Robust Formulations for Handling Uncertainty in Kernel Matrices

We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we derive a formulation which is robust to such noise. The resulting formulation applies when the noise is Gaussian, or has finite support. The formulation in general is non-convex, but in several cases of interest it reduces to a convex program. The problem of uncertainty in kernel matrix is motivated from the real world problem of classifying proteins when the structures are provided with some uncertainty. The formulation derived here naturally incorporates such uncertainty in a principled manner leading to significant improvements over the state of the art. 1.

A Global Constraint On Relative Rotation To Avoid Lumped Compliant Mechanisms In Topology Optimization

Some of the well known formulations for topology optimization of compliant mechanisms could lead to lumped compliant mechanisms. In lumped compliance, most of the elastic deformation in a mechanism occurs at few points, while rest of the mechanism remains more or less rigid. Such points are referred to as point-flexures. It has been noted in literature that high relative rotation is associated with point-flexures. In literature we also find a formulation of local constraint on relative rotations to avoid lumped compliance. However it is well known that a global constraint is easier to handle than a local constraint, by a numerical optimization algorithm. The current work presents a way of putting global constraint on relative rotations. This constraint is also simpler to implement since it uses linearized rotation at the center of finite-elements, to compute relative rotations. I show the results obtained by using this constraint oil the following benchmark problems - displacement inverter and gripper.

Bond graph toolbox for handling complex variable

Bond graph is an apt modelling tool for any system working across multiple energy domains. Power electronics system modelling is usually the study of the interplay of energy in the domains of electrical, mechanical, magnetic and thermal. The usefulness of bond graph modelling in power electronic field has been realised by researchers. Consequently in the last couple of decades, there has been a steadily increasing effort in developing simulation tools for bond graph modelling that are specially suited for power electronic study. For modelling rotating magnetic fields in electromagnetic machine models, a support for vector variables is essential. Unfortunately, all bond graph simulation tools presently provide support only for scalar variables. We propose an approach to provide complex variable and vector support to bond graph such that it will enable modelling of polyphase electromagnetic and spatial vector systems. We also introduced a rotary gyrator element and use it along with the switched junction for developing the complex/vector variable's toolbox. This approach is implemented by developing a complex S-function tool box in Simulink inside a MATLAB environment This choice has been made so as to synthesise the speed of S-function, the user friendliness of Simulink and the popularity of MATLAB.

Constraint effects on multiple void interaction in pressure sensitive plastic solids

In this work, effects of pressure sensitive yielding and plastic dilatancy on void growth and void interaction mechanisms in fracture specimens displaying high and low constraint levels are investigated. To this end, large deformation finite element simulations are carried out with discrete voids ahead of the notch. It is observed that multiple void interaction mechanism which is favored by high initial porosity is further accelerated by pressure sensitive yielding, but is retarded by loss of constraint. The resistance curves predicted based on a simple void coalescence criterion show enhancement in fracture resistance when constraint level is low and when pressure sensitivity is suppressed.

Pressure sensitive flow and constraint factor in amorphous materials below glass transition

The constraint factor, C (given by the hardness-yield strength ratio H/Y in the fully lastic regime of indentation), in metallic glasses, is greater than three, a reflection of the sensitivity of their plastic flow to pressure. Furthermore, C increases with increasing temperature. In this work, we examine if this is true in amorphous polymers as well, through experiments on amorphous poly(methyl methacrylate) (PMMA). Uniaxial compression as well as spherical indentation tests were conducted in the 248-348 K range to construct H/Y versus indentation strain plots at each temperature and obtain the C-values. Results show that C increases with temperature in PMMA as well. Good correlation between the loss factors, measured using a dynamic mechanical analyzer, and C, suggest that the enhanced sensitivity to pressure is possibly due to beta-relaxation. We offer possible mechanistic reasons for the observed trends in amorphous materials in terms of relaxation processes.

Theoretical Maximum Limits on Power-Handling Capacity of HVDC Cables

In the case of an ac cable, power transmission is limited by the length of the cable due to the capacitive reactive current component. It is well known that high-voltage direct current (HVDC) cables do not have such limitations. However, insulation-related thermal problems pose a limitation on the power capability of HVDC cables. The author presents a viable theoretical development, a logical extension to Whitehead's theory on thermal limitations of the insulation. The computation of the maximum power-carrying capability of HVDC cables subject to limits on the maximum operable temperature of the insulation is presented. The limitation on the power-carrying capability is closely associated with the electrothermal insulation failure. The effect of environmental interaction by way of external thermal resistance, an important aspect, is also considered in the formulations. The Lagrange multiplier method has been used to handle the ensuing optimization problem. The theory is based on an accepted theory of thermal breakdown in insulation and is an important and a coherent extension of great significance.

Interval Data Classification under Partial Information: A Chance-Constraint Approach

This paper presents a Chance-constraint Programming approach for constructing maximum-margin classifiers which are robust to interval-valued uncertainty in training examples. The methodology ensures that uncertain examples are classified correctly with high probability by employing chance-constraints. The main contribution of the paper is to pose the resultant optimization problem as a Second Order Cone Program by using large deviation inequalities, due to Bernstein. Apart from support and mean of the uncertain examples these Bernstein based relaxations make no further assumptions on the underlying uncertainty. Classifiers built using the proposed approach are less conservative, yield higher margins and hence are expected to generalize better than existing methods. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle interval-valued uncertainty than state-of-the-art.

A constraint Jacobian based approach for static analysis of pantograph masts

This paper presents a constraint Jacobian matrix based approach to obtain the stiffness matrix of widely used deployable pantograph masts with scissor-like elements (SLE). The stiffness matrix is obtained in symbolic form and the results obtained agree with those obtained with the force and displacement methods available in literature. Additional advantages of this approach are that the mobility of a mast can be evaluated, redundant links and joints in the mast can be identified and practical masts with revolute joints can be analysed. Simulations for a hexagonal mast and an assembly with four hexagonal masts is presented as illustrations.

Magnetic helicity as a constraint on coronal dissipation

The Taylor hypothesis has provided a model for the relaxed magnetic configurations of not only laboratory plasmas, but also of astrophysical plasmas. However, energy dissipation is possible only for systems which depart from a strict Taylor state, and hence a parameter describing that departure must be introduced, when the Taylor hypothesis is used to estimate the dissipation. An application of the Taylor hypothesis to the problem of coronal heating provides an insight into this difficult problem. When particular sorts of footpoint motions put energy and helicity in the corona, the conservation of helicity puts a constraint on how much of the energy can be dissipated. However, on considering a random distribution of footpoint motions, this constraint gets washed away, and the Taylor hypothesis is probably not going to play any significant role in the actual calculation of relevant physical quantities in the coronal heating problem.

A numerical study of crack tip constraint in ductile single crystals

In this work, the effect of crack tip constraint on near-tip stress and deformation fields in a ductile FCC single crystal is studied under mode I, plane strain conditions. To this end, modified boundary layer simulations within crystal plasticity framework are performed, neglecting elastic anisotropy. The first and second terms of the isotropic elastic crack tip field, which are governed by the stress intensity factor K and T-stress, are prescribed as remote boundary conditions and solutions pertaining to different levels of T-stress are generated. It is found that the near-tip deformation field, especially, the development of kink or slip shear bands, is sensitive to the constraint level. The stress distribution and the size and shape of the plastic zone near the crack tip are also strongly influenced by the level of T-stress, with progressive loss of crack tip constraint occurring as T-stress becomes more negative. A family of near-tip fields is obtained which are characterized by two terms (such as K and T or J and a constraint parameter Q) as in isotropic plastic solids.

High-Throughput Flexible Constraint Length Viterbi Decoders on De Bruijn, Shuffle-Exchange and Butterfly Connected Architectures

Flexible constraint length channel decoders are required for software defined radios. This paper presents a novel scalable scheme for realizing flexible constraint length Viterbi decoders on a de Bruijn interconnection network. Architectures for flexible decoders using the flattened butterfly and shuffle-exchange networks are also described. It is shown that these networks provide favourable substrates for realizing flexible convolutional decoders. Synthesis results for the three networks are provided and a comparison is performed. An architecture based on a 2D-mesh, which is a topology having a nominally lesser silicon area requirement, is also considered as a fourth point for comparison. It is found that of all the networks considered, the de Bruijn network offers the best tradeoff in terms of area versus throughput.

Handling sectional views in volume-based approach to automatically construct 3D solid from 2D views

This paper presents an algorithm for solid model reconstruction from 2D sectional views based on volume-based approach. None of the existing work in automatic reconstruction from 2D orthographic views have addressed sectional views in detail. It is believed that the volume-based approach is better suited to handle different types of sectional views. The volume-based approach constructs the 3D solid by a boolean combination of elementary solids. The elementary solids are formed by sweep operation on loops identified in the input views. The only adjustment to be made for the presence of sectional views is in the identification of loops that would form the elemental solids. In the algorithm, the conventions of engineering drawing for sectional views, are used to identify the loops correctly. The algorithm is simple and intuitive in nature. Results have been obtained for full sections, offset sections and half sections. Future work will address other types of sectional views such as removed and revolved sections and broken-out sections. (C) 2004 Elsevier Ltd. All rights reserved.

Delay optimal control algorithm for a multiaccess fading channel with peak power constraint

We consider an optimal power and rate scheduling problem for a multiaccess fading wireless channel with the objective of minimising a weighted sum of mean packet transmission delay subject to a peak power constraint. The base station acts as a controller which, depending upon the buffer lengths and the channel state of each user, allocates transmission rate and power to individual users. We assume perfect channel state information at the transmitter and the receiver. We also assume a Markov model for the fading and packet arrival processes. The policy obtained represents a form of Indexability.

Measurement of air leakage in air-handling units and air conditioning ducts

The purpose of this article is to report the experience of design and testing of orifice plate-based flow measuring systems for evaluation of air leakages in components of air conditioning systems. Two of the flow measuring stations were designed with a beta value of 0.405 and 0.418. The third was a dual path unit with orifice plates of beta value 0.613 and 0.525. The flow rates covered with all the four were from 4-94 l/s and the range of Reynolds numbers is from 5600 to 76,000. The coefficients of discharge were evaluated and compared with the Stolz equation. Measured C-d values are generally higher than those obtained from the equation, the deviations being larger in the low Reynolds number region. Further, it is observed that a second-degree polynomial is inadequate to relate the pressure drop and flow rate. The lower Reynolds number limits set by standards appear to be somewhat conservative.

Second order cone programming approaches for handling missing and uncertain data

We propose a novel second order cone programming formulation for designing robust classifiers which can handle uncertainty in observations. Similar formulations are also derived for designing regression functions which are robust to uncertainties in the regression setting. The proposed formulations are independent of the underlying distribution, requiring only the existence of second order moments. These formulations are then specialized to the case of missing values in observations for both classification and regression problems. Experiments show that the proposed formulations outperform imputation.