62 resultados para Continuous characters
em Indian Institute of Science - Bangalore - Índia
Resumo:
The work studies the extent of asymmetric flow in water models of continuous casting molds of two different configurations. In the molds where fluid is discharged through multiple holes at the bottom, the flow pattern in the lower portion depends on the size of the lower two recirculating domains. If they reach the mold bottom, the flow pattern in the lower portion is symmetrical about the central plane; otherwise, it is asymmetrical. On the other hand, in the molds where the fluid is discharged through the entire mold cross section, the flow pattern is always asymmetrical if the aspect ratio is 1:6.25 or more. The fluid jet swirls while emerging through the nozzle. The interaction of the swirling Jets with the wide sidewalls of the mold gives rise to asymmetrical flow inside the mold. In the molds with lower aspect ratios, where the jets do not touch the wide side walls, the flow pattern is symmetrical about the central plane.
Resumo:
This paper suggests a scheme for classifying online handwritten characters, based on dynamic space warping of strokes within the characters. A method for segmenting components into strokes using velocity profiles is proposed. Each stroke is a simple arbitrary shape and is encoded using three attributes. Correspondence between various strokes is established using Dynamic Space Warping. A distance measure which reliably differentiates between two corresponding simple shapes (strokes) has been formulated thus obtaining a perceptual distance measure between any two characters. Tests indicate an accuracy of over 85% on two different datasets of characters.
Resumo:
Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where one has access only to noise-corrupted values of the objective function. In this paper, we present a novel formulation for noise-tolerant learning of linear classifiers using a CALA team. We consider the general case of nonuniform noise, where the probability that the class label of an example is wrong may be a function of the feature vector of the example. The objective is to learn the underlying separating hyperplane given only such noisy examples. We present an algorithm employing a team of CALA and prove, under some conditions on the class conditional densities, that the algorithm achieves noise-tolerant learning as long as the probability of wrong label for any example is less than 0.5. We also present some empirical results to illustrate the effectiveness of the algorithm.
Resumo:
The photopolymerization of methyl,ethyl,butyl, and hexyl methacrylates in solution was studied. The effect of initial initiator and monomer concentrations on the time evolution of polymer concentration (M) over bar (n) and PDI was examined. The reversible chain addition and beta-scission, and primary radical termination steps were included in the mechanism along with the classical steps. The rate equations were derived using continuous distribution kinetics and solved numerically to fit the experimental data. The regressed rate coefficients compared well with the literature data. The model predicted the instantaneous increase in (M) over bar (n) and PDI to steady state values. The rate coefficients exhibited a linear increase with the size of alkyl chain of the alkyl methacrylates.
Resumo:
An aeration process in ail activated sludge plant is a continuous-flow system. In this system, there is a steady input flow (flow from the primary clarifier or settling tank with some part from the secondary clarifier or secondary settling tank) and output flow connection to the secondary clarifier or settling tank. The experimental and numerical results obtained through batch systems can not be relied on and applied for the designing of a continuous aeration tank. In order to scale up laboratory results for field application, it is imperative to know the geometric parameters of a continuous system. Geometric parameters have a greater influence on the mass transfer process of surface aeration systems. The present work establishes the optimal geometric configuration of a continuous-flow surface aeration system. It is found that the maintenance of these optimal geometric parameters systems result in maximum aeration efficiency. By maintaining the obtained optimal geometric parameters, further experiments are conducted in continuous-flow surface aerators with three different sizes in order to develop design curves correlating the oxygen transfer coefficient and power number with the rotor speed. The design methodology to implement the presently developed optimal geometric parameters and correlation equations for field application is discussed.
Resumo:
In this work, we explore simultaneous geometry design and material selection for statically determinate trusses by posing it as a continuous optimization problem. The underlying principles of our approach are structural optimization and Ashby’s procedure for material selection from a database. For simplicity and ease of initial implementation, only static loads are considered in this work with the intent of maximum stiffness, minimum weight/cost, and safety against failure. Safety of tensile and compression members in the truss is treated differently to prevent yield and buckling failures, respectively. Geometry variables such as lengths and orientations of members are taken to be the design variables in an assumed layout. Areas of cross-section of the members are determined to satisfy the failure constraints in each member. Along the lines of Ashby’s material indices, a new design index is derived for trusses. The design index helps in choosing the most suitable material for any geometry of the truss. Using the design index, both the design space and the material database are searched simultaneously using gradient-based optimization algorithms. The important feature of our approach is that the formulated optimization problem is continuous, although the material selection from a database is an inherently discrete problem. A few illustrative examples are included. It is observed that the method is capable of determining the optimal topology in addition to optimal geometry when the assumed layout contains more links than are necessary for optimality.
Resumo:
Instability in conventional haptic rendering destroys the perception of rigid objects in virtual environments. Inherent limitations in the conventional haptic loop restrict the maximum stiffness that can be rendered. In this paper we present a method to render virtual walls that are much stiffer than those achieved by conventional techniques. By removing the conventional digital haptic loop and replacing it with a part-continuous and part-discrete time hybrid haptic loop, we were able to render stiffer walls. The control loop is implemented as a combinational logic circuit on an field-programmable gate array. We compared the performance of the conventional haptic loop and our hybrid haptic loop on the same haptic device, and present mathematical analysis to show the limit of stability of our device. Our hybrid method removes the computer-intensive haptic loop from the CPU-this can free a significant amount of resources that can be used for other purposes such as graphical rendering and physics modeling. It is our hope that, in the future, similar designs will lead to a haptics processing unit (HPU).
Resumo:
In this paper, we describe a system for the automatic recognition of isolated handwritten Devanagari characters obtained by linearizing consonant conjuncts. Owing to the large number of characters and resulting demands on data acquisition, we use structural recognition techniques to reduce some characters to others. The residual characters are then classified using the subspace method. Finally the results of structural recognition and feature-based matching are mapped to give final output. The proposed system Ifs evaluated for the writer dependent scenario.
Resumo:
A three dimensional elasticity solution for the analysis of beams continuous over an infinite number of equally spaced supports has been given. The beam has been subjected to normal tractions on its two opposite faces and these loads are identical over each span. The other two faces are traction free. Numerical results have been given for different cases when the beam is loaded on its bottom face. The results obtained have been compared with the results of two dimensional elasticity solution.
Resumo:
Continuous CO2 laser welding of an Fe-Cu dissimilar couple in a butt-weld geometry at different process conditions is studied. The process conditions are varied to identify and characterize the microstructural features that are independent of the welding mode. The study presents a characterization of the microstructure and mechanical properties of the welds. Detailed microstructural analysis of the weld/base-metal interface shows features that are different on the two sides of the weld. The iron side can grow into the weld with a local change in length scale, whereas the interface on the copper side indicates a barrier to growth. The interface is jagged, and a banded microstructure consisting of iron-rich layers could be observed next to the weld/Cu interface. The observations suggest that solidification initiates inside the melt, where iron and copper are mixed due to convective flow. The transmission electron microscopy (TEM) of the weld region also indicates the occasional presence of droplets of iron and copper. The microstructural observations are rationalized using arguments drawn from a thermodynamic analysis of the Fe-Cu system.
Resumo:
We present a new computationally efficient method for large-scale polypeptide folding using coarse-grained elastic networks and gradient-based continuous optimization techniques. The folding is governed by minimization of energy based on Miyazawa–Jernigan contact potentials. Using this method we are able to substantially reduce the computation time on ordinary desktop computers for simulation of polypeptide folding starting from a fully unfolded state. We compare our results with available native state structures from Protein Data Bank (PDB) for a few de-novo proteins and two natural proteins, Ubiquitin and Lysozyme. Based on our simulations we are able to draw the energy landscape for a small de-novo protein, Chignolin. We also use two well known protein structure prediction software, MODELLER and GROMACS to compare our results. In the end, we show how a modification of normal elastic network model can lead to higher accuracy and lower time required for simulation.
Resumo:
Continuous common mode feedback (CMFB) circuits having high input impedance and low distortion are proposed. The proposed circuits are characterized for 0.18 mu m CMOS process with 1.8 V supply. Simulation results indicate that the proposed common mode detector consumes no standby power and CMFB circuit consumes 27-34% less power than previous high swing CMFB circuits.
Resumo:
This paper addresses the problem of resolving ambiguities in frequently confused online Tamil character pairs by employing script specific algorithms as a post classification step. Robust structural cues and temporal information of the preprocessed character are extensively utilized in the design of these algorithms. The methods are quite robust in automatically extracting the discriminative sub-strokes of confused characters for further analysis. Experimental validation on the IWFHR Database indicates error rates of less than 3 % for the confused characters. Thus, these post processing steps have a good potential to improve the performance of online Tamil handwritten character recognition.
Resumo:
The notion of optimization is inherent in protein design. A long linear chain of twenty types of amino acid residues are known to fold to a 3-D conformation that minimizes the combined inter-residue energy interactions. There are two distinct protein design problems, viz. predicting the folded structure from a given sequence of amino acid monomers (folding problem) and determining a sequence for a given folded structure (inverse folding problem). These two problems have much similarity to engineering structural analysis and structural optimization problems respectively. In the folding problem, a protein chain with a given sequence folds to a conformation, called a native state, which has a unique global minimum energy value when compared to all other unfolded conformations. This involves a search in the conformation space. This is somewhat akin to the principle of minimum potential energy that determines the deformed static equilibrium configuration of an elastic structure of given topology, shape, and size that is subjected to certain boundary conditions. In the inverse-folding problem, one has to design a sequence with some objectives (having a specific feature of the folded structure, docking with another protein, etc.) and constraints (sequence being fixed in some portion, a particular composition of amino acid types, etc.) while obtaining a sequence that would fold to the desired conformation satisfying the criteria of folding. This requires a search in the sequence space. This is similar to structural optimization in the design-variable space wherein a certain feature of structural response is optimized subject to some constraints while satisfying the governing static or dynamic equilibrium equations. Based on this similarity, in this work we apply the topology optimization methods to protein design, discuss modeling issues and present some initial results.