CPW-Fed Quad-Band Antenna for Compact Wireless Application

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

Design of a Compact Genetic Microstrip Antenna with improved performance

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.

Cumulative Approach to Customer Satisfaction with Respect to Compact Segment Car Users

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.

Design and Development of Compact Chipless RFID Tags with High Data Encoding Capacity

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.

Investigations on Metamaterial Based Spiral Inductors for Compact Microwave Devices

Division of Electronics Engineering

Error estimates for approximate approximations on compact intervals

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.

"Strictly models and objects first" - Unterrichtskonzept und -methodik für objektorientierte Modellierung im Informatikunterricht

Objektorientierte Modellierung (OOM) im Unterricht ist immer noch ein breit diskutiertes Thema - in der Didaktik akzeptiert und gewünscht, von der Praxis oft als unnötiger Overhead oder als schlicht zu komplex empfunden. Ich werde in dieser Arbeit zeigen, wie ein Unterrichtskonzept aufgebaut sein kann, das die lerntheoretischen Vorteile der OOM nutzt und dabei die berichteten Schwierigkeiten größtenteils vermeidet. Ausgehend von den in der Literatur dokumentierten Konzepten zur OOM und ihren Kritikpunkten habe ich ein Unterrichtskonzept entwickelt, das aus Erkenntnissen der Lernpsychologie, allgemeiner Didaktik, Fachdidaktik und auch der Softwaretechnik Unterrichtsmethoden herleitet, um den berichteten Schwierigkeiten wie z.B. dem "Lernen auf Vorrat" zu begegnen. Mein Konzept folgt vier Leitideen: models first, strictly objects first, Nachvollziehbarkeit und Ausführbarkeit. Die strikte Umsetzung dieser Ideen führte zu einem Unterrichtskonzept, das einerseits von Beginn an das Ziel der Modellierung berücksichtigt und oft von der dynamischen Sicht des Problems ausgeht. Da es weitgehend auf der grafischen Modellierungsebene verbleibt, werden viele Probleme eines Programmierkurses vermieden und dennoch entstehen als Ergebnis der Modellierung ausführbare Programme.

Spatio-temporal resolution studies on a highly compact ultrafast electron diffractometer

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.

Generating Compliant Motion of Objects with an Articulated Hand

The flexibility of the robot is the key to its success as a viable aid to production. Flexibility of a robot can be explained in two directions. The first is to increase the physical generality of the robot such that it can be easily reconfigured to handle a wide variety of tasks. The second direction is to increase the ability of the robot to interact with its environment such that tasks can still be successfully completed in the presence of uncertainties. The use of articulated hands are capable of adapting to a wide variety of grasp shapes, hence reducing the need for special tooling. The availability of low mass, high bandwidth points close to the manipulated object also offers significant improvements I the control of fine motions. This thesis provides a framework for using articulated hands to perform local manipulation of objects. N particular, it addresses the issues in effecting compliant motions of objects in Cartesian space. The Stanford/JPL hand is used as an example to illustrate a number of concepts. The examples provide a unified methodology for controlling articulated hands grasping with point contacts. We also present a high-level hand programming system based on the methodologies developed in this thesis. Compliant motion of grasped objects and dexterous manipulations can be easily described in the LISP-based hand programming language.

Computer Analysis of Visual Properties of Curved Objects

A method is presented for the visual analysis of objects by computer. It is particularly well suited for opaque objects with smoothly curved surfaces. The method extracts information about the object's surface properties, including measures of its specularity, texture, and regularity. It also aids in determining the object's shape. The application of this method to a simple recognition task ??e recognition of fruit ?? discussed. The results on a more complex smoothly curved object, a human face, are also considered.

How are Three-Deminsional Objects Represented in the Brain?

We discuss a variety of object recognition experiments in which human subjects were presented with realistically rendered images of computer-generated three-dimensional objects, with tight control over stimulus shape, surface properties, illumination, and viewpoint, as well as subjects' prior exposure to the stimulus objects. In all experiments recognition performance was: (1) consistently viewpoint dependent; (2) only partially aided by binocular stereo and other depth information, (3) specific to viewpoints that were familiar; (4) systematically disrupted by rotation in depth more than by deforming the two-dimensional images of the stimuli. These results are consistent with recently advanced computational theories of recognition based on view interpolation.

Sparse Representations of Multiple Signals

We discuss the problem of finding sparse representations of a class of signals. We formalize the problem and prove it is NP-complete both in the case of a single signal and that of multiple ones. Next we develop a simple approximation method to the problem and we show experimental results using artificially generated signals. Furthermore,we use our approximation method to find sparse representations of classes of real signals, specifically of images of pedestrians. We discuss the relation between our formulation of the sparsity problem and the problem of finding representations of objects that are compact and appropriate for detection and classification.

Component based recognition of objects in an office environment

We present a component-based approach for recognizing objects under large pose changes. From a set of training images of a given object we extract a large number of components which are clustered based on the similarity of their image features and their locations within the object image. The cluster centers build an initial set of component templates from which we select a subset for the final recognizer. In experiments we evaluate different sizes and types of components and three standard techniques for component selection. The component classifiers are finally compared to global classifiers on a database of four objects.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system