10 resultados para Over Head Line Design

em Massachusetts Institute of Technology


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We compare a broad range of optimal product line design methods. The comparisons take advantage of recent advances that make it possible to identify the optimal solution to problems that are too large for complete enumeration. Several of the methods perform surprisingly well, including Simulated Annealing, Product-Swapping and Genetic Algorithms. The Product-Swapping heuristic is remarkable for its simplicity. The performance of this heuristic suggests that the optimal product line design problem may be far easier to solve in practice than indicated by complexity theory.

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This thesis introduces elements of a theory of design activity and a computational framework for developing design systems. The theory stresses the opportunistic nature of designing and the complementary roles of focus and distraction, the interdependence of evaluation and generation, the multiplicity of ways of seeing over the history of a design session versus the exclusivity of a given way of seeing over an arbitrarily short period, and the incommensurability of criteria used to evaluate a design. The thesis argues for a principle based rather than rule based approach to designing documents. The Discursive Generator is presented as a computational framework for implementing specific design systems, and a simple system for arranging blocks according to a set of formal principles is developed by way of illustration. Both shape grammars and constraint based systems are used to contrast current trends in design automation with the discursive approach advocated in the thesis. The Discursive Generator is shown to have some important properties lacking in other types of systems, such as dynamism, robustness and the ability to deal with partial designs. When studied in terms of a search metaphor, the Discursive Generator is shown to exhibit behavior which is radically different from some traditional search techniques, and to avoid some of the well-known difficulties associated with them.

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We describe a program called SketchIT capable of producing multiple families of designs from a single sketch. The program is given a rough sketch (drawn using line segments for part faces and icons for springs and kinematic joints) and a description of the desired behavior. The sketch is "rough" in the sense that taken literally, it may not work. From this single, perhaps flawed sketch and the behavior description, the program produces an entire family of working designs. The program also produces design variants, each of which is itself a family of designs. SketchIT represents each family of designs with a "behavior ensuring parametric model" (BEP-Model), a parametric model augmented with a set of constraints that ensure the geometry provides the desired behavior. The construction of the BEP-Model from the sketch and behavior description is the primary task and source of difficulty in this undertaking. SketchIT begins by abstracting the sketch to produce a qualitative configuration space (qc-space) which it then uses as its primary representation of behavior. SketchIT modifies this initial qc-space until qualitative simulation verifies that it produces the desired behavior. SketchIT's task is then to find geometries that implement this qc-space. It does this using a library of qc-space fragments. Each fragment is a piece of parametric geometry with a set of constraints that ensure the geometry implements a specific kind of boundary (qcs-curve) in qc-space. SketchIT assembles the fragments to produce the BEP-Model. SketchIT produces design variants by mapping the qc-space to multiple implementations, and by transforming rotating parts to translating parts and vice versa.

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Electrical circuit designers seldom create really new topologies or use old ones in a novel way. Most designs are known combinations of common configurations tailored for the particular problem at hand. In this thesis I show that much of the behavior of a designer engaged in such ordinary design can be modelled by a clearly defined computational mechanism executing a set of stylized rules. Each of my rules embodies a particular piece of the designer's knowledge. A circuit is represented as a hierarchy of abstract objects, each of which is composed of other objects. The leaves of this tree represent the physical devices from which physical circuits are fabricated. By analogy with context-free languages, a class of circuits is generated by a phrase-structure grammar of which each rule describes how one type of abstract object can be expanded into a combination of more concrete parts. Circuits are designed by first postulating an abstract object which meets the particular design requirements. This object is then expanded into a concrete circuit by successive refinement using rules of my grammar. There are in general many rules which can be used to expand a given abstract component. Analysis must be done at each level of the expansion to constrain the search to a reasonable set. Thus the rule of my circuit grammar provide constraints which allow the approximate qualitative analysis of partially instantiated circuits. Later, more careful analysis in terms of more concrete components may lead to the rejection of a line of expansion which at first looked promising. I provide special failure rules to direct the repair in this case.

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The next generations of both biological engineering and computer engineering demand that control be exerted at the molecular level. Creating, characterizing and controlling synthetic biological systems may provide us with the ability to build cells that are capable of a plethora of activities, from computation to synthesizing nanostructures. To develop these systems, we must have a set of tools not only for synthesizing systems, but also designing and simulating them. The BioJADE project provides a comprehensive, extensible design and simulation platform for synthetic biology. BioJADE is a graphical design tool built in Java, utilizing a database back end, and supports a range of simulations using an XML communication protocol. BioJADE currently supports a library of over 100 parts with which it can compile designs into actual DNA, and then generate synthesis instructions to build the physical parts. The BioJADE project contributes several tools to Synthetic Biology. BioJADE in itself is a powerful tool for synthetic biology designers. Additionally, we developed and now make use of a centralized BioBricks repository, which enables the sharing of BioBrick components between researchers, and vastly reduces the barriers to entry for aspiring Synthetic Biologists.

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In most classical frameworks for learning from examples, it is assumed that examples are randomly drawn and presented to the learner. In this paper, we consider the possibility of a more active learner who is allowed to choose his/her own examples. Our investigations are carried out in a function approximation setting. In particular, using arguments from optimal recovery (Micchelli and Rivlin, 1976), we develop an adaptive sampling strategy (equivalent to adaptive approximation) for arbitrary approximation schemes. We provide a general formulation of the problem and show how it can be regarded as sequential optimal recovery. We demonstrate the application of this general formulation to two special cases of functions on the real line 1) monotonically increasing functions and 2) functions with bounded derivative. An extensive investigation of the sample complexity of approximating these functions is conducted yielding both theoretical and empirical results on test functions. Our theoretical results (stated insPAC-style), along with the simulations demonstrate the superiority of our active scheme over both passive learning as well as classical optimal recovery. The analysis of active function approximation is conducted in a worst-case setting, in contrast with other Bayesian paradigms obtained from optimal design (Mackay, 1992).

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Manufacturing has evolved to become a critical element of the competitive skill set of defense aerospace firms. Given the changes in the acquisition environment and culture; traditional “thrown over the wall” means of developing and manufacturing products are insufficient. Also, manufacturing systems are complex systems that need to be carefully designed in a holistic manner and there are shortcomings with available tools and methods to assist in the design of these systems. This paper outlines the generation and validation of a framework to guide this manufacturing system design process.

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Caches are known to consume up to half of all system power in embedded processors. Co-optimizing performance and power of the cache subsystems is therefore an important step in the design of embedded systems, especially those employing application specific instruction processors. In this project, we propose an analytical cache model that succinctly captures the miss performance of an application over the entire cache parameter space. Unlike exhaustive trace driven simulation, our model requires that the program be simulated once so that a few key characteristics can be obtained. Using these application-dependent characteristics, the model can span the entire cache parameter space consisting of cache sizes, associativity and cache block sizes. In our unified model, we are able to cater for direct-mapped, set and fully associative instruction, data and unified caches. Validation against full trace-driven simulations shows that our model has a high degree of fidelity. Finally, we show how the model can be coupled with a power model for caches such that one can very quickly decide on pareto-optimal performance-power design points for rapid design space exploration.

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Most glyco-engineering approaches used to improve quality of recombinant glycoproteins involve the manipulation of glycosyltransferase and/or glycosidase expression. We investigated whether the over expression of nucleotide sugar transporters, particularly the CMP-sialic acid transporter (CMP-SAT), would be a means to improve the sialylation process in CHO cells. We hypothesized that increasing the expression of the CMP-SAT in the cells would increase the transport of the CMP-sialic acid in the Golgi lumen, hence increasing the intra-lumenal CMP-sialic acid pool, and resulting in a possible increase in sialylation extent of proteins being produced. We report the construction of a CMP-SAT expression vector which was used for transfection into CHO-IFNγ, a CHO cell line producing human IFNγ. This resulted in approximately 2 to 5 times increase in total CMP-SAT expression in some of the positive clones as compared to untransfected CHO-IFNγ, as determined using real-time PCR analysis. This in turn concurred with a 9.6% to 16.3% percent increase in site sialylation. This engineering approach has thus been identified as a novel means of improving sialylation in recombinant glycoprotein therapeutics. This strategy can be utilized feasibly on its own, or in combination with existing sialylation improvement strategies. It is believed that such multi-prong approaches are required to effectively manipulate the complex sialylation process, so as to bring us closer to the goal of producing recombinant glycoproteins of high and consistent sialylation from mammalian cells.

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Manufacturing has evolved to become a critical element of the competitive skill set of defense aerospace firms. Given the changes in the acquisition environment and culture; traditional “thrown over the wall” means of developing and manufacturing products are insufficient. Also, manufacturing systems are complex systems that need to be carefully designed in a holistic manner and there are shortcomings with available tools and methods to assist in the design of these systems. This paper outlines the generation and validation of a framework to guide this manufacturing system design process.