Fault Tolerant Error Coding and Detection using Reversible Gates

In recent years, reversible logic has emerged as one of the most important approaches for power optimization with its application in low power CMOS, quantum computing and nanotechnology. Low power circuits implemented using reversible logic that provides single error correction – double error detection (SEC-DED) is proposed in this paper. The design is done using a new 4 x 4 reversible gate called ‘HCG’ for implementing hamming error coding and detection circuits. A parity preserving HCG (PPHCG) that preserves the input parity at the output bits is used for achieving fault tolerance for the hamming error coding and detection circuits.

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

Design Considerations of Sonar Projector Arrays with Improved Performance

Systems which employ underwater acoustic energy for observation or communication are called sonar systems. The active and passive sonars are the two types of systems used for the detection and localisation of targets in underwater. Active sonar involves the transmission of an acoustic signal which, when reflected from a target, provides the sonar receiver with a basis for the detection and estimation. Passive sonar bases its detection and estimation on sounds which emanate from the target itself--Machinery noise, flow noise, transmission from its own active sonar etc.Electroacoustic transducers are used in sonar systems for the transmission and detection of acoustic energy. The transducer which is used for the transmission of acoustic energy is called projector and the one used for reception is called hydrophone. Since a single transducer is not sufficient enough for long range and directional transmission, a properly distributed array of transducers are to be used [9-11].The need and requirement for spatial processing to generate the most favourable directivity patterns for transducer systems used in underwater applications have already been analysed by several investigators [12-21].The desired directivity pattern can be either generated by the use of suitable focussing techniques or by an array of non-directional sensor elements, whose arrangements, spacing and the mode of excitation provide the required radiation pattern or by the combination of these.While computing that the directivity pattern, it is assumed strength of the elements are unaffected by the the source acoustic pressure at each source. However, in closely packed a r r a y s , the acoustic interaction effects experienced among the elements will modify the behaviour of individual elements and in turn will reduce the acoust ic source leve 1 wi t h respect to the maximum t heoret i cal va 1ue a s well as degrade the beam pa t tern. Th i s ef fect shou 1d be reduced in systems that are intended to generate high acoustic power output and unperturbed beam patterns [2,22-31].The work herein presented includes an approach for designing efficient and well behaved underwater transd~cer arrays, taking into account the acoustic interaction effect experienced among the closely packed multielement arrays.Architectural modifications reducing the interaction effect different radiating apertures.

State-of-the-Art: Transformation Invariant Descriptors

As the popularity of digital videos increases, a large number illegal videos are being generated and getting published. Video copies are generated by performing various sorts of transformations on the original video data. For effectively identifying such illegal videos, the image features that are invariant to various transformations must be extracted for performing similarity matching. An image feature can be its local feature or global feature. Among them, local features are powerful and have been applied in a wide variety of computer vision aplications .This paper focuses on various recently proposed local detectors and descriptors that are invariant to a number of image transformations.