Representation of facial expression categories in continuous arousal-valence space: Feature and correlation

Representation of facial expressions using continuous dimensions has shown to be inherently more expressive and psychologically meaningful than using categorized emotions, and thus has gained increasing attention over recent years. Many sub-problems have arisen in this new field that remain only partially understood. A comparison of the regression performance of different texture and geometric features and investigation of the correlations between continuous dimensional axes and basic categorized emotions are two of these. This paper presents empirical studies addressing these problems, and it reports results from an evaluation of different methods for detecting spontaneous facial expressions within the arousal-valence dimensional space (AV). The evaluation compares the performance of texture features (SIFT, Gabor, LBP) against geometric features (FAP-based distances), and the fusion of the two. It also compares the prediction of arousal and valence, obtained using the best fusion method, to the corresponding ground truths. Spatial distribution, shift, similarity, and correlation are considered for the six basic categorized emotions (i.e. anger, disgust, fear, happiness, sadness, surprise). Using the NVIE database, results show that the fusion of LBP and FAP features performs the best. The results from the NVIE and FEEDTUM databases reveal novel findings about the correlations of arousal and valence dimensions to each of six basic emotion categories.

The effect of using different regions of interest on local and mean skin temperature

The dynamic nature of tissue temperature and the subcutaneous properties, such as blood flow, fatness, and metabolic rate, leads to variation in local skin temperature. Therefore, we investigated the effects of using multiple regions of interest when calculating weighted mean skin temperature from four local sites. Twenty-six healthy males completed a single trial in a thermonetural laboratory (mean ± SD): 24.0 (1.2) °C; 56 (8%) relative humidity; < 0.1 m/s air speed). Mean skin temperature was calculated from four local sites (neck, scapula, hand and shin) in accordance with International Standards using digital infrared thermography. A 50 x 50 mm square, defined by strips of aluminium tape, created six unique regions of interest, top left quadrant, top right quadrant, bottom left quadrant, bottom right quadrant, centre quadrant and the entire region of interest, at each of the local sites. The largest potential error in weighted mean skin temperature was calculated using a combination of a) the coolest and b) the warmest regions of interest at each of the local sites. Significant differences between the six regions interest were observed at the neck (P < 0.01), scapula (P < 0.001) and shin (P < 0.05); but not at the hand (P = 0.482). The largest difference (± SEM) at each site was as follows: neck 0.2 (0.1) °C; scapula 0.2 (0.0) °C; shin 0.1 (0.0) °C and hand 0.1 (0.1) °C. The largest potential error (mean ± SD) in weighted mean skin temperature was 0.4 (0.1) °C (P < 0.001) and the associated 95% limits of agreement for these differences was 0.2 to 0.5 °C. Although we observed differences in local and mean skin temperature based on the region of interest employed, these differences were minimal and are not considered physiologically meaningful.

Mirror neurons, the representation of word meaning, and the foot of the third left frontal convolution

Previous neuroimaging research has attempted to demonstrate a preferential involvement of the human mirror neuron system (MNS) in the comprehension of effector-related action word (verb) meanings. These studies have assumed that Broca's area (or Brodmann's area 44) is the homologue of a monkey premotor area (F5) containing mouth and hand mirror neurons, and that action word meanings are shared with the mirror system due to a proposed link between speech and gestural communication. In an fMRI experiment, we investigated whether Broca's area shows mirror activity solely for effectors implicated in the MNS. Next, we examined the responses of empirically determined mirror areas during a language perception task comprising effector-specific action words, unrelated words and nonwords. We found overlapping activity for observation and execution of actions with all effectors studied, i.e., including the foot, despite there being no evidence of foot mirror neurons in the monkey or human brain. These "mirror" areas showed equivalent responses for action words, unrelated words and nonwords, with all of these stimuli showing increased responses relative to visual character strings. Our results support alternative explanations attributing mirror activity in Broca's area to covert verbalisation or hierarchical linearisation, and provide no evidence that the MNS makes a preferential contribution to comprehending action word meanings.

Impact of automatic region-of-interest coding on perceived quality in mobile video

At present, the most reliable method to obtain end-user perceived quality is through subjective tests. In this paper, the impact of automatic region-of-interest (ROI) coding on perceived quality of mobile video is investigated. The evidence, which is based on perceptual comparison analysis, shows that the coding strategy improves perceptual quality. This is particularly true in low bit rate situations. The ROI detection method used in this paper is based on two approaches: - (1) automatic ROI by analyzing the visual contents automatically, and; - (2) eye-tracking based ROI by aggregating eye-tracking data across many users, used to both evaluate the accuracy of automatic ROI detection and the subjective quality of automatic ROI encoded video. The perceptual comparison analysis is based on subjective assessments with 54 participants, across different content types, screen resolutions, and target bit rates while comparing the two ROI detection methods. The results from the user study demonstrate that ROI-based video encoding has higher perceived quality compared to normal video encoded at a similar bit rate, particularly in the lower bit rate range.

Leveraging Lean Production Philosophy for Rationalising a Non-Linear Representation of Construction Specifications

This paper presents an approach, based on Lean production philosophy, for rationalising the processes involved in the production of specification documents for construction projects. Current construction literature erroneously depicts the process for the creation of construction specifications as a linear one. This traditional understanding of the specification process often culminates in process-wastes. On the contrary, the evidence suggests that though generalised, the activities involved in producing specification documents are nonlinear. Drawing on the outcome of participant observation, this paper presents an optimised approach for representing construction specifications. Consequently, the actors typically involved in producing specification documents are identified, the processes suitable for automation are highlighted and the central role of tacit knowledge is integrated into a conceptual template of construction specifications. By applying the transformation, flow, value (TFV) theory of Lean production the paper argues that value creation can be realised by eliminating the wastes associated with the traditional preparation of specification documents with a view to integrating specifications in digital models such as Building Information Models (BIM). Therefore, the paper presents an approach for rationalising the TFV theory as a method for optimising current approaches for generating construction specifications based on a revised specification writing model.

Evaluating viewpoint entropy for ribbon representation of protein structure

While many measures of viewpoint goodness have been proposed in computer graphics, none have been evaluated for ribbon representations of protein secondary structure. To fill this gap, we conducted a user study on Amazon’s Mechanical Turk platform, collecting human viewpoint preferences from 65 participants for 4 representative su- perfamilies of protein domains. In particular, we evaluated viewpoint entropy, which was previously shown to be a good predictor for human viewpoint preference of other, mostly non-abstract objects. In a second study, we asked 7 molecular biology experts to find the best viewpoint of the same protein domains and compared their choices with viewpoint entropy. Our results show that viewpoint entropy overall is a significant predictor of human viewpoint preference for ribbon representations of protein secondary structure. However, the accuracy is highly dependent on the complexity of the structure: while most participants agree on good viewpoints for small, non-globular structures with few secondary structure elements, viewpoint preference varies considerably for complex structures. Finally, experts tend to choose viewpoints of both low and high viewpoint entropy to emphasize different aspects of the respective structure.

Integrating eco-efficiency assessment of commercial buildings into the design process : LCADesign

The ability to assess a commercial building for its impact on the environment at the earliest stage of design is a goal which is achievable by integrating several approaches into a single procedure directly from the 3D CAD representation. Such an approach enables building design professionals to make informed decisions on the environmental impact of building and its alternatives during the design development stage instead of at the post-design stage where options become limited. The indicators of interest are those which relate to consumption of resources and energy, contributions to pollution of air, water and soil, and impacts on the health and wellbeing of people in the built environment as a result of constructing and operating buildings. 3D object-oriented CAD files contain a wealth of building information which can be interrogated for details required for analysis of the performance of a design. The quantities of all components in the building can be automatically obtained from the 3D CAD objects and their constituent materials identified to calculate a complete list of the amounts of all building products such as concrete, steel, timber, plastic etc. When this information is combined with a life cycle inventory database, key internationally recognised environmental indicators can be estimated. Such a fully integrated tool known as LCADesign has been created for automated ecoefficiency assessment of commercial buildings direct from 3D CAD. This paper outlines the key features of LCADesign and its application to environmental assessment of commercial buildings.

Translation and news making : a study of contemporary arabic television

Arabic satellite television has recently attracted tremendous attention in both the academic and professional worlds, with a special interest in Aljazeera as a curious phenomenon in the Arab region. Having made a household name for itself worldwide with the airing of the Bin Laden tapes, Aljazeera has set out to deliberately change the culture of Arabic journalism, as it has been repeatedly stated by its current General Manager Waddah Khanfar, and to shake up the Arab society by raising awareness to issues never discussed on television before and challenging long-established social and cultural values and norms while promoting, as it claims, Arab issues from a presumably Arab perspective. Working within the meta-frame of democracy, this Qatari-based network station has been received with mixed reactions ranging from complete support to utter rejection in both the west and the Arab world. This research examines the social semiotics of Arabic television and the socio-cultural impact of translation-mediated news in Arabic satellite television, with the aim to carry out a qualitative content analysis, informed by framing theory, critical linguistic analysis, social semiotics and translation theory, within a re-mediation framework which rests on the assumption that a medium “appropriates the techniques, forms and social significance of other media and attempts to rival or refashion them in the name of the real" (Bolter and Grusin, 2000: 66). This is a multilayered research into how translation operates at two different yet interwoven levels: translation proper, that is the rendition of discourse from one language into another at the text level, and translation as a broader process of interpretation of social behaviour that is driven by linguistic and cultural forms of another medium resulting in new social signs generated from source meaning reproduced as target meaning that is bound to be different in many respects. The research primarily focuses on the news media, news making and reporting at Arabic satellite television and looks at translation as a reframing process of news stories in terms of content and cultural values. This notion is based on the premise that by its very nature, news reporting is a framing process, which involves a reconstruction of reality into actualities in presenting the news and providing the context for it. In other words, the mediation of perceived reality through a media form, such as television, actually modifies the mind’s ordering and internal representation of the reality that is presented. The research examines the process of reframing through translation news already framed or actualized in another language and argues that in submitting framed news reports to the translation process several alterations take place, driven by the linguistic and cultural constraints and shaped by the context in which the content is presented. These alterations, which involve recontextualizations, may be intentional or unintentional, motivated or unmotivated. Generally, they are the product of lack of awareness of the dynamics and intricacies of turning a message from one language form into another. More specifically, they are the result of a synthesis process that consciously or subconsciously conforms to editorial policy and cultural interpretive frameworks. In either case, the original message is reproduced and the news is reframed. For the case study, this research examines news broadcasts by the now world-renowned Arabic satellite television station Aljazeera, and to a lesser extent the Lebanese Broadcasting Corporation (LBC) and Al- Arabiya where access is feasible, for comparison and crosschecking purposes. As a new phenomenon in the Arab world, Arabic satellite television, especially 24-hour news and current affairs, provides an interesting area worthy of study, not only for its immediate socio-cultural and professional and ethical implications for the Arabic media in particular, but also for news and current affairs production in the western media that rely on foreign language sources and translation mediation for international stories.

An empirical investigation of the level effect in Australian interest rates

An extensive literature examines the dynamics of interest rates, with particular attention given to the positive relationship between interest-rate volatility and the level of interest rates—the so-called level effect. This paper examines the interaction between the estimated level effect and competing parameterisations of interest-rate volatility for the Australian yield curve. We adopt a new methodology that estimates elasticity in a multivariate setting that explicitly accommodates the correlations that exist between various yield factors. Results show that significant correlations exist between the residuals of yield factors and that such correlations do indeed impact on model estimates. Within the multivariate setting, the level of the short rate is shown to be a crucial determinant of the conditional volatility of all three yield factors. Measures of model fit suggest that, in addition to the usual level effect, the incorporation of GARCH effects and possible regime shifts is important

Representation and learning of visual information for pose recognition

Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

Merging fact with fiction : a study of year 9 students' developing scientific literacy through the writing of hybridised scientific narratives on a socioscientific issue

International assessments of student science achievement, and growing evidence of students' waning interest in school science, have ensured that the development of scientific literacy continues to remain an important educational priority. Furthermore, researchers have called for teaching and learning strategies to engage students in the learning of science, particularly in the middle years of schooling. This study extends previous national and international research that has established a link between writing and learning science. Specifically, it investigates the learning experiences of eight intact Year 9 science classes as they engage in the writing of short stories that merge scientific and narrative genres (i.e., hybridised scientific narratives) about the socioscientific issue of biosecurity. This study employed a triangulation mixed methods research design, generating both quantitative and qualitative data, in order to investigate three research questions that examined the extent to which the students' participation in the study enhanced their scientific literacy; the extent to which the students demonstrated conceptual understanding of related scientific concepts through their written artefacts and in interviews about the artefacts; and the extent to which the students' participation in the project influenced their attitudes toward science and science learning. Three aspects of scientific literacy were investigated in this study: conceptual science understandings (a derived sense of scientific literacy), the students' transformation of scientific information in written stories about biosecurity (simple and expanded fundamental senses of scientific literacy), and attitudes toward science and science learning. The stories written by students in a selected case study class (N=26) were analysed quantitatively using a series of specifically-designed matrices that produce numerical scores that reflect students' developing fundamental and derived senses of scientific literacy. All students (N=152) also completed a Likert-style instrument (i.e., BioQuiz), pretest and posttest, that examined their interest in learning science, science self-efficacy, their perceived personal and general value of science, their familiarity with biosecurity issues, and their attitudes toward biosecurity. Socioscientific issues (SSI) education served as a theoretical framework for this study. It sought to investigate an alternative discourse with which students can engage in the context of SSI education, and the role of positive attitudes in engaging students in the negotiation of socioscientific issues. Results of the study have revealed that writing BioStories enhanced selected aspects of the participants' attitudes toward science and science learning, and their awareness and conceptual understanding of issues relating to biosecurity. Furthermore, the students' written artefacts alone did not provide an accurate representation of the level of their conceptual science understandings. An examination of these artefacts in combination with interviews about the students' written work provided a more comprehensive assessment of their developing scientific literacy. These findings support extensive calls for the utilisation of diversified writing-to-learn strategies in the science classroom, and therefore make a significant contribution to the writing-to-learn science literature, particularly in relation to the use of hybridised scientific genres. At the same time, this study presents the argument that the writing of hybridised scientific narratives such as BioStories can be used to complement the types of written discourse with which students engage in the negotiation of socioscientific issues, namely, argumentation, as the development of positive attitudes toward science and science learning can encourage students' participation in the discourse of science. The implications of this study for curricular design and implementation, and for further research, are also discussed.

Stability analysis based on birfurcation theory of the DSTATCOM operating in current control mode

This paper presents the stability analysis for a distribution static compensator (DSTATCOM) that operates in current control mode based on bifurcation theory. Bifurcations delimit the operating zones of nonlinear circuits and, hence, the capability to compute these bifurcations is of important interest for practical design. A control design for the DSTATCOM is proposed. Along with this control, a suitable mathematical representation of the DSTATCOM is proposed to carry out the bifurcation analysis efficiently. The stability regions in the Thevenin equivalent plane are computed for different power factors at the point of common coupling. In addition, the stability regions in the control gain space, as well as the contour lines for different Floquet multipliers are computed. It is demonstrated through bifurcation analysis that the loss of stability in the DSTATCOM is due to the emergence of a Neimark bifurcation. The observations are verified through simulation studies.

Application of K-tree to document clustering

Digital collections are growing exponentially in size as the information age takes a firm grip on all aspects of society. As a result Information Retrieval (IR) has become an increasingly important area of research. It promises to provide new and more effective ways for users to find information relevant to their search intentions. Document clustering is one of the many tools in the IR toolbox and is far from being perfected. It groups documents that share common features. This grouping allows a user to quickly identify relevant information. If these groups are misleading then valuable information can accidentally be ignored. There- fore, the study and analysis of the quality of document clustering is important. With more and more digital information available, the performance of these algorithms is also of interest. An algorithm with a time complexity of O(n2) can quickly become impractical when clustering a corpus containing millions of documents. Therefore, the investigation of algorithms and data structures to perform clustering in an efficient manner is vital to its success as an IR tool. Document classification is another tool frequently used in the IR field. It predicts categories of new documents based on an existing database of (doc- ument, category) pairs. Support Vector Machines (SVM) have been found to be effective when classifying text documents. As the algorithms for classifica- tion are both efficient and of high quality, the largest gains can be made from improvements to representation. Document representations are vital for both clustering and classification. Representations exploit the content and structure of documents. Dimensionality reduction can improve the effectiveness of existing representations in terms of quality and run-time performance. Research into these areas is another way to improve the efficiency and quality of clustering and classification results. Evaluating document clustering is a difficult task. Intrinsic measures of quality such as distortion only indicate how well an algorithm minimised a sim- ilarity function in a particular vector space. Intrinsic comparisons are inherently limited by the given representation and are not comparable between different representations. Extrinsic measures of quality compare a clustering solution to a “ground truth” solution. This allows comparison between different approaches. As the “ground truth” is created by humans it can suffer from the fact that not every human interprets a topic in the same manner. Whether a document belongs to a particular topic or not can be subjective.