Improving computer interaction for older people - studying mouse clicks

Interactions using a standard computer mouse can be particularly difficult for novice and older adult users. Tasks that involve positioning the mouse over a target and double-clicking to initiate some action can be a real challenge for many users. Hence, this paper describes a study that investigates the double-click interactions of older and younger adults and presents data that can help inform the development of methods of assistance. Twelve older adults (mean age = 63.9 years) and 12 younger adults (mean age = 20.8 years) performed click and double-click target selections with a computer mouse. Initial results show that older users make approximately twice as many errors as younger users when attempting double-clicks. For both age groups, the largest proportion of errors was due to difficulties with keeping the cursor steady between button presses. Compared with younger adults, older adults experienced more difficulties with performing two button presses within a required time interval. Understanding these interactions better is a step towards improving accessibility, and may provide some suggestions for future directions of research in this area.

Networks of contextualised ontologies for the Semantic Web

Currently many ontologies are available for addressing different domains. However, it is not always possible to deploy such ontologies to support collaborative working, so that their full potential can be exploited to implement intelligent cooperative applications capable of reasoning over a network of context-specific ontologies. The main problem arises from the fact that presently ontologies are created in an isolated way to address specific needs. However we foresee the need for a network of ontologies which will support the next generation of intelligent applications/devices, and, the vision of Ambient Intelligence. The main objective of this paper is to motivate the design of a networked ontology (Meta) model which formalises ways of connecting available ontologies so that they are easy to search, to characterise and to maintain. The aim is to make explicit the virtual and implicit network of ontologies serving the Semantic Web.

Gentlemen, stop your engines!

For fifty years, computer chess has pursued an original goal of Artificial Intelligence, to produce a chess-engine to compete at the highest level. The goal has arguably been achieved, but that success has made it harder to answer questions about the relative playing strengths of man and machine. The proposal here is to approach such questions in a counter-intuitive way, handicapping or stopping-down chess engines so that they play less well. The intrinsic lack of man-machine games may be side-stepped by analysing existing games to place computer engines as accurately as possible on the FIDE ELO scale of human play. Move-sequences may also be assessed for likelihood if computer-assisted cheating is suspected.

Generating recipient-centred explanations about drug prescription

In this paper we describe how we generated written explanations to ‘indirect users’ of a knowledge-based system in the domain of drug prescription. We call ‘indirect users’ the intended recipients of explanations, to distinguish them from the prescriber (the ‘direct’ user) who interacts with the system. The Explanation Generator was designed after several studies about indirect users' information needs and physicians' explanatory attitudes in this domain. It integrates text planning techniques with ATN-based surface generation. A double modeling component enables adapting the information content, order and style to the indirect user to whom explanation is addressed. Several examples of computer-generated texts are provided, and they are contrasted with the physicians' explanations to discuss advantages and limits of the approach adopted.

Improved SOM learning using simulated annealing

Self-Organizing Map (SOM) algorithm has been extensively used for analysis and classification problems. For this kind of problems, datasets become more and more large and it is necessary to speed up the SOM learning. In this paper we present an application of the Simulated Annealing (SA) procedure to the SOM learning algorithm. The goal of the algorithm is to obtain fast learning and better performance in terms of matching of input data and regularity of the obtained map. An advantage of the proposed technique is that it preserves the simplicity of the basic algorithm. Several tests, carried out on different large datasets, demonstrate the effectiveness of the proposed algorithm in comparison with the original SOM and with some of its modification introduced to speed-up the learning.

The role of sketches in supporting near-synchronous remote communication in computer supported collaborative design

This paper presents recent research into the functions and value of sketch outputs during computer supported collaborative design. Sketches made primarily exploiting whiteboard technology are shown to support subjects engaged in remote collaborative design, particularly when constructed in ‘nearsynchronous’ communication. The authors define near-synchronous communication and speculate that it is compatible with the reflective and iterative nature of design activity. There appears to be significant similarities between the making of sketches in near-synchronous remote collaborative design and those made on paper in more traditional face-to-face settings With the current increase in the use of computer supported collaborative working (CSCW) in undergraduate and postgraduate design education it is proposed that sketches and sketching can make important contributions to design learning in this context

Synapsing variable length crossover: Biologically inspired crossover for variable length genomes

Biological Crossover occurs during the early stages of meiosis. During this process the chromosomes undergoing crossover are synapsed together at a number of homogenous sequence sections, it is within such synapsed sections that crossover occurs. The SVLC (Synapsing Variable Length Crossover) Algorithm recurrently synapses homogenous genetic sequences together in order of length. The genomes are considered to be flexible with crossover only being permitted within the synapsed sections. Consequently, common sequences are automatically preserved with only the genetic differences being exchanged, independent of the length of such differences. In addition to providing a rationale for variable length crossover it also provides a genotypic similarity metric for variable length genomes enabling standard niche formation techniques to be utilised. In a simple variable length test problem the SVLC algorithm outperforms current variable length crossover techniques.

The philosophy of W. Ross Ashby and its relationship to 'The Matrix'

Ashby was a keen observer of the world around him, as per his technological and psychiatrical developments. Over the years, he drew numerous philosophical conclusions on the nature of human intelligence and the operation of the brain, on artificial intelligence and the thinking ability of computers and even on science in general. In this paper, the quite profound philosophy espoused by Ashby is considered as a whole, in particular in terms of its relationship with the world as it stands now and even in terms of scientific predictions of where things might lead. A meaningful comparison is made between Ashby's comments and the science fiction concept of 'The Matrix' and serious consideration is given as to how much Ashby's ideas lay open the possibility of the matrix becoming a real world eventuality.

Historical and current machine intelligence

In this article, we provide an initial insight into the study of MI and what it means for a machine to be intelligent. We discuss how MI has progressed to date and consider future scenarios in a realistic and logical way as much as possible. To do this, we unravel one of the major stumbling blocks to the study of MI, which is the field that has become widely known as "artificial intelligence"

Artificial keys for botanical identification using a multilayer perceptron neural network (MLP)

In this paper, practical generation of identification keys for biological taxa using a multilayer perceptron neural network is described. Unlike conventional expert systems, this method does not require an expert for key generation, but is merely based on recordings of observed character states. Like a human taxonomist, its judgement is based on experience, and it is therefore capable of generalized identification of taxa. An initial study involving identification of three species of Iris with greater than 90% confidence is presented here. In addition, the horticulturally significant genus Lithops (Aizoaceae/Mesembryanthemaceae), popular with enthusiasts of succulent plants, is used as a more practical example, because of the difficulty of generation of a conventional key to species, and the existence of a relatively recent monograph. It is demonstrated that such an Artificial Neural Network Key (ANNKEY) can identify more than half (52.9%) of the species in this genus, after training with representative data, even though data for one character is completely missing.

Intrinsic chess rating

This paper develops and tests formulas for representing playing strength at chess by the quality of moves played, rather than by the results of games. Intrinsic quality is estimated via evaluations given by computer chess programs run to high depth, ideally so that their playing strength is sufficiently far ahead of the best human players as to be a `relatively omniscient' guide. Several formulas, each having intrinsic skill parameters s for `sensitivity' and c for `consistency', are argued theoretically and tested by regression on large sets of tournament games played by humans of varying strength as measured by the internationally standard Elo rating system. This establishes a correspondence between Elo rating and the parameters. A smooth correspondence is shown between statistical results and the century points on the Elo scale, and ratings are shown to have stayed quite constant over time. That is, there has been little or no `rating inflation'. The theory and empirical results are transferable to other rational-choice settings in which the alternatives have well-defined utilities, but in which complexity and bounded information constrain the perception of the utility values.

HCI issues in power systems

With the advance of information technology capabilities, and the importance of human computer interfaces within society there has been a significant increase in research activity within the field of human computer interaction (HCI). This paper summarizes some of the work undertaken to date, paying particular attention to methods applicable to on-line control and monitoring systems such as those employed by The National Grid Company plc.