Finding the beat : an analysis of the rhythmic elements of motion pictures

This paper presents a new study on the application of the framework of Computational Media Aesthetics to the problem of automated understanding of film. Leveraging Film Grammar as the means to closing the "semantic gap" in media analysis, we examine film rhythm, a powerful narrative concept used to endow structure and form to the film compositionally and enhance its lyrical quality experientially. The novelty of this paper lies in the specification and investigation of the rhythmic elements that are present in two cinematic devices; namely motion and editing patterns, and their potential usefulness to automated content annotation and management systems. In our rhythm model, motion behavior is classified as being either nonexistent, fluid or staccato for a given shot. Shot neighborhoods in movies are then grouped by proportional makeup of these motion behavioral classes to yield seven high-level rhythmic arrangements that prove to be adept at indicating likely scene content (e.g. dialogue or chase sequence) in our experiments. The second part of our investigation presents a computational model to detect editing patterns as either metric, accelerated, decelerated or free. Details of the algorithm for the extraction of these classes are presented, along with experimental results on real movie data. We show with an investigation of combined rhythmic patterns that, while detailed content identification via rhythm types alone is not possible by virtue of the fact that film is not codified to this level in terms of rhythmic elements, analysis of the combined motion/editing rhythms can allow us to determine that the content has changed and hypothesize as to why this is so. We present three such categories of change and demonstrate their efficacy for capturing useful film elements (e.g. scene change precipitated by plot event), by providing data support from five motion pictures.

Application of computational media aesthetics methodology to extracting color semantics in film

Using film grammar as the underpinning, we study the extraction of structures in video based on color using a wide configuration of clustering methods combined with existing and new similarity measures. We study the visualisation of these structures, which we call Scene-Cluster Temporal Charts and show how it can bring out the interweaving of different themes and settings in a film. We also extract color events that filmmakers use to draw/force a viewer's attention to a shot/scene. This is done by first extracting a set of colors used rarely in film, and then building a probabilistic model for color event detection. We demonstrate with experimental results from ten movies that our algorithms are effective in the extraction of both scene-cluster temporal charts and color events.

Finding the beat : an analysis of the rhythmic elements of motion pictures

This paper forms a continuation of our work focused on exploiting film grammar for the task of automated film understanding. We examine film rhythm, a powerful narrative concept used to endow structure and form to the film compositionally and to enhance its lyrical quality experientially. Of the many, often complex, cinematic devices contributing to film rhythm, this paper investigates the rhythmic elements that are present in edited sequences of shots, and presents a novel computational model to detect shot structural rhythm as either metric, accelerated, decelerated, or free. Details of the algorithm for the extraction of these editing rhythm classes are presented, along with experimental results on real movie data. Following this we study the usefulness of combining the rhythmic patterns induced through both motion and editing in film. We show that, whilst detailed content identification via rhythm types alone is not possible by virtue of the fact that film is not codified to this level in terms of rhythmic elements, analysis of the combined motion/shot rhythm can allow us to determine that the content has changed and hypothesize as to why this is so. We present 3 such categories of change and demonstrate their efficacy for capturing useful film elements (e.g., scene change precipitated by plot event), by providing data support from 5 motion pictures.

Occupant satisfaction of Star Rated Houses in Victoria, Australia

The Victorian government implemented legislation for all new houses to achieve a 6 star rating since May 2011. It is found that having a higher star rating would provide financial and environmental benefits, however the question remains- is this sufficient to satisfy the occupants living in such houses? Are the occupants actually satisfied with the amount of money they have invested in their home? This study investigates the level of satisfaction of occupants living in different star rated houses, and explores if there is a link between the star rating of the house and the satisfaction of the occupants living in such houses.

Human identification from ECG signals via sparse representation of local segments

This work proposes a novel framework to extract compact and discriminative features from Electrocardiogram (ECG) signals for human identification based on sparse representation of local segments. Specifically, local segments extracted from an ECG signal are projected to a small number of basic elements in a dictionary, which is learned from training data. A final representation is extracted by performing a max pooling procedure over all the sparse coefficient vectors in the ECG signal. Unlike most of existing methods for human identification from ECG signals which require segmentation of individual heartbeats or extraction of fiducial points, the proposed method does not need to segment individual heartbeats or detect any fiducial points. The method achieves an 99.48% accuracy on a 100 subjects dataset constructed from a publicly available database, which demonstrates that both local and global structural information are well captured to characterize the ECG signals.

Racism as a determinant of health: a protocol for conducting a systematic review and meta-analysis

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Blind extraction using fractional lower-order statistics

In traditional method to blindly extract interesting source signals sequentially, the second-order or higher-order statistics of signals are often utilized. However, for impulsive sources, both of the second-order and higher-order statistics may degenerate. Therefore, it is necessary to exploit new method for the blind extraction of impulsive sources. Based on the best compression-reconstruction principle, a novel model is proposed in this work, together with the corresponding algorithm. The proposed method can be used for blind extraction of sources which are distributed from alpha stable process. Simulations are given to illustrate availability and robustness of our algorithm.

Form versus function : a study into interactive learning process affecting the implementation of sustainability in commercial buildings

Owners and tenants of sustainable buildings are now realising the sustainable building that they own or occupy and also how they use the building have a significant impact on their work practices. These stakeholders are demanding sustainability outcomes such as improved occupant health and performance, lower energy and material consumption use as well as encouraging healthy ecosystem in their sustainable building. Clearly the level of user knowledge about a sustainable building and its technologies makes a difference about the actual behaviour towards sustainable buildings (Knott 2007, Stenberg 2007) There remains two major challenge faced by sustainable building occupants: (i) addressing the gap between an occupant's expectations of sustainable building outcomes and what the building actually provides and (ii) overcoming the lack of user knowledge about sustainability design and operation for a particular with regards to performance (Jailani et. al, 2011). This is an innovative study designed to address these challenges. It uses a focus group approach to investigate the gap between (a) user expectations and (b) sustainable building performance, with reference to the relationship between interactive learning process and the level of implementation of sustainability in commercial buildings. The outcome from the study will provide a post-occupancy evaluation of the perception of occupants in sustainable buildings. Most importantly, this information can then assist architects and designers in private and government organisations to successfully develop future sustainable design and policy which can fully capitalise on the original intention when delivering sustainable buildings, as well as providing an innovative feedback mechanism between occupiers and architects.

Removing the ambiguity of data processing methods: Optimizing the location of peak boundaries for accurate moment calculations

The calculation of the first few moments of elution peaks is necessary to determine: the amount of component in the sample (peak area or zeroth moment), the retention factor (first moment), and the column efficiency (second moment). It is a time consuming and tedious task for the analyst to perform these calculations, thus data analysis is generally completed by data stations associated to modern chromatographs. However, data acquisition software is a black box which provides no information to chromatographers on how their data are treated. These results are too important to be accepted on blind faith. The location of the peak integration boundaries is most important. In this manuscript, we explore the relationships between the size of the integration area, the relative position of the peak maximum within this area, and the accuracy of the calculated moments. We found that relationships between these parameters do exist and that computers can be programmed with relatively simple routines to automatize the extraction of key peak parameters and to select acceptable integration boundaries. It was also found that the most accurate results are obtained when the S/N exceeds 200.

Integrated DNA extraction and amplification using electrokinetic pumping in a microfluidic device

An integrated system employing anion exchange for the extraction of DNA from biological samples prior to polymerase chain reaction DNA amplification has been developed, based on microfluidic methodology utilising electrokinetic pumping. In this system, the biological samples were added directly to chitosan-coated silica beads to facilitate DNA immobilisation. The purified, pre-concentrated DNA was then eluted using a combination of electro-osmotic flow enhanced with electrophoretic mobility, which enable DNA to be transported by both mechanisms into the DNA amplification chamber. Through optimisation of the DNA elution conditions, average DNA extraction efficiencies of 69.1% were achievable. Subsequent DNA amplification performed on the microfluidic system demonstrated not only the ability to use electrokinetic movement to integrate the two processes on a single device, but also that the quality and quantity of DNA eluted was suitable for downstream analysis. This work offers an attractive real-world to chip interface and a route to simpler Lab-on-a-Chip technology which eliminates the need for moving parts.

Properties of bamboo fibres produced using an environmentally benign method

The properties of bamboo fibres extracted from raw bamboo plants in an environmentally benign manner were investigated. To reduce environmental impacts of the manufacturing process, microwave, ultra-sonication and enzyme were used to extract the bamboo fibres, avoiding the use of hazardous chemicals. The new method enabled the extraction of single fibres while retaining a certain quantity of lignin in fibre. The retained lignin allowed the fibre to possess UV absorption and antibacterial properties, which will be advantageous for many textile applications.

Segmentation of gray scale image based on intuitionistic fuzzy sets constructed from several membership functions

Segmentation is the process of extraction of objects from an image. This paper proposes a new algorithm to construct intuitionistic fuzzy set (IFS) from multiple fuzzy sets as an application to image segmentation. Hesitation degree in IFS is formulated as the degree of ignorance (due to the lack of knowledge) to determine whether the chosen membership function is best for image segmentation. By minimizing entropy of IFS generated from various fuzzy sets, an image is thresholded. Experimental results are provided to show the effectiveness of the proposed method.