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This document describes study of an active star forming region in our galaxy (the Milky Way) known as W22. Physical conditions in these regions can help us in understanding star formation processes in the universe and hence the structure and evolution of the universe. Zeeman effect measurements in 18 cm OH absorption line were carried out in order to estimate the line of sight magnetic field strength in the molecular cloud associated with this star forming region. Other physical parameters such as hydrogen column density, optical depth, critical magnetic field were also determined from these measurements. The region was mapped at 18 cm and the distribution of molecular gas within this star forming complex was described.

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Both feature and class modeling are used in Software Product Line (SPL) engineering to model variability. Feature models are used primarily to represent user-visible characteristics (i.e., features) of products; whereas class models are often used to model types of components and connectors in a product-line architecture. Previous works have explored the approach of using a single language to express both configurations of features and components. Their goal was to simplify the definition and analysis of feature-to-component mappings and to allow modeling component options as features. A prominent example of this approach is cardinality-based feature modeling, which extends feature models with multiple instantiation and references to express component-like, replicated features. Another example is to support feature modeling in a class modeling language, such as UML or MOF, using their profiling mechanisms and a stylized use of composition. Both examples have notable drawbacks: cardinality-based feature modeling lacks a constraint language and a well-defined semantics; encoding feature models as class models and their evolution bring extra complexity. This dissertation presents Clafer (class, feature, reference), a class modeling language with first-class support for feature modeling. Clafer can express rich structural models augmented with complex constraints, i.e., domain, variability, component models, and meta-models. Clafer supports: (i) class-based meta-models, (ii) object models (with uncertainty, if needed), (iii) feature models with attributes and multiple instantiation, (iv) configurations of feature models, (v) mixtures of meta- and feature models and model templates, and (vi) first-order logic constraints. Clafer also makes it possible to arrange models into multiple specialization and extension layers via constraints and inheritance. On the other hand, in designing Clafer we wanted to create a language that builds upon as few concepts as possible, and is easy to learn. The language is supported by tools for SPL verification and optimization. We propose to unify basic modeling constructs into a single concept, called clafer. In other words, Clafer is not a hybrid language. We identify several key mechanisms allowing a class modeling language to express feature models concisely. We provide Clafer with a formal semantics built in a novel, structurally explicit way. As Clafer subsumes cardinality-based feature modeling with attributes, references, and constraints, we are the first to precisely define semantics of such models. We also explore the notion of partial instantiation that allows for modeling with uncertainty and variability. We show that Object-Oriented Modeling (OOM) languages with no direct support for partial instances can support them via class modeling, using subclassing and strengthening multiplicity constraints. We make the encoding of partial instances via subclassing precise and general. Clafer uses this encoding and pushes the idea even further: it provides a syntactic unification of types and (partial) instances via subclassing and redefinition. We evaluate Clafer analytically and experimentally. The analytical evaluation shows that Clafer can concisely express feature and meta-models via a uniform syntax and unified semantics. The experimental evaluation shows that: 1) Clafer can express a variety of realistic rich structural models with complex constraints, such as variability models, meta-models, model templates, and domain models; and 2) that useful analyses can be performed within seconds.

Wireless sensing applications have extended into power transmission line monitoring applications. Minimal power consumption of sensor electronics have enabled kinetic energy harvesting systems to provides a means of self sustainability in the form of parasitic energy harvesting from power transmission lines. With this goal in mind, a miniature piezoelectric bimorph cantilever harvester has been developed using a magnetic tip mass which interacts with the oscillating magnetic flux surrounding power transmission wires. The focus of this thesis is develop an analytical model which can be used to optimize the amount of piezoelectric material to support sensory electronics. Special emphasis has also been placed on magnet orientation and geometry to ensure optimal magnetic flux interaction between input and output mechanisms. A single prototype harvester is designed with an arbitrary piezoelectric material length and experimentally validated at different conductor wire currents. The analytical model shows excellent agreement in frequency prediction for the prototype tested. Two damping techniques are used to experimentally extract modal damping ratios to predict peak mechanical and electrical responses at resonance frequencies. The miniature prototype design is less than 30 mm in length with only 10 mm piezoelectric material to produce a total volume of 154 10^-12 cm^3. The power output is measured at 174.1 W of power when positioned over top a 10 AWG copper conductor a distance of 6 mm with approximately 16 Amps of current passing though the conductor.

The diffuse interstellar bands (DIBs) probably arise from complex organic molecules whose strength in local galaxies correlates with neutral hydrogen column density, N(H I), and dust reddening, E(B−V). Because Damped Lyman-α systems are known to have high N(H I), and Ca II absorbers in quasar (QSO) spectra are posited to have high N(H I) and reddening, both represent promising sites for the detection of DIBs at cosmological distances. I present the results of a search for diffuse bands in seven DLAs and nine Ca II absorbers. I announce the detection of the first narrow DIBs at z>0 towards one DLA and one Ca II system. I further investigate the relative strengths of the DIBs as well as their correlations with N(H I) and E(B−V). Finally, I discuss the prospects for using DIBs to better understand the properties of quasar absorption systems, and for using DIB searches in absorption systems to better understand the properties of DIBs.

Many organizations have transitioned from single-systems development to product-line development with the goal of increasing productivity and facilitating mass customization. Variability modelling is a key activity in software product-line development that deals with the explicit representation of variability using dedicated models. Variability models specify points of variability and their variants in a product line. Although many variability-modelling notations and tools have been designed by researchers and practitioners, very little is known about their usage, actual benefits or challenges. Existing studies mostly describe product-line practices in general, with little focus on variability modelling. We address this gap through a qualitative study on variability-modelling practices in medium- and large-scale companies using two empirical methods: surveys and interviews. We investigated companies' variability-modelling practices and experiences with the aim to gather information on 1) the methods and strategies used to create and manage variability models, 2) the tools and notations used for variability modelling, 3) the perceived values and challenges of variability modelling, and 4) the core characteristics of their variability models. Our results show that variability models are often created by re-engineering existing products into a product line. All of the interviewees and the majority of survey participants indicated that they represent variability using separate variability models rather than annotative approaches. We found that developers use variability models for many purposes, such as the visualization of variabilities, configuration of products, and scoping of products. Although we observed that high degree of heterogeneity exists in the variability-modelling notations and tools used by organizations, feature-based notations and tools are the most common. We saw huge differences in the sizes of variability models and their contents, which indicate that variability models can have different use cases depending on the organization. Most of our study participants reported complexity challenges that were related mainly to the visualization and evolution of variability models, and dependency management. In addition, reports from interviews suggest that product-line adoption and variability modelling have forced developers to think in terms of a product-line scenario rather than a product-based scenario.

Thesis (Ph.D.)--University of South Australia, 1996.

Bibliography: leaves 158-167. / xvii, 173 leaves ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Investigates two level logic synthesis of asynchronous circuits from signal transition graphs (STGs) under the inertial gate delay model and the well behaved environment. Focuses on design methodologies and hazard free implementations based on redundant logic where the inertial delay model does not help to avoid hazards. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1997