Robust bimodal person identification using face and speech with limited training data and corruption of both modalities

This paper presents a novel method of audio-visual fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there is a limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new representation and a modified cosine similarity are introduced for combining and comparing bimodal features with limited training data as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal data set created from the SPIDRE and AR databases with variable noise corruption of speech and occlusion in the face images. The new method has demonstrated improved recognition accuracy.

Virtual Thrower Versus Real Goalkeeper: The Influence of Different Visual Conditions on Performance

In order to use virtual reality as a sport analysis tool, we need to be sure that an immersed athlete reacts realistically in a virtual environment. This has been validated for a real handball goalkeeper facing a virtual thrower. However, we currently ignore which visual variables induce a realistic motor behavior of the immersed handball goalkeeper. In this study, we used virtual reality to dissociate the visual information related to the movements of the player from the visual information related to the trajectory of the ball. Thus, the aim is to evaluate the relative influence of these different visual information sources on the goalkeeper's motor behavior. We tested 10 handball goalkeepers who had to predict the final position of the virtual ball in the goal when facing the following: only the throwing action of the attacking player (TA condition), only the resulting ball trajectory (BA condition), and both the throwing action of the attacking player and the resulting ball trajectory (TB condition). Here we show that performance was better in the BA and TB conditions, but contrary to expectations, performance was substantially worse in the TA condition. A significant effect of ball landing zone does, however, suggest that the relative importance between visual information from the player and the ball depends on the targeted zone in the goal. In some cases, body-based cues embedded in the throwing actions may have a minor influence on the ball trajectory and vice versa. Kinematics analysis was then combined with these results to determine why such differences occur depending on the ball landing zone and consequently how it can clarify the role of different sources of visual information on the motor behavior of an athlete immersed in a virtual environment.

Laughter and Humour as Conversational Mind-Reading Displays

Laughter and humor are pervasive phenomena in conversa- tional interactions. This paper argues that they function as displays of mind-reading abilities in social interactions–as suggested by the Analogi- cal Peacock Hypothesis (APH). In this view, they are both social bonding signals and can elevate one’s social status. The relational combination of concepts in humor is addressed. However, it is in the inclusion of context and receiver knowledge, required by the APH view, that it contributes the most to existing theories. Taboo and offensive humor are addressed in terms of costly signaling, and implications for human computer inter- action and some possible routes to solutions are suggested.

Building autonomous sensitive artificial listeners (Extended abstract)

This paper describes a substantial effort to build a real-time interactive multimodal dialogue system with a focus on emotional and non-verbal interaction capabilities. The work is motivated by the aim to provide technology with competences in perceiving and producing the emotional and non-verbal behaviours required to sustain a conversational dialogue. We present the Sensitive Artificial Listener (SAL) scenario as a setting which seems particularly suited for the study of emotional and non-verbal behaviour, since it requires only very limited verbal understanding on the part of the machine. This scenario allows us to concentrate on non-verbal capabilities without having to address at the same time the challenges of spoken language understanding, task modeling etc. We first summarise three prototype versions of the SAL scenario, in which the behaviour of the Sensitive Artificial Listener characters was determined by a human operator. These prototypes served the purpose of verifying the effectiveness of the SAL scenario and allowed us to collect data required for building system components for analysing and synthesising the respective behaviours. We then describe the fully autonomous integrated real-time system we created, which combines incremental analysis of user behaviour, dialogue management, and synthesis of speaker and listener behaviour of a SAL character displayed as a virtual agent. We discuss principles that should underlie the evaluation of SAL-type systems. Since the system is designed for modularity and reuse, and since it is publicly available, the SAL system has potential as a joint research tool in the affective computing research community.

Turing's menagerie:Talking lions, virtual bats, electric sheep and analogical peacocks: Common ground and common interest are necessary components of engagement

This theoretical paper attempts to define some of the key components and challenges required to create embodied conversational agents that can be genuinely interesting conversational partners. Wittgenstein's argument concerning talking lions emphasizes the importance of having a shared common ground as a basis for conversational interactions. Virtual bats suggests that-for some people at least-it is important that there be a feeling of authenticity concerning a subjectively experiencing entity that can convey what it is like to be that entity. Electric sheep reminds us of the importance of empathy in human conversational interaction and that we should provide a full communicative repertoire of both verbal and non-verbal components if we are to create genuinely engaging interactions. Also we may be making the task more difficult rather than easy if we leave out non-verbal aspects of communication. Finally, analogical peacocks highlights the importance of between minds alignment and establishes a longer term goal of being interesting, creative, and humorous if an embodied conversational agent is to be truly an engaging conversational partner. Some potential directions and solutions to addressing these issues are suggested.

Adaptive automated construction of hybrid heuristics for exam timetabling and graph colouring problems

In this paper, we present a random iterative graph based hyper-heuristic to produce a collection of heuristic sequences to construct solutions of different quality. These heuristic sequences can be seen as dynamic hybridisations of different graph colouring heuristics that construct solutions step by step. Based on these sequences, we statistically analyse the way in which graph colouring heuristics are automatically hybridised. This, to our knowledge, represents a new direction in hyper-heuristic research. It is observed that spending the search effort on hybridising Largest Weighted Degree with Saturation Degree at the early stage of solution construction tends to generate high quality solutions. Based on these observations, an iterative hybrid approach is developed to adaptively hybridise these two graph colouring heuristics at different stages of solution construction. The overall aim here is to automate the heuristic design process, which draws upon an emerging research theme on developing computer methods to design and adapt heuristics automatically. Experimental results on benchmark exam timetabling and graph colouring problems demonstrate the effectiveness and generality of this adaptive hybrid approach compared with previous methods on automatically generating and adapting heuristics. Indeed, we also show that the approach is competitive with the state of the art human produced methods.

Common-sense knowledge for a computer vision system for human action recognition

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed in a realistic environment in which humans behave rationally, that is, motivated by an aim or a reason. © 2012 Springer-Verlag.

Cryopreservation of human semen and prepared sperm: effects on motility parameters and DNA integrity

Objective: To investigate effects of cryopreservation on sperm motility and DNA integrity. Design: Pre-cryopreservation and post-cryopreservation analysis of motility and DNA integrity of semen and prepared sperm samples. Setting: A hospital andrology laboratory. Patient(s): Forty men attending the Regional Fertility Centre, Belfast, Northern Ireland. Intervention(s): Each sample was divided, and an aliquot was frozen unprepared. Remaining aliquots were prepared by Percoll density centrifugation (95.0:47.5) or direct swim-up procedure and divided into aliquots to allow direct comparison of fresh and frozen semen and prepared sperm (frozen with or without the addition of seminal plasma) from the same ejaculate. Samples were frozen by static-phase vapor cooling and being plunged into liquid nitrogen. Thawing was carried out at room temperature. Main Outcome Measure(s): Sperm DNA integrity was determined using a modified alkaline single cell gel electrophoresis (comet) assay, and motility was determined using computer-assisted semen analysis. Result(s): Sperm frozen unprepared in seminal fluid appeared more resistant to freezing damage than frozen prepared sperm. Further improvements can be achieved by selecting out the subpopulation of sperm with best motility and DNA integrity and freezing these sperm in seminal plasma, making this the optimal procedure. Conclusion(s): Freezing sperm in seminal plasma improves postthaw motility and DNA integrity.

A Hybrid Forward Algorithm for RBF Neural Network Construction

This paper proposes a novel hybrid forward algorithm (HFA) for the construction of radial basis function (RBF) neural networks with tunable nodes. The main objective is to efficiently and effectively produce a parsimonious RBF neural network that generalizes well. In this study, it is achieved through simultaneous network structure determination and parameter optimization on the continuous parameter space. This is a mixed integer hard problem and the proposed HFA tackles this problem using an integrated analytic framework, leading to significantly improved network performance and reduced memory usage for the network construction. The computational complexity analysis confirms the efficiency of the proposed algorithm, and the simulation results demonstrate its effectiveness

The Effects of Delta–9–Tetrahydrocannabinol, the primary psychoactive cannabinoid in marijuana, on human sperm function in vitro.

Objective: to investigate the effects of tetrahydrocannabinol; THC on human sperm function in vitro. Design: laboratory analysis of sperm motility with and without exposure to THC using computer assisted semen analysis (CASA) and acrosome reaction by fluoroscein isothiocyanate labelled peanut agglutinin (FITC-PNA) staining. Setting: An ART unit in a tertiary medical centre. Patients: semen was obtained from 78 men attending the Regional Fertility Centre, Belfast. Interventions: Sperm were divided into 90% (the best fertilizing potential used in assisted conception) and 45% (the poorer subpopulation) fractions by density centrifugation and incubated with, or without (controls), tetrahydrocannabinol (THC) at concentrations equivalent to therapeutic (0.032�?�¯?�?�­M) and recreational (4.8 and 0.32�?�¯?�?�­M) plasma levels, at 37�?�¯?�?�°C for 3 hours. Main outcome measures: Sperm motility, spontaneous and induced acrosome reactions Results: There was a dose-dependent decrease in percentage progressive motility (-21% at 4.8�??�?�µM, p0.05) in the 90% fraction. The 45% fraction showed a greater decrease in percentage progressive motility (-56% at 4.8�??�?�µM, p=0.011; -23% at 0.32�??�?�µM, p= 0.039; and -28% at 0.032�??�?�µM, p=0.004). A decrease in the straight line velocity; VSL (-10%) and the average path velocity; VAP (-10%) were also observed in the 90% fraction. A significant inhibition (-15% at 4.8�??�?�µM, p=0.04) in spontaneous acrosome reaction was observed in the 90% fraction. The 45% fraction showed a more marked inhibition [-35% (p

Simultaneous feature selection and feature weighting using Hybrid Tabu Search/K-nearest neighbor classifier

Feature selection and feature weighting are useful techniques for improving the classification accuracy of K-nearest-neighbor (K-NN) rule. The term feature selection refers to algorithms that select the best subset of the input feature set. In feature weighting, each feature is multiplied by a weight value proportional to the ability of the feature to distinguish pattern classes. In this paper, a novel hybrid approach is proposed for simultaneous feature selection and feature weighting of K-NN rule based on Tabu Search (TS) heuristic. The proposed TS heuristic in combination with K-NN classifier is compared with several classifiers on various available data sets. The results have indicated a significant improvement in the performance in classification accuracy. The proposed TS heuristic is also compared with various feature selection algorithms. Experiments performed revealed that the proposed hybrid TS heuristic is superior to both simple TS and sequential search algorithms. We also present results for the classification of prostate cancer using multispectral images, an important problem in biomedicine.

Human information retrieval

Information retrieval in the age of Internet search engines has become part of ordinary discourse and everyday practice: "Google" is a verb in common usage. Thus far, more attention has been given to practical understanding of information retrieval than to a full theoretical account. In Human Information Retrieval, Julian Warner offers a comprehensive overview of information retrieval, synthesizing theories from different disciplines (information and computer science, librarianship and indexing, and information society discourse) and incorporating such disparate systems as WorldCat and Google into a single, robust theoretical framework. There is a need for such a theoretical treatment, he argues, one that reveals the structure and underlying patterns of this complex field while remaining congruent with everyday practice. Warner presents a labor theoretic approach to information retrieval, building on his previously formulated distinction between semantic and syntactic mental labor, arguing that the description and search labor of information retrieval can be understood as both semantic and syntactic in character. Warner's information science approach is rooted in the humanities and the social sciences but informed by an understanding of information technology and information theory. The chapters offer a progressive exposition of the topic, with illustrative examples to explain the concepts presented. Neither narrowly practical nor largely speculative, Human Information Retrieval meets the contemporary need for a broader treatment of information and information systems.