Implications of Research on User Experience Design

Speaker: Ms Elisa del Galdo

Title: Implications of Research on User Experience Design

Abstract: Practitioners in the field of user experience design come from a variety of disciplines; ergonomics, computing science, psychology, interaction design, human-computer interaction, industrial engineering, just to name a few. Due to the variability in education, it is likely that a large proportion of today’s practitioners are not familiar with relevant foundational research and what implications it has for design. It is more likely that practitioners are aware of more mainstream ‘research’ that is more easily digestible, so even more recent empirical research may not be applied to their work. This talk briefly discusses a selection of foundational and recent research studies and their implications for design, with the objective of demonstrating the importance of research to the user experience practitioner.

Efficiency and scalability of the k-Means clustering method

Speaker: Dr. Giuseppe Di Fatta

Title: Efficiency and scalability of the k-Means clustering method

Abstract: One among the most influential and popular data mining methods is the k-Means algorithm for cluster analysis. Clustering is a classical unsupervised machine learning problem of the identification of groups of similar objects within a set, which is particularly useful in typical exploratory data mining applications. The scalability of the algorithms in terms of the input objects, the number of features and the number of clusters is crucial for very large sets of data. Techniques for improving the efficiency of k-Means have been largely explored in two main directions, sequential optimisation techniques and parallel processing. In the first case, the amount of computation in the sequential algorithm can be significantly reduced by adopting geometrical constraints, efficient data structures (e.g. multi-dimensional binary search trees) and partitioning strategies. This talk provides insights on the efficiency and scalability of the k-Means clustering method for both sequential and parallel implementations. In particular, it presents some recent work which improves the performance of the algorithm for very large data sets (millions of patterns) with high numbers of features and clusters.

Measuring Performance

Speaker: Mr. Sam Rakusen, CEO Raukusen Design FX Ltd

Title: Measuring Performance

Abstract: The premise on which Key Performance Indicators are used is that clients want their projects delivered to the highest possible standards of quality, cost and time while at the same time respecting the environment, the people involved in the project and those who use the completed work. The creation of KPI data means that both clients and suppliers can easily implement a system of measurement for these critical issues, can benchmark their performance and compare with the rest of their industry and then by using this information set improvement targets. Identifying weaknesses and addressing them without adverse impact in the areas of strength is the tight rope managers have to walk in order for their companies to remain sustainable, profitable and satisfy their market place.

Social rules as immanent and non-algorithmic imperatives

Speaker: Dr Ismael Al-Amoudi

Title: Social rules as immanent and non-algorithmic imperatives

Abstract: What kind of things are social rules? The paper starts from the critique of social rules articulated by ethnomethodologists and proposes an alternative conception of rules as situated, often tacit, imperatives. This ontological theorization borrows insights from critical realism and post-structuralism to explore general features of rules. For instance: they under-determine fields of legitimate actions, are prone to logical stratification, are anchored to desires and are inherently open to interpretation, though in a discursively structured way. Moreover, it is proposed that a rule is social if and only if it is internally related to a social relation. In turn, this helps to clarify and systematize how social rules relate to social positions and identities. The purpose of this ontological study is three-fold. Firstly, it attempts to articulate a realist conception of rules that avoids their dilution (as in the works of ethnomethodology) as well as their reification into codes or algorithms (as in the works of functionalist sociology). Secondly, it purports to initiate a dialogue with other authors writing on rules such as Giddens, Lawson and Searle. Finally, it aims to facilitate the development of empirical research on rules and related processes of legitimation, identification and subversion.

Research and innovation for energy efficiency in buildings in China

Speaker: Prof. Baizhan Li (PhD, MSc, BSc, FCIBSE,FRICS, CEng) Dean, Faculty of Urban Construction and Environmental Engineering, Chongqing University, China

Title: Research and innovation for energy efficiency in buildings in China

Does Modern Database Technology Solve the Problem of Conceptual Model instability?

Speaker: Mr Yasser Ades

Title: Does Modern Database Technology Solve the Problem of Conceptual Model instability?

Abstract: The seminar is a rebuttal of the claim that modern relational database technology has addressed the problem of malignant change in the conceptual database schema. It presents both empirical and theoretical evidence to suggest that it is impossible to absorb the consequences of conceptual database schema instability by means of technology. It suggests that so called Logical Data Independence is a misleading label.

Nevien Moawad's Seminar

Speaker: Ms Nevien Moawad who is an Egyptian part-time away PhD student of IRC.

Abstract: The current trend of the knowledge sharing and reuse often involves technologies of the multi-agent systems. Reuse in knowledge base system can reduce the cost and time. The most important components for sharing and reuse in knowledge base systems are ontologies and problem-solving methods. Both complementary components can be used to configure new knowledge base system from existing reusable components. This article shows an approach in which the knowledge sharing and reuse could be realized by designing a multi-agent system framework. This framework helps the developers in building a new knowledge-based system from reusable components and works as a specialized shell with pre-existing and robust libraries of knowledge. The implementation of the framework can lead to improved quality of knowledge–based systems.