977 resultados para Semantic technologies
Resumo:
Previous behavioral studies reported a robust effect of increased naming latencies when objects to be named were blocked within semantic category, compared to items blocked between category. This semantic context effect has been attributed to various mechanisms including inhibition or excitation of lexico-semantic representations and incremental learning of associations between semantic features and names, and is hypothesized to increase demands on verbal self-monitoring during speech production. Objects within categories also share many visual structural features, introducing a potential confound when interpreting the level at which the context effect might occur. Consistent with previous findings, we report a significant increase in response latencies when naming categorically related objects within blocks, an effect associated with increased perfusion fMRI signal bilaterally in the hippocampus and in the left middle to posterior superior temporal cortex. No perfusion changes were observed in the middle section of the left middle temporal cortex, a region associated with retrieval of lexical-semantic information in previous object naming studies. Although a manipulation of visual feature similarity did not influence naming latencies, we observed perfusion increases in the perirhinal cortex for naming objects with similar visual features that interacted with the semantic context in which objects were named. These results provide support for the view that the semantic context effect in object naming occurs due to an incremental learning mechanism, and involves increased demands on verbal self-monitoring.
Resumo:
Studies of semantic impairment arising from brain disease suggest that the anterior temporal lobes are critical for semantic abilities in humans; yet activation of these regions is rarely reported in functional imaging studies of healthy controls performing semantic tasks. Here, we combined neuropsychological and PET functional imaging data to show that when healthy subjects identify concepts at a specific level, the regions activated correspond to the site of maximal atrophy in patients with relatively pure semantic impairment. The stimuli were color photographs of common animals or vehicles, and the task was category verification at specific (e.g., robin), intermediate (e.g., bird), or general (e.g., animal) levels. Specific, relative to general, categorization activated the antero-lateral temporal cortices bilaterally, despite matching of these experimental conditions for difficulty. Critically, in patients with atrophy in precisely these areas, the most pronounced deficit was in the retrieval of specific semantic information.
Resumo:
Throughout a lifetime of operation, a mobile service robot needs to acquire, store and update its knowledge of a working environment. This includes the ability to identify and track objects in different places, as well as using this information for interaction with humans. This paper introduces a long-term updating mechanism, inspired by the modal model of human memory, to enable a mobile robot to maintain its knowledge of a changing environment. The memory model is integrated with a hybrid map that represents the global topology and local geometry of the environment, as well as the respective 3D location of objects. We aim to enable the robot to use this knowledge to help humans by suggesting the most likely locations of specific objects in its map. An experiment using omni-directional vision demonstrates the ability to track the movements of several objects in a dynamic environment over an extended period of time.
Resumo:
The growing demand for electricity in New Zealand has led to the construction of new hydro-dams or power stations that have had environmental, social and cultural effects. These effects may drive increases in electricity prices, as such prices reflect the cost of running existing power stations as well as building new ones. This study uses Canterbury and Central Otago as case studies because both regions face similar issues in building new hydro-dams and ever-increasing electricity prices that will eventually prompt households to buy power at higher prices. One way for households to respond to these price changes is to generate their own electricity through microgeneration technologies (MGT). The objective of this study is to investigate public perception and preferences regarding MGT and to analyze the factors that influence people's decision to adopt such new technologies in New Zealand. The study uses a multivariate probit approach to examine households' willingness to adopt any one MGT system or a combination of the MGT systems. Our findings provide valuable information for policy makers and marketers who wish to promote effective microgeneration technologies.
Resumo:
The rate at which people move and resettle around the world is unprecedented. Mobility and resettlement is now greatly assisted by the use of inexpensive internet communication technologies (ICTs) for a wide variety of functions: to communicate locally and across territories, for localised information seeking, geo – locational mapping and for forging new social connections in host countries and cities. This article is based on a qualitative study of newly arrived migrants and mobile people from non English speaking backgrounds (NESB) to the city of Brisbane, Australia and investigates how the internet is used to assist the initial period of settling into the city. As increasing amounts of essential information is placed online, the study asks how people from NESB communities manage to negotiate the types of information they require during the early stages of resettlement, given varying levels of access to ICTs, digital and language literacy. The study finds that the internet is widely used for specific location information seeking (such as accommodation and job-seeking), but this is often supplemented with other non-mediated sources of information. The study identified implications for social policy in regard to the resourcing and access of information. While findings are specific to the study location, it is feasible that the patterns of internet use for resettlement have relevance in a broader context.
Resumo:
Information and Communication Technologies are dramatically transforming Allopathic medicine. Technological developments including Tele-medicine, Electronic health records, Standards to ensure computer systems inter-operate, Data mining, Simulation, Decision Support and easy access to medical information each contribute to empowering patients in new ways and change the practice of medicine. To date, informatics has had little impact on Ayurvedic medicine. This tutorial provides an introduction to key informatics initiatives in Allopothic medicine using real examples and suggests how applications can be applied to Ayurvedic medicine.
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This research has successfully developed a novel synthetic structural health monitoring system model that is cost-effective and flexible in sensing and data acquisition; and robust in the structural safety evaluation aspect for the purpose of long-term and frequent monitoring of large-scale civil infrastructure during their service lives. Not only did it establish a real-world structural monitoring test-bed right at the heart of QUT Gardens Point Campus but it can also facilitate reliable and prompt protection for any built infrastructure system as well as the user community involved.
Resumo:
SITEWORKS is an interdisciplinary research and practice project that invites artists, scientists and scholars to respond to the Bundanon property through the lens of their specific discipline. Over four years this has led to a series of interactive projects, many utilising electronic technologies. The inaugural investigations focussed on the geomorphology of the site and palaeoenvironmental research, specifically in the area of sea level rise and climate change [1]. In subsequent years the focus has been on water and the river; land management; Indigenous cultural heritage, and food security.
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This paper reports on a current initiative at Queensland University of Technology to provide timely, flexible and sustainable training and support to academic staff in blended learning and associated techno-pedagogies via a web-conferencing classroom and collaboration tool, Elluminate Live!. This technology was first introduced to QUT in 2008 as part of the university‘s ongoing commitment to meeting the learning needs of diverse student cohorts. The centralised Learning Design team, in collaboration with the university‘s department of eLearning Services, was given the task of providing training and support to academic staff in the effective use of the technology for teaching and learning, as part of the team‘s ongoing brief to support and enhance the provision of blended learning throughout the university. The resulting program, ―Learning Design Live‖ (LDL) is informed by Rogers‘ theory of innovation and diffusion (2003) and structured according to Wilson‘s framework for faculty development (2007). This paper discusses the program‘s design and structure, considers the program‘s impact on academic capacity in blended learning within the institution, and reflects on future directions for the program and emerging insights into blended learning and participant engagement for both staff and students.
Resumo:
Angiogenesis is indispensable for solid tumor expansion, and thus it has become a major target of cancer research and anti-cancer therapies. Deciphering the arcane actions of various cell populations during tumor angiogenesis requires sophisticated research models, which could capture the dynamics and complexity of the process. There is a continuous need for improvement of existing research models, which engages interdisciplinary approaches of tissue engineering with life sciences. Tireless efforts to develop a new model to study tumor angiogenesis result in innovative solutions, which bring us one step closer to decipher the dubious nature of cancer. This review aims to overview the recent developments, current limitations and future challenges in three-dimensional tissue-engineered models for the study of tumor angiogenesis and for the purpose of elucidating novel targets aimed at anti-cancer drug discovery.
Resumo:
This project is a step forward in the study of text mining where enhanced text representation with semantic information plays a significant role. It develops effective methods of entity-oriented retrieval, semantic relation identification and text clustering utilizing semantically annotated data. These methods are based on enriched text representation generated by introducing semantic information extracted from Wikipedia into the input text data. The proposed methods are evaluated against several start-of-art benchmarking methods on real-life data-sets. In particular, this thesis improves the performance of entity-oriented retrieval, identifies different lexical forms for an entity relation and handles clustering documents with multiple feature spaces.
Resumo:
The first year experience for students within Higher Education institutions has become increasingly important as these institutions strive to improve student retention rates. With many universities also focusing on transforming teaching and learning in an effort to attract and retain students, there is a growing demand to understand and respond to individual student requirements, such as the need to feel a sense of belonging. The literature identifies a sense of belonging as being paramount to a students satisfaction with the institution and it is within this context that this paper reports on a three year study of how first year pre-service education students use social media and mobile technologies in their personal lives and their formal education. More specifically, the study identifies trends in the use of these technologies and the growing need for students to use digital media sharing tools to connect and engage with their peers. The paper contrasts the differences in use between these groups as it seeks to identify the role these technologies can play in their teaching and learning, as well as in promoting an overall positive first year experience.
Resumo:
For preservice teachers new to the teaching profession, reflective practice can be a difficult process. Yet reflective writing, once mastered, has the capacity to support preservice teachers to make connections between teaching theory and professional practice, and to start to take control of their own professional learning journey. The reflective practice described in this chapter was scaffolded through a framework for writing, the use of annotated work samples and explicit teaching. This approach was enhanced through multimodal resources including written peer assessment, audio teacher feedback and a video recording of the class presentation. The video footage assisted the preservice teachers to reconcile the feedback that they received from multiple sources. This chapter describes and analyses the implementation of the PRT Pattern (Prompting Reflection using Technology). Results of this practice revealed that the multiple forms of feedback assisted the preservice teachers to analyse their performance in terms of their developing professional identity and practice.
Resumo:
Semantic Web offers many possibilities for future Web technologies. Therefore, it is a need to search for ways that can bring the huge amount of unstructured documents from current Web to Semantic Web automatically. One big challenge in searching for such ways is how to understand patterns by both humans and machine. To address this issue, we present an innovative model which interprets patterns to high level concepts. These concepts can explain the patterns' meanings in a human understandable way while improving the information filtering performance. The model is evaluated by comparing it against one state-of-the-art benchmark model using standard Reuters dataset. The results show that the proposed model is successful. The significance of this model is three fold. It gives a way to interpret text mining output, provides a technique to find concepts relevant to the whole set of patterns which is an essential feature to understand the topic, and to some extent overcomes information mismatch and overload problems of existing models. This model will be very useful for knowledge based applications.