A latent feature analysis of the neural representation of conceptual knowledge

Bayesian probabilistic analysis offers a new approach to characterize semantic representations by inferring the most likely feature structure directly from the patterns of brain activity. In this study, infinite latent feature models [1] are used to recover the semantic features that give rise to the brain activation vectors when people think about properties associated with 60 concrete concepts. The semantic features recovered by ILFM are consistent with the human ratings of the shelter, manipulation, and eating factors that were recovered by a previous factor analysis. Furthermore, different areas of the brain encode different perceptual and conceptual features. This neurally-inspired semantic representation is consistent with some existing conjectures regarding the role of different brain areas in processing different semantic and perceptual properties. © 2012 Springer-Verlag.

A sparse representation based fast detection method for surface defect detection of bottle caps

A practical machine-vision-based system is developed for fast detection of defects occurring on the surface of bottle caps. This system can be used to extract the circular region as the region of interests (ROI) from the surface of a bottle cap, and then use the circular region projection histogram (CRPH) as the matching features. We establish two dictionaries for the template and possible defect, respectively. Due to the requirements of high-speed production as well as detecting quality, a fast algorithm based on a sparse representation is proposed to speed up the searching. In the sparse representation, non-zero elements in the sparse factors indicate the defect's size and position. Experimental results in industrial trials show that the proposed method outperforms the orientation code method (OCM) and is able to produce promising results for detecting defects on the surface of bottle caps.

Low-rank representation based action recognition

Human action recognition is an important problem in computer vision, which has been applied to many applications. However, how to learn an accurate and discriminative representation of videos based on the features extracted from videos still remains to be a challenging problem. In this paper, we propose a novel method named low-rank representation based action recognition to recognize human actions. Given a dictionary, low-rank representation aims at finding the lowestrank representation of all data, which can capture the global data structures. According to its characteristics, low-rank representation is robust against noises. Experimental results demonstrate the effectiveness of the proposed approach on several publicly available datasets.

Vector representation of directional modulation transmitters

Directional Modulation (DM) is a recently proposed technique for securing wireless communication. In this paper we point out that modulation-directionality is a consequence of varying the beamforming network, either in baseband or in the RF stage, at the information rate In order to formalize and extend on previous analysis and synthesis methods a new theoretical treatment using vector representations of directional modulation (DM) systems is introduced and used to obtain the necessary and sufficient con

The List_Tree - an innovative solution to customer portfolio representation

The scale of BT's operations necessitates the use of very large scale computing systems, and the storage and management of large volumes of data. Customer product portfolios are an important form of data which can be difficult to store in a space efficient way. The difficulties arise from the inherently structured form of product portfolios, and the fact that they change over time as customers add or remove products. This paper introduces a new data-modelling abstraction called the List_Tree. It has been designed specifically to support the efficient storage and manipulation of customer product portfolios, but may also prove useful in other applications with similar general requirements.

Living in The Matrix: Virtual Reality Systems and Hyperspatial Representation in Architecture

In the digital age, the hyperspace of virtual reality systems stands out as a new spatial concept creating a parallel realm to "real" space. Virtual reality influences one’s experience of and interaction with architectural space. This "otherworld" brings up the criticism of the existing conception of space, time and body. Hyperspaces are relatively new to designers but not to filmmakers. Their cinematic representations help the comprehension of the outcomes of these new spaces. Visualisation of futuristic ideas on the big screen turns film into a medium for spatial experimentation. Creating a possible future, The Matrix (Andy and Larry Wachowski, 1999) takes the concept of hyperspace to a level not-yet-realised but imagined. With a critical gaze at the existing norms of architecture, the film creates new horizons in terms of space. In this context, this study introduces science fiction cinema as a discussion medium to understand the potentials of virtual reality systems for the architecture of the twenty first century. As a "role model" cinema helps to better understand technological and spatial shifts. It acts as a vehicle for going beyond the spatial theories and designs of the twentieth century, and defining the conception of space in contemporary architecture.

Explaining the multiparty systems of Western Europe prior to the adoption of proportional representation

The literature has difficulty explaining why the number of parties in majoritarian electoral systems often exceeds the two-party predictions associated with Duverger’s Law. To understand why this is the case, I examine several party systems in Western Europe before the adoption of proportional representation. Drawing from the social cleavage approach, I argue that the emergence of multiparty systems was because of the development of the class cleavage, which provided a base of voters sizeable enough to support third parties. However, in countries where the class cleavage became the largest cleavage, the class divide displaced other cleavages and the number of parties began to converge on two. The results show that the effect of the class cleavage was nonlinear, producing the greatest party system fragmentation in countries where class cleavages were present – but not dominant – and smaller in countries where class cleavages were either dominant or non-existent.

A belief revision framework for revising epistemic states with partial epistemic states

Belief revision performs belief change on an agent’s beliefs when new evidence (either of the form of a propositional formula or of the form of a total pre-order on a set of interpretations) is received. Jeffrey’s rule is commonly used for revising probabilistic epistemic states when new information is probabilistically uncertain. In this paper, we propose a general epistemic revision framework where new evidence is of the form of a partial epistemic state. Our framework extends Jeffrey’s rule with uncertain inputs and covers well-known existing frameworks such as ordinal conditional function (OCF) or possibility theory. We then define a set of postulates that such revision operators shall satisfy and establish representation theorems to characterize those postulates. We show that these postulates reveal common characteristics of various existing revision strategies and are satisfied by OCF conditionalization, Jeffrey’s rule of conditioning and possibility conditionalization. Furthermore, when reducing to the belief revision situation, our postulates can induce Darwiche and Pearl’s postulates C1 and C2.

Northern Ireland Representation at Westminster: Constitutional Conundrums and Political Manoeuvres

This article focuses on the issue of Northern Ireland's representation at Westminster. It investigates the political context of the decision to increase Northern Ireland's representation in the house of commons at Westminster from 12 members to 17 in 1978-9. Exploring this episode in more detail, it is argued, provides a more informed overall understanding of the history of devolution in the UK and of the way issues concerning Northern Ireland often overlapped with questions of constitutional change in Scotland and Wales. The article also throws light on the matter of Northern Ireland MPs and their voting rights at Westminster during Northern Ireland's experience of devolution prior to 1972.

An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets

The predominant fear in capital markets is that of a price spike. Commodity markets differ in that there is a fear of both upward and down jumps, this results in implied volatility curves displaying distinct shapes when compared to equity markets. The use of a novel functional data analysis (FDA) approach, provides a framework to produce and interpret functional objects that characterise the underlying dynamics of oil future options. We use the FDA framework to examine implied volatility, jump risk, and pricing dynamics within crude oil markets. Examining a WTI crude oil sample for the 2007–2013 period, which includes the global financial crisis and the Arab Spring, strong evidence is found of converse jump dynamics during periods of demand and supply side weakness. This is used as a basis for an FDA-derived Merton (1976) jump diffusion optimised delta hedging strategy, which exhibits superior portfolio management results over traditional methods.