Large-Scale Elastic Net Regularized Linear Classification SVMs and Logistic Regression

Elastic Net Regularizers have shown much promise in designing sparse classifiers for linear classification. In this work, we propose an alternating optimization approach to solve the dual problems of elastic net regularized linear classification Support Vector Machines (SVMs) and logistic regression (LR). One of the sub-problems turns out to be a simple projection. The other sub-problem can be solved using dual coordinate descent methods developed for non-sparse L2-regularized linear SVMs and LR, without altering their iteration complexity and convergence properties. Experiments on very large datasets indicate that the proposed dual coordinate descent - projection (DCD-P) methods are fast and achieve comparable generalization performance after the first pass through the data, with extremely sparse models.

A Simple Label Switching Algorithm for Semisupervised Structural SVMs

In structured output learning, obtaining labeled data for real-world applications is usually costly, while unlabeled examples are available in abundance. Semisupervised structured classification deals with a small number of labeled examples and a large number of unlabeled structured data. In this work, we consider semisupervised structural support vector machines with domain constraints. The optimization problem, which in general is not convex, contains the loss terms associated with the labeled and unlabeled examples, along with the domain constraints. We propose a simple optimization approach that alternates between solving a supervised learning problem and a constraint matching problem. Solving the constraint matching problem is difficult for structured prediction, and we propose an efficient and effective label switching method to solve it. The alternating optimization is carried out within a deterministic annealing framework, which helps in effective constraint matching and avoiding poor local minima, which are not very useful. The algorithm is simple and easy to implement. Further, it is suitable for any structured output learning problem where exact inference is available. Experiments on benchmark sequence labeling data sets and a natural language parsing data set show that the proposed approach, though simple, achieves comparable generalization performance.

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.

Inventory Management Performance in Indian Machine Tool SMEs: What factors do influence them

These instructions give on basic guidelines for preparing papers for the IEEM 2008 Proceedings. Inventory Management (IM) plays a decisive role in the enhancement of efficiency for manufacturing enterprise competitiveness. Therefore, major manufacturing industries are following inventory management practices as a strategy to improve efficiency and achieve competitiveness. However, the spread of inventory management culture among Small and Medium Enterprises (SMEs) is limited due to lack of initiation, expertise and financial limitations in developed countries, leave alone developing countries.With this backdrop, this paper makes an attempt to ascertain the factors which influence the IM performance of SMEs in the machine tools industry of Bangalore, India. This issue is probed based on primary data gathered from 91 SMEs. The paper brings out that two sets of factors namely organizational support and external pressure have a positive impact on the inventory performance of SMEs.

Vector control of permanent magnet synchronous motor using DSP controller

PMSM drive with high dynamic response is the attractive solution for servo applications like robotics, machine tools, electric vehicles. Vector control is widely accepted control strategy for PMSM control, which enables decoupled control of torque and flux, this improving the transient response of torque and speed. As the vector control demands exhaustive real time computations, so the present work is implemented using TI DSP 320C240. Presently position and speed controller have been successfully tested. The feedback information used is shaft (rotor) position from the incremental encoder and two motor currents. We conclude with the hope to extend the present experimental set up for further research related to PMSM applications.

Space vector pulsewidth modulation — A status review

The technique of space vector pulsewidth modulation (SVM) is reviewed. The basic principle of SVM is derived and is compared with sine-triangle PWM. Operation in the overmodulation range is explained. Extension of SVM to other inverter-motor combinations such as three level inverters and split phase motors are discussed.

Dodecagonal space vector diagram using cascaded H-Bridge inverters

This paper proposes the development of dodecagonal (12-sided) space vector diagrams from cascaded H-Bridge inverters. As already reported in literatures, dodecagonal space vector diagrams have many advantages over conventional hexagonal ones. Some of them include the absence of 6n±1, (n=odd) harmonics from the phase voltage, and the extension of the linear modulation range. In this paper, a new power circuit is proposed for generating multiple dodecagons in the space vector plane. It consists of two cascaded H-Bridge cells fed from asymmetric dc voltage sources. It is shown that, with proper PWM timing calculation and placement of active and zero vectors, a very high quality of sine-wave can be produced. At the same time, the switching frequency of individual cells can be reduced substantially. Detailed PWM analysis, one design example and an elaborate simulation study is presented to support the proposed idea.

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.

Geographic Resources Decision Support System – an Open Source GIS

Fully structured and matured open source spatial and temporal analysis technology seems to be the official carrier of the future for planning of the natural resources especially in the developing nations. This technology has gained enormous momentum because of technical superiority, affordability and ability to join expertise from all sections of the society. Sustainable development of a region depends on the integrated planning approaches adopted in decision making which requires timely and accurate spatial data. With the increased developmental programmes, the need for appropriate decision support system has increased in order to analyse and visualise the decisions associated with spatial and temporal aspects of natural resources. In this regard Geographic Information System (GIS) along with remote sensing data support the applications that involve spatial and temporal analysis on digital thematic maps and the remotely sensed images. Open source GIS would help in wide scale applications involving decisions at various hierarchical levels (for example from village panchayat to planning commission) on economic viability, social acceptance apart from technical feasibility. GRASS (Geographic Resources Analysis Support System, http://wgbis.ces.iisc.ernet.in/grass) is an open source GIS that works on Linux platform (freeware), but most of the applications are in command line argument, necessitating a user friendly and cost effective graphical user interface (GUI). Keeping these aspects in mind, Geographic Resources Decision Support System (GRDSS) has been developed with functionality such as raster, topological vector, image processing, statistical analysis, geographical analysis, graphics production, etc. This operates through a GUI developed in Tcltk (Tool command language / Tool kit) under Linux as well as with a shell in X-Windows. GRDSS include options such as Import /Export of different data formats, Display, Digital Image processing, Map editing, Raster Analysis, Vector Analysis, Point Analysis, Spatial Query, which are required for regional planning such as watershed Analysis, Landscape Analysis etc. This is customised to Indian context with an option to extract individual band from the IRS (Indian Remote Sensing Satellites) data, which is in BIL (Band Interleaved by Lines) format. The integration of PostgreSQL (a freeware) in GRDSS aids as an efficient database management system.

Study of symmetrical and related components through the theory of linear vector spaces

The paper proposes a study of symmetrical and related components, based on the theory of linear vector spaces. Using the concept of equivalence, the transformation matrixes of Clarke, Kimbark, Concordia, Boyajian and Koga are shown to be column equivalent to Fortescue's symmetrical-component transformation matrix. With a constraint on power, criteria are presented for the choice of bases for voltage and current vector spaces. In particular, it is shown that, for power invariance, either the same orthonormal (self-reciprocal) basis must be chosen for both voltage and current vector spaces, or the basis of one must be chosen to be reciprocal to that of the other. The original �¿, ��, 0 components of Clarke are modified to achieve power invariance. For machine analysis, it is shown that invariant transformations lead to reciprocal mutual inductances between the equivalent circuits. The relative merits of the various components are discussed.

External support and innovation performance of SMEs in Bangalore: Role of firm level factors

This paper probes the role of internal factors in SMEs in obtaining external support and achieving innovation performance in the context of auto component, electronics and machine tool industries of Bangalore in India. Using step-wise logistic regression analysis, the study found that only if SMEs have internal technical competence in terms of technically qualified entrepreneur, an exclusive design centre, and innovate more frequently, they will be able to obtain external support. Further using step-wise multiple regression the study concluded that SMEs which have come up to implement innovative ideas or exploit market opportunities and which have obtained external support with technically qualified entrepreneurs are able to exhibit better innovation performance.

Medium-Voltage Drive for Induction Machine With Multilevel Dodecagonal Voltage Space Vectors With Symmetric Triangles

Multilevel inverters with dodecagonal (12-sided polygon) voltage space vector structure have advantages, such as complete elimination of fifth and seventh harmonics, reduction in electromagnetic interference, reduction in device voltage ratings, reduction of switching frequency, extension of linear modulation range, etc., making it a viable option for high-power medium-voltage drives. This paper proposes two power circuit topologies capable of generating multilevel dodecagonal voltage space vector structure with symmetric triangles (for the first time) with minimum number of dc-link power supplies and floating capacitor H-bridges. The first power topology is composed of two hybrid cascaded five-level inverters connected to either side of an open-end winding induction machine. Each inverter consists of a three-level neutral-point-clamped inverter, which is cascaded with an isolated H-bridge making it a five-level inverter. The second topology is for a normal induction motor. Both of these circuit topologies have inherent capacitor balancing for floating H-bridges for all modulation indexes, including transient operations. The proposed topologies do not require any precharging circuitry for startup. A simple pulsewidth modulation timing calculation method for space vector modulation is also presented in this paper. Due to the symmetric arrangement of congruent triangles within the voltage space vector structure, the timing computation requires only the sampled reference values and does not require any offline computation, lookup tables, or angle computation. Experimental results for steady-state operation and transient operation are also presented to validate the proposed concept.

Low-Order Harmonic Suppression for Open-End Winding IM With Dodecagonal Space Vector Using a Single DC-Link Supply

This paper proposes a technique to suppress low-order harmonics for an open-end winding induction motor drive for a full modulation range. One side of the machine is connected to a main inverter with a dc power supply, whereas the other inverter is connected to a capacitor from the other side. Harmonic suppression (with complete elimination of fifth- and seventh-order harmonics) is achieved by realizing dodecagonal space vectors using a combined pulsewidth modulation (PWM) control for the two inverters. The floating capacitor voltage is inherently controlled during the PWM operation. The proposed PWM technique is shown to be valid for the entire modulation range, including overmodulation and six-step mode of operation of the main inverter. Experimental results have been presented to validate the proposed technique.

Space-Vector-Based Hybrid PWM Technique to Reduce Peak-to-Peak Torque Ripple in Induction Motor Drives

Constant-volts-per-hertz induction motor drives and vector-controlled induction motor drives utilize pulsewidth modulation (PWM) to control the voltage applied on the motor. The method of PWM influences the pulsations in the torque developed by the motor. A space-vector-based approach to PWM facilitates special switching sequences involving the division of active state time. This paper proposes a space-vector-based hybrid PWM technique, which is a combination of the conventional and special switching sequences. The proposed hybrid PWM technique results in a lower peak-to-peak torque ripple than conventional space vector PWM(CSVPWM) at high speeds of an induction motor drive. Furthermore, the magnitude of the dominant torque harmonic due to the proposed hybrid PWM is significantly lower than that due to CSVPWM at high speeds of the drive. Experimental results from a 3.75-kW sensorless vector-controlled induction motor drive under various load conditions are presented to support analytical and simulation results.