Enhanced approach for latent semantic indexing using wavelet transform

Latent semantic indexing (LSI) is a technique used for intelligent information retrieval (IR). It can be used as an alternative to traditional keyword matching IR and is attractive in this respect because of its ability to overcome problems with synonymy and polysemy. This study investigates various aspects of LSI: the effect of the Haar wavelet transform (HWT) as a preprocessing step for the singular value decomposition (SVD) in the key stage of the LSI process; and the effect of different threshold types in the HWT on the search results. The developed method allows the visualisation and processing of the term document matrix, generated in the LSI process, using HWT. The results have shown that precision can be increased by applying the HWT as a preprocessing step, with better results for hard thresholding than soft thresholding, whereas standard SVD-based LSI remains the most effective way of searching in terms of recall value.

TDM modelling and evaluation of different domain transforms for LSI

Latent semantic indexing (LSI) is a popular technique used in information retrieval (IR) applications. This paper presents a novel evaluation strategy based on the use of image processing tools. The authors evaluate the use of the discrete cosine transform (DCT) and Cohen Daubechies Feauveau 9/7 (CDF 9/7) wavelet transform as a pre-processing step for the singular value decomposition (SVD) step of the LSI system. In addition, the effect of different threshold types on the search results is examined. The results show that accuracy can be increased by applying both transforms as a pre-processing step, with better performance for the hard-threshold function. The choice of the best threshold value is a key factor in the transform process. This paper also describes the most effective structure for the database to facilitate efficient searching in the LSI system.

Hierarchical Video Summarization in Reference Subspace

In this paper, a hierarchical video structure summarization approach using Laplacian Eigenmap is proposed, where a small set of reference frames is selected from the video sequence to form a reference subspace to measure the dissimilarity between two arbitrary frames. In the proposed summarization scheme, the shot-level key frames are first detected from the continuity of inter-frame dissimilarity, and the sub-shot level and scene level representative frames are then summarized by using K-mean clustering. The experiment is carried on both test videos and movies, and the results show that in comparison with a similar approach using latent semantic analysis, the proposed approach using Laplacian Eigenmap can achieve a better recall rate in keyframe detection, and gives an efficient hierarchical summarization at sub shot, shot and scene levels subsequently.

Multimodal Biometric Human Recognition for Perceptual Human-Computer Interaction

In this paper, a novel video-based multimodal biometric verification scheme using the subspace-based low-level feature fusion of face and speech is developed for specific speaker recognition for perceptual human--computer interaction (HCI). In the proposed scheme, human face is tracked and face pose is estimated to weight the detected facelike regions in successive frames, where ill-posed faces and false-positive detections are assigned with lower credit to enhance the accuracy. In the audio modality, mel-frequency cepstral coefficients are extracted for voice-based biometric verification. In the fusion step, features from both modalities are projected into nonlinear Laplacian Eigenmap subspace for multimodal speaker recognition and combined at low level. The proposed approach is tested on the video database of ten human subjects, and the results show that the proposed scheme can attain better accuracy in comparison with the conventional multimodal fusion using latent semantic analysis as well as the single-modality verifications. The experiment on MATLAB shows the potential of the proposed scheme to attain the real-time performance for perceptual HCI applications.

Visualising Textual Knowledge about Risks to Aid Risk Communication

This paper demonstrates a potential application for latent semantic analysis and similar techniques in visualising the differences between two levels of knowledge about a risk issue. The HIV/AIDS risk issue will be examined and the semantic clusters of key words in a technical corpora derived from specific literature about HIV/AIDS will be compared with the semantic clusters of those in more general corpora. It is hoped that these comparisons will create a fast and efficient complementary approach to the articulation of mental models of risk issues that could be used to target possible inconsistencies between expert and lay mental models.

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.

The differential effects of chlorpromazine and haloperidol on latent inhibition in healthy volunteers.

Latent inhibition (LI) is a measure of reduced learning about a stimulus to which there has been prior exposure without any consequence. It therefore requires a comparison between a pre-exposed (PE) and a non-pre-exposed (NPE) condition. Since, in animals, LI is disrupted by amphetamines and enhanced by antipsychotics, LI disruption has been proposed as a measure of the characteristic attentional deficit in schizophrenia: the inability to ignore irrelevant stimuli. The findings in humans are, however, inconsistent. In particular, a recent investigation suggested that since haloperidol disrupted LI in healthy volunteers, and LI was normal in non-medicated patients with schizophrenia, the previous findings in schizophrenic patients were entirely due to the negative effects of their medication on LI (Williams et al., 1998). We conducted two studies of antipsychotic drug effects on auditory LI using a within-subject, parallel group design in healthy volunteers. In the first of these, single doses of haloperidol (1 mg. i.v.) were compared with paroxetine (20 mg p.o.) and placebo, and in the second, chlorpromazine (100 mg p.o.) was compared with lorazepam (2 mg. p.o.) and placebo. Eye movements, neuropsychological test performance (spatial working memory (SWM), Tower of London and intra/extra dimensional shift, from the CANTAB test battery) and visual analogue rating scales, were also included as other measures of attention and frontal lobe function. Haloperidol was associated with a non-significant reduction in LI scores, and dysphoria/akathisia (Barnes Akathisia Rating Scale) in three-quarters of the subjects. The LI finding may be explained by increased distractibility which was indicated by an increase in antisaccade directional errors in this group. In contrast, LI was significantly increased by chlorpromazine but not by an equally sedative dose of lorazepam (both drugs causing marked decreases in peak saccadic velocity). Paroxetine had no effect on LI, eye movements or CANTAB neuropsychological test performance. Haloperidol was associated with impaired SWM, which correlated with the degree of dysphoria/akathisia, but no other drug effects on CANTAB measures were detected. We conclude that the effect of antipsychotics on LI is both modality and pharmacologically dependent and that further research using a wider range of antipsychotic compounds is necessary to clarify the cognitive effects of these drugs, and to determine whether there are important differences between them.

Differential effects of the CCKA receptor ligands PD-140, 548 and A-71623 on latent inhibition in the rat.

Latent inhibition (LI) is a behavioural paradigm in which repeated exposure to a stimulus without consequence inhibits the formation of any new associations with that stimulus. To the extent that LI reflects a process of learning to ignore irrelevant stimuli, disrupted LI has been suggested as an animal model for the attentional deficits observed in schizophrenia. The antipsychotic potential of cholecystokinin (CCK) stems from its colocalization with dopamine (DA) in the mesolimbic pathway, where it demonstrates both excitatory and inhibitory effects on dopaminergic activity. This may be explained by mediation through different receptor subtypes. A variety of hypotheses has emerged regarding the potential clinical application of subtype-selective CCK-based drugs. The present experiments examined the effects on LI of two selective CCKA ligands: PD-140,548 (a CCKA antagonist, Experiment 1: 0.001, 0.01, and 0.1 mg/kg) and A-71623 (a CCKA agonist, Experiment 2: 0.02, 0.05, and 0.1 mg/kg). In both experiments, the effects of haloperidol (0.1 mg/kg) were also investigated. Animals receiving 0.1 mg/kg of haloperidol or 0.001 or 0.1 mg/kg (but not 0.01 mg/kg) of PD-140,548 treated the preexposed stimulus as irrelevant after a low number of preexposures. In contrast, no facilitatory effect on LI was detectable at any of the A-71623 doses. The finding that A-71623 failed to enhance LI indicates that it is unlikely that this compound would have any antipsychotic effect within the clinical setting. Considering the facilitatory effect exerted by PD-140,548 on LI, it is probable that the inhibition of CCK activity might prove a more promising strategy for the pharmacological treatment of schizophrenia.

Effects of amisulpride, risperidone and chlorpromazine on auditory and visual latent inhibition, prepulse inhibition, executive function and eye movements in healthy volunteers.

In view of the evidence that cognitive deficits in schizophrenia are critically important for long-term outcome, it is essential to establish the effects that the various antipsychotic compounds have on cognition, particularly second-generation drugs. This parallel group, placebo-controlled study aimed to compare the effects in healthy volunteers (n = 128) of acute doses of the atypical antipsychotics amisulpride (300 mg) and risperidone (3 mg) to those of chlorpromazine (100 mg) on tests thought relevant to the schizophrenic process: auditory and visual latent inhibition, prepulse inhibition of the acoustic startle response, executive function and eye movements. The drugs tested were not found to affect auditory latent inhibition, prepulse inhibition or executive functioning as measured by the Cambridge Neuropsychological Test Battery and the FAS test of verbal fluency. However, risperidone disrupted and amisulpride showed a trend to disrupt visual latent inhibition. Although amisulpride did not affect eye movements, both risperidone and chlorpromazine decreased peak saccadic velocity and increased antisaccade error rates, which, in the risperidone group, correlated with drug-induced akathisia. It was concluded that single doses of these drugs appear to have little effect on cognition, but may affect eye movement parameters in accordance with the amount of sedation and akathisia they produce. The effect risperidone had on latent inhibition is likely to relate to its serotonergic properties. Furthermore, as the trend for disrupted visual latent inhibition following amisulpride was similar in nature to that which would be expected with amphetamine, it was concluded that its behaviour in this model is consistent with its preferential presynaptic dopamine antagonistic activity in low dose and its efficacy in the negative symptoms of schizophrenia.

BSP -Style Computation: A Semantic Investigation

A BSP (Bulk Synchronous Parallelism) computation is characterized by the generation of asynchronous messages in packages during independent execution of a number of processes and their subsequent delivery at synchronization points. Bundling messages together represents a significant departure from the traditional ‘one communication at a time’ approach. In this paper the semantic consequences of communication packaging are explored. In particular, the BSP communication structure is identified with a general form of substitution—predicate substitution. Predicate substitution provides a means of reasoning about the synchronized delivery of asynchronous communications when the immediate programming context does not explicitly refer to the variables that are to be updated (unlike traditional operations, such as the assignment $x := e$, where the names of the updated variables can be extracted from the context). Proofs of implementations of Newton's root finding method and prefix sum are used to illustrate the practical application of the proposed approach.

The validity of a latent class typology of adolescent drinking patterns

Objectives: This study examined the validity of a latent class typology of adolescent drinking based on four alcohol dimensions; frequency of drinking, quantity consumed, frequency of binge drinking and the number of alcohol related problems encountered. Method: Data used were from the 1970 British Cohort Study sixteen-year-old follow-up. Partial or complete responses to the selected alcohol measures were provided by 6,516 cohort members. The data were collected via a series of postal questionnaires. Results: A five class LCA typology was constructed. Around 12% of the sample were classified as �hazardous drinkers� reporting frequent drinking, high levels of alcohol consumed, frequent binge drinking and multiple alcohol related problems. Multinomial logistic regression, with multiple imputation for missing data, was used to assess the covariates of adolescent drinking patterns. Hazardous drinking was associated with being white, being male, having heavy drinking parents (in particular fathers), smoking, illicit drug use, and minor and violent offending behaviour. Non-significant associations were found between drinking patterns and general mental health and attention deficient disorder. Conclusion: The latent class typology exhibited concurrent validity in terms of its ability to distinguish respondents across a number of alcohol and non-alcohol indicators. Notwithstanding a number of limitations, latent class analysis offers an alternative data reduction method for the construction of drinking typologies that addresses known weaknesses inherent in more tradition classification methods.