Detecting Instances of Shape Classes That Exhibit Variable Structure

This paper proposes a method for detecting shapes of variable structure in images with clutter. The term "variable structure" means that some shape parts can be repeated an arbitrary number of times, some parts can be optional, and some parts can have several alternative appearances. The particular variation of the shape structure that occurs in a given image is not known a priori. Existing computer vision methods, including deformable model methods, were not designed to detect shapes of variable structure; they may only be used to detect shapes that can be decomposed into a fixed, a priori known, number of parts. The proposed method can handle both variations in shape structure and variations in the appearance of individual shape parts. A new class of shape models is introduced, called Hidden State Shape Models, that can naturally represent shapes of variable structure. A detection algorithm is described that finds instances of such shapes in images with large amounts of clutter by finding globally optimal correspondences between image features and shape models. Experiments with real images demonstrate that our method can localize plant branches that consist of an a priori unknown number of leaves and can detect hands more accurately than a hand detector based on the chamfer distance.

Face Identification by a Cascade of Rejection Classifiers

Nearest neighbor search is commonly employed in face recognition but it does not scale well to large dataset sizes. A strategy to combine rejection classifiers into a cascade for face identification is proposed in this paper. A rejection classifier for a pair of classes is defined to reject at least one of the classes with high confidence. These rejection classifiers are able to share discriminants in feature space and at the same time have high confidence in the rejection decision. In the face identification problem, it is possible that a pair of known individual faces are very dissimilar. It is very unlikely that both of them are close to an unknown face in the feature space. Hence, only one of them needs to be considered. Using a cascade structure of rejection classifiers, the scope of nearest neighbor search can be reduced significantly. Experiments on Face Recognition Grand Challenge (FRGC) version 1 data demonstrate that the proposed method achieves significant speed up and an accuracy comparable with the brute force Nearest Neighbor method. In addition, a graph cut based clustering technique is employed to demonstrate that the pairwise separability of these rejection classifiers is capable of semantic grouping.

The differences in the social competence of children who attend integrated junior infant classes and children who attend segregated learning environments

There are a number of reasons why this researcher has decided to undertake this study into the differences in the social competence of children who attend integrated Junior Infant classes and children who attend segregated learning environments. Theses reasons are both personal and professional. My personal reasons stem from having grown up in a family which included both an aunt who presented with Down Syndrome and an uncle who presented with hearing impairment. Both of these relatives' experiences in our education system are interesting. My aunt was considered ineducable while her brother - my uncle - was sent to Dublin (from Cork) at six years of age to be educated by a religious order. My professional reasons, on the other hand, stemmed from my teaching experience. Having taught in both special and integrated classrooms it became evident to me that there was somewhat 'suspicion' attached to integration. Parents of children without disabilities questioned whether this process would have a negative impact on their children's education. While parents of children with disabilities debated whether integrated settings met the specific needs of their children. On the other hand, I always questioned whether integration and inclusiveness meant the same thing. My research has enabled me to find many answers. Increasingly, children with special educational needs (SEN) are attending a variety of integrated and inclusive childcare and education settings. This contemporary practice of educating children who present with disabilities in mainstream classrooms has stimulated vast interest on the impact of such practices on children with identified disabilities. Indeed, children who present with disabilities "fare far better in mainstream education than in special schools" (Buckley, cited in Siggins, 2001,p.25). However, educators and practitioners in the field of early years education and care are concerned with meeting the needs of all children in their learning environments, while also upholding high academic standards (Putman, 1993). Fundamentally, therefore, integrated education must also produce questions about the impact of this practice on children without identified special educational needs. While these questions can be addressed from the various areas of child development (i.e. cognitive, physical, linguistic, emotional, moral, spiritual and creative), this research focused on the social domain. It investigates the development of social competence in junior infant class children without identified disabilities as they experience different educational settings.

The early years in Irish multigrade classes: trajectories of practice and identity

This study investigates how the experiences of Junior Infants are shaped in multigrade classes. Multigrade classes are composed of two or more grades within the same classroom with one teacher having responsibility for the instruction of all grades in this classroom within a time-tabled period (Little, 2001, Mason and Doepner, 1998). The overall aim of the research is to problematize the issues of early childhood pedagogy in multigrade classes in the context of children negotiating identities, positioning and power relations. A Case Study approach was employed to explore the perspectives of the teachers, children and their parents in eight multigrade schools. Concurrent with this, a nation-wide Questionnaire Survey was also conducted which gave a broader context to the case study findings. Findings from the research study suggest that institutional context is vitally important and finding the space to implement pedagogic practices is a highly complex matter for teachers. While a majority of teachers reported the benefits for younger children being in mixed-age settings alongside older children, only a minority of case study school teachers demonstrated how it is possible to promote classroom climates which were provided multiple opportunities for younger children to engage fully in classrooms. The findings reveal constraints on pedagogical practice which included: time pressures within the job, an increase in diversity in pupil population, meeting special needs, large class sizes, high pupil/teacher ratios, and planning/organisation of tasks which intensified the complexities of addressing the needs of children who differ significantly in age, cognitive, social and emotional levels. An emergent and recurrent theme of this study is the representation of Junior Infants as apprentices in their ‘communities of practice’ who contributed in peripheral ways to the practices of their groups (Lave and Wenger, 1991, Wenger, 1998). Through a continuous process of negotiation of meaning, these pupils learned the knowledge and skills within their communities of practice that empowered some to participate more fully than others. The children in their ‘figured worlds’ (Holland, Lachiotte, Skinner and Caine 1998) occupy identities which are influenced by established arrangements of resources and practices within that community as well as by their own agentive actions. Finally, the findings of the study also demonstrate how the dimension of power is central to the exercise of social relations and pedagogical practices in multigrade classes.

Proteomic approaches to environmental stress in mussel Mytilus edulis due to emerging classes of anthropogenic pollutants

Anthropogenic pollutant chemicals pose a major threat to aquatic organisms. There is a need for more research on emerging categories of environmental chemicals such as nanomaterials, endocrine disruptors and pharmaceuticals. Proteomics offers options and advantages for early warning of alterations in environmental quality by detecting sub-lethal changes in sentinel species such as the mussel, Mytilus edulis. This thesis aimed to compare the potential of traditional biomarkers (such as enzyme activity measurement) and newer redox proteomic approaches. Environmental proteomics, especially a redox proteomics toolbox, may be a novel way to study pollutant effects on organisms which can also yield information on risks to human health. In particular, it can probe subtle biochemical changes at sub-lethal concentrations and thus offer novel insights to toxicity mechanisms. In the first instance, the present research involved a field-study in three stations in Cork Harbour, Ireland (Haulbowline, Ringaskiddy and Douglas) compared to an outharbour control site in Bantry Bay, Ireland. Then, further research was carried out to detect effects of anthropogenic pollution on selected chemicals. Diclofenac is an example of veterinary and human pharmaceuticals, an emerging category of chemical pollutants, with potential to cause serious toxicity to non-target organisms. A second chemical used for this study was copper which is a key source of contamination in marine ecosystems. Thirdly, bisphenol A is a major anthropogenic chemical mainly used in polycarbonate plastics manufacturing that is widespread in the environment. It is also suspected to be an endocrine disruptor. Effects on the gill, the principal feeding organ of mussels, were investigated in particular. Effects on digestive gland were also investigated to compare different outcomes from each tissue. Across the three anthropogenic chemicals studied (diclofenac, copper and bisphenol A), only diclofenac exposure did not show any significant difference towards glutathione transferase (GST) responses. Meanwhile, copper and bisphenol A significantly increased GST in gill. Glutathione reductase (GR) enzyme analysis revealed that all three chemicals have significant responses in gill. Catalase activity showed significant differences in digestive gland exposed to diclofenac and gills exposed to bisphenol A. This study focused then on application of redox proteomics; the study of the oxidative modification of proteins, to M. edulis. Thiol proteins were labelled with 5-iodoacetamidofluorescein prior to one-dimensional and two-dimensional electrophoresis. This clearly revealed some similarities on a portion of the redox proteome across chemical exposures indicating where toxicity mechanism may be common and where effects are unique to a single treatment. This thesis documents that proteomics is a robust tool to provide valuable insights into possible mechanisms of toxicity of anthropogenic contaminants in M. edulis. It is concluded that future research should focus on gill tissue, on protein thiols and on key individual proteins discovered in this study such as calreticulin and arginine kinase which have not previously been considered as biomarkers in aquatic toxicology prior to this study.

Puzzling thoughts for H. M.: can new semantic information be anchored to old semantic memories?

Researchers currently debate whether new semantic knowledge can be learned and retrieved despite extensive damage to medial temporal lobe (MTL) structures. The authors explored whether H. M., a patient with amnesia, could acquire new semantic information in the context of his lifelong hobby of solving crossword puzzles. First, H. M. was tested on a series of word-skills tests believed important in solving crosswords. He also completed 3 new crosswords: 1 puzzle testing pre-1953 knowledge, another testing post-1953 knowledge, and another combining the 2 by giving postoperative semantic clues for preoperative answers. From the results, the authors concluded that H. M. can acquire new semantic knowledge, at least temporarily, when he can anchor it to mental representations established preoperatively.

The neural basis of naming impairments in Alzheimer's disease revealed through positron emission tomography.

The naming impairments in Alzheimer's disease (AD) have been attributed to a variety of cognitive processing deficits, including impairments in semantic memory, visual perception, and lexical access. To further understand the underlying biological basis of the naming failures in AD, the present investigation examined the relationship of various classes of naming errors to regional brain measures of cerebral glucose metabolism as measured with 18 F-Fluoro-2-deoxyglucose (FDG) and positron emission tomography (PET). Errors committed on a visual naming test were categorized according to a cognitive processing schema and then examined in relationship to metabolism within specific brain regions. The results revealed an association of semantic errors with glucose metabolism in the frontal and temporal regions. Language access errors, such as circumlocutions, and word blocking nonresponses were associated with decreased metabolism in areas within the left hemisphere. Visuoperceptive errors were related to right inferior parietal metabolic function. The findings suggest that specific brain areas mediate the perceptual, semantic, and lexical processing demands of visual naming and that visual naming problems in dementia are related to dysfunction in specific neural circuits.

The abstraction of form in semantic categories.

Undergraduates were asked to generate a name for a hypothetical new exemplar of a category. They produced names that had the same numbers of syllables, the same endings, and the same types of word stems as existing exemplars of that category. In addition, novel exemplars, each consisting of a nonsense syllable root and a prototypical ending, were accurately assigned to categories. The data demonstrate the abstraction and use of surface properties of words.

Mapping the semantic structure of cognitive neuroscience.

Cognitive neuroscience, as a discipline, links the biological systems studied by neuroscience to the processing constructs studied by psychology. By mapping these relations throughout the literature of cognitive neuroscience, we visualize the semantic structure of the discipline and point to directions for future research that will advance its integrative goal. For this purpose, network text analyses were applied to an exhaustive corpus of abstracts collected from five major journals over a 30-month period, including every study that used fMRI to investigate psychological processes. From this, we generate network maps that illustrate the relationships among psychological and anatomical terms, along with centrality statistics that guide inferences about network structure. Three terms--prefrontal cortex, amygdala, and anterior cingulate cortex--dominate the network structure with their high frequency in the literature and the density of their connections with other neuroanatomical terms. From network statistics, we identify terms that are understudied compared with their importance in the network (e.g., insula and thalamus), are underspecified in the language of the discipline (e.g., terms associated with executive function), or are imperfectly integrated with other concepts (e.g., subdisciplines like decision neuroscience that are disconnected from the main network). Taking these results as the basis for prescriptive recommendations, we conclude that semantic analyses provide useful guidance for cognitive neuroscience as a discipline, both by illustrating systematic biases in the conduct and presentation of research and by identifying directions that may be most productive for future research.

All my children: The roles of semantic category and phonetic similarity in the misnaming of familiar individuals.

Despite knowing a familiar individual (such as a daughter) well, anecdotal evidence suggests that naming errors can occur among very familiar individuals. Here, we investigate the conditions surrounding these types of errors, or misnamings, in which a person (the misnamer) incorrectly calls a familiar individual (the misnamed) by someone else's name (the named). Across 5 studies including over 1,700 participants, we investigated the prevalence of the phenomenon of misnaming, identified factors underlying why it may occur, and tested potential mechanisms. We included undergraduates and MTurk workers and asked questions of both the misnamed and the misnamer. We find that familiar individuals are often misnamed with the name of another member of the same semantic category; family members are misnamed with another family member's name and friends are misnamed with another friend's name. Phonetic similarity between names also leads to misnamings; however, the size of this effect was smaller than that of the semantic category effect. Overall, the misnaming of familiar individuals is driven by the relationship between the misnamer, misnamed, and named; phonetic similarity between the incorrect name used by the misnamer and the correct name also plays a role in misnaming.

The centrality of groups and classes

This paper extends the standard network centrality measures of degree, closeness and betweenness to apply to groups and classes as well as individuals. The group centrality measures will enable researchers to answer such questions as ‘how central is the engineering department in the informal influence network of this company?’ or ‘among middle managers in a given organization, which are more central, the men or the women?’ With these measures we can also solve the inverse problem: given the network of ties among organization members, how can we form a team that is maximally central? The measures are illustrated using two classic network data sets. We also formalize a measure of group centrality efficiency, which indicates the extent to which a group's centrality is principally due to a small subset of its members.

Managing digital libraries using semantic web technologies

The aim of this work is to improve retrieval and navigation services on bibliographic data held in digital libraries. This paper presents the design and implementation of OntoBib¸ an ontology-based bibliographic database system that adopts ontology-driven search in its retrieval. The presented work exemplifies how a digital library of bibliographic data can be managed using Semantic Web technologies and how utilizing the domain specific knowledge improves both search efficiency and navigation of web information and document retrieval.

Semantic and conceptual structures in module design

This paper describes the employment of semantic and conceptual structures in module design, specifically course modules. Additionally, it suggests other uses of these structures in aiding teaching and learning.

Personalised e-learning, semantic web and learning ontologies

Kurzel(2004) points out that researchers in e-learning and educational technologists, in a quest to provide improved Learning Environments (LE) for students are focusing on personalising the experience through a Learning Management System (LMS) that attempts to tailor the LE to the individual (see amongst others Eklund & Brusilovsky, 1998; Kurzel, Slay, & Hagenus, 2003; Martinez,2000; Sampson, Karagiannidis, & Kinshuk, 2002; Voigt & Swatman; 2003). According to Kurzel (2004) this tailoring can have an impact on content and how it’s accessed; the media forms used; method of instruction employed and the learning styles supported. This project is aiming to move personalisation forward to the next generation, by tackling the issue of Personalised e-Learning platforms as pre-requisites for building and generating individualised learning solutions. The proposed development is to create an e-learning platform with personalisation built-in. This personalisation is proposed to be set from different levels of within the system starting from being guided by the information that the user inputs into the system down to the lower level of being set using information inferred by the system’s processing engine. This paper will discuss some of our early work and ideas.

Semantic web and e-learning

With emergence of "Semantic Web" there has been much discussion about the impact of technologies such as XML and RDF on the way we use the Web for developing e-learning applications and perhaps more importantly on how we can personalise these applications. Personalisation of e-learning is viewed by many authors (see amongst others Eklund & Brusilovsky, 1998; Kurzel, Slay, & Hagenus, 2003; Martinez, 2000; Sampson, Karagiannidis, & Kinshuk, 2002; Voigt & Swatman, 2003) as the key challenge for the learning technologists. According to Kurzel (2004) the tailoring of e-learning applications can have an impact on content and how it's accesses; the media forms used; method of instruction employed and the learning styles supported. This paper will report on a research project currently underway at the eCentre in University of Greenwich which is exploring different approaches and methodologies to create an e-learning platform with personalisation built-in. This personalisation is proposed to be set from different levels of within the system starting from being guided by the information that the user inputs into the system down to the lower level of being set using information inferred by the system's processing engine.