Hybrid Brains - Biology, Technology Merger

In this paper an attempt has been made to take a look at how the use of implant and electrode technology can now be employed to create biological brains for robots, to enable human enhancement and to diminish the effects of certain neural illnesses. In all cases the end result is to increase the range of abilities of the recipients. An indication is given of a number of areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking the human brain directly with a computer. An overview of some of the latest developments in the field of Brain to Computer Interfacing is also given in order to assess advantages and disadvantages. The emphasis is clearly placed on practical studies that have been and are being undertaken and reported on, as opposed to those speculated, simulated or proposed as future projects. Related areas are discussed briefly only in the context of their contribution to the studies being undertaken. The area of focus is notably the use of invasive implant technology, where a connection is made directly with the cerebral cortex and/or nervous system. Tests and experimentation which do not involve human subjects are invariably carried out a priori to indicate the eventual possibilities before human subjects are themselves involved. Some of the more pertinent animal studies from this area are discussed including our own involving neural growth. The paper goes on to describe human experimentation, in which neural implants have linked the human nervous system bi-directionally with technology and the internet. A view is taken as to the prospects for the future for this implantable computing in terms of both therapy and enhancement.

Innovation clusters: key concepts

Innovation is easier to describe than it is to systematically analyse, and easier to analyse than it is to effectively promote. Part of the problem, of course, is the imprecise way in which the activity of innovation itself is conceptualised. To achieve more precision, the logic of analysis suggests that innovation should be should be systematically analysed and then divided into rough categories to produce a working taxonomy based on a number of key dimensions. A major part of the purpose of this paper is to develop such a working taxonomy.

Modular non-computational-connectionist-hybrid neural network approach to robotic systems

Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a mobile robot.

Key concepts in development geography

Key Concepts in Develpment Geography is an introductory text that provides students with the core concepts that form contemporary research and ideas within the development geography discipline. The book covers the meanings and measurement of development; its theory and practice; work, employment and development; people, culture and development; and contemporary issues in development.

Does training improve understanding of core concepts in cognitive behaviour therapy by people with intellectual disabilities? A randomized experiment

Background. People with intellectual disabilities (ID) experience similar or even higher rates of mental health problems than the general population and there is a need to develop appropriate treatments. Cognitive behaviour therapy (CBT) is effective for a wide range of disorders in the general population. However, there is some evidence that people with ID may lack the cognitive skills needed to take part in CBT. Aims. To test if people with ID can learn skills required for CBT, specifically the ability to distinguish between thoughts, feelings, and behaviours and to link thoughts and feelings (cognitive mediation). Method. A randomized independent groups design was used to examine the effect of training in CBT on two tasks measuring CBT skills. Thirty-four adults with ID were randomly allocated to the experimental condition ðN ¼ 18Þ or to the control condition ðN ¼ 16Þ. CBT skills were assessed blind at baseline and after the intervention. Results. The training led to significant improvements in participants’ ability to link thoughts and feelings, and this skill was generalized to new material. There was no effect of training on participants’ ability to distinguish amongst thoughts, feelings, and behaviours. People with ID can, therefore, learn some skills required for CBT. This implies that preparatory training for CBT might be useful for people with ID. The results might be applicable to other groups who find aspects of CBT difficult.

Exploiting a hybrid environmental design strategy in the continental climate of Beijing

The built environment in China is required to achieve a 50% reduction in carbon emissions by 2020 against the 1980 design standard. A particular challenge is how to maintain acceptable comfort conditions through the hot humid summers and cold desiccating winters of its continental climate regions. Fully air-conditioned sealed envelopes, often fully glazed, are becoming increasingly common in these regions. Remedial strategies involve technical refinements to the air-handling equipment and a contribution from renewable energy sources in an attempt to achieve the prescribed net reduction in energy use. However an alternative hybrid environmental design strategy is developed in this research project. It exploits observed temperate periods of weeks, days, even hours in duration to free-run an office and exhibition building configured to promote natural stack ventilation when ambient conditions permit and mechanical ventilation when conditions require it, the two modes delivered through the same physical infrastructure. The proposal is modelled in proprietary software and the methodology adopted is described. The challenge is compounded by its first practical application to an existing reinforced concrete frame originally designed to receive a highly glazed envelope. This original scheme is reviewed in comparison. Furthermore the practical delivery of the proposal value engineered out a proportion of the ventilation stacks. The likely consequence of this for the environmental performance of the building is investigated through a sensitivity study.

Passive and active hybrid approach to buildings design in Saudi Arabia

The building sector is one of the highest consumers of energy in the world. This has led to high dependency on using fossil fuel to supply energy without due consideration to its environmental impact. Saudi Arabia has been through rapid development accompanied by population growth, which in turn has increased the demand for construction. However, this fast development has been met without considering sustainable building design. General design practices rely on using international design approaches and features without considering the local climate and aspects of traditional passive design. This is by constructing buildings with a large amount of glass fully exposed to solar radiation. The aim of this paper is to investigate the development of sustainability in passive design and vernacular architecture. Furthermore, it compares them with current building in Saudi Arabia in terms of making the most of the climate. Moreover, it will explore the most sustainable renewable energy that can be used to reduce the environmental impact on modern building in Saudi Arabia. This will be carried out using case studies demonstrating the performance of vernacular design in Saudi Arabia and thus its benefits in terms of environmental, economic and social sustainability. It argues that the adoption of a hybrid approach can improve the energy efficiency as well as reduce the carbon footprint of buildings. This is by combining passive design, learning from the vernacular architecture and implementing innovative sustainable technologies.

Connections between concepts revealed by the electronic structure of carbon monoxide

Different models for the electronic structure of carbon monoxide are suggested in influential textbooks. Therefore, this electronic structure offers an interesting subject in teaching because it can be used as an example to relate seemingly conflicting concepts. Understanding the connections between ostensibly different methods and between different concepts, related or conflicting, is important in academic studies. The related reactivities of CO, O2, and N-2 and the notations of molecular orbitals are topics of interest and are discussed in detail.

Community engagement and social organization: introducing concepts, policy and practical applications

This chapter provides an introductory overview of how the term ‘community’ has been conceptualized in sociological literatures, noting that there remains considerable uncertainty with regard to the way in which communities could or should be defined. The chapter examines the salience of underlying concepts of social organization that can shape and influence the extent to which programmes of engagement are likely to be successful. Drawing on recent empirical work some of the key opportunities and challenges for local government in translating the concepts into practice are considered.

TRCM: a methodology for temporal analysis of evolving concepts in Twitter

The Twitter network has been labelled the most commonly used microblogging application around today. With about 500 million estimated registered users as of June, 2012, Twitter has become a credible medium of sentiment/opinion expression. It is also a notable medium for information dissemination; including breaking news on diverse issues since it was launched in 2007. Many organisations, individuals and even government bodies follow activities on the network in order to obtain knowledge on how their audience reacts to tweets that affect them. We can use postings on Twitter (known as tweets) to analyse patterns associated with events by detecting the dynamics of the tweets. A common way of labelling a tweet is by including a number of hashtags that describe its contents. Association Rule Mining can find the likelihood of co-occurrence of hashtags. In this paper, we propose the use of temporal Association Rule Mining to detect rule dynamics, and consequently dynamics of tweets. We coined our methodology Transaction-based Rule Change Mining (TRCM). A number of patterns are identifiable in these rule dynamics including, new rules, emerging rules, unexpected rules and ?dead' rules. Also the linkage between the different types of rule dynamics is investigated experimentally in this paper.

J-measure based hybrid pruning for complexity reduction in classification rules

Prism is a modular classification rule generation method based on the ‘separate and conquer’ approach that is alternative to the rule induction approach using decision trees also known as ‘divide and conquer’. Prism often achieves a similar level of classification accuracy compared with decision trees, but tends to produce a more compact noise tolerant set of classification rules. As with other classification rule generation methods, a principle problem arising with Prism is that of overfitting due to over-specialised rules. In addition, over-specialised rules increase the associated computational complexity. These problems can be solved by pruning methods. For the Prism method, two pruning algorithms have been introduced recently for reducing overfitting of classification rules - J-pruning and Jmax-pruning. Both algorithms are based on the J-measure, an information theoretic means for quantifying the theoretical information content of a rule. Jmax-pruning attempts to exploit the J-measure to its full potential because J-pruning does not actually achieve this and may even lead to underfitting. A series of experiments have proved that Jmax-pruning may outperform J-pruning in reducing overfitting. However, Jmax-pruning is computationally relatively expensive and may also lead to underfitting. This paper reviews the Prism method and the two existing pruning algorithms above. It also proposes a novel pruning algorithm called Jmid-pruning. The latter is based on the J-measure and it reduces overfitting to a similar level as the other two algorithms but is better in avoiding underfitting and unnecessary computational effort. The authors conduct an experimental study on the performance of the Jmid-pruning algorithm in terms of classification accuracy and computational efficiency. The algorithm is also evaluated comparatively with the J-pruning and Jmax-pruning algorithms.