Toward construction of an inexpensive brain computer interface for goal oriented applications

The paper describes the implementation of an offline, low-cost Brain Computer Interface (BCI) alternative to more expensive commercial models. Using inexpensive general purpose clinical EEG acquisition hardware (Truscan32, Deymed Diagnostic) as the base unit, a synchronisation module was constructed to allow the EEG hardware to be operated precisely in time to allow for recording of automatically time stamped EEG signals. The synchronising module allows the EEG recordings to be aligned in stimulus time locked fashion for further processing by the classifier to establish the class of the stimulus, sample by sample. This allows for the acquisition of signals from the subject’s brain for the goal oriented BCI application based on the oddball paradigm. An appropriate graphical user interface (GUI) was constructed and implemented as the method to elicit the required responses (in this case Event Related Potentials or ERPs) from the subject.

Managing groups of files in a rule oriented data management system (iRODS)

The iRODS system, created by the San Diego Supercomputing Centre, is a rule oriented data management system that allows the user to create sets of rules to define how the data is to be managed. Each rule corresponds to a particular action or operation (such as checksumming a file) and the system is flexible enough to allow the user to create new rules for new types of operations. The iRODS system can interface to any storage system (provided an iRODS driver is built for that system) and relies on its’ metadata catalogue to provide a virtual file-system that can handle files of any size and type. However, some storage systems (such as tape systems) do not handle small files efficiently and prefer small files to be packaged up (or “bundled”) into larger units. We have developed a system that can bundle small data files of any type into larger units - mounted collections. The system can create collection families and contains its’ own extensible metadata, including metadata on which family the collection belongs to. The mounted collection system can work standalone and is being incorporated into the iRODS system to enhance the systems flexibility to handle small files. In this paper we describe the motivation for creating a mounted collection system, its’ architecture and how it has been incorporated into the iRODS system. We describe different technologies used to create the mounted collection system and provide some performance numbers.

Information system evolvability, feedback and pattern languages

Information systems for business are frequently heavily reliant on software. Two important feedback-related effects of embedding software in a business process are identified. First, the system dynamics of the software maintenance process can become complex, particularly in the number and scope of the feedback loops. Secondly, responsiveness to feedback can have a big effect on the evolvability of the information system. Ways have been explored to provide an effective mechanism for improving the quality of feedback between stakeholders during software maintenance. Understanding can be improved by using representations of information systems that are both service-based and architectural in scope. The conflicting forces that encourage change or stability can be resolved using patterns and pattern languages. A morphology of information systems pattern languages has been described to facilitate the identification and reuse of patterns and pattern languages. The kind of planning process needed to achieve consensus on a system's evolution is also considered.

Threshold-free object and ground point separation in LIDAR data

Light Detection And Ranging (LIDAR) is an important modality in terrain and land surveying for many environmental, engineering and civil applications. This paper presents the framework for a recently developed unsupervised classification algorithm called Skewness Balancing for object and ground point separation in airborne LIDAR data. The main advantages of the algorithm are threshold-freedom and independence from LIDAR data format and resolution, while preserving object and terrain details. The framework for Skewness Balancing has been built in this contribution with a prediction model in which unknown LIDAR tiles can be categorised as “hilly” or “moderate” terrains. Accuracy assessment of the model is carried out using cross-validation with an overall accuracy of 95%. An extension to the algorithm is developed to address the overclassification issue for hilly terrain. For moderate terrain, the results show that from the classified tiles detached objects (buildings and vegetation) and attached objects (bridges and motorway junctions) are separated from bare earth (ground, roads and yards) which makes Skewness Balancing ideal to be integrated into geographic information system (GIS) software packages.

Production of relative clauses in monolingual Turkish children

Research on the production of relative clauses (RCs) has shown that in English, although children start using intransitive RCs at an earlier age, more complex, bi-propositional object RCs appear later (Hamburger & Crain, 1982; Diessel and Tomasello, 2005), and children use resumptive pronouns both in acceptable and unacceptable ways (McKee, McDaniel, & Snedeker, 1998; McKee & McDaniel, 2001). To date, it is unclear whether or not the same picture emerges in Turkish, a language with an SOV word-order and overt case marking. Some studies suggested that subject RCs are more frequent in adults and children (Slobin, 1986) and yield a better performance than object RCs (Özcan, 1996), but others reported the opposite pattern (Ekmekçi, 1990). Our study addresses this issue in Turkish children and adults, and uses participants’ errors to account for the emerging asymmetry between subject and object RCs. 37 5-to-8 year old monolingual Turkish children and 23 adult controls participated in a novel elicitation task involving cards, each consisting of four different pictures (see Figure 1). There were two sets of cards, one for the participant and one for the researcher. The former had animals with accessories (e.g., a hat) whereas the latter had no accessories. Participants were instructed to hold their card without showing it to the researcher and describe the animals with particular accessories. This prompted the use of subject and object RCs. The researcher had to identify the animals in her card (see Figure 2). A preliminary repeated measures ANOVA with the factor Group (pre-school, primary-school children) showed no differences between the groups in the use of RCs (p>.1), who were therefore collapsed into one for further analyses. A repeated measures ANOVA with the factors Group (children, adults) and RC-Type (Subject, Object) showed that children used fewer RCs than adults (F(1,58)=7.54, p<.01), and both groups used fewer object than subject RCs (F(1,58)=22.46, p<.001), but there was no Group by RC-Type interaction (see Figure 3). A similar ANOVA on the rate of grammatical RCs showed a main effect of Group (F(1,58)=77.25, p<.001), a main effect of RC-Type (F(1,58)=66.33, p<.001), and an interaction of Group by RC-Type (F(1,58)=64.6, p<.001) (see Figure 4). Children made more errors than adults in object RCs (F(1,58)=87.01, p<.001), and children made more errors in object compared to subject RCs (F(1,36)=106.35, p<.001), but adults did not show this asymmetry. The error analysis revealed that children systematically avoided the object-relativizing morpheme –DIK, which requires possessive agreement with the genitive-marked subject. They also used resumptive pronouns and resumptive full-DPs in the extraction site similarly to English children (see Figure 5). These findings are in line with Slobin (1986) and Özcan (1996). Children’s errors suggest that they avoid morphosyntactic complexity of object RCs and try to preserve the canonical word order by inserting resumptive pronouns in the extraction site. Finally, cross-linguistic similarity in the acquisition of RCs in typologically different languages suggests a higher accessibility of subject RCs both at the structural (Keenan and Comrie, 1977) and conceptual level (Bock and Warren, 1986).

Object detecting artificial retina

This paper describes the novel use of agent and cellular neural Hopfield network techniques in the design of a self-contained, object detecting retina. The agents, which are used to detect features within an image, are trained using the Hebbian method which has been modified for the cellular architecture. The success of each agent is communicated with adjacent agents in order to verify the detection of an object. Initial work used the method to process bipolar images. This has now been extended to handle grey scale images. Simulations have demonstrated the success of the method and further work is planned in which the device is to be implemented in hardware.

Object-based three-dimensional X-ray imaging

A form of three-dimensional X-ray imaging, called Object 3-D, is introduced, where the relevant subject material is represented as discrete ‘objects’. The surface of each such object is derived accurately from the projections of its outline, and of its other discontinuities, in about ten conventional X-ray views, distributed in solid angle. This technique is suitable for many applications, and permits dramatic savings in radiation exposure and in data acquisition and manipulation. It is well matched to user-friendly interactive displays.