Augmenting web service discovery by cognitive semantics and abduction

We argue that web service discovery technology should help the user navigate a complex problem space by providing suggestions for services which they may not be able to formulate themselves as (s)he lacks the epistemic resources to do so. Free text documents in service environments provide an untapped source of information for augmenting the epistemic state of the user and hence their ability to search effectively for services. A quantitative approach to semantic knowledge representation is adopted in the form of semantic space models computed from these free text documents. Knowledge of the user’s agenda is promoted by associational inferences computed from the semantic space. The inferences are suggestive and aim to promote human abductive reasoning to guide the user from fuzzy search goals into a better understanding of the problem space surrounding the given agenda. Experimental results are discussed based on a complex and realistic planning activity.

Discovery and characterization of IGFBP-mediated endocytosis in the human retinal pigment epithelial cell line ARPE-19

Insulin-like growth factor binding proteins (IGFBPs) are prime regulators of IGF-action in numerous cell types including the retinal pigment epithelium (RPE). The RPE performs several functions essential for vision, including growth factor secretion and waste removal via a phagocytic process mediated in part by vitronectin (Vn). In the course of studying the effects of IGFBPs on IGF-mediated VEGF secretion and Vn-mediated phagocytosis in the RPE cell line ARPE-19, we have discovered that these cells avidly ingest synthetic microspheres (2.0 μm diameter) coated with IGFBPs. Given the novelty of this finding and the established role for endocytosis in mediating IGFBP actions in other cell types, we have explored the potential role of candidate cell surface receptors. Moreover, we have examined the role of key IGFBP structural motifs, by comparing responses to three members of the IGFBP family (IGFBP-3, IGFBP-4 and IGFBP-5) which display overlapping variations in primary structure and glycosylation status. Coating of microspheres (FluoSpheres®, sulfate modified polystyrene filled with a fluorophore) was conducted at 37 °C for 1 h using 20 μg/mL of test protein, followed by extensive washing. Binding of proteins was confirmed using a microBCA assay. The negative control consisted of microspheres treated with 0.1% bovine serum albumin (BSA), and all test samples were post-treated with BSA in an effort to coat any remaining free protein binding sites, which might otherwise encourage non-specific interactions with the cell surface. Serum-starved cultures of ARPE-19 cells were incubated with microspheres for 24 h, using a ratio of approximately 100 microspheres per cell. Uptake of microspheres was quantified using a fluorometer and was confirmed visually by confocal fluorescence microscopy. The ARPE-19 cells displayed little affinity for BSA-treated microspheres, but avidly ingested large quantities of those pre-treated with Vn (ANOVA; p < 0.001). Strong responses were also observed towards recombinant formulations of non-glycosylated IGFBP-3, glycosylated IGFBP-3 and glycosylated IGFBP-5 (all p < 0.001), while glycosylated IGFBP-4 induced a relatively minor response (p < 0.05). The response to IGFBP-3 was unaffected in the presence of excess soluble IGFBP-3, IGF-I or Vn. Likewise, soluble IGFBP-3 did not induce uptake of BSA-treated microspheres. Antibodies to either the transferrin receptor or type 1 IGF-receptor displayed slight inhibitory effects on responses to IGFBPs and Vn. Heparin abolished responses to Vn, IGFBP-5 and non-glycosylated IGFBP-3, but only partially inhibited the response to glycosylated IGFBP-3. Our results demonstrate for the first time IGFBP-mediated endocytosis in ARPE-19 cells and suggest roles for the IGFBP-heparin-binding domain and glycosylation status. These findings have important implications for understanding the mechanisms of IGFBP actions on the RPE, and in particular suggest a role for IGFBP-endocytosis.

Listening to late discovery adoption and donor offspring stories : adoption, ethics and implications for contemporary donor insemination practices

For most of the 20th Century a ‘closed’ system of adoption was practised throughout Australia and other modern Western societies. This ‘closed’ system was characterised by sealed records; amended birth certificates to conceal the adoption, and prohibited contact with all biological family. Despite claims that these measures protected these children from the taint of illegitimacy the central motivations were far more complex, involving a desire to protect couples from the stigma of infertility and to provide a socially acceptable family structure (Triseliotis, Feast, & Kyle, 2005; Marshall & McDonald, 2001). From the 1960s significant evidence began to emerge that many adopted children and adults were experiencing higher incidences of psychological difficulties, characterised by problems with psychological adjustment, building self-esteem and forming a secure personal identity. These difficulties became grouped under the term ‘genealogical bewilderment’. As a result, new policies and practices were introduced to try to place the best interests of the child at the forefront. These changes reflected new understandings of adoption; as not only an individual process but also as a social and relational process that continues throughout life. Secrecy and the withholding of birth information are now prohibited in the overwhelming majority of all domestic adoptions processed in Australia (Marshall & McDonald, 2001). One little known consequence of this ‘closed’ system of adoption was the significant number of children who were never told of their adoptive status. As a consequence, some have discovered or had this information disclosed to them, as adults. The first study that looked at the late discovery of genetic origins experiences was conducted by the Post Adoption Resource Centre in New South Wales in 1999. This report found that the participants in their study expressed feelings of disbelief, confusion, anger, sorrow and loss. Further, the majority of participants continued to struggle with issues arising from this intentional concealment of their genetic origins (Perl & Markham, 1999). A second and more recent study (Passmore, Feeney & Foulstone, 2007) looked at the issue of secrecy in adoptive families as part of a broader study of 144 adult adoptees. This study found that secrecy and/or lies or misinformation on the part of adoptive parents had negative effects on both personal identity and relationships with others. The authors noted that those adoptees who found out about their adoption as adults were ‘especially likely to feel a sense of betrayal’ (p.4). Over recent years, stories of secrecy and late discovery have also started to emerge from sperm donor conceived adults (Spencer, 2007; Turner & Coyle, 2000). Current research evidence shows that although a majority of couples during the donor assisted conception process indicate that they intend to tell the offspring about their origins, as many as two-thirds or more of couples continue to withhold this information from their children (Akker, 2006; Gottlieb, A. McWhinnie, 2001; Salter-Ling, Hunter, & Glover, 2001). Why do they keep this secret? Infertility involves a range of complex factors that are often left unresolved or poorly understood by those choosing insemination by donor as a form of family building (Schaffer, J. A., & Diamond, R., 1993). These factors may only impact after the child is born, when resemblance talk becomes most pronounced. Resemblance talk is an accepted form of public discourse and a social convention that legitimises the child as part of the family and is part of the process of constructing the child’s identity within the family. Couples tend to become focused on resemblance as this is where they feel most vulnerable, and the lack of resemblance to the parenting father may trigger his sense of loss (Becker, Butler, & Nachtigall, 2005).

Beyond discovery : a case study of teacher interaction, young children and computer tasks

The integration of computer technologies into everyday classroom life continues to provide pedagogical challenges for school systems, teachers and administrators. Data from an exploratory case study of one teacher and a multiage class of children in the first years of schooling in Australia show that when young children are using computers for set tasks in small groups, they require ongoing support from teachers, and to engage in peer interactions that are meaningful and productive. Classroom organization and the nature of teacher-child talk are key factors in engaging children in set tasks and producing desirable learning and teaching outcomes.

Effects of transportation accessibility on residential property values: Application of spatial hedonic price model in Seoul, South Korea, metropolitan area

A number of studies have focused on estimating the effects of accessibility on housing values by using the hedonic price model. In the majority of studies, estimation results have revealed that housing values increase as accessibility improves, although the magnitude of estimates has varied across studies. Adequately estimating the relationship between transportation accessibility and housing values is challenging for at least two reasons. First, the monocentric city assumption applied in location theory is no longer valid for many large or growing cities. Second, rather than being randomly distributed in space, housing values are clustered in space—often exhibiting spatial dependence. Recognizing these challenges, a study was undertaken to develop a spatial lag hedonic price model in the Seoul, South Korea, metropolitan region, which includes a measure of local accessibility as well as systemwide accessibility, in addition to other model covariates. Although the accessibility measures can be improved, the modeling results suggest that the spatial interactions of apartment sales prices occur across and within traffic analysis zones, and the sales prices for apartment communities are devalued as accessibility deteriorates. Consistent with findings in other cities, this study revealed that the distance to the central business district is still a significant determinant of sales price.

Application of reinforcement learning in an open railway access market price negotiation

In an open railway access market price negotiation, it is feasible to achieve higher cost recovery by applying the principles of price discrimination. The price negotiation can be modeled as an optimization problem of revenue intake. In this paper, we present the pricing negotiation based on reinforcement learning model. A negotiated-price setting technique based on agent learning is introduced, and the feasible applications of the proposed method for open railway access market simulation are discussed.

Privacy v IP Litigation : preliminary third party discovery on the Internet

The enforcement of Intellectual Property rights poses one of the greatest current threats to the privacy of individuals online. Recent trends have shown that the balance between privacy and intellectual property enforcement has been shifted in favour of intellectual property owners. This article discusses the ways in which the scope of preliminary discovery and Anton Piller orders have been overly expanded in actions where large amounts of electronic information is available, especially against online intermediaries (service providers and content hosts). The victim in these cases is usually the end user whose privacy has been infringed without a right of reply and sometimes without notice. This article proposes some ways in which the delicate balance can be restored, and considers some safeguards for user privacy. These safeguards include restructuring the threshold tests for discovery, limiting the scope of information disclosed, distinguishing identity discovery from information discovery, and distinguishing information preservation from preliminary discovery.

Who is the corporate entrepreneur? Insights from opportunity discovery and Creation Theory

Recent research has begun to address and even compare nascent entrepreneurship and nascent corporate entrepreneurship. An opportunity based view holds great potential to integrate both streams of research, but also presents challenges in how we define corporate entrepreneurship. We extend (corporate) entrepreneurship literature to the opportunity identification phase by providing a framework to classify different types of corporate entrepreneurship. Through analysis of a large dataset on nascent (corporate) entrepreneurship (PSEDII) we show that these corporate entrepreneurs differ largely from each other in terms of human capital. Prior studies have indicated that independent and corporate entrepreneurs pursue different types of opportunities and utilize different strategies. Our findings from the opportunity identification phase challenge those differences and seem to indicate a difference between the opportunities corporate entrepreneurs identify versus the opportunities they exploit.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

Effective pattern discovery for text mining

Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase) based approaches should perform better than the term-based ones, but many experiments did not support this hypothesis. This paper presents an innovative technique, effective pattern discovery which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance.