27 research outputs found

    Machine Learning And Image Processing For Noise Removal And Robust Edge Detection In The Presence Of Mixed Noise

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    The central goal of this dissertation is to design and model a smoothing filter based on the random single and mixed noise distribution that would attenuate the effect of noise while preserving edge details. Only then could robust, integrated and resilient edge detection methods be deployed to overcome the ubiquitous presence of random noise in images. Random noise effects are modeled as those that could emanate from impulse noise, Gaussian noise and speckle noise. In the first step, evaluation of methods is performed based on an exhaustive review on the different types of denoising methods which focus on impulse noise, Gaussian noise and their related denoising filters. These include spatial filters (linear, non-linear and a combination of them), transform domain filters, neural network-based filters, numerical-based filters, fuzzy based filters, morphological filters, statistical filters, and supervised learning-based filters. In the second step, switching adaptive median and fixed weighted mean filter (SAMFWMF) which is a combination of linear and non-linear filters, is introduced in order to detect and remove impulse noise. Then, a robust edge detection method is applied which relies on an integrated process including non-maximum suppression, maximum sequence, thresholding and morphological operations. The results are obtained on MRI and natural images. In the third step, a combination of transform domain-based filter which is a combination of dual tree – complex wavelet transform (DT-CWT) and total variation, is introduced in order to detect and remove Gaussian noise as well as mixed Gaussian and Speckle noise. Then, a robust edge detection is applied in order to track the true edges. The results are obtained on medical ultrasound and natural images. In the fourth step, a smoothing filter, which is a feed-forward convolutional network (CNN) is introduced to assume a deep architecture, and supported through a specific learning algorithm, l2 loss function minimization, a regularization method, and batch normalization all integrated in order to detect and remove impulse noise as well as mixed impulse and Gaussian noise. Then, a robust edge detection is applied in order to track the true edges. The results are obtained on natural images for both specific and non-specific noise-level

    Radar Technology

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    In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design

    Aeronautical engineering: A continuing bibliography with indexes (supplement 266)

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    This bibliography lists 645 reports, articles, and other documents introduced into the NASA scientific and technical information system in May 1991. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

    Neutralisation of myoelectric interference from recorded nerve signals using models of the electrode impedance

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    Any form of paralysis due to spinal cord injury or other medical condition, can have a significant impact on the quality and life expectancy of an individual. Advances in medicine and surgery have offered solutions that can improve the condition of a patient, however, most of the times an individual’s life does not dramatically improve. Implanted neuroprosthetic devices can partially restore the lost functionalities by means of functional electrical stimulation techniques. This involves applying patterns of electrical current pulses to innervate the neural pathways between the brain and the affected muscles/organs, while recording of neural information from peripheral nerves can be used as feedback to improve performance. Recording naturally occurring nerve signals via implanted electrodes attached to tripolar amplifier configurations is an approach that has been successfully used for obtaining desired information in non-acute preparations since the mid-70s. The neural signal (i.e. ENG), which can be exploited as feedback to another system (e.g. a stimulator), or simply extracted for further processing, is then intrinsically more reliable in comparison to signals obtained by artificial sensors. Sadly, neural recording of this type can be greatly compromised by myoelectric (i.e. EMG) interference, which is present at the neural interface and registered by the recording amplifier. Although current amplifier configurations reduce myoelectric interference this is suboptimal and therefore there is room for improvement. The main difficulty exists in the frequency-dependence of the electrode-tissue interface impedance which is complex. The simplistic Quasi-Tripole amplifier configuration does not allow for the complete removal of interference but it is the most power efficient because it uses only one instrumentation amplifier. Conversely, the True-Tripole and its developed automatic counterpart the Adaptive-Tripole, although minimise interference and provide means of compensating for the electrode asymmetries and changes that occur to the neural interface (e.g. due to tissue growth), they do not remove interference completely as the insignificant electrode impedance is still important. Additionally, removing interference apart from being dependent on the frequency of the interfering source, it is also subject to its proximity and orientation with respect to the recording electrodes, as this affects the field. Hence neutralisation with those two configurations, in reality, is not achieved in the entire bandwidth of the neural signal in the interfering spectrum. As both are less power efficient than the Quasi-Tripole an alternative configuration offering better performance in terms of interference neutralisation (i.e. frequency-independent, insensitive to the external interference fields) and, if possible, consume less power, is considered highly attractive. The motivation of this work is based on the following fact: as there are models that can mimic the frequency response of metal electrodes it should be possible, by constructing a network of an equivalent arrangement to the impedance of electrodes, to fit the characteristic neutralisation impedance – the impedance needed to balance a recording tripole – and ideally require no adjustment for removing interference. The validity of this postulation is proven in a series of in-vitro preparations using a modified version of the Quasi-Tripole made out of discrete circuit components where an impedance is placed at either side of the outer electrodes for balancing the recording arrangement. Various models were used in place of that impedance. In particular, representing the neutralisation impedance as a parallel RC reduced interference by a factor of 10 at all frequencies in the bandwidth of the neural signal while removed it completely at a spot frequency. Conversely, modelling the effect of the constant phase angle impedance of highly polarisable electrodes using a 20 stages non-uniform RC ladder network resulted in the minimisation of interference without the initial requirement of continuous adjustment. It is demonstrated that with a model that does not perfectly fit the impedance profile of a monopolar electrochemical cell an average reduction in interference of about 100 times is achieved, with the cell arranged as a Wheatstone bridge that can be balanced in the ENG band

    Aeronautical engineering: A continuing bibliography with indexes (supplement 276)

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    This bibliography lists 705 reports, articles, and other documents introduced into the NASA scientific and technical information system in Feb. 1992. Subject coverage includes: design, construction, and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

    Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

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    Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018

    Abstracts on Radio Direction Finding (1899 - 1995)

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    The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

    Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

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    In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

    Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

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    In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

    Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

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    This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808
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