87 resultados para Technical thought


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We report some existing work, inspired by analogies between human thought and machine computation, showing that the informational state of a digital computer can be decoded in a similar way to brain decoding. We then discuss some proposed work that would leverage this analogy to shed light on the amount of information that may be missed by the technical limitations of current neuroimaging technologies. © 2012 Springer-Verlag.

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Environmental concerns and fossil fuel shortage put pressure on both power and transportation systems. Electric vehicles (EVs) are thought to be a good solution to these problems. With EV adoption, energy flow is two way: from grid to vehicle and from vehicle to grid, which is known as vehicle-to-grid (V2G) today. This paper considers electric power systems and provides a review of the impact of V2G on power system stability. The concept and basics of V2G technology are introduced at first, followed by a description of EV application in the world. Several technical issues are detailed in V2G modeling and capacity forecasting, steady-state analysis and stability analysis. Research trends of such topics are declared at last.

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Technical market indicators are tools used by technical an- alysts to understand trends in trading markets. Technical (market) indicators are often calculated in real-time, as trading progresses. This paper presents a mathematically- founded framework for calculating technical indicators. Our framework consists of a domain specific language for the un- ambiguous specification of technical indicators, and a run- time system based on Click, for computing the indicators. We argue that our solution enhances the ease of program- ming due to aligning our domain-specific language to the mathematical description of technical indicators, and that it enables executing programs in kernel space for decreased latency, without exposing the system to users’ programming errors.

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The Biospheric Project is a nested multi-scalar urban agriculture project that aims to develop sustainable food systems in disadvantaged communities, though not only physical interventions, such as the urban masterplan and neighbourhood design to the building and its roof and façade, but also through social and commercial interventions, such as community involvement, businesses and a distribution system.

The project is focused around the Biospheric Foundation, a community interest company and research think-tank whose aim is to hasten our transition to a closed cycle, low-carbon economy. Its home is Irwell house, that houses a large-scale aquaponic-based food production system, which is directly linked to a whole-food shop (78 Steps, named after the distance from the productive system) and a whole food distribution system (the Whole Box). The building sits within a post-industrial landscape which is being developed into a new productive landscape, utilizing the the technologies developed by the Biospheric Foundation and Prof Greg Keeffe of Queens University Belfast. The collaboration links designer, academics and activists across the disciplines of Urban design, Architecture, Permaculture, landscape design, environmental science and business and community.

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Across a range of domains in psychology different theories assume different mental representations of knowledge. For example, in the literature on category-based inductive reasoning, certain theories (e.g., Rogers & McClelland, 2004; Sloutsky & Fisher, 2008) assume that the knowledge upon which inductive inferences are based is associative, whereas others (e.g., Heit & Rubinstein, 1994; Kemp & Tenenbaum, 2009; Osherson, Smith, Wilkie, López, & Shafir, 1990) assume that knowledge is structured. In this article we investigate whether associative and structured knowledge underlie inductive reasoning to different degrees under different processing conditions. We develop a measure of knowledge about the degree of association between categories and show that it dissociates from measures of structured knowledge. In Experiment 1 participants rated the strength of inductive arguments whose categories were either taxonomically or causally related. A measure of associative strength predicted reasoning when people had to respond fast, whereas causal and taxonomic knowledge explained inference strength when people responded slowly. In Experiment 2, we also manipulated whether the causal link between the categories was predictive or diagnostic. Participants preferred predictive to diagnostic arguments except when they responded under cognitive load. In Experiment 3, using an open-ended induction paradigm, people generated and evaluated their own conclusion categories. Inductive strength was predicted by associative strength under heavy cognitive load, whereas an index of structured knowledge was more predictive of inductive strength under minimal cognitive load. Together these results suggest that associative and structured models of reasoning apply best under different processing conditions and that the application of structured knowledge in reasoning is often effortful.

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The primary purpose of the BASE Project was to establish how to help individuals with Autism Spectrum Disorder out of poverty by promoting social inclusion. In order to achieve this, a range of methodologies were utilised that aimed to provide a baseline against which the effect of the Autism Act (NI) 2011 and the associated Autism Strategy (2013-2020) and Action Plans can be measured. The BASE Project is reported in 5 volumes. Volume 2 reports on the analysis of the autism module of the Northern Ireland Life and Times (NILT) Survey that assessed public awareness, attitudes, knowledge, and projected behaviours with regard to individuals with ASD (all primary data and technical reports are available at www.ark.ac.uk/nilt/).

The NILT (2012) survey first ever autism module (n=1204) offered a baseline against which the impact of new autism legislation, policies, and strategies can be measured. Key findings:

• 82% awareness: Most people in Northern Ireland are aware of autism (n=989).
• 50% of all participants knew someone with autism personally (n=606).

Of those who were aware of autism:
• 19% had a close family member with autism (n=186), and/or a friends/acquaintance (n=296), and/or a work colleague (n=79) with autism.
• Autism awareness was particularly low for those from ethnic minorities and those with no internet access.
• Awareness of autism specific legislation was low (20%).
• Good levels of knowledge about autism strengths and challenges, slight tendency to overestimate the occurrence of special talents.
• Prevalence of autism was underestimated (62% thought autism was much less prevalent than official figures or did not know).
• Fairly accurate perception about causes of autism, i.e., not caused by poor parenting (84%).
• Strong support for evidence-based behavioural interventions (77%), but confusion about interventions that are not evidence-based (64%).
• Strong positive attitudes towards children and adults in social, educational and employment settings.
• Autism not viewed as necessarily ‘lifelong’ (58%); support for independent living (78%), e.g., driving a car (83%).
• More business for employers who employ people with autism (12%).
• Strong support for families caring rather than residential care (64%).
• Confusion about service responsibility: education (26%) health (33%) or both (28%).

Given increasing prevalence rates of ASD it is important that the general population is aware of autism and able to respond responsibly to the associated strengths and challenges. The results of the NILT (2012) first ever autism module show that the general public was well aware of autism, had positive attitudes, and was relatively knowledgeable about the issues faced by individuals and families affected directly. However, there was a lack of clarity about responsibility for effective service delivery. The NILT results show that a shift in focus is necessary from ‘awareness raising campaigns’ to an approach that delivers clarity with regard to intervention and accountability.

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This paper provides an outline of the development of temporal thinking that is underpinned by the idea that temporal cognition shifts from being event dependent to event independent over the preschool period. I distinguish between three different ways in which it may be possible to have a perspective on time: (1) a perspective that is grounded in script-like representations of repeated events; (2) a more sophisticated perspective that brings in an fundamental categorical distinction between events that have already happened and events that are yet to come; and (3) a mature temporal perspective that involves orienting oneself in time using a linear temporal framework, with a grasp of the distinctions between past, present, and future. I propose that, with development, children possess each of these types of perspective in turn, and that only the last of these involves being able to represent time in an event-independent way.

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Due to increasing water scarcity, accelerating industrialization and urbanization, efficiency of irrigation water use in Northern China needs urgent improvement. Based on a sample of 347 wheat growers in the Guanzhong Plain, this paper simultaneously estimates a production function, and its corresponding first-order conditions for cost minimization, to analyze efficiency of irrigation water use. The main findings are that average technical, allocative, and overall economic efficiency are 0.35, 0.86 and 0.80, respectively. In a second stage analysis, we find that farmers’ perception of water scarcity, water price and irrigation infrastructure increase irrigation water allocative efficiency, while land fragmentation decreases it. We also show that farmers’ income loss due to higher water prices can be offset by increasing irrigation water use efficiency.