Internet Technology And Web Design By Satish Jain Pdf 112 ((HOT))

Internet Technology And Web Design By Satish Jain Pdf 112

in this paper, we present and analyze the images captured by the uavs during the flight. we present the characteristics of the uavs and the images captured by these uavs. we also perform image enhancement and analyze the characteristics of these images. the purpose of this paper is to perform analysis of the images captured by uavs during the flight. this can help the uavs to design better uavs for various applications.

this paper evaluates the performance of the various algorithms used for searching on the internet, including lucene, spider, web crawler, etc. it presents a comparative study of the performance of these algorithms on a set of websites as a benchmark. we conclude by providing a review of the existing research literature in this domain, and give an outlook on future developments.

this thesis provides a detailed analysis of the three phases of product development. the first phase is a short research phase which will typically last for three to six months. this phase is also a time for product discovery. during the discovery phase, we will research the technologies, domains, and markets related to the target product. the goal is to understand who the customers are, what their problems are, and what the market opportunities are. it is this discovery phase that will also help us understand the problem to be solved. we are then ready to move to the second phase which is the product specification phase. in the third and final phase, we will create and test the software product using the existing technology.

in this paper, we describe the esnet-in2 project and a new infrastructure to support use of 100gbps networking. we discuss the use of 100gbps networking in web-based visualization of climate data and the scaling issues that arise in such environments. in the final section, we discuss the challenges faced in designing the infrastructure and configuring web-based applications to run over 100gbps networks.

Since a conventional microstrip patch antenna is inherently a narrowband radiator, stacked-patch antennas are commonly used either to enhance the bandwidth or to achieve multi-band characteristics. However, the stacked patch structure has a number of geometrical variables which need to be optimized to achieve the desired radiation characteristics. The conventional design procedure involves repeated costly and time-consuming simulations on an electromagnetic simulator to optimize the various geometrical parameters to arrive at the desired radiation characteristics. In this paper, the task of stacked patch antenna design has been approached as an optimization problem. In order to make a faster CAD module for the stacked-antenna design problem, the simulator has been replaced by a trained artificial neural network (ANN) and embedded in a particle swarm optimization algorithm (PSOA). The ANN is helpful in constructing the function mapping black-box, which can relate the frequencies and associated bandwidths of the antenna with its dimensional parameters. The role of the PSOA is to decide the geometrical parameters of the antenna, in response to the designer-specified frequencies and bandwidths. In order to validate the authenticity of the proposed method, a number of antennas have been designed, fabricated, and tested in the laboratory. Simulated and measured results have been compared which establish the accuracy of the proposed technique. Since a conventional microstrip patch antenna is inherently a narrowband radiator, stacked-patch antennas are commonly used either to enhance the bandwidth or to achieve multi-band characteristics. However, the stacked patch structure has a number of geometrical variables which need to be optimized to achieve the desired radiation characteristics. The conventional design procedure involves repeated costly and time-consuming simulations on an electromagnetic simulator to optimize the various geometrical parameters to arrive at the desired radiation characteristics. In this paper, the task of stacked patch antenna design has been approached as an optimization problem. In order to make a faster CAD module for the stacked-antenna design problem, the simulator has been replaced by a trained artificial neural network (ANN) and embedded in a particle swarm optimization algorithm (PSOA). The ANN is helpful in constructing the function mapping black-box, which can relate the frequencies and associated bandwidths of the antenna with its dimensional parameters. 5ec8ef588b