Phylogenetic Predictions on Grids

A phylogenetic or evolutionary tree is constructed from a set of species or DNA sequences and depicts the relatedness between the sequences. Predictions of future sequences in a phylogenetic tree are important for a variety of applications including drug discovery, pharmaceutical research and disease control. In this work, we predict future DNA sequences in a phylogenetic tree using cellular automata. Cellular automata are used for modeling neighbor-dependent mutations from an ancestor to a progeny in a branch of the phylogenetic tree. Since the number of possible ways of transformations from an ancestor to a progeny is huge, we use computational grids and middleware techniques to explore the large number of cellular automata rules used for the mutations. We use the popular and recurring neighbor-based transitions or mutations to predict the progeny sequences in the phylogenetic tree. We performed predictions for three types of sequences, namely, triose phosphate isomerase, pyruvate kinase, and polyketide synthase sequences, by obtaining cellular automata rules on a grid consisting of 29 machines in 4 clusters located in 4 countries, and compared the predictions of the sequences using our method with predictions by random methods. We found that in all cases, our method gave about 40% better predictions than the random methods.

Bi-directional Switch Commutation for a Resonant Matrix Converter supplying a Contactless Energy Transmission System

This paper describes a bi-directional switch commutation strategy for a resonant matrix converter loaded with a contactless energy transmission system. Due to the different application compared to classical 3 phase to 3 phase matrix converters supplying induction machines a new investigation of possible commutation principles is necessary. The paper therefore compares the full bridge series-resonant converter with the 3 phase to 2 phase matrix converter. From the commutation of the full bridge series-resonant converter, conditions for the bi-directional switch commutation are derived. One of the main benefits of the derived strategy is the minimization of commutation steps, which is independent from the load current sign.

Classical screw theory: A fresh look using dual eigenvalue approach

This paper presents a novel algebraic formulation of the central problem of screw theory, namely the determination of the principal screws of a given system. Using the algebra of dual numbers, it shows that the principal screws can be determined via the solution of a generalised eigenproblem of two real, symmetric matrices. This approach allows the study of the principal screws of the general screw systems associated with a manipulator of arbitrary geometry in terms of closed-form expressions of its architecture and configuration parameters. The formulation is illustrated with examples of practical manipulators.

A near-singular, flexure jointed, moment sensitive Stewart platform based fore-torque sensor

A force-torque sensor capable of accurate measurement of the three components of externally applied forces and moments is required for force control in robotic applications involving assembly operations. The goal in this paper is to design a Stewart platform based force torque sensor at a near-singular configuration sensitive to externally applied moments. In such a configuration, we show an enhanced mechanical amplification of leg forces and thereby higher sensitivity for the applied external moments. In other directions, the sensitivity will be that of a normal load sensor determined by the sensitivity of the sensing element and the associated electronic amplification, and all the six components of the force and torque can be sensed. In a sensor application, the friction, backlash and other non-linearities at the passive spherical joints of the Stewart platform will affect the measurements in unpredictable ways. In this sensor, we use flexural hinges at the leg interfaces of the base and platform of the sensor. The design dimensions of the flexure joints in the sensor have been arrived at using FEA. The sensor has been fabricated, assembled and instrumented. It has been calibrated for low level loads and is found to show linearity and marked sensitivity to moments about the three orthogonal X, Y and Z axes. This sensor is compatible for usage as a wrist sensor for a robot under development at ISRO Satellite Centre.

An Empirical Study of Synthesis of Multiple State Devices by Engineering Designers

Automated synthesis of mechanical designs is an important step towards the development of an intelligent CAD system. Research into methods for supporting conceptual design using automated synthesis has attracted much attention in the past decades. The research work presented here is based on an empirical study of the process of synthesis of multiple state mechanical devices. As a background to the work, the paper explores concepts of what mechanical device, state, single state and multiple state are, and in the context of the above observational studies, attempts to identify the outstanding issues for supporting multiple state synthesis of mechanical devices.

GEMS of SAPPhIRE: A Framework for Designing?

This paper proposes a framework of designing for conceptual and early embodiment design that uses physical laws and effects explicitly as a central aspect for designing. This is especially important in domains that make explicit use of physical laws and effects in their design, such as novel sensors. The objectives of the paper are: (a) Develop a model, (b) Empirically evaluate the model and (c) Propose a framework. The model is developed by integrating the activity- and outcome-based elements. The model is validated empirically by analyzing protocols of design sessions to find instances of activities and outcomes. Based on the findings, a framework is proposed on how designing should be done. Elements of GEMS (Generate-Evaluate-Modify-Select) and SAPPhIRE (State change-Action-Part-Phenomenon-Input-oRgan-Effect) are used for developing the model.Empirical evaluation confirms that designing can be modeled with the activity and outcome elements. The paper concludes with the identification of areas that require support and future work.

Clustering Based Large Margin Classification: A Scalable Approach using SOCP Formulation

This paper presents a novel Second Order Cone Programming (SOCP) formulation for large scale binary classification tasks. Assuming that the class conditional densities are mixture distributions, where each component of the mixture has a spherical covariance, the second order statistics of the components can be estimated efficiently using clustering algorithms like BIRCH. For each cluster, the second order moments are used to derive a second order cone constraint via a Chebyshev-Cantelli inequality. This constraint ensures that any data point in the cluster is classified correctly with a high probability. This leads to a large margin SOCP formulation whose size depends on the number of clusters rather than the number of training data points. Hence, the proposed formulation scales well for large datasets when compared to the state-of-the-art classifiers, Support Vector Machines (SVMs). Experiments on real world and synthetic datasets show that the proposed algorithm outperforms SVM solvers in terms of training time and achieves similar accuracies.

Scheduling a Burn-In Oven with Non-Agreeable Release Times and Due Dates

We consider the problem of scheduling semiconductor burn-in operations, where burn-in ovens are modelled as batch processing machines. Most of the studies assume that ready times and due dates of jobs are agreeable (i.e., ri < rj implies di ≤ dj). In many real world applications, the agreeable property assumption does not hold. Therefore, in this paper, scheduling of a single burn-in oven with non-agreeable release times and due dates along with non-identical job sizes as well as non-identical processing of time problem is formulated as a Non-Linear (0-1) Integer Programming optimisation problem. The objective measure of the problem is minimising the maximum completion time (makespan) of all jobs. Due to computational intractability, we have proposed four variants of a two-phase greedy heuristic algorithm. Computational experiments indicate that two out of four proposed algorithms have excellent average performance and also capable of solving any large-scale real life problems with a relatively low computational effort on a Pentium IV computer.

Performance Modeling based on Multidimensional Surface Learning for Performance Predictions of Parallel Applications in Non-Dedicated Environments

Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active area of research for several years. The existing curve fitting strategies for performance modeling utilize data from experiments that are conducted under uniform loading conditions. Hence the accuracy of these models degrade when the load conditions on the machines and network change. In this paper, we analyze a curve fitting model that attempts to predict execution times for any load conditions that may exist on the systems during application execution. Based on the experiments conducted with the model for a parallel eigenvalue problem, we propose a multi-dimensional curve-fitting model based on rational polynomials for performance predictions of parallel applications in non-dedicated environments. We used the rational polynomial based model to predict execution times for 2 other parallel applications on systems with large load dynamics. In all the cases, the model gave good predictions of execution times with average percentage prediction errors of less than 20%

Gibbs energy formation of lead titanate

The Gibbs energy of formation of titania-saturated lead titanate has been determined by e.m.f. measurements on the solid state cell;Pt,Ir,Pb + Pb1−xTiO3−x + TiO2(rutile)/CaO-ZrO2/Ni + NiO,Pt in the temperature range 1075–1350 K. The results obtained are significantly different from those reported in the literature based upon vapour pressure measurements, employing Knudsen effusion and transportation techniques, and assuming that the vapor phase consisted entirely of monomeric PbO molecules. A reanalysis of the data obtained in the earlier vapor pressure studies using mass spectrometric measurements on polymeric PbO species in the gas phase, gives Gibbs energies of formation of lead titanate which are in better agreement with those obtained in this study. Earlier electrochemical measurements by Mehrotra et al. and more recent electrochemical measurements by Schmahl et al. both employing CaO-ZrO2 solid electrolytes are in good agreement with the present study. The electro-chemical measurements by Schmahl et al. using PbF 2 solid electrolyte give a slightly more positive Gibbs energy of formation. There was no evidence supporting the formation of compounds other than Pb1−xTiO3−x from yellow PbO and rutile form of TiO2 in the temperature range covered in this study.Résumé L'enthalpie libre de formation du titanate de plomb saturé en oxyde de titane a été déterminée par des mesures de FEM de la pile: Pt,Ir,Pb + Pb1−xTiO3−x + TiO2(rutile)/CaO-ZrO2/Ni + NiO,Pt dans le domaine de températures 1075–1350 K. Les résultats obtenus, different appréciablement de ceux publiés, déterminés par mesures de tensions de vapeur (techniques de transport et d'effusion de Knudsen) en supposant que la phase gazeuse etait uniquement constituée de molécules monomériques de PbO. Une réanalyse des résultats de la littérature, à partir de mesures par spectrométrie de masse sur les polymères de PbO gazeux, donne des enthalpies libres de formation du titanate de plomb se rapprochant de celles obtenues dans cette étude. Les mesures de Mehrotra et al. et plus récemment de Schmahl et al. utilisant toutes deux l'électrolyte CaO-ZrO2 concordent bien avec celles de la présente étude. Les mesures de Schmahl et al., à l'aide de l' électrolyte solide PbF2, donnent une enthalpie de formation légèrement plus positive. Pour la gammede températures étudiée, rien ne permet de supposer que des composés autres que Pb1−x TiO3−x puissent se former à partir du PbO Gaune) et du rutile (TiO2).

Coloured Petri net models for automated manufacturing systems

In this paper, we propose an approach, using Coloured Petri Nets (CPN) for modelling flexible manufacturing systems. We illustrate our methodology for a Flexible Manufacturing Cell (FMC) with three machines and three robots. We also consider the analysis of the FMC for deadlocks using the invariant analysis of CPNs.

Switching Transients in Single-Phase Induction Motors

The subject of transients in polyphase induction motors and synchronous machines has been studied in very great detail by several investigators, but no published literature exists dealing exclusively with the analysis of the problem of transients in single-phase induction motors. This particular problem has been studied in this paper by applying the Laplace transform. The results of actual computation of the currents and developed electrical torque are compared with the data obtained by setting up the integro-differential equations of the machine on an electronic differential analyzer. It is shown that if the motor is switched on to the supply when the potential passes through its zero value, there is a pulsating fundamental frequency torque superimposed on the average steady-state unidirectional torque. If, on the other hand, the switch is closed when the applied potential passes through its maximum value, the developed electrical torque settles down to its final steady-state value during the first cycle of the supply voltage.

Phase-plane techniques for the solution of transient-stability problems

The paper presents a graphical-numerical method for determining the transient stability limits of a two-machine system under the usual assumptions of constant input, no damping and constant voltage behind transient reactance. The method presented is based on the phase-plane criterion,1, 2 in contrast to the usual step-by-step and equal-area methods. For the transient stability limit of a two-machine system, under the assumptions stated, the sum of the kinetic energy and the potential energy, at the instant of fault clearing, should just be equal to the maximum value of the potential energy which the machines can accommodate with the fault cleared. The assumption of constant voltage behind transient reactance is then discarded in favour of the more accurate assumption of constant field flux linkages. Finally, the method is extended to include the effect of field decrement and damping. A number of examples corresponding to each case are worked out, and the results obtained by the proposed method are compared with those obtained by the usual methods.

Digital Dead Time Logic and Protection Circuitry for PWM Voltage Source Converters

Power semiconductor devices have finite turn on and turn off delays that may not be perfectly matched. In a leg of a voltage source converter, the simultaneous turn on of one device and the turn off of the complementary device will cause a DC bus shoot through, if the turn off delay is larger than the turn on delay time. To avoid this situation it is common practice to blank the two complementary devices in a leg for a small duration of time while switching, which is called dead time. This paper proposes a logic circuit for digital implementation required to control the complementary devices of a leg independently and at the same time preventing cross conduction of devices in a leg, and while providing accurate and stable dead time. This implementation is based on the concept of finite state machines. This circuit can also block improper PWM pulses to semiconductor switches and filters small pulses notches below a threshold time width as the narrow pulses do not provide any significant contribution to average pole voltage, but leads to increased switching loss. This proposed dead time logic has been implemented in a CPLD and is implemented in a protection and delay card for 3- power converters.

Time Series Classification for Online Tamil Handwritten Character Recognition – A Kernel Based Approach

In this paper, we consider the problem of time series classification. Using piecewise linear interpolation various novel kernels are obtained which can be used with Support vector machines for designing classifiers capable of deciding the class of a given time series. The approach is general and is applicable in many scenarios. We apply the method to the task of Online Tamil handwritten character recognition with promising results.