Current SOA quality metrics pay little attention to service granularity as an important key design feature that impacts other internal SOA quality attributes. In this paper we introduce the structural attribute of service granularity for measuring service operations granularity. This metrics will assist in identifying key service operations with impact on other SOA quality. An example case study is included to demonstrate proposed metric
'Happiness': Can pervasive computing assist students to achieve success?
No full textComputing is traditionally used in higher education with fairly static configurations (fixed equipment, location and access times), but a range of powerful, sensor-rich, mobile devices are now widely available. Furthermore, the majority of current university students are highly digitally-literate, therefore the adoption of mobile technology to facilitate their learning is an interesting potential development. Such a shift, besides providing enhanced access to learning resources, could offer a greater understanding of student behaviour which could then be used to help students, e.g. by prompting them into adopting behaviour likely to increase their chances of academic success. We have explored the existing use of context-aware technologies in education, and we will study the behaviour of higher-education students in order to inform a behavioural intervention in future studies
Unobstrusive human activity recognition using smartphones and Hidden Markov Models
No full textAccelerometer data is sufficient to compute human activity recognition, even with only a single accelerometer in use. Such data can be used for many pervasive computing applications, user activity being interpreted as real-time contextual information. This paper investigates activity recognition on smartphones, as they are a suitable platform for the implementation of context-aware pervasive systems. Many machine learning algorithms are suitable for this purpose, but Hidden Markov Models (HMMs) are particularly appropriate for their ability to exploit the sequential and temporal nature of data. This paper evaluates HMMs in unobstrusive activity recognition with the added restrictions resulting from the use of the smartphone platform
Comparing attrition prediction in FutureLearn and edX MOOCs
No full textThere are a number of similarities and differences between FutureLearn MOOCs and those offered by other platforms, such as edX. In this research we compare the results of applying machine learning algorithms to predict course attrition for two case studies using datasets from a selected FutureLearn MOOC and an edX MOOC of comparable structure and themes. For each we have computed a number of attributes in a pre-processing stage from the raw data available in each course. Following this, we applied several machine learning algorithms on the pre-processed data to predict attrition levels for each course. The analysis suggests that the attribute selection varies in each scenario, which also impacts on the behaviour of the predicting algorithms
A Metrics Framework for Evaluating SOA Service Granularity
No full textService-Oriented Architecture (SOA) is intended to improve software interoperability by exposing dynamic applications as services. To evaluate the design of services in service-based systems, quality measurements are essential to decide tradeoffs between SOA quality attributes. Current SOA quality metrics pay little attention to service granularity as an important key design feature that impacts other internal SOA quality attributes. In this paper we introduce the structural attribute of service granularity for the analysis of other internal structural software attributes: complexity, cohesion and coupling. Consequently, metrics are proposed for measuring SOA internal attributes using syntax code. These metrics will assist in development of optimal service design by considering appropriate trade-offs. An example case study is included to demonstrate proposed metrics
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