952 resultados para Compact cars
Resumo:
A compact coplanar waveguide (CPW) fed uniplanar antenna for Quad-band applications is presented. The Quad-band operation is realized by imposing various current paths in a modified T-shaped radiating element. The antenna covers GSM 900, DCS 1800, IEEE802.11.a, IEEE802.11.b and HiperLAN-2 bands and exhibits good radiation characteristics. This low profile antenna has a dimension of 32mm×31mmwhen printed on a substrate of dielectric constant 4.4 and height 1.6mm. Details of design with experimental and simulated results are presented
Resumo:
A method for simultaneously enhancing the bandwidth and reducing the size of microstrip antennas (MSAs) using a modified ground plane (GP) has been proposed with design formulas. A combshaped truncated GP is used for this purpose. This method provides an overall compactness up to 85% for proximity-coupled MSAs in the frequency range of 900 MHz–5.5 GHz with an improvement inbandwidth up to seven times when compared with the conventional ones
Resumo:
This paper presents the design and development of a compact CPW fed quad band antenna. This low profile antenna has a dimension of 32mmx31mm when printed on a substrate of dielectric constant 4.4 and height 1.6mm. The antenna covers GSM 900, DCS 1800, IEEE802.11.a, IEEE802.11.b and HiperLAN2 bands. The antenna exhibits good radiation characteristics with moderate gain
Resumo:
In this paper the design issues of compact genetic microstrip antennas for mobile applications has been investigated. The antennas designed using Genetic Algorithms (GA) have an arbitrary shape and occupies less area (compact) compared to the traditionally designed antenna for the same frequency but with poor performance. An attempt has been made to improve the performance of the genetic microstrip antenna by optimizing the ground plane (GP) to have a fish bone like structure. The genetic antenna with the GP optimized is even better compared to the traditional and the genetic antenna.
Resumo:
Automobile Industry in India is influenced by the presence of national and multi-national manufacturers. The presence of many manufacturers and brands in the state provides many choices to the customer. The current market for car manufacturers has been transformed from a monopoly of one or two manufacturers in the seventies to oligopoly of many manufacturers in the current marketing scenario. The main objective of the research paper is to explore and conceptualize various parameters and develop a model, which influence the purchase patterns of passenger cars in the State of Kerala. Thus, the main purpose of this paper is to come up with a model, which shall facilitate further study on the consumer purchase behaviour patterns of passenger car owners in the State of Kerala, India. The author intends to undertake further quantitative analysis to verify and validate the model so developed. The main methods used for this paper are secondary research on available material, depth interview of car dealers, car financing agencies and car owners in the city of Cochin, in Kerala State in India. The depth interviews were conducted with the use of prepared questionnaire for car dealers, car customers and car financing agencies. The findings resulted in the identification of the parameters that influence the consumer purchase behaviour of passenger cars and the formulation of the model, which will be the basis for the further research of the author. The paper will be of tremendous value to the existing and new car manufacturers both indigenous and foreign, to formalize and strategies their policies towards an effective marketing strategy, so as to market their models in the State, which is known for its high literacy, consumerism and higher educational penetration
Resumo:
Globalization and liberalization, with the entry of many prominent foreign manufacturers, changed the automobile scenario in India, since early 1990’s. World Leaders in automobile manufacturing such as Ford, General Motors, Honda, Toyota, Suzuki, Hyundai, Renault, Mitsubishi, Benz, BMW, Volkswagen and Nissan set up their manufacturing units in India in joint venture with their Indian counterpart companies, by making use of the Foreign Direct Investment policy of the Government of India, These manufacturers started capturing the hearts of Indian car customers with their choice of technological and innovative product features, with quality and reliability. With the multiplicity of choices available to the Indian passenger car buyers, it drastically changed the way the car purchase scenario in India and particularly in the State of Kerala. This transformed the automobile scene from a sellers’ market to buyers’ market. Car customers started developing their own personal preferences and purchasing patterns, which were hitherto unknown in the Indian automobile segment. The main purpose of this paper is to develop a model with major variables, which influence the consumer purchase behaviour of passenger car owners in the State of Kerala. Though there are innumerable studies conducted in other countries, there are very few thesis and research work conducted to study the consumer behaviour of the passenger car industry in India and specifically in the State of Kerala. The results of the research contribute to the practical knowledge base of the automobile industry, specifically to the passenger car segment. It has also a great contributory value addition to the manufacturers and dealers for customizing their marketing plans in the State
Resumo:
Globalization and liberalization, with the entry of many prominent foreign manufacturers, changed the automobile scenario in India, since early 1990’s. World Leaders in automobile manufacturing such as Ford, General Motors, Honda, Toyota, Suzuki, Hyundai, Renault, Mitsubishi, Benz, BMW, Volkswagen and Nissan set up their manufacturing units in India in joint venture with their Indian counterpart companies, by making use of the Foreign Direct Investment policy of the Government of India, These manufacturers started capturing the hearts of Indian car customers with their choice of technological and innovative product features, with quality and reliability. With the multiplicity of choices available to the Indian passenger car buyers, it drastically changed the way the car purchase scenario in India and particularly in the State of Kerala. This transformed the automobile scene from a sellers’ market to buyers’ market. Car customers started developing their own personal preferences and purchasing patterns, which were hitherto unknown in the Indian automobile segment. The main purpose of this paper is to come up with the identification of possible parameters and a framework development, that influence the consumer purchase behaviour patterns of passenger car owners in the State of Kerala, so that further research could be done, based on the framework and the identified parameters.
Resumo:
Earlier studies on measurement of customer satisfaction are based on either transaction specific or overall approaches. The transaction specific approach evaluates customer satisfaction with single components in the whole purchase process but the overall satisfaction was based on all the encounters or experiences to the customer throughout the purchase process. Consumers will comment on particular events of their purchase process when asked about transaction-specific satisfaction and they will comment their overall impression and general experiences in overall satisfaction (Bitner & Hubbert 1994) Through a critical review on the literature, it has been identified a new approaches to customer satisfaction, say, cumulative approaches that can be more useful than overall and transaction specific approaches for strategic decision making (Fornell et al 1996). The cumulative approach to customer satisfaction doesn’t study earlier due to the difficulty in operationalization of the concept. But the influencers of customer satisfaction are context specific and the prevailing models doesn’t give the sources of variations in the satisfaction, the importance of cumulative approaches to customer satisfaction has emerges that lights to a new research. The current study has focused to explore the influencers of overall customer satisfaction to form individual elements that can be used to identify the cumulative customer satisfaction.
Resumo:
The main objective of this thesis is to develop a compact chipless RFID tag with high data encoding capacity. The design and development of chipless RFID tag based on multiresonator and multiscatterer methods are presented first. An RFID tag using using SIR capable of 79bits is proposed. The thesis also deals with some of the properties of SIR like harmonic separation, independent control on resonant modes and the capability to change the electrical length. A chipless RFID reader working in a frequency band of 2.36GHz to 2.54GHz has been designed to show the feasibility of the RFID system. For a practical system, a new approach based on UWB Impulse Radar (UWB IR) technology is employed and the decoding methods from noisy backscattered signal are successfully demonstrated. The thesis also proposes a simple calibration procedure, which is able to decode the backscattered signal up to a distance of 80cm with 1mW output power.
Resumo:
Division of Electronics Engineering
Resumo:
The aim of this paper is the investigation of the error which results from the method of approximate approximations applied to functions defined on compact in- tervals, only. This method, which is based on an approximate partition of unity, was introduced by V. Mazya in 1991 and has mainly been used for functions defied on the whole space up to now. For the treatment of differential equations and boundary integral equations, however, an efficient approximation procedure on compact intervals is needed. In the present paper we apply the method of approximate approximations to functions which are defined on compact intervals. In contrast to the whole space case here a truncation error has to be controlled in addition. For the resulting total error pointwise estimates and L1-estimates are given, where all the constants are determined explicitly.
Resumo:
Time-resolved diffraction with femtosecond electron pulses has become a promising technique to directly provide insights into photo induced primary dynamics at the atomic level in molecules and solids. Ultrashort pulse duration as well as extensive spatial coherence are desired, however, space charge effects complicate the bunching of multiple electrons in a single pulse.Weexperimentally investigate the interplay between spatial and temporal aspects of resolution limits in ultrafast electron diffraction (UED) on our highly compact transmission electron diffractometer. To that end, the initial source size and charge density of electron bunches are systematically manipulated and the resulting bunch properties at the sample position are fully characterized in terms of lateral coherence, temporal width and diffracted intensity.Weobtain a so far not reported measured overall temporal resolution of 130 fs (full width at half maximum) corresponding to 60 fs (root mean square) and transversal coherence lengths up to 20 nm. Instrumental impacts on the effective signal yield in diffraction and electron pulse brightness are discussed as well. The performance of our compactUEDsetup at selected electron pulse conditions is finally demonstrated in a time-resolved study of lattice heating in multilayer graphene after optical excitation.
Resumo:
We develop efficient techniques for the non-rigid registration of medical images by using representations that adapt to the anatomy found in such images. Images of anatomical structures typically have uniform intensity interiors and smooth boundaries. We create methods to represent such regions compactly using tetrahedra. Unlike voxel-based representations, tetrahedra can accurately describe the expected smooth surfaces of medical objects. Furthermore, the interior of such objects can be represented using a small number of tetrahedra. Rather than describing a medical object using tens of thousands of voxels, our representations generally contain only a few thousand elements. Tetrahedra facilitate the creation of efficient non-rigid registration algorithms based on finite element methods (FEM). We create a fast, FEM-based method to non-rigidly register segmented anatomical structures from two subjects. Using our compact tetrahedral representations, this method generally requires less than one minute of processing time on a desktop PC. We also create a novel method for the non-rigid registration of gray scale images. To facilitate a fast method, we create a tetrahedral representation of a displacement field that automatically adapts to both the anatomy in an image and to the displacement field. The resulting algorithm has a computational cost that is dominated by the number of nodes in the mesh (about 10,000), rather than the number of voxels in an image (nearly 10,000,000). For many non-rigid registration problems, we can find a transformation from one image to another in five minutes. This speed is important as it allows use of the algorithm during surgery. We apply our algorithms to find correlations between the shape of anatomical structures and the presence of schizophrenia. We show that a study based on our representations outperforms studies based on other representations. We also use the results of our non-rigid registration algorithm as the basis of a segmentation algorithm. That algorithm also outperforms other methods in our tests, producing smoother segmentations and more accurately reproducing manual segmentations.
Resumo:
This paper describes a general, trainable architecture for object detection that has previously been applied to face and peoplesdetection with a new application to car detection in static images. Our technique is a learning based approach that uses a set of labeled training data from which an implicit model of an object class -- here, cars -- is learned. Instead of pixel representations that may be noisy and therefore not provide a compact representation for learning, our training images are transformed from pixel space to that of Haar wavelets that respond to local, oriented, multiscale intensity differences. These feature vectors are then used to train a support vector machine classifier. The detection of cars in images is an important step in applications such as traffic monitoring, driver assistance systems, and surveillance, among others. We show several examples of car detection on out-of-sample images and show an ROC curve that highlights the performance of our system.