42 research outputs found
Integrating digital design and fabrication and craft production
No full textThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 61-63).This thesis examines if methods of manual craft production can be utilised to overcome the indeterminacies of physical materials and processes that hinder Digital Design and Fabrication (DDF). Indeterminacies in physical materials and processes are considered to be errors that prevent DDF from achieving its stated goal of a seamless transition from digital model to physical artefact. One of the definitions of craft, by contrast, is "(potentially) error through and through...[where error is]... an incomputable deviation from the norm" (Dutta, 2007, p. 211). This concept of error as being 'incomputable' is analysed using theories from computation, systems theory and sociology to formulate a definition of material craft production for this thesis. Material craft production is then compared to the concept of digital craft and it is argued that digital craft is limited in its capacity to negotiate physical materials and processes. Tools from systems theory are then used to propose a model describing material craft production. This model is called the Sensing-Evaluating-Shaping (SES) model. The validity of the SES model is tested through case studies of material craft production. The SES model is analysed using systems analysis tools and a role for DDF is proposed within the SES model, giving rise to digital SES production. The ability of digital SES production to negotiate indeterminacies in physical materials and processes is tested through the fabrication of a series of increasingly complex physical artefacts.by Ayodh Vasant Kamath.S.M
Partitioning algorithms for parallel circuit simulation
No full textCircuit simulation is an indispensable tool in the design and analysis of Very Large Scale Integrated (VLSI) circuits. The most widely used circuit simulators rely on direct methods and offer the most accurate, reliable, and technology-independent means of simulating integrated circuits. The simulation process is inherently very computation intensive and, hence, can require a significant portion of the computational resources available for the development of VLSI circuits. With the use of multiprocessor computers becoming more widespread, there exists an opportunity to speed up the simulation by partitioning the circuit so that the computation may be spread among the processors. To accomplish this, the circuit is partitioned into subcircuits using a node tearing method. If the circuit matrix is ordered subcircuit by subcircuit followed by the tearing nodes, then the matrix takes a bordered-block-diagonal form and the LU-factorization of the diagonal blocks may take place in parallel. This thesis defines the important objectives for this partitioning task and presents two algorithms that may be used to meet the partitioning goals. The first algorithm is an iterative improvement algorithm and the second is a network flow algorithm. Partitioning results and speedups are given for a variety of circuits.Made available in DSpace on 2011-05-07T12:46:05Z (GMT). No. of bitstreams: 2
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Combinatorial optimization by stochastic evolution with applications to the physical design of VLSI circuits
No full textIn this thesis, a new general adaptive algorithm for solving a wide variety of NP-Complete combinatorial problems is developed. The new technique is called Stochastic Evolution (SE). The SE algorithm is applied to Network Bisection, Vertex Cover, Set Partition, Hamilton Circuit, Traveling Salesman, Linear Ordering, Standard Cell Placement, and Multi-way Circuit Partitioning problems. It is empirically shown that SE out-performs the more established general optimization algorithm, namely, Simulated Annealing.Made available in DSpace on 2011-05-07T12:15:35Z (GMT). No. of bitstreams: 2
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Predicting Protein-Protein Interaction Sites From Amino Acid Sequence
No full textPredicting Protein-Protein Interaction Sites From Amino Acid Sequence Changhui Yan, Vasant Honavar and Drena Dobbs Artificial Intelligence Research Laboratory Bioinformatics and Computational Biology Graduate Program Iowa State University Ames, Iowa 50011 Corresponding author: Changhui Yan Email address of the corresponding author: [email protected] Abstract We describe an approach for computational prediction of protein-protein interaction sites using a support vector machine (SVM) classifier. Interface residues and other surface residues were extracted from 115 proteins derived from a set of 70 heterocomplexes in PDB. The SVM classifier was trained to predict whether or not a surface residue is located in the interface based on the identity of the target residue and its 10 sequence neighbors. The effectiveness of the approach was evaluated using 115 leave-one-out cross validation (jack-knife) experiments. In each experiment, an SVM classifier was trained using a set of 1250 randomly chosen interface residues and an equal number of non-interface residues from 114 of the 115 molecules. The resulting classifier was used to classify surface residues from the remaining molecule into interface and non-interface residues. The classifier in each experiment was evaluated in terms of several performance measures. In results averaged over 115 experiments, interface residues and non-interface residues were identified with relatively high specificity (71%) and sensitivity (67%), and with a correlation coefficient of 0.29 between predicted and actual class labels, indicating that the method performs substantially better than chance (zero correlation). We also investigated the classifier's performance in terms of overall interactions site recognition. In 80% of the proteins, the classifier recognized the interaction surface by identifying at least half of the interface residues, and in 98% of the proteins, at least 20% of the interface residues were correctly identified. The success of this approach was confirmed by examination of predicted interfaces in the context of the three-dimensional structures of representative complexes. This study demonstrates that an SVM classifier can be used to predict whether or not a surface residue is an interface residue using amino acid sequence information. Because surface residues can be identified based on their solvent accessible surface area (ASA), given recent progress in computational methods for predicting ASA from sequence, the approach described in this paper provides a basis for computational prediction of interaction sites in proteins for which only amino acid sequence information is available. Keywords: protein-protein interaction; interaction site prediction; interface residues; support vector machine.</p
An eigenvalue-based approach to the finite time behavior of simulated annealing
No full textIn this thesis, we present a framework under which the finite time behavior of the simulated annealing for combinatorial optimization can be studied. We will use linear algebraic methods for this purpose. The simulated annealing algorithm will be modeled as a finite space, discrete time Markov chain which can then be represented by a probability transition matrix whose entries are controlled by a parameter known as the temperature.We first consider a simpler version of the algorithm in which the temperature is held to a constant value. The algorithm can then be modeled by a time homogeneous Markov chain which converges to an equilibrium distribution. In this case, the speed of convergence can be ascertained if certain eigenvalues of the transition matrix are known, and the equilibrium distribution depends on the distribution of costs. We explore different approaches to obtain bounds on these eigenvalues and apply these bounds to study the convergence of the fixed-temperature algorithm to solve the integer composition problem, which is NP-complete. We present a detailed study of the cost distribution for this problem. Consequently, we are able to study the computational complexity of the fixed-temperature algorithm to solve the integer composition problem.We also consider the case of simulated annealing in which the temperature is reduced according to a cooling schedule. By using an absorbing chain model of the algorithm, we are able to study its finite time behavior in terms of an eigenvalue of the absorbing chain's transition matrix. We provide asymptotic bounds for this eigenvalue from which we obtain an asymptotic sufficiency result for the annealing algorithm to find an optimal state. We also obtain structural bounds for this eigenvalue, from which the finite time behavior of the algorithm may be studied.Made available in DSpace on 2011-05-07T13:32:44Z (GMT). No. of bitstreams: 2
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Lattice dynamic study of nickel ferrite nanoparticles using high pressure Raman spectroscopy
No full textTheoretical design and evaluation of endoluminal ultrasound applicators for thermal therapy of pancreatic cancer under image guidance
No full textHigh-intensity interstitial ultrasound for thermal ablation of focal cancer targets in prostate
No full textTetramethylene glycol mediated hydrothermal synthesis of defect-rich SnO2 nanoparticles for fast adsorption and degradation of MB dye
No full textZeta potential and Raman studies of PVP capped Bi2S3 nanoparticles synthesized by polyol method
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