Effect of moisture and temperature distribution on dried food microstructure and porosity

Dehydration of food materials requires water removal from it. This removal of moisture prevents the growth and reproduction of microorganisms that cause decay and minimizes many of the moisture-driven deterioration reactions (Brennan, 1994). However, during food drying, many other changes occur simultaneously resulting in a modified overall quality (Kompany et al., 1993). Among the physical attributes of dried food material porosity and microstructure are the important ones that can dominant other quality of dried foods (Aguilera et al., 2000). In addition, this two concerned quality attributes affected by process conditions, material components and raw structure of food stuff. In this work, temperature moisture distribution within food materials during microwave drying will be taken into consideration to observe its participation on the microstructure and porosity of the finished product. Apple is the selective materials for this work. Generally, most of the food materials are found in non-uniformed moisture contained condition. To develop non uniform temperature distribution, food materials have been dried in a microwave oven with different power levels (Chua et al., 2000). First of all, temperature and moisture model is simulated by COMSOL Multiphysics. Later on, digital imaging camera and Image Pro Premier software have been deployed to observation moisture distribution and thermal imaging camera for temperature distribution. Finally, Microstructure and porosity of the food materials are obtained from scanning electron microscope and porosity measuring devices respectively . Moisture distribution and temperature during drying influence the microstructure and porosity significantly. Specially, High temperature and moisture contained regions show less porosity and more rupture. These findings support other literatures of Halder et al. (2011) and Rahman et al (1990). On the other hand, low temperature and moisture regions depict uniform microstructure and high porosity. This work therefore assists in better understanding of the role of moisture and temperature distribution to a prediction of micro structure and porosity of dried food materials.

“Freer than we Feel” : Applying the Critical Dimension of Consciousness to Children’s Multimodal Encoding

Reports of children and teachers taking transformative social action in schools are becoming rare. This session illustrates how teachers, while feeling the weight of accountability testing in schools, are active agents who can re-imagine literacy pedagogy to change elements of their community. It reports the critical dimensions of a movie-making unit with Year 5 students within a school reform project. The students filmed interviews with people in the local shops to gather lay-knowledge and experiences of the community. The short documentaries challenged stereotypes about what it is like to live in Logan, and critically identified potential improvements to public spaces in the local community. A student panel presented these multimodal texts at a national conference of social activists and community leaders. The report does not valorize or privilege local or lay knowledge over dominant knowledge, but argues that prescribed curriculum should not hinder the capacity for critical consciousness.

The kineikonic mode : a multimodal analysis of students’ claymation movies

Globalised communication in society today is characterised by multimodal forms of meaning making in the context of increased cultural and linguistic diversity. This research paper responds to these imperatives, applying Halliday's (1978, 1994) categories of systemic functional linguistics - representational or ideational, interactive or interpersonal, and compositional or textual meanings. Following the work of Kress (2000), van Leeuwen (Kress and van Leeuwen, 1996), and Jewitt (2006), multimodal semiotic analysis is applied to claymation movies that were collaboratively designed by Year 6 students. The significance of this analysis is the metalanguage for textual work in the kineikonic mode - moving images.

Multiliteracies and a new metalanguage for the moving image

Globalised communication in society today is characterised by multimodal forms of meaning making in a context of increased cultural and linguistic diversity, calling for the teaching of multiliteracies. This transformation requires the development of a new metalanguage or language of description for the burgeoning and hybridised variety of text forms associated with information and multimedia technologies. To continue to teach to a narrow band of print-based genres, grammars, and skills is to ignore the reality of textual practices outside of schools. This paper draws from classroom research in a multiliteracies classroom to provide a multimodal analysis of a claymation movie. The significance of the paper is the synthesis of a multimodal metalanguage for teachers and students to describe the features of work in the kineikonic (moving image) mode.

Automatic object segmentation of unstructured scenes using colour and depth maps

This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

Nonparametric semantic segmentation for 3D street scenes

In this paper we propose a method to generate a large scale and accurate dense 3D semantic map of street scenes. A dense 3D semantic model of the environment can significantly improve a number of robotic applications such as autonomous driving, navigation or localisation. Instead of using offline trained classifiers for semantic segmentation, our approach employs a data-driven, nonparametric method to parse scenes which easily scale to a large environment and generalise to different scenes. We use stereo image pairs collected from cameras mounted on a moving car to produce dense depth maps which are combined into a global 3D reconstruction using camera poses from stereo visual odometry. Simultaneously, 2D automatic semantic segmentation using a nonparametric scene parsing method is fused into the 3D model. Furthermore, the resultant 3D semantic model is improved with the consideration of moving objects in the scene. We demonstrate our method on the publicly available KITTI dataset and evaluate the performance against manually generated ground truth.

Science fiction

Few science fiction films have been made in Australia by Australians for Australian audiences, with most of the handful of locally-produced films made since the mid-1990s. Yet there has always been a solid Australian audience for non-Australian science fiction films and a strong international niche audience for the genre. While Australia has provided below-the-line crews and heads of departments (cinematographers, production designers, and so on) for many non-Australian science fiction films produced domestically, few Australian film directors have specialised in the genre. This is somewhat surprising considering that Alex Proyas achieved a degree of international success for his gothic science fiction film Dark City (1998), and George Miller achieved international fame following the worldwide success of Mad Max II (1981). Although the science fiction element of Mad Max II is tenuous – and even more so in the case of the original Mad Max (George Miller, 1979) – Miller is credited with creating a new (sub)genre which incorporates science fiction elements and has been widely imitated internationally: the dystopian, post-apocalyptic movie. Nevertheless, Australia has only produced a small number of science fiction movies. In addition to the above films, key titles include: Mad Max Beyond Thunderdome (George Miller, 1985), Shirley Thompson versus the Aliens (Jim Sharman, 1972), The Time Guardian (Brian Hannant, 1987), The Chain Reaction (Ian Barry, 1980) and, more recently, Knowing (Alex Proyas, 2009), Daybreakers (Michael and Peter Spierig, 2009), and Iron Sky (Timo Vuorensola, 2012).

Aircraft collision avoidance using spherical visual predictive control and single point features

This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

Robust scale initialization for long-range stereo visual odometry

Achieving a robust, accurately scaled pose estimate in long-range stereo presents significant challenges. For large scene depths, triangulation from a single stereo pair is inadequate and noisy. Additionally, vibration and flexible rigs in airborne applications mean accurate calibrations are often compromised. This paper presents a technique for accurately initializing a long-range stereo VO algorithm at large scene depth, with accurate scale, without explicitly computing structure from rigidly fixed camera pairs. By performing a monocular pose estimate over a window of frames from a single camera, followed by adding the secondary camera frames in a modified bundle adjustment, an accurate, metrically scaled pose estimate can be found. To achieve this the scale of the stereo pair is included in the optimization as an additional parameter. Results are presented both on simulated and field gathered data from a fixed-wing UAV flying at significant altitude, where the epipolar geometry is inaccurate due to structural deformation and triangulation from a single pair is insufficient. Comparisons are made with more conventional VO techniques where the scale is not explicitly optimized, and demonstrated over repeated trials to indicate robustness.

Review : "The Man from Hong Kong" -- Brian Trenchard Smith

Synopsis and review of the Australian action film The Man from Hong Kong (Brian Trenchard Smith, 1975). Includes cast and credits. Australia’s first martial arts action film was a coproduction between Hong Kong production company Golden Harvest and director Brian Trenchard Smith’s Movie Company, with significant investment from BEF Distributors, a subsidiary of the Australian exhibition chain Greater Union. Two years previously, Golden Harvest had coproduced the Bruce Lee smash hit Enter the Dragon, with Warner Bros. The Man from Hong Kong was its first partnership with an Australian producer, and the first coproduction between Hong Kong and Australian based companies. Although the film was almost entirely set in Sydney, much of the production was shot in a Hong Kong studio, where sets including Wilton’s gloriously decorated apartment were built...

Visual guidance for fixed-wing unmanned aerial vehicles using feature tracking : application to power line inspection

This thesis presents novel vision based control solutions that enable fixed-wing Unmanned Aerial Vehicles to perform tasks of inspection over infrastructure including power lines, pipe lines and roads. This is achieved through the development of techniques that combine visual servoing with alternate manoeuvres that assist the UAV in both following and observing the feature from a downward facing camera. Control designs are developed through techniques of Image Based Visual Servoing to utilise sideslip through Skid-to-Turn and Forward-Slip manoeuvres. This allows the UAV to simultaneously track and collect data over the length of infrastructure, including straight segments and the transition where these meet.

A combined method for mitigating sparsity problem in tag recommendation

Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.

Effect of temperature distribution on predicting quality of microwave dehydrated food

During food drying, many other changes occur simultaneously, resulting in an improved overall quality. Among the quality attributes, the structure and its corresponding color influence directly or indirectly other properties of food. In addition, these quality attributes are affected by process conditions, material components and the raw structure of the foodstuff. In this work, the temperature distribution within food materials during microwave drying has been taken into consideration to observe its role in color modification. In order to determine the temperature distribution of microwave-dried food (apple), a thermal imaging camera has been used. The image acquired from the digital camera has been analysed using image J software in order to get the color change of fresh and dried apple. The results show that temperature distribution plays an important role in determining the quality of the food. The thermal imaging camera was deployed to observe the temperature distribution within food materials during drying. It is clearly observed from the higher value of (ERGB =102) and the uneven color change that uneven temperature distribution can influence customer perceptions of the quality of dried food. Simulation of a mathematical model of temperature distribution during microwave drying can make it possible to predict the colour and texture of the microwaved food.

Person re-identification using group information

After first observing a person, the task of person re-identification involves recognising an individual at different locations across a network of cameras at a later time. Traditionally, this task has been performed by first extracting appearance features of an individual and then matching these features to the previous observation. However, identifying an individual based solely on appearance can be ambiguous, particularly when people wear similar clothing (i.e. people dressed in uniforms in sporting and school settings). This task is made more difficult when the resolution of the input image is small as is typically the case in multi-camera networks. To circumvent these issues, we need to use other contextual cues. In this paper, we use "group" information as our contextual feature to aid in the re-identification of a person, which is heavily motivated by the fact that people generally move together as a collective group. To encode group context, we learn a linear mapping function to assign each person to a "role" or position within the group structure. We then combine the appearance and group context cues using a weighted summation. We demonstrate how this improves performance of person re-identification in a sports environment over appearance based-features.

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.