10 resultados para requirement-based testing

em Cochin University of Science


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A novel optical add-drop multiplexer (OADM) based on the Mach-Zelauler interferometer (MZI) and the fiber Bragg grating (FBG) is proposed for the first tittle to the authors ' knowledge. In the structure, the Mach-Zehnder interferometer acts as an optical switch. The principle of the OADM is analyzed in this paper. The OADM can add/drop one of the multi-input channels or pass the channel directly by adjusting the difference of the two arms of the interferometer. The channel isolation is more than 20 dB

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Transparent conducting oxides (TCO’s) have been known and used for technologically important applications for more than 50 years. The oxide materials such as In2O3, SnO2 and impurity doped SnO2: Sb, SnO2: F and In2O3: Sn (indium tin oxide) were primarily used as TCO’s. Indium based oxides had been widely used as TCO’s for the past few decades. But the current increase in the cost of indium and scarcity of this material created the difficulty in obtaining low cost TCO’s. Hence the search for alternative TCO material has been a topic of active research for the last few decades. This resulted in the development of various binary and ternary compounds. But the advantages of using binary oxides are the easiness to control the composition and deposition parameters. ZnO has been identified as the one of the promising candidate for transparent electronic applications owing to its exciting optoelectronic properties. Some optoelectronics applications of ZnO overlap with that of GaN, another wide band gap semiconductor which is widely used for the production of green, blue-violet and white light emitting devices. However ZnO has some advantages over GaN among which are the availability of fairly high quality ZnO bulk single crystals and large excitonic binding energy. ZnO also has much simpler crystal-growth technology, resulting in a potentially lower cost for ZnO based devices. Most of the TCO’s are n-type semiconductors and are utilized as transparent electrodes in variety of commercial applications such as photovoltaics, electrochromic windows, flat panel displays. TCO’s provide a great potential for realizing diverse range of active functions, novel functions can be integrated into the materials according to the requirement. However the application of TCO’s has been restricted to transparent electrodes, ii notwithstanding the fact that TCO’s are n-type semiconductors. The basic reason is the lack of p-type TCO, many of the active functions in semiconductor originate from the nature of pn-junction. In 1997, H. Kawazoe et al reported the CuAlO2 as the first p-type TCO along with the chemical design concept for the exploration of other p-type TCO’s. This has led to the fabrication of all transparent diode and transistors. Fabrication of nanostructures of TCO has been a focus of an ever-increasing number of researchers world wide, mainly due to their unique optical and electronic properties which makes them ideal for a wide spectrum of applications ranging from flexible displays, quantum well lasers to in vivo biological imaging and therapeutic agents. ZnO is a highly multifunctional material system with highly promising application potential for UV light emitting diodes, diode lasers, sensors, etc. ZnO nanocrystals and nanorods doped with transition metal impurities have also attracted great interest, recently, for their spin-electronic applications This thesis summarizes the results on the growth and characterization of ZnO based diodes and nanostructures by pulsed laser ablation. Various ZnO based heterojunction diodes have been fabricated using pulsed laser deposition (PLD) and their electrical characteristics were interpreted using existing models. Pulsed laser ablation has been employed to fabricate ZnO quantum dots, ZnO nanorods and ZnMgO/ZnO multiple quantum well structures with the aim of studying the luminescent properties.

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The thesis introduced the octree and addressed the complete nature of problems encountered, while building and imaging system based on octrees. An efficient Bottom-up recursive algorithm and its iterative counterpart for the raster to octree conversion of CAT scan slices, to improve the speed of generating the octree from the slices, the possibility of utilizing the inherent parallesism in the conversion programme is explored in this thesis. The octree node, which stores the volume information in cube often stores the average density information could lead to “patchy”distribution of density during the image reconstruction. In an attempt to alleviate this problem and explored the possibility of using VQ to represent the imformation contained within a cube. Considering the ease of accommodating the process of compressing the information during the generation of octrees from CAT scan slices, proposed use of wavelet transforms to generate the compressed information in a cube. The modified algorithm for generating octrees from the slices is shown to accommodate the eavelet compression easily. Rendering the stored information in the form of octree is a complex task, necessarily because of the requirement to display the volumetric information. The reys traced from each cube in the octree, sum up the density en-route, accounting for the opacities and transparencies produced due to variations in density.

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Present work deals with the studies on energy requirement and convervation in selected fish harvesting systems.Modem fishing is one of the most energy intensive methods of food production. Fossil fuels used for motorised and mechanised fishing are nonrenewable and limited. Most of the environmental problems that confront mankind today are connected to the use of energy in one way or another. Code of Conduct for Responsible Fisheries (FAO, 1995) highlights the need for efficient use of energy in the fisheries sector. Information on energy requirement in different fish harvesting systems, based on the principles of energy analysis, is entirely lacking in respect of Indian fisheries. Such an analysis will provide an unbiased decision making support for maximising the yield per unit of non-renewable energy use, from different fishery resource systems, by rational deployment of harvesting systems. In the present study, results of investigations conducted during 1997-2000 on energy requirement in selected fish harvesting systems and approaches to energy conservation in fishing, are presented along with a detailed description of the fish harvesting systems and their operation. The content of the thesis is organised into 8 Chapters.

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The motivatitni for" the present work is from .a project sanctioned by TSRO. The work involved the development of a quick and reliable test procedure using microwaves, for tflue inspection of cured propellant samples and a method to monitor the curing conditions of propellant mix undergoing the curing process.Normal testing CHE the propellant samples involvecuttimg a piece from each carton and testing it for their tensile strength. The values are then compared with standard ones and based on this result the sample isaccepted or rejected. The tensile strength is a measure ofdegree of cure of the propellant mix. But this measurementis a destructive procedure as it involves cutting of the sample. Moreover, it does not guarantee against nonuniform curing due to power failure, hot air-line failure,operator error etc. This necessitated the need for the development of a quick and reliable non-destructive test procedure.

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This thesis summarizes the results on the studies on a syntax based approach for translation between Malayalam, one of Dravidian languages and English and also on the development of the major modules in building a prototype machine translation system from Malayalam to English. The development of the system is a pioneering effort in Malayalam language unattempted by previous researchers. The computational models chosen for the system is first of its kind for Malayalam language. An in depth study has been carried out in the design of the computational models and data structures needed for different modules: morphological analyzer , a parser, a syntactic structure transfer module and target language sentence generator required for the prototype system. The generation of list of part of speech tags, chunk tags and the hierarchical dependencies among the chunks required for the translation process also has been done. In the development process, the major goals are: (a) accuracy of translation (b) speed and (c) space. Accuracy-wise, smart tools for handling transfer grammar and translation standards including equivalent words, expressions, phrases and styles in the target language are to be developed. The grammar should be optimized with a view to obtaining a single correct parse and hence a single translated output. Speed-wise, innovative use of corpus analysis, efficient parsing algorithm, design of efficient Data Structure and run-time frequency-based rearrangement of the grammar which substantially reduces the parsing and generation time are required. The space requirement also has to be minimised

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Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations

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Speech is a natural mode of communication for people and speech recognition is an intensive area of research due to its versatile applications. This paper presents a comparative study of various feature extraction methods based on wavelets for recognizing isolated spoken words. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. This work includes two speech recognition methods. First one is a hybrid approach with Discrete Wavelet Transforms and Artificial Neural Networks and the second method uses a combination of Wavelet Packet Decomposition and Artificial Neural Networks. Features are extracted by using Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Training, testing and pattern recognition are performed using Artificial Neural Networks (ANN). The proposed method is implemented for 50 speakers uttering 20 isolated words each. The experimental results obtained show the efficiency of these techniques in recognizing speech

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The Towed Array electronics is a multi-channel simultaneous real time high speed data acquisition system. Since its assembly is highly manpower intensive, the costs of arrays are prohibitive and therefore any attempt to reduce the manufacturing, assembly, testing and maintenance costs is a welcome proposition. The Network Based Towed Array is an innovative concept and its implementation has remarkably simplified the fabrication, assembly and testing and revolutionised the Towed Array scenario. The focus of this paper is to give a good insight into the Reliability aspects of Network Based Towed Array. A case study of the comparison between the conventional array and the network based towed array is also dealt with

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Cancer treatment is most effective when it is detected early and the progress in treatment will be closely related to the ability to reduce the proportion of misses in the cancer detection task. The effectiveness of algorithms for detecting cancers can be greatly increased if these algorithms work synergistically with those for characterizing normal mammograms. This research work combines computerized image analysis techniques and neural networks to separate out some fraction of the normal mammograms with extremely high reliability, based on normal tissue identification and removal. The presence of clustered microcalcifications is one of the most important and sometimes the only sign of cancer on a mammogram. 60% to 70% of non-palpable breast carcinoma demonstrates microcalcifications on mammograms [44], [45], [46].WT based techniques are applied on the remaining mammograms, those are obviously abnormal, to detect possible microcalcifications. The goal of this work is to improve the detection performance and throughput of screening-mammography, thus providing a ‘second opinion ‘ to the radiologists. The state-of- the- art DWT computation algorithms are not suitable for practical applications with memory and delay constraints, as it is not a block transfonn. Hence in this work, the development of a Block DWT (BDWT) computational structure having low processing memory requirement has also been taken up.