Empirical analysis of the effect of dimension reduction and word order on semantic vectors

The aim of this paper is to provide a comparison of various algorithms and parameters to build reduced semantic spaces. The effect of dimension reduction, the stability of the representation and the effect of word order are examined in the context of the five algorithms bearing on semantic vectors: Random projection (RP), singular value decom- position (SVD), non-negative matrix factorization (NMF), permutations and holographic reduced representations (HRR). The quality of semantic representation was tested by means of synonym finding task using the TOEFL test on the TASA corpus. Dimension reduction was found to improve the quality of semantic representation but it is hard to find the optimal parameter settings. Even though dimension reduction by RP was found to be more generally applicable than SVD, the semantic vectors produced by RP are somewhat unstable. The effect of encoding word order into the semantic vector representation via HRR did not lead to any increase in scores over vectors constructed from word co-occurrence in context information. In this regard, very small context windows resulted in better semantic vectors for the TOEFL test.

Cross-border insolvency

Panellist commentary on delivered conference papers on the topic of Cross-border Insolvency.

Efficient real-time face detection for high resolution surveillance applications

This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

Finding additional semantic entity information for search engines

Entity-oriented search has become an essential component of modern search engines. It focuses on retrieving a list of entities or information about the specific entities instead of documents. In this paper, we study the problem of finding entity related information, referred to as attribute-value pairs, that play a significant role in searching target entities. We propose a novel decomposition framework combining reduced relations and the discriminative model, Conditional Random Field (CRF), for automatically finding entity-related attribute-value pairs from free text documents. This decomposition framework allows us to locate potential text fragments and identify the hidden semantics, in the form of attribute-value pairs for user queries. Empirical analysis shows that the decomposition framework outperforms pattern-based approaches due to its capability of effective integration of syntactic and semantic features.

High-resolution imaging of ordered mixed-layer clays

HRTEM has been used to examine illite/smectite from the Mancos shale, rectorite from Garland County, Arkansas; illite from Silver Hill, Montana; Na-smectite from Crook County, Wyoming; corrensite from Packwood, Washington; and diagenetic chlorite from the Tuscaloosa formation. Thin specimens were prepared by ion milling, ultra-microtome sectioning and/or grain dispersal on a porous carbon substrate. Some smectite-bearing clays were also examined after intercalation with dodecylamine hydrochloride (DH). Intercalation of smectite with DH proved to be a reliable method of HRTEM imaging of expanded smectite, d(001) 16 A which could then be distinguished from unexpanded illite, d(001) 10 A. Lattice fringes of basal spacings of DH-intercalated rectorite and illite/smectite showed 26 A periodicity. These data support XRD studies which suggest that these samples are ordered, interstratified varieties of illite and smectite. The ion-thinned, unexpanded corrensite sample showed discrete crystallites containing 10 A and 14 A basal spacings corresponding with collapsed smectite and chlorite, respectively. Regions containing disordered layers of chlorite and smectite were also noted. Crystallites containing regular alternations of smectite and chlorite were not common. These HRTEM observations of corrensite did not corroborate XRD data. Particle sizes parallel to the c axis ranged widely for each sample studied, and many particles showed basal dimensions equivalent to > five layers. -J.M.H.

Structure of the immature retroviral capsid at 8 Å resolution by cryo-electron microscopy

The assembly of retroviruses such as HIV-1 is driven by oligomerization of their major structural protein, Gag. Gag is a multidomain polyprotein including three conserved folded domains: MA (matrix), CA (capsid) and NC (nucleocapsid)(1). Assembly of an infectious virion proceeds in two stages(2). In the first stage, Gag oligomerization into a hexameric protein lattice leads to the formation of an incomplete, roughly spherical protein shell that buds through the plasma membrane of the infected cell to release an enveloped immature virus particle. In the second stage, cleavage of Gag by the viral protease leads to rearrangement of the particle interior, converting the non-infectious immature virus particle into a mature infectious virion. The immature Gag shell acts as the pivotal intermediate in assembly and is a potential target for anti-retroviral drugs both in inhibiting virus assembly and in disrupting virus maturation(3). However, detailed structural information on the immature Gag shell has not previously been available. For this reason it is unclear what protein conformations and interfaces mediate the interactions between domains and therefore the assembly of retrovirus particles, and what structural transitions are associated with retrovirus maturation. Here we solve the structure of the immature retroviral Gag shell from Mason-Pfizer monkey virus by combining cryo-electron microscopy and tomography. The 8-angstrom resolution structure permits the derivation of a pseudo-atomic model of CA in the immature retrovirus, which defines the protein interfaces mediating retrovirus assembly. We show that transition of an immature retrovirus into its mature infectious form involves marked rotations and translations of CA domains, that the roles of the amino-terminal and carboxy-terminal domains of CA in assembling the immature and mature hexameric lattices are exchanged, and that the CA interactions that stabilize the immature and mature viruses are almost completely distinct.

High resolution imaging of boron carbide microstructures

Two samples of boron carbide have been examined using high resolution transmission electron microscopy (HRTEM). A hot pressed B13C2 sample shows a high density of variable width twins normal to (10-11). Subtle shifts or offsets of lattice fringes along the twin plane and normal to (10 5) were also observed. A B4C powder showed little evidence of stacking disorder in crystalline regions.

How activation, entanglement, and searching a semantic network contribute to event memory

Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.

Conflict and seduction in the public sphere

In a critical but sympathetic reading of Habermas’s work (1984, 1987a, 1987b, 2003), Luke Goode (2005) recently sought to rework his theory of deliberative democracy in an age of mediated and increasingly digital public spheres. Taking a different approach, Alan McKee (2005) challenged the culture- and class-bound strictures of Habermasian rationalism, instead pursuing a more radically pluralist account of postmodern public spheres. The editors of this special section of Media, Culture & Society invited us to discuss our differing approaches to the public sphere. Goode holds that the institutional bases of contemporary public spheres (political parties, educational institutions or public media) remain of critical importance, albeit in the context of a kaleidoscopic array of unofficial and informal micro-publics, both localized and de-territorialized. In contrast, McKee sustains a ‘hermeneutics of suspicion’ toward the official, hegemonic institutions of the public sphere since they tend to exclude and delegitimize discourses and practices that challenge their polite middle-class norms. McKee’s recent research has focused on sexual cultures, particularly among youth (McKee, 2011). Goode’s recent work has examined new social media spaces, particularly in relation to news and public debate (e.g. Goode, 2009; Goode et al., 2011). Consequently, our discussion turned to a domain which links our interests: after Goode discussed some of his recent research on (in)civility on YouTube as a new media public sphere, McKee challenged him to consider the case of pornographic websites modelled on social media sites.1 He identifies a greater degree of ‘civility’ in these pornographic sibling sites than on YouTube, requiring careful consideration of what constitutes a ‘public sphere’ in contemporary digital culture. Such sites represent an environment that shatters the opposition of public and private interest, affording public engagement on matters of the body, of intimacy, of gender politics, of pleasure and desire – said by many critics to be ruled out of court in Habermasian theory. Such environments also trouble traditional binaries between the cognitive and the affective, and between the performative and the deliberative. In what follows we explore the differences between our approaches in the form of a dialogue. As is often the case, our approaches seemed less at odds after engaging in conversation than may have initially appeared. But important differences of emphasis remain.

Semantic labelling for document feature patterns using ontological subjects

Finding and labelling semantic features patterns of documents in a large, spatial corpus is a challenging problem. Text documents have characteristics that make semantic labelling difficult; the rapidly increasing volume of online documents makes a bottleneck in finding meaningful textual patterns. Aiming to deal with these issues, we propose an unsupervised documnent labelling approach based on semantic content and feature patterns. A world ontology with extensive topic coverage is exploited to supply controlled, structured subjects for labelling. An algorithm is also introduced to reduce dimensionality based on the study of ontological structure. The proposed approach was promisingly evaluated by compared with typical machine learning methods including SVMs, Rocchio, and kNN.

High resolution transmission electron microscopy of the Murchison Carbonaceous Chondrite and the Kenna Ureilite

Fine-grained matrices in carbonaceous chondrites and small, micron-sized inclusions in achondrites can be characterized effectively using high resolution transmission electron micro­scopy (HRTEM).

Modelling word activation in semantic networks : three scaled entanglement models compared

Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. Previous research assumed a quantum-like model in which the semantic network was modelled as entangled qubits, however the level of activation was clearly being over-estimated. This paper explores three variations of this model, each of which are distinguished by a scaling factor designed to compensate the overestimation.

Escalation of conflict in large private family businesses

This study investigates escalation of intra-familial conflicts in family top management teams. Using a Critical Incident Technique approach, this study uses interviews to collect data from 23 family and non-family individuals and groups within six large-scale privately-held family businesses in Indonesia. The study develops a theoretical model to explain why family business conflicts escalate and become destructive. An inductive content analysis found that the use of a dominating strategy by both parties in dealing with conflict, the expression of negative emotions, and the involvement of non-family employees are more likely to cause escalation. This study contributes to the theory of family business conflict to help family business more satisfying and productive.