Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Abstract-The tongue can substitute human sensory systems and has been used as a medium of input to help impaired patients communicate with the world. Innovative techniques have been employed to realize tongue movement, sense its position and exploit tongue dexterity, in order to achieve Tongue Supported Human Computer Interaction (TSHCI). This paper examines various approaches of using tongue dexterousness in TSHCI systems and then introduces two infrared signal supported minimally-invasive TSHCI systems developed at Curtin University. Methods of sensing tongue movement and position are especially discussed and depending on the employed methods, TSHCI systems are categorized as either invasive or minimally-invasive. A set of system usability criteria is proposed to help build more effective TSHCI systems in future.

Wear debris analysis is becoming an efficient method for machinery condition monitoring due to the recent development in image analysis techniques. It gives us information about not only the wear mode but also the wear mechanism of a machine component. Five types of debris are produced during the operation of a machine: Sphere, Platelet, Long-thin, Cutting and Chunky. A variety of parameters, related to the identification process of wear debris, can affect the performance of image analysis. This paper presents five numerical features to describe the boundary morphology of a debris. An ratio based methodology using Genetic Algorithms is used for classification. The experimental results indicate that due to the simplicity of proposed features, the classification of debris can be done quite rapidly and accurately.

Due to the strong correlation between symmetric frames, video signals have a high degree of temporal redundancy. Motion estimation techniques are computationally expensive and time-consuming processes used in symmetric video compression to reduce temporal redundancy. The block-matching technique is, on the other hand, the most popular and efficient of the different motion estimation and compensation techniques. Motion compensation based on the block-matching technique generally uses the minimization of either the mean square error (MSE) or mean absolute difference (MAD) in order to find the appropriate motion vector. This paper proposes to remove the highly temporally redundant information contained in each block of the video signal using the removing temporal redundancy (RTR) technique in order to improve the data rate and efficiency of the video signal. A comparison between the PSNR values of this technique and those of the JPEG video compression standard is made. As a result of its moderate memory and computation requirements, the algorithm was found to be suitable for mobile networks and embedded devices. Based on a detailed set of testing scenarios and the obtained results, it is evident that the RTR compression technique allowed a compression ratio of 22.71 and 95% loss in bit rate reduction while maintaining sufficient intact signal quality with minimized information loss.

This work explores use of Thermal Infrared Image based Flow Visualization (TIIFV) for qualitative analysis of gasoline engine combustion performance. It proposes determining engine combustion performance through analysis of the exhaust plume turbulence and radiation extinction patterns. The employed methodology requires estimating the point spread function (PSF) prevailing in a LWIR image and using the PSF estimates for enhancing the engine exhaust plume LWIR images. Influence of exhaust plume composition on the plume flow characteristics, made evident by the turbulence and radiation extinction patterns, is then ascertained. The observed plume flow characteristics and underlying flow patterns are used to qualitatively determine the engine combustion performance. Results suggest that engine exhaust flow visualization can help in qualitative analysis of combustion performance from a distance and our reliance on photochemical-based analysis of gasoline engine combustion efficiency can be reduced. Thus a time consuming and untidy process, difficult to be carried out in real life situations, may be replaced with a swift and cleaner one.