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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
31

Computer explorations.

Howson, Hugh R. January 1971 (has links)
No description available.
32

Large scale integer programming : a novel solution method and application

Gzara, Fatma January 2003 (has links)
Integer programming is a powerful modeling tool for a variety of decision making problems such as in telecommunications network design and in routing and scheduling. Integer programming models of realistic problems are large in size and pose serious challenge to available software. This creates an urgent need for solution methodologies that can deal with their size and complexity. In this thesis, we focus on the theoretical development, implementation and testing of a novel methodology: an interior-point branch-and-price algorithm with cut generation for large scale integer programming. / The methodology applies to any integer program but is built for a general class of integer programming that has a large, possibly exponential set of constraints. It starts by applying a decomposition method to the complicating constraints. We focus on Lagrangian relaxation or Dantzig-Wolfe decomposition; both lead to a master problem with an exponential number of variables and constraints. The same analysis applies when one starts by relaxing the exponential constraints and then applying a decomposition method. In both cases, one has to solve iteratively a master problem that is updated by appending violated cuts and columns. For that, we propose a cut and column generation algorithm based on analytic centers. / The cut and column generation algorithm solves a restricted master problem using a primal analytic center cutting plane method to obtain a bound on the original problem. The bound may be poor in quality since most of the complicating constraints are relaxed. To strengthen the bound, we generate violated constraints and append them to the master problem. At this point we use available information to warm-start the solution of the updated restricted master problem. This is done using a dual Newton method to calculate the next analytic center, after which we proceed with the primal method. / The bound is then embedded within a branch-and-bound algorithm leading to a branch-and-price algorithm. In fact, the algorithm is more than a branchand-price since it is able to deal with valid cuts added at the level of the master problem. This is a major step towards an interior-point branch-andcut-and-price algorithm. For an efficient integration of the cut and column generation algorithm within branch-and-bound, we use available information from a parent node to warm-start the calculation of the bound at child nodes. This is achieved by a dual Newton method.
33

Musical expertise as a scaffold for novice programming

Benton, Thomas Jonathan 04 September 2015 (has links)
This study addresses the role of musical expertise on novice computer programming. Engaging novices with computer programming is one of the great challenges of computer science education. Although there is extensive research focusing on constructionist approaches to programming education and creative entry points to programming, little research addresses the topic of how musical expertise informs an unstructured programming activity. To answer this question I focused on the role of participant talk during programming, patterns in participant programming, and evidence of computational thinking in participants’ final Scratch projects. For this interpretivist study, I worked with a dozen novice programmers from a variety of musical backgrounds: classical musicians, jazz musicians, composers, and non- musicians. Each participant worked on a free-form musical project in the Scratch programming environment. I collected data including participant talk, screen recordings of participant programming, and participants’ final Scratch projects. Overall, musical participants more readily took to the numeracy involved in programming music in Scratch. Also, musical participants were able to use musical concepts and techniques as jumping-off points for programming challenges. Considering my results by participant group, composers stood out in a number of ways: working the longest, testing their programs the most often, adding Scratch objects the slowest, v removing the most Scratch objects, creating projects of the greatest nested depth, and unanimous use of operators and random numbers. Non-musicians, on the other hand, worked for the shortest amount of time, added the fewest Scratch objects, and created projects of the lowest nested depth. In addition to adding to the body of research around chunking and tinkering, this study reinforces the importance of context and comfort in an introduction to computer programming. Composition may be an especially rich area to leverage, given the design- like programming activity of the composers here. Future research projects could resemble this one while focusing on younger learners, explicit musical concepts like those invoked by participants, or alternative performing arts framings such as theater or dance. / text
34

The complexity of recognizing linear systems with certain integrality properties

Feng, Li, 馮麗 January 2007 (has links)
published_or_final_version / abstract / Mathematics / Master / Master of Philosophy
35

A language with class : the theory of classification exemplified in an object-oriented language

Simons, Anthony James Howard January 1995 (has links)
No description available.
36

Projection methods for large scale structured nonlinear programming problems

Simms, Peter Douglas January 1979 (has links)
iv, 123 leaves : ill., tables ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Applied Mathematics, 1980
37

A duality approach for solving problems of optimum allocation of resources / by John Bednarz

Bednarz, John January 1980 (has links)
Typescript (photocopy) / iv, 136 leaves ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--Dept. of Applied Mathematics, University of Adelaide, 1980
38

An experimental investigation of some heuristics for scheduling resource-constrained projects / by Dale F. Cooper

Cooper, Dale Francis January 1974 (has links)
ix, 295 leaves : tables ; 25 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.1975) from the Dept. of Computing Science, University of Adelaide
39

Designing an application-specific programming language for mobile robots

Biggs, Geoffrey January 2007 (has links)
The process of programming mobile robots is improved by this work. The tools used for programming robot systems have not advanced significantly, while robots themselves are rapidly becoming more capable because of advances in computing power and sensor technology. Industrial robotics relies on simple programming tools usable by non-expert programmers, while robotics researchers tend to use general purpose languages designed for programming in other domains. The task of developing a robot cannot be assumed to be identical to developing other software-based systems. The nature of robot programming is that there are different and additional challenges when programming a robot than when programming in other domains. A robot has many complex interfaces, must deal with regular and irregular events, real-time issues, large quantities of data, and the dangers of unknown conditions. Mobile robots move around and are capable of affecting everything in the environment. They are found in cluttered environments, rather than the carefully-controlled work spaces of industrial robots, increasing the risk to life and property and the complexity of the software. An analysis of the process of developing robots provides insight into how robot programming environments can be improved to make the task of robot development easier. Three analyses have been performed: a task analysis, to determine the important components of the robot development process, a use case analysis, to determine what robot developers must do, and a requirements analysis, to determine the requirements of a robot programming environment. From these analyses, the important features of a robot development environment were found. They include features such as data types for data commonly found in robotics, semantics for managing reactivity, and debugging facilities such as simulators. The analyses also found that the language is an important component of the programming environment. An application-specific language designed for robot programming is proposed as a solution for providing this component. Application-specific languages are designed for a particular domain of programming, allowing them to overcome the difficulties in that domain without concern for their usefulness in other domains. To test the hypothesis that such a language would improve robot development a set of language extensions has been created. These extensions, named RADAR, provide explicit support for robotics. The prototype implementation uses the Python programming language as the base language. RADAR provides support for two of the necessary features found in the analyses. The first is support for dimensioned data via a new primitive data type, ensuring all dimensioned data is consistent throughout a program. Dimensional analysis support is provided, allowing the safe mixing of data with compatible units, the creation of more complex units from simple single-dimension units, and built-in checking for errors in dimensioned data such as performing operations involving incompatible dimensioned data. For example, the data type will prevent the addition of distance and speed values. Several dimensional analysis systems have been developed for general purpose languages in the past. However, this is the first application of the concept specifically to robotics. The second feature is semantics for managing reactivity. In RADAR, the principle of ease-of-use through simplicity is followed. Special objects represent events and responses, and a special syntax is used for both specifying these objects and managing the connections between them in response to the changing state of the program. This reduces programming complexity and time. There are many other languages for managing reactivity, both the more general languages, such as Esterel, and languages for robotics, such as TDL and Colbert. RADAR is simpler than the general languages, as it is aimed solely at the needs of robot developers. However, it takes a different approach to its design than other languages for reactivity in robotics. These are designed to provide support for a specific architecture or architecture style; RADAR is designed based on the needs of robot developers and so is architecture-independent. RADAR’s design philosophy is to provide robot-specific features with simple semantics. RADAR is designed to support what robot developers need to do with the language, rather than providing a special syntax for supporting a particular robot, architecture or other system. RADAR has been shown to provide an improvement in dimensioned data management and reactivity management for mobile robot programming. It increases the readability, writability and reliability of robot software, and can reduce programming and maintenance costs. RADAR shows that an application-specific approach to developing a robot programming language can improve the process of robot development.
40

Designing an application-specific programming language for mobile robots

Biggs, Geoffrey January 2007 (has links)
The process of programming mobile robots is improved by this work. The tools used for programming robot systems have not advanced significantly, while robots themselves are rapidly becoming more capable because of advances in computing power and sensor technology. Industrial robotics relies on simple programming tools usable by non-expert programmers, while robotics researchers tend to use general purpose languages designed for programming in other domains. The task of developing a robot cannot be assumed to be identical to developing other software-based systems. The nature of robot programming is that there are different and additional challenges when programming a robot than when programming in other domains. A robot has many complex interfaces, must deal with regular and irregular events, real-time issues, large quantities of data, and the dangers of unknown conditions. Mobile robots move around and are capable of affecting everything in the environment. They are found in cluttered environments, rather than the carefully-controlled work spaces of industrial robots, increasing the risk to life and property and the complexity of the software. An analysis of the process of developing robots provides insight into how robot programming environments can be improved to make the task of robot development easier. Three analyses have been performed: a task analysis, to determine the important components of the robot development process, a use case analysis, to determine what robot developers must do, and a requirements analysis, to determine the requirements of a robot programming environment. From these analyses, the important features of a robot development environment were found. They include features such as data types for data commonly found in robotics, semantics for managing reactivity, and debugging facilities such as simulators. The analyses also found that the language is an important component of the programming environment. An application-specific language designed for robot programming is proposed as a solution for providing this component. Application-specific languages are designed for a particular domain of programming, allowing them to overcome the difficulties in that domain without concern for their usefulness in other domains. To test the hypothesis that such a language would improve robot development a set of language extensions has been created. These extensions, named RADAR, provide explicit support for robotics. The prototype implementation uses the Python programming language as the base language. RADAR provides support for two of the necessary features found in the analyses. The first is support for dimensioned data via a new primitive data type, ensuring all dimensioned data is consistent throughout a program. Dimensional analysis support is provided, allowing the safe mixing of data with compatible units, the creation of more complex units from simple single-dimension units, and built-in checking for errors in dimensioned data such as performing operations involving incompatible dimensioned data. For example, the data type will prevent the addition of distance and speed values. Several dimensional analysis systems have been developed for general purpose languages in the past. However, this is the first application of the concept specifically to robotics. The second feature is semantics for managing reactivity. In RADAR, the principle of ease-of-use through simplicity is followed. Special objects represent events and responses, and a special syntax is used for both specifying these objects and managing the connections between them in response to the changing state of the program. This reduces programming complexity and time. There are many other languages for managing reactivity, both the more general languages, such as Esterel, and languages for robotics, such as TDL and Colbert. RADAR is simpler than the general languages, as it is aimed solely at the needs of robot developers. However, it takes a different approach to its design than other languages for reactivity in robotics. These are designed to provide support for a specific architecture or architecture style; RADAR is designed based on the needs of robot developers and so is architecture-independent. RADAR’s design philosophy is to provide robot-specific features with simple semantics. RADAR is designed to support what robot developers need to do with the language, rather than providing a special syntax for supporting a particular robot, architecture or other system. RADAR has been shown to provide an improvement in dimensioned data management and reactivity management for mobile robot programming. It increases the readability, writability and reliability of robot software, and can reduce programming and maintenance costs. RADAR shows that an application-specific approach to developing a robot programming language can improve the process of robot development.

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